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A global drought dataset for Multivariate Composite Drought Index (MCDI) and its constituent drought indices
Mengjia Yuan1,2, Guojing Gan3, Jingyi Bu4
1Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
None:
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.
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