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Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (p

A simple model for the simulation of growth and development of Sangiovese vines has been presented in a previous paper. In this paper the model is validated to examine whether the description of the physiological relationships in the model describe the growth of grapevine (cv. Sangiovese) realistically. Furthermore, the model was adapted and validated for the simulation of growth of another cultivar (cv. Cabernet Sauvignon). Comparisons of simulated and experimental data for both cultivars reveal that the model made good predictions of vine growth for the whole growing season., VITIS - Journal of Grapevine Research, Vol. 36 No. 2 (1997): Vitis

A downward titration of antihypertensive drug regimens in summertime is often performed on the basis of seasonal variations of clinic blood pressure (BP). However, little is known about the actual interaction between outdoor air temperature and the effects of antihypertensive treatment on ambulatory BP. The combined effects of aging, treatment, and daily mean temperature on clinic and ambulatory BP were investigated in 6404 subjects referred to our units between October 1999 and December 2003. Office and mean 24-hour systolic BP, as well as morning pressure surge, were significantly lower in hot (>90th percentiles of air temperature; 136±19, 130±14, and 33.3±16.1 mm Hg; P P P P

Nowadays, no studies have been published on the relationship between meteorological conditions and work-related mortality and morbidity in Italy. The aim of this study was to evaluate the relationship between hot weather conditions and hospital admissions due to work-related accidents in Tuscany (central Italy) over the period 1998-2003. Apparent temperature (AT) values were calculated to evaluate human weather discomfort due to hot conditions and then tested for work accident differences using non-parametric procedures. Present findings showed that hot weather conditions might represent a risk factor for work-related accidents in Italy during summer. In particular early warming days during June, characterized by heat discomfort, are less tolerated by workers than warming days of the following summer months. The peak of work-related accidents occurred on days characterized by high, but not extreme, thermal conditions. Workers maybe change their behaviour when heat stress increases, reducing risks by adopting preventive measures. Results suggested that days with an average daytime AT value ranged between 24.8 degrees C and 27.5 degrees C were at the highest risk of work-related accidents. In conclusion, present findings might represent the first step for the development of a watch/warning system for workers that might be used by employers for planning work activities.

Leaf wetness duration (LWD) is one of the most critical variables involved in the development of plant diseases. Many pathogens require the presence of free water on plant organs to move and to start their infective processes. For this reason LWD is extremely significant in the management of crop protection activities and in particular, the successful use of weather-related disease forecasting models. Their operational application is a very important tool for reducing fungicide applications, for environmental safeguarding in high quality production systems, and for reducing the waste of resources and financial losses. Despite the relevance of LWD, no standard has yet been accepted for its measurement. For this reason the use of simulation models, based on agrometeorological variables, represents a valuable alternative to field monitoring. In this work a physical model based on the energy balance was applied for the simulation of LWD on a grapevine ( Vitis vinifera ). The model, developed in the United States on the cultivars Chardonnay and Concord, and in Australia on Cabernet Franc, was applied for the Sangiovese variety and was adapted for use with agrometeorological data easily available from standard weather stations. The model outputs were compared both with data measured by sensors in the 1995–2003 period and with visual inspections of LWD conducted on vines during 2003. Following, simulated and recorded LWD data were used as input by a model for the simulation of grapevine downy mildew ( Plasmopara viticola ) and the results were compared with observed data in order to establish the impact of different LWD data on the quality of model simulations.

The impact of powdery (Uncinula necator) and downy mildew (Plasmopara viticola) on grapevine leaf gas exchange was analysed. Gas exchange measurements (assimilation A, transpiration E, stomatal conductance g(s), intercellular concentration of CO(2)C(i)) were made on three different leaf materials: (i) healthy tissue of diseased leaves, (ii) infected tissue of diseased leaves, (iii) healthy tissue of healthy leaves (control treatment). Using the same source of leaf tissue, photosynthetic pigment concentration (chlorophyll a, b) and fluorescence levels (minimal fluorescence F(0), maximal fluorescence F(m) and the optimal quantum yield [F(m) - F(0)]/F(m)) were determined to explain the mechanism of action of the two diseases on leaf assimilation. The results indicated that powdery and downy mildew reduced the assimilation rates, not only through a reduction in green leaf area (visual lesions), but also through an influence on gas exchange of the remaining green leaf tissues, determining a 'virtual lesion'. The ratios between virtual and visual lesions were higher in powdery mildewed leaves than in the downy mildewed leaves. The photosynthetic fluorescence level (F(v)/F(m)) was affected by neither of the two pathogens. The reduction in intercellular concentration of CO(2) and photosynthetic pigment may explain the lower assimilation rates in the healthy tissues of powdery and downy mildewed leaves respectively.

