Proceedings of the International Conference on Urban Climate and History of Meteorology

TWO HUNDRED YEARS OF URBAN METEOROLOGY IN THE HEART OF FLORENCE Proceedings of the INTERNATIONAL CONFERENCE ON URBAN CLIMATE AND HISTORY OF METEOROLOGY

FIRENZE ( ITALY ) Palazzo Medici Riccardi 25th -26th February 2013

TWO HUNDRED YEARS OF URBAN METEOROLOGY IN THE HEART OF FLORENCE

Proceedings of the International Conference On Urban Climate And History Of Meteorology Firenze, Italy, 25th /26th February 2013

Edited by T. GEORGIADIS, M. A. LOKOSHCHENKO , C. SCRETI, C. VAGNOLI

Firenze, Italy, June 2013 ISBN 9788895597188

FOREWORD

The International Conference “Two hundred years of urban meteorology in the heart of Florence” held in Florence, Palazzo Medici Riccardi, on 25th and 26th of February 2013 was an occasion to join the scientific communities of historical climatologists along with the urban climatologists and meteorologists, in order to share methodologies and results to provide a common vision of the urban environment to allow the development of new instruments both theoretical and practical to planning our urban future. Humankind it is expected in few dozens of years to transform itself in a community of citizens in terms of persons living within the borders of cities or, better, megalopolis. Within these borders it will be a matter of facts that the concept of citizenship could assume a high relevant value if the expectations and wellness of the populations are respected, or a badly representing the animus of the people just only allow to live inside the city without dignity. Not only the social arrangement, or the political inclusion are issues of paramount importance in the frame to live together: the physical environment plays a crucial role in determining the conditions for the proper wellbeing perceived as a physiological optimum. This condition can be achieved bearing in mind the specific genius loci of the city itself and its development of the urban structure during the course of the years, of the centuries, along with the transformations of the land use as morphology and materials changes. The Conference allowed to deeply exchange information in order to built a common language between scientists of different disciplines and to understand the fundamental role of the urban observatories in monitoring the changes over hundred years collecting data that represent not only a diagnosis of the past but a tool to forecast our common future.

“Two hundred years of urban meteorology in the heart of Florence”

EARLY HYGROMETRIC OBSERVATIONS: THE CHIMINELLO GOOSE PEN HYGROMETER VERSUS THE DE SAUSSURE HAIR HYGROMETER USED IN PADUA FROM 1794 TO 1826. Camuffo D.1, Bertolin C.1, Amore C.2, Bergonzini A.2 1

National Research Council– Institute for Atmospheric Sciences and Climate (ISAC), Padua, Italy 2 Physic Department, University of Modena and Reggio Emilia, Italy

Summary The hygrometer was invented in the 16th century with some instruments weighting samples of some hygroscopic materials, e.g. seeds, cotton, invented by L.B. Alberti and Leonard. In the 17th century, S. Santorio invented a hygrometer with string sensor; the Grand Duke of Tuscany, Ferdinand II another hygrometer based on condensation and F. Folli a third one based on the elongation of a paper strip. At the end of the century, R. Hooke, made attempts to employ catgut and beard of a wild oat. In the second half of 18th century, Lambert built an improved catgut hygrometer and M.J.A. De Luc in 1773 invented an ivory hygrometer improving an idea by G. Amontons. This instrument was similar to a thermometer but with an ivory cylinder bulb, filled of mercury and with a glass tube. This was the first almost reliable instrument, which won the prize of the Amiens Academy, although it had problems in correcting the temperature dependence of the response. In 1783 V. Chiminello won the prize from the Theodoro-Palatina Academy of Sciences, Mannheim, for a new type of hygrometer, having a goose pen as a sensor, fixed to a glass tube and filled with mercury. In the same year of the Academy Prize, i.e. 1783, H.B. De Saussure invented an instrument made with a hair wound on a cylinder connected to a pointer, the father of the most popular hair hygrometer. In Padua we found unbroken daily observations of relative humidity for the 1794-1826 period recorded by Chiminello and his pupils. They made two parallel series, with simultaneous readings made using a Chiminello goose pen hygrometer and a De Saussure hair hygrometer. The Chiminello hygrometer was fixed to a tablet on the side of a Reaumur thermometer having the same tube diameter and size, to make temperature correction easier. The calibration was made with four fixed, extreme points. The first two were: dampness, immerging the sensor into a water bath and dryness, placing the sensor in front of a fireplace with light fire. The operation was repeated several times in order to anneal the goose pen with repeated cycles to obtain a stable sensor. The sensor was also immersed in boiling and freezing water in order to determine the temperature dependence with these two additional calibration points. Chiminello considered that a reliable instrument should have the following characteristics: well determined calibration points, repeatability, no drift and easy temperature correction. The readings were made in apparent degrees making reference to a reversed scale fixed to the instrument and later transformed to apparent degrees making a temperature correction. A comparison made by the Academy of Sciences, Mannheim found that the Chiminello’s hygrometer was the most reliable instrument and recommended it for the Palatina Network observations 1781-1792 and regularly published 1783-1795. Three original hygrometers, built by G.B. Rodella, technician of Chiminello and his pupil F. Bertirossi-Busatta, are still preserved in Padua, i.e. Museum of History of Physics, Botanical Garden of the Padua University and Galilean Academy of Sciences, Letters and Arts. A replica of it was built by the authors to verify in the lab instrumental performances and calibration problems. The paper will present the results obtained after having recovered the data, calibrated the instrument and transformed readings in modern units (%), made corrections, homogenization and data analysis.

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THE FUTURE FOR URBAN CLIMATOLOGY Mills G. School of Geography, Planning & Environmental Policy, UCD, Dublin, Ireland.

[email protected]

Summary This paper is a discussion of the development, status and future of Urban Climatology, the field concerned with the study of the urban effect on the atmosphere and the application of this knowledge to the better design and planning of cities. Urban areas have a profound effect on the overlying air as a result of changes to the nature of surface cover (urban form) and emissions of heat, water vapour and materials that attend human activities (urban function). While these changes have been well known and observed for over 100 years, it is only recently that Urban Climatology has developed a coherent structure for organising this knowledge so that urban observations can be conducted and urban models developed that are transferrable from place to place. In this paper, I give a personal perspective on the history of the field from the vantage point of its current standing. In addition, I suggest some pathways that the field may take in the near future.

Keywords: Luke Howard, process-response, urban climatology, urban scales.

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THE DILEMMA IN THERMAL COMFORT ESTIMATIONS IN URBAN AREAS Matzarakis Α. Chair of Meteorology and Climatology, Albert-Ludwigs-University Freiburg, Werthmannstr. 10, D-79085 Freiburg, Germany

[email protected]

Summary Current quantifications of the thermal environment are based on the human energy balance and the derived thermal indices (i.e. Physiologically Equivalent Temperature or Universal Thermal Climate Index). The advantage of these indices based on the human energy balance is the possibility of their application to environments ranging from cold to hot conditions. One advantage of the thermal indices is the output from human energy balance calculations is terms of a temperature and easy understandable by non-specialists in human biometeorology. Another advantage is that most of the thermal indices require the same meteorological input data (air temperature, air humidity, wind speed and mean radiant temperature) and thermo-physiological information (activity and heat transfer of clothing covering skin surface). Meteorological parameters contain pronounced variability in the spatial and temporal dimension. In addition, the input parameters vary with measurement height and different transfer techniques into appropriate input conditions of thermal indices. Several examples for this influence of input parameters and their variability on thermal indices in urban structures are shown.

Keywords: thermal indices, physiologically equivalent temperature, universal thermal climate index, measurements, modelling

INTRODUCTION Modern human biometeorological methods are based on the human energy balance of the human body and extracted thermal indices can describe the effects of the thermal environment on humans (Mayer 1993). The result of a thermal index is mostly given as a temperature (e.g. Physiologically Equivalent Temperature (PET) or Universal Thermal Climate Index (UTCI)), which is easier acceptable and understandable by applied sciences (Höppe 1999, Matzarakis 2006, Matzarakis and Amelung 2008). In order to derive a specific result about the influence of the thermal environment, the human energy balance has to be solved with meteorological data and thermo-physiological information. The thermo-physiological data can be summarized in terms of clothing and activity. They are well quantified in several studies and can be used as standard for several studies in order to have comparable conditions (e.g. VDI 1998). The meteorological data required are air temperature, air humidity (relative humidity or vapour pressure), wind speed and the synthetically human-biometeorological quantification of the short- and long wave radiation fluxes in terms of the mean radiant temperature (VDI 1998, Matzarakis et al. 2007). The availability and accuracy of meteorological data is the first step to be done in order to quantify thermal comfort or stress issues. From the data required usually air temperature and air humidity are avail-able at most from synoptic or climatological networks (Matzarakis 2006). Wind is usually included in synoptic observations and measured at 10 m height a.g.l. and has to be reduced for the human weighting center of 1.1 m a.g.l for the most thermal indices. The wind information from climatological or synoptic networks has to be also transformed from wind force to wind velocity. It has to be mentioned that at most the wind has a large variability in the spatial dimension and is also modified by regional and local climatological factors, e.g. land and sea breezes. Finally, the mean radiant temperature, which is ________________________________________________________________________________________________ ISBN 9788895597188

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difficult to be quantified due to atmospheric influences firstly by clouds and other meteorological compounds as vapour pressure or particles (Matzarakis et al. 2010). In addition, the influences of topography or urban morphology modify not only wind but also radiation properties in the meso- and micro-scale (Lin et al. 2010). The data measured is based on different kind of instruments and are accompanied with different resolutions, quality and accuracy. Therefore the challenge is often not the used method but the required and available data in the spatial and temporal dimension (Matzarakis 2001, 2010). All this parameters or factors fitted in human energy balance models delivers a specific thermal index, which describes in an appropriate manner the thermal environment and can be used for several applications from global to micro scale issues (Matzarakis 2006, 2007, Matzarakis and Amelung 2008, Scott et al. 2009).

METHODS The effect of the thermal environment on humans, can be described by thermal indices, which are based on the human energy balance and are appropriate for the description of the effects of climate not only for cold but also for warm conditions (Fanger 1972; Gagge et al. 1996; Matzarakis 2007; Spagnolo and de Dear 2003, Jendritzky et al., 2012, Staiger et al., 2012). Two of the most popular physiological thermal indices derived from the human energy balance (Höppe 1993) the Physiologically Equivalent Temperature (PET) (Mayer and Höppe, 1987, Höppe, 1999, Matzarakis et al., 1999) and Universal Thermal Climate Index (UTCI) are chosen. PET is defined as the physiological equivalent temperature at any given place (outdoors or indoors), equivalent to the air temperature at which, in a typical indoor setting, the heat balance of the human body (with light activity (80 W) and heat resistance of clothing (0.9 clo) is maintained with core and skin temperatures equal to those under the conditions being assessed (VDI 1998, Höppe 1999). The following assumptions are made for the indoor reference climate: •

Mean radiant temperature equals air temperature (Tmrt=Ta).

•

Air velocity (wind speed) is fixed at v = 0.1 m/s.

• Water vapour pressure is set to 12 hPa (approximately, equivalent to a relative humidity of 50% at 20°C).

Ta =

The procedure for the calculation of PET contains the following steps (Höppe 1984, 1999): • Calculation of the thermal conditions of the body with Munich-Energy-Balance-Model for Individuals (MEMI) for a given combination of meteorological parameters. • Insertion of the calculated values for mean skin temperature and core temperature into the model MEMI and solving the energy balance equation system for the air temperature Ta (with v =0.1 m/s, VP = 12 hPa and Tmrt = Ta). •

The resulting air temperature is equivalent to PET.

Compared to other thermal indices, which are likewise obtained from the human energy balance, e.g., the predicted mean vote (PMV), PET offers the advantage of a widely known unit (degrees Celsius), which makes results more comprehensible to regional or tourism planners, who may not be so familiar with the modern human-biometeorological terminology (Matzarakis et al. 1999). Similar to the frequently used PMV index (Fanger 1972; Matzarakis and Mayer 1997), PET is one of the universal indices to characterise the thermal bioclimate. It allows the evaluation of thermal conditions in a physiologically significant manner. With respect to this, Matzarakis and Mayer (1996) transferred ranges of PMV for thermal perception and grade of physiological stress on human beings (Fanger 1972; Mayer 1993) into corresponding PET ranges. They are valid only for the assumed values of internal heat production and thermal resistance of the clothing (Matzarakis and Mayer, 1996) and are applied very often.

The UTCI is defined as the air temperature of the reference condition causing the same model response as the actual condition. Thus, UTCI is the air temperature, which would produce under reference conditions the same thermal strain ________________________________________________________________________________________________ ISBN 9788895597188

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as in the actual thermal environment. Both, meteorological and non-meteorological (metabolic rate and thermal resistance of clothing) reference conditions were defined: •

Wind speed (v) of 0.5 m/s at 10 m height (approximately 0.3 m/s in 1.1 m),

•

Mean radiant temperature (Tmrt) equal to air temperature and,

• Vapour pressure (VP) that represent relative humidity of 50%; at high air temperatures (>29 ºC) the reference humidity was taken constant at 20 hPa. • Representative activity to be that of a person walking with a speed of v = 4 km/h (1.1 m/s). This provides a metabolic rate of 2.3 met (135 W/m²). The adjustment of clothing insulation is a powerful behavioral response to changing climatic conditions. Thereby, the philosophy for UTCI was to consider seasonal clothing adaptation habits of Europeans based on available data from field surveys in order to obtain a realistic representation of this behavioral action that notably affects the human perception on the outdoor climate. For applications the categorization of the different values of UTCI in terms of thermal stress is required (Błażejczyk et al., 2010). The present approach looks at responses for the reference conditions and deducts load (i.e. heat or cold stress) caused by physiological response of an organism at actual environmental conditions. It can be noted that with respect to the averaged dynamic thermal sensation UTCI values between 18 and 26 °C may comply closely with the definition of the “thermal comfort zone” supplied in the Glossary of Terms for Thermal Physiology (International Union of Physiological Sciences - Thermal Commission, 2003) as: “The range of ambient temperatures, associated with specified mean radiant temperature, humidity, and air movement, within which a human in specified clothing expresses indifference to the thermal environment for an indefinite period”. The thermal environment expressed in terms of PET or UTCI can be calculated by the radiation and energy balance model RayMan (Matzarakis et al. 2007, 2010). For the assessment of thermal comfort issues the meteorological information needed has to be adjusted and cannot be taken directly from a meteorological station or measurement network. The needed parameters (air temperature, air humidity, and wind speed) have to be converted to the gravity center of the human body (1.1 m). More complicated is the mean radiant temperature, which has to be calculated or simulated. Table 1. Human-biometeorological parameters in their spatial and temporal dimension required for the quantification of thermal comfort. Parameter

Spatial

Temporal

Air temperature

Medium

High

Vapour pressure

Medium

High

Wind speed

Large

Medium

Mean radiant temperature (short-

Large

Large

Activity

None

High

Clothing

None

Medium

and long-wave radiation)

In addition the input parameters have a temporal and spatial variability (Table 1), which has a huge influence on thermal indices and has to be considered in the assessment and quantification of thermal comfort issues. Table 1 shows ________________________________________________________________________________________________ ISBN 9788895597188

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the spatial and temporal variability of the input parameters. So, for a diurnal quantification of thermal comfort the input parameters have to be known and be available considering their daily variability. In complex areas, wind speed and mean radiant temperature have the highest variability and are modified by surroundings and obstacles. Many measurements are performed without the required quality and appropriateness, i.e. excluding artificial ventilation or without radiation shield in air temperature leading to errors in the results. The aim of this paper is therefore to show the effects and difficulties in the assessment of the input parameters and the differences in the used thermal indices. This was done by making adjustments in the input parameters, mostly in wind speed and mean radiant temperature.

RESULTS AND EXAMPLES Based on the mentioned and described methods, emphasis has to be given in the parameters required as input. The possibilities and limitations of the applied thermal indices and on the way derived results are presented. Focus on the results and exampled is given here on the factors, which have the highest influence and variability.

Input parameters The primary concern about the input parameters is their accuracy. Meteorological measurement guidelines have to be followed first in order to have appropriate data sets. Second, for human-biometeorological thermal indices (e.g. PET and UTCI) the simulations are performed at a height, which is the center of gravity of the human body (1.1 m). However, meteorological parameters are measured and obtained at different heights. Air temperature and air humidity are usually measured at 1.5 m or 2 m above the ground. Global radiation is measured at least at a height of 2 m, in order to reduce the effects of albedo and the souroundings. Standard observations of wind are done at a minimum height of 6 m and mostly at 10 m. This is valid for standard measurements station like synop and climate station, which are located mostly on flat areas and airports. Concerning the adjustment of measurement heights and application for humanbiometeorological application the input parameters have to be adjusted. Figure 1: Changes (in %) of wind speed from originally 10 m height to human-biometeorological height of 1.1 m for different roughness lengths.

Variation of wind speed is usually high and depends mostly on the surroundings and the related roughness length of the obstacles. The wind adjustment to 1.1 m is of relevant importance and the reduction can be to 40 to 60 % of the wind at 10 m (Fig. 1) for the adjustment of wind speed in urban areas. Appropriate knowledge of roughness lengths is required. The simulation and calculation of wind can be performed with micro scale models (like ENVI-met) (Bruse and Fleer, 1998) or by known equations for the wind profile (Matzarakis et al. 2009). In most of simulations, limitation exists, which have to be addressed. The wind profile equations are difficult to apply in urban areas and micro scale models (mostly prognostic) have the limitation of long running time and are complex for application.

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Figure 2: SkyHelios Screenshot and estimation of SkyView Factor.

The input parameter with the highest temporal and spatial variability is the mean radiant temperature (Tmrt), which is a synthesis of the short and long wave radiation fluxes and it describes the effect of radiation as a single value. Tmrt is not only dependent on atmospheric factors and radiation fluxes but also on the modification of the radiation fluxes by urban morphology. The variability of radiation fluxes is even higher than for wind speed. For studies in urban areas the measurement of principle factors affecting Tmrt is possible and then the calculation of Tmrt (Höppe, 1992, VDI, 1998). In addition Tmrt and affecting factor (i.e. Sky View Factor) can be estimated (Fig. 2) by several micro scale models provide (Matzarakis et al., 2007, 2010; Lindberg et al., 2008, Bruse and Fleer, 1998). Several studies have addressed modifications and variability and factors affecting Tmrt in simple and complex environments (Matzarakis et al., 2007, 2010, Lin, 2009, Lin et al., 2010, 2012). It has to be pointed out that Tmrt has the highest variability in temporal terms and also in different urban structures especially during day time. Recently many researchers have started to focus on the variability and modifications of wind speed and Tmrt in urban structures and the effects of them on thermal indices (Herrmann and Matzarakis, 2012, Fröhlich and Matzarakis, 2013, Matzarakis and Endler, 2010). Thermal Indices As mentioned in the input parameters, the large variability can be found in wind speed. Concerning wind speed effect on thermal indices, it has to be mentioned that mostly wind has a cooling effect. Except, when air temperature is higher are skin temperature has not anymore a cooling but the heat exchange is positive (increased) for the surface of humans. This can be seen from Fig. 3, where different wind speeds and the relationship between air temperature and PET are visualized. For air temperature and PET lower than 35 °C a cooling effect and higher than 35 °C and increasing effect on PET. For UTCI (right figure) it can be seen also that the effect of wind speed in cooler regimes even is higher than PET.

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Figure 3: Effect of wind speed on PET and UTCI based on different air temperature levels (Ta) for 1 to 20 m/s.

Figure 4: Temporal variability of air temperature (Ta), PET and PET is shade for a typical day (light cloudy and moderate windy) in Freiburg.

For radiation fluxes (expressed here in terms of Tmrt), it can be seen for the example of Fig. 4, that Tmrt has the highest influence on PET. It can be also seen that the difference between PET and Ta is during the day much higher up to 15 °C in the specific case. In addition, it can be seen that PET during the night is lower than air temperature. In general it is obvious that PET has a much higher daily variability than air temperature (Fig. 4). Presentation Of Results Usually results for thermal comfort issues are presented in terms of mean condition or daily patterns. Based on the data used in different time resolution for single points the possibility of considering presentation possibilities of frequencies of occurrence based on thermal perception ranges and thresholds has to be discussed. A recent possibility can be the frequency diagrams which include specific ranges of PET or UTCI and can represent the overall assessment of background conditions of PET or other thermal indices (i.e. Lin and Matzarakis, 2008, Herrmann and Matzarakis, 2012, Fröhlich and Matzarakis, 2013). The presentation of results based on frequency diagrams has the advantage that more information is included than monthly means and represents all classes from cold to hot conditions and are easier to be applied and understood by planers and authorities. Another important factor builds the mapping issue because of the demand and application in planning. Planners prefer detailed information on the spatial behaviour of the human-biometeorological conditions for the decision-making (Matzarakis et al., 2008). To provide spatial information on the thermal bioclimate, numerical or statistical models can ________________________________________________________________________________________________ ISBN 9788895597188

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be applied. Here, has to be mentioned that urban climate maps are mostly produced as a case study and do not deliver information for the overall assessment of thermal conditions and the mobility of urban dweller including time to stay indoor and outdoor should be included and considered. DISCUSSION AND CONCLUSION The examples shown, indicate that there are difficulties and deficiencies in the quantification of thermal comfort. First of all the data used has to be accurate and in an appropriate way. Mean daily data cannot accurately and precise reproduce the thermal conditions during the day. As mentioned before, there are two major factors that can mostly affect the assessment of thermal comfort: a) the input data with their accuracy and variability and b) the method used for the quantification (VDI 1998). The methods used rely on the human energy balance in steady state conditions and assess the thermal environment by solving the human energy balance for long period while considering the change in the meteorological conditions in the temporal scale. This assumption is used for different reasons, primarily because of the calculation time. In addition the way of presentation of results is important and has to be in an easily understandable way. Limitations and defficiencies has to be expressed and quantified. A third important factor and often not considered is the mobility of humans and the frequency of use of a specific space. Dwellers have a high mobility during the day and, depending on the time of day they spend their time, due to several reasons, in- and outdoors. This makes an assessment of their thermal comfort conditions difficult, because the periods of stay have to be known. Another issue is quantifying from another point of view, the use of different spaces (i.e., parks, indoor and outdoor). A first approach, concerning this issue, is described as affect analysis, is given in the integral climate analysis for Freiburg (Röckle et al., 2003, Matzarakis et al., 2008). Thermal comfort assessment performed in the past had some deficiencies, which can be reduced with modern techniques and possibilities. This requires reliable spatial and temporal data, which are relevant as input data for thermal indices. The periods of use of different land use areas and periods of stay indoor (also in cars and bus) and their appropriate representation of their climate are required and is of great relevance in the thermal comfort quantification.

AKNOWLEDGMENT This work is financially supported by the transnational cooperation project within the Central Europe Programme “Development and application of mitigation and adaptation strategies and measures for counteracting the global urban heat island phenomenon”. This project is implemented through the CENTRAL Europe Programme co-financed by the ERDF.

REFERENCES Błażejczyk, K., Broede, P., Fiala, D., Havenith, H., Holmér, I., Jendritzky, G., Kampmann, B., Kunert, A., (2010). Principles of the new universal thermal climate index (UTCI) and its application to bioclimatic research in European scale. Miscellanea Geographica 14: 91-102. Bruse, M., Fleer, H. (1998). Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model. The challenge of awareness in developing societies. Environmental Modelling & Software 13: 373–384. Fanger, P.O. (1972). Thermal comfort. McGraw-Hill, New York. Fröhlich, D., Matzarakis, A. (2013). Thermal bioclimate and urban planning in Freiburg - Examples based on urban spaces. Theoretical and Applied Climatology 111: 547-558. Gagge, A. P., Fobelets, A. P., Berglund, L. G. (1986). A standard predictive index of human response to the thermal environment. ASHRAE Trans 92: 709-731. ________________________________________________________________________________________________ ISBN 9788895597188

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Herrmann, J., Matzarakis, A. (2012) Mean radiant temperature in idealized urban canyons – Examples from Freiburg, Germany. International Journal of Biometeorology 56: 199-203. Höppe, P. (1984). Die Energiebilanz des Menschen, Wiss. Mitt. Meteorol. Inst. Univ. München No. 49. Höppe, P. (1992). Ein neues Verfahren zur Bestimmung der mittleren Strahlungstemperatur im Freien. Wetter und Leben 44: 147-151. Höppe, P. (1993). Heat balance modelling. Experientia 49: 741–746. Höppe, P. (1999). The physiological equivalent temperature – a universal index for the biometeorological assessment of the thermal environment. International Journal of Biometeorology 43: 71–75. International Union of Physiological Sciences - Thermal Commission (2003). Glossary of Terms for Thermal Physiology. Journal of Thermal Biology 28: 75-106. Jendritzky, G., De Dear, R., Havenith, G. (2012). UTCI - Why another thermal index?. International Journal of Biometeorology 56: 421. Lin, T.-P. (2009). Thermal perception, adaptation and attendance in a public square in hot and humid regions. Building & Environment 44: 2017–2026 Lin, T.-P., Matzarakis, A. (2008). Tourism climate and thermal comfort in Sun Moon Lake, Taiwan. International Journal of Biometeorology 52:281–290 Lin, T.-P., Matzarakis, A., Hwand, R.-L. (2010). Shading effect on long-term outdoor thermal comfort. Building and Environment 45: 213-211. Lin, T. P., Tsai, K. T., Hwang, R. L., Matzarakis, A. (2012). Quantification of the effect of thermal indices and sky view factor on park attendance. Landscape and Urban Planning 107: 137-146. Lindberg, F., Holmer, B., Thorsson, S. (2008). SOLWEIG 1.0 – Modelling spatial variations of 3D radiant fluxes and mean radiant temperature in complex urban settings. International Journal of Biometeorology 52: 697–713. Matzarakis, A. (2001). Die thermische Komponente des Stadtklimas, Wiss. Ber. Meteorol. Inst. Universität Freiburg No. 6. Matzarakis, A. (2006). Weather and climate related information for tourism. Tourism and Hospitality Planning & Development 3: 99-115. Matzarakis, A. (2007). Climate, human comfort and tourism. In: Amelung, B., Blazejczyk, K., Matzarakis, A., (eds.) Climate Change and Tourism: Assessment and Coping Strategies. 139-154. Matzarakis, A. (2010). Climate Change: Temporal and spatial dimension of adaptation possibilities at regional and local scale. In: Schott, C. (ed.) Tourism and the implications of Climate Change: Issues and Actions, Emerald Group Publishing. Bridging Tourism Theory and Practice Vol. 3, 237-259. Matzarakis, A., Mayer, H. (1996). Another Kind of Environmental Stress: Thermal Stress. WHO Colloborating Centre for Air Quality Management and Air Pollution Control. NEWSLETTERS 18: 7-10. Matzarakis, A. and Mayer, H. (1997). Heat stress in Greece. International Journal of Biometeorology 41: 34-39. Matzarakis, A., Amelung, B. (2008). Physiologically Equivalent Temperature as indicator for impacts of climate change on thermal comfort of humans. In: M. C. Thomson et al. (eds.), Seasonal Forecasts, Climatic Change and Human Health. Advances in Global Change Research 30, Springer-Sciences and Business Media, 161-172. Matzarakis, A., Endler, C. (2010). Climate change and thermal bioclimate in cities: impacts and options for adaptation in Freiburg, Germany. International Journal of Biometeorology 54: 479–483.

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Matzarakis, A., Mayer, H., Iziomon, M.G. (1999). Applications of a universal thermal index: physiological equivalent temperature. Int. J. Biometeorol. 43: 76-84. Matzarakis, A., Rutz, F., Mayer, H. (2007). Modelling Radiation fluxes in simple and complex environments – Application of the RayMan model. International Journal of Biometeorology 51: 323-334. Matzarakis, A., Rutz, F., Mayer, H. (2010). Modelling radiation fluxes in simple and complex environments: basics of the RayMan model. International Journal of Biometeorology 54: 131–139. Matzarakis, A., De Rocco, M, Najjar, G. (2009) Thermal bioclimate in Strasburg – The 2003 heat wave. Theoretical and Applied Climatology 98: 209-220. Matzarakis, A., Röckle, R., Richter, C.-J., Höfl, H.-C., Steinicke, W., Streifeneder, M., Mayer, H. (2008). Planungsrelevante Bewertung des Stadtklimas – Am Beispiel von Freiburg im Breisgau. Gefahrstoffe – Reinhaltung der Luft 68: 334-340. Mayer, H. (1993). Urban bioclimatology. Experientia 49: 957-963. Mayer, H., Höppe, P. (1987). Thermal comfort of man in different urban environments. Theor. Appl. Clim. 38: 43–49. Röckle, R., Richter, C.-J., Höfl, H.-C.; Steinicke, W.; Streifeneder; M.; Matzarakis, A. (2003). Klimaanalyse Stadt Freiburg. Auftraggeber Stadtplanungsamt der Stadt Freiburg. November 2003. Scott, D., C.R. de Freitas, Matzarakis, A. (2009). Adaptation in the tourism and recreation sector. In: G. R. McGregor, I. Burton, K. Ebi (Eds.), Biometeorology for Adaptation to Climate Variability and Change. Springer, 171-194. Spagnolo, J., de Dear, R. A. (2003). Field study of thermal comfort in outdoor and semi-outdoor environments in subtropical Sydney Australia. Building and Environment 38: 721-738. Staiger, H., Laschewski, G., Grätz, A. (2012). The perceived temperature – a versatile index for the assessment of the human thermal environment. Part A: scientific basics. International Journal of Biometeorology 56:165–176. VDI (1998). Methods for the human-biometerological assessment of climate and air hygiene for urban and regional planning. Part I: Climate, VDI guideline 3787. Part 2. Beuth, Berlin.

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‘THE RAIN IN SPAIN STAYS MAINLY IN THE PLAIN’ – WHY IS IT IMPORTANT TO CONSIDER SOCIAL PERCEPTIONS ON METEOROLOGY AND CLIMATE STUDIES IN THE ASSESSMENT AND MANAGEMENT OF RISK? Figueiredo E. Department of Social, Political and Territorial Sciences, University of Aveiro, Aveiro, Portugal.

[email protected]

Summary Until recently, studies on meteorology and climate issues, as well as on the majority of other environmental questions, were traditionally developed within the scope of the so-called natural sciences, evidencing a complete neglect of social dimensions. On the one hand natural scientists tended to not consider social action as relevant to address environmental problems and, on the other hand, social scientists emphasized the social contexts where those actions took place independently of the biophysical conditions. Since the 70’s however, natural and social scientists start to recognize each other contributions of paramount relevance to the understanding of the increasingly global environmental problems, based on the recognition that the environment is more than the natural conditions, resources and elements and it is much influenced by social actions and perceptions. In fact, many environmental questions – climate questions included – are social constructions, meaning that besides their objective existence, they possess a social meaning frequently not in accordance with the existing scientific knowledge. The way people perceive meteorological events is particularly relevant when they configure situations of risk and situations in which risk is effectively materialized and demand for action both in terms of prevention and mitigation. Frequently, lay discourses on environmental risk differ from decision makers and technical and experts discourses. First are based and depend on various different aspects, predominantly of subjective nature and including an intuitive and qualitative evaluation. Second are related to quantitative assessment, probabilities and calculations. Although the relevance of integrating social (or lay) perceptions in technical and policy assessment and management of risk is increasingly recognized, many difficulties subsist in conciliating these diverse discourses. Taking all the above considerations, we intend to discuss the content of social perceptions on meteorological and climate related events, particularly in situations of risk, and its relevance to assess, manage and mitigate risk in contemporary societies. Keywords: integration of perspectives on meteorological and climate change issues; lay knowledge; social perceptions; risk; technical and scientific expertise

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INTRODUCTION The title of my paper refers to a very well known song, from the movie My Fair Lady 1. It is a language exercise which has little to do with the reality of the Spanish meteorological conditions. In fact, the rain in Spain does not stay mainly in the plain, as the rainiest part of that country is the hilly northwest on the Bay of Biscay and the northern mountains in general. However this song has entered the popular knowledge and expresses a misinterpretation of weather conditions. The title of the song (and the song itself) illustrates the main point of my argument: that not always the popular or lay perceptions on meteorology and climate are in accordance with the technical and scientific expertise and, that it is important to consider social perceptions on meteorology and climate studies in the assessment and management of the effects of extreme meteorological events, particularly when they represent risk situations. (Lima, 2004; Figueiredo et al., 2009). Although the study of social perceptions and corresponding management and control mechanisms of risk are subjects of study since more than three decades ago (Lima, 2004), research on the need to integrate lay knowledge into measures to prevent and to mitigate environmental and technological risk is still very recent (Figueiredo et al., 2009). This is due to several reasons, from the neglect of the influence of social aspects in natural or environmental phenomena to the assumption that the technical and scientific rationality is the only valid manner of assessing risk. Until recently, studies on meteorological and climate issues, as well as on the majority of other environmental aspects, were traditionally carried on within the scope of the so-called natural sciences, evidencing the complete neglect of social dimensions. On the one hand, natural scientists tended to not consider social action as relevant in influencing environmental phenomena and to address environmental problems and, on the other hand, during several decades, social scientists emphasized the social contexts where those actions occurred independently of the biophysical conditions (e.g. Butler, 1986; Figueiredo, 2003). Since the 70’s, however, natural and social scientists come to terms with the recognition of each other contributions as possessing a paramount relevance to the understanding of the increasing global environmental problems, as well as of their growing complexity. A major impulse to that recognition has been made by sociology, based on the finding that the environment is much more than the natural conditions, resources and elements and its much influenced (and influence the) by social actions and perceptions (Dunlap and Catton Jr., 1983; 1994; Mormont, 1993; Redclift and Woodgate, 1994). Many environmental questions – meteorological and climate questions included – are social constructions, meaning that besides their material existence and objective measurability, they possess a social meaning frequently – as the song from My Fair Lady illustrates – not in accordance with the existent scientific evidence and knowledge. The way people perceive meteorological events is particularly relevant when they configure situations of risk and situations in which risk is effectively materialized and demand for action both in terms of prevention and mitigation. Frequently, lay discourses on environmental risk differ from decision makers and technical and experts discourses. First are based and depend on various different aspects, predominantly of subjective nature and including an intuitive and qualitative evaluation. Second are related to quantitative assessment, probabilities and calculations. Although the relevance of integrating social (or lay) perceptions in technical and policy assessment and management of risk is increasingly recognized, many difficulties subsist in conciliating these diverse discourses. Taking all the above considerations, we intend to discuss the content of social perceptions on meteorological and climate related events, particularly in situations of risk, and its relevance to assess, manage and mitigate risk in contemporary societies. Basically, if one intends that people does not believe (and act accordingly with that belief, since perceptions determine actions) that the rain in Spain stays mainly in the plain, more than simple information seems to be needed.

1

My Fair Lady is a movie from 1964, directed by George Cukor. The main character is Eliza Doolittle, a flower girl, that learns how to speak proper English language. The song is a language exercise. You can listen it here: http://www.youtube.com/watch?v=uVmU3iANbgk ________________________________________________________________________________________________ ISBN 9788895597188

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THE CLIMATE AND THE PEOPLE – CULTURE, EXPERIENCE, PSYCHOSOCIAL DIMENSIONS IN THEIR CONSTRUCTION

MEMORY

AND

OTHER

What is climate from a social sciences perspective? As Hulme et al. (2009: 197) state, “climate can neither be experienced directly by our senses, nor measured indirectly by our instruments. Unlike the wind which we feel in our face or a raindrop that wets our hair, climate is a constructed idea”. This idea seems to carry much “richer and longer tradition of meaning than is captured by the rather unimaginative convention that defines climate as ‘being the average course or condition of the weather at a place usually over a period of years and exhibited by temperature, wind, velocity and precipitation’”. Although climate is, by definition, a statistical concept representing frequencies of surface variables, assessed over months to millions of years (Salomon et al., 2007), people possess subjective, full of preconceptions and marked by feelings and experiences, perspectives on weather. Weather and climate “play a vital role in individuals’ perceptions and interpretations of the world they live in” (Akerlof et al., 2013: 89), as well as it plays a relevant role in the way people conducted their activities, practices and lives. Climate issues such as temperature, precipitation and winds, integrate individual and social beliefs, narratives and condition peoples’ practices (Strauss and Orlove, 2003; Akerlof, 2013). Climate possesses, therefore, both cultural and biophysical interpretations (Hulme, 2008). It can be assessed using meteorological instruments and knowledge and it can be constructed through memories, experience and social imaginary. In fact, if one cannot deny the objectivity of climate and its expression in a given region when compared to another, it is also evident that climate is subject to social and cultural interpretations, since, for example, the rain means something diverse for a Basque or for an Andalusian and, of course, something even more different for a Spanish or for a Cape Verde inhabitant. Climate changes due to both natural and man induced factors, but cultural interpretations of climate and of climate changes also vary over time and from one social context to another. Assessing the climate and the weather requires both natural sciences and social sciences. As referred in the previous section, the role of social sciences in the study of environmental and natural questions, including climate and climate change issues, only recently has been recognized. Social sciences play a relevant role in identifying the main components of social perceptions regarding weather and meteorological events, the ways in which perceptions influence action, particularly when a meteorological event poses a risk situation, in understanding the way lay people interpret and react to the weather forecasts, as well as in identifying and contributing to design better communication tools. As Keul and Holzer (2013: 33) refer, despite the recognition that social sciences and meteorology “have plenty of interrelations (i.e. hydrometeorological risk analysis, communication and perception, societal impacts), the academic interrelations are more scarce”, therefore giving the opportunity for a new field of research and to improve current knowledge on climate and on climate perceptions and related risk. Basically, social sciences understand climate as a social construction, dependent of a number of not (at least, not always) completely measurable aspects. This does not mean to deny the objective and material existence of climate and of meteorological events, but to emphasise that climate, as many other biophysical and not biophysical aspects, are created in a great part by the symbolic game play of the social subject. In order to comprehend how climate events affect people and communities, it is relevant to understand those people and communities and the way they interact with meteorological issues.

The social construction of weather and climate (and risk ) Social perceptions may be defined, in theoretical terms, as being informed by external and internal factors and stimuli (Decrop, 2006, Hübner and Gösseling, 2012). Internal factors are related to individual characteristics and external factors related to the features of the social contexts in which individual live in. External stimuli include controlled, induced or targeted information, deriving from advertisement or promotional issues. Internal stimuli may be defined as uncontrolled information directly related to what is conveyed by television, newspapers, experiences, memories, social interaction (Hübner and Gösseling, 2012), among other factors. The authors point out that the last type of information – uncontrolled – seems to have larger credibility and more immediate effect on individual and social beliefs. The role of social perceptions, and consequently the role of culture, experience, memories, social contexts, internal and external stimuli and other psychosocial dimensions in the public’s assessment of climate, climate change, and risk, received growing attention over the past decades, particularly from geographers, anthropologists, sociologists and other social scientists (Marin, 2010), but also from natural scientists and decision makers (Akerlof et al., 2013). ________________________________________________________________________________________________ ISBN 9788895597188

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As Hulme et al. (2009) note, the way in which individuals and communities constructed their notions on climate substantially vary from the way climatologists and meteorologists do it. The authors also argue that climate is socially constructed based on people places of living, sharing of a given culture and corresponding values, as well on their experiences and memories of past weather related events and on what they learned from past generations. These factors are mobilized not only to interpret and to cope with present climate, but also to predict and to construct expectations on future weather events (Rebetz, 1996, Hulme et al., 2009). Based on these perceptions people define what is ‘normal’ or ‘abnormal’ weather, what is ‘good’ or ‘bad’ weather, as well as evaluate risk situations and the likelihood of their occurrence. In many countries, if not in all, these experiences, memories and perceptions are frequently represented through paintings, photographs and other art pieces. Moreover, “sensory and social encounters with climate also shape the linguistic repertoire through which weather and climate is described” (Hulme et al., 2009: 198). In Portugal, for example, there is a set of popular sayings regarding the weather: “a água em janeiro, vale dinheiro” [“water in January means money”]; “em abril, águas mil” [“in April, tones of rain”]; “corra o ano como correr, em agosto há-de aquecer” [“be the year what it be, August will be warm”]. Also in Italy, there is a quite reasonable amount of sayings about the meteorology: “Rosso al mattino il brutto tempo è vicino” [“red in the morning, ugly weather is about to start”]; “La tramontana la pioggia tiene lontana” [“the north wind keeps the rain away”]. And, of course, in the rest of the world, popular culture translate the weather events into popular sayings, which also express the liasions between climate and everyday life, economic activities, among other aspects. The majority of the studies regarding social perceptions on climate issues emphasise the role of sociodemographic variables in explaining the diversity of lay perspectives. Particularly age, literacy level, professional status and political views seem to be powerful variables when explaining the visions people have on climate matters. The youngest, the more educated, the left-wing voters and the ones working in intelectual or scientific related professions seem to possess a more accurate perspective, at least a more informed one, on climate issues, climate change questions and related risks. However, as Kahan et al. (2011) note, social perceptions and the factors underlying social construction of climate issues are strongly related to psychosocial dimensions, such as the beliefs and values of the social group, social experience, social imaginary and memories (Akerlof et al., 2013). As Akerlof et al. (2013: 81) refer “experience is the best teacher, it is said. The consequences of risk that we can see, hear and feel – the sting of a bee, a cut from broken glass, or a burn from time in the sun – create memorable impressions that shape individuals’ subsequent behaviour, and in their retelling, even that of others”. The same can be said about direct experience of extreme meteorological events, such as floods, heavy winds, tsunamis. However, direct experience on climate change and its effects on the weather are not so easy to live, since the changes tend to be slow and do not provide sensorial. The majority of lay people only have contact (not experience) with climate change and its potential effects through the mass media news experiences (Marx et al, 2007; Moser and Dilling, 2011). Experience of an event is fundamental to the perception and construction of expectations and future behaviour related to similar situations. Also the memory of past meteorological weather is relevant in this domain. Memory of paste weather events is “biased in favour of ‘extremes’ or exceptional episodes and by those climate events to which there is a strong personal or collective attachment” (Hulme et al., 2009: 198). The duration and content of these collective memories on weather tends to vary between historical and cultural contexts and individuals (Meze-Hausken, 2004). As described in the paper of Hulme et al. (2009), based on findings from Hassan (2000), societies seem to evaluate climate variation within a timescale of 60 to 100 years, i.e., ‘much beyond living memory’, which means that memory of an event is not only individual, but frequently collective and transmitted from one generation to another. Also determinant to the way in which weather events are socially constructed and/or perceived is the meaning attributed to the weather forecasts, in different contexts and by diverse users. As Hulme et al. (2009) note, there is a widespread notion that information regarding meteorological and climate change events flows from the scientific experts to different countries and communities following the same paths. However “the ways in which different actors engage with and transform universalised ideas and images while ignoring others, demonstrates the processes by which the same (statistically framed) climate can have a multiplicity of meanings in different cultural settings” (Hulme et al., 2009: 200). Meteorological and climate events are not only biophysical, but also cultural, localized, experienced, lived and memorized. Regarding the ways in which meteorological and weather forecasts are transmitted and disseminated among the general public, one should start by acknowledging the role of mass media (radio, television and internet) in mediating information and, sometimes, in transforming it, creating simplified messages of complex events. As Hübner and Gösseling, 2012: 48) refer “the media is an important external source of information on climate, weather and climate change”. Media coverage on climate change and associated risk has grown over the recent past decades, “with ________________________________________________________________________________________________ ISBN 9788895597188

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representations and discourses about the causes and consequences of climate change often focusing on purported or real uncertainties, as well as diverging opinions between scientists”. Boykoff and Smith (2010) also note that media tend to report and to highlight ‘bad’ weather and extreme meteorological events, since these are generally considered as factors to increase audiences. Deriving from a technical and scientific universe, weather forecasts transmitted by the media seem, sometimes, to fail its purpose in informing and raising awareness among the public on meteorological events, particularly in situations of extreme ones. In a seminal work on this matter, Baruch Fischhoff (1994) identified a series of pitfalls in communicating meteorological events to the public. As the author refers, “one source of problems in this communication process is ambiguity regarding the event being predicted and what exactly is being said about it. Another is the difficulty of determining the relevance of the problem that the forecaster has solved for the problem that the user is facing” (Fischhoff, 1994: 387). Fischhoff (1994: 388) identifies four main reasons for the fail or misinterpretation in the communication of weather forecasts with the general public: -

Ambiguity – not being clear about an event and its consequences;

-

Irrelevance – not addressing the needs of the general public regarding a particular event;

-

Immodesty – not admitting that sometimes predictions may fail;

-

Impoverishment – not addressing the broader context in which forecasts (and following decisions) are made.

These aspects may affect (and do affect) the levels of confidence of the public regarding climate predictions and weather forecasts. The well known aphorism “climate is what you expect, weather is what you get” seem to summarize very well the discrepancy between what the experts are predicting, what is conveyed by the media and what occurs in practical terms, at least what people perceive that occurs. Trust in the predictions seem to be of fundamental relevance, since when people do not trust weather forecasts, their actions regarding an extreme meteorological event, may be unpredictable, as well as its consequences. Even in a scenario of complete trust, the users of the weather forecasts may have some doubts, may be left guessing “whether the forecaster have overstated or understated how much they know” about an event and its effects (Fischhoff, 1994: 393). Therefore, transparency and interaction are relevant aspects in communicating weather forecasts and events, again particularly when communicating risk situations. Keul and Holzer (2013) refer that weather forecasting, in order to be efficient, must send intelligible messages via the mass media. In fact, it is worthwhile to notice the transformation in the weather reports conveyed by the media over the few past decades from extremely technical weather reports to the use of much more simple and intelligible signs and symbols which may help people to better understand the forecasts and to act accordingly in an easier way. In fact, during the last decades, not only climate changed, not only our perceptions changed, but also the way in which meteorological information is transmitted suffered major transformations. Figures 1 and 2 show two current ways, although completely different, of presenting weather forecasts which conditioned the perception of the general public.

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Figure 1 – Surface Wind on Monday 11 Feb at 1pm Roma time

Source: http://www.weather-forecast.com/static_maps/Italy/wind/6

Figure 2 – Italy weather forecast

Source: http://www.europe-map.org/weather/italy.htm The interpretations these maps provide are quite different, as well as it is their complexity and the tools they offer to allow the public to construct a certain perception on the weather (in this case) for Italy. One may argue on the technical and scientific accuracy of both maps, but in terms of general public’s understanding on the weather the second one, although probably not so accurate, is more useful and efficient than the first one. Some maps also relate to the weather forecast a set of alerts, from green to red, trying to alert people for potential risk situations that can occur in consequence of ‘abnormal’ meteorological events. These may help people to perceive the seriousness of a given situation and to act accordingly. However, and once again, the way people perceive climate risk situations depends on a variety of aspects, and sometimes, despite the red alerts, and based on previous experiences with the same type of weather, on popular beliefs, on cultural aspects and on previous inaccurate weather forecasts, people tend to disregard meteorological predictions. Also during the last few decades, some specialized meteorological sites were designed to attend specific needs of specific groups of population and activities, like weather reports for agriculture, for fishermen and for sea sports. This is in accordance with the need to attend the problem of the irrelevance of the information conveyed sometimes, as pointed out by Fischhoff (1994) and to make the forecasts useful to the users that, in fact and for specific reasons, do need it. ________________________________________________________________________________________________ ISBN 9788895597188

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The neglect of weather forecasts and warnings/alerts may be more concerning, as argued before, in situations of extreme meteorological events (e.g. floods, heavy rain, heavy snow, strong winds, tsunamis) in which people must be prepared to act and react. Therefore, assessing the social perceptions of risk related to extreme meteorological events and to climate change is an area of extreme relevance, since people and communities face decisions about how to best cope with risk, adapt to probable coming changes and/or to act in the event of risk occurrence. As risk is complex and multidimensional, social perceptions of risk are also imbued with major complexity, subjectivity and value. Moreover, there are a set of factors, relating to the socioeconomic context, the individual sphere and the biophysical conditions which contribute to explain the way in which risk is perceived. Slovic et al. (1981), Slovic (1987), Renn (2004) and Figueiredo et al. (2009) provide a wide list of circumstances or qualitative factors underlying risk perception that must be taken into account when dealing with social perceptions of extreme meteorological events 2: -

Familiarity with risk source – tolerance regarding risk increases in direct proportion to frequency possibility of risk occurrence;

and

-

Voluntary acceptance of risk – the willingness to voluntarily accept risk is intimately connected to the perceive benefits (economic or of other nature);

-

Ability to control risk degree – the ability to cope with a given danger is related to the possibility of controlling risk factors in advance, whether individually or through awareness of adequate technical and official control mechanisms;

-

Catastrophic potential of the risk source – people tend to be less negligent regarding risk if it is perceived as having catastrophic proportions and impacts;

-

Certainty of the risk impacts – this is related to the ability to control risk degree, whereby knowing the risk’s impacts, people will be more prepared to cope with it;

-

Risk impact on future generations – this is related to the durability of the effects of a certain risk; people tend to cope better if there are no long lasting effects;

-

Sensorial awareness of danger – there is at present a significant risk set to which the social actors do not have “a sensorial warning system” (Spaargaren and Mol, 1993: 443). This sort of sensory deprivation leads to less tolerance of risks that are not immediately perceivable through sensory experience (Figueiredo et al., 2009);

-

Perception of justice in the distribution of benefits and burdens – the ability to accept and cope with risk depends on the way that distributive justice is perceived to deal with (positive or negative) risk impact (Figueiredo et al., 2009);

-

Awareness of the (ir)reversibility of risk impact – if the consequences of a natural and/or technological accident are perceived as irreversible, the ability to accept and cope with it will be reduced (Figueiredo et al., 2009);

-

Trust in the mechanisms and entities responsible for risk management and control – the greater is trust placed in the political and technical instruments of management and control, then greater will be the ability to cope with certain risk factors (e.g. Yearley, Forrester and Bailey, 2000);

-

Trust in information sources – this point is very closely linked to the previous one, and also to the ability to control risk degree. Social actors will show a greater level of risk acceptance and a greater willingness to cope with it if they consider that the information is reliable. The clarity of information about risk and the effectiveness of communication mechanisms here assume an equally relevant role (Figueiredo et al., 2009).

These qualitative factors tend to vary with different social contexts and, of course, regarding diverse types of risk and its effects. As expressed in a previous work (Figueiredo et al., 2009), although it is true that individuals use some of these factors in the way they represent, evaluate and behave towards hazard, the presence of these criteria in forming an 2

Although this list of circumstances or qualitative factors underlying risk perception may be applied to almost every risk situation and not only to meteorological events. ________________________________________________________________________________________________ ISBN 9788895597188

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opinion and in the tolerance of environmental risk varies considerably between social groups and different cultures (Sjöberg, 1994). As White et al. (2002: 87) state “nature, technology and society interact to generate vulnerability and resilience vis-à-vis disaster”. The existence as well as credibility of technical and political instruments for predicting, management and control are among the most important factors in the social construction of risk and in the extent to which people are able to accept, adjust and cope with it.

