Heatwaves (HWs) are one of the "natural" hazards with the greatest impact worldwide in terms of mortality and economic losses, and their effects may be exacerbated in large urban areas. For these reasons, more detailed analyses of urban HW trends represent a priority that cannot be neglected. In this study, HW trends were investigated during the warmest period of the year (May-September) by using a slightly improved version of the EuroHEAT HW definition applied on long meteorological time-series (36-year period, 1980-2015) collected by weather stations located in the capitals of the 28 European Union member countries. Comparisons between two 18-year sub-periods (1980-1997 vs. 1998-2015) were carried out and a city-specific HW hazard index (HWHI), accounting for the main HW characteristics, was proposed. Most of the capitals revealed significant positive trends of the majority of HW hazard characteristics and substantial HWHI increases were observed during the sub-period 1998-2015, especially in the central-eastern and southeastern cities. Conversely, minor HWHI increases were observed in most of the northern capitals and opposite situations were even observed in several northern and especially southwestern cities. The results of this study represent a support for planning urban HW-related mitigation and adaptation strategies with the priority given to the southeastern cities.

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.

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.