Leaf wetness duration (LWD) is one of the most important variables responsible for the outbreak of plant diseases but, in spite of its importance, the technology for measurement is not rather reliable. For this reason the modelling appears to be a valid support for LWD assessment. In this work a technique for LWD estimation that was applied in some agro-environmental studies from few years was used: artificial neural network (ANN). The ANN output then was used as input for an epidemiological model to predict Plasmopara viticola infections. The aim of this work was to carry out an ANN capable to find out the relationships between the agrometeorological input and LWD and to evaluate the impact of this estimated LWD when integrated in epidemiological simulations.

Un modele mecaniste appele PLASMO avait deja ete developpe pour simuler le mildiou de la vigne (Plasmopara viticola) et est utilise dans plusieurs zones viticoles d'Italie depuis 1988 en collaboration par plusieurs organismes de recherche de Firenze. Dans cette etude, un nouveau modele de simulation base sur la logique floue a ete developpe selon la meme structure (cycle biologique de P. viticola). Cette approche permet d'utiliser a la fois des informations classiques quantitatives et des informations qualitatives. Les concepts vagues peuvent aussi etre traites. Les donnees agrometeorologiques sont utilisees, avec un pas d'une heure, en partant du debourrement jusqu'a la fin de la saison vegetative. La temperature de l'air, l'humidite relative, les precipitations et l'humectation des feuilles sont necessaires. Les processus simules sont la croissance de la surface foliaire de la vigne et les principales phases du cycle biologique de l'agent pathogene: incubation, sporulation, germination, survie des spores et inoculation. Les principales donnees epidemiologiques fournies par le modele sont les periodes d'infection et l'intensite de la maladie. La performance du modele est evalue et les approches mecanistes et de logique floue sont comparees.

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, andwater (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models’ responses to CTW changes (R¨otter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012)...

The frequency of natural hazards has been increasing in the last decades in Europe and specifically in Mediterranean regions due to climate change. For example heavy precipitation events can lead to disasters through the interaction with exposed and vulnerable people and natural systems. It is therefore necessary a prevention planning to preserve human health and to reduce economic losses. Prevention should mainly be carried out with more adequate land management, also supported by the development of an appropriate risk prediction tool based on weather forecasts. The main aim of this study is to investigate the relationship between weather types (WTs) and the frequency of floods and landslides that have caused damage to properties, personal injuries, or deaths in the Italian regions over recent decades. In particular, a specific risk index (WT-FLARI) for each WT was developed at national and regional scale. This study has identified a specific risk index associated with each weather type, calibrated for each Italian region and applicable to both annual and seasonal levels. The risk index represents the seasonal and annual vulnerability of each Italian region and indicates that additional preventive actions are necessary for some regions. The results of this study represent a good starting point towards the development of a tool to support policy-makers, local authorities and health agencies in planning actions, mainly in the medium to long term, aimed at the weather damage reduction that represents an important issue of the World Meteorological Organization mission.

Climatic factors and weather type frequencies affecting Tuscany are examined to discriminate between vintages ranked into the upper- and lower-quartile years as a consensus from six rating sources of Chianti wine during the period 1980 to 2011. These rankings represent a considerable improvement on any individual publisher ranking, displaying an overall good consensus for the best and worst vintage years. Climate variables are calculated and weather type frequencies are matched between the eight highest and the eight lowest ranked vintages in the main phenological phases of Sangiovese grapevine. Results show that higher heat units; mean, maximum and minimum temperature; and more days with temperature above 35 °C were the most important discriminators between good- and poor-quality vintages in the spring and summer growth phases, with heat units important during ripening. Precipitation influences on vintage quality are significant only during veraison where low precipitation amounts and precipitation days are important for better quality vintages. In agreement with these findings, weather type analysis shows good vintages are favoured by weather type 4 (more anticyclones over central Mediterranean Europe (CME)), giving warm dry growing season conditions. Poor vintages all relate to higher frequencies of either weather type 3, which, by producing perturbation crossing CME, favours cooler and wetter conditions, and/or weather type 7 which favours cold dry continental air masses from the east and north east over CME. This approach shows there are important weather type frequency differences between good- and poor-quality vintages. Trend analysis shows that changes in weather type frequencies are more important than any due to global warming.

