Evaluation of the Fengyun-4B Downward Surface Shortwave Radiation (DSSR) Product over Guangxi Using a Dense Photovoltaic Station Network

The 4 km/15 min downward surface shortwave radiation (DSSR) product from Fengyun-4B (FY-4B)/AGRI shows great potential for solar energy assessment in China, but its applicability requires further validation. This study conducts a comprehensive evaluation of the FY-4B DSSR product over Guangxi for 2025, using ground-observed irradiance from a dense network of 101 photovoltaic (PV) power stations. The overall comparison shows a correlation coefficient (R) of 0.84, a root-mean-square error (RMSE) of 161.78 W/m2, a relative prediction error (RPE) of 51.02%, and a mean bias error (MBE) of 56.23 W/m2, indicating systematic overestimation. Seasonally, the largest discrepancies occur in spring (MBE = 85.27 W/m2, RPE = 53.12%) and summer (R = 0.82, RMSE = 184.10 W/m2). Diurnally, retrievals are most reliable around 09:00–13:00 local time, deteriorating notably in the early morning and, especially, the afternoon and evening. Spatially, errors are larger in the hilly, elevated terrain of northwestern Guangxi (e.g., Hechi) than in flatter southern and coastal cities, with RPE rising from roughly 40–60% at lower elevations to around 80% above 600–700 m. Sky-condition classification confirms that data quality follows clear > cloudy > overcast sky, while AOD-binned analysis shows aerosol loading playing a secondary but non-negligible role, especially under high-AOD pollution events. Solar zenith angle (SZA) also strongly affects accuracy: R peaks around 0.75–0.8 in the 30–50° SZA range and drops below 0.4 beyond about 75°. This study offers the most spatially and dimensionally comprehensive validation of FY-4B DSSR over Guangxi to date, characterizing accuracy across seasonal, diurnal, spatial, cloud, aerosol, solar-geometry, and elevation dimensions using a denser ground-truth network than previously available, with direct implications for photovoltaic resource assessment and power forecasting in subtropical hilly regions.