WHEN THE WEATHER BECOMES DANGEROUS – THE RELEVANCE OF INTEGRATING LAY AND SCIENTIFIC-TECHNICAL PERSPECTIVES IN A CONTEXT OF RISK As previously mentioned, the relevance of studying and understanding social perceptions towards meteorological events and climate change becomes more obvious when dealing with extreme events which may pose risk situations and may imply that individuals and communities face and take decisions on how to cope, adapt, act and react to risk and its effects. As Hulme et al. (2009) refer, cultural and psychological factors can shape expectations on future climate and meteorological events and on future changes, as much as can scientific calculations. Taking it into account is relevant both for designing more adequate communication tools and for implementing measures of prevention, mitigation and management of risk situations. While “risk, social perception and corresponding management and control mechanisms are subjects that have been studied at length for three decades now (e.g. Lima, 2004), concern with the need to integrate lay knowledge into measures to prevent, mitigate and combat risk is a relatively recent field of research” (Figueiredo et al., 2009: 585). Despite of the relatively recent recognition that social perception of risk is extremely important to design and implement adequate, legitimate and efficient measures to mitigate, control and manage risks, and accordingly with Flynn and Slovic (2000) and Lima (2004) there is extreme difficulty in integrating the results from technical and scientific analysis of risk and those from research into social perception of risk. Lima (2004: 150) also tells us that “technical experts and the general public often disagree about the best course of action and about the risks at stake”. This occurs due to the differences in terms of rationalities and discourses between the experts and the lay public. To specialists, as already mentioned, climate and meteorological risk assessment and management are based on probabilities, statistics and quantification, while to the general public meteorological risk assessment involves (as also previously shown) a wide range of factors resulting from presupposition and subjective values and perspectives. They are in fact two worlds apart, two parallel universes that seem difficult to conciliate (Figure 3). Figure 3 – The lay and the expert perspectives on risk 1st World

2nd World

accumulated experience statistics probabilities comparison of numbers/quantities optimization certainties

lay knowledge perception intuition emotion fear opinion (public) volatile decision mass media

Experts

Public

Source: Betâmio de Almeida (2006) The multidimensional character of the decisions related to risk situations is subjective and full of moral judgements and should, according to Flynn and Slovic (2000), become more self-evident through knowledge from specialists and the lay public alike. Therefore, integrating the assessments of both social actors and experts is important in the communication of risk as well as for the design and implementation of risk management policies an measures. As Yearley, Forrester and Bailey (2000:183) refer “it has been repeatedly concluded that ‘specialized’ explanations about physical reality clash with local knowledge and that this knowledge, rather than being inferior or deficient, as it is ________________________________________________________________________________________________ ISBN 9788895597188

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sometimes seen, is in fact more sensitive to ‘local realities’”. As, in fact, people live and work in places affected by a set of meteorological and other biophysical and environmental events, and have to cope with, this formulation seems adequate and the need to take into account ‘local knowledge’ and ‘local perceptions’ cannot be easily neglected. According to Bikerstaff (2004), a good deal of the negligence shown by social actors regarding risk situations (posed by meteorological events or other) is related to the belief that scientists and technicians are not of trust and that they tend to devaluate lay perspectives. As Klinke and Renn (2002: 173) state “many technical experts have argued forcefully against this proposition [the inclusion of lay perspectives on risk management]: they argue that sensational press coverage and intuitive biases may misguide public perceptions” and so “ignorance and misperceptions should not govern the priorities of risk management”. The tendency of lay perception to differ substantially from the proposals made by experts has frequently been attributed to public ignorance and irrationality concerning technical and scientific aspects of the problems 3 (Figueiredo et al., 2009). But as Bikerstaff (2004: 836) states, based on research on atmospheric pollution and climate change, “the gulf between ‘lay’ and ‘expert’ perceptions cannot be defined simply as a function of error or ignorance on the part of ‘the public’ but is founded in issues such as power, values, trust and place”. In addition, Renn (2004: 410) tells us that “any attempt to combat political paralysis by rejecting risk perception as irrational and relying solely on expert assessment would be misguided”. Without denying the need to create risk management instruments essentially supported by scientific knowledge 4 and recognizing that social perception cannot be a substitute for quantitative-based management policies and instruments Renn (2004: 412) states that “what is really need is mutual enhancement between technical risk assessment and intuitive risk perception. Risk policy should neither be purely science-based nor purely valuebased”. Lima (2004) refer that one frequent strategy to trying to conciliate technical and lay perspectives on risk (on every type of risk) involves the use of information tools. Although, as previously noted, information (particularly the one conveyed by the mass media) possess a paramount role in transmitting data on the weather and climate and in broadcasting extreme weather events, therefore contributing to raise awareness among the public, the fact is that citizens have virtually no control over what is being transmitted and over the decision processes. Information is, in fact, a unilateral process, frequently determined and oriented by specialists (although very often mediated by the mass media), in which lay public is seen solely as the repository. As Frank et al. (2011: 67) refer, “the availability of information alone remains unlikely to motivate adaptation” to a particular situation or to motivate action. Individuals are not mere repositories of the information, but they perceive it, use it or reject it in rather different manners. Cash et al. (2002) refer that at the core of any decision involving the construction of knowledge, individuals are focused on the salience, credibility and legitimacy of the information and manage these components is fundamental to successfully produce and mobilize knowledge to inform actions. As already mentioned in the previous sections, regarding weather information individuals tend to mix their personal experience, their memories, the local knowledge and culture and scientific and technical data when assessing meteorological events and the risk they pose. As information alone does not seem to be an adequate strategy when one needs to communicate extreme weather events and, particularly, the potential risk they may represent in order to motivate people’s behaviour and action, Lima (2004) suggest the use of participatory mechanisms, such as public consultations and partnerships. As the author states (Lima, 2004: 152-153) “partnerships refers to a form of public consultation which results have a mandatory value towards the final decision, through a commitment agreed upon by both parties”. In terms of meteorological and climate risk, this perspective is based on some presuppositions that are worthwhile to highlight (Figueiredo et al., 2009): − Firstly, in the assumption that the knowledge we have of the world and on meteorological events (particularly of extreme ones) is fallible, that there are various interpretations of reality and of risk and its effects; − Secondly, in the assumption that the difference between technical and lay positions is a result of different interests and information and that the knowledge and experience of citizens may help positively to find the decision and to mitigate risk effects, if and when risk occurs; 3

Lima (2004) states that apart from their perception of public irrationality, technicians, scientists and politicians also see lay social actors as extremely emotional (i.e. they panic easily in risk situations); selfish (where the so-called Nimby – Not in my backyard - effect plays a decisive role) and taking dubious positions regarding risk situations, technicians and scientists, according to their interests. 4 Since this knowledge alone has the ability to compare relative risks and mitigation options.

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− Finally, in the assumption that the difference in positions may also be minimized through the reassessment of technical analysis, considering new parameters and actions proposed by citizens. Although it seems possible to conciliate both perspectives (lay and technical/scientific) through the use of partnerships with successful results regarding risk assessment, management and mitigation, “such processes of public participation are difficult to implement since lay public opinions are still underestimated relative to science and technology perspectives (...) there is a visible lack of transparency in the processes of decision-making (...) as well as a lack of public trust in the administrative and/or political institutions responsible for the creation and application of measures and policies towards risk prevention, mitigation and management” (Figueiredo et al., 2009: 586). Furthermore, the implementation of these processes is frequently slow (contrasting with the general rapidity of the occurrence of extreme weather events), time consuming and expensive. Despite the great emphasis given to partnerships as a way of constructing communication, mutual meaning and improving the reaction and action regarding the occurrence of a given risk, it is important to bear in mind that evaluation of risks and management strategies, as well as the need to integrate, in a greater or lesser scale, lay and scientific perspectives, may vary accordingly with the nature of risks, its complexity, uncertainty and ambiguity (Klinke and Renn, 2001; 2002). Regarding meteorological and climate risks, one should take into account its frequency, the extent and catastrophic potential of its effects and its ubiquity and irreversibility of the impacts caused. Accordingly, three main management strategies may be identified (Klinke and Renn: 2002: 1091): − Risk-based – the most common and traditional strategy, used when the probability of occurrence of a given risk and the extent of the damages are well known and there is little uncertainty attached; − Precaution-based – this strategy must be used when uncertainty plays a large role, particularly when there is large indeterminacy or absence of sound knowledge about a given risk; − Discourse-based – this strategy seems adequate when there is a large ambiguity about a given risk. The procedures used within this strategy “include legal deliberations as well as novel participatory approaches” (idem, 2002: 1092) like the partnerships, which also involve methods of negotiation and conflict resolution. All the three types of management strategies require deliberative processes in order to assure an effective outcome and a balance between the procedure adopted and the outcome achieved (Figueiredo et al., 2009). Despite the difficulties in integrating lay and technical and scientific knowledge regarding risk in general and risks posed by extreme weather events in particular, as Bikerstaff (2004: 837) note, such processes offer at least two potential benefits: “first, by facilitating the inclusion and consideration of a wider range of knowledge – both ‘expert’ and ‘lay’ – they offer distinct cognitive gains that help to obviate misjudgement attributable to a narrow and inadequate knowledge base”, to obviate misinterpretations and to prevent inadequate actions. “Second, by facilitating more comprehensive and systematic appraisal and deliberation of the social and cultural values associated with environmental and technological risk issues, they can help to avoid the policy process becoming bogged down in intractable controversy and confrontation” and lacks social legitimacy and risks not to be feasible.

CONCLUDING REMARKS This paper intended to discuss the factors underlying the social construction of climate and weather, stressing the aspects which contribute to form social perceptions and the relevance of integrating these perceptions into the assessment and management of extreme meteorological events that, frequently, pose situations of risk to people and communities. Experiences, feelings, preconceptions, misinterpretations, memories, culture, social contexts, individual traits, among other factors, are actively (although not always in a conscious manner) used by people to assess and interpret climate and weather events. Although climate is by definition a statistical concept, subject to quantitative interpretations, calculations and predictions, it is also the subject of cultural and psychosocial interpretations which tend to condition the way people understand weather and extreme meteorological events. In fact, heavy rain, flash floods, strong winds, hurricanes, tsunamis etc., may be interpreted and seen in a completely different way accordingly with the part of the planet where people live. In the same sense, the notions of ‘normal’ or ‘abnormal’ weather and of ‘bad’ and ‘good’ weather may considerably vary accordingly to the social, economic and biophysical contexts. Assessing the climate and the weather requires, therefore, both natural and social sciences, since the way people perceive meteorological events affects their daily life and activities, as well as the way they act and react ________________________________________________________________________________________________ ISBN 9788895597188

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in case of risk occurrence. Meteorological events, the weather and the climate possess not only a biophysical character, but they are also cultural, localized, experienced, memorized and lived. Information is an important factor in the way people construct, experience and live weather events. In this respect, the role of mass media (television, radio, newspapers, internet) cannot be underestimate. As previously discussed, being the most relevant sources of information in contemporary societies, mass media have a paramount role in the construction, transmission, mediatisation and even in the transformation of weather events. Deriving from a scientific universe, the weather forecasts and news transmitted by the media sometimes seem to fail its purpose of informing and raising awareness among the public, in particular when dealing with extreme phenomena. This happens because of the mass media nature and purposes (e.g. conquering and raising larger audiences) but also due to the difficulties in being clear, unambiguous and relevant in transmitting messages that are useful to the users. Frequently there is a discrepancy between what the experts are predicting, what is transmitted by the media and what people understand. This is due to several factors, ranging from the lack of trust in scientific assessments, discrepancies in terms of discourse and misinterpretations to the psychosocial aspects underlying social perceptions and knowledge. However, it is important to emphasise the transformations, over recent years, in the mass media transmission of weather forecasts. It passed from statistical and graphic representations of complex scenarios, using a set of concepts not familiar to the general public, to the utilisation of user-friendly maps and symbols that allows the average person to understand the basics of meteorological forecasts. At the same time, the number and type of specific meteorological sites and information, directed to the needs of specific users and activities (e.g. agriculture, fisheries) has increased over the last 20 years. Both aspects demonstrate an attempt to make the information relevant and clearer to a diversity of publics, as well as the recognition (both by experts and mass media) of this diversity of publics and corresponding needs. All these factors and aspects may be more significant in situations of extreme meteorological events in which people must be prepared to act and react and are compelled, by extreme circumstances, to make and face decisions about how to best cope with the risk and its impacts. In this respect, it is important to bear in mind that, besides the quantitative assessment of risk, once again based on calculations, probabilities, statistics, there are qualitative factors influencing the way people perceive, cope and react to diverse types of risks, as discussed in the second section of this paper. These factors include familiarity with the source and effects of hazard; ability to control the degree of risk; the catastrophic potential of the risk; the way in which the distributional justice of costs and benefits is perceived; the extent to which it is reversible; and the trust placed in available information as well as in the entities and management mechanisms. The recognition of the need to integrate social or lay perceptions and technical and scientific perspectives on risk is still relatively recent, as it is the research on the interrelations between social sciences and meteorology and climate studies, therefore posing some difficulties in addressing these subjects. However, at the same time, this also gives new opportunities to develop new fields of research and to contribute to improve current knowledge on climate and climate related risks’ perceptions. Despite the recent academic and political concerns with the need to integrate lay and scientific perspectives on risk, there is a growing and consistent set of studies that emphasise it, as well as propose ways for a successful integration. Much of the empirical and theoretical evidence on the integration of lay and scientific perspectives of risk, point out major differences between the two ‘worlds’, emphasising the diversity of discourses, rationalities and experiences as obstacles for the construction of a mutual understanding. Although information procedures and strategies are seen as relevant in reconciling these two universes, many authors (e.g. Figueiredo et al., 2009; Frank et al., 2011; Lima, 2004) stress that information alone is not enough to build mutual understanding and to motivate action. The fact that the general public do not have control over the sources and content of the information conveyed (by scientists, technicians, mass media and politicians) together with the diversity of interpretations of what is transmitted, are important aspects to be considered here. Individuals are not mere repositories of information, they perceive it, interpret it, use or reject it accordingly to a multiplicity of aspects related to the psychosocial dimensions discussed in the paper. In face of these limitations, some authors (e.g. Lima, 2004) suggest the use of participatory mechanisms to integrate lay and scientific perspectives of risk, such as partnerships. However not all the type of risks posed by meteorological conditions may be the subject of such public consultation and involvement mechanisms, since the strategy must be adequate to the frequency, extent of damages, catastrophic potential, irreversibility, among other features, of risk (Klinke and Renn, 2002). In sum, the way lay people perceive meteorological events, especially extreme ones, is extraordinarily variable and substantially differ from the scientific perspectives, notions and predictions. The way people perceive meteorological and climate phenomena is crucial in their actions and reactions in preventing, mitigating and managing risks. Therefore ________________________________________________________________________________________________ ISBN 9788895597188

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there is a clear need to improve communication of risks between experts and lay persons if one intends to avoid or to minimize the impacts of risk situations. It is true that the rain in Spain does not stay mainly in the plain, although probably many individuals believe it stays. But the most relevant question here, even to the design of adequate civil protection mechanisms, seems to be: what if, suddenly, the rain in Spain really stays in the plain? Would be people prepared to cope with it and to react to the impacts of a completely unexpected situation?

AKNOWLEDGMENTS I would like to thank Antonio Raschi and the organizing committee of the ‘Two hundred years of urban meteorology in the heart of Florence: international conference on urban climate and history of meteorology’ for inviting me to participate, therefore giving me the opportunity to celebrate (and congratulate!) the two hundred years of the Osservatorio Ximeniano.

REFERENCES Akerlof, K.; Maibach, E.; Fitzgerald, D.; Cedeno, A. Y.; Newman, A. (2013). Do people ‘personally experience’ global warming, and if so how, and does it matter? Global Environmental Change, 23: 81-91. Betâmio de Almeida, A. (2006). O Cientista Face à Análise do Risco - A importância de incorporar a comunicação nos estudos sobre o risco. Presentation to the Seminário Comunicar o Risco: o papel dos cientistas e dos mass media na construção e amplificação social do risco, Aveiro, University of Aveiro, 16 June. Bickerstaff, K. (2004) Risk perception research: socio-cultural perspectives on the public experience of air pollution, Environment International, 30, 827-840. Boykoff, M. T.; Smith, J. (2010). Media presentations of climate change. In Lever-Tracy, C. (ed), Routledge handbook of climate change and society, Oxon, Routledge, 210–218. Buttel, F. H. (1986). Sociologie et environnement: la lente maturation de l'ecologie humaine. Revue Internationale des Sciences Sociales, 109: 359-378. Cash, D.; Clark, W. C.; Alcock, F.; Dickson, N.; Eckley, N; Jäger, J. (2002). Salience, Credibility, Legitimacy and Boundaries: Linking Research, Assessment and Decision Making. KSG Working Papers Series RWP02-046, available at SSRN: http://ssrn.com/abstract=372280 or doi:10.2139/ssrn.372280. Decrop, A. (2006). Vacation decision making, Wallingford, CABI Publishing. Dunlap, R. E. and Catton Jr., W. R. (1983). What environmental sociologists have in common (whether concerned with 'built' or 'natural' environments. Sociological Inquiry, vol.52, nº2/3: 113-135. Dunlap, R. E. and Catton Jr., W. R. (1994). Struggling with human exemptionalism: the rise, decline and revitalization of environmental sociology. The American Sociologist, vol. 25: 5-30. Figueiredo (2003). Um Rural para viver, outro para visitar: o ambiente nas estratégias de desenvolvimento para as áreas rurais, PhD Thesis, Aveiro, University of Aveiro. Figueiredo, E.; Valente, S.; Coelho, C. and Pinho, L. (2009). Coping with Risk – Analysis on the importance of integrating social perceptions on flood risk into management mechanisms - the case of the municipality of Águeda, Portugal. Journal of Risk Research, 12(5): 581 – 602. Fischhoff, B. (1994.) What forecasts (seem to) mean. International Journal of Forecasting, 10: 387-403. Flynn, J. e Slovic, P. (2000). Avaliações dos peritos e do público acerca dos riscos tecnológicos. In Gonçalves, M. E. (org.). Cultura Científica e Participação Pública, Oeiras, Celta, 109 – 120.

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Frank, E.; Eakin, E.; López-Carr, D. (2011). Social identity, perception and motivation in adaptation to climate risk in the coffee sector of Chiapas, Mexico. Global Environmental Change, 21(1): 66-76. Hassan, F., 2000. Environmental perception and human responses in history and pre-history. In McIntosh, R.J., Tainter, J.A., McIntosh, S.K. (eds.), The Way the Wind Blows: Climate, History and Human Action. Cambridge University Press, 121-140. Hübner, A.; Gösseling, S. (2012). Tourist perceptions of extreme weather events in Martinique. Journal of Destination Marketing & Management, vol 1 (1,2): 47-55. Hulme, M.; Dessai, S.; Lorenzoni, I. and Nelson, R. D. (2009). Unstable climates: exploring the statistical and social constructions of ‘normal’ climate. Geoforum, 40: 197-206. Kahan, D.; Wittlin, M.; Peters, E.; Slovic, P.; Ouellette, L. L.; Braman, G.; Mandel, G. (2011). The tragedy of the risk perception commons: cultura, conflicto, rationality conflicto and climate change. Working Paper No. 89, available at: http://probeinternational.org/library/wp-content/uploads/2011/07/SSRN-id1871503.pdf Keul, A. G.; Holzer, A. M. (2013). The relevance and legibility of radio/tv weather reports to the australian public. Atmospheric Research, 122: 32-42. Klinke, A. and Renn, O. (2001). Precautionary principle and discursive strategies: classifying and managing risks, Journal of Risk Research, 4(2): 159 – 173. Klinke, A. and Renn, O. (2002). A new approach to risk evaluation and management: risk-based, precaution-based, and discourse-based strategies, Risk Analisys, 22(6): 1071 – 1094) Lima, M.L. (2004). Images of the public in the debates about risk – consequences for participation, Portuguese Journal of Social Sciences, 2(3): 149-163. Marin, A. (2010). Riders under storms : contributionsof nomadic herders’ observations to analysing climate change in Mongolia. Global Environmental Change, 20: 162-176. Marx, S. M.; Weber, E. U.; Orlove, B. S.; Leiserowitz, A.; Ktantz, D. H.; Roncoli, C.; Phillips, J. (2007). Communication and mental processes: Experiential and analytic processing of uncertain climate information. Global Environmental Change, 17 : 47-58. Meze-Hausken, E., 2007. Seasons in the sun – weather and climate front-page news stories in Europe’s rainiest city, Bergen, Norway. International Journal of Biometeorology. 52 (1): 17–31. Mormont, M. (1993). Sciences Sociales et Environnement - Approches et Conceptualisations, Rapport au Service de la Recherche du Ministére de L'Environnement, Belgium, FUL. Moser, S.; Dilling, L. (2011). Communicating cliamte change : closing the science-action gap. In Dryzec, J. S.; Norgaard, R. B. ; Schlosberg, D. (eds.) The Oxford Handbook of Climate Change and Society, Osford, Oxford University Press, 161-174. Rebetez, M. (1996). Public expectations as an element of human perception of climate change. Climatic Change, 32 : 495-509. Redclift, M. and Woodgate, G. (1994). Sociology and the environment: discordant discourse? In Redclift, M. and Benton, T. (eds) Social Theory and the Global Environment, London, Routledge, 51-66. Renn, O. (2004). Perception of risks. Toxicology Letters. 149: 405 – 413. Sjöberg, L. (1994). Perceived risk vs demand for risk reduction. Risk Research Report, 18, Stockolm: Centre for Risk Research. Slovic, P. (1987). Perception of risk. Science, 236: 280-285.

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Slovic, P.; Fischhoff, B. and Lichtenstein, S. (1981). Perceived risk: psychological factors and social implications. In Proceedings of the Royal Society, Risk Report A376, London: Royal Society, 17 – 34. Solomon, S. et al. (2007). Glossary. In Climate Change 2007: the physical science basis. Contribution of WG 1 to the 4th Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, University Press. Spaargaren, G.; Mol, A. P. J. and Buttel, F.H. (2000). Introduction: globalization, modernity and the environment. In Spaargaren, G.; Mol, A. P. J. and Buttel, F. H. (eds.) Environment and Global Modernity, London, Sage, 1 – 16. Strauss, S.; Orlove, B.S. (2003). Up in the air: the anthropology of weather and climate. In Strauss, S.; Orlove, B. S. (eds) Weather, Climate, Culture, Oxford, Berg Publishers, 3-16. White, G.; Kates, R.W. and Burton, I. (2002). Knowing better and loosing even more: the use of knowledge in hazards management, Global Environmental Change, Part B – Environmental Hazards, 3(3-4): 81 – 92. Yearley, S.; Forrester, J. and Bailey, P. (2000). Participação e perícia científica: sobre os modelos científicos e os seus públicos. In Gonçalves, M. E. (org.) Cultura Científica e Participação Pública, Oeiras, Celta, 183 – 200.

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THE DEVELOPMENT OF MODERN THEORIES ON WEATHER FORECASTING IN ITALY UP TO THE SECOND WORLD WAR Iafrate L.1and Perini L. 1 1

Consiglio per la Ricerca e la Sperimentazione in Agricoltura – Unità di Ricerca per la Climatologia e la Meteorologia applicate all’Agricoltura [Agricultural Research Council – Research Unit for Climatology and Meteorology applied to Agriculture]

Summary Weather forecasting has always been a human need since ancient times. However, the theoretical foundations of modern weather forecasting were laid in the 19th and 20th centuries. In Italy the scientific progress of weather forecasting methods came from the development of original theories conceived by Italian scientists and from researches aimed at adapting the most important contributions of foreign meteorologists to the particular synoptic conditions of Italy. Our main goal is to highlight the known and unrecognized theoretical contributions concerning the Italian Dynamic and Synoptic Meteorology.

Keywords: weather forecasting – modern theoretical development – Italy – 19th and 20th centuries – rediscovery of forgotten forecasting methods

A GENERAL OVERVIEW Dynamic meteorology was born in the last quarter of 1600 and developed in the subsequent century. Edmund Halley (1656-1742) and George Hadley (1685-1758) gave impetus to the first studies on this subject. Halley was the first to identify the cause of the general circulation of atmosphere in the unequal distribution of solar heat on the Earth’s surface, by recognizing its starting point in the effects of greater equatorial heating (Historical Account of the Trade Winds and Monsoons, 1686). George Hadley, a lawyer by profession, provided the first scientific explanation of the deflecting force acting on the atmospheric motions (Philosophical Transactions of the Royal Society of London, 1735). Meanwhile, the Swiss mathematician Daniel Bernoulli (1700-1782), developed his Hydrodynamica (1738), which marked the beginning of theoretical hydrodynamics. In it, among other things, he clearly anticipated some fundamental elements of the kinetic theory of gases (19th century). A great contribution to dynamic meteorology was given by the French mathematician and philosopher Jean Le Rond d'Alembert (1717-1783). In his work Réflexion sur la Cause des Ventes General (1747), awarded by the Berlin Academy, he was the first to describe the atmospheric motions in terms of partial differential equations. The meteorological science owes much to Swiss Leonhard Euler (1707-1783), famous like Bernoulli. Through the calculation of the forces acting on the fluid particles and applying the second law of Newton, Euler came to the generalization of the equation of continuity or conservation of mass, which represents a particular simplified form of the Navier Stokes equations. The equation of continuity is, along with the equations of motion, one of the fundamental equations which govern the atmospheric movements.

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Joseph Louis Lagrange (1736-1813), an Italian mathematician of French origin, formulated the fundamental equations of hydrodynamics in the other widely known form (1769). The 18th century ended with the formalization of the fundamental equation of hydrostatics by the French astronomer and physicist Pierre Simon de Laplace (1749-1827), one of the greatest scientists of the Napoleonic epoch. From this equation Laplace derived the well-known equation of Statics of atmosphere. During the 1700s, scientists, through their theoretical studies on the dynamics of atmosphere, laid the foundations for a development of meteorology as an autonomous science. Indeed, the atmosphere has been investigating by the laws of Mechanics and Thermodynamics since the first half of 1800. This is for a high and humanitarian purpose: the weather forecasting. A new kind of scientist was being born: the weatherman. In this regard, the American scientist William Ferrel (1817-1891) suggested the existence of a circulation cell in the mid-latitudes, with air being deflected by the Coriolis Force to create the prevailing westerly winds. The formalization of such a known theory marked the full entry of meteorology in the domain of Dynamics. Indeed, since then the greatest physicists and meteorologists have been turning their attention to it, such as Maurice de Tastes, Aleksandr I. Voeikov, Hermann von Helmholtz, Heinrich R. Hertz, Cato M. Guldeberg, Henrik Mohn, Franz Exner and the Italian Luigi De Marchi. As far as Atmospheric Sciences are concerned, the decade 1880-1890 was one of the most intense periods in the history of meteorology. In those years, the famous German physiologist, mathematician and physicist Hermann von Helmholtz (1821-1894), starting from the Eulerian form of the general equations of hydrodynamics, analytically studied the equilibrium conditions at the boundary between air masses with different temperature and movement (discontinuity surface). He took into account the concept of hydrodynamic instability to explain the origin of fronts and depressions from a theoretical point of view. Hermann von Helmholtz’s theoretical approach to meteorology was developed later, in more detail, by Max Margules (1856-1920), Franz von Exner (1849 -1926) and William Napier Shaw (1854-1945) and at the Norwegian Meteorological School (the polar front and cyclone theory). In the 19th century, history of science also saw the birth of thermodynamics and its subsequent application to the atmospheric phenomena. Von Helmholtz was the first, in 1847, to formalize the first law of thermodynamics, or the principle of "conservation of energy”, which opened a new horizon for meteorological research: the study of the thermodynamic properties of atmosphere. The 1800s synoptic meteorology began under the sign of the study of storms and cyclones. In 1831, an American engineer of Connecticut, William Redfield (1798-1857), conceived the nature of the whirling cyclones or depressions and the direction of wind rotation within them: counterclockwise in the northern hemisphere and clockwise in the Southern one (“Circular Theory of Cyclones”). Redfield’s theory was followed by a lively debate between the author and one of the most eminent meteorologists of America, James Pollard Espy (1785-1860). Espy built his theoretical meteorology mainly on the new concepts of convection and adiabatic process, in order to fully understand the role played by water vapor in the atmospheric thermodynamic processes. Meanwhile, the German physicist and meteorologist Heinrich Wilhelm Dove (1803-1879) attacked the Redfield and Espy cyclone models. He conceived the atmosphere of the mid-latitudes as a zone of interaction between the currents of polar origin, cold and dry, from northeast, and the tropical air, hot and wet, from southwest. In their “fight”, Dove recognized the cause underlying the origin of cyclonic storms formed at these latitudes (1837). The English admiral Robert Fitz Roy (1805-1865) came to a similar theory too. He also added that the cyclones develop right on the border between the two currents and are organized into families. However, Dove and Fitz Roy’s ideas will be elevated to the dignity of theories only in the subsequent century by the Norwegian Meteorological School. The interest of meteorologists for anticyclones appears poor in all this time. The naturalist and statistician Francis Galton (1822-1911), one of the founders of the Royal Meteorological Society of London, was the first to identify the particular characteristics of a high pressure area (1863). The French meteorologist Léon Teisserenc de Bort (1855-1913) developed original researches about both the Azzorre anticyclone and the Asian cold high pressure, the two main “action centers” which govern the evolution of weather in Europe. In this regard, he also recognized the Iceland semi-permanent depression as an equally important action center.

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The English meteorologist Ralph Abercromby (1842-1897) added to cyclones and anticyclones (the two main isobaric patterns) five other secondary ones, namely the promontory or wedge, the trough, the secondary cyclone (secondary low pressure originating from a trough), the saddle, the slope. This classification is exhaustively treated in his book Weather, published in 1888, and is of interest not only historic, being universally adopted today. While Abercromby worked on his classification, Wladimir P. Köppen, a renowned climatologist, W. J. van Bebber and N. A. Rykachev (both meteorologists) were turning their interest to the study of the trajectories followed by cyclones in Europe (extra-tropical cyclones), in order to identify those prevailing, from a statistical point of view.

THE FIRST MODERN WEATHER FORECASTING SERVICE IN THE WORLD In Italy and in the rest of the world, the first weather forecasting Service was founded by the famous astronomer Father Angelo Secchi (1818-1878). This is exactly the prototype of the modern meteorological Services. Angelo Secchi, when he was the director of the Astronomical and Meteorological Observatory at the “Collegio Romano”, was able to organize, within the borders of the Papal States, a coordinated and systematic Service for synchronous meteorological observations and weather forecasting. It began to operate in June 1855 and had its main stations in Rome (Collegio Romano), Civitavecchia, Ancona, Bologna, Ferrara, Pesaro, Urbino and Perugia. The stations in Rome, Ancona, Bologna and Ferrara were all equipped with telegraph in order to interchange data. Every day, they mutually exchanged their observations of pressure, temperature, humidity, wind and the general state of the atmosphere, in order to draw useful indications for forecasting. Weather forecasting, storm warnings at first, were formulated according to the most likely meteorological evolution, figured by Father Secchi starting from the values of pressure, temperature, humidity and wind at the European scale, with regard to a given instant. After the weather forecasts had been prepared, the stations of Rome, Ancona, Bologna and Ferrara were systematically alerting the nearby Harbour Master, in order to prevent possible damage to navigation. Secchi’s forecastings were based on the fundamental principles of the emerging dynamic meteorology. Angelo Secchi says about them in his booklet L’Astronomia in Roma nel pontificato di Pio IX [The Astronomy in Rome during Pius IX's pontificate], published in 1877: «La meteorologia in questi ultimi anni è entrata in una fase novella; essa non si occupa solo della climatologia, ma della fisica generale dell’atmosfera e delle correnti aeree e del giro delle burrasche. Lo scrivente si trovava in America all’epoca delle grandi scoperte di Maury, gli vide i suoi metodi [di studio], e dalla sua bocca stessa raccolse le sue [moderne] idee [di meteorologia dinamica], e fu sua cura informarne al ritorno i suoi compatrioti … Le osservazioni raccolte dal Leverrier venivano poscia litografate e rinviate così raccolte agli osservatorii. All’osservatorio [del Collegio Romano], sulla base di tali bollettini, si studiavano le leggi delle burrasche. Il giovane signor Serra-Carpi tracciava le curve isobariche ed isotermiche sulle carte mute d’Europa. Attraverso la loro analisi, si riuscì a riconoscere la direzione ben definita che le burrasche ben circoscritte di natura ciclonica hanno, da N-W verso S-E e si riconobbero queste linee di corso così marcate, che quando un «pozzo», ossia una notabile depressione si presentava nella Scozia, essa generalmente veniva difilata sull’Italia, impiegando due o tre giorni ad arrivarvi, ma se essa si presentava più alta o più bassa, Roma non sentiva che gli effetti indiretti dei suoi margini. Grazie a questi risultati, è molto probabile che simili carte venissero fatte costruire sistematicamente e pubblicate a Parigi, dal Leverrier, che con mezzi posseduti da una nazione ricca come la Francia poté diffonderle: così la teoria dei preavvisi delle burrasche nacque». I will summarize the content of this quotation below. At the Collegio Romano Observatory, Father Secchi studied the laws of storms. According to national and international meteorological data, the young Mr. Serra Carpi traced isobars and isotherms on the mute maps of Europe, the first in the world constructed for this purpose. Through their analysis, it was possible to recognize the direction of the wellcircumscribed cyclonic storms, generally from NW to SE. In particular, a deep depression over Scotland meant that the weather would be worsened in Italy after two or three days. Thus the theory about storm warnings was born. Angelo Secchi also based its forecasts on the hypothesis of a likely correlation between the magnetic variations and the subsequent atmospheric phenomena: ________________________________________________________________________________________________ ISBN 9788895597188

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«Benché la legge di relazione non sia semplice, è dimostrato però che non accade burrasca grande che non sia accompagnata da cambiamenti magnetici. Anzi, questi possono benissimo servire a preannunziare l’arrivo della burrasca stessa. Sono ormai 18 anni che si osserva tale coincidenza, per cui non si può dire che la cosa sia fortuita o accidentale». Figure 1: Father Angelo Secchi’s letter written to Father Francesco Denza in order to claim the merit of the foundation of the first modern weather forecasting Service in the world.

Here is the transcription of Father Angelo Secchi’s letter:

‹‹Ch.mo Sig. Professore e Revdo Padre Roma 9 Marzo 1866. La è gran questione quella di dire chi abbia pel primo iniziato il servizio meteorologico telegrafico. - Passioni senza fine si sono mescolate a questa semplice scoperta, che poteva venire in mente a tutti.- Se parliamo di un servizio momentaneo eccezionale, molti possono avervi avuto merito. E credo che in America e in Inghilterra si sia fatto prima che in Europa. A desiderarlo e proporlo molti più. In Italia e in Europa sono stato io il primo a effettuarlo, tra Roma, Bologna, Ferrara, ed Ancona, ma altri l’aveva già progettato. Ma quelle idee chi sa in quanti cervelli sono fiorite: meglio è che ognuno si faccia valere i suoi titoli, e io non mi scalderò molto perché ho documenti sicuri di quel che ho fatto, che cosa siasi fatto prima lo lascio agli altri … Sono con distinta stima, Suo dev.mo A. Secchi››

THE BIRTH OF A NEW WEATHER FORECASTING METHOD IN ITALY: THE SYSTEMATIC ANALYSIS OF ISOBARIC PATTERNS The study of isobaric patterns was in Italy unique in its kind. It started in 1876 with the astronomer Paolo Frisiani, and was related to the thunderstorms which struck the Po Valley. The first results are in an original memory processed by a famous astronomer at the Brera Observatory (Milan), Giovanni Virginio Schiaparelli (1835-1910). The systematic analysis of the thunderstorm isobaric patterns was later performed by the Regio Ufficio Centrale di Meteorologia (the “forefather” of CRA-CMA) and extended throughout Italy. This activity led to the classic memories by Ciro Ferrari and M. Sacchi, within a few years. Ferrari was particularly interested in thunderstorm observations at ________________________________________________________________________________________________ ISBN 9788895597188

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different atmospheric levels and inside the phenomenon: intrinsic conditions and “physiology” of thunderstorms. This new Italian method was successfully used abroad, especially in Germany, Sweden and Norway, where scientists such as Van Bebber, Richard Assmann, Henrik Mohn and Hugo Hildebrand Hildebrandsson were inspired to it. To Atlantic and African isobaric patterns studied by Schiaparelli, Luigi De Marchi added another one: the so called “Anti-Atlantic”, all three dispenser of rain and thunderstorms, mostly in Northern Italy. Schiaparelli has also the merit of basing his forecasts on account of high pressure areas. Figure 2: Weather Chart of Italy, on 3rd February 1904. Anti-Atlantic pattern: widespread rains in the Po Valley.

A MISUNDERSTOOD GENIUS: LUIGI DE MARCHI Luigi De Marchi was born in Milan on May 16, 1857, and died in Padua on February 15, 1936. He graduated in Physics and Mathematics in 1880. He worked as a librarian from 1881 to 1902. De Marchi was a professor of Physical Geography at the University of Padua from 1902 to 1932. On February 24, 1934, he was named Senator of the Kingdom for his high scientific merits. Luigi De Marchi, geophysicist and geographer at the same time, was a very versatile scientist, able of moving, with ease, from a research to another, in many different fields of Physics of the Earth and Physical Geography. He began his career with original scientific researches on Theoretical Meteorology. The origin of these studies consists of his youth study entitled Ricerche sulla teoria matematica dei venti 5, published in 1883 and followed by an original Appendix titled Sulla costanza della rotazione totale in un sistema di venti 6 (1884), and a memory that completes them: Sulla teoria dei cicloni 7 (1893). In such works he described, for the first time, the fundamental concept of “absolute vorticity”, generally attributed to Carl-Gustav A. Rossby (1898-1957).

5

Research on the Mathematical Theory of Winds (1883) On the constancy of the total rotation in a system of winds. 7 On the theory of cyclones. ________________________________________________________________________________________________ 6

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It is likely that Rossby theorized the concept of vorticity (in the ‘40s years of the last century), by drawing inspiration from De Marchi’s studies, since they are mentioned in Lehrbuch der Meteorologie by Adolf Sprung (Hamburg 1885), the most important book on dynamic meteorology for about three decades. In his researches on the mathematical theory of winds (1883), De Marchi established a relationship between the density of air and the “hydrodynamic rotation”, theoretically determined on the basis of the evolution a fixed cyclone. He also attempted to distinguish cyclones in thermal and dynamic ones. He argued that their motion responds exactly to the thermal distribution determined in the upper layers by vertical movements: descending on the north and west sides, ascending on the south and east ones. As a result, he explained the character and distribution of precipitations in these two different areas of cyclones, ahead of the Norwegian theories about cold and warm fronts. Figure 3: Luigi De Marchi: the founder of Theoretical Meteorology in Italy.

With regard to the new theoretical achievements of the Norwegian School, which substantially considered cyclogenesis as the result of a kind of instability along the border of air masses with different density (discontinuity surface), De Marchi showed skepticism, for their generalization. He asked his student Cesare Fabris to examine the Norwegian theories and his assistant Lucia Venturelli to analyze the aerological measurements, in order to verify the correspondence of these “ideas” to weather phenomena actually observed. Figure 4: Cover of “Meteorologia Generale” [General Meteorology] by Luigi De Marchi, 5th edition (1944).

OTHER EMPIRIC WEATHER FORECASTING METHODS In the early 1920s, the new method of the Norwegian School was widely used in almost all countries. However, forecasting was not based only on it, but obtained taking into account the results of other methods too, both classical ________________________________________________________________________________________________ ISBN 9788895597188

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and modern. The spectral analysis developed by Francesco Vercelli and the so-called "cloudy systems" method deserves to be described in our work. According to Francesco Vercelli (1883-1952), a well-known Italian geophysicist, meteorology has the task to forecast, on “theoretical” basis, the continuous pressure variations, as "the first cause, if not unique, of all atmospheric phenomena”. Instead of studying the likely changes of isobaric patterns, he experienced the analysis of the future aperiodic oscillations of atmospheric pressure, to which weather modifications are intimately connected. The spectral analysis method consists of decomposing each primitive barometric diagram in its oscillatory components and their subsequent extension for future time intervals (as far as aperiodic ones are concerned). General weather forecasting obtained by this method was a “synthesis” of the different “omens” separately calculated for each location. The spectral analysis was carried out by an early original calculation engine (see the picture below), known as “harmonic Analyzer”. It was created by an officer of the R. Servizio Aerologico Italiano (Italian Aerological Service), Lieutenant engineer Domenico Tavanti. It seems that such forecasts were not disappointing, especially in the most serious and decisive moments of the First World War. Figure 5: Mechanical analyzer of atmospheric pressure oscillating curves, a very early example of calculating machine for weather forecasting (at the Museo di Fisica dell’Università di Torino).

The cloudy systems method, conceived by the meteorologists Philippe Schereschewsky and Philippe Wehrlé, was based on the examination of the clouds, independently of other meteorological elements and only in connection with atmospheric pressure changes. Schereschewsky and Wehrlé were referring to a group of cloud masses associated with each other and constituting, overall, an organic, complex cloud system, that originates, develops, moves, extinguishes, but always retaining their own individuality. Each system is composed of: the contour, with clear skies; the front, with cirrus, cirrocumulus and cirrostratus formations; the body, which forms and identifies its rainy region; the margin (around the body); towing, a vast and irregularly cloudy area that follows the body, where the presence of isolated cumulonimbus may give rise to violent storms (along the squall lines). Weather forecasting was based mainly on wind observations at high altitudes and the isallobaric analysis. Isallobars are lines depicting all points with equal pressure tendencies.

CONCLUSIONS In this paper, we have described original theories and brilliant ideas on weather forecasting methods developed in Italy, especially by scientists such as Angelo Secchi, Giovanni Virginio Schiaparelli, Ciro Ferrari, Luigi De Marchi, Francesco Vercelli, Cesare Fabris and Lucia Venturelli, in order to shed light on the history of Italian meteorology since the mid- 1800s to the Second World War. The only way to rediscover forecasting methods now fallen into oblivion.

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ACKNOWLEDGEMENTS AND REMARKS Our work was carried out within the research activities developed in the Agroscenari Project, concerning the impact of Climate Change on Italian agricultural systems. We are deeply grateful to Prof. Vittorio Cantù for his useful suggestions, to Dr. Domenico Vento (the coordinator of Agroscenari), who allowed us to accomplish this contribution under this Project, and to Dr. Angelo Caglioti for the revision of the draft.

REFERENCES Abbe, C. (1907). The progress of science as illustrated by the development of meteorology. Annual Report of the Board of Regents of the Smithsonian Institution: 287-309. Affronti, F. (1977). Atmosfera e meteorologia. Modena: STEM. Affronti, F. (1958). Cento anni dalla legge di Buvs-Ballot. Rivista di Meteorologia Aeronautica 1: 40-53. Alippi, T. (1909). La previsione del tempo. Rivista Meteorico-agraria 30: 389-394. Baroni, A. (1984). La circolazione generale dell’atmosfera. In Corso di aggiornamento sull’agrometeorologia. Roma: Federazione Nazionale Dottori in Scienze Agrarie e Forestali. Bernacca, E. (1991). Il tempo domani. Firenze: Giunti. Boffito, G. (1929). Gli strumenti della scienza e la scienza degli strumenti. Firenze: Libreria Internazionale Seeber. Camuffo D. (1990). Clima e uomo. Meteorologia e cultura: dai “fulmini” di Giove alle previsioni via satellite. [Milano]: Garzanti. Cantù, V. (1983). Ferdinando II de’ Medici creatore della meteorologia moderna. Atti della Fondazione Giorgio Ronchi 38: 661-675. Cantù, V. (2004). Meteorologia. Climatologia. Cambiamenti di clima. Storia della meteorologia nel sec. XX in tre saggi. In Quaderni di geofisica 37. Roma: Istituto Nazionale di Geofisica e Vulcanologia. Cappello, C. (1911). La previsione del tempo e il metodo di Guilbert. Rivista Meteorico-agraria 32: 31-37. Chaboud, R. (1993). La météo. Questions de temps. Paris: Nathan. Dampier, W. C. (1953). Storia della scienza. Torino: Einaudi. Denza, F. (1883). La meteorologia in Italia. Gli Studi in Italia 6: 405-449. Eredia, F. (1914). L’organizzazione del servizio dei presagi del tempo in Italia. Rivista Meteorico-Agraria 35: 10011048. Eredia, F. (1941). Nuovi orizzonti della meteorologia. Milano: V. Bompiani. Fierro, A. (1991). Histoire de la météorologie. Paris: Denoel. Frisinger, H. H. (1977). The history of meteorology to 1800. New York: S.H.P. Hellmann, G. (1891). Sulle origini delle osservazioni e degl’istrumenti meteorologici. Rivista Marittima: 99-116. Hildebrandsson, H. and Teisserenc De Bort, L. (1907). Les bases de la météorologie dynamique. Paris: GauthierVillars et Fils.

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Iafrate, L. (2008). Fede e scienza: un incontro proficuo. Origini e sviluppo della meteorologia fino agli inizi del ‘900. Roma: Ateneo Pontificio Regina Apostolorum. Iafrate, L. (2011). Padre Angelo Secchi: l’astronomo italiano che inventò le previsioni del tempo. Nova Historica: rivista internazionale di storia 36: 110-130. Khrgian, A. Kh. (1970). Meteorology. A historical survey. Jerusalem: Israel Program for scientific Translation. Mangianti, F. and Beltrano, M. C. (1990). Il Collegio Romano: 100 anni di osservazioni meteorologiche. Roma: UCEA. Palmieri, S. (2000). Il mistero del tempo e del clima. Napoli: Cuen. Perini, L. (2008). La desertificazione in Italia: processi, indicatori, vulnerabilità del territorio. Acireale: Bonanno. Racca, G. and Esposito, S. (2006). Meteorologia in dentelli. Prima parte: Evoluzione storica. Roma: CRA – UCEA. Secchi, A. (1879). Lezioni elementari di fisica terrestre. Con l’aggiunta di due discorsi sopra la grandezza del Creato. Torino: Ermano Loescher.

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OZONE MEASUREMENTS IN 19TH CENTURY ON THE TERRITORY OF THE HABSBURG EMPIRE Baranka G.1, Weidinger T.2, Bozó L.1, Balázs R.1, Somfalvi-Tóth K.1, Szabó Z.2 and Tarjányi Z.2 1

2

Hungarian Meteorological Service, Budapest, Hungary Department of Meteorology, Eötvös Loránd University, Budapest, Hungary)

Summary Ozone, one of the most important trace gases in atmosphere was discovered by Christian Friedrich Schönbein (1799– 1886), a chemistry professor at the University of Basel. The method developed by him was used from the middle of nineteenth century until the 1920’s in much of the world. In this study, we will convert Schönbein numbers to ozone concentrations in ppbv using the approach outlined in Pavelin et al. (1999). We obtained records for ozone measured in the Habsburg Empire for analyse the long term environmental processes. According to records kept in the Habsburg Empire, ozone was measured at more than twenty sites between 1853-1856. It should be emphasized that the earliest datasets in the world we have are from the stations in the Habsburg Empire. Some interesting aspects of these early measurements have been also mentioned here (Weidinger et al., 2009).Furthermore, we report here reconstructed ozone measurements obtained in the Habsburg Empire from the latter half of the 19th century until the 1910s. Long term datasets are available from Buda (1871–1898) and Ó-Gyalla (Altdala, Hurbanovo, 1898–1905), which indicate differences between urban and rural areas. This difference could be related to emissions of reducing gases such as SO2 emitted in urban areas. Additionally meteorological variables (like air temperature, relative humidity, air pressure, wind speed, cloud cover, precipitation) were also observed several times a day. Finally ozone datasets from the 19th and 21st century and the differences in ozone concentration and deposition between rural and urban areas are compared. Ozone concentrations and deposition are found to be approximately three times higher now than in the 19th century over Central European region.

Keywords: historical ozone, deposition, Schönbein’s method, urban effect

DISCOVERY OF OZONE AND ITS ENVIRONMENTAL EFFECTS The first technique for measuring ozone was developed by Schönbein. The method was based on an indicator paper coated with starched potassium iodide. A color-change of an indicator test paper was recorded on a scale ranging from 0 to 10 or 0 to 14. The strip of paper turns brown depending on the extent of the reaction of iodine with ozone and also because of humidity. Because of the effect of humidity on the measurement, the relation between color change and the concentration of ozone is not linear ((e.g., Fox, 1873; Linvill et al., 1980; Kley et al., 1988; Walshaw, 1990; Möller, 1999; Mordecai, 2001). Ozone is beneficial in the stratosphere by absorbing UV radiation, in the same time it is a pollutant near the surface. Ozone near the surface damages vegetation, animals and is toxic to humans; decreased agricultural crop yields; and damage to man-made materials. Ozone is a secondary pollutant meaning that it is not directly emitted into the atmosphere. Instead, ozone is produced in the atmosphere by photochemical reactions involving precursor species (such as NO, NO2, CO, VOC) released from man-made sources (such as traffic and industry) and from natural sources (such as vegetation and lightning). Stratospheric-tropospheric exchange is another important source of tropospheric ozone (Sándor et al., 1994). The concentration of near surface ozone has characteristic seasonal and daily variations. Its seasonal variation is characterized by winter minima and summer maxima in areas that are strongly influenced by pollution sources. Secondary maxima occur in early spring due to intrusions of stratospheric air. The highest ozone concentrations are typically found in the afternoon and in the early evening as the result of photochemical activity. In ________________________________________________________________________________________________ ISBN 9788895597188

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remote areas, i.e., areas not strongly influenced by recent pollution, ozone has a maximum in spring and a minimum in fall. The diurnal variation of ozone is much weaker in remote areas than in polluted areas and maxima can occur at any time of the day or night (Nolle et al., 2002; Wilson et al., 2011). Ozone is a potent greenhouse gas and is ranked third in importance after CO2 and CH4 (IPCC, 2007). For calculating the contribution of ozone to radiative, and hence climate forcing due to anthropogenic activities, it is necessary to know the history of ozone extending from the pre-industrial era to the present. In addition, long term trends in ozone concentrations are needed to assess the long-term effects of exposure of vegetation to ozone. Currently, measurements of ozone are obtained routinely around the world by surface based measurement networks and by satellites. However, these methods have only been in use for a few decades and other techniques must be relied on to obtain semiquantitative data for ozone.

CALCULATION OF OZONE CONCENTRATION AND FLUX FROM HISTORICAL MEASUREMENTS Since shortly after the development of the Schönbein test paper method, studies have attempted to relate the color changes to ozone concentrations. Fox (1873) noted that the color change is related to humidity. This happens because a damper surface can absorb more ozone. He also found that higher temperatures lead to higher ozone. Albert-Levy (1877) realized that gases such as SO2 lead to reduction of ozone and developed the first quantitative method for measuring ozone, based on the oxidation of arsenite. Several more recent studies have examined the question of how to relate Schönbein numbers from the color changes to ozone concentrations (e.g., Linvill et al., 1980; Bojkov, 1986; Volz and Kley, 1988; Marenco et al., 1994; Pavelin et al., 1999). Wind speed and sampling time (usually 8–14 hours) can also affect the measurements. Based on data from Linvill et al. (1980) and Anfossi et al. (1991), Pavelin et al. (1999) developed a procedure to account for the dependence on relative humidity. The estimated uncertainty of the method is ~ 25%. The ozone flux (F) can be determined over a given type of vegetation using data for ozone concentration and deposition velocity (Wesely−Hicks, 2000; Lagzi et al., 2004; Mészáros et al., 2009):

F = vd (C ref − C0 ), C0 = 0 where vd is deposition velocity, Cref is concentration at reference level, C0 is concentration at the absorbent surface. Measurements of deposition velocity were made in the early 1990s in Hortobágy (over a grassy surface) and Nyírjes (in the Mátra Mountains in Hungary over a coniferous forest) are shown in Table 1. Values from Nyírjes will be used for estimating ozone deposition during the vegetation growing season (from April to October) over coniferous forests. Table 1. Deposition velocity of ozone [cm/s] over a coniferous forest in the Mátra Mountains on the basis of field measurement campaigns from 1991 to 1993 (Horváth et al., 1996). Spring Summer Autumn Winter Daytime

0.50

1.20

0.63

0.17

Nighttime

0.04

0.34

0.03

0.04

Entire day

0.34

0.86

0.39

0.12

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Reconstructed ozone measurements, measurement sites and measurement periods from the 19th century currently available in the literature (Pavelin et al., 1999) are shown in a contemporary geographical map (Figure 1.). We report here reconstructed ozone measurements obtained in the Habsburg Empire from the latter half of the 19th century until the 1910s. According to the map, earliest data obtained outside the Habsburg Empire were in Hong Kong, Michigan, in France at the Pic de Midi Observatory. The measurements at each site were carried out using the Schönbein method, with different scales used, e.g., 0–10, 0–11, 0–14, 0–21. The values on the map are presented in ppbv, which has been introduced more recently. Available values were between 5 and 15 ppbv. Figure 1: Ozone measurements at the end of the 19th and the beginning of the 20th century.

Ozone measurements in the Habsburg Empire between 1853–1856 It should be emphasized that the earliest datasets in the world we have are from the stations in the Habsburg Empire shown in Figure 2. Yearbooks between 1853–1856 of the Central Meteorological Institute of the Habsburg Empire in Vienna (Wien) contain data on ozone concentration from more than 20 stations. However, ozone data were not obtained and recorded for subsequent years, except for data obtained in Vienna. Figure 2: Ozone measurement sites in Central Europe between 1853–1856.

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Numerous meteorological stations in the Kingdom of Hungary also made ozone measurements using the Schönbein method (scale of 0–10) during the day and night: Buda (Ofen), Szeged (Szegedin), Selmecbánya (Schemnitz) and Besztercebánya (Neusohl). In this study, we will convert Schönbein numbers to ozone concentrations in ppbv using the approach outlined in Pavelin et al. (1999). There are some interesting aspects of the measurement worth mentioning: (i) Vienna has quite a long ozone measurement period from 1853 to the end of 19th century; (ii) Ozone observation started in 1856 in Buda, however there was continuous published dataset in yearbooks only from 1871; (iii) in Krakau (Krakow), four Schönbein papers were simultaneously posted towards the four points of the compass to study the differences caused the wind speed outside the building (shielded vs. exposed); (iv) in Lemberg (Lviv) two daytime measurements were carried out; one in the morning and one in the afternoon. The concentrations measured were similar (Weidinger et al., 2009).