SUMMARYModern agriculture is based on the control of in-field variability, which is determined by the interactions of numerous factors such as soil, climate and crop. For this reason, the use of remote sensing is becoming increasingly important, thanks to the technological development of satellites able to supply information with high spatial resolution and revisit frequency. Despite the large number of studies on the use of remote sensing for crop monitoring, very few have addressed the problem of spatial variability at field scale or the early prediction of crop yield and grain quality. The aim of the current research was to assess the potential use of high resolution satellite imagery for monitoring durum wheat growth and development, addressing forecast grain yield and protein content, through vegetation indices at two stages of crop development. To best represent the natural variability of agricultural production, the study was conducted in wheat fields managed by local farmers. As regards dry weight, leaf area index and nitrogen (N) content, the possibility of describing the crop state is evident at stem elongation, while at anthesis this potential is completely lost. However, satellites seem to be unable to estimate the N concentration. Aboveground biomass accumulated from emergence to stem elongation is strictly related to the final yield, while it has been confirmed that the crop parameters observed at anthesis are less informative, despite approaching harvesting time.

The pollination period and pollen concentrationof olive trees (Oleaeuropea L.) and olive production were analysedfor Prato and Florenceusing a data set of 8 years (1991–1998).Meteorological data have been usedto obtain information about weather conditionsduring vegetative seasonsand correlations were found both for thephenology and yield.

A correct approach to crop protection must consider the effect of disease on plant activity and its impact in terms of economical losses. These evaluations can drive the farmers to a quantification of plant responses to pathogen attack and to the application of economical thresholds for fungicide sprays. For grapevine (Vitis vùlÎfera L.), the knowledge of plant responses to disease is still very limited independently from the level of investigation (physiology, growth, development, etc.). The aim of this research was to evaluate the impact of downy mildew (Plasmopara viticola Berl. et De Toni) on grapevine photosynthesis under controlled and field conditions. Downy mildew was shown to reduce to a negative value net photosynthesis in the oilspot, as well as to affect the physiology of gas exchanges of the tissues surrounding the oilspot. The daily trend under field condition pointed out a normal trend of assimilation, without differences between green portions of healthy and diseased leaves. The consequences on source-sink relationships were discussed, as well as the relation between visible symptoms and physiological alterations.

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (>=75 years) who died in inland and coastal cities from 2006 to 2008 (May-October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress. © 2014 Marco Morabito et al.

Urban planners and managers need tools to evaluate the performance of the present state and future development of cities in terms of comfort and quality of life. In this paper, an approach to analyse the intra-urban summer thermal variability, using an urban planning indicator, is presented. The proportion of buildings and concrete surfaces in a specific buffer area are calculated. Besides, the relationship between urban and temperature indicators is investigated and used to produce thermal maps of the city. This approach is applied to the analysis of intra-urban variability in Florence (Italy), of two thermal indices (heat index and cooling degree days) used to evaluate impacts on thermal comfort and energy consumption for indoor cooling. Our results suggest that urban planning indicators can describe intra-urban thermal variability in a way that can easily be used by urban planners for evaluating the effects of future urbanization scenarios on human health. (C) 2014 Elsevier Ltd. All rights reserved.

Cultivation of sweet sorghum for the production of bioenergy is an attractive option to cope with the challenges of climate change and variability. In fact, on one hand it represents an interesting strategy of mitigation and, on the other, the use of drought resistant species could be considered as an opportunity of adaptation to the change of precipitation patterns. Anyway, when considering the production of agricultural feed stocks, particular attention should be addressed to the environmental sustainability of field production in order to avoid trade-offs in relation to food production, land use and pressure on the water resources. In this context, the cultivation of drought-tolerant energy crops as sweet sorghum ( Sorghum vulgare (L.) var. Saccharatum) could be an interesting option. On the bases of these considerations, the current study had the aims i) to monitor the sweet sorghum growth and productive responses to different water treatments, in order to assess the extent of tolerance to constant water stress and ii) to assess the potential for first and second-generation bioethanol production obtainable from soluble sugars and residual biomass at two different development stages, flowering and physiological maturity. Results show that the length of the growing period should be decided on the bases of the objective pursued. If the objective is just the production of bioethanol, a longer cultivation period could be more suitable, but, on the contrary, if the objective is more addressed to an optimization of water, flowering should be considered the best harvest time.

