Standardized　Precipitation　Index　(SPI)　and　Standardized　Precipitation　Evapotranspiration　Index　(SPEI),　traditionally　derived　at　a　monthly　scale,　are　widely　used　drought　indices.　To　overcome　temporal-resolution　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　resolu-tion　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　degrees　x　0.1　degrees,　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　con-sistent　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　nor-malized　root　mean　square　error　of　0.98,　0.15,　and　0.32,　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).