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　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).　©　2023　The　Author(s).　Published　by　Taylor　&　Francis　Group　and　Science　Press　on　behalf　of　the　International　Society　for　Digital　Earth,　supported　by　the　International　Research　Center　of　Big　Data　for　Sustainable　Development　Goals,　and　CASEarth　Strategic　Priority　Research　Programme.