As more than half of the world population live in cities, the design of liveable urban spaces is increasing- ly a strategic issue. Therefore, urban planners need tools allowing the evaluation of the benefits of de- sign choices that take into account thermal comfort. Ground surface characteristics as well as shading conditions can affect spatial temperature variability of an urban area. The aim of this study was to inves- tigate the relationship between different types of urban ground covers, sun exposure conditions and daily variation of air temperature. Our case study was based on data collected in two sites of the urban area of Florence in summer 2013. For each site, five weather stations equipped with air temperature, rel- a t i v e h u m i d i t y a n d s o l a r r a d i a t i o n s e n s o r s w e r e s e t u p a t 2 m e t e r s h e i g h t t o a n a l y s e t h e t h e r m a l c o n d i- tions at pedestrian level. Each station was classified according to ground cover characteristics (permeability and albedo), use of irrigation in green areas and sun exposure. The relationship between these characteristics and hourly variation of air temperature was investigated. According to our results shading conditions explained more than 70% of temperature variability during the hottest hours of the day. Air temperature over the shaded green surface was 3°C lower than temperature over sandstone ex- posed to the sun. On the other hand, night temperatures were significantly reduced by approximately 1° C on permeable surfaces

Erythema is the most familiar short-term symptom of human skin associated with overexposure to unperceivable ultraviolet radiation (UV). However, people are able to perceive the warm infrared component of the solar radiation by means of thermal (dis)comfort. This study investigated the potentiality of perceived outdoor heat stress as a valuable proxy for the unperceivable effect of UV-induced risk of erythema in a Mediterranean city. Meteorological data and UVB (280-320 nm) measurements were obtained for the 2004-2012 period by a weather station located in the municipality of Florence. Continuous measurements of erythemally effective UV (UVEry) were performed by means of a broadband temperature-corrected radiometer with the spectral response close to the erythemal action spectrum. Hourly UVEry doses were expressed as Standard Erythemal Doses (SEDs). The newly developed Universal Thermal Climate Index (UTCI), that represents the state-of-the-art of outdoor thermal (dis)comfort evaluation, was also assessed. Descriptive analyses of the hourly distribution per month of the frequencies of days with heat stress and UVEry exceeding 2.0, 3.0, 4.5 and 6.0 SEDs were carried out based on the general skin-type characteristics. The association between UVEry and UTCI was analyzed by a two-way contingency table approach. The probability of UVEry exceeding specific SED thresholds when heat stress occurs was often significantly higher than the same probability when no heat stress is perceived. Furthermore, increased magnitudes of the ratios, ranging from the very sensitive to the minimally sensitive skin types, were also found. However, during several months, too many days occur without any signs of heat discomfort, even when people may be exposed to relevant doses of harmful UVEry for the skin of various phototypes. These findings underlie the need for public health authorities to provide differentiated advice per month in relation to potential UV skin damage in the city of Florence.

Drs Dhar and Lambert1 correctly note that the potential relationship between sunlight and seasonal blood pressure (BP) changes is not investigated in our study.2 We agree that this interaction, possibly mediated, at least in part, by changes in brain monoamine concentration, should not be neglected. In addition, the UV-dependent cholecalciferol formation is a potential modifier of …

COST Action 734 was launched thanks to the coordinated activity of 29 EU countries. The main objective of the Action was the evaluation of impacts from climate change and variability on agriculture for various European areas. Secondary objectives were: collection and review of existing agroclimatic indices and simulation models, to assess hazard impacts on European agricultural areas; to apply climate scenarios for the next few decades; the definition of harmonised criteria to evaluate the impacts of climate change and variability on agriculture; the definition of warning systems guidelines. Based on the result, possible actions (specific recommendations, suggestions, warning systems) were elaborated and proposed to the end-users, depending on their needs.

