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Surface solar radiation (SSR) is the main factor affecting the earth’s climate and environment and its variations and the reason for these variations are an important part of climate change research. In this research, we investigated the long-term variations of SSR during 1984–2016 and the quantitative influences of atmospheric aerosols, anthropogenic emissions, and meteorological conditions on SSR over China’s mainland. The results show the following: (1) The annual average SSR values had a decline trend at a rate of −0.371 Wm−2 yr−1 from 1984 to 2016 over China. (2) The aerosol optical depth (AOD) plays the main role in inducing variations in SSR over China, with r values of −0.75. Moreover, there are marked regional differences in the influence of anthropogenic emissions and meteorological conditions on SSR trends. (3) From a regional perspective, AOD is the main influencing factor on SSR in northeast China (NEC), Yunnan Plateau and surrounding regions (YPS), North China (NC), and Loess Plateau (LP), with r values of −0.65, −0.60, −0.89, and −0.50, respectively. However, the main driving factors for SSR in northwest China (NWC) are “in cloud optical thickness of all clouds” (TAUTOT) (−0.26) and black carbon (BC) anthropogenic emissions (−0.21). TAUTOT (−0.39) and total precipitable water vapor (TQV) (−0.29) are the main influencing factors of SSR in the middle-lower Yangtze Plain (MYP). The main factors that influence SSR in southern China (SC) are surface pressure (PS) (−0.66) and AOD (−0.43). This research provides insights in understanding the variations of SSR and its relationships with anthropogenic conditions and meteorological factors.

Diffuse solar radiation is an essential component of surface solar radiation that contributes to carbon sequestration, photovoltaic power generation, and renewable energy production in terrestrial ecosystems. We constructed a 39-year (1982–2020) daily diffuse solar radiation dataset (CHSSDR), using ERA5 and MERRA_2 reanalysis data, with a spatial resolution of 10 km through a developed ensemble model (generalized additive models, GAM). The validation results, with ground-based measurements, showed that GAM had a high and stable performance with the correlation coefficient (R), root-mean-square error (RMSE), and mean absolute error (MAE) for the sample-based cross-validations of 0.88, 19.54 Wm−2, and 14.87 Wm−2, respectively. CHSSDR had the highest consistency with ground-based measurements among the four diffuse solar radiation products (CERES, ERA5, JiEA, and CHSSDR), with the least deviation (MAE = 15.06 Wm−2 and RMSE = 20.22 Wm−2) and highest R value (0.87). The diffuse solar radiation values in China range from 59.13 to 104.65 Wm−2, with a multi-year average value of 79.39 Wm−2 from 1982 to 2020. Generally, low latitude and low altitude regions have larger diffuse solar radiation than high latitude and high altitude regions, and eastern China has less diffuse solar radiation than western China. This dataset would be valuable for analyzing regional climate change, photovoltaic applications, and solar energy resources. The dataset is freely available from figshare.

Abstract. Solar irradiance (SI) is the main driving factor contributing to climate change and energy balance between the land and atmosphere. High-quality records of global solar irradiance (GHI), direct normal irradiance (DNI) and diffuse solar irradiance (DIF) are of vital importance for solar applications, but the solar radiation observations are sparse around the world. As an alternative, numerous SI reanalysis data in grid format have been developed in regional and global scales. Among them, the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) products could provide high quality SI records with acceptable accuracy and long temporal ranges. This study attempted to improve the accuracy of GHI records derived from MERRA-2 products, and to generate grid DNI and DIF datasets for all-sky conditions over mainland China during 1981–2014, based on the REST2 model and cloud transmittance estimates combining sunshine observations. The results indicate that the estimated GHI values (GHInew) show higher agreements with GHI measurement at 17 CMA (China meteorological administrations) stations than that for the GHI records derived from MERRA-2 products (MERRA-2 GHI). Then, grid GHI, DNI and DIF datasets (0.50° (lat) *0.625° (lon)) throughout China were constructed. The results indicated that the MERRA-2 GHI records may overestimate the GHI values over mainland China. Generally, the GHI and DNI values gradually decreased during 1981-2014, however, DIF values gradually increased from 1981 to 2014, especially in 1992 (DIF = 90.914 W m−2, anomaly DIF value = 15.544 W m−2). The Qinghai Tibetan Plateau has always been an area with the highest GHI, the highest DNI and the lowest DIF values, whereas the Sichuan Basin has always been an area with the lowest GHI, the lowest DNI and the highest DIF values. The grid GHI, DNI and DIF dataset generated in this study can assist in numerous solar studies and applications. We provide these solar irradiance data in publicly available repository: https://doi.org/10.6084/m9.figshare.10026563 (Qin, W. et al., 2019).

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