A dense station-based, long-term and high-accuracy dataset of daily surface solar radiation in China

Abstract

Abstract. The lack of long-term and high-quality solar radiation data has been an obstacle for scientific and industrial fields. In this study, a dense station-based, long-term and high-accuracy dataset of daily surface solar radiation was developed using two surface radiation models. One is the model developed by Yang et al. (2006) for global radiation estimation, and the other is the model developed by Tang et al. (2018) for direct radiation estimation. The main inputs for the development of the dataset are surface pressure, air temperature, relative humidity, horizontal visibility and sunshine duration, which are the routine meteorological variables observed at the 2743 China Meteorological Administration (CMA) weather stations. Validation against in situ observations and comparisons with two satellite-based radiation products shows that our station-based radiation dataset clearly outperforms the satellite-based radiation products at both daily and monthly scales. In addition, our dataset is available for more than 60 years and includes three radiation components of global, direct and diffuse radiation, which is not possible with satellite products. This station-based radiation dataset will contribute to the climate change research and solar energy engineering applications in the future. The station-based dataset is now available at https://doi.org/10.11888/Atmos.tpdc.300461 (Tang, 2023).