If climate change scenarios include higher variance in weather variables, this can have important effects on pest and disease risk beyond changes in mean weather conditions. We developed a theoretical model of yield loss to diseases and pests as a function of weather, and used this model to evaluate the effects of variance in conduciveness to loss and the effects of the color of time series of weather conduciveness to loss. There were two qualitatively different results for changes in system variance. If median conditions are conducive to loss, increasing system variance decreases mean yield loss. On the other hand, if median conditions are intermediate or poor for disease or pest development, such that conditions are conducive to yield loss no more than half the time, increasing system variance increases mean yield loss. Time series for weather conduciveness that are darker pink (have higher levels of temporal autocorrelation) produce intermediate levels of yield loss less commonly. A linked model of decision-making based on either past or current information about yield loss also shows changes in the performance of decision rules as a function of system variance. Understanding patterns of variance can improve scenario analysis for climate change and help make adaptation strategies such as decision support systems and insurance programs more effective.

Seasonal blood pressure (BP) changes have been found to be related to either outdoor or indoor temperature. No information regarding the independent effects of temperature measured proximally to the patient, the personal-level environmental temperature (PET), is available. Inclusion of daylight hours in multivariate analysis might allow exploring the independent interaction of BP with seasonality. To investigate whether ambulatory BP monitoring is affected by PET or by seasonality, 1897 patients referred to our hypertension units underwent ambulatory BP monitoring with a battery-powered temperature data logger fitted to the carrying pouch of the monitor. Predictors of 24-hour daytime and nighttime BP and of morning BP surge were investigated with a multivariate stepwise regression model, including age, sex, body mass index, antihypertensive treatment, office BP, ambulatory heart rate, PET, relative humidity, atmospheric pressure, and daylight hours as independent variables. At adjusted regression analysis, daytime systolic BP was negatively related to PET (-0.14; 95% confidence interval, -0.25 to -0.02); nighttime BP was positively related to daylight hours (0.63; 0.37-0.90); and morning BP surge was negatively related to daylight hours (-0.54; -0.87 to -0.21). These results provide new evidence that PET and seasonality (daylight hours) are 2 independent predictors of ambulatory BP monitoring. (Hypertension. 2013;61:908-914.)

The aim of this study was to assess the current aerobiological situation and to investigate the influence of the hot and dry summer 2003 on pollen season (onset, end and duration of the pollen season, peak pollen day and value, total seasonal amount of pollen grains) of herbaceous family as Poaceae, Urticaceae and Compositeae. Heat wave of 2003 influenced the phenology of the main pollen families in Tuscany: the high temperatures occurred during 2003 affected pollen season of different family with different responses. This study confirms the role that the climate has on the flora species and in particular on herbaceous species phenology and the high variability of the pollination among different places, during extreme events. In general, high spring temperature induces an advance of the flowering period and a release of higher pollen quantity of Urticaceae and Poaceae; however, exceptional weather conditions (i.e.; summer 2003) could exert an opposite effect, resulting in an impairment of flowering of Urticaceae during autumn. Compositeae species produced a low amount of pollen in 2003, even if the peak value was higher than the average in some stations. © 2013 Springer Science+Business Media Dordrecht.

A description of a software program for the simulation of grapevine downy mildew ( Plasmopara viticola ) biology and its mathematical model are shown in this paper. It represents an improvement of the software PLASMO presented in a previous report by the authors. The model describes the development of the pathogen through computations based on weather data and it allows farmers to reduce the number of chemical treatments needed to control the fungus attacks. The improvements, suggested by several field experiments under different conditions, are discussed. The program has been shown to be a useful instrument for deducing the best moments for the fungicide application, on the basis of graphics and numeric values, during vineyards trials performed in Tuscany (central Italy) in the years 1992 and 1993. The user's interface, providing a friendly approach to the simulation and management of disease control, is fully described.

The association between air temperature and human health is described in detail in a large amount of literature. However, scientific publications estimating how climate change will affect the population's health are much less extensive. In this study current evaluations and future predictions of the impact of temperature on human health in different geographical areas have been carried out. Non-accidental mortality and hospitalizations, and daily average air temperatures have been obtained for the 1999-2008 period for the ten main cities in Tuscany (Central Italy). High-resolution city-specific climatologic A1B scenarios centered on 2020 and 2040 have been assessed. Generalized additive and distributed lag models have been used to identify the relationships between temperature and health outcomes stratified by age: general adults (= 75). The cumulative impact (over a lag-period of 30 days) of the effects of cold and especially heat, was mainly significant for mortality in the very elderly, with a higher impact on coastal plain than inland cities: 1 degrees C decrease/increase in temperature below/above the threshold was associated with a 2.27% (95% CI: 0.17-4.93) and 15.97% (95% CI: 7.43-24.51) change in mortality respectively in the coastal plain cities. A slight unexpected increase in short-term cold-related mortality in the very elderly, with respect to the baseline period, is predicted for the following years in half of the cities considered. Most cities also showed an extensive predicted increase in short-term heat-related mortality and a general increase in the annual temperature-related elderly mortality rate. These findings should encourage efforts to implement adaptation actions conducive to policy-making decisions, especially for planning short- and long-term health intervention strategies and mitigation aimed at preventing and minimizing the consequences of climate change on human health. (C) 2012 Elsevier B.V. All rights reserved.

