Evidence map›Paper›PMID 41285986›Full record

ArticleScientific data2025

A global drought dataset for Multivariate Composite Drought Index (MCDI) and its constituent drought indices.

Mengjia Yuan, Guojing Gan, Jingyi Bu, Yanxin Su, Hongyu Ma, Xianghe Liu, Leyao Zhang, Yongqiang Zhang, Yanchun Gao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Mengjia YuanKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Guojing GanState Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 211135, China. gjgan@niglas.ac.cn.
Jingyi BuEarth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824, USA.
Yanxin SuKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Hongyu MaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Xianghe LiuKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Leyao ZhangKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Yongqiang ZhangKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.ORCID http://orcid.org/0000-0002-3562-2323
Yanchun GaoKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. gaoyanc@igsnrr.ac.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) No. 42071054National Natural Science Foundation of China (National Science Foundation of China) No. 42330506National Natural Science Foundation of China (National Science Foundation of China) No. 42361144709
6 · The paper itself

Abstract

High-resolution drought index datasets are essential for drought monitoring and assessment. Despite numerous global/regional drought index datasets, the composite drought index datasets that comprehensively consider meteorological, agricultural, and hydrological factors are still very few, thus hindering the capture of complex drought dynamics and comprehensive risk assessment. To address this gap, this study produced a 0.1° resolution global drought dataset (1980-2019) based on the newly developed concept of Multivariate Composite Drought Index (MCDI), which considered the time lag and cumulative effects of drought and could characterize comprehensive drought characteristics effectively. The dataset contains MCDI and its four constituent indices (Standardized Precipitation Actual Evapotranspiration Index (SPAEI), Standardized Soil Moisture Index (SSI), Standardized Runoff Index (SRI), Water Storage Deficit Index (WSDI)) on a monthly scale. Verification results showed that they indicated the drought evolution and ecosystem response process well, especially the MCDI. Overall, the dataset compensated for the data deficit of the comprehensive drought index and would provide data support for global drought monitoring and adaptive management of drought under climate change.

Identifiers

PMID41285986
PMCPMC12749506

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