Valerio Capecchi

Environmental temperature and thermal indices: What is the most effective predictor of heat-related mortality in different geographical contexts?

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.

Analysis of NDVI trends and their climatic origin in the Sahel 1986–2000

The first objective of the current work was to confirm the existence of consistent NDVI trends in the Sahelian region by applying per-pixel linear regression analyses to an 8-km dataset ranging from 1986 to 2000. These analyses ascertained that evident NDVI increases took place at the peak of the rainy season (August) in most of the Sahelian belt. Three sample areas were then selected in order to investigate the main origin of these increases, which was identified in corresponding rainfall variations during the previous periods, and particularly July. On this basis, per-pixel correlation analyses were conducted to identify zones where July rainfall and August NDVI values were concurrently increasing during the study period. A rainfall/NDVI correlation map was thus obtained that highlighted areas where vegetation productivity was particularly variable from year-to-year depending on the development of the rainy season. Such ‘hot spot’ areas were demonstrated to correspond to those where the predictive power of NDVI data on crop (millet) yield was highest. The paper finally discusses the possible developments of the analytical methodology applied, as well as the environmental relevance of the thematic maps produced.

Fractal characterization of rain-gauge networks and precipitations: an application in Central Italy

The measuring stations of a geophysical network are often spatially distributed in an inhomogeneous manner. The areal inhomogeneity can be well characterized by the fractal dimension DH of the network, which is usually smaller than the euclidean dimension of the surface, this latter equal to 2. The resulting dimensional deficit, (2 − DH), is a measure of precipitating events which cannot be detected by the network. The aim of the present study is to estimate the fractal dimension of a rain-gauge network in Tuscany (Central Italy) and to relate its dimension to the dimensions of daily rainfall events detected by a mixed satellite/radar methodology. We find that DH ≃ 1.85, while typical summer precipitations are characterized by a dimension much greater than the dimensional deficit 0.15.

Air temperature exposure and outdoor occupational injuries: a significant cold effect in Central Italy

Objective To investigate the short-term effect of air temperature on outdoor occupational injuries (out_OI) in Central Italy, also by taking different geographical factors and employment sectors of workers into account. Methods Out_OI for all of Tuscany (Central Italy), from 2003 to 2010 (n=162 399), were provided by the National Institute of Insurance for Occupational Illness and Injury. Representative daily meteorological data of the geographical area under study were obtained from the European Reanalysis-interim climatological reanalysis archive. Relationships between short-term changes in air temperature and out_OI were studied through Generalised Additive Models. Results The exposure-response curves of out_OI and short-term changes in air temperature generally showed significant out_OI increases when cold conditions occurred. The air temperature breakpoint corresponded to the 10th centile (−0.8°C) of the air temperature time series used in this study: a 1°C decrease in temperature below the 10th centile corresponded to a 2.3% (CI 1.3% to 3.3%) increase of out_OI throughout all of Tuscany. The cold effect was strongest in plain areas, especially when out_OI occurred in vehicles other than cars. No relationships of injuries with temperature extremes were observed in workers who generally spend half or most of their time outdoors, such as construction, land and forestry workers. However, these latter outdoor workers showed significant linear associations of injuries with typical (far-from-extreme) temperatures. Conclusions This large population-based study highlights the significant and independent effects of short-term air temperature changes (especially cold) in triggering out_OI. These findings represent the first step towards developing a geographically differentiated, operative outdoor-temperature-occupational-health warning system aimed at preventing outdoor work injuries.

Determining optimal clothing ensembles based on weather forecasts, with particular reference to outdoor winter military activities

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.

Sensitivity Analysis for Shallow Landsliding Susceptibility Assessment in Northern Tuscany

In two areas located in the north-western part of Tuscany, central Italy, Lunigiana and Garfagnana, noticeable heavy rainfall events occurred in the last years. During these events, the rainfall amounts and intensities triggered a great number of shallow landslides, causing damages, injuries and human losses. Steep slopes and deep valleys induced a persistently high relief of energy and high shallow landsliding susceptibility. In the present paper, the authors considered 4 heavy rainfall events that affected the area in 2009–2011. They carried out an analysis including a statistical modelling of spatial landslide occurrence by using Random Forest classifiers (RFc) after model selection by means of a stepwise AIC (Akaike Information Criterion) procedure. Event landslides occurrences permitted to build four event-specific RFc training sets, considering a large number of predictors reliable to characterize landslide susceptibility. Furthermore, the analysis took into account some relevant meteorological variables directly linked to the events themselves. An exploratory evaluation of the skills of a numerical weather prediction (NWP) model was conducted, to give a reliable supply to the RFc framework by using its weather forecast. For one selected event, a shallow landslide hazard model with meteorological inputs was validated. The preliminary results are shown and discussed.

Weather and climate monitoring for food risk management

Food insecurity represents one of the main indicators of the poverty level of a country and can breed a strong dependence on foreign aid with a strong slowdown of the national economy. African arid and semi-arid areas are characterised by food precariousness and their agricultural activity is strongly dependent on the extreme climatic conditions that affect the available water supply. This situation has led to the need to develop new tools for the prediction and the management of crisis. The characterisation of climate and the identification of anomalies, the monitoring of weather conditions and their influence on crops, short and medium range weather forecasts and long-term climate predictions are among the most powerful tools to predict, in as short a time as possible, crises due to the absence or delay of rainfall season. Meteorological information can also be used as an input to agrometeorological models applied for crisis prevention or for its management during the growing season when the crops are already present. In this paper, a review of these tools is made and some operational products presented. Copyright

Seasonal Predictions and Monitoring for Sahel Region

Although seasonal forecast applications are still in an early stage of development there is now enough collective experience from research efforts around the world to induce some meaningful considerations.