Results show that the year-to-year quality variation of wines produced in North and Central Italy depends on the large-scale climate variability, and that the wine quality improvement in the last four decades is partially due to an increase of temperature and to a decrease of precipitation in West and Central Mediterranean Europe (WME; CME). In addition, wine quality is positively correlated with air temperature throughout the entire active period of the grapevine, weakly negatively correlated with precipitation in spring, and well negatively correlated in summer and fall. The month-to-month composites of the NAO anomaly show that, in years of good quality wine, this anomaly is negative in late spring, oscillates around zero in summer, and is positive in early fall; while, in years of bad quality wine, it is positive in late spring and summer, and negative in early fall, i.e. its polarity has an opposite sign in spring and fall in good versus bad years. The composite seasonal maps show that good wines are produced when the spring jet stream over the Atlantic diverts most of the weather perturbations towards North Europe, still providing a sufficient amount of rainwater to CME; when summer warming induced by southerly winds is balanced by the cooling induced by westerly winds; and when a positive geopotential anomaly over WME shelters CME from fall Atlantic storms. Bad quality wines are produced when the jet stream favors the intrusion of the Atlantic weather perturbations into the Mediterranean. Results suggest that atmospheric pattern persistencies can be used as precursors for wine quality forecast.

Intra-urban thermal range can reach similar values of the urban-rural difference. In this paper 5-years of thermal measurements carried out in Florence (Italy) by 25 air temperature sensors are presented. To evaluate the thermal difference within the urban environment of Florence, daily and hourly indices were applied to hourly data. Daily extreme indices were calculated on pre-defined arbitrary threshold according to the European Climate Assessment (ECA) indices definitions. Data were analyzed by season and significant differences were observed. A mean difference of almost 3 °C between the hottest and the coolest station was found in all seasons in maximum, minimum and average daily temperature. Significant intra-urban differences were also found in all climatological indices, such as frost and summer days. The difference in tropical nights was even more evident. The results of this study contribute to quantify the thermal intra-urban temperature range in the city of Florence, suggesting important application in phenology, aerobiology, human health and urban planning.

Over recent years the impact of weather on human health has become more severe, especially for people living in urban areas. Even though many studies have analysed the impact of weather on human mortality, few have quantified the impact of heat on morbidity, including ambulance response calls. In this study, 13,354 calls collected in the city of Florence (Italy) during summer were analyzed by month, day of the week, hour, and time slot of the day. An objective air mass classification was used to classify days and time slots with similar weather characteristics and a multiple variable analysis was applied to evaluate the relationship between emergency calls and weather. A positive trend was observed in the morning and a negative one during the night for all emergency calls, but only for food poisoning and alcoholic diseases. Calls for cardiovascular events increased in the morning and on hot days. Calls for psychiatric disorders rose significantly with temperature during the afternoon. The total number of calls and those for alcoholic diseases rose during the hottest nights. Our results, which show a clear relationship between ambulance response calls, periodicity, and weather, could contribute to an understanding the impact of weather on morbidity.

In this study, the relationship between the percentage of green areas (green cover ratio - GCR) and intraurban minimum and maximum temperature was investigated during the summer period. A network of air temperature sensors (HOBO® PRO series Temp/RH Data Logger, Onset Computer Corporation) was used to collect intra-urban thermal data in Florence (Italy). Temperature data were related to GCR calculated on areas of different size (from 10 to 250 m radius) centred on each sensor. Our results evidence a clear negative relationship between both minimum and maximum temperature values and GCR. It was correlated with maximum air temperatures only in areas of small radius, and with minimum air temperatures in all the considered areas. These results can be useful for urban planners to evaluate the effect of the increase of green areas in an urban environment.

