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Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes
Wildfires are widespread disasters and are concurrently influenced by global climatic drivers. Due to the widespread and far-reaching influence of climatic drivers, separate regional wildfires may have similar climatic cause mechanisms. Determining a suite of global climatic drivers that explain mos...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755812/ https://www.ncbi.nlm.nih.gov/pubmed/35022560 http://dx.doi.org/10.1038/s41598-021-04726-2 |
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author | Shi, Ke Touge, Yoshiya |
author_facet | Shi, Ke Touge, Yoshiya |
author_sort | Shi, Ke |
collection | PubMed |
description | Wildfires are widespread disasters and are concurrently influenced by global climatic drivers. Due to the widespread and far-reaching influence of climatic drivers, separate regional wildfires may have similar climatic cause mechanisms. Determining a suite of global climatic drivers that explain most of the variations in different homogeneous wildfire regions will be of great significance for wildfire management, wildfire prediction, and global wildfire climatology. Therefore, this study first identified spatiotemporally homogeneous regions of burned area worldwide during 2001–2019 using a distinct empirical orthogonal function. Eight patterns with different spatiotemporal characteristics were identified. Then, the relationships between major burned area patterns and sixteen global climatic drivers were quantified based on wavelet analysis. The most significant global climatic drivers that strongly impacted each of the eight major wildfire patterns were identified. The most significant combinations of hotspots and climatic drivers were Atlantic multidecadal Oscillation-East Pacific/North Pacific Oscillation (EP/NP)-Pacific North American Pattern (PNA) with the pattern around Ukraine and Kazakhstan, El Niño/Southern Oscillation-Arctic Oscillation (AO)-East Atlantic/Western Russia Pattern (EA/WR) with the pattern in Australia, and PNA-AO-Polar/Eurasia Pattern-EA/WR with the pattern in Brazil. Overall, these results provide a reference for predicting wildfire and understanding wildfire homogeneity. |
format | Online Article Text |
id | pubmed-8755812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87558122022-01-14 Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes Shi, Ke Touge, Yoshiya Sci Rep Article Wildfires are widespread disasters and are concurrently influenced by global climatic drivers. Due to the widespread and far-reaching influence of climatic drivers, separate regional wildfires may have similar climatic cause mechanisms. Determining a suite of global climatic drivers that explain most of the variations in different homogeneous wildfire regions will be of great significance for wildfire management, wildfire prediction, and global wildfire climatology. Therefore, this study first identified spatiotemporally homogeneous regions of burned area worldwide during 2001–2019 using a distinct empirical orthogonal function. Eight patterns with different spatiotemporal characteristics were identified. Then, the relationships between major burned area patterns and sixteen global climatic drivers were quantified based on wavelet analysis. The most significant global climatic drivers that strongly impacted each of the eight major wildfire patterns were identified. The most significant combinations of hotspots and climatic drivers were Atlantic multidecadal Oscillation-East Pacific/North Pacific Oscillation (EP/NP)-Pacific North American Pattern (PNA) with the pattern around Ukraine and Kazakhstan, El Niño/Southern Oscillation-Arctic Oscillation (AO)-East Atlantic/Western Russia Pattern (EA/WR) with the pattern in Australia, and PNA-AO-Polar/Eurasia Pattern-EA/WR with the pattern in Brazil. Overall, these results provide a reference for predicting wildfire and understanding wildfire homogeneity. Nature Publishing Group UK 2022-01-12 /pmc/articles/PMC8755812/ /pubmed/35022560 http://dx.doi.org/10.1038/s41598-021-04726-2 Text en © The Author(s) 2022 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 Shi, Ke Touge, Yoshiya Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title | Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title_full | Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title_fullStr | Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title_full_unstemmed | Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title_short | Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
title_sort | characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755812/ https://www.ncbi.nlm.nih.gov/pubmed/35022560 http://dx.doi.org/10.1038/s41598-021-04726-2 |
work_keys_str_mv | AT shike characterizationofglobalwildfireburnedareaspatiotemporalpatternsandunderlyingclimaticcauses AT tougeyoshiya characterizationofglobalwildfireburnedareaspatiotemporalpatternsandunderlyingclimaticcauses |