Estimating downward surface shortwave radiation using MTSAT-1R and ground measurements data by Bayesian maximum entropy method

The surface downward shortwave radiation (250~3000 nm), also known as insolation, is referred to as total solar irradiance incident at Earth surface, which is an essential parameter in land surface radiation budget and many land surface process models. Currently, the downward shortwave radiation is obtained either from satellite observations based on empirical and physical-based retrieval methods or geostatistical methods using ground-based measurements. Both data type of remote sensing product convey substantial information: the ground-based measurements provide hard (accurate) but scare data, whereas, the radiation images (estimated from remotely sensed data or provided in reanalysis and GCMs data) provide exhaustive but soft (vague) information. In this paper we present a novel approach which takes advantages of both hard and soft data to estimate the surface downward shortwave radiation. This method, which based on a realistic representation of the spatiotemporal domain, can combine rigorously and efficiently various forms of physical knowledge and sources of uncertainty. Cross-validation results using ground measurements indicate that surface downward shortwave radiation estimates from BME are slightly improved.