| Abstract: | Surface solar radiation (SSR) is a key component of the energy budget of the Earth’s surface, and it varies at different spatial and temporal scales. Considerable knowledge of how and why SSR varies is crucial to a better understanding of climate change, which surely requires long-term measurements of high quality. The objective of this study is to introduce a value-added SSR dataset from Oct 2004 to Oct 2019 based on measurements taken at Xianghe, a suburban site in the North China Plain; two value-added products based on the 1-minute SSR measurements are developed. The first is clear sky detection by using a machine learning model. The second is cloud fraction estimation derived from an effective semi-empirical method. A “brightening” of global horizontal irradiance (GHI) was revealed and found to occur under both clear and cloudy conditions. This could likely be attributed to a reduction in aerosol loading and cloud fraction. This dataset could not only improve our knowledge of the variability and trend of SSR in the North China Plain, but also be beneficial for solar energy assessment and forecasting. |
