Analysis of the thermal comfort in cycling athletes

Abstract This research presents a detailed analysis of thermal comfort in road cycling athletes. The data have been collected during experimental road test in prevision of the UCI Road World Championship 2013 (Florence-Tuscany, Italy), considering the different technical situations and the different environmental conditions expected as the most probable for the race's period. The analysis presented in this work is based on the in-situ measurements of both environmental and physiological parameters (i.e.: air temperature, relative humidity, true wind velocity, apparent wind velocity, skin temperature, clothing temperature, heat transfer resistance of the clothing, internal heat production) made over different athletes in different race conditions. The recorded data have been used as input for the model "RayMan" [1] , [2] for the assessment of the thermal comfort using thermal indices such as Predicted Mean Vote (PMV) and Physiological Equivalent Temperature (PET). It should be noted that the apparent wind velocity, which is a fundamental parameter in this kind of analysis but often disregarded, is evaluated in relationship with the movement and the effort made by the cyclist. The results obtained by the comparison of the PET and PMV indices with the measured skin temperature confirm the importance of considering the variation of environmental parameters in both training and strategy assessment and provide a working method which is believed to be innovative for the applied sport research

Italian codified hashtags for weather warning on Twitter – who is really using them?

Abstract. During emergencies, an increasing number of messages are shared through social media platforms, becoming a primary source of information for lay people and emergency managers. Weather services and institutions have started to employ social media to deliver weather warnings even if sometimes this communication lacks in strategy. In Twitter, for example, hashtagging is very important to associate messages with certain topics; in recent years, codified hashtagging is emerging as a practical way to coordinate Twitter conversations during emergencies and quickly retrieve relevant information. In 2014, a syntax for codified hashtags for weather warning was proposed in Italy: a list of 20 hashtags, realized by combining #allertameteo (weather warning) + XXX, where final letters code the regional identification. This contribution presents a monitoring of Twitter usage of weather warning codified hashtags in Italy (since July 2015) and an analysis of different contexts. Twitter messages were retrieved using TwitterVigilance, a multi-users platform to crawl Twitter data, collect and store messages and perform quantitative analytics, about users, hashtags, tweets/retweets volumes. The Codified Hashtags data set is presented and discussed with main analytics and evaluation of regional contexts where it was successfully employed

On the Implementation of a regional X-bandweather radar network

In the last few years, the number of worldwide operational X-band weather radars has rapidly been growing, thanks to an established technology that offers reliability, high performance, and reduced efforts and costs for installation and maintenance, with respect to the more widespread C- and S-band systems. X-band radars are particularly suitable for nowcasting activities, as those operated by the LaMMA (Laboratory of Monitoring and Environmental Modelling for the sustainable development) Consortium in the framework of its institutional duties of operational meteorological surveillance. In fact, they have the capability to monitor precipitation, resolving very local scales, with good spatial and temporal details, although with a reduced scanning range. The Consortium has recently installed a small network of X-band weather radars that partially overlaps and completes the existing national radar network over the north Tyrrhenian area. This paper describes the implementation of this regional network, detailing the aspects related with the radar signal processing chain that provides the final reflectivity composite, starting from the acquisition of the signal power data. The network performances are then qualitatively assessed for three case studies characterised by different precipitation regimes and different seasons. Results are satisfactory especially during intense precipitations, particularly regarding what concerns their spatial and temporal characterisation

The 8 and 9 September 2002 flash flood event in France: a model intercomparison

Within the framework of the European Interreg IIIb Medocc program, the HYDROPTIMET project aims at the optimization of the hydrometeorological forecasting tools in the context of intense precipitation within complex topography. Therefore, some meteorological forecast models and hydrological models were tested on four Mediterranean flash-flood events. One of them occured in France where the South-eastern ridge of the French “Massif Central”, the Gard region, experienced a devastating flood on 8 and 9 September 2002. 24 people were killed during this event and the economic damage was estimated at 1.2 billion euros. To built the next generation of the hydrometeorological forecasting chain that will be able to capture such localized and fast events and the resulting discharges, the forecasted rain fields might be improved to be relevant for hydrological purposes. In such context, this paper presents the results of the evaluation methodology proposed by Yates et al. (2005) that highlights the relevant hydrological scales of a simulated rain field. Simulated rain fields of 7 meteorological model runs concerning with the French event are therefore evaluated for different accumulation times. The dynamics of these models are either based on non-hydrostatic or hydrostatic equation systems. Moreover, these models were run under different configurations (resolution, initial conditions). The classical score analysis and the areal evaluation of the simulated rain fields are then performed in order to put forward the main simulation characteristics that improve the quantitative precipitation forecast. The conclusions draw some recommendations on the value of the quantitative precipitation forecasts and way to use it for quantitative discharge forecasts within mountainous areas

Stima dei danni da vento ai soprassuoli forestali in Regione Toscana a seguito dell'evento del 5 marzo 2015

Il vento è uno dei maggiori fattori di disturbo per le foreste europee e i cambiamenti climatici hanno provocato un aumento di eventi estremi negli ultimi anni. La regione Toscana tra il 4 e il 5 marzo 2015 è stata colpita da una tempesta di vento che ha provocato notevoli danni ai soprassuoli forestali. L’obiettivo di questo lavoro è di sviluppare una metodologia speditiva per la mappatura delle aree danneggiate in termini di superfici interessate, numero di piante atterrate e volume legnoso a terra. Il contributo illustra a tal fine l’utilizzo di dati telerilevati e in particolare le potenzialità dei dati Airborne Laser Scanning (ALS)

The effect of training system and cultivar on the rate of leaf appearance of the grapevine (<em>Vitis vinifera</em> L.)

The rate of leaf appearance was compared in two grapevine (Vitis vinifera L.) varieties (Sangiovese and Cabernet-Sauvignon) and in three different short pruning training systems (traditional cordon, single curtain and vertical cordon pruned). Results showed that there was no significant effect of training systems on leaf appearance. There was instead a significant effect of cultivar that suggested a different adaptive response of cultivars to climates they were selected for. A recently published simulation model of leaf appearance in grapevine was used to interpretate these differences

Assessment of Water Stress Conditions in Central Italy by the Use of Ground and Remotely Sensed Weather Datasets

Aridity and drought, which are determined by climatic and temporary water scarcity, respectively, are important limiting factors for plant gross primary production. These phenomena are commonly assessed and/or monitored by means of weather indices, most of which are based on observations of precipitation and potential evapotranspiration. The estimation of such indices over large areas can be carried out using multiple datasets, i.e., those derived from weather stations, satellite images, and ground radars. The possibility of using interpolated or remotely sensed datasets in place of ground measurements was currently investigated for Tuscany, a region in Central Italy, showing complex and heterogeneous environmental features. The former weather datasets were first evaluated versus corresponding ground measurements. Next, the basic weather variables were combined and cumulated over 30–60 days to yield synthetic indicators of water deficit, which were assessed in the same way. Finally, these indicators were evaluated to predict the soil water conditions of a meadow and an olive grove during the 2021 summer period. The results obtained indicate that the use of the multi-source weather datasets induces only a minor deterioration of the water stress indicators and is therefore efficient to monitor the water status of different ecosystems with high spatial (200 m) and temporal (daily) details