Autor: |
Giuseppe Prete, Elenio Avolio, Vincenzo Capparelli, Fabio Lepreti, Vincenzo Carbone |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Atmosphere, Vol 14, Iss 3, p 553 (2023) |
Druh dokumentu: |
article |
ISSN: |
2073-4433 |
DOI: |
10.3390/atmos14030553 |
Popis: |
We apply extreme value theory (EVT) to study the daily precipitation and temperature extremes in the Calabria region (southern Italy) mainly considering a long-term observational dataset (1990–2020) and also investigating the possible use of the ERA5 (ECMWF Reanalysis v5) fields. The efficiency of the EVT applied on the available observational dataset is first assessed—both through a punctual statistical analysis and return-level maps. Two different EVT methods are adopted, namely the peak-over-threshold (POT) approach for the precipitation and the block-maxima (BM) approach for the temperature. The proposed methodologies appear to be suitable for describing daily extremes both in quantitative terms, considering the punctual analysis in specific points, and in terms of the most affected areas by extreme values, considering the return-level maps. Conversely, the analysis conducted using the reanalysis fields for the same time period highlights the limitations of using these fields for a correct quantitative reconstruction of the extremes while showing a certain consistency regarding the areas most affected by extreme events. By applying the methodology on the observed dataset but focusing on return periods of 50 and 100 years, an increasing trend of daily extreme rainfall and temperature over the whole region emerges, with specific areas more affected by these events; in particular, rainfall values up to 500 mm/day are predicted in the southeastern part of Calabria for the 50-year-return period, and maximum daily temperatures up to 40 °C are expected in the next 100 years, mainly in the western and southern parts of the region. These results offer a useful perspective for evaluating the exacerbation of future extreme weather events possibly linked to climate change effects. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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