An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering

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作者
Carmelo Cammalleri
Juan Camilo Acosta Navarro
Davide Bavera
Vitali Diaz
Chiara Di Ciollo
Willem Maetens
Diego Magni
Dario Masante
Jonathan Spinoni
Andrea Toreti
机构
[1] European Commission, Dipartimento di Ingegneria Civile e Ambientale
[2] Joint Research Centre (JRC),undefined
[3] ARCADIA SIT,undefined
[4] Technische Universiteit Delft,undefined
[5] ARHS Developments,undefined
[6] Politecnico di Milano,undefined
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Droughts evolve in space and time without following borders or pre-determined temporal constraints. Here, we present a new database of drought events built with a three-dimensional density-based clustering algorithm. The chosen approach is able to identify and characterize the spatio-temporal evolution of drought events, and it was tuned with a supervised approach against a set of past global droughts characterized independently by multiple drought experts. About 200 events were detected over Europein the period 1981-2020 using SPI-3 (3-month cumulated Standardized Precipitation Index) maps derived from the ECMWF (European Centre for Medium-range Weather Forecasts) 5th generation reanalysis (ERA5) precipitation. The largest European meteorological droughts during this period occurred in 1996, 2003, 2002 and 2018. A general agreement between the major events identified by the algorithm and drought impact records was found, as well as with previous datasets based on pre-defined regions.
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