Meteorological conditions can influence the main biological processes responsible of plant growth and development affecting vegetative growing, setting and ripening of different plant organs, onset and duration of phenological stages and the final production, exerting a strong impact on agricultural activities. In particular, the study of the variability of timing and length of the plants growing season is gaining importance because plant phenology is a sensitive indicator of climate change and has large impacts on terrestrial ecosystems through changes in productivity and in the annual carbon and water cycles. For many years, starting from meteorological information, mathematical descriptions of these effects have been formulated in order to provide users (farmers, technicians, extension services, researchers, etc.) with operational tools for improving management and planning activities. Besides common meteorological information supplied by local or synoptic weather stations, the use of large-scale climatic variables has also been investigated in order to forecast agricultural yields and production quality in several regions of the world. In Europe, the North Atlantic Oscillation (NAO) seems to be responsible for a large component of climate variability, particularly influencing winter and, through climate interactions on plants, crop production quality and quantity characteristics. The use of large-scale meteorological information showed great potential, particularly for the development of crop production forecasting systems.

Le logiciel d'exploitation est presente pour le modele PLASMO (Plasmopara Simulation Model), utilise pour la prevision du developpement du mildiou (Plasmopara viticola) de la vigne et developpe de facon a rendre tres simple sa validation, son eventuelle amelioration et son emploi direct dans le vignoble. Le programme n'utilise pas de fonctions d'aide car il comporte de simples legendes dans la partie inferieure de l'ecran. Pour se derouler correctement, il a besoin seulement, sur PC, d'une carte graphique ordinaire et d'un disque dur. Chaque ensemble de donnees doit figurer dans un fichier ASCII, qui sera transforme automatiquement en un format interne. Par traitement de ces donnees, des options sont disponibles dans le menu principal et donnent des informations utiles comme, par exemple, le developpement des periodes d'incubation du mildiou ou les epoques d'application de fongicides.

The problem of protecting grapevine against diseases is an old one, but in the last few years new techniques have been developed to reduce cost to the farmer and damage to the ecosystem. These are based on mathematical models describing the state of the plant-parasite environment system. A model for forecasting development of grapevine downy mildew (Plasmopara viticola) is presented. The input variables are temperature, rainfall and leaf wetness (determining infection by sporangia), and RH and temperature (for incubation period). The model also takes into account the limited survival of spores. The output is expressed as %, disease progress. Field validation tests, performed in 1990, 1991 and 1992 in several vineyards in Toscana (central Italy) showed a good correlation between observed and simulated infections. The model allowed the number of treatments to be reduced without any increase in downy mildew damage. It could in future be integrated with grapevine growth and development simulation models in an expert system to determine infected tissue area and thus the economic damage threshold.

A software implementation of PLASMO (Plasmopara Simulation Model) model for downy mildew (Plasmopara viticola Berl. et De Toni) of grapevine (Vitis vinifera L.) development forecasting is presented in this paper. The computer program has been developed to facilitate validation and further improvements and to allow direct model use in vineyard management. The model simulates the development of downy mildew on the basis of climatic conditions. The inputs to the model are: temperature and leaf wetness for the inoculation phase, temperature and relative humidity for the incubation phase and the type of treatment applied. Numeric or graphic outputs are available. The program provides useful information for identifying fungicide application times on the basis of the actual downy mildew development. Field validation tests performed in untreated rows show a good correlation between field observed and model simulated infections. Moreover the model identifies only three treatment distribution periods, while with the traditional method six treatments were applied.

High ambient temperatures have been associated with increased mortality across the world. Several studies suggest that timely preventive measures may reduce heat-related excess mortality. The main aim of this study was to detect the temporal modification of heat-related mortality, in older adults (aged 65-74) and in elderly >=75 years old, in the Florentine area by comparing previous (1999-2002) and subsequent (2004-2007) periods to the summer of 2003, when a regional Heat-Health Warning System (HHWS) was set up. Mortality data from 1999 to 2007 (May-September) were provided by the Mortality Registry of the Tuscany Region (n = 21,092). Weather data were used to assess daily apparent temperatures (AT). Case-crossover time-stratified designs and constrained segmented distributed lag models were applied. No significant heat-related mortality odds ratio (OR) variations were observed among the sub-periods. Nevertheless, a general OR decrease dating from 1999-2002 (OR 1. 23; lack of HHWS) to 2004-2005 (OR 1. 21; experimental HHWS running only for Florence) and to 2006-2007 (OR 1. 12; official HHWS extended to the whole Florentine area) was observed when the maximum AT was considered. This modification was only evident in subjects >=75 years old. The heat effect was higher and sustained for more days (until lag 9) during the period 1999-2002 than 2004-2007. The decrease of the excessive heat effect on mortality between periods with the absence and existence of a HHWS is also probably due to the mitigation of preventive measures and the implementation of a HHWS with specific interventions for safeguarding the health of the "frail elderly". © 2011 ISB.

