Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas

In this paper, an evaluation strategy for two-candidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.