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An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering
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 evolut...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950368/ https://www.ncbi.nlm.nih.gov/pubmed/36823221 http://dx.doi.org/10.1038/s41598-023-30153-6 |
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author | Cammalleri, Carmelo Acosta Navarro, Juan Camilo Bavera, Davide Diaz, Vitali Di Ciollo, Chiara Maetens, Willem Magni, Diego Masante, Dario Spinoni, Jonathan Toreti, Andrea |
author_facet | Cammalleri, Carmelo Acosta Navarro, Juan Camilo Bavera, Davide Diaz, Vitali Di Ciollo, Chiara Maetens, Willem Magni, Diego Masante, Dario Spinoni, Jonathan Toreti, Andrea |
author_sort | Cammalleri, Carmelo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9950368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99503682023-02-25 An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering Cammalleri, Carmelo Acosta Navarro, Juan Camilo Bavera, Davide Diaz, Vitali Di Ciollo, Chiara Maetens, Willem Magni, Diego Masante, Dario Spinoni, Jonathan Toreti, Andrea Sci Rep Article 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. Nature Publishing Group UK 2023-02-23 /pmc/articles/PMC9950368/ /pubmed/36823221 http://dx.doi.org/10.1038/s41598-023-30153-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cammalleri, Carmelo Acosta Navarro, Juan Camilo Bavera, Davide Diaz, Vitali Di Ciollo, Chiara Maetens, Willem Magni, Diego Masante, Dario Spinoni, Jonathan Toreti, Andrea An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title | An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title_full | An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title_fullStr | An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title_full_unstemmed | An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title_short | An event-oriented database of meteorological droughts in Europe based on spatio-temporal clustering |
title_sort | event-oriented database of meteorological droughts in europe based on spatio-temporal clustering |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950368/ https://www.ncbi.nlm.nih.gov/pubmed/36823221 http://dx.doi.org/10.1038/s41598-023-30153-6 |
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