Surface solar radiation data and its long-term variation

With the rapid development of satellite observation technology, scientists have made relatively accurate estimates of the energy budget at the top of the Earth"s atmosphere. However, the level of estimation error in the Earth"s surface energy imbalance is still more than an order of magnitude greater than the changes in radiative forcing caused by the increase in greenhouse gases. Among the various components of energy imbalance estimation on the Earth"s surface, the downward shortwave solar radiation contributes one of the most important sources of error. Therefore, accurate observation of surface solar radiation (SSR) has become a key variable in reducing this error. At the same time, SSR is not only an important driving data for simulating land surface processes, but also an important indicator for the utilization of renewable solar photovoltaic energy. Its long-term changes have always been a key scientific issue of concern for scientists in many fields. This paper starts with a comparison of existing SSR data products, discusses the bias and uncertainty issues in the long-term changes of SSR, and clarify the importance of developing high-quality SSR observation baseline data products. On this basis, the paper introduces a series of researches in recent years, based on the most complete SSR station observation data to date, systematically considering its inhomogeneity and sampling problems, performing systematic homogenization processing and AI reconstruction on site sequences, and estimating the long-term changes and uncertainty levels of global and regional SSRs. These studies provide new evidence for global and regional climate change observation, detection attribution, and future projection. Finally, the paper provides an outlook on the existing problems and future development trends in current SSR data and long-term change research.