Cargando…
A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022
Droughts cause multiple ecological and social damages. Drought indices are key tools to quantify drought severity, but they are mainly limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673942/ https://www.ncbi.nlm.nih.gov/pubmed/38001318 http://dx.doi.org/10.1038/s41597-023-02756-1 |
_version_ | 1785149664954155008 |
---|---|
author | Zhang, Xia Duan, Jianping Cherubini, Francesco Ma, Zhuguo |
author_facet | Zhang, Xia Duan, Jianping Cherubini, Francesco Ma, Zhuguo |
author_sort | Zhang, Xia |
collection | PubMed |
description | Droughts cause multiple ecological and social damages. Drought indices are key tools to quantify drought severity, but they are mainly limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (e.g., onset and cessation time) and help timely potential mitigation of adverse effects. Here, we propose a dataset of a daily drought index named daily evapotranspiration deficit index (DEDI), which is produced for global land areas from 1979 to 2022 using actual and potential evapotranspiration data. Validation efforts show that the DEDI dataset can well identify dry and wet variations in terms of spatial patterns and temporal evolutions when compared with other available drought indices on a daily scale. The dataset also has the capability to capture recent drying trends and to detect ecology- or agriculture-related droughts. Overall, the DEDI dataset is a step forward in facilitating drought monitoring and early warning at higher temporal resolution than other compared existing products. |
format | Online Article Text |
id | pubmed-10673942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106739422023-11-24 A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 Zhang, Xia Duan, Jianping Cherubini, Francesco Ma, Zhuguo Sci Data Data Descriptor Droughts cause multiple ecological and social damages. Drought indices are key tools to quantify drought severity, but they are mainly limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (e.g., onset and cessation time) and help timely potential mitigation of adverse effects. Here, we propose a dataset of a daily drought index named daily evapotranspiration deficit index (DEDI), which is produced for global land areas from 1979 to 2022 using actual and potential evapotranspiration data. Validation efforts show that the DEDI dataset can well identify dry and wet variations in terms of spatial patterns and temporal evolutions when compared with other available drought indices on a daily scale. The dataset also has the capability to capture recent drying trends and to detect ecology- or agriculture-related droughts. Overall, the DEDI dataset is a step forward in facilitating drought monitoring and early warning at higher temporal resolution than other compared existing products. Nature Publishing Group UK 2023-11-24 /pmc/articles/PMC10673942/ /pubmed/38001318 http://dx.doi.org/10.1038/s41597-023-02756-1 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 | Data Descriptor Zhang, Xia Duan, Jianping Cherubini, Francesco Ma, Zhuguo A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title | A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title_full | A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title_fullStr | A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title_full_unstemmed | A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title_short | A global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
title_sort | global daily evapotranspiration deficit index dataset for quantifying drought severity from 1979 to 2022 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673942/ https://www.ncbi.nlm.nih.gov/pubmed/38001318 http://dx.doi.org/10.1038/s41597-023-02756-1 |
work_keys_str_mv | AT zhangxia aglobaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT duanjianping aglobaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT cherubinifrancesco aglobaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT mazhuguo aglobaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT zhangxia globaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT duanjianping globaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT cherubinifrancesco globaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 AT mazhuguo globaldailyevapotranspirationdeficitindexdatasetforquantifyingdroughtseverityfrom1979to2022 |