A BAYESIAN APPROACH FOR A SAC-D/AQUARIUS SOIL MOISTURE PRODUCT

CINTIA BRUSCANTINI; FRANCISCO MATIAS GRINGS; MATIAS BARBER; HAYDEE KARSZENBAUM

Pasadena, CA

Congreso; 13th spetialist meeting on microwave radiometry and remote sensing of the environment (MICRORAD); 2014

NASA

In this work, several retrieval algorithms were implemented to retrieve soil moisture (sm) and optical depth ( ) from Aquarius/SAC-D observations. Currently used sm retrieval algorithms (H- and V-pol Single Channel Algorithm, Microwave Polarization Difference Algorithm) were computed over Pampas Plains, Argentina. The methodology of a novel Bayesian algorithm developed is also presented, and its results are contrasted with the previous algorithms. Finally, performance metrics for each algorithms were derived using SMOS Level-2 sm and  as benchmark products. The new Bayesian approach was the sm algorithm that exhibited the lowest ubRMSE (0:115m3=m3), though very close to USDA and SCAV ubRMSE (0:116m3=m3). Nevertheless, some advices are discussed in Section 4 that might improve significantly the Bayesian algorithm performance.