Spatial distribution of ozone over the Habsburg Empire in 1855 The good coverage of measuring sites of ozone allows to analyze the spatial distribution of ozone concentration. Density of measurements was quite high compared to today. The frequency of measurements allows us to determine daytime and nighttime ozone concentrations. Figure 3: Annual average ozone concentration [ppbv] on the Habsburg Empire in 1855.

The spatial distribution of ozone concentration in 1855 – produced from numerous measurements was characterized by maximum values around Vienna and low values (less than 10 ppbv) in Szeged and in Krakow (Figure 3). A simple model using deposition velocities shown in Table 1 was adapted to calculate ozone deposition over coniferous forests. The results for the vegetation growth season (from April to October) are presented in Figure 4. Assuming the concentrations were very similar in daytime and nighttime, the differences between ozone deposition rates are caused by the different deposition velocities in daytime and nighttime (Table 1). Over coniferous forests during vegetation growth seasons ozone deposition was between 1,7 g/m2 and 3 g/m2. On the basis of land-use data from the 19th century (Timár et al., 2006, 2007) more correct calculations can be made.

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Figure 4: Ozone deposition [g/m2] over coniferous forest during the vegetation growth season (April-October) on the Habsburg Empire in 1855, calculated on the basis of reconstructed ozone concentration and deposition velocity data measured during day- and nighttime in Nyírjes (Table 1) (The coniferous forest is an example. It is not autochthonous in the Hungarian Plain.)

Ó-Gyalla dataset (1893–1905) The meteorological and geomagnetic observatory founded by Miklós Konkoly in Ó-Gyalla (now Hurbanovo, Slovakia) plays an important role in the history of Hungarian meteorology. Starting in 1900 it operated as the Observatory of the Meteorological and Geomagnetic Institute (Czelnai, 1995). Yearbooks of the Observatory contain ozone measurements (daytime and nighttime, on 0–10 Schönbein scale) besides meteorological and geomagnetic observations between 1897 and 1905. The relative humidity was measured three times of the day same as the earlier in the Szeged. Figure 5 shows monthly averages for daytime and nighttime relative humidity, Schönbein number, and reconstructed ozone concentrations over a 13 year period. Average monthly values are indicated by continuous lines. Seasonal variation of ozone shows slight changes without summer maxima (not suitable anthropogenic emissions). Maximum values occurred in early spring (at daytime as well as nighttime), which are also found in the recent ozone dataset, explained by tropopause folding, which permits transfer to the surface (Sándor et al., 1994).

COMPARISON OF OZONE DATASETS AND FLUXES IN THE 19TH AND 21ST CENTURIES OVER URBAN AND RURAL AREAS Daytime and nocturnal average ozone values are available for the stations located in the lower area of the Carpathian Basin for a period of over 150 years. In the evaluation ozone data measured at Szeged between 1854 and 1856, at Buda between 1871 and 1898 and at Ó-Gyalla between 1893 and 1905 were used. The highest Schönbein value and ozone concentration are found in Ó-Gyalla and the lowest ones at Buda. The differences between ozone values at Buda and Szeged are very small. There are not significant trends in the ozone dataset in Buda. At the same time, measured ozone data in Ó-Gyalla (12–14 ppbv) and Buda (8–12 ppbv) indicate differences between urban and rural areas. This difference could be related to emissions of reducing gases such as SO2 emitted in urban areas. Sulphate aerosol formed from the oxidation of sulphur dioxide and the ozone are interconnected since sulphate affects O3 and the oxidant chemistry by providing a surface for the conversion of NOx to nitric acid, thus blocks the formation of ozone (Unger et al., 2006).

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Figure 5: Monthly averages of nighttime and daytime Schönbein number (a, d), relative humidity (b, e) and ozone concentration (c, f ) in Ó-Gyalla between 1893 and 1905.

a)

b)

c)

d)

e)

f)

The differences in ozone levels between urban and rural areas are increasing from beginning the observations until the present day. Differences between daytime and nighttime concentrations are also rising. Increasing emissions of nitrogen oxides and other trace gases playing important roles in ozone formation and the photochemical processes have been recognized (Mészáros, 1997). On the basis of the measurements of the Hungarian Meteorological Service (for the period 1990–2008 as shown on Figure 7) increasing concentrations were found at both rural and urban areas until 1998. From 1999 however, the concentrations are decreasing in both environments. At present time ozone levels are about three times higher than they were in the 19th century (compare Figure 7 vs. Figure 6). The change of ozone deposition from 19th to 21st century was illustrated over the coniferous forest during seven months (from April to October) of vegetation growth season (Table 2.).

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Figure 6: Annual averages of Schönbein number (a) and ozone concentration (b): daytime (grey triangles), nighttime (grey circles) and entire day (black line) measurements in Szeged, Ó-Gyalla and Buda between 1854–1904.

Table 2. Estimated ozone deposition [g/m2] during the vegetation growth season (from April to October). Daytime

Nighttime

Entire day

Selmecbánya (1855)

2,2

0,3

2,5

Lemberg (1855)

2,4

0,3

2,7

Farkasfa (2008)

7,7

1,2

8,9

K-puszta (2008)

9,1

1,3

10,4

Nyírjes

9,5

2,0

11,5

(2008)

Values almost three times higher were also found in later measurements cases than in earlier ones. In 1855, ozone deposition (Figure 4.) was 2.5 g/m2 in Selmecbánya (Banska Štiavnica), while in Nyírjes 11.5 g/m2 was calculated in 2008. Currently, differences of ozone deposition between two stations (Farkasfa and Nyírjes) are higher than the baseline deposition in the 19th century. In other words the spatial changes are larger than for the total deposition a century and a half ago. Due to anthropogenic activities, photochemical reactions play more important roles at present. The differences between day and night values are increasing, and day to day variations in ozone concentrations are also increasing (see also Lagzi et al., 2004).

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Figure 7: Annual averages of ozone levels between 1990 and 2008 in Budapest (urban site) and at K-puszta (rural site).

CONCLUSIONS We present reconstructed ozone measurements and ozone deposition calculations based on these measurements (i) in the Habsburg Empire and in the Carpathian Basin in the middle of 19th century and the early 20th century; and (ii) in Hungary in the late 20th and the early 21st century. The Schönbein method is able to track the changes of concentration in the daytime and nighttime, and the seasonal changes as well. In summary: •

Reconstructed ozone concentrations in Central Europe are consistent with those deduced for measurements reported for other regions in the literature (i.e. generally in the range of 5 to 15 ppbv based on the widely accepted methodology of Pavelin et al. (1999).

•

Although the data are subject to large uncertainties (~25% and possibly larger), they indicate that ozone concentrations were not likely to be substantially greater than this range and not as high as predicted by model calculations of pre-industrial background ozone.

•

Small spatial variability of measurements over Central Europe between 1854 and 1905 for daytime, nighttime and daily values;

•

Differences in ozone level between rural (Ó-Gyalla) and urban areas (Buda) were demonstrated;

•

In Central Europe current ozone level and ozone deposition are about three times higher than in the 19th century.

AKNOWLEDGMENTS We express our thanks, for providing deposition velocity data measured in Nyírjes between 1991 and 1993, to László Horváth (Hungarian Meteorological Service), Ernő Führer (Hungarian Forest Research Institute) and Róbert Mészáros (Eötvös Loránd University), as well as to the Hungarian Meteorological Service for ozone data from the present dataset. Special thanks are due to the financial support of the project UHI3CE292P3 in Central Europe Program; COST ES0804. This work was partially supported by the European Union and the European Social Fund through project FuturICT.hu (grant no.: TÁMOP-4.2.2.C-11/1/KONV-2012-0013) and through project of Research of Critical Infrastructure (grant no.: TÁMOP-4.2.1.B-11/2/KMR-2011-0001).

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REFERENCES Anfossi, D.–Sandroni, S. (1997): Ozone levels in Paris one century ago. Atmospheric Environment 31, 3481-3482. Albert-Levy (1877): Annuaire de l’Observatoire de Montsourris 1877. Paris, pp. 398-405. Büker, P., Emberson, L.D., Ashmore, M.R., Cambridge, H.M., Jacobs, C.M.J., Massman, W.J., Müller, J., Nikolov, N., Novak, K., Oksanen, E., Schaub, M. and De La Torre, D. (2007): Comparison of different stomatal conductance algorithms for ozone flux modeling. Environmental Pollution 146, 726–735. Czelnai R., (1995): Az Országos Meteorológiai Szolgálat 125 éve (1870–1995). [125 years of the Hungarian Meteorological Service.] Országos Meteorológiai Szolgálat, Budapest, 142 p. (in Hungarian) Emberson, L.D., Ashmor, M.R., Simpson, D., Tuvinen, J.P. and Cambridge, H.P. (2001): Modelling and mapping ozone deposition in Europe. Water, Air and Soil Pollution 130, 577–582. Finkelstein, P.L., Ellestad, T.G., Clarke, J.F., Tilden P., Meyers, T.P., Schwede, D.B., Hebert, E.O., Julie A. and Neal, J.A. (2000) Ozone and sulfur dioxide dry deposition to forests: Observations and model evaluation. Journal of Geophysical Research 105, D12, 15,365–15,377. Fox, C., (1873): Ozone and Antozone. Churchill, London. Horváth, L., Weidinger, T., Nagy, Z. and Führer, E. (1996): Measurement of dry deposition velocity of ozone, sulfur dioxide and nitrogen oxides above pine forest and low vegetation in different seasons by the gradient method. In The Proc. of EUROTRAC Symp.’96 (Edited by Borell, P. M., Borell, P., Cvitas, T., Kelly, K. and Seiler, W.), Computational Mechanics Publications, Southampton, 315–318. Kley, D., Volz, A. and Mulheims, F. (1988): Ozone measurements in historic perspective. In: ISAKSEN, I.S.A. (Ed), Tropospheric Ozone, D. Reidel Publishing Co., 63–78. Lagzi, I., Mészáros, R., Horváth, L., Tomlin, A.S., Weidinger, T., Turányi, T., Ács, F. and Haszpra, L. (2004): Model calculation of ozone fluxes over Hungary. Atmospheric Environment 38, 6211–6222. Lamaud, E., Carrara, A., Brunet, Y., Lopez, A. and Druilhet, A. (2002): Ozone fluxes above and within a pine forest canopy in dry and wet conditions. Atmospheric Environment 36, 77–88. Linvill, D.E., Hooker, W.J. and Olson, B. (1980): Ozone in Michigan’s environment 1876–1880. Monthly Weather Review, 108, 1883–891. Marenco, A., Gouget, H., Nedelec, P. and Pages, J.P. (1994): Evidence of a long-term increase in tropospheric ozone from Pic du Midi data series. Consequences: Positive radiative forcing. Journal of Geophysical Research 99, 16,617– 16,632. Meyers, T.P., Finkelstein, P., Clarke, J., Ellestad, T.G. and Sims, P.F. (1998): A multilayer model for inferring dry deposition using standard meteorological measurements. Journal of Geophysical Research 103, 22645–22661. Mészáros E. (1997): Levegőkémia, [Atmospheric Chemistry], Veszprémi Egyetemi Kiadó. (in Hungarian) Mészáros, R., Zsély, I.G., Szinyei, D., Vincze, C. and Lagzi, I. (2009): Sensitivity analysis of an ozone deposition model. Atmospheric Environment 43, 663–672. Mordecai B.R. (2001): The history of Ozone. The Schönbein Period, 1839–1868. Bulletin of the History of Chemistry 26(1), 40–56. Möller, D. (1999): Global Problems of Atmospheric Chemistry – The Story of Man’s Impact on Atmospheric Ozone. Chapter 1. In: Möller, D. (ed.) Atmospheric environmental research: critical decisions between technological Process and Preservation of Nature. Springer-Verlag Berlin, Heidelberg, 3–30.

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Nolle, M., Ellul, R., Heinrich, G. and Güsten, H (2002) A long-term study of background ozone concentrations in the central Mediterranean – diurnal and seasonal variations on the island of Gozo. Atmospheric Environment 36, 1391– 1402. Padro, J. (1996): Summary of ozone dry deposition velocity measurements and model estimates over vineyard, cotton, grass and deciduous forest in summer. Atmospheric Environment 30(13), 2363–2369. Pavelin, E.G., Johnson, C.E., Rughooputh, S. and Toumi, R. (1999): Evaluation of pre industrial surface ozone measurements made using Schönbein’s method. Atmospheric Environment 33, 919–929. Sándor, V., Haszpra, L. and Baranka, G. (1994): Ozone episodes in Hungary in March. Időjárás 98, 167–178. Timár, G., Molnár, G., Székely, B., Biszak, S., Varga, J. and Jankó, A. (2006): Digitized maps of the Habsburg Empire – The map sheets of the second military survey and their georeferenced version. Arcanum, Budapest, 59 p. Timár, G., Molnár, G., Imecs, Z. and Păunescu, C. (2007): Data and projection parameters for the Transylvanian sheets of the 2nd and 3rd military surveys. Geographia Technica 1, 84–88. Unger, N., Shindell, D.T., Koch, D.M. and Streets, D.G. (2006): Cross influences of ozone and sulphate precursor emissions changes on air quality and climate. PNAS 103 (12): 4377-4380. Walshaw, C.D. (1990): The Early History of Atmospheric Ozone. Chapter 17. In: Roche, J. (ed.), Physicists look back: studies in the history of physics, CRC Press, 313–325. Weidinger, T., Pinto, J., Baranka, G. and Ivády, A. (2009): Historical ozone Measurements made in the Habsburg Empire during the 19th century. XXIII International Congress of History of Science and Technology, Ideas and Instruments in Social Context. 28 July – 2 August, 2009, Budapest, Hungary, Abstract, 554 p. Wesely, M.L. and Hicks, B.B. (2000): A review of the current status of knowledge on dry deposition. Atmospheric Environment 34, 2261–2282. Wilson, R.C., Fleming, Z.L., Monks, P.S., Clain, G., Henne, S., Konovalov, I.B., Szopa, S. and Menut, L. (2011) Have primary emission reduction measures reduced ozone across Europe? An analysis of European rural background ozone trends 1996–2005, Atmospheric Chemistry and Physics Discussions 11, 18433–18485. Zhang, L., Padro, J. and Walmsley, J.L. (1996): A multi-layer model vs. single-layer models and observed O3 dry deposition velocities. Atmospheric Environment 30, 339–345. Zhang, L., Moran, M.D., Makar, P.A., Brook, R. and Gong, S. (2002): Modelling gaseous dry deposition in AURAMS: a unified regional air-quality modelling system. Atmospheric Environment 36, 537–560. Zhu, Z., Moravek, A., Serafimovich, A., Andreae, M.O., Foken, T. and Meixner, F.X (2008): Turbulent ozonefluxes and ozone deposition velocities with in and above a spruce forest (Waldstein/Fichtelgebirge). Geophysical Research Abstracts, 10, EGU2008-A-04768.

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RECONSTRUCTING THE URBAN CLIMATE OF VIENNA USING HISTORICAL MAPS DATING TO THE EARLY INSTRUMENTAL PERIOD Žuvela-Aloise M.1, Böhm R.1, Neureiter A.1 and Koch R.1 1

ZAMG – Central Institute for Meteorology and Geodynamics / Climate Research Department, Vienna, Austria

[email protected]

Summary Observed long-term increase in temperature at the monitoring stations in urban environment has often been assigned to urbanization and intensification of the urban heat island effect. We investigate historical modifications in the urban heat island of Vienna by modeling present-day spatial distribution of heat load and comparing with one based on land use characteristics dating to the beginning of the instrumental period. The simulations are performed with the dynamical urban climate model MUKLIMO_3. Urban heat load is expressed in mean annual number of summer days (Tmax ≥ 25°C) for a 30-year climatological period which is calculated using the so-called “cuboid method”. The model simulations rely on high-resolution orography and land use data. As input data for the historical simulations we used geographical maps from the First Military Mapping Survey of Austrian Empire from the period 1764-1787, also known as “Josephinische Landesaufnahme”. The historical maps were geo-referenced, digitalized and adapted for the urban climate model. In both present-day and historical simulations, we used observational climatological data for the period 1971 – 2000 from a reference station located outside of Vienna as input and investigated differences in urban heat load originating from the land use change only. Setting aside long-term changes in the regional climate, modeling results indicate that the intensity of urban heat load in the historical center of Vienna might have been of the same magnitude compared to today’s values. The old settlement which remained mostly unchanged since the 18th century and additional defensive wall around the city center might have been sufficient to induce a strong urban heat island effect. However, severe changes in landscape outside of the city center are to be noted such as regulation of the Danube River, deforestation and urbanization of hillside Wienerwald. These changes in return modified the extent and structure of the urban heat island.

Keywords: urban heat island, urban climate modeling, Vienna historical maps, Josephinische Landesaufnahme, urbanization

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A BRIEF HISTORY OF THE FLORENTINE OBSERVATIONS BETWEEN THE SEVENTEENTH AND EIGHTEENTH CENTURIES Vergari D. 1 Crisci A. 2 Casati S.3 1

Associazione G. B. Landeschi – San Miniato (PI) / Gruppo Ricerche storiche – Museo di Storia Naturale. Università di Firenze 2 National Research Council–Institute for Biometeorology (CNR–IBIMET), Via Caproni 8 – 50145 Firenze, Italy 3 Museo Galileo - Istituto e Museo di Storia della Scienza · Piazza dei Giudici 1 - 50122 Firenze Italy

[email protected]

Summary After the birth of the first worldwide meteorological network (the well-known Rete Medicea ) during the eighteenth century, further observations were made in Florence. The role of the Florentine scientific community and its contribution to the history of meteorology, in the second half of the XVIII century , until 1812 when Ximeniano observatory started weather observation regularly, is investigated. During this period many observers have left a consistent corpus of documents, where is possible to retrieve a systematic catalogues of daily meteorological conditions, within the annotations of remarkable climatic events. These observations was collected by doctors and scientists, such a, Pietro Grifoni, Alessandro Bicchierai, Luca Martini. This ones have given a noticeable contribution to "Alimurgia", one of more relevant work of Giovanni Targioni Tozzetti, but their references are weak and not well know . The aim of work is to build a framework of the daily thermometric measurements carried out from 1751 and ending in 1775 carried out by L. Martini and P. Grifoni, through textual sources available as unpublished manuscripts and other referenced texts in order to recognize the reliability of these observations to obtain a Florentine daily time series of observations for the period investigated. This one could be to represent an important source of information in regard to pre-industrial urban climatology of Florence. The work methodology merge an historical review within a statistical analisys perspective to perform a better evaluation of these urban climatic historical sources. In this work we present in details only the historical notes and the source analisys. Keywords: Targioni Tozzetti, History of meteorology, instrument, Florence

INTRODUCTION Florence is considered by many researchers to be the birth–home of modern meteorology. This idea has also been supported by recently reported studies (BORCHI MACII, 2009). The 17th century witnessed the invention of the main meteorological instruments such as the thermometer and barometer . Other more reliable instruments such as hygrometers, anemometers and rain gauges were also developed during the same time period. The natural philosophers of that time were moving away from the former Aristotelian secular authority and turned toward to the study of natural phenomena preferring the more evident ones such as atmospheric changes. This fact facilitated an intense increase in the activity of measurement of physical quantities such as temperature, pressure, humidity. In fact the observers found reliable and useful in their work the adoption of the ________________________________________________________________________________________________ ISBN 9788895597188

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novel spirit of the "Experimental Method" established by Galileo Galilei where the scales of unit of measurement to quantify processes began to have a fundamental importance. This is the historical turning point that have marked the birth of modern meteorology which began in Florence. Indoubdetely this city had played an undisputed role in this highly innovative process in the methods of scientific investigation. Thanks to the experiments carried out in the mid-17th century in Tuscany on temperature, in 1654, the Grand Duke Ferdinando II established the first synoptic meteorological network of observers, the so-called “Rete Medicea” (Medici Network). This network sent, to the observers involved in other locations that have similar instruments, the basic knowledge to lead measurements and, later, the appropriate indications to manufacture the apparatus as well in order to maintain an adequate homogeneity in measurements. The “Rete Medicea”, coordinated by Luigi Antinori (1599-1679), was an ambitious and international initiative, involving not only local observers working in different Italian places as the Monastery of the S. Maria degli Angeli in Florence, Vallombrosa, Cutigliano-Pistoia, Bologna, Parma, Pavia, Milan, but involves other international institutions located in many different European cities as Warsaw, Paris, Innsbruck, and Osnabrück. It was the first real attempt to create a truly international scientific community based on the sharing and collaboration. This project, which was full enhanced and promoted by the Medici Court preceded the foundation of the well-known "Accademia del Cimento" by three years later. Most of the observations did not last more than a few years. The network, however, continued to exist until the closing of the Florentine Accademia del Cimento in 1667 partly due to the hostility of the Church authorities. In the years following 1670, the observations in Florence ceased. Other observers interested in meteorology probably remained active inside the Florentine scientific community. We have to wait another fifty years to find a new first record of meteorological observations directly made in Florence in 1715 by Giovanni Gualberto Beccari (FINZI, 1986). These records are currently archived at the Library of Archiginnasio at Bologna and show the renewed and growing interest from the wide scientific community, not only the Florentine's one. Moreover indicates also that the study of meteorological phenomena in the previous years that had not found favorable conditions for their development in reason to the depressed Tuscan cultural environment dominated in the last years of the Medicean power. In the last part of the Medici period, the interest concerning scientific works gradually fell and, excluding general reports of the news, there are no mention about meteorological observers as several authors (TARGIONI, 1773; ELOGJ, 1774) documented. A singular exception is given by meteorological data collected between 1728 and 1748 by Antonio Cipriano Targioni (1672-1748) and the ones carried out by Carlo Taglini in Pisa (the monthly data collected from 1724 to 1725 and yearly cumulated rainfall recorded from 1721 to 1734; TAGLINI, 1736). With transition to the Lorraine Dynasty in 1737, in Tuscany began a period of progressive reforms that affected not only politics but society as a whole. The jointed study of natural and applied sciences, knew a strong renovation creating the basis for a deep renewal in natural and experimental sciences. In a few years, physicists, botanists and physicians began to play a more important role in meteorological studies introducing many novel topic to explore. During this same period, more precise instruments were being perfected not only in Italy and Florence but also in Europe, especially in England and France. In those years, Giovanni Targioni Tozzetti, emulating the work of his uncle Cipriano, kept the daily records of temperature and pressure until the flood of Arno, in 1740, that seriously damaging his home on Via Ghibellina, destroyed all the his manuscript sheets (TARGIONI, 1767). In the same period Florentine artisans and other skilled investigators, with a solid background in science, joined together to design and create precise instruments such as the barometer designed and made by Carlo Alfonso Guadagni (1722-1801) and described in his “Lettera sopra una nuova struttura d’un barometro portatile” (GUADAGNI, 1767). The interest about meteorology notably increased in the second half of the 18th century. We find that different observers, whether for their own interest or pleasure, began making a consistent corpus of meteorological observations and created referenced data sets with the aim to document the variations in temperature regime and also the related changes in barometric pressure, fundamentally in order to understand the laws which regulate the historical variations in weather and climate as well. Thanks to the influential Jurin's work, stated in 1723, the profession most interested in meteorological observations were the medical physicians who studied how the onset of particular human diseases are correlated and influenced by local weather conditions (JURIN, 1723; CAMUFFO, 2002; PIGATTO, 2000). ________________________________________________________________________________________________ ISBN 9788895597188

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The connection between the outbreaks of epidemics and weather conditions, as well as the interactions between climate and agriculture, soon became the main topics focused on in the studies by the Florentine observers and served as an incentive and example for other investigations in Tuscany. In a few years these observations multiplied in Pisa starting with Angelo Attilio Tilli. His son Gian Lorenzo carried out thermometric observations combined with the measurement of the amount rainfall in the Botanical Garden (MAGAZZINO TOSCANO, 1771 et seg.; TARGIONI TOZZETTI, Le Selve, mss.). After 1760 in Siena the Accademia dei Fisiocritici began recording data about the rainfalls and, finally, Giorgio Antonio Pizzetti, a physician that compiled the “Effemeridi” weather and medical observation in Grosseto between 1771 and 1787 (PIZZETTI, mss.). Similar observations were also made in the cities of Pistoia and Camaiore. Most of these observations were leaded by physicians and scientists who did not always have “the conception that meteorological observations would follow precise and documented rules” (LO VECCHIO, NANNI, 2000). In Florence, the type of observations made revealed a different situation probably due to the strong scientific influence of the Accademia del Cimento's experience. In the observations analyzed, all the detectors devoted great care to many aspects: the location and surroundings, sometimes briefly, the tools used, the method of their exposure, and the hours in which the data was collected. This considerations support the hypothesis that, at least in the Florentine area, observers were partially aware of the fundamental role and the needs to follow homogeneous methodology in order to obtain and recording sharable data. In the second half of the 18th century other Florentine observers came in on the scene. In addition to Pietro Antonio Grifoni, Father Leonardo Ximenes (1716-1786) published three years worth of barometric and thermometric observations between 1751 and 1753 (BORCHI, MACII, 2009; XIMENES 1752). Another scientist known in the city for his remarks was Luca Martini, a medical physician of Arcispedale di Santa Maria Nuova, member of Società Botanica Fiorentina and in this way a colleague of Giovanni Targioni Tozzetti Despite scarce biographical information, we know that Luca Martini was an acclaimed physician and wrote numerous articles on medical 's topics. For about 19 years, from 1756 to 1775, he made regular, reliable observations on the various of weather parameter. He also kept a diary where he recorded in addition to temperature and sky conditions, the values of barometric pressure as well following the prevalent diseases meet in its regular work and took into account the seasonality the year, that were considered important in health care. In line with the observations of the Martini, Bicchierai Alessandro (1734-1797), another medical and physician of wellknown Florentine hospital from 1775 to 1795 (and according to other sources even a few years earlier) carried out other regular meteorological observations (VERGARI, 2006; MARACCHI, 1991). Unfortunately, the structure of the records of the diary only in 1775 were quiet irregular throughout the year, however, after his trip to Ferrara, carried in April of the same year, the observations appear more regularly. Each page is divided into three columns: the first two with thermometric and barometric observations of the morning and evening and the last column for “notable things”. The number of daily observations for the first four months varied from 2 to 6 times per day including parameter as the air temperature, the barometric height, the wind direction and the state of the sky. From May onwards there were at least 3 or 4 entries made at fixed times of day. The instrument’s placing is not well-known but it does seem that the thermometric recording was leaded in the coldest room of the hospital house (as recommended by Jurin in 1723) so that on February 21, 1775 the Bicchierai notes that “the window of the room where the thermometer is today was open until XJ (23 h.) last night”. The thermometer seems to have remained for most of the year in the room, at least until December 11th when it was then affixed to the inside of window panes thus making a leap of 8° Fahrenheit from the previous day’s temperature. The structure of the diary of 1795 is even more precise for along with existing data measurements of air humidity were made with a hygrometer. There were 6 daily observations made: two in the morning and four in the evening, once again at fixed hours. Even the Ephemeris published in 1794 in Atti della R. e l. Accademia Fiorentina dei Georgofili were drafted in accordance with this same structure. The Bicchierai's data series, although incomplete, shows that this work have many methodological similarities with the one leaded by Luca Martini. It is clear that the compilation of Ephemeris had, for the Florentine scientist, a close relationship with medical science and disease control even if the scientific environment that links observers appears to be more of an idea from the Accademia dei Georgofili, than that of the Arcispedale of Santa Maria Nuova that, under the reformations of Granduke Pietro Leopoldo of Tuscany, was to become a laboratory for healthcare, teaching and research . It's quite that in the Atti della R. e l. Accademia Fiorentina dei Georgofili found place the works published by Bicchierai ________________________________________________________________________________________________ ISBN 9788895597188

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where observations and archives were kept in diaries and manuscripts regarding years of 1775, 1794 and 1795. The Georgofili Academy's interest in meteorology was not new for this time. Georgofili observations were already available and made by Jacopo Ambrogio Tartini (1737-1816), a Florentine physician who published his data in the Magazzino Georgico (1785) , an unofficial journal of the Accademia dei Georgofili. Here he reported the monthly data summaries of maximum and minimum barometric height, the maximum and minimum temperatures (both in degrees Fahrenheit and that of Reaumeur), the prevailing wind, the number of rainy days and the measurement of cumulated rainfall for 1784 year (MAGAZZINO GEORGICO, 1783-1785). Observations continued to be published up until 1788 but we are not able to trace in Florentine archives where is located the original Tartini 's manuscripts in which are, probably, documented the observations starting from 1775. Other observations were made in the hospital of Santa Maria Nuova between 1776 and 1778. These were published in the “Collezione istorica di casi chirurgici” - "A Collection of Historical Surgical Cases”,-(CAVALLINI, 1779) and included a synthetic view of the thermometric observation in Fahrenheit degrees (°F ) linked to the dominant "sickness of the month". Unfortunately we have no further information of these observations and only further studies may help us to discover if other regular observations were made in the "Santa Maria Nuova " hospital. In the last years of the 18th century the number of observers further increased. We find Giuseppe Raddi (1779-1829), a botanist of the Imperial and Royal Museum of Physics, who recorded temperature data in the Florentine museum from 1797 to 1807. But we must wait for the inclusion of Tuscany in the French Empire (1808)to have a new impetus of the observations in atmospheric phenomena investigation. This inclusion, for Tuscany, means that the maintenance of records and diaries and their fulfillment meet the needs of an official registry and becom a governmental request for tuscan prefectures. These record along relating to weather climatic issued were regularly sent to the central administration of French Empire located in Paris. In the Sommaire de la sitation Politique et Morale du Departement of Arno prefecture (the French department of Florence) is possible to find any barometric and thermometric observations, followed by monthly summaries for rainfall, average atmospheric state, prevailing winds and interesting data concerning the dates of flowering phenology of different plants. Unfortunately there is no information on the exact site of the observations, even if we assume that the observations were carried out at the Physics Museum of Florence. Similar observations of the period between 1811 and 1813 can be found on Compte Rendus for the cities of Livorno and Pisa by the Professors Branchi, Savi and Torrigiani who were all members of the Imperial Academy. At the Museum of Physics of Florence, which later became Lycée Impérial, Cosimo Del Nacca and Domenico de’Vecchi recorded regular meteorological data for several years starting in 1810 (ANNALI MUSEO FISICO, 1808). This short observative history of Museum Physics of Florence ends in 1812 when the Ximeniano Observatory actually main weather observatory of Florence - began to do regular weather observation that still continues at present.

OBSERVERS, OBSERVATIONS AND SOURCES Unlike many other meteorological historical series, like the ones done by P. Toaldo and B.Corti in other italian context, those Florence observation and reports often show a clear separation between the observer and the referenced source were the data had originally published. In this article we have examined and acquired on digital support the two longest, meteorological series, known today for Florence city logged between 1751 and 1775. These series were originally kept by Pietro Antonio Grifoni and Luca Martini. We know that Pietro Antonio Grifoni, belonged to a noble and wealthy Florentine family, he was very interested in physics. In his palace - currently named Palazzo Budini Gattai located Via de'Servi in center of Florence - he had set up a experimental cabinet of physics where the same data's editor C.A. Guadagni performed his various practical demonstrations (GUADAGNI, 1767; NOVELLE LETTERARIE, 1748). Although we have not yet identified the exact location of Grifoni’s observatiory, we know that the observation were made with the "thermometer of Reaumur […] three hours before noon” and that “the thermometer was located outdoor on the North side [of building]", while the barometric observations were made with a portable apparatus designed by Guadagni and described in his Lettera as being "divided into Parisian inch, and each inch divided into 12 lines” (GUADAGNI, 1767). The observations by Grifoni covered a period ranging dates from 1 January 1751 to 31 December 1766 and, despite ________________________________________________________________________________________________ ISBN 9788895597188

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some shortcomings, we find other important qualitative annotations like the days of frost, snow and hail. Although Grifoni’s measurements still remain limited when compared to the number of physics experiments they still remain an important source of instrumental data even though they failed to see the connection between the meteorological data and the influence of nature on mankind and agriculture.

Fig. 1. The observation carried out by Taglini in Pisa and published in 1736.

Fig. 2. Table of thermometric observations made by P. Grifoni and published in Lettera sopra una nuova struttura d’un barometro portatile ________________________________________________________________________________________________ ISBN 9788895597188

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Fig. 3. Title page and page of observations by L. Martini drawn from Alimurgia by Giovanni Targioni Tozzetti. Luca Martini graduated in Pisa in 1743, only few years before Giovanni Targioni Tozzetti. Martini was a physician at the Hospital of Santa Maria Nuova and member, and later became secretary, of the Florentine Botanical Society. He also authored several medical essays as well as recorded his meteorological observations from 1 November 1756 until 31 December 1775. His observations, ranging dates from from 1 November 1756 to 17 June 1765, and were published in Alimurgia, one of main Giovanni Targioni Tozzetti’s works (TARGIONI TOZZETTI, 1767). His observations from 1765 to 1775 can be found both in the manuscripts of G. Targioni Tozzetti (TARGIONI TOZZETTI mss.; VERGARI, 2006) and in the Raccolta di Opuscoli medico-pratici, a medical periodical edited by Luigi Targioni (TARGIONI, 1767-1778). Every day - apart from the first few weeks where observations appear more sporadic and less regular - Martini took regularly three thermometric observations with two Reaumur scaled thermometers : the first one , (an "exact mercury thermometer") used for annotations at 8 AM o'clock and1 PM , was located outside a window of his house while the second ( a "thermometer spirit of wine"), used for the 11 PM-hour readings, was held first in a lodge outside and then, from 1765, inside the house (VERGARI, 2006). Martini also added the barometric observations to his reports starting from 8 January 1765. The time of observation of the first morning reading had changed in 1765, in function to the month: for the period between May and September the first observation was read at 7 AM o'clock in the morning and 8 AM o'clock for the other months (TARGIONI, 1773-1780 ). The regular qualitative observations made by Martini are also very interesting. In addition to temperature measurement Martini also noted, in a separate column, the daily state of the sky and other noticeable weather events that took place in Florence such as thunderstorms, snowfall, etc.. In detail Martini uses the following abbreviations: S (sunny), V (Wind), C (sky covered with clouds or hazy), B (frost), D (ice or "Diaccio" in Tuscan dialect), N (Fog) P (Rain), M (Snow), G (hail) and the lines after the letter indicated if the event was of high intensity. The transcription and analysis of the data on instrumental data are cross verified throughout the analysis of the manuscripts of Targioni (in particular the MSS Targ Tozz 206 conserved at the National Central Library of Florence). This procedure lead to some corrections of errors due to printing in the Alimurgia and, also permit a preliminary check of weather events' magnitude of described in diaries of the 18th century. In the latter case, the main source used for this test was the Ephemeris of Bencivenni Giuseppe Pelli (1729-1808). ________________________________________________________________________________________________ ISBN 9788895597188

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Luca Martini 's observations by, play an even more important scientific role if we consider that they are published inside the Alimurgia by Giovanni Targioni Tozzetti, well-established as one. most important scientists of the 18th century in Tuscany. His book and his comprehensive work is targeted to study the causal framework and the ways to overcome the famine's episodes. In Alimurgia the author recounts a long and erudite chronicle of the atmospheric events in Tuscany in order to analyze the famine onsets and the related process on population occuring in Grand Duchy of Tuscany between 1764 and 1767 when prolonged and serious famine are strictly linked to many unfavorable weather events for agriculture. In 1765 the low temperatures recorded in early Spring combined with the subsequent heavy rains in early Summer have seriously damaged crops and harvests and caused severe famines. The situation did not improve in the following years because, in 1766, the cold episodes happens again and the summer appeared hot and humid . The consequence are poor harvests and the occurrence of wheat rust (a pathogen that destroyed three-quarters of the crop) lead to a disastrous situation that hit vulnerable people . The basic food resources become scarce and the prices rose causing serious repercussions on the whole Tuscan economy. The general conditions of the country become poor, with large occurence in human diseases and epidemics being these ones the most serious consequences of this long period of famine. In Giovanni Targioni Tozzetti’s work, published the same year as C. A. Guadagni’s Lettera, it is possible to find not only many operative solutions but, as already proposed in other texts, and thanks to meteorological observations, a complete framework for stakeholder is furnished illustrating the whole set of complex interactions between humans and the environment . The problem of famine was approached with a wide view that include knowledge on climate, of agriculture and medicine as far from a reductionist and limited view of process following a mere physical approach. For these reasons Alimurgia remains one of the more significant work in the history of science in the 18th century, not only for the weather reporting that are given accurately, but for the claims inside in the fifth and last part of his work where Targioni describe one of the most important scientific discoveries of the period: the identification of wheat rust disease as a parasite that posed the Florentine’s botanist as one of the founders of modern phytopathology.

Fig. 4. On the left is the first page of the first volume of the Raccolta di opuscoli medico-pratici (1773) with observations carried out by L. Martini. On the right a page from Raccolta showing the barometric observations and the weather in the morning and afternoon.

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CONCLUSIONS Florence knew in 18th century a very dynamic period for meteorological observations, as in other Italian cities. In only a few decades, several observers evolved the state-of-art of the scientific observations by using the basic methodology launched in by well-know Accademia del Cimento having the main aim to understand which are the reliable interactions between climate and good-living of peoples. During the "Enlightenment period" knowledge was considered as the way to lead to an unified view between good practices and pleasant theories, and this is well verified in the scientist's style of working as in the case of Luca Martini and Giovanni Targioni Tozzetti. Our research was conducted with rigorous historiographical methods revealing their care in meteorological data validation carried out following the scientific procedures of measurements. This kind of approach opens up many lines of research that promotes ever the multidisciplinary approach in face to any scientific problem involving society and people well-being as well. The validation of historical meteorological data, cannot be carried out in other way than the ones proposed by scientific research, but however the historical research remains fundamental to identify and analyze these ancient records and to contextualize them. The validation of historical data records can be assessed with qualitative data, using textual sources like diaries that contain extremely long and often detailed archives able to identify any additional valid that integrate the findings done by instrumental data that may have been lost overtime or are unknown.

ACKNOWLEDGMENTS We want to thanks Col. Vittorio Cantù for his precious suggestions and Karen Giacobassi for her valuable time revising the English text. Thanks also to Davide Fiorino and Accademia dei Georgofili Library for images.

REFERENCES (1771) Magazzino Toscano, VI, 1771. (1772) “Nota del peso, e misura dell'Acqua passata per la Pevera del Giardino dei Semplici di Pisa nell'anno 1771”. Magazzino Toscano. XII, 1772: 102-106. (1774) Elogj degli uomini illustri Toscani, Vol. IV, s.n., Lucca, 1774 Borchi E., Macii R. (1997). Termometri & termoscopi, Osservatorio Ximeniano, Firenze. Casati, S. (2001), Il tempo a corte : le effemeridi meteorologiche dell'Accademia del Cimento, in Scienziati a corte : l'arte della sperimentazione nell'Accademia galileiana del Cimento, 1657-1667 /a cura di Paolo Galluzzi, Livorno : Sillabe: 43-47. Borchi E., Macii, R. (2009) Meteorologia a Firenze. Nascita ed evoluzione, Pagnini, Firenze. Camuffo D., 2002, ‘Calibration and Instrumental Errors in Early Measurements of Air Temperature’. Climatic Change 53: 7-75. Cavallini G. (1762-1779) Collezione istorica di casi chirurgici metodicamente disposti e con note illustrati da Giuseppe Cavallini di Cevoli alunno nel R. Spedale di S. M. Nuova di Firenze, presso Andrea Bonducci, Firenze. ________________________________________________________________________________________________ ISBN 9788895597188

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Cocheo C, Camuffo D. (2002). Corrections of systematic errors and data homogenization in the daily temperature Padova series (1725–1998). Climatic Change 53: 77–100. Contardi S. (2002), La casa di Salomone a Firenze. L'Imperiale e Reale Museo di Fisica e Storia Naturale (1775-1801), Leo Olschki, Firenze. Diaz F. (1987). I Lorena in Toscana: la reggenza, UTET, Torino. Fierro A. (1991). Histoire de la meteorologie, Denoël, Paris. Frisinger H.H. (1977), The history of meteorology to 1800, S.H.P., S.H.P., New York. Galilei, G. (1929-1939) Le opere di Galileo Galilei, G. Barbèra, Firenze. Knowles Middleton, W. E. (1969). Invention of the meteorological instruments, The J. Hopkins press, Baltimore. Lo Vecchio G., Nanni T. (2000), Gli strumenti meteorologici a Bologna nel Settecento in Giuseppe Toaldo e il suo tempo nel bicentenario della morte: scienze e lumi tra Veneto e Europa : atti del Convegno, Padova, 10-13 novembre 1997 / a cura di Luisa Pigatto Cittadella : Bertoncello artigrafiche, stampa 2000. Magalotti L. (1667), Saggi di naturali esperienze fatte nell'Accademia del Cimento sotto la protezione del serenissimo principe Leopoldo di Toscana e descritte dal segretario di essa Accademia, per Giuseppe Cocchini , In Firenze. Palmieri S. (a cura di) (2000), Il mistero del tempo e del clima, CUEN, Napoli. Rapetti F., Vittorini S. (2003). Le osservazioni meteorologiche condotte a Camaiore (Lucca) dal canonico Pietrantonio Butori tra la seconda metà del XVIII e la prima metà del XIX secolo. Ghelardoni P. (ed.), Per ricordare Mario Pinna. Memorie Rivista Geografica Italiana 70: 149-188. Rapetti F., Ruschi M. (2009). Osservazioni botanico-meteorologiche condotte da Giovanni Lorenzo Tilli presso il Giardino dei Semplici di Pisa (1775-1780). Atti Società toscana Scienze naturali, Mem., Serie A, 114: 45-59. Rossi P. (1997). La nascita della scienza moderna in Europa, Roma, Laterza, 1997. Taglini, C. (1736), Libri duo de aere ejusque natura et effectis cum notis et animadversionibus, ex typographia Petri Cajetani Viviani, sub Signo D. Thomae Aquinatis, prope Ecclesiam S.Mariae in Campo, Florentiae Targioni Tozzetti G. (1767), Alimurgia o sia Modo di render meno gravi le carestie proposto per sollievo de' poveri ed umilmente presentato dal dottor Giovanni Targioni Tozzetti. Tomo primo, Moücke, Firenze. Targioni Tozzetti G. (mss), Le Selve… , National Library of Florence, Fondo Targioni, Targ.Tozz.189 Vergara Caffarelli R. (2000). Carlo Alfonso Guadagni: i suoi strumenti e i suoi manuali di fisica, in: Giuseppe Toaldo e il suo tempo nel bicentenario della morte: scienze e lumi tra Veneto e Europa : atti del Convegno, Padova, 10-13 novembre 1997 , a cura di Luisa Pigatto ; presentazione di Paolo Casini. Bertoncello artigrafiche. Cittadella (PD): 503519. Vergari D., (2006). Contributo alla storia meteorologica di Firenze. Le osservazioni meteorologiche fiorentine fra il 1751 e il 1813. Annali di Storia di Firenze: 1. University Press, Firenze: 99-120.

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150 YEARS OF THERMOMETRIC OBSERVATIONS IN ROME Beltrano M.C.1 and Sorrenti S.1 1

Consiglio per la ricerca e la sperimentazione in agricoltura - Unità di ricerca per la climatologia e la meteorologia applicate all’agricoltura (CRA-CMA), Rome, Italy

[email protected]

Summary We present several results about a study carried out on the historical (1862-2010) thermometric series recorded in the heart of Rome at the “Collegio Romano Observatory”, located at 56 metres above the street level, on the top of the Calandrelli tower, in the renowned Jesuit college built at the end of XVI century. Regular meteorological observations started in 1786 at and since then it has not undergone significant displacements. For this raison it is a very interesting site to study the urban climate of Rome. Over the time new instruments and technologies are adopted for measuring temperatures, however classic thermometers are still being used. We analysed the thermometric series recorded between 1862 and 2010 by liquid-inglass minimum (with alcohol) and maximum (with mercury) thermometers. The rich collection of information about history of the station, instruments, operating procedures, data processing algorithms and other factors relevant to interpreting data are analysed and used to evaluate the quality of the dataset. From raw daily data extracted from the original bulletins, we calculated and explored the annual series of the minimum and maximum temperatures, to identify the presence of break-points. Afterwards, for each subseries defined by the break-points we calculated several climatic indices, among those suggested by the ETCCDI. In the last sub-period we observe the increasing of the number of warm days and tropical nights in comparison with the first subseries; in the same subseries the number of the cold days is very decreased, even if the threshold value of the 10th percentile is higher than in the first sub-period. Our results agree with some results of other studies on urban temperatures, however we believe it needs to deepen the analysis to better distinguish the signals of the natural climate change from the impact of the urban effect.

Keywords: historical temperature series, metadata, breakpoint, urban climate, climate index.

INTRODUCTION The urbanization phenomenon, linked to overbuilding, increase of population, traffic, carbon dioxide and other pollutants emissions, can determine environmental impacts in the towns greater than those depending from the global warming (IPCC, 2001; Landsberg, 1981; Mariani et al. 2001). In studying climate and climate change in the towns, the analysis of urban meteorological time series received a great deal of attention from researchers, especially in the case of long and high quality data sets. ________________________________________________________________________________________________ ISBN 9788895597188

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In the last decades scientific community has become more aware of the fact that the climate change signals in series of original meteorological data, even more in the urban environment, generally are hidden behind non-climatic noise due to several causes: station relocation, changes in instruments and instrument screens, changes in observation times, in observers and observing routines, in algorithms, change in surrounding area, urban growth and so on. So today the statement that time series of meteorological data cannot be used for climate and climate change researches without a clear knowledge about the state of the data, in terms of homogeneity, finds a very large agreement (Aguilar et al., 2003). It is very important to understand correctly inhomogeneities; therefore, it is very important to know the history of weather station, obtaining information from metadata, to clean the data set from mistakes linked to external factors. There are different ways for solving homogeneity problems, and the choice of the most suitable one is not our goal. In this work we explored the behavior of annual maximum (TX) and minimum (TN) temperature averages, to analyze discontinuities with the help of metadata, starting from daily measures recorded between 1862 and 2010 in Rome, at the Collegio Romano Observatory (CRO). Afterwards we carried out some investigations about temperatures recorded in the150 years in the town.

MATERIAL AND METHODS Data series of high quality longer than 100 years are not very frequent, because often an historical observatory can be relocated, over the time can change exposure, position of the instruments, observing systems or new calibration corrections can be adopted. While it is important to improve measuring techniques, on the other hand, each renovation could determine variations on the measures, that appear in the series of data as inhomogeneities, abrupt discontinuities, or gradual changes. Information about the observatory, its instruments history and all other information, known as metadata —information about data—, are very important because the “history” of the observation station can explain the occurrence and the nature of the inhomogeneities. Commonly very poor, rare and inadequate metadata are available: it is a limitation to correctly analyse and interpret data sets; conversely to have a riche collection of metadata, permitting to reconstruct in the data set the ‘history’ of the station, is a guarantee of data quality. To have the headquarter of the office designated to collect, store, process and publish meteorological data recorded on the whole Italian territory in the same location of the observatory, is a coincidence which allowed us also to have a great deal of information on the history, instruments and methods of observation of the observatory and on data processing. Brief historical notes about the Collegio Romano Observatory Collegio Romano Observatory is one of the oldest Italian meteorological observatories. It, born like astronomic observatory, started regular meteorological activity in 1782 and still operates like “meteorological observatory of Rome”. Currently, it is located at the third floor of the Calandrelli tower of the college (on Southeast corner of the building); thermometers and hygrometers are placed outside the northern little terrace protected by a wood shelter, 56 m far above the street level. CRO is always located at the Collegio Romano building, in the heart of Rome, in the same site of its establishment, without noticeable variation of the surroundings and with a single important relocation of the instruments inside the same building anyway. In fact, the more important displacements was from the Calandrelli tower (“old observatory”) to the top of the Saint’Ignatius church (“new observatory”, about 40 meters direct distance Northwest from the tower, about 5 meters lower, 58 m on sea level, 41 above the street level) in 1854, 25 October. While the date of this displacement is sure, we have not certain knowledge about the date in which observatory came back at the Calandrelli tower; in reports we have examined there are not information about it. We suppose it occurred in the early twenties of the twentieth century, coinciding with merging of Collegio Romano astronomic observatory with those one of the Campidoglio in order to form Monte Mario astronomic observatory. ________________________________________________________________________________________________ ISBN 9788895597188

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In new observatory, at first, thermometers were placed on the northern balustrade, protected from solar rays by the mobile astronomic observatory dome. Since 1st February 1855 thermometers were moved in a northern terrace of the oriental wing of the church, 8 m below the balustrade (48,37 m on sea level), sheltered from the solar rays at the sunrise by a wooden shutter and at sunset to the wall of the central nave (Eredia, 1912). Various direct information about exposure and characteristics of the instruments used at the observatory between XVIIIth and the end of XIXth century are described by directors or assistants (Secchi, 1862; Ferrari, 1878). Through the time observations have been performed using ever more modern tools. Regarding thermometric observations, over the time new instruments and technologies are adopted, however classic thermometers are still being used. Before 1870, observation were usually performed four time per day at 7.00, 12.00, 15.00 and 21.00, Mean Local Time (MLT) which is Mean Solar Time (MST) related to the culmination of the sun across the local meridian (Camuffo, 2002). Daily TX and TN were deduced from those measures, even if since 1854 had started working minimum alcohol thermometer by Six Bellani and mercury maximum thermometer (interrupt column) by Negretti and Zambra (Secchi, 1862). Recordings of minimum and maximum temperatures were started in 1862 by the liquid-in-glass thermometers at that time in use (Ferrari, 1878). In 1874 directives suggested by the Agriculture and Statistics Office of the Royal Ministry for Agriculture, Industry and Commerce 8 (Cantoni, 1873), standardized meteorological observations, also in measuring air temperature: at CRO liquid-in-glass minimum (with alcohol) and maximum (with mercury) thermometers were employed and thermometric observations were performed at hours 7.00 (from April to September; at 8.00 in the other months), 9.00, 12.00, 15.00 and 21.00 MLT (Eredia, 1912). Currently observations are performed at 8.00, 14.00, 19.00, local solar hour. In the XXth century there are less information about changes in instruments at CRO, but modern thermometers had already reached a relatively high level of accuracy. At the end of the 30’s, thermographic measurements were started by a recorder instrument placed near the thermometers in the wooden shelter. Moreover, currently an automatic weather station, installed in the second half of 1999, is running close to the traditional instruments, temperature sensor is a PT100 placed in its white shelter located in the same Stevenson wood screen of traditional station. The scientific importance of the CRO derives from the length, consistency and completeness of the dataset. It has never moved from the building and thanks to its elevated position, the thermometric series represent valuable datasets to study the climate of Rome and the urban climatic changes. Dataset In this paper we examined daily measures of TX and TN recorded between 1862 and 2010 at the CRO by comparable liquid-in-glass minimum and maximum thermometers. Original daily measures are collect in original documents gathered at the CRA-CMA 9 seat: ones between 1862 to 1878 published in the Bulletins of the Collegio Romano observatory (Secchi, 1862-1878) and ones between 1879-November and 1927-March published in the ”Bollettino meteorico gionaliero” edited by the Central Office of Meteorology (UCM, 1880-1926), all preserved in the institute Library; ones since 1891 to today in handwritten forms collect in the Meteorological Archive of the CRA-CMA (Beltrano et al., 2012). Such daily data were stored in the National Agrometeorological Data Base (BDAN), the computerized archive of the CRA-CMA, where they were submitted to several automatic quality control procedures of internal, climatic and spatial consistency. However, once extracted from the BDAN, they were subjected to further tests; outliers identified were monitored in the original documents with the aim to well test minimum and maximum daily temperature series.

8

Prof. Giovanni Cantoni , first director of the Agricultural and Statistics Office (established in 1865, with headquarter in Florence) took care the standardization of meteorological observation methods (tools, schedules, rules), in accordance with international standards, discussed and accepted at the International Meteorological conference which took place in September 1873 in Wien.

9

Consiglio per la ricerca e la sperimentazione in Agricoltura – Unità di ricerca per la climatologia e la meteorologia applicate all’agricoltura. Since its establishment in 1876, with name of Central Office of Meteorology, it has its headquarter at the Collegio Romano building and manage the meteorological Observatory.

