A comprehensive characterization of mesocyclonic and nonmesocyclonic tornadoes in Italy - Roberto Ingrosso; Leonardo Bagaglini; Federico Baggiani; Roberta D’Agostino; Gianni Messeri; Alessandro Piazza; Pierluigi Randi; Stefano Salvatore; Roberto Vallorani; Mario Marcello Miglietta (Atmospheric Research, 2026)

Climate change and occupational health and safety. Risk of injuries, productivity loss and the co-benefits perspective - A. Marinaccio; C. Gariazzo; L. Taiano; M. Bonafede; D. Martini; S. D'Amario; F. de’Donato; M. Morabito; Filippo Ariani; Alessandra Binazzi; Andrea Bogi; Michela Bonafede; et al. (Environmental Research, 2025)

Temperature–humidity index monitoring during two summer seasons in dairy cow sheds in Mugello (Tuscany) - Alessandro Messeri; Marco Mancini; Riccardo Bozzi; Silvia Parrini; Francesco Sirtori; Marco Morabito; Alfonso Crisci; Gianni Messeri; Alberto Ortolani; Bernardo Gozzini; Simone Orlandini; Luca Fibbi; et al. (International Journal of Biometeorology, 2023)
Many studies have reported that the impact of high temperatures affects physiology, welfare, health, and productivity of farm animals, and among these, the dairy cattle farming is one of the livestock sectors that suffers the greatest effects. The temperature–humidity index (THI) represents the state of the art in the evaluation of heat stress conditions in dairy cattle but often its measurement is not carried out in sheds. For this reason, the aim of this study was the monitoring of the THI in three dairy cattle farms in Mugello (Tuscany) to understand its influence on dairy cows. THI values were calculated using meteorological data from direct observation in sheds and outdoor environments. Data relating to the animal’s behavior were collected using radio collars. The Pearson test and Mann–Kendall test were used for statistical analysis. The results highlighted a significant ( P < 0.001) upward trend in THImax during the last 30 years both in Low Mugello (+ 1.1 every 10 years) and in High Mugello (+ 0.9 every 10 years). In Low Mugello sheds, during the period 2020–2022, more than 70% of daytime hours during the summer period were characterized by heat risk conditions (THI > 72) for livestock. On average the animals showed a significant ( P < 0.001) decrease in time spent to feeding and rumination, both during the day and the night, with a significant ( P < 0.001) increase in inactivity. This study fits into the growing demand for knowledge of the micro-climatic conditions within farms in order to support resilience actions for protecting both animal welfare and farm productivity from the effects of climate change. This could also be carried out thanks to estimation models which, based on the meteorological conditions forecast, could implement the thermal stress indicator (THI) directly from the high-resolution meteorological model, allowing to get a prediction of the farm’s potential productivity loss based on the expected THI.

Extreme precipitation events and their relationships with circulation types in Italy - Maurizio Iannuccilli; Giorgio Bartolini; Giulio Betti; Alfonso Crisci; Daniele Grifoni; Bernardo Gozzini; Alessandro Messeri; Marco Morabito; Claudio Tei; Tommaso Torrigiani Malaspina; Roberto Vallorani; Gianni Messeri (International Journal of Climatology, 2021)
Extreme precipitation (EP) events are life‐threatening phenomena that are expected to continue to increase because of ongoing climate change. In the past decade, these events have been caused by important and well‐documented variations in large‐scale atmospheric circulation. Identifying the trends, dynamics, and related causes of EP could help in recognizing geographical areas that are at great risk and reducing their adverse impacts, particularly on a relatively small area such as the Italian peninsula. The relationships between large‐scale circulation types (CTs) and EP were investigated using a long time‐series (1979–2015) of meteorological data recorded by 46 weather stations in Italy. EP was defined as the number of days with accumulated precipitation above the 90th percentile (R90p). The seasonal trends of R90p were not homogeneous and showed significant increases primarily in winter and spring. Only a few CTs were significantly related to R90p, and this relationship was strongly dependent on latitude, orographic exposure, and season. Heterogeneous seasonal trends for daily CT occurrences were also observed. ‘Cyclonic’ CTs grouped together showed significant increasing trends in all seasons, whereas ‘Anticyclonic’ ones showed a generalized decreasing trend, explaining, only partially, the increase of R90p observed in some stations. Meanwhile, the R90p trends seem to be more influenced by the variations in the internal characteristics of CTs (i.e., the variation of some meteorological parameters that characterize them) observed over the past few decades than by changes in CT frequencies but still with high heterogeneity in Italy. The results of this and other similar studies can provide useful support for the implementation of mitigation and adaptation strategies to minimize the impacts of severe weather, particularly in complex areas such as the Mediterranean basin.

Wild ungulates and environmental temperature: analysis on the possible utilization of data from sensor placed on GPS collars - Alessandro Messeri; Valentina Becciolini; Gianni Messeri; Marco Morabito; Alfonso Crisci; Simone Orlandini; Maria Paola Ponzetta (International Journal of Biometeorology, 2019)

Circulation type classifications for temperature and precipitation stratification in Italy - Roberto Vallorani; Giorgio Bartolini; Giulio Betti; Alfonso Crisci; Bernardo Gozzini; Daniele Grifoni; Maurizio Iannuccilli; Alessandro Messeri; Gianni Messeri; Marco Morabito; Giampiero Maracchi (International Journal of Climatology, 2018)
During the last few decades, weather circulation type classifications (CTCs) have been widely used to gain insight into processes at the synoptic scale, but also for studying the relationship between atmospheric circulation and surface climate variability. This study aims to evaluate the best performing CTCs based on COST733 software for the stratification of daily ground‐level precipitation and surface air temperature across Italy by means of four statistical metrics. Six classification methods belonging to the four COST733 groups (threshold‐based, PCA‐based, leader algorithms and optimization algorithms) were investigated on 32 and 26 data time series derived from Italian weather stations for daily mean temperature and daily mean precipitation, respectively. CTCs were computed using gridded mean sea level pressure and geopotential height at 500 hPa derived from the NCEP Reanalysis 2 dataset between 1979 and 2015 and tested on three different numbers of classes (8/9, 11/12 and 18 circulation types). Evaluation metrics showed an evident seasonal variability and high‐spatial heterogeneity reflecting the geographical complexity of the Italian territory. The study points out that the best classification, both for temperature and precipitation, is strongly dependent on the classification variable (mean sea level pressure and geopotential height at 500 hPa) showing relevant differences between surface temperature and precipitation. A low number of circulation types (8/9) resulted as the most appropriate grouping for the Italian domain and the Principal Component Transversal and Simulated Annealing were the best performing classification procedures for ground‐level precipitation and temperature stratification, respectively.

Recent trends in seasonal and annual precipitation indices in Tuscany (Italy) - Giorgio Bartolini; Alessandro Messeri; Daniele Grifoni; Daniele Mannini; Simone Orlandini (Theoretical and Applied Climatology, 2014)