Disclaimer: This material is being kept online for historical purposes. Though accurate at the time of publication, it is no longer being updated. The page may contain broken links or outdated information, and parts may not function in current web browsers. Visit the NASA Salinity website for more information.

Science Meetings

A Bayesian Approach for a SAC-D/Aquarius Soil Moisture Product
Bruscantini, C.A., Grings, F., Barber, M., Perna, P., and Karszenbaum, H. (10-Sep-15)

In this work, several retrieval algorithms were implemented to retrieve soil moisture (sm) and optical depth (Ï„) from Aquarius/SAC-D observations. Currently used sm retrieval algorithms (H- and V-pol Single Channel Algorithm, SCAH and SCAV; Microwave Polarization Difference Algorithm, MPDA) 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 Ï„ as benchmark products. The new Bayesian approach provide the sm retrieval algorithm that exhibited the lowest ubRMSE (0.115m3/m3), though very close to USDA SCA and SCAV ubRMSE (0.116m3/m3). Nevertheless, some improvements are discussed in Section 4 that might increase significantly the Bayesian algorithm performance.