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Elaborations The first step was to elaborate the TX and TN annual average and analyse series to check discontinuities, by special statistics test. Specific advantage of discontinuities analysis is to attract attention about climatic, and non, causes, that are the origin of the climate behavior. We adopted the discontinuities analysis by flat step regression. The aim of the flat-step regression is the detection of breakpoints in a time series defining a partition in stationary climatic sub-periods described by two different mean values, in our case, of temperature. This approach permits to define the climatic normal levels before and after breakpoints, where the mean values minimize gaps. For each parameter and each year the annual average was calculated. The detection of breakpoint has been carried out by the “STRUCCHANGE” package in the R software (Zeleis et al. 2002). This model estimates discontinuities in regressive models applied to historical series (Bai, 1994) and at same time employed to individuate several change points (Bai, 1997a,b). Consider the standard regression model yi = xiT βi + ui

i = 1,….,n

where: yi is the observation of the dependent variable at time i, xi is a vector of regressors, βi is the k-dimensional vector of regression coefficient and ui is an error term. Assuming the existence of m breakpoints, that is the existence of m+1 partitions with a constant value of the regression coefficients, the optimal position of these is determined by minimizing the residual sum of m +1 squares RSS (i1 ,...., im ) = ∑ rss (i j −1 + 1, i j ) where:

j =1

1, i jresidual ) rss (i j −1is+the sum of squares of the j partition.

The optimal number of breaks can be determined by minimizing an information criterion. Bai and Perron (2003) argue that the Bayesian Information Criterion (BIC) is a suitable selection (Zeileis et al., 2002). If there are discontinuities, it need to separately analyze each sub-period. In a second time, for each sub-period in which the full series was split by break-points analysis, we elaborated several climatic indices, among those ones suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) (Klein et al., 2009), in order to investigate about possible expressions of climate change in the town. We considered: • Frost days: count of days in the years where TN < 0°C. Let TNij be the daily minimum temperature on day i in period j. Count the number of days where TNij 20°C. Let TNij be the daily minimum temperature on day i in period j. Count the number of days where TNij > 20°C. • Summer days: count of days where daily TX > 25°C and 32°C (significant for Rome geographic position). Let TXij be the daily maximum temperature on day i in period j. Count the number of days where TXij > 25°C and 32 °C. ________________________________________________________________________________________________ ISBN 9788895597188

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• Warm spell duration index: count of days in a span of at least six days where TX > 90th percentile. Let TXij be the daily maximum temperature on day i in period j and let TXin90 be the calendar day 90th percentile of daily maximum temperature calculated for a five-day window centred on each calendar day in the base period n (each sub-period in which all series has been split by break-points). Count the number of days where, in intervals of at least six consecutive days, TXij > TXin90. • Cold spell duration index: count of days in a span of at least six days where TN > 10th percentile. Let TNij be the daily minimum temperature on day i in period j and let TNin10 be the calendar day 10th percentile of daily minimum temperature calculated for a five-day window centred on each calendar day in the base period n (each sub-period in which all series has been split by break-points). Count the number of days where, in intervals of at least six consecutive days, TNij < TNin10.

RESULTS Breakpoint analysis The behavior of the annual TN average (mean value of all series 11,3 °C) shows three break points (1919, 1942 and 1986) which split series is in four sub-periods (SP), each characterised by a stationary average. Average in first and second SP is lower than the mean value of historical series. The more recent SP, starting about in 1986, increased of +1,3 °C related to the series average (Figure1). The behaviour of the annual TX average (mean value of all series 19,9 °C) (Figure 2) shows two discontinuities (1919, 1986) which split series in three SP, each characterised by a stationary average. In the first period average is lower than the mean value of the historical series. In the last SP, starting about in 1986, we observe a remarkable increase of the mean temperature (+1,0 °C).

Figure 1: Rome, CRO: Annual average of minimum temperatures (1862-2010) and break points.

Figure 2: Rome, CRO: Annual average of maximum temperatures (1862-2010) and break points. °C

°C 10.7 °C

11.1 °C

11.6 °C

12.6 °C

11.3°C

19.4 °C

19.9 °C

20.9 °C

19.9°C

1919

1942 Years

1986

1984

1919 Years

In 1919 are present discontinuities both in TN and TX: we have some doubts about them, linked to the movement of the instruments from the new to the old observatory, but until today we have not enough information about as far as this issue. TN discontinuity in 1942 is not enough analyzed. Meteorological discontinuity in the middle eightieth was described in other Italian series of temperature and precipitation (Giavante et al., 2007) and explained in several climatological studies (Werner, 2000).

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Climatic indices For each SP, we elaborated climatic indices i) frost days (Tables 1), ii) tropical nights (Tables 2). Table 1: Roma, CRO - Basic statistic about number of frost days (TN20°C ) in the sub-periods. [1862 1919]

[1920 1942]

Min

4

18

10

42

1,25

1st Qu

10

25,5

26,25

48,5

4

3

Med.

14

31

35

53

5,87

3,45

Avera ge

16,38

33,48

35,76

56,73

3rd Qu

22,75

39

45

63,25

9

Max

41

64

66

86

2,87

St Dev

8,51

10,65

13,24

12,36

8,75

[1989 2010]

5,5

[1943 1988]

[1989 2010]

The mean number of frost days is decreased from the first (9,24) to the more recent SP (3,45), of about the 60%. Also the number maximum of occurrences is greatly decreased. The variability of this kind of occurrences is reduced by half from first to last SP. The other hand, the mean number for year of tropical nights has more than tripled from the first (16,38) to the last (56.73 cases) SP. It is interesting to observe that maximum number of cases recorded during one year in the first SP is lesser (41 cases) than the minimum number of those ones recorded in one year (42) in the more recent SP. At the same time, from the first to the last the standard deviation is increased of 30%, indicating that inter-annual variability is raised. A deeper analysis was carried out about extreme temperature events, both for cold and warm periods. About cold spells analysis, for each SP we calculated the 10th percentile temperature value, the mean number of cold spell (CS) per year, the mean and maximum length of the recorded occurrences. Table 3 summarizes results. They overall exhibit that from the first SP to the last one the threshold value rises (+1,2°C) and there are about three occurrences of CS every two years, each long about seven days. Thus periods of cold nights are less cold than in the past, while there are not modifications in average and maximum length of occurrences.

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Table 3: Roma, CRO – Cold spells analysis for sub-period 10th p value °C

Nr. Runs

[1862 - 1919]

2,7

1,48

6,70

25

[1920 - 1942]

3,0

1,87

7,73

32

[1943 - 1988]

3,6

1,52

7,18

22

[1989 - 2010]

3,9

1,50

7,34

23

Subperiod

Avg length (days) Max length (days)

About warm spells analysis, for each SP we calculated the 90th percentile temperature value, the mean number of warm spell (WS) per year, the mean and maximum length of the recorded occurrences. Table 4 summarizes results. The threshold value is increased of 0,9 °C, other information in the table seem to suggest a decrease in the distribution of the WS from the first to the last SP. Table 4: Roma, CRO – Warm spells analysis for sub-period 90th p value °C

Nr. Runs

[1862 - 1919]

30,1

1,97

12,47

46

[1920 - 1984]

30,6

1,97

10,47

45

[1985 - 2010]

31,0

1,69

11,13

32

Subperiod

Avg length (days) Max length (days)

Then, we have investigated more thoroughly WS, in analysing the number of occurrences per year and lengths of each occurrence. We calculated the frequencies of WS in each SP, based on the 90th threshold (Figure 3), and the mean length of each WS per number of occurrences (Figure 4). Figure 3: Roma, CRO – Frequency of the warm spells occurrences per year and per sub-period.

Figure 4: Roma, CRO – Mean length in days of each warm spell per classes of occurrence in the year and per sub-period. Day s

%

n. occurrence of WS per year

n. occurrences of WS per year

Heat waves there was even in the past, more frequent one≈40%) ( or two times (≈33%) for year in the first SP, also three times for year (≈30%) in the second SP and sometimes four or five. In the more recent SP overall in the 80% of the years occurred heat waves (one or two or three times for years). In the same period is increased the number of years without WS, signal of increase of the variability of the phenomenon. Between 1985-2010, the mean duration of each WS (in case of one or three occurrences per year) is longer than in the other SP. It need to remember that the threshold ________________________________________________________________________________________________ ISBN 9788895597188

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value of the 90th percentile is increased of 0,9 °C from the first to the last SP: the consequence is a greater sense of discomfort for citizen. Last analysis was performed to evaluate different distribution of summer days in the three SP. We also calculated the frequency of days with temperatures higher than 25 °C (ETCCDI) and 32°C, threshold selected on the basis of the typically Mediterranean climate characteristics of Rome, considering that 30,3°C represents the maximum temperature average in July (CLINO 1961-1990). Figures 5 and 7 represent the frequency distribution of days with temperature higher than the 25 and 32°C thresholds. Figures 6 and 8 for each sub-period graphically represent the synthetic elements which describe the days number distribution related to the thresholds temperature of 25 and 32°C: median (horizontal segment in box-plot) give information about the central value of the series; first and third quartile values (bases of box, represent dispersion index) give information about the series variability; maximum and minimum values (horizontal lines external at the box) represent upper and lower adjacent values of the series.

Figure 5: Roma, CRO – Frequency of occurrences with maximum temperature >25°C, per days/year classes and sub-period.

Figure 6: Roma, CRO – Distribution of days with maximum temperature >25°C per sub-period.

Days %

1862-1919 N. days classes

Figure 7: Roma, CRO – Frequency of occurrences with maximum temperature >32°C, per days/year classes and sub-period.

i i

%

N. days classes

1920-1984 Sub-periods

1985-2010

Figure 8: Roma, CRO – Distribution of days with maximum temperature >32°C per sub-period.

Days

1862-1919

1920-1984 Sub-periods

1985-2010

Higher frequency of occurrences of days with temperatures >25° is in classes 100-110, 110-120 days in first and second SP; is in class 120-130 in the last SP. In this last one there are several years with more numerous summer days ( until 150 days). Higher frequency of occurrences related to 32°C is in classes 0-10, 10-20 in the first and second SP. In the last SP higher frequency is in classes 10-20,20-30, but there are also occurrences until 60-70 days per year. Box-plots ________________________________________________________________________________________________ ISBN 9788895597188

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concerning summer days both over 25 and 32 °C, show a general shift in high of the number of days (median, 1st and 3rd Q.le) in the more recent SP, in which the distributions are symmetric. DISCUSSION AND CONCLUSIONS Analysis of thermometric series recorded in Rome shows a general increase both of minimum and maximum temperatures, nevertheless they don’t growth uniformly along the 150-year: external factors (movement of instruments from new observatory to the old one) could explain at least the two discontinuities in TX e TN in 1919, but we have not enough certain information about as far as. About that one of the mid-eighties, it is well supported by several studies carried out in the recent years, which demonstrated there was a change in the global atmospheric circulation in that period (Werner, 2000); it caused increase of the temperatures and decrease of the precipitation on West-Europe. In Rome the minimum temperatures are mostly increased: frost night and cold spell are very fell off; tropical nights are increased and intensified. During the Summer season, minimum temperatures growth may be due to urban effect: heat cumulated during the day in the town remains steadily and cannot be easily dissipated from surfaces during the night. Mean temperature in Summer (June, July and August) in Rome is 29,0 °C. Summer temperature are frequently higher than 30,0 °C and sequences of days with temperatures >30,0°C are very common. More than six days with temperatures higher than the 90th percentile threshold value (in the last period = 31,0°C) are named “warm spells”. Between 1985 and 2010, they are more common almost each year, also two or three times for years, and each occurrence has a mean duration of 13 days. In the same time, during the nights it is not possible to recover comfort and then the warm spells become ever more severe. Finally, it should be noted that a marked increase of the variability of the occurrence of the warm spells is observed in the last 25 years. Results of our analysis about the historical series of temperatures of Rome recorded at the Collegio Romano Observatory confirm some outcomes of other studies about climate change signals in the Mediterranean area. Particularly, the Italian region are concerned, several studies carried out about temperature series covering the second half of the last century and some longer ones starting even in the 19th century (Brunetti et al., 2000; Ciccarelli et al., 2008) show that the series of annual and seasonal minimum and maximum temperatures exhibit discontinuities (Giavante S. et al., 2007) and significant positive trends during the period from 1865 to 1996, trends greater in CentralSouthern Italy than in Northern Italy; in both the sub-regions mostly depend on the behavior of data in the last few decades of the 20th century. Recent studies demonstrated in several meteorological stations of the Latium region the presence of significant signal of climate change (Malvestuto et al., 2011). It is known that the increase of temperature observed in the town is mostly due to the heat added by overall citizen context (Mariani et al., 2005). Rome, in the years after the Second World War, underwent the most significant urban growth of its story. The population grew from 1,500,000 to 2,800,000 in approximately 25 years, from 1945 to ‘71, due to the huge flux of immigration. Between 1951 and 1971 this rise consequently raised the number of houses from 320.000 to 870.000 (Fabrizi et al., 2010). Building materials retain heat, the heat coming from the production of energy (i.e.: warming buildings systems, cooling ones -air conditioners give off the warm air-) adds to the natural heat; emissions of greenhouse gases and pollutants due to the traffic have consequence not negligible on the urban climate; in particular smog operates as a cover on the town so that the ability to absorb solar radiation increases, avoids the turnover and the cooling air, modifying the atmospheric cycles and the microclimate citizen. In Rome, in the last three decades traffic is very increased and, mostly in the last years, cooling systems in houses became ever more common: this seems to have in the last two decades an urban impact on the temperatures during the Summer months, especially on the minimum ones. Results regarding the study of the 150 years of temperatures recorded at the Collegio Romano observatory need a deeper analysis, in considering that its history is not completely clear and we cannot confirm it is an homogeneous series. ________________________________________________________________________________________________ ISBN 9788895597188

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Anyway a single secular series of urban thermometric observations are interesting at local level under the point of view of the evolution of temperature in the heart of the town, but to investigate about the effects of urbanization on climate change in urban area, it need to compare the results obtained in the town centre in a wider context. Results of this work have an explorative character and need of deeper verifications by the comparison with data recorded in other stations located in the surrounding of the town. It is the further needed step to assess the climatic effects of urbanisation on temperature in a context of climate change on a larger scale (Ventura et al., 2002).

REFERENCES Aguilar, E.. Auer, I., Brunet, M., Peterson, T.C. and J. Wieringa, (2003). Guidelines on climate metadata and homogenization, WMO/TD No. 1186. Bai J., (1994). Least Squares Estimation of a Shift in Linear Processes, Journal of Time Series Analysis, 15, 453-472. Bai J., (1997a). Estimating Multiple Breaks One at a Time, Econometric Theory, 13, 315-352. Bai J., (1997b). Estimation of a Change Point in Multiple Regression Models, Review of Economics and Statistics, 79, 551-563. Bai J. and P. Perron (2003). Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 1- 22. Beltrano, M. C., Esposito, S. and L. Iafrate, (2012). The archive and library of the former Italian Central Office for Meteorology and Climatology, Adv. Sci. Res., 8, p. 59-65. Brunetti, M., Buffoni, L., Maugeri, M. and T. Nanni, (2000). Trends of minimum and maximum daily temperatures in Italy from 1865 to 1996. Theor. Appl. Climatol., 66, p. 49-60. Brunetti, M., Maugeri, M., Monti, F. and T. Nanni, (2006). Temperature and precipitation variability in Italy in the last two centuries from homogenized instrumental time series. Int. J. Climatol., 26: p. 345–381. doi: 10.1002/joc.1251. Camuffo, D., (2002). Errors in early temperature series arising from changes in style of measuring time, sampling schedule and number of observations, Climatic Change, Volume 53, Numbers 1-3, April 2002 , pp. 331-352(22). Cantoni, G., (1873). Notizie su le osservazioni meteoriche. Meteorologia Italiana , Serie I, vol. VIII, Anno 1872. Ed. 1874, p. 28-33+ 1 tab. Ciccarelli, N., Hardenberg von, J., Provenzale, A., Ronchi, C., Vargiu, A. and R. Pelosini, (2008). Climate variability in north-western Italy during the second half of the 20th century, Global Planet. Change 63, p. 185-195. Conte, M. and A. Giuffrida, (1990). L 'evoluzione a lungo termine del clima italiano, Atti del Convegno della Società geografica italiana, Roma -VOL. XLVI. Eredia, F., (1912). Il clima di Roma. Annali dell’ufficio Centrale di Meteorologia e Geodinamica Italiano, vol. XXXII, 1910, parte I- 1910, Tipografia Nazionale Bertero, Roma, 1912. Fabrizi, R., Bonafoni, S. and R. Biondi, (2010). Satellite and Ground-Based Sensors for the Urban Heat Island Analysis in the City of Rome. Remote Sens., 2, p. 1400-1415. Ferrari, G. S., (1878). Meteorologia Romana ________________________________________________________________________________________________ ISBN 9788895597188

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Giavante, S., Quaresima, S., Di Giuseppe, E., Esposito, S. and M.C. Beltrano, (2007). Discontinuità di serie storiche termopluviometriche italiane nel periodo 1961-2007. Italian Journal of Agrometeorology, Quaderno degli Abstract del 12° Convegno nazionale di Agrometeorologia- AIAM 2009, Anno 14 - N.2- giugno 2010. Klein Tank, A.M.G., Zwiers F. W. and X. Zhang, (2009). Guidelines on Analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data and Monitoring WCDMP-No. 72, WMO-TD No. 1500, 56 pp. IPCC, (2001). Third Assessment Report on Climate Change, Cambridge University Press: www.ipcc.ch/. Landsberg H.E., (1981). City Climate. In Landsberg H. E. (Ed). General Climatology, World Survey of Climatology. Elsevier, Amsterdam, Vol. 3, p. 299-334. Mariani, L. and G. Sovrano Pangallo, (2001). Effetti urbani di piccoli centri della pianura padana sulla temperatura dell’aria, Acqua & Aria, 6, p. 97-104. Mariani, L. and G. Sovrano Pangallo, (2005). Quantitative approach to the analysis of the urban effects on climate. Rivista Italiana di Agrometeorologia, (2) 2005, p. 31-36. Malvestuto, V., Beltrano, M.C., and O. Testa, (2011). The study of some daily temperature series by spectral methods. Eur. Phys. J. Plus 126:25, DOI: 10.1140/epjp/i2011-11025-9. Palmieri, S., Siani, A., and A. D'Agostino, (1994). Tendenze evolutive e fluttuazioni climatiche, AER-Marzo 1994. Secchi, A., (1862-1878). Bullettino meteorologico dell'Osservatorio del Collegio Romano. Vol. 1., n. 1 (1. mar. 1862) vol. 17., n. 12 (31 dic. 1878). Roma : Tip. delle scienze matematiche e fisiche, 1862-1878. UCM, (1880-1926). Bollettino meteorico giornaliero. Roma Ventura, F., Rossi Pisa, P. and E. Ardizzoni, (2002). Temperature and precipitation trends in Bologna (Italy) from 1952 to 1999. Atmospheric Research, 61 (3), p. 203-214. Werner, P., Gerstengarbe, F.W., Fraedrich, K. and H. Oesterle, (2000). Recent climate change in the north attlantic/European sector. Int. J. Climatol. 20: 463-471 (2000). WMO, (1966). Climatic change, Note Technique N°79 WMO- World Meteorological Organization. Geneve. Zeileis, A., Leisch, F., Hornik, K., and C. Kleiber (2002). “Strucchange: An R Package for Testing forStructural Change in Linear Regression Models.” Journal of Statistical Software, 7(2), 1–38. URL http://www.jstatsoft.org/v07/i02/.

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THE CLIMATE OF SALÒ: THE HISTORICAL PERSPECTIVE OF A LAKE OBSERVATORY IN ITALY Foffa M. 1, Iovene G.1, Nardino M. 2, Panosetti D. 2 1 2

Meteorological Obeservatory “Pio Bettoni”, Salò, Brescia, Italy IBIMET CNR Bologna, Via Gobetti 101, 40129 Bologna, Italy.

Summary The Salò historical Observatory “Pio Bettoni” collected meteorological and hydrological data since 1884. In the period 1889-2004 the seismic station of the National Institute of Geophysics and Volcanology was operational in “Pio Bettoni” observatory. The climate parameters recorded since 1884 were analyzed to perform a general characterization of a lake-city microclimate. Moreover, the specific site topography gives the possibility to highlight how a lake influences the local climate patterns. Maps, hortophotos, geographical, topographical and land use maps recorded during the years allowed to perform fundamental considerations about changes in some climatic patterns according to the land use modifications. The urbanization and, in particular, “urban sprawl”, occurred during the XX century, is well described by land use maps and a specific analysis of climate patterns of two different years (before and after changes in urbanization) was conducted in order to understand the role of urban sprawl in the formation and development of urban heat island.

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EVEN TUSCANY AND THE NEIGHBORING REGIONS WERE STRUGGLING WITH THE LITTLE ICE AGE (LIA) Iafrate L.1, Perini L.1, Casagrande G..2, MalaspinaF. 2 1

Consiglio per la Ricerca e la Sperimentazione in Agricoltura – Unità di Ricerca per la Climatologia e la Meteorologia applicate all’Agricoltura [Agricultural Research Council – Research Unit for Climatology and Meteorology applied to Agriculture] 2 Università Europea di Roma [European University of Rome]

[email protected]

Summary Italy is very rich in archival sources containing meteorological records. All of this information is of great interest for an accurate historical reconstruction of the past climate of Italy. Their rigorous historiographic and climatological analysis would allow us to study in depth the Italian climatic variations, from month to month, at least for the last millennium. This work comes from a fruitful collaboration between the Agricultural Research Council – Research Unit for Climatology and Meteorology applied to Agriculture (CRA-CMA) and the European University of Rome – Geographic Research and Application Laboratory (GREAL). It is a historical research aimed at analyzing the beginning and the central phase of the Little Ice Age (about 1550÷1850 A.D.), for Tuscany and the neighboring regions, using only qualitative weather observations. Documents used for this study are mainly preserved in ecclesiastical and municipal archives. They contain a large number of weather information. Each of them, both direct and indirect, has been analyzed on the basis of its date of entry, its author, the historic and cultural context in which it was noted and the reason which led the author to write it down (historiographic analysis). All that in order to check the good quality of the weather news just recovered. It follows that such qualitative meteorological data may be considered valid, as a whole. Three distinct sets of qualitative observations have been recovered and taken into account. The series recorded in Popiglio (a picturesque village in the Pistoia Apennines, at an altitude of 523 meters above sea level) is the first we have studied. It covers the period 1568÷1595 and is representative of the beginning of the Little Ice Age (LIA) in Tuscany. Its preliminary assessment confirms the general trend of this phase: increasingly cold winters and cool and rainy summers, sometimes even with snow and frost. The second descriptive set concerns Vallombrosa (near Florence, at almost 1000 meters above sea level), another location of the Tuscan Apennines. It consists of short notes written by the Benedictine monks of the Abbey on atmospheric phenomena they perceived as abnormal or exceptional. We have obtained them from their memories (“Ricordanze di Vallombrosa”). The time covered by the series is very short, from 1688 to 1695, but representative of the central phase of the Little Ice Age, that was the coldest period of this climatic cycle in many European regions. It is not a mere coincidence that in Vallombrosa it snowed even in summer! This research has also been extended to places of neighboring regions, such as in the Province of Ancona and Passignano sul Trasimeno (near Perugia), in order to analyze, through some local documentary sources, the other relevant aspect of the Little Ice Age: the increase in precipitation and frequency of floods. Our paper concludes with a brief review about the hard frosty winter of 1709 as far as Tuscany and adjacent regions are concerned. No anomaly/intensity index has yet been assigned to the climatic events so far recovered. Unfortunately, this work has not been completed, due to lack of funds. Therefore, our goal is to illustrate the climatic information regarded as more significant, although in an empirical way, for our climate reconstruction.

Keywords: Little Ice Age – qualitative climatic data – Popiglio (PT) – Vallombrosa (FI) – Ancona – Lake Trasimeno (PG) – first assessment – history of local climate.

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GENERAL HISTORICAL AND GEOGRAPHICAL REMARKS The study we hereby present is the result of a fruitful cooperation between the CRA-CMA and the GREAL. The former is the Consiglio per la Ricerca e la Sperimentazione in Agricoltuyra – Unità di Ricerca per la Climatologia e la Meteorologia applicate all’Agricoltura (CRA-CMA), an Italian scientific institution involved in researching on Agrometeo-climatology. The latter is the Geographic Research and Application Laboratory of Università Europea di Roma, an applied geography lab active in various fields, from environmental science to landscape archaeology. Both the historian and the geographers can draw important knowledge elements from studying the climate and its variations in time. Geography investigates the process through which humankind perceives its physical context, uses it and organizes it depending on needs, choices and priorities. In spite of the century-long defeat of ancient deterministic views, which tried to univocally explain the evolution of human presence and action in a certain environment, as if it were based only on such environmental conditions, still the latter do significantly affect natural and anthropical elements of landscape. As a matter of fact, environmental conditions and variables are the very framework within which human presence and action take place. Among various environmental factors, climate – through its complex evolutionary dynamics – plays a primary role in shaping landscape and giving it its particular connotation, that we call “geographical landscape”. In the common opinion, there is a widespread – but mistaken – belief that after the end of the last ice-age climate had remained substantially unvaried through the centuries; and that only from the beginning of the industrial revolution, humankind had increased its potential of interaction with environmental systems, in a way to modify climate. In reality, this idea does not take into account the fact that climate did change in the course of the centuries and that major climatic variations did occur at different geographical scales, mostly for natural reasons. Such variations went along with the history of human communities and societies on the planet, conditioning more or less profoundly their choices and habits. It is possible to reconstruct this process for the ages which came before the birth of writing, although such reconstruction presents scholars with several difficulties. Methods for this kind of investigations are those of paleoclimatology. As soon as we enter into a full “historical” phase, that is from the moment in which humankind was able to leave written testimonies of its life on earth, the reconstruction of the history of climate becomes more accurate and rich in details. Through the centuries, then, climate changed many times in many ways. Variations occurred as fluctuations, either regular or not. If it is true that science tends to emphasize the effects of more or less significant transformations in global climatic trends, it is also true, however, that one can be induced not to properly evaluate the implications of climate changes for individuals and communities. For a physicist of the atmosphere, a variation of 1 or 2 degrees Celsius in the seasonal temperature averages in a certain area is important because it can trigger important changes, for instance, in rainfall or in evaporation. For a geographer, the same variation can mean radical changes in entire sectors of the economy; the disappearance of traditions and social habits; deep changes in the landscapes. Let us now consider the purpose of this work of ours. It is the attempt to reconstruct the history, in some areas of central Italian peninsula, limited to the period 1550-1709, of the most important meteorological phenomena of the climatic fluctuation known as the “Little Ice Age”. Leaving alone the climate in more ancient times, we briefly mention the “Warm period of early Middle Ages”, that is the phase of relatively warm climate experienced by Europe and North America between A.D. 800 and circa A.D. 1100 (though with some exception), in order to properly compare it with the later colder period, the so called “Little Ice Age”. During the early middle age phase, the Euro-Atlantic area experienced average temperature values higher than the present ones, about circa 1 to 1.5°C, with generally milder winters, warmer and dryer summers, especially in southern Europe. There were numerous cases of drought in Italy and France during the early Middle Ages (Pinna, 1996, p. 128). A case of drought worth noting occurred in year 1088. We find an account of it in the Chronicon Placentinum: “Gran siccità”, with “disseccamento dei corsi d’acqua e delle fonti, processioni a Piacenza per ottenere la pioggia” (Nimbus, 2010, 3/4, p. 39). Modifications of landscape due to the general climate warming are well documented: migration of plant species, either wild or cultivated, towards more northern latitudes; reduction in surface of the Arctic pack, ________________________________________________________________________________________________ ISBN 9788895597188

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contraction and consequent reduction of glaciers of the Alps and other mountain ranges, due to the increased average altimetric limit of perennial snows, about 150 or 200 m. As a consequence of melting of the polar and mountain ices, the sea level increased in such a way that many coastal plains of the European continent were flooded or invaded by waters. Marshes and swamps developed behind dune cordons, also due to the loss in functionality of hydraulic systems which had operated in antiquity. It is worth underlining that the described climate warming had nevertheless a positive impact on the anthropization of several European regions. During the apex of the medieval warm phase (10th and 11th centuries), Central and Northern Europe could grow vineyards in regions where it had been impossible before, such as central British island and East Anglia. Medieval warmth allowed also for the spreading of the growth of the olive tree in the Alps, for instance in Valle d’Aosta and in Val Camonica (Mariani 2008, p. 46). Such a view of the medieval warm phase, however, is now subject for a lively debate by experts of climate history: many of them point out the scarcity of sources and documentation in support of that phase and the difficulty to turn available information into quantitative data, in order for the scientific community to evaluate them. During the 12th century, European climate turned towards a general cooling. Its origin could be associated with the colder winters of the period 1116-1133. A remarkable moment in this phase is the freezing winter 1132-1133, when “si gela il Po da Cremona fino al mare; neve immensa copre le strade; […] le quercie e le noci si squarciano, indi si seccano gli olivi e le viti” (Nimbus, 2010, 3/4, p. 32). The trend towards cooling persisted until circa 1350 and it featured a new increase in mountain glaciers. The average temperature decreased and there was an increase in precipitations, an increase in inter-annual variability and an increase in cyclonic activity, with more frequent large storms in the Atlantic and the North Sea. Very cold winters and cool and rainy summers. There was a series of bad years (particularly the decade 1310-1320), which seriously affected farming, up to the point of causing famine such as, for instance, that of 1351-1317 10, one of the real “anticipatory events” of the great plague which struck Europe between 1348 and 1349. In the first half of the 1400s, a phase for which there are not many documentary sources, cool and humid years prevailed. In the subsequent decades and until the first half of 1500s, normal and sunny years were intercalated by other irregular and rather humid ones. In the 1540s, however, the first symptoms of the cooling and worsening of climate which prepared for the freezing winter 1564-1565 and affected the entire European continent, marking the beginning of a new climatic cycle: the “Little Ice Age”. Well documented in the whole northern hemisphere, it featured a general lowering of temperature, on average 1°C less than present-day values; an evident climatic variability from one year to the other, a widespread growth of mountain and Arctic ice, up to conditions never reached again after Würm’s glaciation, a clear increase in precipitations in the temperate and sub-tropical zones of the planet. The purpose of this work of ours is an attempt to historically reconstruct the complex phenomena of the climatic fluctuation called “Little Ice Age” in some places of Central Italy, with regard to the period 1550-1709.

TOWARDS AN ATTEMPT OF RECONSTRUCTING THE CLIMATE IN TUSCANY AND NEIGHBOURING AREAS IN THE PERIOD 1550-1709 In Italy there are archive sources with meteorological information of major interest for a reconstruction of the history of climate. A rigorous historiographic analysis of them would allow for a reconstruction of climatic variations down to a month-to-month basis, if not to a day-to-day basis, for at least the last millennium. The history of climate in a certain location, to be intended as a study of “past climate” based on the documentary sources, such as information contained in the parishes’ archives, in the dioceses’ and in the townships’ archives, consists in somehow “digging” in human everyday life, looking for even the minimal details, in order to acquire all the possible cause-effect relationships which might turn useful for a reconstruction of continuous fluctuations of the very climatic system 11. This can be achieved by 10

In those times, farming had much lower productivity than present-day one. There was also no way to compensate for a famine at continental scale, since an efficient storage and transportation system was not available. Furthermore, Europe was then struggling through wars and many kinds of tensions. The result was a general crisis: the price of wheat peaked and the result was a terrible increase in mortality among the lower class throughout Europe.

11

It is clear that the study of climatic evolution, conceived in this way is, stricto sensu, within the interdisciplinary domain of historic climatology.

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following the example of the tradition of the renewed historiographic school-of-thought born in France around the magazine Annales d’histoire économique et sociale 12. It was one among the most important groups of French historians in the 20th century, and it is well-known for having introduced important methodological innovations in traditional historiography. Among its most important members were historians Fernand Braudel ed Emmanuel Le Roy Ladurie. The historiographic school, risen around the Annales, revolutionized the historical method: it turned the main focus of investigation from the great battles, institutions and characters to the small details of everyday life and to local history. The new approach involved subjects beyond the traditional scope of history, such as geography, anthropology, economy and sociology. The climatic history of a place, then, if reconstructed according to the aforementioned approach, could allow for a better understanding of general history, since the latter is inextricably connected to the former. This will be the case for the study of famines, epidemics and deaths in the Middle Ages and in the early centuries of modernity, down to the French Revolution and to the later defeats suffered by Napoleon in Russia. In the Anglo-Saxon countries, the use of archive data in the reconstruction of climatic variations from the Late Middle Ages on, is a well-established tradition. Such does not seem to be the case in countries of Latin culture, even though the latter do have a considerable patrimony of documentation, both in terms of quantity and in terms of quality. Let us now turn back to the main purpose of this study. First of all, it is our intention to show how the inhabitants of a community on the Appennino Pistoiese, Popiglio, perceived the severe meteorological phenomena associated with the beginning of the “Little Ice Age”. We can do that by going through the “impressions” that can be found in the unpublished “memoirs” of Girolamo Magni, priest of Popiglio, which appear to have particular significance. In the second place, we will analyze some meteorological information, concerning abnormal or exceptional phenomena, as recorded by the Benedictine monks of the Vallombrosa Abbey in their “Ricordanze”, through the last two decades of the 17th century, right in the peak of this “mini-glaciations”. In the third place, our purpose is to provide information about the climate, equally “extracted” from archive documentation, also for some locations of neighboring regions, such as Falconara Marittima and Jesi, for the Marche, and Passignano sul Trasimeno, for Umbria. They are very useful, in a spatial and temporal comparative view, to demonstrate – although indirectly – the significant increase in cloud coverage and precipitation, especially in the spring and summer months, and the consequent higher frequency of floods. The latter often had catastrophic effects during the Little Ice Age: the other fundamental aspect of climate in Europe in that phase, besides freezing cold. A brief historic review, for Tuscany and the other central and northern regions, with regard to the most intense and disastrous consequences of the terrible winter 1709 concludes this work of ours. The archive sources, either published or unpublished, examined by us, offer plenty of meteorological information which, although heterogeneous, seem to be generally reliable. This results from a rigorous historiographic analysis of the same sources and of the meteo-climatic information they contain. Every meteo-climatologic reference was interpreted in light of its particular historic and cultural context. Much attention was paid to define a correct “datation” for the document, to its author and his historical, social and cultural environment; to the motivations which brought to writing the document and to the addressees of the document. The analyzed climatologic information in this research is both direct, and indirect. In the first case, it is expressly referring to climatic events that the author perceived as catastrophic or unusual. In the second case, it is extracted from bureaucratic and administrative documents, especially describing damage, particularly to farming activities, caused by severe meteorological phenomena. However, no anomaly/intensity index was assigned to the identified meteorological and climatic events, in this initial stage of our study.

The Alto Pistoiese at the beginning of the Little Ice Age. The testimonies of the Popiglio parish-priest Popiglio, a hamlet in the township of Piteglio, is a village on the Appennino Pistoiese, at 523 meters above sea level, along the state road to the Abetone and Brennero (SS.12) A handwritten diary by a parish-priest of the Santa Maria Assunta church, Girolamo Magni, who lived in the 16th century, summarizes, with both direct and indirect reference in the form of various annotations, the history of climate in this small Tuscany’s village, with special regard to the last three decades of 1500s, that is the early phase of the Little Created in 1929 by Marc Bloch and Lucien Febvre, the magazine exists today. Since 1994 it is published with the title Annales. Histoire. Sciences sociales

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Ice Age. The original diary is jealously preserved in the Diocesan Archive of Pistoia, due to its authoritative value as a source for local history. The text was recently published and we have used the published version after having verified its adherence to the original. Figure 1: A diary page by Girolamo Magni.

The climatologic information which follows is specifically related to the climatic events that the author perceived as anomalous or exceptional for Popiglio. News is in original language and translated in a footnote. -

“Questo medesimo anno [1568] di gennaio, il giorno de la Conversion di San Pavolo, ch’è a i 25 di gennaio, […] non essendo ancora stato verno, si levò una fiera burrasca di vento e nieve, da la quale due donne buonissime da Popiglio … moriron di freddo […]”. Quest’anno [1568], da mezzo gennaio […] sino a questo presente giorno, che siamo a gli 8 di giugno 1568, non s’è ancor veduto segno di state, essendo stato un pioviosissimo e freddissimo tempo […] Così il freddo, che noi aspettavamo di novembre, dicembre e gennaio passati, c’è stato reso ora di maggio ed giugno. Dio cela mandi buona”.

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“È stato notabile questo anno 74 [1574]: da febbraio a luglio il spesso spirare de’ venti aquiloni, quali han recato freddi intensi … cagionato freddure quasi continue, tosse e punte mortifere talmente che in cinque o sei dì ha ammazzato molti […]. E questi primi cinque giorni di luglio, essendosi riscoperti, han recato freddo grande e nieve, onde la gente è di nuovo infreddata, ed […] l’aria sì maligna, che, nasca la canicola a posta sua, farà poco caldo”.

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“Fu notabile questo anno 76 [1576] in montagna di Pistoia … per freddi stati di maggio e tutta state, quando […] le castagne inanimavano e, per certe brenate state d’agosto con gran freddo e venti freddi, le foglie de gli castagni ingiallorno e la ricolta diede di sé pessima mostra e aspettatione […]”.

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“Questo mese di maggio 77 [1577] fu notabile per piogge quasi continue, nieve e tempo freddo, con pericolo manifesto de la futura ricolta a i piani del grano, a noi de le castagne: né meno si teme de la peste”.

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“Fu notabile questo anno 1579 che a dì 18 di aprile […] venne un mal nodo di tempo, tirando venti freddi e nevicando in montagna, con gran pericolo del vino e de’ castagni e la primavera fu molto ventosa e tutto maggio andò ventoso e freddo: anzi pure tutto giugno, e in sul solstizio, cioè a mezzo giugno, si diroppe il tempo in acqua e saltorno in campo venti occidentali da piogge e freddo, tutto giugno andò male, onde i gran maggiori reser poco frutto”.

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“Fu notabile quest’anno 1580 il gran caldo e secco, che tutta la state fu, in cui una o due volte piovve e di agosto erano i caldi sì fervidi ed eccessivi che non si potevano sopportare […] seguì una infermità generalissima […] appellata mal montone o castrone o pecorone […]”.

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“Il verno questo anno ha durato da ottobre dell’86 [1586] sin a San Giovanni Battista, cioè a 24 di giugno 87 [1587], sicché la ricolta è molto serotina e la gente per tutto ha patito e patisce gran carestia di grano […]”.

-

“Questo anno 1591 fu carestia per tutta Italia, e ‘l grano in Toscana valse otto lire e più e la farina sei […]”.

-

“Gran disagio e freddo […] a dì 22 di aprile [1595], giorno del sabbato, che tuttavia nevicava et era tempo molto freddo […]” 13 .

At a first climatologic analysis of the most important reported anomalies, it is evident that right in the aftermath of the terrifying freezing wave that hit Europe in winter 1564-65, long cold winters were followed by cool and rather rainy summers at Popiglio and, more in general, in the rest of the Alto Pistoiese. Cold and abundant rain of the long winter 1567-68, late snows and frosts, respectively in July 1574 and in August 1576, the great cold of interminable winter 1586-87: these are the most severe climatic events in Popiglio. Their persistent and exceptional (on a longer time-scale) nature rings a bell in the mind of historic climatology investigators. An exception seems to be the summer of 1580, featuring an unbearable heat and an evident drought. In light of this preliminary evaluation of the Popiglio “series”, it is possible to conclude that the trend of the identified climatic evidence confirms the general, incipient tendency to cooling, appropriate to the early phase of the Little Ice Age, especially as far as its most relevant aspect is concerned: a decrease in temperature and an increase in rainfall also in the warm semester (April- September) 14. The famine which struck Italy in 1591, as it can be read in the text, is in our opinion the inevitable consequence of the poor cereal harvest especially connected to this aspect 15.

The highlight of the "mini ice age" in the account of Vallombrosa Benedictine monks.

13

“This year [1568], in January, on the day of Saint Paul’s conversion, which is on January 25th, without any previous anticipation of winter, there was a strong wind storm with snow, and two very good women from Popiglio died because of the cold”. “This year [1568],beginning from half January until this present day, which is June 8th 1568, there was no sign of summer, since weather was extremely rainy and cold. So cold winter, which we would have expected in November, December and January, we now had in May and June. God bless us”. “It was remarkable, this year 74 [1574]: from February to July the frequent blow of northern winds brought about intense cold, caused almost continuous illnesses, coughs and mortality in a way that in five or six days many people died […] And these first five days of July, occurring again these phenomena, many people are sick again and the air is so bad that summer might not even come”. “It was remarkable this year 1576 in the mountains of Pistoia, due to cold weather in May and throughout the summer, when the chestnuts were growing, and due to some freezing conditions in august with much cold and winds, the leaves of the chestnuts trees became yellow and the chestnuts harvest was extremely poor”. “This May 1577 was remarkable for almost continuous rains, snow and cold weather, with evident danger for the future harvest, of wheat in the plains and of chestnuts for us. Furthermore, there is fear of plague”. “This year 1579 was remarkable because on April 18th there was such a bad weather, with cold winds and snow on the mountains, with great danger for vineyards and chestnuts trees; spring was very windy and all May was windy and cold; June was cold too, and at about the solstice, in mid June, the weather broke into rains and westerly rainy and cold winds came up; all of June was bad, and wheat had a poor harvest”. “This year 1580 was remarkable because of much heat and drought, enduring throughout the summer, in which rain fell only once or twice. In August heat was so high and excessive that it was unbearable. There was a widespread illness, called mutton or sheep illness”. “Winter in this year 1586 endured from October to the feast of Saint John the Baptist, that is June 24th 1587, so that harvest was extremely poor and people did suffer and still suffer great famine”. “This year 1591 there was a famine in all Italy and wheat in Tuscany cost eight lire and more, flour six”. “Great distress and cold on April 22nd 1595, on a Saturday, in which there was snowfall and it was very cold”. 14 The high frequency of cool and humid summers, often rainy and sometimes even snowy (at medium altitudes) is a distinctive character of the Little Ice Age. 15

The increase in the wheat price ascertained for this historical phase is in this case an indirect climatic information of great importance.

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Vallombrosa is a wonderful mountain place in the Province of Florence, in the township of Reggello. It is at about 1000 meters above sea level, on the slopes of Monte Secchieta (Mountain Secchieta, 1.449 m a.s.l.) in the range of Pratomagno, a group of reliefs which appears as a foothill of the Appennino Tosco Emiliano. That is the site of a famous Abbey held by the Benedictine congregation of Vallombrosani (Congregatio Vallis Umbrosae Ordinis S. Benedicti), founded in the 11th century by San Giovanni Gualberto. Meteorology owes much to these monks, since they conducted sistematic meteo-climatic observations, both instrumental and descriptive, since 1656 to 1670 as part of the meteorologic network instituted by the Grand-Duke of Tuscany, Ferdinando II de’Medici, in 1654. The network was created to compare the climate of different geographic sites, and it can therefore be considered as the earliest Meteorological Service in the World: the first attempt made in the modern age to systematically collect meteorological data from national and international sites. They were Florence, Pisa, Vallombrosa, Cutigliano (Pistoia), Bologna, Parma, Milano, Paris, Innsbruck, Osnabrück and Warsaw. The main meteorological variable to be measured was air temperature. Measures were taken, in the shade and in the sun, through perfectly identical alcohol thermometers ruled according to a fifty-degrees scale: the so called “Piccoli termometri fiorentini” [“Little Florentine Thermometers”]. Readings were taken according to surprisingly uniform procedures. In all stations of the network, registration of temperature and other visual observations were conducted several times a day (on average 5 to 8 times). What is more important from the standpoint of synoptic meteorology, all measures were taken at the same hours. Let us now consider the climate at Vallombrosa in the peak of the Little Ice Age. Temperature measures recorded there by the monks of the Abbey, along with other more generic, descriptive meteorological observations (generally the state of the sky, direction of the wind, frequency of precipitations), are significant scientific assets for the studies of historic climatology. What we read through those ancient measures and descriptive annotations is the central phase, the coldest one (“pessimum”) of the Little Ice Age. The Vallombrosa Abbey, as the site of one among the most important nodes in the Medicean observation network, keeps, on the basis of our knowledge, 10 years of systematic thermometric measures, integrated with rather detailed observations on the state of the sky: 1656, 1657, 1660, 1661, 1662, 1664, 1665, 1666, 1667, and 1670 for the months of March, April and May. This information is collected in 9 volumes. Measures and observations are presently preserved at the Biblioteca Nazionale Centrale di Firenze (mss. gal. 296-304). Observers in this ancient station were, as previously mentioned, the Benedictines of the Abbey. Father Niccolò Signorini and Father Filiberto Casini, from January 1st to July 20th 1656; Father Petronio Paceschi, from July 21st 1656 to May 31st 1670. It is possible that Paceschi continued measurements of temperature and the observations on the state of the sky, wind direction and precipitations, for seven years more, that is to say until the time of its appointment as Abbot of Chiusdino. His personal interest for the subject appears evident from his annotations (this is a hypothesis) 16. Based on current data on the subject, we can assert that the Vallombrosa meteorological series appears to be very accurate and it is the second most continuous and complete after the one recorded in Florence. All data of temperature from the Medicean network were recently recovered, analyzed and appropriately processed, for the purposes of Historical Climatology, by two distinguished scholars of the Istituto di Scienze dell’Atmosfera e del Clima (ISAC) of Italian National Council for Research (CNR), Dario Camuffo and Chiara Bertolin. It is a scientific work with no precedents, presented in the publication: “The earliest temperature observations in the world: the Medici Network (1654–1670)”, March 2012, issue of the International magazine “Climatic Change” (vol. 111, n. 2, pp. 335363). In the paragraph dedicated to results and discussion, the authors, based on a rigorous climatologic analysis, conclude that, at Vallombrosa, in the 15 year period between 1656 – 1670, climate was generally colder in comparison to present-day conditions (reference period 1961-1990), especially in summer and in winter. Examining the different descriptions of anomalies as reported on the Vallombrosa meteorological sheets, some appeared to be particularly representative of the initial phase of that further climatic worsening that, in brief time, would have led to the peak of the Little Ice Age. Among them, we quote some:

16 With regard to the missing data in the series (December 1654, years 1655, 1658, 1659, 1663, 1668, 1669, January and February 1670, and maybe from June 1670 to year 1677) we have not given up, yet, the hope to find them.

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•

October 3rd, 1657: «Tuoni, saette, pioggia, vento grande, sradicamento di alberi, tetti scoperchiati» [“Lightnings, rain, strong wind, uprooted trees, roofs come off”];

•

July 17th, 1660: max temperature 32 °G (about 28 °C), «caldo eccessivo, pesci morti» [“excessive heat, dead fish”];

•

December 29th, 1662, at about 8 (“Italic hour”, approximately 1 o’clock of the night): 5 °G (around -12,5 °C), «diaccio, sereno» [“ice, clear sky”];

•

September 22nd, 1664, during the night between September 21st and 22nd: «vario, neve» [“various, snow”];

•

May 5th, 1667: «nella notte del 4-5 venne una neve grossissima come se fosse stato di mezzo inverno, e la mattina del dì 5 si trovarono diacciuoli a tetti, ed il terreno diacciato dove era la neve. Li vecchi si ricordano che una simil neve venne anco nel 1655 alli 20 di maggio» [“during the night between May 4th and 5th, there came a very thick snow, as if it were mid winter, and in the morning of 5th there was ice from the roofs, and terrain was frozen where the snow was. Elderly people remember that a similar snow came also in 1655, on May 20th”].

Figure 2: Image of the original Meteorological Bulletin of May 5th, 1667, compiled by the Benedictine monks of the Abbey of Vallombrosa.

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In accordance with the Righini Bonelli conversion scale, reproduced below, 32 °G (degrees Galileo or Accademia) correspond to 28 °C circa, 5 °G to about -12,5 °C. Figure 3: The Righini Bonelli conversion scale.

Annotations we just read are self-commenting. Cold and snow in late spring and in the early autumn were typical. However, there were still very hot summers, such as, for instance, that of 1660. In that case, due to the excessive heat, all fish in the pool located in front of the Abbey died. Equally important, for the climatic reconstruction of the central phase of this mini-ice age, are the meteorological “oddities” which the Benedictines reported in the pages of the “Ricordanze di Vallombrosa” (Memoires of Vallombrosa). In this case, meteorological annotations are only of descriptive nature, scattered in the thick manuscript volumes which collect the memoires 17. All of these were subsequent of the closure of the Medicean meteorological network. They are in original language and translated in a footnote. Let us view some:

17

•

9 giugno 1688: «E’ cosa memorabile il registrare che, da tre giorni antecedenti al detto, si è sentito e provato un freddo come d’inverno, e finalmente nel dì ora detto è nevicato su questi monti, […] Qui […] si sono visti fiocchi di neve, ma toccata terra si liquefecero.»;

•

9,10,11 maggio 1692: «Nevicò in questi tre giorni a Vallombrosa talmente, che alzò la neve molto braccio, con stupore universale, non trovandosi chi si ricordasse di tal nevicata in detto tempo […]»;

Most of this collection is preserved at the Archivio di Stato in Florence.

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•

16 agosto 1692: Accadde in questo giorno cosa molto insolita et straordinaria, che nevicò ai monti e particolarmente sopra quello di Secchieta alzando la neve quasi a scarpa, e ne arrivò ancora, benché poca e rada, a Vallombrosa, […]»;

•

30 gennaio 1695: « Nevi altissime e diacci terribili, essendo le strade impraticabili […]. Per esser in questo medesimo tempo alzate le nevi straordinariamente, che non vi è memoria […], si spalarono i tetti di Vallombrosa sui quali era sopra due braccia, temendosi certamente rovine. Vi si consumarono più giorni, […] essendo seguita la spalatura sino a quattro o cinque volte, per le nevi che sempre più abbondanti cadevano […]»;

•

22 agosto 1695: «La mattina di questo giorno veniva la neve nella montagna di Secchieta» 18.

Figure 4: Excerpt of Ricordanze di Vallombrosa where we read that on August 22nd, 1695, it snowed on the mountain Secchieta.

18

“June 9th, 1688: it is a memorable thing that since three days before that one, a winter-like cold was felt; and finally on the aforementioned day there came snow on these mountains, […] Here […] snowflakes were seen, but as soon as they touched the ground, they melted”. “May 9th, 10th, 11th, 1692: in these three days snow fell on Vallombrosa in such a way, that a thick layer of snow formed, with general awe, since no one could remember a similar snow fall in those times”. “August 16th, 1692: in this day a strange and extraordinary thing happened: there was snow on the mountains and particularly on the one of Secchieta. A snow layer formed, almost as thick as a shoe, and other snow fell, although just a little and not thick, on Vallombrosa”. “January 30th, 1695: very thick snows and terrible ice, the roads became unusable […]. Since in this same time the snows accumulated extraordinarily, in a way that can’t be remembered […], roofs in Vallombrosa, if snow exceeded two arms of thickness, were swept, due to the fear they might collapse. That took several days, […], as that sweeping had to be repeated up to four or five times, because abundant snow kept on falling”. “August 22nd, 1695: this day, in the morning, snow fell on the mountain of Secchieta”.

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The increasing frequency with which the monks, from 1688 to 1695, included meteorological remarks referring to anomalous situations in their Ricordanze, lead us into thinking that, as it happened in other regions of Europe, the Appennino Tosco Emiliano had fallen into the worst phase of the climatic period. If Vallombrosa saw snow and ice in late spring and early autumn in the 15 year period between 1654-1670, towards the end of the 17th century snow would also fall in midsummer! By the way, two snowfalls in mid August occurred over just a three year period (1692-1695), whitening the Monte Secchieta and Vallombrosa itself 19. In light of what is reported by the historical sources, the last decade of 1600s was very cold in all seasons, throughout Europe. There were two consecutive freezing winters in 1693-94 and 1694-95, when Lake Constance froze so thickly that wagons could cross it. During that decade, wheat seldom reached complete maturity. A large percentage of European population suffered from serious famines and, by consequence, mortality became extremely high. Through this phase of “climatic pessimum”, while the Appennini, although capped with snow even in summer, did not show any particular form of glaciations, the entire Alpine region knew one of the most wide (if not the widest) expansion of its glaciers (in “history” times), due to the lower temperatures in spring and summer.

The Little Ice Age in the sources of neighboring areas: the Province of Ancona and the Trasimeno Lake At this point, our attention moves to the other fundamental climatic aspect of the little ice age. The increase in rainfall and the consequently increased frequency of floods. We can see that by underlining accounts of catastrophic floods and inundations, sometimes written by direct witnesses. They relate to the Province of Ancona and Lake Trasimeno (Perugia). Let us begin with the first area: - 1577: floods wreck the mills at Fiumesino, the tavern and the ferry 20; -

1608: [in Fiumesino] the river overflowed near the recently built bridge and damaged the riverbanks 21;

-

1636: the water covered the whole valley from Jesi to the Adriatic “on both sides of the river down to the sea, and in such a way that it seemed that the sea itself had entered the land” 22. The inhabitants in Castelferretti could barely escape by climbing onto the roofs of the houses 23;

-

1694-1718: frequent floods damaged seriously the mill in the valley of Ancona 24.

