%0 Dataset
%T Global Integrated and Homogenized Solar surface Radiation Datasets
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/42879a63-111d-4065-add7-12436d9e0f9d
%W NCDC
%A None
%K Surface solar radiation;SSRIH;convolutional neural network
%X Surface solar radiation (SSR) is an essential factor in the flow of surface energy, enabling accurate capturing of long-term climate change and understanding of the energy balance of Earth's atmosphere system. However, the long-term trend estimation of SSR is subject to significant uncertainties due to the temporal inhomogeneity and the uneven spatial distribution of in situ observations. This paper develops an observational integrated and homogenized global terrestrial (except for Antarctica) station SSR dataset (SSRIHstation) by integrating all available SSR observations, including the existing homogenized SSR results. The series is then interpolated in order to obtain a 5° × 5°  resolution gridded dataset (SSRIHgrid). On this basis, we further reconstruct a long-term (1955–2018) global land (except for Antarctica) SSR anomaly dataset with a 5° × 2.5° resolution (SSRIH20CR) by training improved partial convolutional neural network deep-learning methods based on 20th Century Reanalysis version 3 (20CRv3).