Experiments of satellite data simulation based on the Community Land Model and SCE-UA algorithm

The study developed a dual-phase satellite data simulation system to simulate the gridded Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) satellite brightness temperature (BT) data and calibrate the microwave wetland surface emissivity, which based on the National Center for Atmosphere Research (NCAR) Community Land Model version 2.0 (CLM2.0), microwave land emissivity model (LandEM), Shuffled Complex Evolution algorithm (SCE-UA) and gridded AMSR-E BT data. The system was implemented in two phases: the parameters calibration phase and the AMSR-E BT simulation phase. It used the outputs of the CLM2.0 as the inputs of the LandEM, the LandEM parameters and the wetland emissivity were calibrated by the SCE-UA algorithm in the parameters calibration phase, and the calibrated parameters were used as the final model parameters of the LandEM in the AMSR-E BT simulation phase. The experimental results indicate that the SCE-UA algorithm can effectively calibrate the LandEM parameters and microwave wetland surface emissivity, and they possess excellent transportability. It provides a promising solution to obtain the microwave wetland surface emissivity through parameters calibration method, thus we can simulate the gridded AMSR-E BT data for various land cover types, such as bare soil, vegetation, snow, lake, and wetland, which will greatly improve land data assimilation study. In addition, we attempted to use the parameterized bare surface and snow emissivity model to substitute that of the LandEM, the simulation results can make great improvement.