Now it is the turn of Lake Trasimeno, a natural lake whose hydrology was always strongly dependent on the precipitation trends. Throughout history, in fact, the lake suffered periodical phenomena of swamping in dry times and overflows in highly rainy periods. Let us consider one of the historical inundations occurred. In year 1602 the overflow was so huge that it was necessary to update local maps in order to take into account the new “borders”. The emissary lake was occluded, but besides that the reason is certainly to be related to heavy rains. In Passignano the waters of the lake inundated a wide area of the town, as it can be noticed in a “level-line” indicated on a stone. It shows the top level

19

Some authors maintain that the Benedictines could have mistakenly called “snow” what was actually hail. To these we should respond that the difference between the two phenomena was well-known, among the cultured people, since the time of Dante: “Grandine grossa, acqua tinta e neve per l’aere tenebroso si riversa]” [Large hail, colored water and snow throughout the air pours dark] (Inferno, Canto VI). 20 21

Archivio Comunale di Ancona [presso l’Archivio di Stato di Ancona], Consigli, vol. 59, 16 novembre 1577, c. 9v. Archivio Comunale di Ancona [presso l’Archivio di Stato di Ancona], Consigli, vol. 59, 16 novembre 1577, c. 9v.

22

The original language quote is as follows: «di qua et di là dal fiume sino al mare, et in tal modo, che pareva vi fusse entrata una lingua del detto mare».

23

Cfr. R. Domenichini, Rilevamenti demografici inerenti alle città di Ancona e di Macerata. Secolo XVII, in “Atti e Memorie della Deputazione di Storia Patria per le Marche”, n. 96 (1991), pp. 399-400. 24

Cfr. G. Campana e G. Piccinini, Il Mulino di Ancona a Fiumesino, in Autori vari, Falconara: Storie e immagini, Falconara M., 1989, p. 71.

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reached in the middle of the historical town (at Via Nazionale). It is worth noting that present-day level of Lake Trasimeno is about 4 meters lower than the maximum level of 1602 25. The serious consequences that the aforementioned events had on the social and economical systems of the areas (damage to farming activities and serious famines), and the inevitable transformations of the rural landscapes, along with the analogy with floods occurred in Tuscany, are the reasons for which we included this paragraph in our work.

DEALING WITH THE FREEZING WINTER OF 1709 : ACCOUNTS FROM TUSCANY AND BORDERING AREAS At the beginning of XVIII century, in Europe, as can be pointed out by collected accounts, climate appeared to be very different from how we see it today. Its “engine”, the sun, behaved unusually: The 11 year cycle of its activity, in this period, was irregular or even absent. Its typical “spots” were not often seen. Winters were harsh and freezing phases jeopardized the survival of even some tree species, such as the Olive tree. Summers were sometimes very bad, with frequent storms or even floods, which were a serious threat for harvests. The inhabitants of Europe, in those times, were used to weather oddities, unlike their posterity in present-day times. However, in the first decade of the 1700s there was such a terrible freezing phase that it was considered to be exceptional even in that time. The winter 1708/1709, also known as “The Great Frost” o “Le Grand Hiver”, was possibly the coldest of the last 500 years, although the little ice age had at least 10 winters of extreme harshness. In the night of the Epiphany, between January 5th and 6th 1709, cold air from Siberia invaded Europe, striking Central and Mediterranean Europe with particular intensity. Almost no area of the Old Continent was spared. That night, temperatures went down suddenly, decreasing for even 20 °C. It was so cold that, in a few hours, fountains, pits and streams froze. In two or three days, many large European rivers froze in such a way that they could be crossed by entire armies. The same thing happened to many lakes, lagoons and coastal areas. Tuscany was also besieged by General Winter, especially during that January. The Arno froze, developing a thick layer of ice which endured for many days. Even the port of Livorno, although only for a limited time and in its innermost locations, suffered freezing of its waters, as the British ambassador in Florence reported in a letter to theologian and scientist of nature William Derham (1657-1735). Abundant snow fell on the entire region. In Florence, the snow layer was up to 60 centimeters thick. Due to that exceptional cold phase, serious damage to crops was suffered in Tuscany. Not even the species which were most resistant to cold weather (apple trees, cherry trees etc.) were able to survive in some areas. Therefore, it can be concluded that in the innermost areas, minimum temperatures might have been around 30 °C. The meteorological situation was similar in the neighboring regions, especially with regard to the coldest phase of winter, which terminated around the end of January. In Rome, for instance, during that only one month, snow fell 10 times (between January 7th and 24th); for a comparison, it should be noted that there were 6 snow precipitations in January 1893 and in February 1956. Meanwhile, in Bologna, on January 14th 1709, “it was so cold, with thick snow, bread and wine froze. On January 22nd cold increased remarkably” 26. Even in a mild-climate city as Genoa, that winter was harsh. Its port, in January, froze in its innermost sites. And speaking about Genoa, it is worth noting that, in that year, it is probably the only Italian city that keeps to this day air temperature recordings, accurately associated with the indication of rainy, snowy, icy days and with the wind direction. The observer was Marquis Paris Maria Salvago, in his observatory at Carbonara, at about 96 meters above sea level. All instruments were located in a room with closed windows, while observations were conducted at non specified hours.

A quite different situation occurred in 1639. Due to a prolonged drought, the level of the lake decreased in such a way, that it th could not reach the emissary built in the 15 century. See: Luigi Iafrate, Fede e Scienza: un incontro proficuo. Origini e sviluppo della meteorologia fino agli inizi del ‘900, Roma, Ateneo Pontificio Regina Apostolorum, 2008, (Scienza e Fede – Saggi, 4), p. 64-66. 26 Cfr. D.M. Galeati, Diario o sia notizie varie di Bologna dall’anno 1660 all’anno 1713, Biblioteca comunale dell’Archiginnasio di 25

Bologna, ms B 83. The original language quote is: «un gran freddo con neve grossissima, gelava il pane, e vino all’eccesso, e

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Besides temperature, atmospheric pressure was also measured. The thermometer was of amontonian type and the temperatures were indicated in Paris inches and lines. The observations by Salvago were recorded in the period 17051724. By examining the temperature variations at Genoa between January 1st and March 2nd 1709, it becomes evident that the lowest value (detected at the beginning of the last ten days of January), once it is converted into Celsius degrees, is very close to 0 °C. It is very low for a city like Genoa, considering that such a measure was taken inside a closed room! The cold and stormy spring which followed that freezing winter, throughout Europe, seriously aggravated the wellknown disastrous consequences of the latter. Therefore, Tuscany had to face one of the worst famines of the 18th century, which triggered a demographic crisis. Unfortunately, not even summer showed positive trends in its beginning. According to the writings of that time, there were late freezing conditions, until about mid-June. For instance, those which covered the countryside around Forlì in the mornings from June 10th to 14th27.

CONCLUSIONS This research is still developing.

ACKNOWLEDGEMENTS We are deeply grateful to Professor Dario Camuffo and Professor Daniele Salmelli for their useful suggestions, to Professor Antonio Krase for the work of reviewing draft. All Authors contributed equally to this paper, according to their specific expertise: Luigi Iafrate to Historical Climatology, Luigi Perini to Agroclimatology, Gianluca Casagrande to Geography and Fabio Malaspina to Meteorology.

REFERENCES Antinori, V. (1858). Archivio Meteorologico Centrale Italiano. Firenze. Camuffo, D. (1990). Clima e uomo. Meteorologia e cultura: dai “fulmini” di Giove alle previsioni via satellite. [Milano]: Garzanti. Borchi, E. and Macii, R. (1997), Termometri & termoscopi. Firenze: CT. Cantù V, (1985). Alla ricerca di documenti sul clima passato. Accademie e Biblioteche d’Italia 53: 103-110. Cantù, V. (1983). Ferdinando II de’ Medici creatore della meteorologia moderna. Atti della Fondazione Giorgio Ronchi 38: 661-675. Cantù, V. (2004). Meteorologia. Climatologia. Cambiamenti di clima. Storia della meteorologia nel sec. XX in tre saggi. In Quaderni di geofisica 37. Roma: Istituto Nazionale di Geofisica e Vulcanologia. Chaboud, R. (1993). La météo. Questions de temps. Paris: Nathan. Hellmann, G. (1891). Sulle origini delle osservazioni e degl’istrumenti meteorologici. Rivista Marittima: 99-116.

Several climatic information reported in this section were drawn from Daniele Salmelli’s essay: L’alluvione e il freddo: il 1705 e il 1709, published in Le meteore e il frumento: Clima, agricoltura, meteorologia a Bologna nel ‘700 (a cura di Roberto Finzi), Bologna, Società editrice il Mulino, 1986.

27

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Lamb, H. H. (1978). Climate: present, past and future. London: Methuen. Le Roy Ladurie, E. (1982). Tempo di festa, tempo di carestia. Storia del clima dall’anno mille. Torino: Einaudi. Magni, G. (1999), Il diario del pievano Girolamo Magni. Vita, devozione e arte sulla montagna pistoiese nel Cinquecento, Ospedaletto, PI: Pacini. «Nimbus» (2010). A. XVIII, n. 3-4. Bussoleno, TO: Società Meteorologica Italiana. Pinna, M. (1984). La storia del clima. Variazioni climatiche e rapporto clima-uomo in età postglaciale. Roma: Società Geografica italiana. Pinna, M. (1996). Le variazioni del clima. Dall'ultima grande glaciazione alle prospettive per il XXI secolo. Milano: F. Angeli. Targioni Tozzetti, G. (1767). Alimurgia o sia Modo di render meno gravi le carestie ... Firenze: Moücke. Vernelli, C. (1999). Belvedere Ostrense. Istituzioni, economia e società dal Medioevo all'età contemporanea, Belvedere Ostrense: Comune. Vernelli, C. (2003). Fiumesino. Storia di un borgo adriatico. Falconara Marittima: Comune di Falconara Marittima.

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THE METEOROLOGICAL OBSERVATORY “PIETRO MONTE” AND ITS HISTORICAL, SCIENTIFIC AND DIDACTIC IMPORTANCE Massetti L.1, Pellegrino L.1, Raschi A.1 and Rossini G.1 1

Institute of Biometeorology, National Research Council, Florence, Italy

[email protected]

Summary The aim of this work is to present the cultural heritage and importance of the “Pietro Monte” meterological observatory. In 1856, the Barnabite Father Pietro Monte (1823-1888) founded a meteorological observatory in Leghorn (Tuscany). Tuscany is in the central part of Italy and can be considered the birthplace of meteorology. In the 17th century, the first meteorological instruments were created and the Grand Duke of Tuscany, Ferdinando II de 'Medici, made the first attempt to create a European meteorological network, the so called “Rete Medicea”. Having already developed a strong interest in weather science, when the young Father Pietro Monte arrived in Leghorn, he set up a weather station near the Church of San Sebastiano. In 1862 the Meteorological Observatory was transferred to the Royal High School, today's High School 'ISIS Niccolini-Palli'. Here Pietro Monte built a more efficient laboratory where he collected and verified a large number of observations that were then published in the local journal and sent to Ufficio Centrale di Ecologia Agraria di Roma (UCEA). After his death, the observatory was managed by the teachers of the “Istituto Nautico” and by the municipality until 1998. In 2003, after a period of inactivity, monitoring was resumed by the “Centro di Meteorologia Marina e Monitoraggio Ambientale del Mediterraneo” (CoMMA-Med by IBIMET, Tuscany region and Leghorn province). In 2007, all the historical archives of the Meteorological observatory "Pietro Monte" were reproduced using digital photography. Digitization and storage of these datasets in an electronic format is already in place in collaboration with the students of the Istituto Tecnico Nautico “A. Cappellini”. The management and the analysis of such an important historical archive can also be a powerful training environment for students wishing to experience meteorological studies.

Keywords: meterology, historical data series, Pietro Monte, Leghorn, Livorno, education, ACARISS

INTRODUCTION Climate change is one of the most important issues that modern society should face in order to mitigate the impact of human activities on the environment and life. Many studies investigated present and future climate trends by analysing long historical data series (Moberg and Jones, 2005, Klok et al. 2009) and the impacts of these changes on the environment and human health (Parry et al, 2007). In this context, particular attention is now dedicated to urban climate. More and more people now live in expanding cities and urbanization causes an increase of the urban heat ________________________________________________________________________________________________ ISBN 9788895597188

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island effects (Oke, 1976, Unger, 2004 , Yan et al., 2010) as well as strengthens the intra-urban climatic variability (Petralli et al, 2011; Chen et al, 2012). And these effects can have important consequences on human health (Petralli et al. 2012, Modesti et al., 2013). Cities are also the first places where the first weather stations were installed and therefore the longest meteorological series are available. For this reason, historical observatories, even with all limitations related to the different protocols and monitoring tools that have been used in the course of the decades, are a valuable source of information of past climate for several scientific studies (Kumar et al. 2005, Brunetti et al. , 2006). Leghorn is a city on the coast of Tuscany (Italy) where one of the ancient observatories was setup in the middle of 19th century, even though the city was not part of the first attempt to establish a World Meteorological network made by the Grand Duke of Tuscany, Ferdinando II de 'Medici in the seventeenth century. This meteorological observatory, founded by ‘Pietro Monte’, together with Seismic Observatory 'Schiavazzi', has registered detailed and important information about the weather in this town since 1856. The aim of this paper is to describe the history of the observatory ’Pietro Monte’ and how the recent recovery and restore of its archives has discovered a large amount of documents and data of historical importance that also have important and useful application in research and didactic activities.

HISTORY OF THE OBSERVATORY The Historical Meteorological Observatory was founded in 1856 by Barnabite father Pietro Monte. Pietro Monte was born in Monte Tonengo (Asti – Italy) 21st, August 1823 and entered the Barnabites at 16. His passion for Physics led him to teach this discipline at the College Barnabite 'Marie Louise' of Parma and since November 1855, at the High School of Leghorn. Just after his arrival in Leghorn, he set up a primordial weather station at his own expense near the Church of San Sebastiano. In 1862 the Meteorological Observatory was transferred to the new premises of the Royal High School (nowadays High School 'Niccolini') (Figure 1). Figure 1. Observatory “Pietro Monte” on the top of High School “ISIS Niccolini-Palli” Leghorn

Here he was able to improve his observatory and proceed carefully and professionaly to collect, check and elaborate a huge number of meteorological data. His meteorological observations were also published in the research magazine “Il Nuovo Cimento” in 1858 and on the newspaper “L’Utile Col Dolce” (P. Monte, 1858). Pietro Monte continued to manage and collect data since his dead (1888) and when he was tired and seriously ill decided to donate his observatory to Leghorn Municipality. After his death, the Observatory was alternatively managed by teachers of the Regio Istituto Nautico di Livorno (Quaderni dell’Associazione ex studenti, 2006), by civil servants of the municipality and, later, by the “Corpo dei Vigili Urbani” until 1998. After that year, the Meteorological Observatory was overlooked until 2003, when meteorological data collection was resumed by the Center for Marine Meteorology and Environmental Monitoring in the Mediterranean (COMMA-Med), established by the Institute of Biometeorology of Florence (IBIMET-CNR) in collaboration with the Tuscany Region and the Province of Leghorn. This center is set in an area of the Istituto Tecnico Nautico “A. Cappellini” provided by the Province of Leghorn, in front of the harbour area in a strategic position both for the observation and the logistics. In 2004 the Education Activities Unit and the Environmental Protection Office of Leghorn, with the collaboration of LAMMA COMMA-Med (Laboratory of Monitoring and Environmental Modelling for Sustainable Development) published a report "L’Antico Osservatorio Meteorologico di Livorno” that suggested to turn the meteorological observatory also into an environmental education center. Then in February 2006, the Pro Liceo Classico Association of Leghorn published the book "Pietro Monte e l’Osservatorio Meteorologico di Livorno”. The work is accompanied by interesting archival research conducted by Prof. Mumolo, former director of the Nautical Institute "Cappellini". In 2006 the municipality of Leghorn signed an agreement with FCS (Foundation for climate and sustainability for the ________________________________________________________________________________________________ ISBN 9788895597188

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"Protection and conservation of meteorological instruments of the Historical Observatory Pietro Monte of Leghorn". In the framework of this agreement an inventory of the historic instruments of the observatory was made and the instruments were moved to Villa Maria waiting to be restored (Figure 2). Some of these instruments were partly restored and shown at the exhibition “Sotto il segno di Galileo” in Leghorn (Taddei et al., 2009). Figure 2. Fortin’s Barometer and Thermometer

THE HISTORICAL ARCHIVES In 2007, the whole historical archive of the observatory has been reproduced by digital photography and the meteorological observations from 1856 to 1996 are in the process of being stored in an electronic archive (Table 1). These archives and a scientific library of books since 18th to 19th century are now stored in “Archivio Storico Comune Livorno” (CLAS). They have a great historical interest for their cultural heritage and they also have a high scientific value for climatic studies in the Leghorn area.

Table 1 Meteorological data series available in electronic format; * 1899-1954 data series were recorded in the framework of the Project “Autonomy of the individual and introduction into the working environment (protected working environment)“ Parameter

From

To

Minimum daily temperature at 2 m

1866

1996

Maximum daily temperature at 2 m

1866

1996

Sunshine duration

1984

1996

Daily Precipitation in mm (at 19 h)

1961

1996

Wind direction at 8:14:19 h

1899*

1996

Wind speed at 8:14:19 h

1899*

1996

Atmospheric pressure at 8:14:19 h

1899*

1996

Atmospheric pressure at 0 °C and 0 m a.s.l. at 8:14:19

1961

1996

Temperature at 8:14:19 h

1961

1996

Cloud cover at 8:14:19 h

1961

1996

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Relative Humidity at 8:14:19 h

1961

1985

In the “Business” archive, there are documents and letters between the observatory and the municipality that give useful information on the tools and data collected in the course of 140 years. Figure 3 shows a copy of an original letter in which Pietro Monte writes about the purchase of a new anemometer and meteograph and this information has been used to derive some important metadata about the maintenance of the station that should be taken into consideration during the analysis of the historical data series. Figure 3. Letter by Pietro Monte to the mayor of Livorno October, 13th 1871

RESEARCH AND DIDACTIC ACTIVITIES In recent years, the data of the Meteorological Observatory have been used in various studies and projects. A first climatic analysis on 1857-1976 meteorological data has been published by Meini et al. (1979) in the Bulletin of the Italian Geographical Society. Since the early 70’, this historical data series was included in a database of all the historical Italian observatories made by the Central Bureau of Agricultural Economics (UCEA) in the framework of several national projects. Then CLIMAGRI (Climate Change and Agriculture) project had further recovered new data and metadata and each time series has been updated and described by a form containing all the information on the methods used to collect observations. The analysis of extreme events of Libeccio wind in Leghorn showed that the warming of the Mediterranean Sea due to the alteration of the Earth's radiation budget on a global scale can lead to local changes in atmospheric circulation (Scartazza et al. 2007). Recently another study was performed to investigate the relationship between wind intensity and direction and sea surface temperature (SST) anomalies (Scartazza et al. 2011). Other publications on the history of Libeccio wind and marine meteorology were also published (Brugnoni et al, 2006, Scartazza et al. 2008). The historical archive of the observatory was also used directly and indirectly in didactic activities with the Nautical Institute “Cappellini”. In the framework of the project “autonomy of the individual and introduction into the working environment (protected working environment)“ by Ibimet and LaMMA, students did a working experience where they helped to interpret and store historical wind data in electronic format. This project allowed to reach two important goals. Firstly students had the opportunity to do professionally a real job. Secondly their work they contributed to extend wind an atmospheric pressure series 1899-1954 (Table 1). The Pietro Monte data series were also used in the “Marine Meteorology” Module developed in the framework of ACARISS (Increasing the knowledge on environment and risks of pollution involving Schools with experimental activities), funded by Tuscany Region– Italy and realized by the Institute of Biometeorology, National Research Council (CNR - IBIMET), the School of University Studies and Sant'Anna (SSSA) and the Department of Psychology at the University of Florence (UNIFI). The aim of this project is to develop didactic modules based on an inquiry approach to engage and increase students’ interest towards science. These modules were designed according to the inquiry approach proposed in the 5E model (Bybee et al. 2006), that stimulates pupils to experiment, observe, investigate on phenomena and find solutions autonomously. For example, the Marine Meteorology module was introduced by the creation of a tornado in classroom that was effectively used to raise students’ interest. ________________________________________________________________________________________________ ISBN 9788895597188

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CONCLUSION The Meteorological Observatory "Pietro Monte" and its historical documents and archives has been a very rich source of useful information for past and present research and didactic activities and it will be also especially if the process of restoration of the documents and historical instruments continue in the future. An important step towards this objective could be reached if “Pietro Monte” would be part of the network of historical observatories as it was outlined during the “Workshop on the urban climate historians and observers in Italy: The use of old and new data".

REFERENCES Brugnoni, G., De Sario, G., Doronzo, B., A., Taddei, S. and Vaccari, F.P. (2004). L’Antico Osservatorio Meteorologico di Livorno, Comma-Med Ibimet Cnr Lamma, Livorno Brugnoni, G., Doronzo, B., Gozzini, B., Pellegrino, L., Petralli, S., Scartazza, A., Taddei, S. and Vaccari, F.P. (2006). Appunti di meteorologia marina. Regione Toscana, Giunta regionale, Direzione generale dello sviluppo economico. Comma-Med Ibimet Cnr Lamma. Firenze Regione Toscana, Ricerca, trasferimento, innovazione: 225. Brunetti M., Maugeri M., Monti F. and Nanni T. (2006). Temperature and precipitation variability in Italy in the last two centuries from homogenised instrumental time series. International Journal of Climatology 26 (3): 345–381. DOI: 10.1002/joc.1251 Bybee, R.W., Taylor., J.A., Gardner, A., Van Scotter, P., Carlson Powell, J., Westbrook, A. and Landes, N. (2006). The BSCS 5E Instructional Model: Origins and Effectiveness, BSCS Colorado Springs. Klok EJ, Klein Tank AMG. 2009. Updated and extended European dataset of daily climate Observations. International Journal of Climatology 29: 1182–1191. DOI: 10.1002/joc.1779. Centro di Meteorologia Marina e Monitoraggio Ambientale del Mediterraneo (2007) L'Osservatorio Meteorologico Storico "Pietro Monte" http://www.comune.livorno.it/_livo/uploads/2007_04_5_10_11_16.pdf Kumar, VP., Bindi, M., Crisci, A. and Maracchi, G. (2005) Detection of variations in air temperature at different time scales during the period 1889–1998 at Firenze, Italy. Clim Change 72:123–150. doi:10.1007/s10584-005-5970-8 Moberg, A. and Jones PD. (2005). Trends in indices for extremes in daily temperature and precipitation in central and western Europe, 1901–99. International Journal of Climatology 25(9): 1149–1171. DOI: 10.1002/joc.1163. Meini, L., Mucci, G. and Vittorini, S. (1979): Ricerche meteomarine sul litorale toscano:centoventi anni di osservazioni meteorologiche a Livorno (1857-1976). Collana Società Geografica Italiana, Ser. X, Vol. VIII Modesti, PA., Morabito, M., Massetti, L., Rapi, S., Orlandini, S., Mancia, G., Gensini, GF. and Parati, G. (2013) Seasonal Blood Pressure Changes: An Independent Relationship With Temperature and Daylight Hours. Hypertension DOI:10.1161/Hypertension AHA.111.00315 Monte, P. (1858) Osservazioni Meteorologiche fatte nell’ I e Regio Liceo di Livorno. L’Utile Col Dolce. Giornale di Istruzione Popolare , Livorno Oke, T.R., (1976). The distinction between canopy and boundary layer urban heat island. Atmosphere 14: 268–277. Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J. and C.E. Hanson (2007) Climate Change 2007: Impacts, Adaptation and Vulnerability, edited by Cambridge University Press. Petralli, M., Massetti, L., and Orlandini, S. (2011) Five years of thermal intra-urban monitoring in Florence (Italy) and application of climatological indices. Theor Appl Climatol 104 (3/4): 349-356.

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Petralli, M., Morabito, M., Cecchi, L., Crisci, A., and Orlandini, S. (2012). Urban morbidity in summer: ambulance dispatch data, periodicity and weather. Central European Journal of Medicine 7(6): 775-782. Quaderni dell’Associazione ex studenti e docenti del Liceo Ginnasio Statale Niccolini e Guerrazzi di Livorno (2006). Pietro Monte e l’Osservatorio Meteorologico Storico Pietro Monte. Debatte Editore Scartazza A., Brugnoni G., Doronzo B., Gozzini B., Pellegrino L., Rossini G., Taddei S. and Vaccari F.P., Maracchi G., (2007) Analisi climatologica degli eventi estremi di Libeccio a Livorno, Clima e cambiamenti climatici, le attività di ricerca del CNR a cura di Bruno, C., et al., Roma: 245-248 Scartazza, A., Brugnoni, G., De Chiara, G., Doronzo, B., Pellegrino, L., Rossini G. and Taddei, S. (2008). Il Libeccio e Livorno tra cultura, storia e scienza Livorno, IT: Sillabe Scartazza A, Doronzo B., Rossini G., Taddei S., Brugnoni G., Gozzini B., Pellegrino L. and Vaccari F.P., (2011) Influence of the increasing Mediterranean Sea Surface Temperature on local wind regimes in Leghorn area, in Marine Research at CNR Consiglio Nazionale delle Ricerche, Roma, vol. DTA/06-2011: 1349-1358 Taddei, S., Vaccari, F.P. and Zabini F. (2009) Geometrie e isocronie. Gli studi di Galileo sul moto dei proiettili e del pendolo. Comune di Livorno Unger, J., (2004). Intra-urban relationship between surface geometry and urban heat island: review and new approach. Climate Research 27: 253–264. Yan, Z. and Z. Li and Q. Li and P. Jones, (2010). Effect of site change and urbanization in the Beijing temperature series 1977-2006. International Journal of Climatology 30: 1226–1234 .

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LONG TERM TURBULENCE MEASUREMENTS OVER URBANIZED AREA IN ŁODŹ, CENTRAL POLAND Fortuniak K.1,, Pawlak W.1 1

University of Łódź - Faculty of Geographical Science - Department of Meteorology and Climatology

Summary The aim of the work is to present results of almost 12 years of eddy-covariance measurements of turbulence characteristics in Lodz, central Poland. Lodz is a third largest town in Poland with population around 750 thousands. As it is located on a flat area, far from large water reservoirs and it is characterized by regular city arrangements with a clear roof level, the town is a good polygon for urban studies. Two measurement sites (Lipowa and Narutowicza) are located in the core of the city centre. The sensors heights (37m and 42m respectively) exceed mean roof level more than two times at both sites. The data are collected in 1 hour files and turbulence characteristics are calculated for the same time intervals. The high quality of the data is ensured by different stationarity tests and careful data selection procedure. In last three years turbulence intensity and sensible heat flux are measured on a path of 3.2 km over a city centre with the aid of scintillometer BLS 900. On the base of available data integral and spectral characteristics of turbulence, like normalized standard deviations of wind components, temperature, water vapour and carbon dioxide concentration as well as normalized spectra of these variables are calculated. The data from Lodz show general agreement with Monin-Obukhov similarity functions commonly used in literature. Analyzing dependence of normalized standard deviations on stability parameter we observe in unstable conditions than, normalised standard deviations of wind components, humidity and CO2 concentration have a power law exponent of ±1/3 in the free convection limit, and approaches a constant value in close to neutral stratification. For stable conditions, the constant value approached for the neutral limit remains the same for humidity and CO2 concentration and increases for the wind components. Normalised standard deviation of temperature fits the –1/3 law in free convection limit, approaching a constant value in stable limit. Spectra and cospectra follows -2/3 law for spectra and -4/3 law for cospectra in the inertial subrange. We also observed progression towards higher frequency of the spectral and cospectral peak with increasing stability. On the base of spectra shape the non-dimensional dissipation rates of turbulent kinetic energy, φε, ware calculate as a function of stability parameter, ζ. In contrast to the Kansas experiment in unstable conditions φε2/3(ζ )/ φε2/3(0 ) first decrease from 1 at ζ =0 to a minimum approximately at ζ =-0.25 and next increase with more negative ζ. For the stable conditions φε2/3(ζ )/ φε2/3(0 ) follows standard function.

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NUMERICAL SIMULATIONS OF BOUNDARY-LAYER PHENOMENA AND URBAN-SCALE PROCESSES IN THE ALPINE CITY OF TRENTO Giovannini L.1, Zardi D.1,de Franceschi M.1,2 , Chen F.3 1

Atmospheric Physics Group, Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy 2 Major Seminary, Diocese of Bolzano-Bressanone, Bressanone, Italy 3 National Center for Atmospheric Research, Boulder, CO

[email protected]

Summary Simulations are performed with the Weather Research and Forecasting (WRF) model, coupled with an urban parameterisation scheme, to evaluate the alterations induced by the urban area of Trento on boundary-layer processes in the Alpine Adige Valley. Simulations, with 500-m grid spacing, focus on a typical summer sunny day, when both valley winds and the urban heat island are well developed. Specific gridded datasets of urban morphology parameters and anthropogenic heat flux releases were created to provide high resolution input information to the urban scheme. Validation of numerical results against measurements from surface weather stations shows that the model is able to simulate with reasonable accuracy valley winds, as well as the urban heat island, characterised by strong intensities at night and low values in the central hours of the day. It is found that the city inhibits the development of the groundbased thermal inversion at night, especially in the city centre, displaying a denser urban morphology and higher buildings. Furthermore comparisons with an idealised simulation, where all the urban land use grid points are replaced by cropland, suggest that the city also affects the development of valley winds, modifying both the typical down-valley wind in the early morning, and the interaction between the up-valley wind in the Adige Valley and a lake breeze flowing from a tributary valley.

Keywords: mesoscale models, urban parameterisations, urban heat island, valley city, valley winds

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INTERACTION BETWEEN URBAN METEOROLOGY AND BUILDING ENERGY CONSUMPTION: MODELLING APPROACH AND APPLICATION TO MADRID (SPAIN). Martilli A.1, Salamanca F. 2 1

Environmental Department, CIEMAT, Spain, School of Mathematical and Statistical Sciences, Arizona State University

2

[email protected] [email protected]

Summary Thermodynamics of the atmospheric urban canopy layer (UCL) has strong interactions with building energy consumption. From one side the energy consumed in buildings is an important component of the anthropogenic heat fluxes that go into the atmosphere. From the other side the UCL air temperature evolution is a key parameter to determine the energy consumed in the buildings to keep the internal temperature in a range of comfort appropriate for humans. Furthermore, the UCL strongly interacts (through exchanges of heat and momentum) with the Planetary Boundary Layer (PBL) above the city that, in turn, responds to a forcing at mesoscale (10-100km). An appropriate tool to account for the multiple feedbacks between building energy consumption and UCL, and between UCL and PBL, is the atmospheric mesoscale model WRF, in which an urban canopy parameterization (BEP, Building Effect Parameterization, Martilli et al. 2002) with a simple Building Energy Model (BEM, Salamanca et al. 2010) has been implemented. BEP is a multilayer urban canopy scheme that accounts for the impact of walls, roofs and roads on the momentum, potential temperature and turbulence kinetic energy equations. Shading and multiple reflections are considered in the scheme. BEM accounts for sources of heat in the buildings due to occupants and equipments, radiation through windows, natural ventilation, heat diffusion through walls, and the effect of air conditioning systems. This model has been applied to the city of Madrid. In this city, in fact, the interactions mentioned above are becoming increasingly relevant because of the occurrence of several factors: 1) a strong expansion of the city in the last 20 years, 2) high temperatures in summer which will be exacerbated by climate change, 3) a massive use of air conditioning systems. In particular two days of the field campaign DESIREX (june 2008) are simulated. After a validation against the data of the campaign, the model is used as tool to investigate the impact of the anthropogenic heat due to air conditioning on UCL and PBL structure, and on thermal comfort.

References: Martilli, A., A. Clappier, M. W. Rotach, 2002: An urban surface exchange parameterisation for mesoscale models’, Boundary-Layer Meteorology, 104, 261-304. Salamanca, F., Krpo, A., Martilli, A., Clappier, A., 2010, A new building energy model coupled with an Urban Canopy Parameterization for urban climate simulations – Part I. Formulation, verification and sensitivity analysis of the model. Theoreical and Applied Climatology. 99, 331-344.

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ANALYSIS OF 20-YEAR AIR QUALITY TRENDS IN THE CITY OF FLORENCE (ITALY) Gualtieri G.1, Crisci A.1, Gioli B.1, Tartaglia M.2, Toscano P.1, Vagnoli C.1, Andreini B.P.3 1

2

National Research Council–Institute for Biometeorology (CNR–IBIMET), Via Caproni 8 – 50145 Firenze, Italy University of Firenze, Department for Historic and Geographic Studies, Laboratory for Social Geography (LAGES), Via San Gallo 10 – 50129 Firenze, Italy 3 Tuscany Region Environmental Protection Agency (ARPAT), Via Porpora 22 – 50144 Firenze, Italy

[email protected]

Summary Today, about 80% of people in developed countries live in cities, while urbanization is rapidly growing in the developing countries. Due to high spatial density of human activities, cities exhibit high air pollutant concentrations, that impact human health risk across a wide range of socioeconomic and/or climatic features. In EU, and particularly in Italy, a significant percentage of urban population is exposed to pollutant concentrations above the reference levels. In this paper we report a 20-year (1993–2012) air quality analysis in the city of Florence (Italy). Concentrations of main atmospheric pollutants have been addressed: CO, NO2, NOx, SO2, PM10, and O3. Hourly (daily for PM10) observations collected by all the stations of Florence air quality monitoring network since the beginning of its activity (i.e., 1993) have been processed. Monitoring stations falling into each area category (urban, suburban and rural) and source category (traffic, industry and background) have been considered. Trends of annual mean concentrations of all pollutants observed at both central and periferic stations have been analysed, along with occurrences of concentrations exceeding legal thresholds. Meteorological parameters as wind speed and prevailing direction, air temperature, solar radiation, and stability class measured at a station located in the city centre (i.e., the Ximeniano Observatory) have been considered to depict a full description of Florence meteorological conditions. Trends of annual pollutant inventorial emission data in the province of Florence, disaggregated by SNAP category, have been also analysed and related to pollutant concentrations by means of a linear multi-regressive framework to assess the significance of their contribution to annual concentration trends.

Keywords: urban air quality; meteorological data; emission data; linear trend analysis; Florence.

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12 YEARS OF ENERGY BALANCE AND CARBON DIOXIDE FLUX MEASUREMENTS IN ŁÓDŹ, POLAND Pawlak W.1, Fortuniak K.1 1 Department of Meteorology and Climatology, University of Łódź, Poland

[email protected]; [email protected]

Summary Measurements of turbulent fluxes of momentum, mass and energy were initiated Łódź, central Poland, in the fall of 2000. Until now, with break in the year 2004, continuous eddy covariance measurements of radiation balance and heat fluxes has been conducting in the city center but short measurement campaigns were also carried out in other city districts (residential and post-industrial areas) and in suburban area (Łódź airport, agricultural terrain). Since 2006 one of the measurement points in the city center is equipped with infra-red gas analyzer which has enabled conducting continuous measurements of turbulent flux of carbon dioxide. These measurements allowed us to know the variability of turbulent exchange of mass and energy between the urban surface and the lower troposphere. Both fluxes of sensible and latent heat, and carbon dioxide flux are characterized by a distinct annual and diurnal cycles observed in other cities as well. Turbulent energy exchange is the most intense in the warm season, when, in average, city emits more than 6 MJ·m-2·day-1 heat by sensible heat and about 4 MJ·m-2·day-1 by latent heat. In winter, these values decrease in both cases, up to about 1 MJ·m-2·day-1. The CO2 flux is most intense in winter, when the city emits, in average, about 40 gCO2·m-2·day-1. In the summer, the emission is much less intense, in average 15 to 20 gCO2·m-2·day-1. The center of Łódź emits, in average, 10 kg of CO2·m-2·year-1. In autumn of 2011 another eddy covariance measurement set has been established on the agricultural terrain. Thus, we can analyze differences between mass and energy exchange on urban and rural area.

Keywords: eddy covariance sensible and latent heat fluxes, carbon dioxide, urban climate

INTRODUCTION One of the characteristic feature of urban climate is specific, in comparison with non-urbanized areas, turbulent exchange of mass, energy and momentum between atmosphere and active surface. Although research on climate separateness of urban areas are carried out for centuries, the issue of turbulent mass and energy transport is intensively undertaken in decades (Aubinte et la., 2012). The theoretical basis of the problem were formulated many years ago, but the appearance of relevant instruments in the last 20-30 years allowed to take extensive research. The specificity of the urban area and the methodological problems associated with measuring of turbulent fluxes causes that such measurements are still not very common. This applies especially to the continuous measurements, which means that a longtime series, covering at least a few years of turbulent fluxes sensible and latent heat measurements, and the above all fluxes of carbon dioxide, are still rare. Measurements of turbulent fluxes of momentum, mass and energy were initiated Łódź, central Poland, in the fall of 2000 (Offerle, 2003). The first research experiments (measurements of sensible and latent heat fluxes) were carried out in collaboration between Department of Meteorology and Climatology, University of Łódź and prof. S. Grimmond (then Indiana University, USA, now King’s College, London) and Dr B. Offerle. Measurement point was located in a ________________________________________________________________________________________________ ISBN 9788895597188

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densely built-up western part of the city center, and the eddy covariance measurements set was placed on a high tower, 37 m above the ground. These measurements were carried out continuously until the summer of 2003 (Offerle et al., 2005; Offerle, et al., 2006a, 2006b; Fortuniak, 2003). At the same time short measurement campaigns were carried out in the districts outside of the city center (residential and post-industrial areas) and in suburban (Lodz airport) (Offerle, 2003; Pawlak et al. 2007). In 2005, measurements were resumed and conducted independently by Department of Meteorology and Climatology to this day. Firstly, the new measurements has been started on a new point located in the eastern part of the city center on Narutowicza street (Fortuniak, 2010). Moreover, measurement site on Lipowa street has been equipped with infra-red gas analyzer which allowed conducting continuous measurements of turbulent flux of carbon dioxide (Pawlak et al., 2011). These measurements allowed us to know the variability of turbulent exchange of mass and energy between the urban surface and the lower troposphere. In autumn 2011 we decided to install additional measurement set on rural, agricultural terrain, which enables comparison of mass and energy exchange on urban and rural areas. The aim of this paper is short presentation of results of turbulent mass and energy exchange obtained in Łódź since 2000. The paper presents an analysis of the results of continuous measurements carried out in the city center in comparison with the rural station, excluding short-term measurements conducted outside of the center.

MEASUREMENT SITES Łódź is the third most populous city in Poland (~725 000). City buildings can be regarded as typical of European cities a densely built-up city center is surrounded by industrial districts, residential areas, green areas, etc. (Kłysik, 1996). City is placed on a relatively flat terrain, and what is especially important from the urban climate research point of view, there is no river, lakes and orographic obstacles which cloud affect the local climate of a city. Since 2000, measurements of turbulent exchange of mass and energy were conducted at six sites, located in districts with different characteristics of the active surface. The main two measurement points located in the west (Lipowa Street, fig. 1, middle, fig. 2) and eastern (Narutowicza Street, fig. 1, left, fig. 2) of the city center. Measurements of sensi ble and latent heat fluxes are performed here since 2000 (Lipowa, with a break in the years 2004-2005) and since 2005 (Narutowicza). Since July 2006, the measurement set at Lipowa is equipped with gas analyzer to measure carbon dioxide flux. In the neighborhood of the points dense building development prevails, with an average height of 11 and 16 m (tab. 1) (Kłysik, 1998). At a distance of less than 500 meters from the measurement points, the percentage of artificial surfaces (buildings, streets, pavements, squares, etc.) reaches 38% (Lipowa) and 40% (Narutowicza), other surfaces are green areas, with trees covering only 10% (Kłysik, 1998; Fortuniak, 2010, Pawlak, 2011). Since November 2011 rural station also operates, established in agriculture in village Annosław, 60 km east of Łódź (fig. 1, right). Surroundings of this point it's almost a 100% green areas (fields, tab. 1).

Table 1. Basic characteristics of measurements sites (zH – measurement height, zc – mean canopy height, zd – displacement height , z0m, ). zH

zc

zd

z0m

artificial surfaces

[m]

[m]

[m]

[m]

[%]

Urban – Lipowa

42.0

11.0

7.7

2.0

62

Urban – Narutowicza

37.0

16.0

11.2

1.9

60

Reference – agricultural

3.3

0.5

0.35

0.04

1

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Figure 1: Measurement sites of energy and carbon dioxide turbulent fluxes: Narutowicza street (left), Lipowa street (middle) and reference site on agricultural terrain (right).

MEASUREMENT METHOD The exchange of mass and energy between the atmosphere and the active surface is a result of turbulent transport, so eddy covariance method to measure fluxes was used. In this method, the heat flux (sensible QH or latent QE) or mass (carbon dioxide FCO2) is calculated directly from the definition as a covariance of the fluctuations of vertical wind speed w 'and temperature T', humidity q ' and carbon dioxide concentration ρCO2' (Lee et al., 2004; Foken, 2008; Fortuniak, 2010; Aubinet, 2012):

The advantage of this method is its high accuracy, resulting in the possibility of calculating fluxes directly from the definition, without taking into account empirical coefficients during calculations. Moreover, the method allows to determine not only the value of the stream over a period of time, but also his direction. Negative value of the flux indicates that uptake of heat or mass prevail over emission and net flux is directed downwards (from the atmosphere to the active surface). Positive value of the flux indicates net transport is in the opposite direction, that is, the emission from the active surface to the atmosphere. Systems has been installed on high towers poles at a height of 37 (Lipowa) and 42 meters (Narutowicza) that is at least two times higher than the urban canopy layer in the surroundings of sites (tab. 1). Therefore, according to the methodology it was possible to assume that the fluxes were measured above the roughness sub-layer and were representative to a surface, rather than a single building (Grimmond and Oke, 1999).

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Table 2. Instrumentation installed at measurement sites. w’, T’

q’

ρCO2’

Urban – Lipowa street

Sonic anemometer RMYoung 810001

Li7500 IRGA2

Li7500 IRGA2

Urban – Narutowicza street

Sonic anemometer RMYoung 810001

Krypton hygrometer KH2O3

-

Reference – agricultural terrain

Sonic anemometer RMYoung 810001

Li7500A IRGA2

Li7500A IRGA2

1 RMYoung (USA) 2 Li-cor Biosciences (USA) 3 Campbell Scientific (USA) Furthermore, source areas for unstable conditions were calculated at all sites with use of Schmid model (Schmid, 1994; Fortuniak, 2010). The results of calculations (fig. 2) confirm that the calculated fluxes relate to the parts of the urban surface with a diameter of ~1000 m. In the case of rural station source area was smaller, because the sensors were installed lower, at a height of 3.3 m. For measurements standard set of measurement sensors has been used: ultrasonic anemometer, krypton hygrometer or infrared gas analyzer (tab. 2). Instruments recorded the fluctuations with the frequency of 10 Hz and fluxes were calculated with 1 hour averaging period. Before calculating of the final fluxes value appropriate corrections and the analysis of data quality were added. Therefore, all the data registered during the occurrence of rainfall or atmospheric deposits were rejected, spike detection, maximization of covariance due to distance between sensors, and wind coordinates double rotations procedures were added (Lee et al., 2004; Foken, 2008; Fortuniak, 2010; Aubinet, 2012). Corrections for sonic temperature and WPL were also added (Webb et al. 1980). Figure 2: Aerial photos of measurement sites surroundings (top left – Lipowa street, bottom left – Narutowicza street, bottom right – reference station, top right – map of Łódź with sites localisation) and turbulent fluxes source areas at p =25, 50, 75 and 90% calculated for unstable stratification (all available data in the period 2005 – 2012). Dotted lines indicate distances 250, 500, 750 and 1000 m from sites. Photos source: Municipal Centre of Geodesis and Cartographic Documentation of Łódź.

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RESULTS The relatively long term nature of mass and energy fluxes measurements held in Lodz allows for detailed analysis and selected results are presented here. First of all, as it is observed in other mid-latitude cities, relatively large portion of energy partitioning devoted sensible heat flux QH. In the summer at both urban stations sensible heat flux QH reaches average values of 150 W·m-2 (fig. 1). The latent heat flux QE is significantly lower, and reaches about 80-100 W·m-2 (fig. 1). For comparison, at the rural station sensible heat flux QH values are similar but latent heat flux QE is much higher and reaches a value similar to the QH. This difference is due to the limited ability of urban surface to evaporation because of less green areas in the surroundings of measurement sites and the drainage of rainfall water into the sewage system. An interesting feature of the sensible heat flux QH diurnal variability is its positive value when radiation balance becomes negative. This phenomena can be attributed to the heat release from the city, and associated with the altered thermal properties of a city, e.g. the large heat storage capacity. In winter, when the radiation balance is positive only for a few hours a day, variability of fluxes in- and outside the city is similar. Fluxes are small or oscillate around the zero. Days with negative values of sensible heat flux QH appear in the city relatively rare, unlike the rural area where the winter advection of relatively warm air for a few days cause a negative value of this flux even in a few days in a row. Moreover, latent heat flux QE is always positive in a city center and cases with negative values of QE are extremely rare. As it was reported in other cities heat fluxes are characterized by clear diurnal and annual rhythm (fig. 3, tab. 3). Figure 3: Mean diurnal courses of radiation balance Q*, sensible (QH) and latent (QE) heat fluxes (W·m-2) on urban and rural sites in January and July.

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Table 3. Mean diurnal radiation balance Q*, sensible (QH) and latent (QE) heat fluxes (MJ·m-2·day-1) on urban and rural sites in 2012. J

F

M

A

M

J

J

A

S

O

N

D

year

Lipowa

Q*

-1.1

0.1

3.3

7.0

11.8

12.3

11.5

9.2

4.5

1.3

-1.0

-1.7

4.8

Narutowicza

Q*

-1.0

1.0

3.6

7.0

10.6

12.5

11.7

8.8

5.6

1.5

-0.4

-1.0

4.9

agr. terrain

Q*

-1.0

-0.1

4.6

7.8

10.8

11.0

11.8

8.7

5.5

2.4

0.2

-0.9

5.1

Lipowa

QH

1.2

1.6

3.0

4.7

6.2

6.5

5.4

5.0

2.9

1.3

0.9

1.7

3.4

Narutowicza

QH

0.1

1.6

2.6

4.4

4.9

5.6

5.6

3.6

2.9

1.2

0.7

0.5

2.8

agr. terrain

QH

-1.2

-0.6

-0.1

1.3

2.3

1.9

3.7

2.3

1.5

0.2

-0.5

-0.7

0.8

Lipowa

QE

0.7

0.7

2.2

2.0

3.2

4.0

3.9

3.1

2.5

1.9

1.2

1.2

2.2

Narutowicza

QE

1.5

1.6

2.2

2.2

3.4

4.2

3.6

3.7

2.9

1.9

1.5

1.4

2.5

agr. terrain

QE

1.3

0.9

3.2

4.9

6.8

7.3

5.4

4.6

3.2

2.2

0.9

0.5

3.4

Source: own elaboration

Carbon dioxide flux is characterized by similar clear diurnal and annual variability (fig. 4, tab. 4). The annual rhythm is opposite to air temperature annual variability - maximum values are observed in winter, when the total monthly flux reaches 1000 g CO2·m-2, or even higher. Such high values of FCO2 flux are the result of emissions of anthropogenic carbon dioxide, forced by combustion of fossil fuels (cars traffic, house heating, cooking, etc.). In a rural area carbon dioxide exchange in the winter is close to 0. Another characteristic feature of carbon dioxide exchange in a city is the occurrence of two peaks in a day. The first maximum is the effect of morning peak of car traffic (hours 6 to 9), while the second, generally higher is caused by the afternoon/evening peak of car traffic and human house activities (heating, cooking, etc.). In the summer CO2 exchange in the city is much less intense. Both sources of anthropogenic carbon dioxide are significantly reduced, and some amount of CO2 is absorbed by the plants (fig. 4, tab. 4). Nevertheless, even in the summer Łodź center is a net source of this gas - total monthly flux reaches 350 - 600 g CO2·m-2. At the same time, in an agricultural area where the anthropogenic emission is negligible, strong uptake of carbon dioxide is observed. Another interesting feature of FCO2 variability in urban area is clear weekly rhythm. On weekends, carbon dioxide emissions in the city center is less than on the working day, while in rural areas this phenomenon does not occur.

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Figure 4: Mean diurnal courses of carbon dioxide fluxes FCO2 in Łódź center and on rural sites.

Table 4. Monthly and annual carbon dioxide flux on urban and rural sites in 2012. FCO2 (kgCO2·m-2·month-1) J

F

M

A

M

J

J

A

S

O

N

D

2012

Urban – Lipowa

0.98

0.96

0.96

0.85

0.64

0.35

0.43

0.57

0.53

1.04

0.94

1.12

9.37

Reference – agricultural

0.03

0.01

0.00

0.03

0.34

-0.40

0.20

-0.01

-0.15

0.06

0.02

0.01

-1.08

CO2 throughout the year. In 2012 the annual exchange of CO2 was 9.37 kg CO2·m-2, but in years with very cold winter annual total can reach nearly 12 kg CO2·m-2. Agricultural terrain uptakes carbon dioxide during the warm season, in cold season exchange in near zero.

CONCLUSIONS 12 years of fluxes measurements allow for detailed analysis of turbulent exchange of mass and energy between the urban surface and the atmosphere, but this study includes only a small part of it. The results confirm the mechanisms of turbulent exchange of heat and carbon dioxide in the mid-latitude city, known from the literature. In the near future we are going to expand our research and start with methane flux measurements on Lipowa Street station. We also plan the comparison of the obtained results with another measurement site, running since the November 2012 and measuring energy and greenhouse gases exchange (carbon dioxide and methane) in the wetland (Biebrza National Park).

ACKNOWLEDGMENTS Many thanks to Sue Grimmond and Brian Offerle who initiated eddy covariance measurements in Łódź at Lipowa station. Funding for this research was provided by The North Atlantic Treaty Organization (NATO 977460) and the National Science Foundation (NSF 0221105 and BCS-0095284) and the Polish Ministry of Science and Higher ________________________________________________________________________________________________ ISBN 9788895597188

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Education (State Committee for Scientific Research) under grants 6 P04E 010 17 (2000 – 2002), 2P04E 041 28 (2005 – 2007), N N306 276935 (2008 – 2010), N N306 519638 and 2011/01/D/ST10/07419 (2010 – 2012).

REFERENCES Aubinet, M., Vesala, T., Papale, D., (ed.) (2012). Eddy Covariance. A Practical Guide to Measurement and Data Analysis. Springer. Foken, T. (2008). Micrometeorology. Springer, Berlin. Fortuniak K. (2003). Urban heat island. Energetic basis, experimental studies, numerical and statistical models (in Polish). University of Łódź Press. Fortuniak K. (2010). Radiative and turbulent components of heat balance of urban terrain – Łódź case study (in Polish). University of Łódź Press. Grimmond C. S. B. and Oke T. R. (1999). Aerodynamic properties of urban areas derived from analysis of surface form. Journal of Applied Meteorology 38: 1262-1292. Kłysik K. (1996). Spatial and seasonal distribution of anthropogenic heat emission in Lodz, Poland. Atmospheric Environment 30: 3397–3404. Kłysik K. (1998). The characteristics of urban areas in Łódź from a climatological point of view. Acta Universitatis. Lodziensis, Folia Geographica Physica 3: 173–185 (in Polish). Lee X., Massman W., Law B., (ed.) (2004). Handbook of Micrometeorology. A Guide for Surface Flux Measurement and Analysis. Kluwer Academic Publishers. Dordrecht. Offerle B. (2003). The energy balance of an urban area: Examining temporal and spatial variability through measurements, remote sensing and modelling. PhD dissertation (manuscript). ProQuest Dissertations And Theses; Thesis (Ph.D.), Indiana University, Publication Number: AAI3122725; ISBN: 9780496700530; Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0793.; 219 p. Offerle, B., Grimmond, C. S. B. and Oke, T. R. (2003). Parameterization of net all-wave radiation for urban areas. Journal of Applied Meteorology 42: 1157–1173. Offerle, B., Grimmond, C. S. B. and Fortuniak, K. (2005). Heat storage and anthropogenic heat flux in relation to the energy balance of a central European city centre. International Journal of Climatology 25: 1405–1419. Offerle, B., Grimmond, C. S. B., Fortuniak, K., Kłysik, K. and Oke T. R. (2006a). Temporal variations in heat fluxes over a central European city centre. Theoretical and Applied Climatology 84: 103–115. Offerle, B., Grimmond, C. S. B., Fortuniak, K. and Pawlak, W. (2006b). Intra-urban differences of surface energy fluxes in a central European city. Journal of Applied Meteorology and Climatology 45: 125–136. Pawlak, W., Fortuniak, K., Offerle B. and Grimmond, C. S. B. (2007). Application of eddy-covariance method to CO2/H2O fluxes measurements from the grass surface. Przegląd Geofizyczny 52: 95–106 (in Polish). Pawlak, W., Fortuniak, K. and Siedlecki, M. (2011). Carbon dioxide flux in the centre of Łódź, Poland – analysis of a 2-year eddy covariance measurements data set. International Journal Of Climatology 31: 232-243. Schmid, H. P. (1994). Source areas for scalar and scalar fluxes. Boundary Layer Meteorology 67: 293–318. Webb, E. K., Pearman, G. I. and Leuning, R. (1980). Correction of flux measurements for density effects due to heat and water vapor transfer. Quarterly Journal of the Royal Meteorological Society 106: 85-100.

