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The high spatial resolution and century-long Standardized Precipitation Evapotranspiration Index (SPEI) dataset with a spatial resolution of 0.0083 degrees (~1 km) was spatially downscaled from the global SPEI data with a 0.5 degrees spatial resolution (https://spei.csic.es/database.html) based on machine learning integrated with high spatial resolution climatic and topographic variables. The 1-km SPEI datasets are across the land areas of China from January 1901 to December 2020, including 1-month, 3-month, 6-month and 12-month SPEIs. The unit of the data is 0.01. The dataset was evaluated using the root zone soil moisture and the historical drought events, and the evaluation indicated that the high spatial resolution SPEI dataset is reliable. Data Information: GPRChinaSPEI1km: High spatial resolution and century-long SPEI datasets over China from 1901 to 2020 generated by machine learning Publication: He, Q., Wang, M., Liu, K., & Wang, B. (2025). High-resolution Standardized Precipitation Evapotranspiration Index (SPEI) reveals trends in drought and vegetation water availability in China. Geography and Sustainability, 6(2), 100228. https://doi.org/10.1016/j.geosus.2024.08.007 ----------------------------------------------------data description--------------------------------------------- This is a gridded dataset for the Standardized Precipitation Evapotranspiration Index (SPEI) at a spatial resolution of 1 km over the main terrestrial lands of China for each month during 1901-2020, which is generated using the Gaussian process regression (GPR) based on the Global SPEI database (https://spei.csic.es/database.html) integrated with high spatial resolution climatic and topographic variables. Four timescales of SPEI were generated: 1-month (SPEI-1), 3-month (SPEI-3), 6-month (SPEI-6) and 12-month (SPEI-12). The details are as follows: Region: China Temporal Extent: January 1901 to December 2020 Spatial resolution: 0.0083° (~1 km) Temporal resolution: month Timescales: 1-month, 3-month, 6-month and 12-month Data format: GeoTIFF Unit: unitless (0.01) Geographic coordinate system: WGS 1984 ---------------------------------------------------dataset filename--------------------------------------------- The file name specifically shows the data information. For example, “SPEI_1_2020_1.tif” means “1-month SPEI of January 2020”. “SPEI_3_2020_1.tif” means “3-month SPEI of January 2020”. All the file names are formatted in “SPEI_timescale_year_month” timescale: 1, 3, 6 and 12 indicate 1-month, 3-month, 6-month and 12-month, respectively year: from 1901 to 2020 month: from 1 to 12 --------------------------------------------------storage information------------------------------------------- The high-resolution SPEI dataset is stored in TIFF format using WGS 1984 coordinate system. The data type is int16 with a scale factor of 0.01. The nodata value is -32768. The dataset requires multiplication by 0.01 during application to obtain the actual value ranges. The data were compressed into .rar format every 10 years for each timescale SPEI.
Machine Learning, China, Drought, High spatial resolution, Standardized Precipitation Evapotranspiration Index, Century-long
Machine Learning, China, Drought, High spatial resolution, Standardized Precipitation Evapotranspiration Index, Century-long
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