Abstract
Surface incident solar radiation (Rs) of reanalysis products is widely used in ecological conservation, agricultural production, civil engineering and various solar energy applications. It is of great importance to have a good knowledge of the uncertainty of reanalysis Rs products. In this study, we evaluated the Rs estimates from two representative global reanalysis (ERA-Interim and MERRA-2) using quality- controlled surface measurements from China Meteorological Administration (CMA) and Multi-layer Simulation and Data Assimilation Center of the Tibetan Plateau (DAM) from 2000 to 2009. Error causes are further analyzed in combination radiation products from the Earth’s Radiant Energy System (CERES) EBAF through time series estimation, hotspot selection and Geodetector methods. Both the ERA-Interim and MERRA-2 products overestimate the Rs in China, and the MERRA-2 overestimation is more pronounced. The errors of the ERA-Interim are greater in spring and winter, while that of the MERRA-2 are almost the same in all seasons. As more quality-controlled measurements were used for validation, the conclusions seem more reliable, thereby providing scientific reference for rational use of these datasets. It was also found that the main causes of errors are the cloud coverage in the southeast coastal area, aerosol optical depth (AOD) and water vapor content in the Sichuan Basin, and cloud coverage and AOD in the northeast and middle east of China.
Highlights
Surface incident solar radiation (Rs) is the basic energy of biological, physical and chemical processes, and the essential input parameters of biological physics models and hydrological simulation mathematical models[1,2]
Considering the influence of atmospheric factors on the reanalysis Rs products and the spatial heterogeneity of the distribution of atmospheric factors, we introduce the Geodetector[32] to quantitatively analyze the causes of the spatial-temporal errors of Rs in the hotspots and utilize CERES-Energy Balanced and Filled (EBAF) atmospheric products to verify the results of the dominant atmospheric influence factors
The difference between the two reanalysis products and China Meteorological Administration (CMA) or DAM is very small; the difference of Root Mean Square Error (RMSE) is 3.93 and 0.80 W/m2, respectively; and the difference of the bias is 2.49 and 8.16 W/m2, respectively, which further illustrates that the DAM datasets have high consistency with CMA and can be used as validation www.nature.com/scientificreports data
Summary
Surface incident solar radiation (Rs) is the basic energy of biological, physical and chemical processes, and the essential input parameters of biological physics models and hydrological simulation mathematical models[1,2]. Goddard Space Flight Center (GSFC)’s Global Modeling and Assimilation Office (GMAO); NCEP–NCAR reanalysis, NCEP-DOE reanalysis, Climate Forecast System Reanalysis (CFSR) from the National Centers for Environmental Prediction (NCEP); JRA-55 from the Japan Meteorological Agency (JMA) These reanalysis data are widely used in the field of atmospheric sciences, for example, surface temperature changes, regional precipitation distribution, and surface solar radiation distribution[18,19,20]. More observation data are needed to confirm the applicability of reanalysis Rs. Zhang et al.[17] used 674 ground-based observation stations to conduct research on the seasonal changes and spatial distribution at the global scale taking advantage of six kinds of reanalysis Rs products (NCEP–NCAR, NCEP-DOE, CFSR, ERA-Interim, MERRA, and JRA-55). Solar radiation varies on spatial-temporal scales and influenced by many factors, such as cloud coverage, AOD, water vapor content, ozone concentration, surface albedo and other factors
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