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SCINTILLOMETER MEASUREMENTS OF THE SENSIBLE HEAT FLUX IN ŁÓDŹ, CENTRAL POLAND Zieliński M.1, Fortuniak K.1, Pawlak W.1, Siedlecki M.1 1

Department of Meteorology and Climatology, University of Łódź, Łódź, Poland

[email protected]

Summary The energy balance components play an important role in Urban Climate studies measurements . The most common method of flux measurements – eddy covariance – allows to obtain the representative fluxes for relatively small areas, while scintillometry has an ability to measure the fluxes along the path even up to few kilometers long. Therefore, such measurements could be used i.e. for verification of the numerical weather prediction models. This method has been proved reliable in natural areas while only few studies have been conducted in urban ones. In Łódź scintillometer (Scientec BLS900) was deployed in August 2009 and operated until October 2012. The measurements path is nearly 3.2 km long and traverses over the city centre. As in cities the visibility is often, especially in winter, significantly reduced the amount of reliable data is reduced as well. Moreover, in case of considered measurements the technical problems has contribute to gap occurrence. Therefore the statistical model based on the additional measurements of energy balance components have been used to fulfill the mentioned gaps. This study presents the results of three-year measurements of the sensible heat flux. Its diurnal and annual course is discussed as well as intercomparison with eddy covariance measurements. As urban areas are heterogeneous the variability of the surface beneath the optical path is considered as well.

Keywords: scintillometer, sensible heat flux, urban climate

INTRODUCTION The signularities of the urban climate are well known and one the most essential is the modification of the energy balance. Due to the heterogeneity of the surface in urban areas the point measurements such as eddy covariance could be representative for relatively small areas. The scintillation method has the advantage of delivering the area-averaged values of the surface fluxes of sensible and latent heat. Many studies has prooved the reliability of this method in the heat fluxes estimation (e.g. De Bruin et al 1995, Meijninger et al. 2006). However, there are only few studies considering the application of scintillometer in the urban areas. One of the first such experiments was performed in Tokyo (Kanda et al., 2002), the next measuerements were conducted during the BUBBLE and ESCOMPTE campaigns in Bassel and Marseille respectively (Roth et al., 2006; Lagouarde et al., 2006). More recently the scintillometer were deployed in i.a. London, Swindon, Helsinki. This study presents some of the results of nearly 3-year measurements of the sensible heat flux (QH ) by means of scintillation method. The previous studies revealed quite good agreement of scintillometer meauserements with the ________________________________________________________________________________________________ ISBN 9788895597188

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eddy covariance (Zieliński et al., 2012). Consideration are given to the estimation of the footprint area, moreover the modeled QH is discussed as well.

MEASUREMENTS SITES, DATA AND METHODS Łódź (51°47’N, 19°28’E) is a city located in Central Poland. Considering the population it is the third biggest city in abovementioned country. The relatively flat surface and the lack of rivers and large water reservoirs contributed development of distinctly visible singularities of urban climate in Łódź. The urban flux measurements are conducted in the city centre, that is occupied with 15-20 m height buildings, built mainly in the end of 19th century. The relatively uniform height and similar roof coverage (mainly tarred roofs are present here) makes this part of the city rather a homogeneous surface. Outward the city centre the surface is more complex as some parks with high vegetation could be found as well as industrial areas. The Scintec BLS 900 scintillometer (hereinafter BLS) was used in that study. The BLS transmitter was mounted at a height of 31 m above ground level on the mast 20 m in height standing on the roof of the 17 m height building at 81 Lipowa Str. (51°45’45’’N, 19°26’43’’E, 204 m a.s.l.) (Fig. 1). The mean height of the surrounding buildings (zH) is about 16 m. That site is located in the city centre about 1.5 km to the south-west from most densely built-up areas in Łódź. The BLS receiver was deployed on the roof of the building at 12 Matejki Str. (51°46’24’’N, 19°28’52’’E, 221 m a.s.l.) that is 36 m in height. The optical path of the BLS is 3142 m long and traverses over the city centre. Since the BLS path height above the ground is not uniform the effective measurements height (zeff) had to be estimated (Hartogensis et. al 2003, Kleissl et al, 2008). Figure 1: The location of scintillometer (BLS) measurements in Łódź. 1- transmitter of the BLS, 2 – receiver of the BLS, eddy covariance system, radiation balance measurements, 3 - eddy covariance system, radiation balance measurements. Aerial photograph source: www.geoportal.gov.pl

In case of considered measurements the zeff for unstable conditions is 22.14 m (with standard deviation equal 0.06 m) while for stable 22.22 m. The weighted average (with BLS path-weighting function) displacement height (d) estimated as a d=0.7zH (GRIMMOND AND OKE, 1999) is 11.54 m while roughness length (z0) is 1.65 m (z0=0.1zH). The ratio of z/zH is 2.14 so the measurements were conducted close to the blending height.

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The BLS measurements started in Łódź in August 2009 and were conducted until November 2012. Nevertheless this study considers only the data set from September 2009 to May 2012. As the extensive construction works have started in the beginning of 2012 in the central part of analyzed area, their influence on the measured values still have to be studied. In urban areas BLS operation is frequently prevented by unfavorable weather conditions including the low visibility and increased amount of aerosols in the air. Thus the amount of available data was significantly reduced. Another reason for this were the technical problems that occurred mainly in the winter. Data have undergone the quality control i.e. 1-hour intervals with insufficient amount of data or stored with BLS errors were rejected, as well as time periods when precipitation occurred or EC data did not passed stationarity tests. For the estimation of the sensible heat flux from the BLS measurements some additional data are necessary. In addition to the BLS two eddy covariance (EC) systems operates in Łódź (Fig. 1). The first is mounted at the same mast as BLS transmitter, however, 6 m higher. Here as well as at the second site (EC on Fig. 1) the radiation balance components are measured. The second EC is mounted at height of 42 m (17 m height building and mast 25 m in height) at 88 Narutowicza Str. (51°46’24’’N, 19°28’52’’E, 221 m a.s.l.). The mean temperature and mean atmospheric pressure from both sites were used for computation of the temperature structure parameter (CT2) from the BLS measurements (15-minute intervals). The CT2 values were corrected according to Bowen-correction (Wesely, 1976) for which the mean Bowen ratio from both EC measurements was used.

 0,03  p2  C ≈ α ⋅ 4 ⋅ CT2 1 + T β  

2

2 n

(1)

where: α is a constant depending on scintillometer type, T is the absolute temperature [K], p is the atmospheric pressure [hPa] and β is the Bowen ratio. The sensible heat flux (QH) from the BLS was computed iteratively with the application of Monin-Obukhov Simarity Theory (MOST) and then averaged in 1-hour intervals. The universal function presented by Andreas (1988) was applied in the set of equation 2-5. In addition mean wind speed from both EC sites was used for the friction velocity computation in consecutive steps of iterative procedure.

CT2 ( zeff ) 2 / 3

θ

2 *

z  = fTT  eff   LOB 

(2)

2

LOB

u( z) =

u* k

u T = * gkvθ*

  z ln   z 0

  z  − Ψm (ζ ) + Ψm  0   LOB

QH = − ρ ⋅ c p ⋅ u* ⋅ θ *

(3)

  

(4) (5)

where: θ* is the turbulent temperature scale, fTT is the universal MOST function, LOB is the Obukhov length, u is the wind speed, u* is the friction velocity, z is the measurements height, z0 is the surface roughness, ζ is the stability parameter (z/LOB) and Ψm is a well-known Businger-Dyer equation. ________________________________________________________________________________________________ ISBN 9788895597188

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SCINTILLOMETER SOURCE AREA To evaluate the source area (SA) of the BLS the analytical footprint model FSAM by Schmid (1994, 1997) was applied. As the FSAM model was developed for single point measurements to determine the source area of the BLS the superposition of multiple model runs along the optical path were computed. As the BLS measurements are the most sensitive to the turbulence in the centre of optical path, all of computed footprints were normalized with path-weighting function. To provide the ultimate BLS source area all acquired footprints for points along the path were averaged. Similar approach was applied by Göckede et al. (2005). For the unstable conditions (fig. 2) the BLS source area at p=90% covers the area about 3.5 km2 (for near-neutral conditions the SA is nearly twice as big – 6.1 km2 – not shown in fig. 2), however, for specific case the SA could be significantly decreased. It highly depends on the wind direction. When wind direction is perpendicular to the BLS path the SA is the largest, on the other hand while the wind direction is parallel to the measurement path, the footprint covers considerably smaller area. In considered case the 25% of measured QH developed over the 0.4 km2 area situated in the centre of the BLS path. In general the SA is covered with the artificial surfaces, however, close to the centre of the considered area a few parks could be found. The areas covered with vegetation occupies 0.16 km2 what is 4.6% of the SA at p=90%. Even though the amount of vegetation cover is not significant, the BLS SA could not be assumed as homogeneous. It is distinctly shown by the Land Surface Temperature (LST) pattern. The most uniform is the surface in the north-western and western sector of the BLS SA. On the other hand the greatest spatial variability could be found in the eastern part of considered area. The measurement height along the BLS path is not uniform, therefore it affects the estimated footprint. Above the city centre (western part of SA) measurements are conducted a few meters lower than in the rest of the considered area, thus the SA do not reach so large distance as for instance in the eastern part of BLS path. Figure 2: The scintillometer source area. Solid lines point indicates source areas at p = 25, 50, 75 and 90% calculated for turbulent fluxes measured in unstable stratification. In the footprint area the Land Surface Temperature obtained from the LANDSAT 5TM image acquired on 6th July 2011 is shown. Aerial photograph source: www.geoportal.gov.pl

SENSIBLE HEAT FLUX PARAMETRIZATIONS In this study two model were used for modeling of the QH from the BLS measurements. The first model (CT2) was based on the relation between the temperature structure parameter measured by the BLS and CT2 obtained from EC on the basis of equation 2. The CT2 from the EC were next inferred in the iterative procedure. Therefore, model CT2 allowed to obtain not only the QH values but also the rest of the parameters estimated in the iterative process (i.e. u*, zeff). ________________________________________________________________________________________________ ISBN 9788895597188

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The second model (MR) was based on the additional measurements of radiation balance, temperature and wind speed. For the unstable conditions the multiple regression based on all abovementioned variables was applied, while for stable condition model was based only on the wind speed. In figure 3 the observed diurnal and annual course of QH is presented as well as the difference between the observed and modeled data. Both models presents quite good agreement with the observed values (table. 1), however, there are some significant differences. The first of considered models (CT2) seems to overestimate the observed QH, especially during the winter and spring (fig. 3c). The another interesting pattern could be found in July, when model underestimates QH. The second model (MR) is better fitted to observed data what is confirmed by relatively small errors (table 1.).

Table 1. Mean Bias Error (MBE), Mean Square Error (MSE) and its root (RMSE), Mean Absolute Error (MAE) and index of agreement (d) computed between observed and modeled QH. All errors [Wm-2], d – dimensionless. MODEL

MBE

MSE

RMSE

MAE

D

CT2

14.55

1100.19

33.17

21.08

0.98

MR

-1.57

602.306

24.54

16.91

0.98

Figure 3: Observed values of sensible heat flux QH (a), difference between modeled data with model CT2 and MR (b), difference between observed and modeled data for model CT2 (c), MR (d). Only data after quality control are presented here.

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Figure 4:The course of the turbulent sensible heat flux in centre of Łódź in the period September 2009 – May 2012 modeled with model CT2 (a) and MR (b).

The modeled course of the QH in the period from Septmember 2009 to May 2012 (fig. 4) indicates that the highest values of QH could be found in May and June. Nevertheless, one must be aware that in considered period the July and August were relatively cold and wet in Poland, what in turn could contribute to lower QH. This phenomena is distinctly highlighted by the model CT2 (fig. 4a), however, model MR also indicates the summer decrease of QH. Both models agree that in Janury and February the heat flux is positive almost during the whole day. During the rest of the year the couse of QH is similar in case of both considered models, and the greatest discrepancies occurs durign the nights and winter time – the periods when stable conditions prevail.

SUMMARY This study presented some aspects of the scintillometer measurements of the sensible heat flux (QH) conducted in Łódź. Consideration was given to the source area (SA) estimation and the modelling of the QH on the basis of the additional measurements. The applied approach of SA estimation (average superposition of source area for point measurements) allowed to determine the areas that contributed most to the measured values of QH. The extent of the BLS SA is greater than in case of point measurement technique such as eddy covariance, therefore obtained fluxes are representative for relatively vast areas (up to a few square kilometres). However, the size of SA depends on the optical path length and the wind direction. Models applied in this study could give the opportunity to fulfil the gaps found in the QH time series. This might be the most helpful in winter when the amount of valid data was significantly reduced. From two considered models the MR model based on radiation balance, air temperature and wind speed data performed better than the CT2 model based on the temperature structure parameter (obtained from eddy covariance with Monin-Obukhov Similarity Theory). Nevertheless, some more consideration should be given to QH modelling with CT2 model, as it is promising since it could deliver more parameters, such as path-averaged friction velocity or Obukhov length, than the second of the considered models.

ACKNOWLEDGMENTS Present work was funded by Polish National Science Centre under grant DEC-2011/01/N/ST10/07529 in years 20112014 and by Polish Ministry of Science and Higher Education (State Committee for Scientific Research) under grant N N306 276935 in years 2008-2011 .

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REFERENCES Andreas, E.L. (1988). Estimating Cn2 over snow and sea ice from meteorological data. J. Opt. Soc. Amer. A 5:481-495. De Bruin, H.A.R., Van Der Kurk, B.J.J.M., Kohsiek, W. (1995). The scintillation method tested over dry vineyard area. Boundary Layer Meteorol. 76: 25-40. Göckede, M., Markkanen, T., Mauder, M., Arnold, K., Leps, J.-P., Foken, T. (2005). Validation of footprint models using natural tracer measurements from a field experiment. Agr. Forest. Meteorol. 135: 314-325. Grimmond, C.S.B., T.R. Oke (1999). Aerodynamic properties of urban areas derived from analysis of surface form. J. Appl. Meteorol. 38: 1262-1292. Kanda, M., Moriwaki, R., Roth, M., Oke, T. (2002). Area-averaged sensible heat flux and a new method to determine zero-plane displacement length over an urban surface using scintillometry. Boundary-Layer Meteorol. 105: 177-193. Meijninger, W.M.L., Beyrich, F., Lüdi, A., Kohsiek, W., De Bruin, H.A.R. (2006). Scintillometer-based turbulent fluxes of sensible and latent heat over a heterogeneous land surface – a contribution to LIFTASS-2003. Boundary Layer Meteorol.121: 89-110. Roth, M., Salmond, J.A., Satyanarayana, A.N.V. (2006). Methodological considerations regarding the measurements of turbulent fluxes in the urban roughness sublayer: the role of scintillometry. Boundary-Layer Meteorol,121: 351-357. Lagouarde, J.P., Irvine, M., Bonnefond, J.M., Grimmond, C.S.B., Long, N., Oke, T.R., Salmond, J.A., Offerle, B. (2006). Monitoring the sensible heat flux over urban areas using large aperture scintillometry: case study of Marseille city during the ESCOMPTE experiment. Boundary-Layer Meteorol. 118: 449-476. Schmid, H.P., 67: 293–318.

(1994).

Source

areas

for

scalar

and

scalar

fluxes.

Boundary-Layer

Meteorol.

Schmid, H.P. (1997). Experimental design for flux measurements: Matching scales of observations and fluxes. Agric. For. Meteorol. 87: 179–200. Wesely, M.L. (1976): The Combined Effect of Temperature and Humidity on the Refractive Index. J. Appl. Meteorol. 15: 43-49. Zieliński, M., Fortuniak,. Pawlak, W., Siedlecki, M., 2012, Sensible heat flux in Lodz – scintillometer and eddy covariance measurements, Proceedings of 8th International conference on Urban Climate, Dublin, Ireland, ICUC, 4.

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DEVELOPMENT AND CHARACTERIZATION OF MINIATURIZED SOLID-STATE DEVICES FOR ENVIRONMENTAL MONITORING Borchi E.1, Bruzzi M.2, Macii R.1 M. Scaringella3 1

2

Osservatorio Ximeniano, Via Borgo S.Lorenzo 6, Firenze, Italy Dipartimento di Fisica ed Astronomia Università di Firenze and Consorzio I.C.A.D., Italy 3 Dipartimento di Ingegneria Industriale, Università di Firenze, Italy

[email protected]

Summary This paper presents a resume of the activity of Osservatorio Ximeniano on various aspects of environmental monitoring, carried out by means of solid-state devices. Specific portable-units providing instantaneous measurements have been developed by means of miniaturized devices based on innovative materials. Demonstrative examples of pollutant gas concentrations monitoring both out-door and in-door as well as of UV solar radiation are reported.

Keywords: solid-state detectors, environmental monitoring, gas sensing, UV solar radiation

INTRODUCTION Environmental monitoring is becoming a stringent necessity, especially in urban sites. A study reported by the World Health Organization (WHO) states that over 3 million people die each year from the effects of air pollution [1]. Increasing concerns are focused on a multitude of parameters that can affect air quality. Of the group of pollutants that contaminate urban air, nitrous oxide (NOx), fine suspended particulate matter (PM), sulphur dioxide (SO2), volatile organic compounds (VOCs) and ozone pose the most widespread and acute risks. Gas as carbon dioxide (CO2) and carbon monoxide (CO) are also important sources of pollution. CO is one of the most common and widely distributed air pollutants, and one of the leading causes of unintentional poisonings. Its ambient concentration measured in urban areas depend greatly on the density of combustion powered vehicles, and it is influenced both by topography and weather conditions. In the streets, carbon monoxide concentration varies greatly according to the distance from traffic, in general highest at the leeward side of the “street canyon”, with a sharp decline from pavement to rooftop level [2]. CO2 is one of the greatest variables affecting indoor environmental quality, since it is produced by people occupying the building. CO2 production is a function of the number, size and activity levels of the people present in the building, indoor CO2 generation rate is estimated 0.31 L/min per person [3]. Excess CO2 levels can lead to tiredness and lack of concentration, it can contribute to symptoms of Sick Building Syndrome as headaches, eye, nose and throat irritation, itchy skin and nausea. Measurements of CO and CO2 levels is therefore an intrinsic part of outdoor/indoor environmental quality strategies. ________________________________________________________________________________________________ ISBN 9788895597188

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Other environmental concerns regards the high levels of exposure to ultraviolet radiation especially in outdoor workers and the associated increased risk of skin cancer. This is the most common type of cancer in the United States [4]. High levels of exposure to ultraviolet (UV) radiation increase the risk of all common forms of skin cancer, and approximately 65%-90% of melanomas are caused by exposure to UV radiation [5]. UV radiation levels at the earth surface are influenced by factors as: Sun elevation, latitude, cloud cover and aerosol presence, altitude, ozone concentration, ground reflection. At present, weather forecast analysis is used to determine the UV Index (UVI) from meteorological conditions [6], but the accuracy is limited by the quantity and quality of available input data on the UV solar radiation. Moreover, a precise evaluation of the change of the UVA and UVB direct solar radiation during daytime, would allow for evaluating the total atmospheric optical thickness. Increased concentrations of suspended materials in air result in higher extinction coefficients, so the measurement of optical thickness can represent a good support to the overall analysis of the out-door air quality especially in urban sites. In general, air pollutant measurements are carried out with analytical instruments such as optical spectroscopy, gas chromatography, mass spectrometry, non-dispersive infrared (NDIR), and chemiluminescence. Such monitoring systems are bulky, expensive, time-consuming, and can seldom be used for real-time monitoring. Recent development of thin semiconductor films employing polycrystalline and nanostructured materials, Nerst-type potentiometeric devices based on solid-electrolyte membrane, capacitor-type gas sensors and epitaxial detectors offer excellent alternatives for environmental monitoring. Portable analyzers with automated data-logging have become available for personal exposure monitoring. These measurements are based on miniaturized solid-state detectors with low-power consumption, that can fit into a pocket, directly embedded in garment accessories or vastly distributed in the field in view to perform real-time remote sensing. This paper presents a resume of the activity of Osservatorio Ximeniano on various aspects of environmental monitoring, from gas sensing to solar UV radiation measurements, carried out by means of miniaturized solid-state devices.

EXPERIMENTAL SET-UPS AND RESULTS CO and CO2 real-time monitoring Traditional approaches for gas sensing are based upon discrete sampling methods followed by laboratory analysis. The usual reference method for the measurement of the concentration of toxic gas as carbon monoxide in air is based on the absorption of infrared radiation by the gas in a non-dispersive photometer. This method is suitable for stable installations at fixed-site monitoring stations. Continuous analytical methods able of detecting chemical species with high temporal and spatial resolution in real-time making use of portable devices are much more convenient for a systematic test in the field. This requires miniaturized and robust sensors, with high sensitivity and long lifetime. Electrochemical sensors represent an important subclass of chemical sensors, highly qualified for meeting size, cost, and power requirements of on-site environmental monitoring in real-time. Two electrochemical devices have been tested by the research group of Osservatorio Ximeniano to measure in real-time the CO and CO2 concentrations in air. The device used to monitor CO concentration is produced by LASCAR Technologies, UK, characterised by a [CO] measurement range of 0-300ppm, resolution ±0.5ppm and operating temperature from -10°C to +40°C. Measurements in a controlled climatic chamber with air in standard conditions allowed for measuring the base-line of the device during several hours, resulted in value always less than 35℃) in Beijing during summer increase accordingly.

Wang, Y., Hu, F. (2006)

1990-2004

Variations of the urban heat island in summer

UHI intensity is more obvious during the nighttime than daytime.

Li, X.R., Hu, F., Shu, W.J.(2006)

UHI intensity has positive correlation with the increase of the urban population and area, but seasonal UHI variation tends to be negatively correlated with the seasonal variation of relative humidity and vapor pressure. UHI intensity is observed in the late nighttime or evening.

Liu, Ji, Zhong, Jiang, and Zheng (2007)

1977-2000

UHI Temporal characteristics

1975-2004

Temperature and precipitation change

Temperature increasing trend slope in summer: 0.2℃/10a;

Ji, C.P. et al. (2006)

Sun, J.S, Shu, W.J. (2007)

Temperature increasing trend slope in

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winter: 0.6℃/10a; Urbanization is the main cause of urban 1978-2002

Air temperature

1961-2000

Winter precipitation distribution

1971-2003

Urban-rural humidity The effect of urban on local temperature, and temperature relative humidity and vapour pressure were discussed. differences

1960-2006

Contribution rate of urbanization to local temperature rise

1940-2000

Urban dry island and Hot days in summer were keeping increase hot days in summer during 1970s-1990s in Beijing.

1961-2008

Temperature, precipitation change in urban area

Temperature rise in Beijing. Estimated contribution rate of urban heat effect to urban temperature is from 47.5% to 61.2%. Beijing slow urbanization period is from 1961 to 1980, the fast urbanization period is from 1981 to 2000.

Estimated contribution rate of urban heat effect to urban temperature is 44.8% to 73.5% during 1960-2006 and 1979-2006, respectively.

Temperature increasing trend slope in summer: 0.29℃/10a;

Zheng, Z.F., Zheng, Y., Li, Q.C.(2007)

Wang, X.Q et al. (2009)

Liu, W., You, H., and Dou, J. (2009)

Si, P. et al.(2009)

Wang, X., and Gong, Y. (2010)

Zhao, N., Liu, S.H., Yu,H.Y. (2011)

Precipitation change rate: -17.28mm/10a Source: own elaboration

To sum up, following facts can be summarized: first, like in all other megacities all around the world, in Beijing, urbanization is the primary contributing factor to local temperature rise which is the essential issue of UHI effect and it makes the urban area becoming more and more vulnerable when facing the challenges brought by global warming; second, to review the status from quantitative angle, all these researches show that and the acceleration of local temperature increasing in Beijing urban area is at least 0.2-0.3℃• (10 a)-1 which is faster than the background temperature increasing of climate change which is 0.13 ℃• (10 a) -1 (IPCC, 2007); Regarding to the diurnal and seasonal characteristics, the results show that UHI effect is less obvious in spring and autumn than in summer or winter, and nighttime UHI intensity is more obvious than daytimes during the whole year. UHI effect also lead to meteorological disasters including hot days or hot wave in summer and urban rain island effect.

RS and GIS Based Study Temporal analysis of UHI also can be conducted via RS and GIS method, but different from air temperature based meteorological observation data, satellite image provided data of the land surface temperature (LST), therefore, UHI effect observed from RS is defined as SUHI(surface urban heat island) (PENG, J et al ,2007). The Chinese Academy of Sciences, Chinese Academy of Meteorological Sciences and Beijing Meteorological Bureau also conducted research about the diurnal and seasonal characteristics of urban heat island variation in Beijing using EOS-MODIS and Land TM/ETM+ respectively (Zhang, Zhou and Li et al, 2005; Zhou, Chen and Weng et al.,2008; Yang, Zhao and Shen et al., 2010). These researches show the similar results with the historical meteorological data analysis based research, meanwhile, urban cool island effect in winter was observed, and the cool island during winter may increase the near surface air stability, consequently worsen the air pollution dispersion in Beijing urban area (WANG, J et al,2007).

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Almost all of the historical meteorological data analyses in Beijing are recorded by fixed meteorological stations. However, the amount and distribution of meteorological stations are discrete; therefore, it is not very convenient to conducted continuous analysis such as the UHI isotherm distributions and sections, since the data is discrete. Compared with the former ways, researchers prefer to use RS and GIS to do spatial analysis of urban climate condition for megacities since the large scale and huge urban area make the measurements become more difficult and unfeasible. The Beijing UHI spatial distribution investigation via Land Sat Satellite Remote Sensing was conducted by Key Laboratory of System Ecology Research Centre for Eco—Environmental Sciences Chinese Academy of Sciences (Zhang, Z et al, 2005) and Beijing Institute of Landscape Architecture (Li, Y., Guo, J., Li, W., 2011). In both researches, 5-level UHI classification was put forward based on the measured UHI intensity. Table.2 show the latest results that with the growth of Beijing central city built-up area, the UHI affected area is increasing. Table 2. UHI affected area and its proportion in total urban planning area of Beijing central city UHI affected area (km2)

Intermediate area (km2)

Non-UHI area (km2)

Year

UHI area-to-urban area ratio (%)

Level 1

Level 2

Level 3

Level 4

Level 5

1987

34.56

76.48

199.56

634.56

88.51

10.74

2000

53.26

193.39

275.82

458.64

52.55

23.86

2007

54.18

210.36

463.21

301.80

4.12

25.59

Source: Li, Y., Guo, J., Li, W., 2011

Remote sensing and satellite image are also applied to evaluate the relationship between urban construction and UHI effect because the LST can be estimated via retrieval algorithm based on land surface emissivity (Dash, Gottsche and Olesen et al, 2002). Landsat TM is one of the most widely used RS images for environmental research (Sobrino, Jiménez-Muñoz, & Paolini, 2004). Normal Difference Vegetation Index (NDVI) can be calculated, and then LST can be retrieved. JIANG et al. (2006) create the linear regression relationship equation between NDVI and LST for Beijing urban area and use it to evaluate the UHI effect on different underlying urban surface types. Similar researches were also conducted by Wang and Shen et al. (2006), Zhang and He (2007), Ouyang, Z. et al. (2008), Wu, Wang and Zhang (2009). These researches describe the correlation between UHI spatial variation and Beijing urban construction and land use layout based on NDVI, NDBI (Normal difference building index) and NDWI (Normal difference water index). In summary, before 1980s, the urban development of Beijing was relatively slow and the UHI intensity also increased with slow rate; from 1980s, the urban construction process was accelerated, and both the UHI intensity and the UHI affected area were increased rapidly; after 2000, the UHI effect in Beijing was alleviated gradually, since the implementation of reasonable urban planning strategies include green space planning and construction restrictions which aims to improving urban environmental quality for the objective of "Green Olympic Games".

Mobile Measurement The earliest urban mobile measurement was conducted by W.Schmidt in 1927 (Landsberg, 1981), it is an effective way to observe the UHI. Zhang, J et al (1984) and GUO, Y et al (2006), conducted Beijing UHI effect mobile measurements. Zhang's research combines the conventional fixed field measurement with mobile measurement to draw the isotherms and define four main types of the UHI in Beijing urban area: Clam-light air clear night type, Light breeze clear sky type, Gentle-moderate breeze clear sky type and Cloudy type. The isotherms distributions of these four types of UHI are shown in Fig 1. However, the limitation of the research is that the sizes of field measurement sample (64 times during 4 months) are not enough for represent the real occurrences of different UHI type during a whole year.

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Fig 1. Isotherms distributions of 4 types of UHI in Beijing urban area.

Clam-light air clear night type UHI

Light breeze clear sky type UHI

Gentle-moderate breeze clear sky type UHI

Cloudy type UHI

Source: Zhang ,J et al (1984)

Different from the former, mobile measurement conducted by Guo et al. mainly focuses on the effect of different urban underlying surface on air temperature. In this research, green space and water body were proved effective on local temperature reduction in both urban scale and district scale.

Modelling and Simulations Meteorological modelling and simulation is one of the most effective ways to understand and predict the urban climate condition. Since the mainstream meteorological simulation model such as MM5 and WRF can be coupled with other models via programming, Yang, Y et al. (2003) interpolated building height and land use data into non-hydrostatic mesoscale model MM5 and used the coupled model to simulate the daily variation of urban boundary layer UHI in Beijing. By comparing the simulation results with the observations, this method is proved correct to predict the urban boundary layer UHI and its circulation. Similar research were also conducted based on NARP, UCM, RBLM scheme respectively (Cui, Liu, Hu, Wang and Kuang, 2012; Zhou, Jiang and He, 2008; Xu, Jiang, Liu and Wang, 2002) to simulate the surface energy balance in Beijing urban areas. AMELIORATION STRATEGIES FOR BEIJING URBAN CLIMATE During the past two decades, with both the continually increased environmental needs of urban development and the enhancement of environmental awareness, Beijing local government and environmental related institutions put many efforts to mitigate the UHI and improve air quality. Since this review mainly aims to provide information for climatic and environmental consideration in urban planning, the part will focus on urban planning related strategies. Fig 2. Beijing urban greenbelt system in central urban area

Source: Beijing Municipal Commission of Urban Planning, 2010.

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Urban Planning Strategies For the purpose of improving the urban climate condition and receding the UHI intensity, Beijing urban greenbelt system planning was conducted. This greenbelt system is a series of comprehensive greening vegetation areas around the Beijing central city. It is an indispensable integral part of the Beijing urban greening systems (Fig 2) which is planned by Beijing Municipal Institute of City Planning & Design (Beijing Municipal Commission of Urban Planning, 2004). The function of the annular greenbelt is to maintain the "decentralized syndicated" urban layout, keep the reasonable width and connection of urban air path and to ensure the environmental and ecological functions of urban green spaces are exerted effectively and efficiently. The wedge-shaped green spaces are designed as the main air paths of the Beijing central city to guarantee the fresh air can flow into the city easily with enough wind speed and amerliate , meanwhile the atmospheric pollutants can spread quickly. Fig 3. Evaluation Index System Framework of Beijing Urban Planning Program Atmospheric Environmental Effects

Source: Ren, C., Ng, Y., 2012.

Urban Climatic Map Research The urban climatic map (UCMap) is an information platform and assessment tool to integrate urban climatic considerations into urban planning practices by presenting climatic phenomena and problems into two-dimensional spatial maps (Ren, Ng and Katzschner, 2011). Compared with other academic research results, UCMap is easier and more feasible for urban development policy makers and urban planners to understand and apply into practical projects. Beijing UCMap research now is in its infancy. As the first step is also the basis of UCMap, research on the Relationship among Beijing Urban Planning and Construction and the Meteorological Conditions and Atmospheric Pollution has been conducted by specialized research group (Research group of , 2004; WANG Guangtao et al., 2005), research based on different scales and methods are involved. The Technical route and indexes system framework (Fig 3) of Beijing urban meteorological evaluation has been put forward.

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CONCLUDING REMARKS With its rising as one of the international cities, Beijing has higher and higher requirements for the urban environment quality. As an important part of the urban environment improvement, urban climate research has made great progress in Beijing, which contributes to the urban environment improvement accordingly. However, there still exist a number of issues in research studies: (1) most of the studies have proven the existence of urban climate issues, such as the heat island effect, by observation and simulation methods, and have clearly indicated the reasons and temporal and spatial variation of the problem. However, the majority of research only offered recommendations at the liberal and qualitative description levels with few further quantitative improvement strategies. (2) Few studies were closely linked to the level of urban planning, and the study results are not intuitive which affected the availability to urban planning practice. (3) Most studies are still only written in Chinese, which is not conducive to the international academic exchanges and cooperation. In this paper, due to space limitations, the content mainly focus on the heat island effect and the existing improvement strategies, while more studies will be conducted and further summarized in the future.

REFERENCES Beijing Municipal Commission of Urban Planning. (2004). Beijing City Master Planning (2004-2020). Beijing: BMCUP. Beijing Municipal Commission of Urban Planning. (2010). Beijing Green Space System Planning. Beijing: BMCUP. Chan, C. K., and Yao, X. (2008). Air pollution in mega cities in China. Atmospheric Environment 42(1): 1-42. Chen, S.B.and Pan, L.Q.(1997). Effects Of Urbanization On The Annual Mean Temperature Of Beijing. ACTA GEOGRAPHICA SINICA 52 (1): 27-36. (in Chinese with English abstract) Chung, J.-Y., Honda, Y., Hong, Y.-C., Pan, X.-C., Guo, Y.-L., & Kim, H. (2009). Ambient temperature and mortality: An international study in four capital cities of East Asia. Science of The Total Environment 408(2), 390-396. Cui, Y., Liu, J., Hu, Y., Wang, J., and Kuang, W. (2012). Modeling the radiation balance of different urban underlying surfaces. Chinese Science Bulletin 57 (9): 1046-1054. Curriero, F. C., Heiner, K. S., Samet, J. M., Zeger, S. L., Strug, L., & Patz, J. A. (2002). Temperature and Mortality in 11 Cities of the Eastern United States. American Journal of Epidemiology 155(1): 80-87. Dash, P., Gottsche, F. M., Olesen, F. S., et al. (2002). Land Surface Temperature and Emissivity Estimation from Passive Sensor Data: Theory and Practice-current Trends. International Journal of Remote Sensing 23(13): 2563-2594. EEA. (2010). The European environment - state and outlook 2010: adapting to climate change. Copenhagen: European Environment Agency. Guo, Y., Barnett, A., Pan, X. et al.(2011). The impact of temperature on mortality in Tianjin, China: A case-crossover design with a distributed lag nonlinear model. Environ Health Perspect 119 (12): 1719–1725. Guo, Y., Long, B., Li, W., Li, M. (2006). Primary Study of Urban Heat Island Effect in Beijing Using Mobile Measurements. Meteorological Science and Technology 34 (6): 656-661. (in Chinese with English abstract) IPCC. (2007). IPCC Fourth Assessment Report: Climate Change 2007, Switzerland: Intergovernmental Panel on Climate Change. Ji, C.P., Liu, W.D., Xuan, C.Y. (2006). Impact of urban growth on the heat island in Beijing, CHINESE JOURNAL OF GEOPHYSICS 49 (1): 69-77. (in Chinese with English abstract) Jiang, Z., Chen, Y., Li, J. (2006). Heat Island Effect of Beijng Based on Landsat TM Data. Geomatics and Information Science of Wuhan University 31 (2): 120-123. (in Chinese with English abstract)

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Kan, H. D., Jia, J., & Chen, B. H. (2003). Temperature and daily mortality in Shanghai: a time-series study. Biomedical and environmental sciences : BES 16(2): 133-139. Landsberg, HE (eds.). (1981). The Urban Climate. New York: Academic Press. Li, T. T., Gao, Y. L., Wei, Z. H. et al. (2012). Assessing Heat-related Mortality Risks in Beijing, China. Biomedical and Environmental Sciences 25(4): 458-464. Li, X.R., Hu, F., Shu, W.J. (2006). Characteristics and Variations of Urban Heat Island Effect in Beijing for Last 15 years. Meteorological Monthly 32 (8): 42-46 (in Chinese with English abstract) Li, Y., GUO, J., Li, W. (2011). Thermal environment changes in Beijing central city during 1987-2007. Beijing Landscape 27 (1): 30-34. (in Chinese) Liu et al. (2011). Associations between air temperature and cardio-respiratory mortality in the urban area of Beijing, China: a time series analysis. Environmental Health 10: 51. Liu, W., Ji, C., Zhong, J., Jiang, X., & Zheng, Z. (2007). Temporal characteristics of the Beijing urban heat island. Theoretical and Applied Climatology 87 (1-4): 213-221. Liu, W., You, H., and Dou, J. (2009). Urban-rural humidity and temperature differences in the Beijing area. Theoretical and Applied Climatology 96 (3-4): 201-207. National Bureau of Statistics of China. (2009). Urban Statistical Yearbook of China. Beijing, China: China Statistics Press. National Bureau of Statistics of China. (2010). Urban Statistical Yearbook of China. Beijing, China: China Statistics Press. Ouyang, Z., Xiao, R.B., Schienke, E.W., Li, W.F., Wang, X., Miao, H., Zheng. H. (2008). Chapter 27 Beijing Urban Spatial Distribution And Resulting Impacts On Heat Islands. In S.-K. Hong, N. Nakagoshi, B.J. Fu and Y. Morimoto (eds.), Landscape Ecological Applications in Man-Influenced Areas: Linking Man and Nature Systems, 459–478. Peng, J., Liu, W., Long, B., Hu, J. (2007). A study of the urban heat island of Beijing based on remote sensing images. Progress in Geophysics 22 (6): 1942-1947. Ren, C., Ng, E. Y.-y. (2012). Urban Climatic Map - An Information Tool for Sustainable Urban Planning. Beijing: China Architecture and Building Press. Ren, C., Ng, E. Y.-y., and Katzschner, L. (2011). Urban climatic map studies: a review. International Journal of Climatology 31(15): 2213-2233. Research group of . (2004). Urban Planning and Atmospheric Environment. Beijing: China Meteorological Press. Si, P., Li, Q.X., Xuan, C.Y., Yin, H. (2009). Contribution of urbanization to change of air temperature in Beijing. Journal of Natural Disasters 18 (4): 138-144. (in Chinese with English abstract) Sobrino, J. A., Jiménez-Muñoz, J. C., and Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment 90 (4): 434-440. Sun, J.S, Shu, W.J. (2007). The effect of urban heat island on winter and summer precipitation in Beijing region. Chinese Journal of Atmospheric Sciences 31 (2): 311-320. (in Chinese with English abstract) UN, Department of Economic and Social Affairs United Nations, Population Division. (2012). World Urbanization Prospects, The 2011 Revision. New York. Vaneckova, P., Beggs, P. J., de Dear, R. J., & McCracken, K. W. J. (2008). Effect of temperature on mortality during the six warmer months in Sydney, Australia, between 1993 and 2004. Environmental Research 108(3): 361-369. ________________________________________________________________________________________________ ISBN 9788895597188

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Wang, G., Wang, X., Miao, S., Jiang, W., Guo, W., Ji, C., Chen, X. (2005). Research and application on the technology system of multi-scale assessment of the impact on the atmospheric environment by urban planning. Science in China (Series D) 48 (suppl.Ⅱ): 173-184. Wang, J., Wang, K., Wang, P. (2007). Urban Heat(or Cool) Island over Beijing from MODIS Land Surface Temperature. Journal of Remote Sensing 11 (3): 330-339. (in Chinese with English abstract) Wang, W., Shen, W., Liu, X., Zhang, F., Pan, Y., Luo, H. (2006). Research on the Relation of the Urbanization and Urban Heat Island Effect Changes in Beijing Based on Remote Sensing. Research of Environmental Sciences 19 (2): 44-48 (in Chinese with English abstract). Wang, X., and Gong, Y. (2010). The impact of an urban dry island on the summer heat wave and sultry weather in Beijing City. Chinese Science Bulletin 55 (16): 1657-1661. Wang, X.Q., Wang, Z.F., Qi, Y.B., Guo, H. (2009). Effect of urbanization on the winter precipitation distribution in Beijing area. Science in China Series D: Earth Sciences 52 (2): 250-256 Wang, Y., Hu, F. (2006). Variations of the urban heat island in summer of the recent 10 years over Beijing and its environment effect. Chinese Journal Of Geophysics 49 (1): 61-68. (in Chinese with English abstract) Wu,P., Wang, M., Zhang, X. (2009). Distribution of urban heat island effects based on normalized difference built-up index in Beijing city. Ecology and Environmental Sciences 18 (4): 1325-1331. Xu, M., Jiang, W., Ji, C., Liu, H., Gao, Y., Wang, X. (2002). Numerical modeling and verification of structures of the boundary layer over Beijing area. Quarterly Journal of Applied Meteorology 13 (Z1): 61-68. (in Chinese with English abstract) Xu, Y.Y., Liu, S.H., Hu, F. et al. (2009). Influence of Beijing urbanization on the characteristics of atmospheric boundary layer. Chinese Journal of Atmospheric Sciences (in Chinese) 33 (4) : 859-867. Yang, S., Zhao, X., Shen, S. et al. (2010). Characteristics of urban heat is land seasonal pattern in Beijing based on Landsat TM /ETM + imagery. Trans Atmos Sci 33 (4) : 427-435. (in Chinese with English abstract) Yang, Y., XU, X., Weng, Y. (2003). Simulation of Daily Cycle of Boundary Layer Heat Island in Beijing. Journal of Applied Meteorological Science 14 (1): 61-68. Zhan, Z., He, G.(2007). A Study on the Urban Growth and Thermal Environmental Changes of Beijing City Based on TM Imagery Data. GEO- INFORMATION SCIENCE 9 (5): 83-88. (in Chinese with English abstract) Zhang, G.Z., Xu, X.D., Yang, Y.Q., Wan, J.Z. (2002). A Study Of Characteristics And Evolution Of Urban Heat Island Over Beijing And Its Surrounding Area. Journal Of Applied Meteorological Science 13, Suppl: 43-50. (in Chinese with English abstract) Zhang, J., Li, J., Zhou, Y., Wang, Y.(1984). Some Patterns of the heat island in Beijing, Acta Geographica Sinica 39 (4): 428-435. (in Chinese with English abstract) Zhang, L., XU, Z.X., Ruan, B.Q. (2006). Effect of Urban heat island on the air temperature and precipitation in Beijing Region. Journal of Natural Resources 21 (5): 743-755. (in Chinese with English abstract) Zhang, J., Zhou,Y., LI, G., Yan, H., Yang, L., Yao, F. (2005). The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing Satellite data. Science in China Series. D Earth Sciences 48 Supp. II: 220-229. Zhang, Z., He, G., Xiao, R., Wang, W. (2005). A Study of the Urban Heat Island Changes of Beijing City Based on Remote Sensing. Remote Sensing information 6: 46-48. (in Chinese with English abstract) Zhao, N., Liu, S.H., Yu,H.Y. (2011). Urbanization Effects on Local climate in Beijing in recent 48 years. Chinese Journal of Atmospheric Sciences 35 (2): 373-385. (in Chinese with English abstract)

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Zheng, Z.F., Zheng, Y., Li, Q.C. (2007). Effect of urbanization on the temperature of Beijing metropolis in recent 30 years. Chinese Journal of Eco-Agriculture 15 (4): 26-29. (in Chinese with English abstract) Zhou, S.Z., Shu, Q. et al.(1994). Urban climatology. Beijing, China: China Meteorological Press. (in Chinese). Zhou, J., Chen,Y., Li, J., Weng,Q, Yi, W. (2008). A Volume Model for Urban Heat Island Based on Remote Sensing Imagery and Its Application: A Case Study in Beijing. Journal of Remote Sensing 12 (5): 734-742. (in Chinese with English abstract) Zhou, R., Jiang, W., He, X. (2008). Numerical simulation of the impacts of the thermal effect of urban canopy structure on the formation and the intensity of the urban heat island. Chinese J. Geophys. (in Chinese), 51 (3): 715~726.

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A NEW URBAN SITE TO DEVELOP FUTURE SUSTAINABLE PLANNING ALTERNATIVES Spano, D.1,2, Marras S.1,2, Sirca C.1,2, Casula M.1, BelluccoV.1 , Kyaw. Tha Paw U3 , Snyder R. L.2,3, Pyles R. D.2,3, Falk M.2,3, Cecchini A.4, Blecic I.4, Trunfio A.4, Duce P.5 1

DIPNET, Department of Science for Nature and Environmental Resources, University of Sassari, Italy 2 CMCC, Euro-Mediterranean Centre on Climate Change, Sassari, Italy 3 LAWR, Land, Air and Water Resources, University of California, Davis, CA, USA 4 DADU, Department of Architecture, Planning and Design, University of Sassari, Alghero, Italy 5 CNR IBIMET, Institute of Biometeorology, National Research Council, Sassari, Italy

Summary Changes in urban climate greatly affect cities’ liveability and human health. The main factor altering urban climate is recognized to be the increase in GHGs concentration (mainly carbon dioxide) due to human activities in urban areas (such as traffic, domestic heating/cooling, etc.). To reduce the impact of urbanization on climate, it is crucial to monitor the urban environment and to develop planning strategies, which could help in reducing carbon emissions. A new project just started in Italy with the purpose of providing new tools,methodologies, and strategies to local and regional authorities of the Island of Sardinia for reducing carbon emissions of cities. The general aim of the project is to develop a methodology framework, including inventory tools, direct measurements and models, for identifying and planning future urban low carbon scenarios. The project aims to quantitatively estimate the urban metabolism components and for this reason an Eddy Covariance station will be used to monitor long-term energy, water, and carbon fluxes over a Sardinian city. An inventory approach will also allow for monitoring of the air quality and identification of the main emissions sources. An innovative point of the project is the development of a modeling system to study the impact of different urban planning strategies on carbon emission rates. At this stage, interactions with local stakeholders are crucial to understand the real needs of the city in terms of future development and to identify the scenarios to test. Four models are involved: 1) the land surface model ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) will be calibrated to simulate the urban metabolism components at local scale 2) a Cellular Automata model will simulate the urban land-use dynamics for the next 10-20 years 3) a transportation model will estimate the variation of the transportation network load 4) the coupled model WRF-ACASA will simulate the urban metabolism components for the entire municipality. In this way, the impact of changes in land use demand and transportation network load in the city will be tested at both local and regional scale. At the end of the project in 2014, results will provide local authorities with detailed information about the temporal and spatial dynamics of CO2 emissions and the main environmental factors affecting emission rates. Results will also help in assessing the sustainability and the applicability of the identified planning strategies in mitigating CO2 emissions. In addition, stakeholders will have information to implement localenvironmental policies to meet the strategic objectives identified in the framework of Europe 2020. A detailed description of project activities and methods will be reported here.

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DEVELOPMENT AND APPLICATION OF ASSESSMENT METHODS FOR THERMAL BIOCLIMATE CONDITIONS IN STUTTGART, GERMANY Ketterer C. and Matzarakis A. Chair of Meteorology and Climatology, Albert-Ludwigs-University, Werthmannstrasse 10, D-79085 Freiburg, Germany

[email protected]

Summary The urban heat island and the spatial differences of the urban climate are assessed using measured data and humanbiometeorological methods for Stuttgart, a city in Southern Germany. The urban heat island can be detected in mean air temperature differences of 1.7 °C, but more appropriated when using thermal indices as the Physiologically Equivalent Temperature (PET) or the Universal Thermal Climate Index (UTCI). The maximum rural-urban difference is always visible comparing the minimum temperature and amounts to 25 °C PET. In the city the wind speed is mostly less than 3 m/s, the wind roses are very inconsistent and thermally induced winds can be clearly observed. At the measuring station Schnarrenberg, the highest minimum and mean air temperature is measured, but especially during summer maximum temperature occurs most frequently at the measuring station in the city centre (Schwabenzentrum). Inner urban variabilities are most obvious using thermal indices rather than air temperature as an indicator. The current and changing background conditions are analysed using the ENSEMBLE model RT2B for the greater area of Stuttgart. It is clearly visible, that the number of frost, ice and extreme cold days will decrease by 77 %. On the other hand the first very hot days, which are defined by air temperature above 39 °C, will occur in the 21st century. The number of hot and summer days is expected to increase by more than 50 % until the end of the century. These results, the expected increase heat load during summer in the 21st century and current urban heat island intensity clarify the urgent need and further need of adaptation measures in Stuttgart.

Keywords: thermal bioclimate, microclimate, PET, Stuttgart

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A COMPARATIVE ANALYSIS OF THE CHANGE IN TEMPERATURE ON URBAN, TOWN AND RURAL AREAS OF PAKISTAN S. H. Sajjad*1,2, N. Blond1, A. Clappier1 1

Laboratoire Image Ville Environnement, ERL7230, Centre National de la Recherche Scientifique, Université de Strasbourg, 67000 Strasbourg – France 2

Department of Earth Sciences, University of Sargodha, 40100 Sargodha – Pakistan

[email protected]

Summary The purpose of this study is to comparatively quantify the change in temperature on urban, town and rural areas of Pakistan and then compare the change in temperature trends of urban stations with global trends. For this purpose, monthly averages of minimum (Tn) and maximum (Tx) temperatures data from 1950 to 2004 of 37 meteorological stations was first homogenized by using PRODIGE method and then the resulting homogenized data was analyzed by using the least square linear regression. The data was divided into phase1 (1950–1979) and phase2 (1980–2004). The analyses for both phases are based on per year change in temperature at urban, town and rural stations. The analysis shows that during phase 1 annual and seasonal dTn at urban stations decreased while at town and rural stations, dTn increased in all seasons except in winter. During phase 2, annual and seasonal dTn and dTx at urban and town stations increased in all the seasons. During this phase, dTn at rural stations decreased in all the seasons except in winter and dTx increased in all the seasons except in summer. For 1979 to 2004, the corresponding linear trends at global scale were observed 0.29°C per decade for both maximum and minimum temperature. In case of Pakistan, nearly during the same period (1980-2004), the corresponding linear trend at urban scale was observed 0.43°C/decade and 0.33°C/decade for minimum and maximum temperature, respectively. It shows that increase in minimum temperature at urban areas of Pakistan is 0.14°C/decade greater than the increase in global minimum temperature (0.43°C vs 0.29°C per decade, respectively). However, the increase in maximum temperature at urban stations of Pakistan is nearly close to the increase in global maximum temperature (0.33°C vs 0.29°C, respectively). The extra increase in minimum temperature at urban stations of Pakistan as compare to increase in global minimum temperature is a possible result of local urban effect.

INTRODUCTION The twentieth century also witnessed the rapid urbanization throughout the world and especially in third world countries. The global proportion of urban population increased from a mere 13 per cent in 1900 to 29 per cent in 1950. It reached to 49 per cent in 2005. Since the world is projected to continue to urbanize, 60 per cent (about 4.6 billion) of the global population is expected to live in cities by 2030 (World Urbanization Prospects, 2005). Urban areas are major consumer of energy. Major part of the energy consumed in the world is produced from combustion of fossil fuels. The burning of fossil fuels in combustion reactions results in emission of number of pollutants and greenhouse gases in atmosphere (Vedal, 1997; Oke, 1997). So the first consequence of the urbanization is to deliberate more energy consumption in the cities. The second consequence is to degrade human quality of life and health. Urbanization leads to a modification of the local energy exchanges between the surface and the atmosphere: pavements and buildings are replacing natural landscape and thus changing the radiation balance of the earth's surface; heat generated by fossil fuels combustions is released in to the atmosphere. Consequently urban areas are becoming highly warmer than the rural surrounding areas, contributing to so-called urban heat island (Quattrochi and Rid, 1994; Grimmond et al., 2002; Shepherd and Burian, 2003; Martilli, 2003; Martilli et al., 2003; Bounoua et al., 2009). ________________________________________________________________________________________________ ISBN 9788895597188

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Individual cities show a large heat-island effect, measuring up to 5°C ~ 11°C warmer than their surrounding rural areas (Aniello et al., 1995). The urban heat island (UHI) intensity varies with urban size and population growth (Bacci and Maugeri, 1992; Chung et al., 2004; Liu et al., 2007; Yin et al., 2007), urban surface characteristics and anthropogenic heat release (Landsberg, 1981). The UHI also vary according to different types of atmospheric circulation pattern or air masses e.g. in Madrid, Spain (Yagüe et al., 1991). In this context, cities are more and more concerned by climate change: first by concentrating dense population, they become more and more vulnerable to climate change risks; secondly by concentrating human activities and energy consumption, their responsibilities in climate change are increasing. In order to reduce the vulnerability and the energy consumption of such cities and improve inhabitants comfort, urban planners and decision makers may try to find best sustainable urban strategies. The objective of the present study is to quantify the effect of urbanization, town and rural stations of Pakistan on local temperatures and then evaluate the contribution of urban temperatures by comparing with global climate change. Pakistan’s urbanization situation is discussed in section 2. Data and methodology to find the trends over the studied period is presented in section 3. Results are given in section 4 and conclusion and discussion of the study are given in section 5.

