A daily high-resolution surface net radiation dataset in China (2000-2019)

Surface net radiation (Rn) characterizes the energy available at the Earth's surface and is essential for studying atmospheric, water, and carbon cycles. While some global-scale Rn products are available, they often suffer from issues such as data gaps, low resolution, and large uncertainties. Therefore, we developed a high-resolution (0.05°×0.05°) daily Rn dataset from 2000 to 2019 in China using routine meteorological variables from more than 2400 stations and remotely sensed albedo. To ensure the reliability of the dataset, we tested a series of net shortwave and longwave algorithms using ground-based measurements and then employed the optimal combination of algorithms to generate this dataset. The dataset was validated against Rn observations from 43 flux towers across China. Our dataset exhibits high accuracy with KGE and Bias values of 0.81 and 0.38%, respectively.