All-sky 0.05° daily Tmax across Eurasia during 2003-2018

This is an all-sky daily maximum air temperature (Tmax) product at 0.05° spatial resolution across Eurasia for 2003-2018. This product is generated using a satellite-derived model, including parameters such as daytime and nighttime land surface temperature (LST), downward shortwave radiation, net radiation, leaf area index, enhanced vegetation index, and albedo. The machine learning method, histogram-based gradient boosting (HGB) was employed to train Tmax estimation models using 4476 stations from GHCN, GSOD, and CMDC. The determination coefficient (R2) and root-mean-square-error (RMSE) of the HGB model are 0.984 and 1.736 ℃ with non-missing values in datasets and 0.985 and 1.812 ℃ with missing values respectively. In comparison with existing temperature products, the R2 and MAE values were reported as 0.980 and 1.531℃, indicating strong competition among existing Tmax products. In summary, our study provides a scheme for estimating parameters with missing feature values in a consistent manner and provides a solid foundation for the environmental and climate changes studies.