PAKISTAN: URBANIZATION AND ENERGY CONSUMPTION According to urban population data of United Nations, Department of Economic and Social Affairs (UNDESA), among major countries of South Asian region, Pakistan has the highest percentage of population living in urban areas. In Pakistan, the share of urban population increased from 17.5% in 1950 to 33.1% in year 2000. It is further guesstimate that in 2050, 59.4% of total population of the country will be living in urban areas (UNDESA, 2011). With urbanization in the country, since 1980s, the demand of energy in urban areas is increase has many folds. The consumption of electricity in 1980 was just 10.15 billion kilowatt-hours which reached to 68.54 billion kilowatt-hours in 2008 (U.S. Energy Information Administration, 2008). To overcome the hot weather effect, the use of Air Conditioner Systems (ACS) is quite common that are one of the major source of emission of anthropogenic heat into urban atmosphere. This extra heat emitted into the urban atmosphere causes further warming of the cities and this process of use of energy and heating up of cities will keep on continuing until the measures and methods are not adopted to reduce the energy consumption especially in urban areas.

DATA AND METHODOLOGY Meteorological data Meteorological data including monthly averages of annual and seasonal temperatures data of minimum (Tn) and maximum (Tx) of 37 meteorological stations of Pakistan for the period of 1950–2004 is collected from Pakistan Meteorological Department (PMD). The classification of the monitoring stations here in this study into urban, tow and rural stations is based on population density, local government administrative status that is done by considering population data and government official reports i.e., census reports (Easterling et al., 1997; Hansen et al., 1999). In many ways, the long time series climatic data are altered by non-climatic factors. Such non-climatic factors hide the real signal of clime change during one specific period (Heino, 1994; Vincent, 1998; Aguilar et al., 2003; Caussinus and Mestre, 2004; Costa and Soares, 2009). Thus, in order to make sure about the quality of climate data, the first stage is to homogenize the data series (Alexanderson and Moberg, 1997). In this study, temperature series of Tn and Tx of 37 observing stations are homogenized by using PRODIGE method (Mestre, 2000). Details of the techniques and processes used in this homogenization process can be studied in details in the Mestre (2000), Caussinus and Lyazrhi, 1997, and in Caussinus and Mestre (2004). Temperature trend computation The focus of this study is on analysis of change in annual and seasonal minimum (dTn) and maximum (dTx) temperatures with time at urban, town and rural stations. The time series quality controlled data of dTn and dTx of 37 stations (17 urban, 7 town and 13 rural) is analysed by using the least square linear regression. In order to significantly ________________________________________________________________________________________________ ISBN 9788895597188

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identify the change in trends because of urbanization, Mann-Kendall test was performed and then the data was divided into two periods of times: 1950-1979 and 1980-2004 (i.e., Chung et al., 2004). It helped us to get the clear picture to understand easily that in which period, there is significant effect of urbanization on temperature trends.

RESULTS Analysis of dTn and dTx Table 1 represents the trends of annual and seasonal dTn and dTx computed for the periods 1950–1979 and 1980–2004. It also presents the trend differences between these two periods (as phase 2 – phase 1). Table 2 represents the percentage of positive trends for dTn and dTx (annual, winter, spring, summer and autumn) based on average trends of all urban, town and rural stations. This table helps us to understand the evolution in temperature trends with changing time. 1950–1979: out of 17 urban stations only 35% of the stations showed positive trends in dTn_An and dTx_An (Table 2). Overall average dTn_An and dTx_An during this period have shown negative trends with -0.011°C/per decade and 0.046°C/per decade, respectively. During phase 1, out of 7 town stations, 57% of the stations showed the positive trends in dTn_An and 71% showed the positive trends in dTx_An. However, during 1950-1979, 77% of the rural stations unexpectedly contrary to the urban and town stations showed the positive trends. For the seasonal variation, see Table 1 and Table 2. 1980-2004: During 1980-2004, dTn and dTx trends remained very significant and more positive than first phase. Annual dTn at 94% of urban stations and annual dTx at 86% of urban stations is observed positive with a growth of 0.427°C/decade and 0.336°C/decade, respectively. In case of town stations, annual and winter dTn at 86% of stations, spring and autumn dTn at 71% of stations and summer dTn at 57% of stations showed positive trends. During this period, dTx at town stations is observed higher than dTn at urban and rural stations. During this phase, at rural stations, contrary of urban and town stations trends, annual and seasonal (except winter) dTn has not shown positive inclinations.

Phase 2 - Phase 1

Phase 2

Type

dTn_An dTn_Wi dTn_Sp dTn_Su dTn_Au dTx_An dTx_Wi dTx_Sp dTx_Su dTx_Au

1950 - 1979

Period

Phase 1

Phase

Urban

-0.0111

-0.0248

-0.0030

-0.0150

-0.0106

-0.0046

-0.0162

0.0076

-0.0241

0.0045

Town

0.0117

-0.0122

0.0243

0.0093

0.0164

-0.0179

-0.0388

-0.0036

-0.0230

-0.0160

Rural

0.0157

-0.0066

0.0244

0.0250

0.0112

0.0021

-0.0122

0.0168

0.0006

-0.0051

1980 - 2004

Table 1: Trends of annual and seasonal temperatures computed for periods 1950-1979, 1980-2004 and trends differences between phase 2 and phase 1. dTn and dTx correspond to minimum and maximum temperatures, An, Wi, Sp, Su, Au to the averaging periods used to compute, respectively, the Annual, Winter, Spring, Summer and Autumn mean trends.

Urban

0.0427

0.0395

0.0597

0.0221

0.0427

0.0336

0.0325

0.0968

-0.0042

0.0081

Town

0.0266

0.0237

0.0411

0.0097

0.0256

0.0487

0.0639

0.0929

0.0120

0.0257

Rural

-0.0046

0.0146

-0.0041

-0.0369

-0.0003

0.0305

0.0524

0.0527

-0.0060

0.0211

Urban

0.0538

0.0643

0.0628

0.0371

0.0533

0.0382

0.0487

0.0892

0.0199

0.0037

Town

0.0149

0.0359

0.0167

0.0004

0.0093

0.0667

0.1027

0.0965

0.0350

0.0417

Rural

-0.0203

0.0212

-0.0285

-0.0619

-0.0115

0.0283

0.0646

0.0359

-0.0066

0.0262

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Table 2: Percentage of positive trends for dTn and dTx (annual, winter, spring, summer and autumn) based on average trends of all urban, town and rural stations. Period dTn_An dTn_Wi dTn_Sp dTn_Su dTn_Au dTx_An dTx_Wi dTx_Sp dTx_Su dTx_Au

URBAN 1950 - 1979 1980-2004 35% 94% 29% 94% 59% 88% 24% 82% 41% 88% 35% 88% 12% 71% 53% 100% 12% 53% 53% 47%

TOWN 1950 - 1979 1980-2004 57% 86% 43% 86% 57% 71% 43% 57% 71% 71% 29% 71% 14% 57% 43% 86% 29% 57% 57% 57%

RURAL 1950 - 1979 1980-2004 77% 62% 46% 62% 100% 54% 69% 23% 62% 62% 62% 85% 31% 100% 77% 100% 54% 38% 69% 77%

Figure 1 highlights the dTn trends as a function of dTx trends observed on 17 urban, 7 town and 13 rural stations for both of the analysed periods. Figure 1(a) shows that during 1950-1979, it is found that majority of the urban stations have negative annual dTn and dTx and majority of the town and rural stations have positive dTn but have negative dTx at majority of the town stations. However, the behaviour of annual dTn and dTx observed during 1980-2004, is seen different than the trends noticed during 1950-1979. During 1980-2004, urban effect is extensively observed on dTn and dTx. Figure 1(b) elaborates that dTn and dTx almost at all the urban stations have positive trends. Like as the urban stations, all the town stations except one station also have shown positive dTn and dTx. Contrary of the period 19501979, many of the rural stations have shown negative dTn and have observed lower dTn and dTx than urban and town stations. Figure 1(c) shows per year average dTn and dTx of all urban, town and rural stations for 1950-1979 and 19802004. It shows clear shift in dTn and dTx urban stations. The dTn and dTx are significant seen at urban stations during 1980-2004 and it is possibly due to the urban effect.

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Figure 1: dTn trends as a function of dTx trends for urban, town and rural stations. Per year trends computed for 1950– 1979 (a) ; for 1980–2004 (b); mean trends computed for all urban, town and rural stations for phase 1 and phase 2 (c). The values of dTn and dTx are in °C/year.

Figure 2 illustrates per year variance in dTn(phase2) – dTn(phase1) as a function of per year variance in dTx(phase2) – dTx(phase1) for each station as well as for average of each type of stations (urban, town and rural stations) for annual and seasonal trends. This type of investigation makes us able to clearly understand the effect of urbanized period (19802004) as compared to non-urbanized period. Figure 2(a) highlights the annual difference dTn and dTx between phase 2 and phase 1. It is very important to note that positive dTn trends at most of the urban stations highlight that during second period, minimum and maximum temperature at urban stations increased higher than the town and rural stations. ________________________________________________________________________________________________ ISBN 9788895597188

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It also shows that dTx is mostly affected by town stations where on average; it is increased more than the urban average. However, the difference in dTn and dTx during the two phases shows that at rural stations dTx increased more than the dTn. Figure 2(a) to figure 2(e) shows the seasonal variance in dTn(phase2) – dTn(phase1) as a function of per year variance in dTx(phase2) – dTx(phase1) for each station as well as for seasonal average of each type of stations (urban, town and rural stations). Figure 2(a) highlights the dTn and dTx difference for annual average; figure 2(b) for winter; figure 2(c) for spring; figure 2(d) for summer; and figure 2(e) for autumn. Based on the difference in annual average of two phases it can be realized that at urban areas, dTn has more prominent trends than dTx. Moreover, it is noticed that during all the seasons, dTn difference in average of all urban stations between the two phases is higher than the difference in average of all town and rural stations. However, dTx difference in average of all town stations between the two phases is higher than the difference in average of all urban and rural stations.

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Figure 2: Illustration of per year variance in dTn(phase2) – dTn(phase1) as a function of per year variance in dTx(phase2) – dTx(phase1) for each station as well as for average of each type of stations (urban, town and rural stations) for annual (a); winter (b); spring (c); summer (d); and autumn (e).

DISCUSSION AND CONCLUSION At global scale, the daily minimum temperature increasing at a faster rate or decreasing at a slower rate than the daily maximum, resulting in a decrease in the diurnal temperature range (DTR) for many parts of the world (Karl et al., 1991; Karl et al., 1993; Trenberth, 2007). Many local studies also have demonstrated that the average temperature of many cities of the world is increasing faster than their surrounding rural areas such as Barrow in Alaska (Hinkel et al., 2003); Göteborg in Sweden (Eliasson and Holmer, 1990), Seoul in South Korea (Kim and Baik, 2002), Karachi in Pakistan (Sajjad et al., 2009), Asian mega cities (Hung et al., 2006) and Mexico city in Mexico (Jauregui, 1997). However, the key issue from a climate change standpoint is whether urban-affected temperature records have significantly biased large-scale temporal trends. Studies that have looked at hemispheric and global scales conclude that any urban-related trend is an order of magnitude smaller than decadal and longer time-scale trends evident in the series (e.g., Jones et al., 1990; Peterson et al., 1999). Urban anthropogenic heat fluxes do not have a direct impact upon global warming however the cities are a very important source of anthropogenic greenhouse gases and thereby contribute indirectly to global warming. On other hand, the impacts of global warming (including its impacts upon human well-being and health, various ecosystems, and on levels of energy and water consumption) may be exacerbated in urban areas (Alcoforado and Andrade, 2008). For 1979 to 2004, the corresponding linear trends at global scale were observed 0.29°C per decade for both maximum and minimum temperature (Vose et al., 2005; Trenberth et al., 2007). In case of Pakistan, nearly during the same period (1980-2004), the corresponding linear trend at urban scale was observed 0.43°C/decade and 0.33°C/decade ________________________________________________________________________________________________ ISBN 9788895597188

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for minimum and maximum temperature, respectively. It shows that increase in minimum temperature at urban areas of Pakistan is 0.14°C/decade greater than the increase in global minimum temperature (0.43°C vs 0.29°C per decade, respectively). However, the increase in maximum temperature at urban stations of Pakistan is nearly close to the increase in global maximum temperature (0.33°C vs 0.29°C, respectively). The extra increase in minimum temperature at urban stations of Pakistan as compare to increase in global minimum temperature can be the direct result of local urban effect that caused the phenomenon of UHI. Depending on the functionality, structure, sizes, building material and location of a city, the UHI greatly vary from city to city. So, to understand the fact of increasing minimum temperature faster than maximum temperature at urban areas, the study is progress to see the effect of building height, city size and urban vegetation fraction.

ACKNOWLEDGEMENT: Prof. Enric Aguilar (Spain), Higher Education Commission and University of Sargodha (Pakistan) Réseau Alsace de Laboratoires en Ingénierie et Sciences pour l'Environnement (REALISE) and Région Alsace (France) and Pakistan Meteorological Department (Pakistan).

REFERENCES: Aguilar E, Auer I, Brunet M, Peterson TC, Weringa J. (2003) Guidelines on Climate Metadata and Homogenization, World Climate Programme Data and Monitoring, WMO/TD No. 1186, World Meterorological Organization, Geneva, 51 pp Alcoforado M.J, Andrade H (2008) Global warming and the urban heat island. Urban Ecology, 3: 249–262. Alexanderson H, Moberg A (1997) Homogenization of Swedish temperature data. Part 1: Homogenization for linear trends. Int J Climatol., 17: 25–34. Aniello C, Mogan K, Busbey A, Newland L (1995) Mapping micro-urban heat island using LANDSAT TM and GIS. Computers & Geoscience. 21:965–969. Bacci P, Maugeri M (1992) The urban heat island of Milan. Il Nouvo Cimento 15C:417-424. Bounoua L, Safia A, Masek J, Peters-Lidarad C, Imhoff ML (2009) Impacts of urban growth on surface climate: Acase study in Oran, Algeria. J. Appl. Meteorol., 48: 217–231. Caussinus H and Lyazrhi F (1997) Choosing a linear model with a random number of change-points and outliers. Ann. Inst. Statist. Math. 49: 761–775. Caussinus H, Mestre O (2004) Detection and correction of artificial shifts in climate series. App. Statist. 53: 405–425. Chung U, Choi J, Yun J.I (2004) Urbanization effect on the observed change in mean monthly temperatures between 1951-1980 and 1971-2000 in Korea, Climatic Change 66: 127–136. Costa AC, Soares A (2009) Homogenization of climate data: Review and new perspectives using geostatistics. Math Geosci., 41: 291–305. Easterling D.R, Horton B, Jones P.D, Peterson T.C, Karl T.R, Parker D.E, Salinger M.J, Razuvayev V, Plummer N, Jamason P, Folland C.K (1997) Maximum and minimum temperature trends for the globe. Scinece 277: 364–367. Eliasson I, Holmer B (1990) Urban Heat Island Circulation in Goteborg, Sweden. Theor. Appl. Clirnatol. 42: 187–196. Grimmond C.S, King T.S, Cropley F.D, Novak D.J, Souch C (2002) Local-scale fluxes of carbon dioxide in urban environments: Methodological challenges and results from Chicago. Environ. Pollut., 116: S243–S254.

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Hansen J, Ruedy R. Glascoe J, Sato M (1999) GISS analysis of surface temperature change. J Geophys Res., 104: 30997–31022 Heino R (1994) Climate in Finland during the period of Meteorological observations, Finnish Meteorological Institute Contributions 12 Academic dissertation, Helsinki, 209 pp. Hinkel K.M, Nelson F.E, Klene A.E, Bell J.H (2003) The urban heat island in winter at Barrow, Alaska. Int. J. Climatol. 23: 1889–1905. Hung T, Uchihama D, Ochi S, Yasuoka Y (2006) Assessment with satellite data of the urban heat island effects in Asian mega cities. International Journal of Applied Earth Observation and Geoinformation 8: 34–48. Jauregui E (1997) Heat island development in Mexico city. Atmospheric Environment, 31(22): 3821–3831. Jones P.D, Groisman P.Y, Coughlan M, Plummer N, Wang W-C, Karl T.R (1990) Assessment of urbanization effects in time series of surface air temperature over land. Nature, 347: 169–172. Karl T.R et al., (1991) Global Warming: Evidence for asymmetric diurnal temperature change. Geophysical Research Letter 18(12): 2253–2256. Karl T.R, Jones P.D, Knight R.W, Kukla G, Plummer N, Razuvayev V, Gallo K. P, Lindseay J, Charlson R, Peterson T.C (1993) A new perspective on Recent Global Warming: Asymmetric trends of daily maximum and minimum temperature. Bull. Am. Meteorol. Soc. 74: 1007–1023. Kim Y.H, Baik J.J, (2002) Maximum urban heat island intensity in Seoul. J. Appl. Meteorol., 41: 651–659. Landsberg H.E (1981) The urban climate. Academic, New York. Liu W, Ji C, Zhong J, Jiang X, Zheng Z (2007) Temporal characteristics of the Beijing urban heat island, Theor. Appl. Climatol. 87: 213–221. Martilli A (2003) A Two-dimensional numerical study of the impact of a city on atmospheric circulation and pollutant dispersion in a coastal environment. Boundary Layer Meteorol., 108: 91–119. Martilli A, Roulet Y.A, Junier M, Kirchner F, Rotach M, Clappier A (2003) On the impact of urban surface exchange parameterisations on air quality simulations: the Athens case, Atmos. Environ., 37: 4217–4231. Mestre O (2000) Methodes statistiques pour l’homogeneisation de longues series climatiques. PhD thesis, L’universite Paul Sabatier de Toulouse. Oke T.R (1997) Urban climate and global environmental change. In R.D. Thompson and A. Perry, Applied climatology: principles and practices (pp. 273-287). Routledge, New York. Peterson T. C, Gallo K. P, Lawrimore J, Owen T. W, Huang A, McKittrick and D. A (1999) Global rural temperature trends. Geophys. Res. Lett., 26: 329–332. Quattrochi D.A, Ridd M.K (1994) Measurement and analysis of thermal energy responses from discrete urban surfaces using remote sensing data. Int J Remote Sens., 15: 1991–2022. Sajjad S.H, Hussain B, Khan M.A, Raza A, Zaman B, Ahmed A (2009) On rising temperature trends of Karachi in Pakistan. Climatic Change, 96: 539–547. Shepherd J.M, Burian S.J (2003) Detection of urban-induced rainfall anomalies in a major coastal city. Earth Interactions, 7: 1–17. Trenberth, K.E., P.D. Jones, P. Ambenje, R. Bojariu, D. Easterling, A. Klein Tank, D. Parker, F. Rahimzadeh, J.A. Renwick, M. Rusticucci, B. Soden and P. Zhai (2007) Observations: Surface and Atmospheric Climate Change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. ________________________________________________________________________________________________ ISBN 9788895597188

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Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. U.S. Energy Information Administration (2008) Energy statistics on Pakistan during 1980 to 2008. http://www.eia.gov/countries/country-data.cfm?fips=PK#undefined UNDESA (United Nations, Department of Economic and Social Affairs), Population Division (2011): World Population Prospects: The 2010 Revision. New York, http://esa.un.org/unpd/wup/index.htm Vedal S (1997) Ambient particles and health: Lines that divide. J. Air & Waste Manage. Assoc., 47: 551–581. Vincent L (1998) A technique for the identification of inhomogeneities in Canadian temperature series, J Climat., 11: 1094–1104. Vose R.S, Easterling D.R, Gleason B (2005) Maximum and minimum temperature trends for the globe: An update through 2004. Geophys. Res. Lett., 32, L23822, doi:10.1029/2004GL024379. World Urbanization Prospects: The 2005 Revision, Department of Economic and Social Affairs, United Nation Population Division, http://www.un.org/esa/population/publications/WUP2005/2005wup.htm Yagüe C, Zurita E, Martinez A, (1991) Statistical analysis of the Madrid urban heat island. Atmos Environ., 25: 327– 332. Yin D, Zhiqing X, Yan Z, Yafeng S., Jingang W (2007) Impact of urban expansion on regional temperature change in the Yangtze River Delta. J Geog Sci., 17: 387–398.

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FIRST FINDINGS ON THE THERMAL REGIME OF THE BIGGEST LIVING WALL IN EUROPE (ROZZANO, ITALY) Panosetti D., Nardino M. IBIMET CNR Bologna, Via Gobetti 101, 40129 Bologna, Italy.

Summary The present work is developed in the frame of the PRIN-SENSE National Project, whose aim is to study the impact of building green envelope on the urban environment. In this case, particular emphasis is put on the role of green walls inthe mitigation of heat waves in the city of Milan (Italy). The urban heat island, its main aspects and impact on the urban environment have been taken into account considering literature studies in Barcelona, New York City and, of course, Milan. Green walls and roofs can provide environmental benefits in several ways:shading (preventing sunlight from reaching the underlying roof membrane), aircooling by using heat from the air to evaporate water (evapotranspiration),energy use reduction, air pollution and greenhouse gases absorption, humanhealth and thermal comfort improvement, stormwater management and water quality enhancement. The greatest living wall in Europe (Rozzano, Italy) has been chosen as case study to better analyze the thermal regime of such a structure and modeling its role in the mitigation of an urban heat island. Data of air temperature and humidity in the wall canopy, vertical wind speed and thermal images were collected on September, the 17th 2012. First results about the differences in surface temperature with a concrete wall are here presented together with the diurnal dynamic of the wall surface temperature gradient. A modeling point of view is also considered including a brief description of two models (TownScope and ENVI-met) that can be of help in such studies.

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IMPACT OF THE CITY STREETS ON CITY TEMPERATURES STREETS OF ERBIL CITY AS A CASE STUDY A. M. A. Kaka Shekh Naqshbandi University of Salahaddin, Erbil, Iraq

INTRODUCTION: This study aims to clarify the impact of the city streets on the temperatures in general, and impact of Erbil city streets on the temperatures of the city in particular. The importance of this study can be found in the following points: 1 – Impact of cities climate on the convenience of residents whose numbers are increasing year after year. 2 – Streets occupy large proportion of the area of the cities. This rate reached in 1960 in U.S. cities with populations of more than (100) thousand and more than (250) thousand people (17.5%) and (18.3%), respectively. (1) 3 - The cities, its installation and activities, a major cause of climate change and global warming. To achieve the objectives of the study the temperature of the air in (7) main streets, (Ring & Radial), and areas adjacent to them, located on both sides of the streets at a distance of (50) and (100) meters in different parts of the city was measured. (Fig.1).The process of this measurement took place during different times of winter month's days and under good and cloudy weather conditions. The nature of the study requires being on the following themes: First: Impacts of the city streets on the temperature. Second: Erbil city and its streets. Third: Impacts of Erbil city streets on the temperature.

FIRST: IMPACTS OF THE CITY STREETS ON THE TEMPERATURE City streets contribute largely to raise the temperature of the cities, because: 1 - The nature of streets formation. Streets, in most cases, format of asphalt, concrete and bricks. Studies have shown that temperature of the lands covered with asphalt is (13) 0 c more than the temperature of the cultivated lands. (2) 2 - The streets are often surrounded by high buildings and apartment blocks, consisting of stones, brick, concrete, glass and mineral materials, which contribute significantly to the production of heat. Studies show that heat conduction capability of building materials in the cities is (3) times more than heat conduction capability of the soil. (3) 3 – High buildings surrounding streets impede the movement of air. These high buildings surrounding streets sometimes even cause calmness and prevent dispersal of the heat generated by the street and by means of transportation passers by. 4 – High density of traffic on the streets, cars in particular, contribute significantly to increase of greenhouse gases and thus to raise the temperature in the cities.

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Fig1 Erbil streets

The role of city streets in increasing the temperature of the cities varies from one street to another. It depends on several factors. The following are some of important ones: 1 - The shape and direction of the streets affect the movement of air. 2 - The breadth of the streets affects the movement of air and the flow of traffic on the street. ________________________________________________________________________________________________ ISBN 9788895597188

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3 - The nature of street configurations affects their ability to produce heat and heat conduction capability. 4 – Edifices and buildings morphology and Pattern of building forms surrounding streets affects the movement of air and production of heat. 5 - The density of vegetation, (vegetable cover condition), on the streets, (in what we call, middle islands and on the sides of the street). Increase in density of vegetation leads to reduce the contribution of the streets to raise the temperature and vice versa. 6 - Density of traffic (cars), on the streets. Increase in density of traffic causes increases the contribution of the streets to raise the temperature and vice versa.

SECOND: ERBIL CITY AND ITS STREETS: Erbil city and its streets Can be defined through the following points: 1 - Erbil is the oldest city in the world where life has continued without interruption. Historically they have been around and have been inhabited for five thousand years BC, at the very least. (5) 2 - The city of Erbil is located at the intersection of longitude eastward 44:00 and 36:11 north latitude, and thus is located in the southern part of the northern temperate zone away from the water bodies. 3 - Today Erbil is the center of Erbil Governorate, (Province), and the capital of Kurdistan Region of Iraq. 4 - The area of the city of Erbil, in 2010, was about (133) sq. km. and the number of inhabitants was more than (750) thousands people during the same year. (6) 5 - The city of Erbil occurrence in the plain area, (Erbil Plain). The city land descend from the north-east towards the south-east and reach a height in the city center (412) m. above sea level. 6 - Erbil Citadel is located in the center of the city, it served as the nucleus of the city that grew around it. Erbil Castel is the oldest part of the city with height of (26.5) m. from the rest of the city center. (7) 7 - The climate of the city of Erbil, as well as the climate of the Erbil Plain in which the city is located, is characterized by, continental and a semi-arid climate. The system of rainfall is like Mediterranean climate in terms. That means the climate of the city is characterized by, (hot and dry summers and mild rainy winters), where the climate is of type (BSsh) according to Koppen classification. Location of Erbil city within the, semi-arid climate on the one hand and its proximity to the region of the dry climate of the south and west on the other hand, as well as its continental location causes: • Exposing the city to dust storms from the south and west, especially in summer and autumn. • Occurring phenomenon of the repetition of drought, lack of rainfall compared to the annual rates, to the city and surrounding areas. • Displaying the city and surrounding areas to the phenomenon of desertification, which its appearances began to emerge during the last three decades. 8 - In terms of urban structure, the city of Erbil with a binary structure that combines the old and the modern and the fabric is composed of a variety of buildings and streets. Most of the homes in the old parts of the city, which constitute a small percentage of building space, have oriental style and built of mud, clay, plaster and single-floor. Unlike the old neighborhoods, shops and buildings of modern parts are of many floors, especially residential buildings, hotels and malls which have been built in the present century. Materials used for building the modern structures are of iron, aluminum, glass, cement, bricks and concrete blocks. 9 – Erbil city has modest industrial activity. 10 - Green space occupy's only (% 4.6) of the total area of the city. (8) (Fig. 2).

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Fig. 2 Land Use in Erbil City

Green space Streets Others

In terms of the streets of Erbil city it can be define through the following points: 1 - Erbil street occupation is (% 15.7) of the total area of the city. 2 - There are three kinds of street systems in the city of Erbil. They are: 3- The ring and semi-ring streets. 4 - Radial streets.(The streets that come out from the city center and nearby bodies outward). 5 - Organic streets.(The streets that are scattered in residential neighborhoods).

3 – Erbil main streets vary in terms of their properties, (radial or ring pattern, breadth, morphology of streets and surrounding buildings, vegetation density and density of traffic to). Table (1) illustrates some of these variations in the properties of the streets included in the study. Table 1Some characteristics of the streets included in the study Name of street

Pattern of street

Breadth (meter)

Streets formation

Density of vegetation

Density of traffic (car/minute)

(30) Meters

Ring streets

30

asphalt & concrete

very poor

45

(60) Meters

Ring streets

60

asphalt & brick

good

66

(100) Meters

Ring streets

100

asphalt & concrete

very poor

27

(Bahraka)

Radial streets

30

asphalt & concrete

very poor

71

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(Makhmur)

Radial streets

60

asphalt & concrete

very poor

107

(Kirkuk)

Radial streets

60

asphalt & concrete

very poor

32 *

(Koya)

Radial streets

60

asphalt & concrete

poor

120

Source: Field study.

The low density of traffic on the street (Kirkuk) is due to the presence of maintenance work in some sections of the street during the field study for the measurement of temperature and traffic on the street.

THIRD: IMPACTS OF ERBIL CITY STREETS ON THE TEMPERATURE The results of measuring the air temperature above the streets included in the study and nearby areas at a distance of (50) and (100) meters, which depending on it explain impacts of Erbil streets on the temperature of the city, it is incorporated in tables (2) and (3).

According to data contained in Table (2):

1 – The average temperature of the air above the streets in all cases is more than the average air temperature above the nearby areas. The average of air temperature at a distance of 50 meters and 100 meters from the street is below the average of the air temperature above the street by (1.2) and (1.7) (° C) , respectively (Fig. 3 a & 3 b). This discrepancy between the rates of air temperature above the streets and nearby areas is a result of large possibility of street configurations and traffic on it for heat production.

2 - The differences between the rate of air temperature above the radial streets and average of air temperature above the nearby areas are greater than the differences between the rate of air temperature above the ring streets and nearby areas (Fig. 3 b). These thermal differences between the radial streets and areas away from streets at a distance of (50) meters and (100) meters reach (1.4) and about (2) (° C) respectively, while the low thermal differences between the ring streets and nearby areas at the same distances is (1) and about (1.4) (° C) respectively. This variation in the amount of decrease in the rates of temperature between each of the streets, (radial and circular), is due to the immense expansion of some of the ring streets and lack of density of traffic out, (street 100 meters), and the increase in density of vegetation on the (60 meters) street, compared to other streets. Table 2 Rate of decrease in temperature away from streets (°C) Name & pattern of street

Rate of decrease (good weather)

Rate of decrease (cloudy weather)

Rate of decrease

At a distance of (50) meters

At a distance of (100) meters

At a distance of (50) meters

At a distance of (100) meters

At a distance of (50) meters

At a distance of (100) meters

(30) Meters (Ring)

1.59

2.20

0.62

0.78

1.11

1.49

(60) Meters

1.42

1.97

0.63

0.92

1.03

1.45

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(Ring) (100)Meters (Ring)

1.37

1.52

0.32

0.72

0.85

1.12

Bahraka (Radial)

2.58

3.08

0.53

1.15

1.56

2.12

Makhmur (Radial)

2.25

3.08

0.58

1.03

1.42

2.06

Kirkuk (Radial)

1.32

1.83

0.85

1.07

1.09

1.45

Koya (Radial)

2.30

3.02

0.75

1.32

1.53

2.17

Rate of Ring streets

1.46

1.90

0.52

0.81

1.00

1.35

Rate of Radial streets

2.11

2.75

0.68

1.14

1.40

1.95

Rate of streets

1.83

2.39

0.61

1.00

1.23

1.69

Source: Field study.

3 - Relatively there is a large difference in the amount of decrease in temperature away from the street under the good weather and cloudy weather. The amount of decrease in temperature away from the street for a distance of (50) meters under good weather is around (3) times more than amount of decrease under cloudy weather and about (2.4) twice for a distance of (100) meters away from the street. This large variation in the amount of decrease in temperature away from the street under the good weather and cloudy weather confirms the known fact that the characteristics of local climate, (including characteristics of the street climate), is manifested in the good weather and almost disappear in the cloudy weather.

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Fig. 3 a Rate of decrease in temperature away from streets 2.5

Temperature (° C)

2

1.5

At a distance of (50) meters At a distance of (100) meters 1

0.5

0 (30) Meters (Ring)

(60) Meters (Ring)

(100)Meters (Ring)

Bahraka (Radial)

Makhmur (Radial)

Kirkuk (Radial)

Koya (Radial)

Streets

Fig. 3 b Rate of decrease in temperature away from streets

2.5

Temperature (° C)

2

1.5

At a distance of (50) meters At a distance of (100) meters 1

0.5

0 Rate of Ring streets

Rate of Radial streets

Rate of streets

Streets

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Fig. 3 a Rate of decrease in temperature away from streets at a distance of (50) meters 3

2.5

Temperature (° C)

2

good weather

1.5

cloudy weather

1

0.5

0 (30) Meters (60) Meters (100)Meters (Ring) (Ring) (Ring)

Bahraka (Radial)

Makhmur (Radial)

Kirkuk (Radial)

Koya (Radial)

Rate of Ring streets

Rate of Radial streets

Rate of streets

Streets

Fig. 3 b Rate of decrease in temperature away from streets at a distance of (100) meters 3.5

3

Temperature (° C)

2.5

2 good weather cloudy weather 1.5

1

0.5

0 (30) Meters (60) Meters (100)Meters (Ring) (Ring) (Ring)

Bahraka (Radial)

Makhmur (Radial)

Kirkuk (Radial)

Koya (Radial)

Rate of Ring streets

Rate of Radial streets

Rate of streets

Streets

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4 – Variation in the contribution of the streets included in the study in increasing the temperature of the air led to variation in decreasing amount of temperature away from the street. The biggest decline in temperature away from the street is found in each of the streets (Bahraka , Makhmur and Koya) which are all radial streets and the least in the ring street (100 meters). This variation in the amount of decrease in temperature away from the streets included in the study is due to the variation in the characteristics of these streets in terms of patterns, breadth, density of vegetation and density of traffic upon the street which is shown in the table (1). 5 - The impact of the streets to raise the temperature least whenever we with moved away from the streets. The study showed that the rate of the impact of Erbil streets on raising the temperature in a second (50) meters, (50 - 100) away from the streets, is only (38%) their impact in the first (50) meters, (01 - 50) away from the streets, and this ratio falls to only (30%) under good weather.

According to the data contained in Table 3: 1 - In most cases rates of decline in temperature away from the radial streets during all times are greater than the rates of decrease in temperature away from the ring streets. 2 - Under the good weather conditions, which characteristics of the street climate exemplary shown the highest rate of decrease in temperature away from the street, record in the 12 noon and the least in 8 am. Recording the highest decrease in temperature during noon in line with the ideal time for the emergence of local climate during the day time, (13 am). (11) (Fig. 4)

Table 3 Decreasing in temperature away from streets during different times of the day (°C )

Pattern & name of street

Decreasing in temperature ( 8 am )

Decreasing in temperature (12 noon)

Decreasing in temperature (16 pm )

good weather

cloudy weather

good weather

cloudy weather

good weather

cloudy weather

distance of

distance of

distance of

distance of

distance of

distance of

50 M.

100 M.

50 M.

100 M.

50 M.

100 M.

50 M.

100 M.

50 M.

100 M.

50 M.

100 M.

Ring streets (30)M.

1.11

1.90

0.75

0.75

0.75

0.95

0.50

0.75

2.90

3.75

0.60

0.85

Ring streets (60)M.

2.00

2.25

1.00

1.25

1.15

1.65

0.55

0.75

1.10

2.00

0.35

0.75

Ring streets (100)M.

0.75

0.80

0.35

0.75

2.00

2.25

0.25

0.45

1.35

1.5

0.35

0.95

Radial streets (Bahraka)

1.50

1.75

0.85

1.20

3.50

4.00

0.40

1.50

2.75

3.5

0.35

0.75

Radial streets (Makhmur)

2.00

2.75

0.25

0.50

3.00

4.00

0.75

1.50

1.75

2.50

0.75

1.10

Radial streets (Kirkuk)

1.00

1.50

0.75

0.85

1.95

2.75

1.05

1.50

1.00

1.25

0.75

0.85

Ring streets

3.00

3.5

0.75

1.20

2.75

4.10

0.75

1.50

1.15

1.45

0.75

1.25

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(Koya) Rate of Ring streets

1.29

1.65

0.70

0.92

1.30

1.62

0.43

0.65

1.78

2.42

0.43

0.85

Rate of Radial streets

1.88

2.38

0.65

0.94

2.80

3.71

0.74

1.50

1.66

2.18

0.65

0.99

Rate of streets

1.62

2.06

0.67

0.93

2.16

2.81

0.61

1.14

1.71

2.28

0.56

0.93

Source: Field study.

Fig. 4 Decreasing in temperature away from streets during different times of the day 3

2.5

Temperature (° C)

2

At a distance of (50) meters

1.5

At a distance of (100) meters

1

0.5

0 ( 8 am )

(12 noon)

(16 pm )

Different times of the day

3 - Times of recording the highest and lowest decreases in temperatures away from the streets varied due to the pattern of the streets. The highest rate of decrease in temperature away from the radial streets is recorded in the (12 noon) and the lowest at (16 pm) while in the ring streets is the highest rate of decline recorded at (16 pm) and lowest at (8 am) (Fig. 5 a & 5 b). This variation in the times of recording the highest and the lowest rate of decrease in temperature away from the streets between radial and ring streets back to the variance in the function of these streets that affect the variation in times of high and low traffic density on the streets. 4 - During all times of the day and in all the streets the amount of decrease in temperature away from the streets under the good weather is more than the amount of decrease under the cloudy weather.

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Times of recording the highest and lowest decreases in temperatures at a distance of (50) meters and (100) meters away from the streets Fig. 5 a. At a distance of (50) meters 3

2.5

Temperature (° C)

2

Rate of Ring streets

1.5

Rate of Radial streets

1

0.5

0 ( 8 am )

(12 noon)

(16 pm )

Different times of the day

Fig. 5 b At a distance of (100) meters 4

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CONCLUSIONS AND RECOMMENDATIONS: The study reached the following conclusions: 1 - Erbil streets, with their area of about (16%) of the total area of the city contribute to raise the city temperature around (0.2) (° C). 2 - The contribution of Erbil streets to raise the city temperature in good weather conditions rise up to (0.33) (° C) and falls down under the cloudy weather conditions to only (0.13) (° C). 3 - The effect of Erbil streets on the temperature which varies from one street to another is due to the differences in their characteristics. 4 - The effect of Erbil streets on the temperature varies during different times of the day (morning, noon and evening). The study recommends the following: 1 - Conducting new studies to know the effect of Erbil city streets on temperatures of the city during the other seasons of the year and during night times. 2 - Increasing the density of vegetation cover on the streets of Erbil city and in the surrounding areas of the street. 3 - Reducing the density of traffic on the streets of Erbil by: •

- Reducing the use of cars inside the city.

• - Achieving a high flow of traffic in the city through the expansion of streets and building bridges and tunnels on the streets.

REFERENCES Murphy, Raymond E., The American City – An Urban Geographu, New York, 1971, p. 281. Naqshbandi, Azad M. A. Kaka Shekh, Local Climate, Erbil, 2010, p. 171. (In Kurish). Al. Rawi , Aadel & Al. Samarrie , Kousay A. , Applied Climatology , 1990 , P. 367. (In Arabic). Naqshbandi, Azad M. A. Kaka Shekh, Global Warming and its Effects on Iraqi Kurdistan Region, Erbil, 2008, pp. 38 – 44. (In Kurdish). Chaoshley, Hadi, Erbil's historic heritage, Mosul, 1985 p. 18. (In Arabic). Naqshbandi, Azad Mohammed Ameen Kaka Shekh, Geographical Analysis of Open (Green) Spaces In The City Of Erbil by Using GIS Techniques, Zanco, Journal, Salahaddin University, No. (50), Erbil, 2011, p. 371. (In Arabic). Sharif, Azad Jalal, Erbil Area Climate, Ph.D. Thesis, Salahaddin University, Erbil, 1998, p. 9. (In Arabic). Naqshbandi, Azad M. A. Kaka Shekh , Op.cit. 2011, p. 379. Kak Ahmed , Huner Abdulla , Urban Land Use Changes in Erbil City From 1985 – 2002 by Using GIS & Remote Sensing Techniques , M.A. Thesis, Salahaddin University, Erbil, 2006 , P. 86. (In Arabic). Naqshbandi, Azad M. A. Kaka Shekh , Op.cit. 201o, p. 25. Hedid, A. S., Al. Heseni, F. B. & Al. Aani, H. T., Local Climate, Mosul, 1982, P. 36. (In Arabic) .

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CLIMATE EXTREMES IN URBAN AREA AND HUMAN HEALTH: THESUMMER HEAT WAVES Baldi M. National Research Council – Institute of Biometeorology, CNR-Ibimet, Via Taurini 19, Rome, Italy

[email protected]

Summary In the last 100 years the average temperature at global scale has increased by approximately 0.74°C and is projected to continue to rise at a rapid rate. Since 1880, nine of the ten warmest years are in the 21st century, the only exception being 1998, which was warmed by the strongest El Niño of the past century. One of the consequences of the observed changes in the climate is an increase in the frequency and intensity of extremely hot days, which represent an health risk specially in largely populated areas, as documented for several regions in the world, including the Euro-Mediterranean region. If it is still under discussion if such heat wave episodes are a direct result of the warming of the lower troposphere, or more likely, they are a regional climate event, some Authors analyzed the heat episodes in order to define their correlation with large scale atmospheric patterns and with changes in the regional circulation. Despite the undergoing discussion about the causes and spatio-temporal extension of the episodes, epidemiological studies have shown that these conditions pose increasing health risks inducing heat-related diseases including hyperthermia and heat stress, cardiovascular and respiratory illnesses in susceptible individuals with a significant increase in morbidity and mortality. In several Mediterranean cities (Athens, Barcelona, Rome, among others), summer peaks of mortality associated with extremely high temperature (and humidity) have been documented showing that, in some of the events, an increase in daily mortality up to 100% has been reached compared to the average for the period. The summer 2003 heat wave in Europe resulted in an estimated excess of fatalities ranging from 22000 to 50000 (more than 15000 fatalities in France alone). The summer of 2003 was also unusually hot across much of Asia, and Shanghai recorded the hottest summer in over 50 years. Shanghai is particularly prone to extreme heat waves which usually result in elevated death tolls: during the intense and prolonged heat wave occurred in 1998 for several days (3 consecutive episodes for a total of 27 days), the daily number of deaths in the city was over three times the daily summer average. In more recent years it was noticed a lower number of fatalities during heat wave episodes due, probably,to some socioeconomic factors, such as the air-conditioning usage, the adoption of health risk warning systems, however other environmental factors such as air pollution combined with extreme weather conditions can exacerbate the effects and increase the risk for human wellness. This study aims to describe the occurrence of heat wave episodes and the effects, in terms of mortality, of high temperatures and humidity on the urban population for some recent episodes in the Mediterranean region.

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THE CONTRIBUTION OF BUILT ENVIRONMENT TO THE FORMATION OF URBAN CLIMATE IN GREEK CITIES Papamanolis N. Department of Architectural Engineering, Technical University of Crete El. Venizelou 127 (former French School), 73133 Chania Phone +302821037106

[email protected]

Summary The Greek cities, regardless of their differences in sizes, have similar town-planning characteristics. In addition, the buildings inside them have similar and specific architectural and constructional features and operating characteristics. For instance, in their common feature they are included the dense construction, the lack of urban green areas, the relative equal-height structures, the relatively high roughness of the building surfaces, the increased albedo, the burning products and photochemical reactions as the main components of their atmospheric pollution. These features inevitably reflect on the characteristics of the urban climate in Greek cities and differentiate them from the relevant urban climate characteristics in urban environments in other regions of the planet. This work identifies and presents these features and examines their influence on the shaping of urban climate in the Greek cities.

Keywords: built environment, city, Greece, urban climate

INTRODUCTION The urban climate, as the transformation result of the climate in a region, has features that are formed by the urban environment to which it refers and the activities that take place in this environment. The urban environment, in turn, is analysed into urban-planning and architectural features. These features affect, by specific mechanisms and processes, important meteorological factors like radiation, temperature, humidity, wind etc. Therefore, it is logical that, in contradiction with other types of climate which are based on geographical data only, the study of the urban climate in a region should take into account the characteristics of the structures and activities of people in this region. The key features of the built environment with effect in shaping climatic factors are: The form of the structures, the surfaces albedo, the heat capacity of the construction materials, the water permeability of the soil. Heat island development for example can be attributed to a number of factors including construction materials of high heat capacity and low solar reflectivity such as asphalt and concrete, reduced turbulent heat transfer and long-wave radiative heat loss due to street canyons geometry, reduced latent heat loss by evaporation due to the replacement of the natural green surfaces with dry surfaces and increased anthropogenic heat emissions into the urban atmosphere. The intensity of the Urban Heat Island is reflected by the temperature differences between urban and rural sites and depends on the size, population and industrial development of a city, topography, physical layout, regional climate and meteorological conditions. Similar features have similar influences and lead to similar results.

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In Greece, the basic town-planning characteristics of large cities as well as the architectural and constructional characteristics of buildings in this urban environment display notable similarities (Papamanolis, 2005). Several of these similarities, related either to design choices or to constructional choices, extend largely to elements that determine the influence on the characteristics of urban climate. This work, identifies and examines these elements and, insofar as the available data permits, investigates their impact in the formation of the urban climate in Greek cities.

THE MAIN CHARACTERISTICS OF URBAN CLIMATE IN GREEK CITIES. Greece, with an overall land area of approx. 132,000 km2, is situated in the south-eastern part of Europe. Greece consists, by the four-fifths of its mainland, of mountainous terrain, while it is also a maritime country with numerous islands and a coastline of over 15,000 km in length. The country’s population stands at about 11 million (EL.STAT. 2012). The bulk of this population (i.e. about 59%) lives in urban areas. Most urban centres and the largest of them, including the conurbation of the capital, Athens, with a population of about 4 million, and the second largest city, Thessaloniki, with a population of about 1 million inhabitants, lie on the coast. The climate in Greece is predominantly Mediterranean. However, due to the country's unique geography, Greece has a remarkable range of micro-climates and local variations. The north areas of Greece have a transitional climate between the Continental and the Mediterranean climate. There are mountainous areas that have an Alpine climate. Characteristics of urban climate in Greece are found mainly in the Attica basin, where the cities of Athens and Piraeus, in the area of Eleusis (Thriasio pedio) with large industrial facilities, and in the area of Thessaloniki in northern Greece (Zabakas, 1981). Figure 1: A satellite image of the Attica basin with the cities of Athens (1) and Piraeus (2) and of the industrial zone of Eleusis (3).

3 1 2

In the Athens region, the characteristics of urban climate start appearing after 1945, when the stream of urbanization in Greece became more intense. In particular, it has be observed that: - Increasing trend of hourly temperature values. The daily trend of the variation of the mean hourly temperature values in the 1946-1975 period as opposed to 1894-1929 appears an increase along the entire 24-hour day, excluding the first morning hours following the sunrise. The increase is greater during the afternoon and evening hours, reaching 0.5 °C in average (Zabakas, 1981). Since the middle 70's there has been a continuous tendency for hotter summers in the area of ________________________________________________________________________________________________ ISBN 9788895597188

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Athens. The city started experiencing quite sudden extreme heat from the beginning of 1990's. It seems that there is an increasing tendency in the city for longer periods of maximum air temperatures of more than 36°C (Santamouris, 2001). - Increasing trend of irradiation. For the 1955-1995 period rise of irradiation by 5.2% was recorded. During hot months, despite the significant rise of irradiation, there is a decrease in sunlight. This is due to the big concentration of atmospheric pollutants in the atmosphere of Athens, from anthropogenic activities, which increases in summer due to the extensive use of air-conditioning systems. This increase of irradiation is one of the reasons for the rise of air temperature in Athens, in recent years (Sachsamanoglou, 1999). - Appear of urban heat island phenomenon that, based on studies of the 1980s, show the greatest intensities during the nighttime. These intensities reach +3°C during the cooling period and +3.5°C during the heating one. On the contrary, during the pre-noon and noon hours, negative intensities in the magnitude of 1.5 – 2°C are recorded (Katsoulis and Theoharatos, 1985). More recent and more in-depth studies on the phenomenon detect levels of urban heat island as strong as exceeding 10°C in extreme cases in central Athens during daytime and up to 5°C during the night (Santamouris et al., 2001). - Considerable increase in drought days. From the comparison of observations for the 1871-1900 and 1941-1970 periods an increase in drought days by 14.9% has been recorded (Zerefos et al., 1977). Since 1925 (period when the city expanded on forests of the area and rivers and the number of buildings increased dramatically in the greater area of the city) the rainfall in the area of Athens has been decreased by 10%. On the contrary, an increase in the frequency of storms has been recorded. - Reduction of wind speed on the surface. The reduction is recorded during the entire 24-hour day and is more intense in high-density areas. At a local level, the wind direction follows the direction of the main road network as moving air is channelled and accelerated in urban canyons (Niachou et al., 2005). - Significant increase in levels of air pollution. Air pollution began to be a problem in Athens after World War II, due to a burgeoning rate of industrialization, intense urbanization, and economic growth in combination with the meteorological conditions in the area that favor photochemical reactions. Some years ago the main sources of air pollution in Athens were industry, automobile traffic and central heating during the cold months (Dassenakis, 2000). A number of measures for the improvement of air quality that were introduced by the government in 1994 and 1995 (fuel quality improvement, motor vehicle reduction, public transport promotion, natural gas use for heating), have already shown some positive results. Studies on the urban heat island effect in the area of Thessaloniki show that it is stronger in the nighttime than in the daytime and decreases with increasing wind speed, while there are indications that it is more pronounced during the warm half of the year. Observations of the maximum urban heat island intensity in Thessaloniki range from 2°C to 4°C and from 1°C to 3°C during the warm and the cold part of the year, respectively, showing a smaller variability during the summer moths than in the winter (Giannaros and Melas, 2012). Studies on the urban heat island effect have been done and proved its existence, with less intensities, even in smaller cities, such as Patras, Heraklion, Volos (Stathopoulou and Cartalis, 2007) and Chania (Kolokotsa et al., 2009).

THE MAIN CHARACTERISTICS OF URBAN RESIDENTIAL BUILDINGS IN GREECE The Greek cities experienced strong growth after the war combined with many severe weaknesses. Following a centralized town planning system, the extension of their built space was extensive and continuous. This phenomenon had as basic impact, largely arbitrary structuring which entailed social practices contravening the scientific and technical planning rules while pushed in an extensive legislative output for the settlement of this anomalous situation. The organization of urban space was non-functional, with main characteristics the lack of organization of contemporary central operations, the closed vents to the natural environment of surrounding country and the lack of organized building on the outskirts of the city (Avdelidi, 2000). The large Greek cities lag obviously against other European cities in the proportion of green space per inhabitant. According to the official records of 1994, Athens is at the end of the list with 2.55 m2 per capita, while Thessaloniki has 2.73 m2 per capita. Worth to mention that according to the Greek legislation the desired (rather than mandatory) free space per capita is 8 m2 (YPEKA, 1994).

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The mixture of incompatible land uses is a significant characteristic of the urban web of Greek cities (Residence with central functions and major traffic axes. Residence with manufacture and trade. Wholesale with central functions. Transportation activities with central functions or residence etc). Residence in particular, and its existence in an extensive form in all spectrum of the city web , from the central areas and up to the fringes of the city complexes and beyond them, to the agricultural or countryside regions, is a key feature of the big Greek (Figure 2). Figure 2: Partial view of Athens.

In Greece, almost all urban residential buildings take the form of multi-storey apartment buildings. The great majority of these buildings consist of a ground floor and a series of higher floors usually between three and five in number and very rarely more than seven. The height between successive floor-levels is a little less than 3 m, making the net height of each floor between 2.7 and 2.8 m. Before 1985, the General Building Code favoured a recession of the highest levels (penthouse apartments). However, insomuch as subsequent provisions have not favoured such an arrangement, this feature has largely ceased to be applied. Apart from their façade, apartment buildings in Greece have another open side at the rear overlooking the open space at the centre of the street block in which the building stands. In addition, depending on the construction method that was followed, one or even both of the lateral surfaces of the building may also be open. The size of each apartment building is calculated on the basis of the area of the plot on which it is erected together with the building factor for that particular location. As a result of historical and social influences and townplanning measures, the plots of land in urban areas in Greece are generally small in size. Typically, many of the plots on which apartment buildings have been erected formerly contained small dwellings (usually detached houses) with a small yard. Consequently, the buildings that can be constructed on these plots are objectively small. Indeed, an analysis of building statistics for the period 1991-2002 reveals that the average volume of private buildings in Greek towns is in the region of 1500 m3 (EL.STAT., 2002).

