SAC-D/Aquarius soil moisture product development and evaluation for Pampas Plains (Argentina)

In this work, several retrieval algorithms were implemented to retrieve soil moisture (sm) and optical depth (τ) 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 was also presented, and its results were contrasted with the previous algorithms. Furthermore, an Artificial Neural Network (ANN) approach to retrieve sm from Aquarius brightness temperature was implemented and trained using SMOS Level-2 sm product. Finally, performance metrics for each algorithm were derived using SMOS L2 sm as benchmark product.