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The first high spatial resolution multi-scale daily SPI and SPEI raster dataset for drought monitoring and evaluating over China from 1979 to 2018 被引量:2
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作者 Rongrong Zhang Virgílio A.Bento +6 位作者 Junyu Qi Feng Xu Jianjun Wu jianxiu qiu Jianwei Li Wei Shui Qianfeng Wang 《Big Earth Data》 EI CSCD 2023年第3期860-885,共26页
Standardized Precipitation Index(SPI)and Standardized Precipitation Evapotranspiration Index(SPEI),traditionally derived at a monthly scale,are widely used drought indices.To overcome temporalresolution limitations,we... Standardized Precipitation Index(SPI)and Standardized Precipitation Evapotranspiration Index(SPEI),traditionally derived at a monthly scale,are widely used drought indices.To overcome temporalresolution limitations,we have previously developed and published a well-validated daily SPI/SPEI in situ dataset.Although having a high temporal resolution,this in situ dataset presents low spatial resolution due to the scarcity of stations.Therefore,based on the China Meteorological Forcing Dataset,which is composed of data from more than 1,000 ground-based observation sites and multiple remote sensing grid meteorological dataset,we present the first high spatiotemporal-resolution daily SPI/SPEI raster datasets over China.It spans from 1979 to 2018,with a spatial resolution of 0.1°×0.1°,a temporal resolution of 1-day,and the timescales of 30-,90-,and 360-days.Results show that the spatial distributions of drought event characteristics detected by the daily SPI/SPEI are consistent with the monthly SPI/SPEI.The correlation between the daily value of the 12-month scale and the monthly value of SPI/SPEI is the strongest,with linear correlation,Nash-Sutcliffe coefficient,and normalized root mean square error of 0.98,0.97,and 0.04,respectively.The daily SPI/SPEI is shown to be more sensitive to flash drought than the monthly SPI/SPEI.Our improved SPI/SPEI shows high accuracy and credibility,presenting enhanced results when compared to the monthly SPI/SPEI.The total data volume is up to 150 GB,compressed to 91 GB in Network Common Data Form(NetCDF).It can be available from Figshare(https://doi.org/10.6084/m9.figshare.c.5823533)and ScienceDB(https://doi.org/10.57760/sciencedb.j00076.00103). 展开更多
关键词 Drought index climate change climatic disaster Generalized Extreme Value
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