Soil Moisture downscaling algorithm for combining radar and radiometer observations for SMAP mission

Abstract

In this study, a downscaling algorithm to disaggregate the radiometer Brightness Temperature (TB) using the radar backscatter observations for SMAP (Soil Moisture Active and Passive) was developed. The algorithm is based on the spectral downscaling which combines both phase and amplitude information in Fourier domain. Using the information from radar measurements at finer resolution, a new way to estimate the Fourier phase was proposed. The algorithm has been successfully applied to the PALS datasets from SMEX02 producing better results than radiometer-only inversions. The RMSE (Root-Mean-Square-Error) of the downscaling Brightness Temperature are 3.26K and 6.12K for Vertical and Horizontal polarization, respectively. Then medium resolution soil moisture was retrieved from disaggregated/downscaled TB. The accuracy (RMSE) of the downscaling soil moisture retrievals is 0.0459m3/m3, which is very close to SMAP science requirement of 0.04. The results indicate that the downscaling algorithm presented in this study is a promising approach to achieve finer resolution and more accurate soil moisture retrievals for the future SMAP mission.