Estimating hourly surface shortwave radiation over northeast of the Tibetan Plateau by assimilating Himawari-8 cloud optical thickness

Abstract

Abstract To reduce the uncertainty estimation of clouds and improve the forecast of surface shortwave radiation (SSR) over the Tibetan Plateau, a new cloud assimilation system is proposed which is the first attempt to directly apply the four-dimensional local ensemble transform Kalman filter method to assimilate the cloud optical thickness (COT). The high-resolution spatial and temporal data assimilated from the next-generation geostationary satellite Himawari-8, with the high-assimilation frequency, realized an accurate estimation of the clouds and radiation forecasting. The COT and SSR were significantly improved after the assimilation by independent verification. The correlation coefficient (CORR) of the SSR was increased by 11.3%, and the root-mean-square error (RMSE) and mean bias error (MBE) were decreased by 28.5% and 58.9%, respectively. The 2-h cycle assimilation forecast results show that the overestimation of SSR has been effectively reduced using the assimilation system. These findings demonstrate the high potential of this assimilation technique in forecasting of SSR in numerical weather prediction. The ultimate goal that to improve the model forecast through the assimilation of cloud properties requires further studies to achieve.