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Figure 3: Typical buildings in a Greek city

The supporting structure of the building is of concrete. In Greece, apart from concrete, essentially no other materials are used to construct the supporting structures of residential buildings. Wood and metal are occasionally used in supporting structures either when these form part of additional structures or special types of buildings (e.g. agricultural, industrial). The almost exclusive use of concrete, coupled with the strict requirements of the seismic code, leads to the creation of bulky supporting structures. The walls between the concrete piers are constructed of bricks and plaster on both sides. Thermal insulation is applied since 1980 to all external walls, typically in an cavity between two, 9 cm thick, layers of bricks. The roofs of apartment buildings take the form of flat accessible terrace roofs with thermal insulation and dampproofing over the concrete slab and sloping surfaces for the run-off of rainwater. Rarely, in areas with more adverse climatic conditions, apartment buildings may be found with tiled roofs, usually resting on slanting concrete slabs. The external surfaces of the buildings are usually simply plastered and painted with emulsion paints. As for choice of colour, light colours are the most common, usually ochres, blue, beige, orange or green. More rarely, some sections of facades are covered with ceramic tiles (usually in the shape of bricks), natural stone or, in luxurious buildings, marble. An essential feature of all residential buildings in Greece is the balcony. Every apartment above ground-level has at least one balcony in the form of a projection. Indeed, apartments with a larger number of balconies are much easier to find or even buildings where continuous balconies occupy most of the external surface areas. Balconies vary in width from a minimum of 0.5 m, in the case of secondary balconies, to almost 2.5 m. Sometimes the balcony width is further increased by incorporating a section of the roofed area of the apartment within it (Papamanolis, 2005). A typical feature in the facades of apartment buildings in Greece is the existence of awnings to permit sun control. They regularly occur on all balconies facing the sun. They consist of canvas blinds or thin metal sheets which are suspended from the lower surface of the balcony above and are opened and closed at an angle by means of a hand-operated device. All apartments possess a heating system. In the vast majority of apartment buildings this takes the form of a central heating system with radiators in which the boiler, distributor and fuel (oil) storage tank lie in the basement, from which via a network of pipes embedded in the floors the water is circulated to all the apartments in the building. In the last years natural gas through main distribution networks receives even more spread in the big Greek cities. The main activities which take place in Greek cities and have an influence to the atmospheric pollution and trough this to the formation of the micro-meteorological parameters, are mainly transportations and the burn outs for the heating of buildings during the cold months. In cities with industrial activity, the pollution from the industry is an additional source of pollution. In Greek cities, two types of air pollution are recognized: the first is characterized by high concentrations of particles. The second type - photochemical smog - is linked to an excess of nitrogen oxides, hydrocarbons, carbon monoxide (primary pollutants), ozone, and organic nitrates (secondary pollutant) and results from a series of chemical reactions driven by sunlight (ΕΕΑ, 2008).

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CONCLUSIONS The presentation of climatic data of a region is a simple presentation of numbers. Numbers receive a meaning if linked to the region they refer to and a scientific value if correlated to the factors they are formed by. The Greek cities, regardless of their differences in sizes, have many common features as for their city planning organization, the architectural and constructional features of the buildings and other structures they are comprised of and as of the uses and activities they host. For instance, in their common feature they are included the dense construction, the lack of urban green areas, the relative equal-height structures, the relatively high roughness of the building surfaces, the increased albedo, the burning products and photochemical reactions as the main components of their atmospheric pollution. These features inevitably reflect on the characteristics of the urban climate in Greek cities and differentiate them from the relevant urban climate characteristics in urban environments in other regions of the planet. Important factors which are affected are the temperature, the humidity, the wind. It is, therefore, logical that the improvement of the environmental conditions in Greek cities – but also in all cities, wherever they are – results in changes of the characteristics of the built environment and the activities it hosts.

REFERENCES Avdelidi, K. (2000). The successive expansions of Athens. In Maloutas T. (ed.) Social and Economical Atlas of Greece. Volume I: Cities, Athens-Volos: EKKE, University of Thessaly, 30-31. Dassenakis, M. (2000) Environmental Problems of Greece from a Chemical Point of View, Chemistry International 22(1).

European Environment Agency (2008), Air and Health, Air pollution in Athens: existing status and abatement practices. http://www.eea.europa.eu/publications/2599XXX/page018.html General Secretariat of National Statistical Service of Greece (2002). Construction Activity Statistics. Athens. Giannaros, Th. and Melas, D. (2012) Study of the urban heat island in a coastal Mediterranean City: The case study of Thessaloniki, Greece. Atmospheric Research 118: 103-120. Hellenic Ministry of Environment, Energy and Climatic Change (1994) Attica SOS, Urban and Suburban and Quality of Life. http://www.minenv.gr/4/44/4401/440102/44010201/g4401020102.html Hellenic Statistical Authority, EL.STAT. (2012) Announcement of the results of the 2011 Population Census for the Resident Population. http://www.statistics.gr/portal/page/portal/ESYE/BUCKET/General/resident_population_census2011.xls Katsoulis, B. and Theoharatos, G. (1985). Indications of the urban heat island in Athens, Greece. J. Climate Appl.Meteor. 24: 1296 - 1302. Kolokotsa, D., Psomas, A. and Karapidakis, E. (2009), Urban heat island in southern Europe: The case study of Hania, Crete, Journal: Solar Energy - SOLAR ENERG, 83(10): 1871-1883. Niachou, K., Livada, I. and Santamouris, M.(2005). A study of temperature and wind distribution inside two urban street canyons in Athens. International Conference Passive and Low Energy Cooling for the Built Environment, Santorini, Greece Papamanolis, N. (2005). The Main Constructional Characteristics of Contemporary Urban Residential Buildings in Greece. Building and Environment, 40(3): 389 - 396. Sachsamanoglou, Ch. (1999). Solar Radiation in Athens the last 40 years. Sixth National Conference for Renewable Energy Sources, Vol. A: 1-8, Volos. Santamouris, M. (ed) (2001). Energy and Climate in the Urban Built Environment, James & James, London. ________________________________________________________________________________________________ ISBN 9788895597188

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Santamouris, M., Papanikolaou, N., Livada, I., Koronakis, I., Georgakis, A. and Assimakopoulos, D.N. (2001). On the impact of urban climate on the energy consumption of buildings. Solar Energy, 70(3): 201 - 216. Stathopoulou, M. and Cartalis, C. (2007). Daytime urban heat islands from Landsat ETM+ and Corine land cover data: An application to major cities in Greece. Solar Energy 82(3): 358 - 368 Zabakas, I. (1981). Some Characteristics of the Microclimate in Attica basin in the General Climatology. In Zabakas, I. (ed), General Climatology. Athens, 440- 447 (in Greek). Zerefos, C., Kosmas, G., Repapis, C., Zabakas, I. (1977) Study on the time series of rainfall in the station of the National Observatory for the century 1871-1970, Publication of the Laboratory of Climatology of the University of Athens, No. 14 (in Greek).

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MODELING OF THE METEOROLOGICAL PARAMETERS AND THERMAL COMFORT CONDITIONS INSIDE THE URBAN BOUNDARY LAYER DURING MOSCOW'S 2010 SUMMER HEAT WAVE. Konstantinov P.I1. Varentsov M.I1. Malinina E.P.1 1

- Department of Meteorology and Climatology, Geographical faculty, Lomonossov Moscow State University, Russia

Summary This paper is based on the results of the first Russian detailed meteorological observations inside city canyons, which took place in April 2011 in Moscow, are considered in this work. This experiment involved a wide spectrum of observations, including the surfaces and air temperatures measurement at the different parts of the canyon and the sensible heat flux measurement by the acoustic anemometer. Canyon observations were compared with similar and synchronous observations at the closely-located meteorological ground, which can be considered as a natural and homogeneous surface. This revealed special features of the diurnal regimes of the temperature, humidity, wind and heat fluxes in the canyon and meteorological ground. Also observed data were used to calculate the drag coefficients for two places with 20 minutes frequency. Analysis of the calculated values and their diurnal variations cleared up the canyon turbulence patterns. The specified patterns can be used for better turbulence accounting in the urban microclimate models, such as MosClim model (Kislov, Konstantinov, 2011). Observed data were used for the validation of the developed model of the city canyon with stability-depending turbulence accounting. This allowed to consider and test several stability and turbulence parameterizations and to reach a good level of the reproduction of the canyon parameters and their variations by the model. Meteorological conditions of 29 July 2010 (warmest day in Moscow during 143-year period of direct meteorological measurements) were reproduced in south-west of Moscow-city at micrometeorological scale. Biometeorological indices (particularly PET (physiological equivalent temperature), WBGT and EET), were calculated for every hour of 29 July using output data of elaborated microscale model for Moscow megalopolis. Map of thermal comfort for the certain territory of Moscow region was drawn basing on this material. On the Fig.1 below the diurnal variation of WBGT index is presented. This graph shows the difference in bioclimatic condition in four the most demonstrative points in the city canyon and points on the metrological ground and in the botanic garden. The same graphs were made for PET and equivalent effective temperature (EET). Furthermore, the risk of thermal injury for workers and risk of thermal stress for slightly moving person were estimated. These results showed that the most comfort points are the balcony on the north-west oriented wall and botanic garden. At these points the extreme meanings of all of the biometeorological indices were not observed. The most dangerous for people points are the balcony on south-east oriented wall and the roof.

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Fig.1. The diurnal variation of WBGT (wet-bulb globe temperature) for 29.07.2010 for four different points in city canyon and for meteorological ground and botanic garden in Moscow.

REFERENCES

Kislov, A. & Konstantinov, P. (2011), Detailed spatial modeling of temperature in Moscow, Russian Meteorology and Hydrology 36(5), 300--306.

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THE IMPACT OF URBANIZATION ON LAND USE AND LANDSCAPE. AN ARCHITECTURAL APPROACH. Jiménez-Díaz, P.1 ,Jiménez, J.I.2

Urban Climatology And Climate Change Group - University Of Granada 1 architect In “Unifica Servicios Integrales S.L.” 2 professor Of Applied Physics, Dpt. Applied Physics, Faculty Of Sciences

Summary One of the most pervasive changes the world over is occurring at the fringe of urban areas where urban development is spreading onto less populated and less intensely developed land formerly in field or forest. Urbanization, an important driver of climate change and pollution, alters both biotic and abiotic ecosystem properties within, surrounding, and even at great distances from urban areas. As a result, research challenges and environmental problems must be tackled at local, regional, and global scales. The impact of urban development has been estimated by comparing observations in cities with those in surrounding rural areas. The changes in scenic quality resulting from urbanization are explored for a region in Granada a medium-sized city (250.000 inhabitants) surrounded by the rich valley of three rivers in which dwellings are emerging in a seemingly random fashion along quiet country roads using too much lands previously dedicated to agriculture, meanwhile increasing the density in specific places in would be a better way. Therefore, human socio-demographic changes are the primary drivers of land-use change, urbanization, and pollution at continental and sub-continental scales; in turn, these patterns are influenced by a continental template of climate and geography (fig.1).

Fig. 1: “Wild urbanization” gradually destroying agricultural plain. There are two points of view to focus on this problem. On the one hand, the study architectural and landscape of the recovery of the soil for traditional use; this is the object of this work. On the other hand, the study from the physical point of view of the trends of temperature changes caused by the change of land use due to urbanization, which is a second part that is currently under development. Therefore, the main purpose of this work is to present an architectural sustainable self consistent prototype in energy supplies and water use to manage the regulation of this environment in order to recover and preserve the land use but also allowing the necessary growing of the city.

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EVALUATING COMMUNICATION EFFORTS AND URBAN CLIMATE CONSTRAINTS FOR ENERGY SAVINGS. THE RACES PROJECT. Grasso V. 1,2 Crisci A. 1 Vaccari F.P.1 1

National Research Council–Institute for Biometeorology (CNR–IBIMET), Via Caproni 8 – 50145 Firenze, Italy 2 Consorzio LaMMA, Via Madonna del Piano 10 – 50019 Sesto Fiorentino (FI), Italy

[email protected]

Summary The Institute of Biometeorology (CNR) was partner in a communication campaign on energy saving within RACES project (Raising Awareness on Climate and Energy Savings - European programme LIFE+). A main action was the “carbon budget” which involved 250 families in an annual monitoring of CO2 emissions generated by family’s consumption behaviours. Five selected Italian cities were considered: Florence, Trento, Modena, Bari and Potenza, showing different climatic and geographical features. Family energy consumptions, and their equivalent CO2 emissions, have been investigated along three main components: domestic winter heating, household electrical load and family mobility by car or motorcycles. The first aim was to identify which are the structural factors, like building and house features, heating surface and age structure, home location in urban context, the presence of energy intensive domestic appliance (i.e dishwasher, air–conditioner) affect significantly the family carbon budget and, in each geographical context, how the local weather have modulated energy consumption and equivalent CO2 emissions. Weather derivative as HDD- Heating Degree Days and the amount of rainy days, RD, were considered. The role and weight of each variable was investigated through a generalized linear model framework. Factor significance design has been estimated for each family budget component (heating, electrical and mobility). The second target of this work was to evaluate the effectiveness of the project’s communication actions involving families as drivers of consumption’s reductions. Each action have been evaluated to quantify the impact on domestic consumption life-style. Overall results are showed and presented.

Keywords: energy saving; urban resilience; environmental communication; climate change; sustainability

INTRODUCTION Climate change is maybe one of the most challenging environmental threats we’re facing nowadays, but widespread mitigation actions are still lacking. Besides the fact that climate science is complex for lay people to understand, many impacts of actual climate change remain “hidden” to most of the people, that tend to disregard the issue in everyday decision making compared to other more compelling needs and immediate demands. One of the first source of climate altering emissions is surely related to energy consumption, that’s why is so important for researchers and communicators to focus on it the attention of the public. Energy consumption represents a perfect area where it’s possible to highlight the link between personal behaviors and global issues, like climate change and sustainability. Energy saving is in fact one of the most important mitigation policy that national and local government endorse. Unfortunately the vast majority of citizens living in urban areas is usually not even aware of domestic energy ________________________________________________________________________________________________ ISBN 9788895597188

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consumption, except for the periodic energy bill. Consumption levels tend to remain “invisibles” to people, even if in a country like Italy they account for the 20% of the national carbon dioxide (CO2) emissions (ENEA, 2010). This invisibility of domestic energy use is a tough limit to be considered in any saving effort. Evidence from the survey of implementation of the EU directive on labeling of cold appliances in the EU indicates that ‘the message about energy saving and the environment has been noted by consumers in every country’, but few actually link the importance of energy saving to their own personal behavior (Winward et al, 1998). Delivering the environmental message to the public is not enough to change behaviors, what is critical is to develop peoples’ ability to identify what can be done in specific terms to improve the situation (Darby 2001). Initiatives aimed at reducing energy use has failed so far to recognize the crucial link between a general sense of our environment and the specific daily needs: there is a need to focus on how people connect their lives to the environment (Eden, 1996) Previous researches have analyzed which can be the good mix of tools to sustain people effort in changing behaviors, in relations to energy savings. The literature specifically concerned with energy consumption presents a consensual view on the positive role feedbacks can have (Farhar & Fitzpatrick, 1989), although not always illustrating the kind of feedback that is most effective (Brandon, 1999). Arvola (1993) found that when people had the opportunity to compare their present consumption with a previous similar period they changed their consumption. A common agreement was not reached on the effect of feedbacks emphasizing the financial dimension of energy conservation, with some researches recognizing to this component a valuable effect (Farhar and Fitzpatrick, 1989) others finding its failure on other samples (Hutton et al., 1986). This kind of assessment and results should be taken in consideration when designing information material to promote energy-consumption awareness (Brandon, 1999). Direct feedback on energy consumption, alone or in combination with other factors, seems to be the most promising tool, with almost all of the projects involving direct feedback producing savings of 5% or more. In four programs aimed at low-income households, direct feedback together with some form of advice or information gave savings of about 10%(Brandon, 1999).Following this kind of assessment we present an energy conservation action realized within a European project aimed at raising awareness on climate change and energy saving in different cities.

DATA AND METHODS The RACES project The challenge of global climate change need a large effort for providing the public with the best information possible, establishing and sustaining a genuine sharing of understanding between science and society. Within this frame, a project involving teachers, families and stakeholders was realized – starting January 2009 ending April 2011- with the support of the European Commission: LIFE RACES – Raising Awareness on Climate Change and Energy Savings. RACES involved five partners: the scientific partner Institute of biometeorology of the Italian National Research Council (CNR Ibimet), the Municipality of Florence, acting as project coordinator, the Municipality of Modena, the EuropeDirect offices of Bari, Potenza and Trento. Main objective of RACES was to set up an awareness raising campaign on climate change issues in the five partner cities of Trento, Modena, Florence, Bari and Potenza, providing citizens with an accurate information context on the local dimension of climate change, linking information and educational aspects with the experimentation of eco-friendly and energy saving consuming patterns. The project main target were: public stakeholders; teachers, and indirectly students; families. In order to develop an effective information action, firm belief was the need to apply a bottom-up approach, starting from the ideas, opinions and attitudes expressed from the targeted publics: before planning and implementing the communication actions, a qualitative research was realized in the five Italian cities involved in the project, with families representatives, teachers and stakeholders. Main topics of the discussion concentrated on the perception of the climate change, the main local issues on the problem, the best communication activities and contents hold as effective to involve the citizenship. Carbon Budget: monitoring energy consumption A strong asset of RACES project was to test if and how communication efforts towards a specific group of people could lead changes in behaviors. To measure this changes one of the main actions of the project was the “Carbon Budget” (CB) which involved almost 250 families in a long monitoring of CO2 emissions generated by family’s energy ________________________________________________________________________________________________ ISBN 9788895597188

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consuming behaviors. Five selected Italian cities were considered: Florence, Trento, Modena, Bari and Potenza, showing different climatic and geographical features. Trento is in the North- Est of Italy just South to the Dolomite Mountains, Florence and Modena are located in a more central; Bari and Potenza are both in the South of the country, however Bari is in front of the sea while Potenza is a more inland location at 820 meters above sea level. During the Carbon Budget participants were committed to monitor their family’s energy use, specifically heating, power and vehicles’ fuel usage, for a period of 8 months at least. Participants were selected in different ways. Pre requisites were only two: to provide all the consumption data of the previous year (2008) and to have an house with an independent heating system, that can be switched on/off liberally during the day. In Florence, home of the project coordinator, the Municipality sent a letter to a sample of 7000 families registered in the municipality demographic data base, inviting them to take part in the Carbon Budget experiment. In the other cities families were selected by the partners through their mailing list of stakeholders and participants of previous environment and sustainability projects. A total selection of 316 families was the starting sample of the CB. The monitoring covered the period from November 2009 to October 2010. Data collection had three fundamental required step: a first entry, the starting point of the monitoring, an intermediate record after 6 months, and a final monitoring after 8-10 months. People were also invited to increase monitoring participating in monthly competitions. All the monitoring were based on self-reading of domestic meters. As baseline to assess reductions achieved, it was agreed to consider the energy usage data of the previous year, 2008. Participants provided to project coordinators data about power and heating consumptions and about family’s vehicles, included average Km/year travel by owned cars or motorcycles. Besides, participants also answered a questionnaire about family composition and households characteristic, providing details about number of family components and relative age; number of room and square meters of the house; type of fuel used for domestic heating; details about characteristic and location of the house they live in; information on the number of vehicles used by the family components and their specific features. All this details were used to assess the reference point of consumption for 2008 as compared to the monitoring period during RACES CB. Being RACES a project to raise awareness on climate change, all energy consumptions were calculated in corresponding carbon dioxide emissions, to make people relate their own energy use to the amount of CO2 emitted globally. Emission factors published in the Delibera 14/2009 issued by Italian Ministry of the Environment (2009) were used to convert power and heating consumption into equivalent CO2 emissions. For the mobility component of the CB, the reference was the emission factors provided by the ARTEMIS project (Boulter, 2007), based on the drive-styles, and calculating the amount of CO2 emitted per Km, depending on vehicle’s power and fuel. To encourage people towards energy conservation behaviors participants were provided with a kit of eco-friendly and thorough energy saving tips. The material was distributed during the first meeting at the beginning of the CB action, were families were also provided with all the information needed for data collection and reporting. Further information was also collected and published on the project web site http://www.liferaces.eu, also hosting a community section (http://community.liferaces.eu/) where participants could share good practices exploited to save energy. Families were supported by tutors (4 tutors in Florence, and one for each of the other cities) who would give them advices on request also helping in reporting periodical consumption. A dedicated section of RACES web site was implemented to record the energy monitoring. Participants were provided with a personal account to log into their profile and fill in the periodical energy consumption data; for participants non provided with internet access or without a personal computer, the tutors collected data contacting people by telephone. After each data recording on the web site, participants received a feedback on their Carbon Budget account showing their actual trend in energy usages compared to similar period of the previous year. As final reporting each participant received a Carbon Budget report, a sort of school report with a feedback about consumption and saving reached during the monitoring period (see appendix A). In the next section we’re going to explain the method of evaluation. Evaluating effort and energy savings The Carbon Budget in RACES was conceived as crucial part of the communication campaign to a raise awareness on climate change and its relation with energy consumption and sustainable lifestyles. Thus main objective of the CB was to evaluate “if” and “how much” the participation in the project was a real trigger for participants “effort” in changing behaviours, compared to own previous consumption standards. Family energy consumptions, and their equivalent CO2 emissions, were investigated along three main components: domestic winter heating, household electrical load and family mobility by car or motorcycles. 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structure, home location in urban context, the presence of energy intensive domestic appliance (i.e dishwasher, air– conditioner) in other terms every potential factor that could affect significantly the family carbon budget. Moreover, for each geographical context the local weather effects having impact in energy consumption and equivalent CO2 emissions were considered using weather parameters as HDD- Heating Degree Day and the amount of rainy days, RD. These parameters become useful weights to apply on the collected data in cities to take into account climatic differences in assessing participants performances. The role of the more important variables was investigated through a statistical model framework. Factor significance design has been estimated for each family budget component (heating, electrical and mobility). On this basis a specific “effort index” was developed to evaluate the effectiveness of the project’s communication actions in involving families and to compare efforts amongst participants. For each participant energy consumption on CB period was compared to the one of reference period. Data were always normalized for the values of significant dimension affecting each specific energy sector. The choice was based on the results previously obtained using three generalized linear models (GLMs). Baseline participants’ consumptions for each energy sector were predicted as a function of specific variables with well recognized association to energy consumption level. The values of these predictors were given by (I) participants' household features, mainly the surface in squared meters and the family size; (II) climatic analysis carried out for each cities using urban meteorological observations carried related to the CBR period. From these data, the climatic heatinghouse request (HDD) and the local daily rainfall occurrences (RD) were calculated. Finally GLMs models were used to confirm the expected significance of the variables involved in the analysis. The more reliable variables indicated by GLMs were chosen to perform a data normalization using the simple ratio between their values and the consumptions assessed for each participants. GLMs details are not shown in the work but are fully available at GitHub repository of work (https://github.com/alfcrisci/races_analitics.git). Another obvious parameter of normalization was the duration of the CB participation period (days of monitoring). These one showed a wide linear positive relationship with energy consumption for sufficiently long period (longer than 200 days). Table 1: Structural factors having significant positive impact on consumption data by sectors (GLMs). Calendar parameters

Family parameters

Household parameters

N° of family components

Surface

Weather parameters

Heating Deg. Days

Home - Heating

Monitoring days

Home Electricity

Monitoring days

N° of family components

Surface

-

Mobility

Monitoring days

N° of family components

-

Rainy Days

Resuming each energy sector data are normalized by: -

power sector: total monitoring days; number of family’s components.

heating sector: total monitoring days; number of family’s components; number of square meters of the house; HDD Heating Degree Days , as index of weather component. -

mobility: total monitoring days; number of family’s components; RD or number of rainy days.

The normalization scheme allows an unbiased comparison between the CB and referenced period and lead to a metric to evaluate the effort of each single participant, independently from geography location, households and mobility assets. ________________________________________________________________________________________________ ISBN 9788895597188

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Eventually, the final goal of the CB was the evaluation of both the project communication “potential” and the participants ”effort” and not the measurement of the mere “efficiency” in terms of absolute CO2 reduction. The normalized CO2 relative reduction, later indicated briefly with the term “reduction”, thus become an index of the whole effort, averaging the assessed reduction performance cumulated by each participant in all three sectors. The final metric of the effort index is expressed as the percentage of change in the normalized consumption during the monitoring period compared to 2008 baseline.

RESULTS AND DISCUSSION Of the 316 households that started the trial, 247 completed it. Amongst those 247 participants, only 184 were considered as providing valid results for the statistical analysis (Tab 2). Households were excluded for several reasons: participation shorter than 240 days was considered unfitting for the whole CB analysis; in several cases during the experiment we found errors in the calculations, due to these miscalculations, participant were excluded. Some criteria were defined to assess valid results: electricity increase higher than +200% respect previous years was unvalued; heating reductions higher than -85% or increase over +200% respect previous year were unvalued; consumptions in mobility with an increase higher than +300% respect previous higher was unvalued. Generally consumption differences greater than 15.000 KgCO2 respect to baseline values were not considered. Such robust changes in energy consumption in fact could not have been ascribed to the project participation, but appeared more likely due to significant changes in family lifestyles and, accordingly, were not considered as valid results.

Table 2: Participants who completed the monitoring period.

City

Bari

Florence

Modena

Potenza

Trento

Total participants

Participants

24

156

21

26

20

247

Excluded participants

7

22

10

20

4

63

Valid sample

17

134

11

6

16

184

The suitability of variables used for data normalization are widely confirmed by GLMs scheme (Table 1). The following figures, 1 and 2, show respectively the “effort index” and the reductions achieved by the CB participants. The median score of effort on 184 participants was -15%, (Tab. 3). The effort set was grouped into three classes composed as follows: a 32% of the sample didn’t registered a sufficient effort in reducing energy consumption respect to the 2008 baseline period, while the 68% registered a certain effort: a smaller effort for the 30% of the participants and a great one for the remaining 38%.

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Figure 1: Pie chart representation of the effort classes achieved by the sample and the average reduction associated with the “effort” classes.

Figure 2: Pie chart representation of the distribution of “energy savers” and the average reduction in terms of tons of CO2 produced by each “effort” class.

Table 3 shows reductions achieved by the sample of 184 valid participants. The effort index show an average reduction achieved by the participants of - 15% respect to 2008 baseline. In terms of effective savings this produced a 2% of saving respect baseline period. But as we can see in Tab. 3 some cities performed worse than others; in Potenza many results were considered invalids and the sample was reduced to only 6 families. Table 3: Reductions scores per city and median value on the whole sample of 184 participants. “Effort” %

Savings %

Monitoring dd

Power sector

Heating sector

Mobility sector

2008 Kg CO2

CB Kg CO2

CO2 savings

Potenza

+30%

+46%

323

-28%

-56%

+131%

8.677

10.546

+1.869

Bari

-25%

-31%

280

-56%

-12%

0%

4.962

2.657

- 2.305

Florence

-17%

-1%

323

-34%

-10%

11%

7.739

7.110

- 629

Modena

-13%

-10%

326

-16%

-24%

-2%

9.197

6.688

- 2.509

Trento

-13%

0%

345

-10%

-7%

-37%

9.592

8.712

- 880

City

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Median value

-15%

-2%

323

-47%

-14%

-2%

7.247

6.335

- 912

Considering the different sectors, power performed well and also did heating. Mobility was the more difficult area of changing behaviors due also to the many structural constraints that are difficult to overcome, for time or cost reasons: people that use car for work cannot switch to alternatives ways of transportation, and also do not people living far off local transport station or in rural areas. This results turn out to be even more worthy if the sample is cleared from outliers, people who perform far worse the mean values. Table 4 shows the figures if we were to consider only a segment of the participants ranking: taking into account only the first 150 in the ranking based on effort index, the reductions are far better, showing a median value of -19% compared to 2008 baseline; value that rise up to a reduction effort index value of -43% (with a correspondent savings of 23% in energy consumption) for the first 50 in the ranking. Those were also the people who made the greatest number of reporting (almost once a month) confirming the importance of regular feedback as valuable trigger for energy conservation.

Table 4: Results about effort index, total and per sector, and energy savings compared to baseline. “Effort” index*

Savings *

Power sector “effort” *

Heating sector “effort” *

Mobility sector “effort” *

First 50

-44%

-26%

-68%

-33%

-45%

First 100

-32%

-15%

-57%

-22%

-24%

First 150

-19%

-8%

-53%

-17%

-8%

First 174

-17%

-5%

-48%

-14%

-3%

*calculated as median value on selected sample

Looking at single sectors, mobility is by far the most critical dimension of family energy consumption budget, as shown also by Figure 3. Considering households component of CO2 emission, heating reveals to be the more important source of CO2 emission compared to electricity (Fig. 4)

Figure 3: CO2 emission baseline 2008: composition of emission source per family (average of the sample group).

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Figure 4: CO2 emission baseline 2008: composition of households emissions by source for each city.

Heating consumptions has also a strong structural component depending on households constructions features and location, that cannot be compensated with changes in behaviors. Trento e Potenza that share almost the same number of HDD during the year, show quite different heating emissions trend, ascribable to very dissimilar building feature. Climatic features of cities and the annual meteorological variability have a deep impact in energy consumption level on the CB dataset. The preliminary statistical analysis have shown this more clearly. The analysis of relative importance carried out with R “relaimpo package” (Grömping, 2006) tell us more. Climate agents are more critical in triggering households heating emissions than the number of family components, while this last become more relevant for mobility sector. The building surface is a key parameter for energy consumption, the following figures show this clearly (electricity and heating), and confirm that is more difficult to have saving behaviours when climate is not mild: HDD is the climatic request for heating and if increase the energy consumption growth independently to people behaviors. Structural modification are needed to mitigate climate impacts in heating consumptions.

Figure 5:Histogram of Relative importance of agents having impacts on each CB energy sector considered.

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CONCLUSIONS As many research have shown the majority of people with positive environmental attitudes do not always turn them into practice as eco-friendly behaviors. Moreover, lay public not always consider the connections between individual energy consumption and environmental problems, thus energy savings is not always perceived as an environmental issue. Many studies (Darby, 2001; Brandon, 1999) suggest however that feedbacks coupled with practical savings advice can be useful to overcome this situation if targeted at people who already hold positive environmental attitudes. RACES Carbon Budget results confirm this outcomes , where the Carbon Budget realized a final normalized reduction, the effort index, of about -15% respect to baseline consumption of previous year, and corresponding energy saving of 2%. Excluding the ten participants performing worse in the CB ranking, the median value achieved by the trial increase to values of -17% , corresponding to a 5% of savings respect to the 2008 baseline. This is in line with previous trials reporting energy reduction of around 5 to 10%, as claimed by other researches (Darby 2001; Brandon 1999) . Finding effective ways to trigger behaviour changes in citizens is crucial to promote urban resilience to face climatic change, especially in urban environment. From 2008 more than half of the world’s population live in urban areas (UNFPA, 2007), and we also know that climate change will have severe effects on population living in cities in the next years (UNFPA, 2007). Mitigation and adaptation policies should find within cities’ government a special attention and dedicated efforts. Communication campaigns and energy conservation initiatives represents a crucial dimension if we want to increase urban resilience to present and future climate change and involve citizens as informed and active players. Eventually we want to mention some weak points that should be considered in future research: (1) computer mediated communication was not suitable for the whole sample group, that in RACES included also many “aged” participants” who were not familiar with computer. The selection of the sample would have been more careful on this aspect, maximizing the positive effect of computer mediated communication with an appropriate selection of the group of people; (2) feedbacks about consumption should have been more regular to produce more positive effects on energy conservation, in fact participant who made regular monthly reporting on own consumption achieved higher savings.

ACKNOWLEDGMENTS We want to thank all the families taking part in the RACES project, tutors who supported participants with patience and useful advices and also all the partners and collaborators who contributed to the project. Without them this study would not have been possible. RACES was funded under the European Commission LIFE + Programme, contract n° “LIFE07 INF/IT/000487”

REFERENCES Arvola, A. (1993). Billing feedback as a means to encourage household electricity conservation: a field experiment in Helsinki. In R. Ling and H. Wilhite .Eds The Energy Efficiency Challenge For Europe. Proceedings of ECEEE, Denmark, June 1993. Brandon, G. & Lewis, A. (1999). Reducing household energy consumption: a qualitative and quantitative field study. Journal of Environmental Psychology 19: 75- 85 Boulter, P..& McCrae,I. (2007). ARTEMIS: Assessment and reliability of transport emission models and inventory systems. Final Report. Deliverable No. 15. TRL Unpublished Report UPR/IE/044/07. TRL Limited, Wokingham. Darby, S. (2001) Making it obvious: designing feedback into energy consumption. Proceedings, 2nd International Conference on Energy Efficiency in Household Appliances and Lighting. Italian Association of Energy Economists/ EC-SAVE Programme Italian Ministry of the Environment, ( 2009) Delibera 14/2009, http://www.minambiente.it/opencms/opencms/home_it/menu.html?menuItem=/menu/menu_informazioni/Monitoraggio _delle_emissioni_di_CO201.html&menu=/menu/menu_informazioni/argomenti.html|/menu/menu_informazioni/Clima. ________________________________________________________________________________________________ ISBN 9788895597188

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html|/menu/menu_informazioni/Direttiva__Emission_trading_.html|/menu/menu_informazioni/Monitoraggio_delle_em issioni_di_CO201.html&lang=it Eden, S.E. (1996). Public participation in environmental policy: considering scientific, counter-scientific and nonscientific contributions. Public Understanding of Science 5: 183-204 ENEA (2010). Inventario annuale delle emissioni di gas serra a scala regionale. Le emissioni di anidride carbonica dal sistema energetico, Rapporto 2010, Roma Farhar, B. C. & Fitzpatrick, C. (1989). Effects of Feedback on Residential Electricity Consumption: a literature review. Solar Energy Research Institute, US Department of Energy. Grömping U.(2006). Relative Importance for Linear Regression in R: The Package relaimpo. Journal of Statistical Software, 17(1), 1--27. Hutton, R. B., Mauser, G. A., Filiatrault, P. & Ahtola, O. T. ,(1986). Effects of cost related feedback on consumer knowledge and consumption behaviour: a field experiment approach. Journal of Consumer Research 13: 327-336 R Development Core Team (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/. UNFPA,(2007). State of the world population 2007. Unleashing the potential of urban growth. http://www.unfpa.org/webdav/site/global/shared/documents/publications/2007/695_filename_sowp2007_eng.pdf Accessed on 20/12/2012 Winward, J., Schiellerup, P. and Boardman B. (1998). Cool Labels: the first three years of the European Energy Label. Energy and Environment Programme, Environmental Change Unit, University of Oxford

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ANNEX 1: The RACES report given to each participant as final feedback of family performance

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SENSOR WEB BIKE: A PARTICIPATORY ENVIRONMENTAL URBAN MONITORING De Filippis T.1, Rocchi L.1, Rapisardi E.2, Zaldei A.1, Vagnoli C.1, Martelli F.1 1

National Research Council - Institute of Biometeorology, Florence, Italy 2 PhD Candidate, UNITO - Earth Sciences Dep., Turin, Italy

[email protected]

Summary Sustainable development and effective environmental policies are key to ensure public safety and health. People feel safer in their cities when national and local government are clearly committed with a better environmental governance, building public trust and transparency. Urban environmental monitoring is a driving force to set up continuous information services able to provide input for spatial decision support systems. Data have still a low interoperability, due to a lack of policy coordination and “closed” data infrastructures. But data, may be made available from different sources, as local and national infrastructures could be positively integrated by a participatory involvement of diverse stakeholders, including citizens. SensorWebBike is a real-time Spatial Data Infrastructure (SDI) and web interface that seeks to tackle this challenge: setting up an open sensing and participative approach for urban environmental monitoring. Bikers becomes voluntary citizens-sensors able to measure environmental parameters, by using a small sensor’s box - an innovative low-cost mobile device - mounted on their bikes. Through General Packet Radio Service (GPRS) technology, the sensor transmits geolocated data on environment and air quality to the data server connected to the applications and web server, where real time observations are visualized in a web browser. The data are open and the whole system is compliant with geospatial standards throughout the entire process flow: from sensor data acquisition to web visualisation. The prototype has been tested in the city of Florence, and is online at [http://149.139.16.20:8080/bikeclimate/] where the geolocated measures, bike tracks and user-generated meta-data are visualized on a GIS mashup and shared automatically, contributing to build a comprehensive and constantly updated spatial representation of air quality pattern of the whole urban area. SensorWebBike opens environmental monitoring systems and data to the public, “augmenting” urban social interactions so to increase citizens’ awareness on air quality issues. The overall aim is to share a participatory monitoring tool for the collective environmental mapping, contributing to the building of the “intelligence data spots” of cities.

Keywords – urban monitoring; air quality; SensorWeb; real-time; citizens participation,

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A VECTOR-BASED GIS METHOD FOR MAPPING OF LOCAL CLIMATE ZONES AND ITS APPLICATION IN A CENTRALEUROPEAN CITY Unger J., Lelovics E., Gál T. Department of Climatology and Landscape Ecology, University of Szeged

[email protected]

Summary A new vector-based method was developed to determine geometrical and land cover parameters of different urban neighborhoods. The database for this method contains 3D building database and remotely sensed information from Landsat satellite images. The obtained parameters are the sky view factor, aspect ratio, mean building height, terrain roughness, building surface fraction and impervious/pervious surface fractions. The aim of this automatic procedure is the delineation of thermally different Local Climate Zones (LCZs) based the value ranges of the mentioned parameters. The mapping of LCZs was performed in a South-Hungarian city of Szeged where the urban climate investigations have already a long history. These studies have provided a thorough knowledge about the thermal peculiarities of the city, namely about the intra-urban temperature distribution on average and in different synoptic situations. These earlier obtained temperature data across the city provided an opportunity for us to verify whether the delineated zones with different physical properties have indeed different thermal reactions. According to our preliminary results the mean seasonal temperature by zones meet the expectations, ie, the more urbanized the warmer is an area within the city. As a second step of our study we will (i) involve satellite and aerial images in order to determine other physical properties (e.g. albedo) of the urban surfaces and (ii) gather information about the distribution of transport density, domestic and industrial energy usage in order to assess the anthropogenic heat flux. With this additional information the mapping of the LCZs may be more accurate. The final version of the standalone GIS method will be appropriate for use in any other urban areas if the necessary input data are available.

Keywords: Local Climate Zones, GIS methods, temperature patterns, Szeged, Hungary

INTRODUCTION Nowadays about half of the human population is affected by the burdens of urban environments: pollution, noise and the modified characteristics of the urban atmosphere compared to the natural environment. This makes studies dealing with the urban impact on climate particularly important. Owing to the anthropogenic activity, a local climate develops in the built-up areas. This urban climate is different from the pre-urban (natural) one and is a result of the construction of buildings, roads, etc., as well as of the emission of heat, moisture and pollution related to human activities.

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Among the parameters of the urban atmosphere the near-surface (1.5-2 metres above ground level or screenheight) air temperature shows the most obvious modification compared to the rural area (Oke, 1987). This urban warming is commonly referred to as the urban heat island (UHI) and its magnitude is the UHI intensity (ΔTu-r). Nevertheless, in the heat island literature the term “urban” has no single, objective meaning as the areas around the measuring sites could be very different depending on the investigated cities (e.g. park, college ground, street canyon, housing estate, etc.). In addition, for landscape classification or description of the site surroundings the simple “urban” versus “rural” is not appropriate because of the abundant variety of the landscapes according to their surface properties to development of relevant near-surface micro and local climates (Stewart 2007, 2011). To diminish this deficiency, Stewart and Oke (2012) developed a climate-based classification system for describing the local physical conditions around the temperature measuring field sites universally and relative easily based on the earlier studies from the last decades (e.g. Auer, 1978; Ellefsen, 1991; Oke, 2004; Stewart and Oke, 2009), as well as a thorough review on the empirical heat island literature and world-wide surveys of the measurement sites with their surroundings. The elements of this system are the “local climate zones” (LCZ) and they are presented shortly in Section 2.2. Because of the complexity of the urban terrain the monitoring of the representative intra-urban thermal features is a difficult task (Oke, 2004). The locations of the sites of an urban station network within the city and thus the question about its appropriate configuration raises an essential problem. This problem is related to the relationship between the intra-urban built and land cover LCZ types and the locations of the network sites. Two situations arise:

(1) In the case of an already existing network (e.g. Schroeder et al. 2010) it may be required to characterize the relatively wider environment around the measuring sites, namely what type of urban area (LCZ) surrounds a given station and whether it can be clearly determined. In other words, how representative is the location of a station regarding a specific, clearly defined LCZ type in an urban environment? (2) In the case of a planned station network (e.g. Unger et al. 2011) the most important questions are what built and land cover LCZ types can be distinguished in a given urban area, how precisely they can be delimited, how many they are, and whether their extension is large enough to install a station somewhere in the middle of the area (representing the thermal conditions of this LCZ) while of course taking care to minimize the microclimatic effects of the immediate environment. The aims of this study are: (i) to determine the LCZ types in Szeged which are representative for the urbanized area of the city using seven geometric, surface cover and radiative properties from the ten ones listed by Stewart and Oke (2012), (ii) to develop GIS methods in order to calculate these seven property values for any part of the study area and (iii) to compare the thermal reactions of the selected LCZ areas based on the earlier temperature measurement campaigns carried out in this city. STUDY AREA AND METHODS Temperature measurements in Szeged Szeged is located in the south-eastern part of Hungary (46°N, 20°E) at 79 m above sea level on a flat terrain (Figures 1a and 1b) with a population of 160,000 within an administration district of 281 km2. The area is in Köppen's climatic region Cf (temperate warm climate with a rather uniform annual distribution of precipitation). The annual mean temperature is 10.4ºC and the amount of precipitation is 497 mm (Unger et al., 2001).

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“Two hundred years of urban meteorology in the heart of Florence” The study area consists of 103 cells (500 × 500 m) covering the urban and suburban parts of Szeged (25.75 km2). Additionally, in order to represent non built-up areas four cells (1 km2) were added to the network at the western side of the area (Figure 1c). Figure 1: (a) Location of the Szeged in Europe, (b) in Hungary and (c) the grid network of the study area (gray – urbanized area).

Mobile measurements were taken by cars at the same time on fixed return routes during a one-year period (April 2002 – March 2003) by several times. Return routes were taken to make time-based corrections to a reference time (4 hours after sunset). Readings were obtained using radiation-shielded resistance sensors mounted at 1.45 m above ground and connected to data loggers. Data were collected every 10 s, so at a car speed of 20-30 kmh-1 the distance between measuring points was 55-83 m. The logged values at forced stops were omitted. After averaging the usually 15-20 measurement values by cells in every measurement nights, the obtained values referred to the cell centres (for more details see Unger, 2004, 2006; Balázs et al., 2009).

That is, as a result of mobile measurements, our “measuring sites” are in the centres of the cells so the obtained average values by cells are regarded as “measured” temperature values in these “measuring sites” in a given night. As the most ideal conditions for UHI developments prevail in summer and early autumn in this region (WMO, 1996), two nights were selected in summer (15 July 2002, 21 August 2002), one in autumn (18 September 2002), and additionally one in spring (25 March 2003). At these times the weather was clear and calm in the preceding days too, thus during these nights the weather conditions promoted the surface influence on the thermal conditions in the near-surface air layer. Additionally, the ground was relatively dry and the trees had foliage. Key features of the lcz classification system The necessity and ideas of the development of “local climate zone” classification system and its structure are presented and discussed in details by Stewart and Oke (2012). Therefore here we highlight only the key features of the system. LCZs are defined as “regions of uniform surface cover, structure, material, and human activity that span hundreds of meters to several kilometres in horizontal scale. Each LCZ has a characteristic screen-height temperature regime that is most apparent over dry surfaces, on calm, clear nights, and in areas of simple relief.” (Stewart and Oke, 2012). Among them there are ten built types (from LCZ 1 to LCZ 10) and seven land cover types (from LCZ A to LCZ G), and additionally, the types can have variable seasonal or shorter period land cover properties. The main characters of the types are reflected in their names (Table 1).

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Table 1. Names and designation of the LCZ types (after Stewart and Oke, 2012) Built types LCZ 1 – Compact high-rise LCZ 2 – Compact midrise LCZ 3 – Compact low-rise LCZ 4 – Open high-rise LCZ 5 – Open midrise LCZ 6 – Open low-rise LCZ 7 – Lightweight low-rise LCZ 8 – Large low-rise LCZ 9 – Sparsely built LCZ 10 – Heavy industry

Land cover types LCZ A – Dense trees LCZ B – Scattered trees LCZ C – Bush, scrub LCZ D – Low plants LCZ E – Bare rock / paved LCZ F – Bare soil / sand LCZ G – Water

Variable land cover properties b – bare trees s – snow cover d – dry ground w – wet ground

The LCZ types can be distinguished by the measurable physical properties (parameters) (Table 2). These parameters are partly dimensionless (e.g. sky view factor), partly given in %, m, etc. (e.g. building surface fraction) and their values have different ranges according to the different types. Stewart and Oke (2012) give the typical values of them (see Table 3 too). Table 2. Zone properties of LCZ system (after Stewart and Oke, 2012)

Properties

Type of properties Geometric, surface cover Thermal, radiative, metabolic sky view factor surface admittance (Jm-2s-1/2K-1) aspect ratio surface albedo building surface fraction (%) anthropogenic heat output (Wm-2) impervious surface fraction (%) pervious surface fraction (%) height of roughness elements (m) terrain roughness class

In the frame of this new classification system the intra-urban UHI intensity is an LCZ temperature difference (ΔTLCZ:X–Y), not an “urban-rural” difference (ΔTu–r) (Stewart and Oke, 2012). Vector based GIS method From the ten geometric, surface cover and radiative properties listed by Stewart and Oke (2012) we can determine seven of them with our methods for any given area inside the study area. These are the sky view factor (SVF), building surface fraction (BSF), impervious surface fraction (ISF), pervious surface fraction (PSF), height of roughness elements (HRE), terrain roughness class (TRC) and albedo (A). Our calculations were carried out in circle areas with 250 m radius centered in the middle of the grid network cells. This size is necessary as the upwind fetch of typically 200-500 m is required for air at screen-height to become fully adjusted to the underlying, relatively homogeneous surface (Stewart and Oke, 2012). The applied methods by parameters: - SVF: The input was a SVF database with 5 m horizontal resolution originated from our earlier studies. It was calculated using the 3D building database of Szeged with a vector based method. The building database contains building footprint areas as polygons, and the height value for each building measured with photogrammetric methods. During the SVF calculation all of the buildings were regarded with flat roof and the effect of the vegetation was neglected (Gál et al., 2009; Unger, 2006). Now the SVF values of grid points inside the examined circle area were averaged. - BSF: The input was the 3D building database of Szeged where all of the footprints of the buildings are available from the study area. BSF is the fraction of summarized area of buildings inside the circle. The buildings on the border of the circle were divided into two parts, and the area of intersecting part had been taken into account for the summarized building area. - PSF: The input for the PSF was a built-up dataset calculated from RapidEye satellite image using NDVI index, a 1:25000 topographic map, a road database and the Corine Land Cover (CLC) (Bossard et al., 2000) database. The ________________________________________________________________________________________________ ISBN 9788895597188

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RapidEye image is atmospherically corrected (resolution of 5.16 m) and the NDVI was calculated using bands 3 and 5. Basically the point where the NDVI is above 0.3 was regarded as built-up area. The CLC dataset was used to locate the agricultural areas as these areas have small NDVI because after harvest the amount of plants on them is almost zero. As a second correction the shape of water bodies were digitized in the topographic map because water has NDVI values very similar to the values of some building materials. As a last correction the road database was used to locate the asphalt roads in the area because in the urban canyons these roads are usually under tree cover and roads (ISF) which slice agricultural areas do not appear in CLC dataset. - ISF: The value of the ISF were calculated using this formula: ISF = 1 – (BSF + PSF). - HRE: The input for the HRE was also the 3D building database of Szeged. For each examined circle area height of the buildings (and building parts) weighting with their footprint areas were averaged. - TRC: For describing the roughness the Davenport roughness classification method was used (Davenport et al., 2000). All of the circle areas were classified into roughness classes with visual interpretation of aerial photographs, the topographical map and the building database. - A: As an input we used the atmospherically corrected reflectance values of the 5 band RapidEye satellite image. Broadband albedo was calculated as an average of reflectance values weighted with the integral of the radiation within the spectral range of a given band (Starks et al. 1991). RESULTS As a first step we determined the possible LCZ types occurring in the study area of Szeged and we selected areas with 250 m radius for each type which represent them. Secondly, the temperature differences between these areas were compared on the above mentioned measurements nights separately and on average, too. LCZ types in Szeged and their representative areas With the help of the obtained parameter values supplemented by viewing aerial photographs and authors’ local knowledge of the study area, theoretically every areas in the 103 cells can be classified. In Szeged the high-rise type areas (LCZs 1 and 4), the lightweight low-rise shanty districts (LCZ 7) and the heavy type industry (LCZ 10) are not present among the built type LCZs, thus we searched for representative areas of the remaining six types (LCZs 2, 3, 5, 6, 8 and 9). As the study area of temperature measurements concentrated on the urbanized parts of the city (Fig. 1c), only the westernmost cell can be regarded as a non built-up cell, because it consists of agricultural fields with low plants without trees and a few small houses. So, according to the land cover type classification, the circle area in this cell can be regarded as a representative area of LCZ D type (low plants). As a result, Figures 2 and 3 show the locations and aerial photographs of the selected circle areas.

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Figure 2: Locations of the selected circle areas representing the LCZ types occurring in Szeged with their names and designations.

The values of the areas characterized as LCZs 2 and 6 fit into the formally defined parameter ranges given in Table 3. Nevertheless, in some cases there are smaller deviations in the obtained parameter values from the defined ranges (these values are marked with underlines). The aerial pictures in Figure 3 give us much help in the final decision regarded the classification. Although we are convinced that the selected areas represent the LCZ types as we specified, these deviations require some explanation: - LCZ 3 “Compact low-rise” – It has extended covered areas, the ISF barely exceeds the upper limit (50.4%), thus it has a slightly higher SVF (0.68). The BSF is a bit under the lower limit of this parameter (31.4%) so it could be even LCZ 6 (open low-rise), but the PSF is under 20% which is typical of LCZ 3. - LCZ 5 “Open midrise” – As this area is well vegetated the PSF is slightly higher (41.5%) than the upper limit with the result of a bit lower BSF value (16.2%). This could us lead to classify this area even as LCZ 6 (open low-rise), but the HRE value (15.4 m) justifies the selection of LCZ 5. - LCZ 8 “Large low-rise” – The PSF is larger (24.9%) as this area has a sport field, as well as the ISF is also higher (59.6%) thus the BSF is a bit smaller (15.5%). However, as the picture in Figure 3 shows, it is a typical warehouse area with factory buildings, so it is classified as LCZ 8. - LCZ 9 “Sparsely built” – This area is characterized with low BSF (2.5%) and TRC (4) so it could be even LCZ D (low plants), but because of its high ISF (22.5%) it is better classified as LCZ 9.

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Figure 3: Aerial photographs of the circle areas with their designations representing the LCZ types occurring in Szeged.

Table 3. Formally defined ranges of the properties for LCZ types (Stewart and Oke, 2012) compared to the values (italics) of the representative areas in Szeged (underlined values deviate from the defined ranges). LCZ name and designation

SVF sky view factor

LCZ 2 Compact midrise LCZ 3 Compact low-rise LCZ 5 Open midrise LCZ 6 Open low-rise LCZ 8 Large low-rise LCZ 9 Sparsely built LCZ D Low plants

0.3–0.6 0.59 0.2–0.6 0.68 0.5–0.8 0.74 0.6–0.9 0.83 > 0.7 0.92 > 0.8 0.99 > 0.9 0.999

BSF building surface fraction (%) 40–70 45.4 40–70 31.4 20–40 16.2 20–40 20.3 30–50 15.5 10–20 2.5 < 10 0.2

ISF impervious surface fraction (%) 30–50 44.0 20–50 50.4 30–50 42.3 20–50 45.3 40–50 59.6 < 20 22.5 < 10 0.0

Properties PSF pervious surface fraction (%) < 20 10.5 < 30 18.2 20–40 41.5 30–60 34.4 < 20 24.9 60–80 75.0 > 90 99.8

HRE height of roughness elements (m) 10–25 13.6 3–10 7.9 10–25 15.4 3–10 5.4 3–10 6.6 3–10 5.0