Improving the AMSR-E Soil Moisture Algorithm of the University of Tokyo through Field Experiments and Parameters Optimization

This paper reports the progresses of AMSR-E soil moisture algorithm development at the University of Tokyo. The first progress is made through improving the forward model, i.e. radiative transfer model (RTM), based on field experiment and numerical simulation. The second progress is the development of a new parameterization method, through which the parameters necessary for the algorithm are optimized by a land data assimilation system developed at the University of Tokyo (LDAS-UT). The capability of LDAS-UT was validated successfully with winter wheat experiment data. Finally, the new RTM and parameterization method was validated on AMSR-E match up data set. The results demonstrate that the simulated brightness temperature is in good agreements with the one observed by AMSR-E.