A New Cloud Base Height Retrieval Method and Its Application in Cloudy-Sky Surface Downwelling Longwave Radiation Estimation

Cloud base height (CBH) is crucial for determining cloud radiation effects, and uncertainty in CBH retrieval can lead to significant errors in the estimation of surface downwelling longwave radiation (SDLR) under cloudy-sky conditions. This study proposes a new CBH retrieval model utilizing top-of-atmosphere (TOA) reflectance and brightness temperature observations from the Fengyun-4A (FY-4A) satellite, employing the random forest algorithm. The accurately retrieved CBH is then used to estimate cloudy-sky SDLR, accounting for the radiative effects of the entire cloud layer. The CBH retrieval algorithm relies solely on TOA observations and cloud top parameter information, enabling CBH retrieval even in the absence of cloud optical thickness (COT). The verification results indicate that the newly proposed CBH retrieval algorithm achieves good accuracy, with a bias of −0.19 km and a root-mean-square error (RMSE) of 1.52 km. Compared to existing studies, the new algorithm performs well in both water cloud and ice cloud phases. Based on the accurately retrieved CBH, this study employs an estimation scheme that uses cloud effective temperature to characterize the radiation contribution of the entire cloud layer, enabling accurate estimation of cloudy-sky SDLR. Ground-based measurements from the Baseline Surface Radiation Network (BSRN) and the National Tibetan Plateau Data Center (TPDC) sites were used to validate the SDLR estimation scheme. The results showed that the cloudy-sky SDLR estimated using the retrieved CBH achieved reasonable accuracy, with a bias of 7.15 W/m2 and an RMSE of 27.42 W/m2.