A 1 km monthly dataset of historical and future climate changes over China

The ANUSPLIN interpolated historical data showed a strong correlation with observations (all correlation coefficients above 0.91). The historical interpolations generated by the ANUSPLIIN software showed a good fit (above 0.91) with observations. The bias correction improved the accuracy of most GCM original simulations, reducing the bias by 0.69%–58.63%.

This dataset aims to provide high-resolution, bias-corrected long-term historical and future climate data for climate and ecological research. All computations were performed using R, and the corresponding code can be found in the dataset folder: “Code”.All data are provided in GeoTIFF (.tif) format, where each file for the basic climate variables contains 12 bands, representing monthly data in ascending order (e.g., Band 1 corresponds to January).

To facilitate data storage, all files are provided in compressed archives, following a consistent naming convention:(1) Historical data: China_Variable_1km_1991–2020.tifWhere, Variable represents the abbreviation of the 28 climate variables.Example: China_pr_1km_1991–2020.tif.(2) Future data: China_Variable_Model_VariantLabel_1km_StartYear-EndYear_Scenario.tifWhere, Variable is the 28 climate variables; Model is the GCM name; VariantLabel is r1i1p1f1 in this study; StartYear-EndYear is the future period; Scenario is the SSP climate scenarioExample: China_tasmin_MRI-ESM2-0_r1i1p1f1_1km_2071–2100_SSP585.tif.