Grid-based fusion data of monthly temperature and precipitation data of 41 CMIP6 models for China

The spatial resolution was 0.5 × 0.5° with the time period from 1979-01 to 2014-12 as historical period and 2015-01 to 2099-12 as the future projection.The new data was synthesized through gird-based model assessment and selectiton for the 5 models with the bestperformance, corrected the inherent biases of models with the Quantile Mapping (QM) method, then applied the multi-model ensemble of the 5 best performing bias-corrected CMIP6 models for each grid.The results verified that the Grid-based fusion data of monthly temperature and precipitation of 41 CMIP6 models for China (GFCC) showed significant simulation improvement in both spatial and temporal scales compared with other fusion data constructed by methods commonly used.