Military and civil defense personnel are often involved in complex activities in a variety of outdoor environments. The choice of appropriate clothing ensembles represents an important strategy to establish the success of a military mission. The main aim of this study was to compare the known clothing insulation of the garment ensembles worn by soldiers during two winter outdoor field trials (hike and guard duty) with the estimated optimal clothing thermal insulations recommended to maintain thermoneutrality, assessed by using two different biometeorological procedures. The overall aim was to assess the applicability of such biometeorological procedures to weather forecast systems, thereby developing a comprehensive biometeorological tool for military operational forecast purposes. Military trials were carried out during winter 2006 in Pokljuka (Slovenia) by Slovene Armed Forces personnel. Gastrointestinal temperature, heart rate and environmental parameters were measured with portable data acquisition systems. The thermal characteristics of the clothing ensembles worn by the soldiers, namely thermal resistance, were determined with a sweating thermal manikin. Results showed that the clothing ensemble worn by the military was appropriate during guard duty but generally inappropriate during the hike. A general under-estimation of the biometeorological forecast model in predicting the optimal clothing insulation value was observed and an additional post-processing calibration might further improve forecast accuracy. This study represents the first step in the development of a comprehensive personalized biometeorological forecast system aimed at improving recommendations regarding the optimal thermal insulation of military garment ensembles for winter activities.

The possible existence of bound states in small helium clusters containing atomic and molecular hydrogen has been investigated by means of three completely independent sets of calculations. The first set employs the Jacobi-Davidson filtering procedure recently implemented in the Distributed Gaussian Functions (DGF) approach, the second one is based on the solution of the Faddeev equation by means of the hyperspherical adiabatic expansion method and the third follows the Quantum Monte Carlo approach. The partners within each complex are taken to interact via two-body potentials chosen among the most accurate existing in the literature. All the present quantum treatments show that no bound states are found for H(4He)2 and for D(4He)2 while only one very diffuse bound state is present in T(4He)2, where H, D and T are the three isotopes of hydrogen. The substitution of the atomic dopant with its molecular counterpart, H2, also gives rise to only one bound state whose spatial attributes are reported and analysed, underlining again the ultraweak nature of the interaction forces and the need to implement highly specific tools for the investigation of the ensuing bound states., The financial support of the University of Rome Research Committee, of the CASPUR Supercomputing Center and of the PRIN 2006 Research Programme is gratefully acknowledged. This work has been supported by the Spanish MICINN under projects FIS2007-62006 and FIS2008-01301. We also acknowledge the support of the INTAS collaboration and of the Italy-Spain Integrated Action Programme.

We aimed to characterise the coincidence of yield variations with weather variables for major field crops using long-term datasets and reveal whether there are commonalities across the European agricultural regions. Long-term national and/or regional yield datasets were used from 14 European countries (total of 25 regions). Crops studied were spring and winter barley and wheat, winter oilseed rape, potato and sugar beet. Relative yield deviations were determined for all crops. Meteorological data on monthly means for temperature variables, solar radiation, accumulated precipitation and evapotranspiration were provided for the relevant agricultural regions of each country for 1975-2008. Harmful effects of high precipitation during grain-filling in grain and seed crops and at flowering in oilseed rape were recorded. In potato reduced precipitation at tuber formation was associated with yield penalties. Elevated temperatures had harmful effects for cereals and rapeseed yields. © 2010 Elsevier B.V. All rights reserved., JRC.H.4-Monitoring Agricultural Resources

Monitoring of environmental variables and provision of the derived information (see Box III.5.14) represents necessary support for decision making in agroforestry management and planning (Black et al. 2000). Information can hardly be used as a raw datum, but it needs to be analysed, processed and organised according to its final operational use. New approaches to agriculture seek to increase the application of agrometeorological information for the assessment of environmental risks (Orlandini et al. 2007), also based on the establishment of agrometeorological services (WMO 2010).