An Intercomparison of ERS-Scat and AMSR-E Soil Moisture Observations with Model Simulations over France

• Published in: Journal of hydrometeorology 2009-04, Vol.10 (2), p.431-447
• Main Authors: Rüdiger, Christoph, Calvet, Jean-Christophe, Gruhier, Claire, Holmes, Thomas R. H., de Jeu, Richard A. M., Wagner, Wolfgang
• Format: Article
• Language: English
• Subjects: Correlations; Datasets; Ecology, environment; Ecosystems; Forest soils; Life Sciences; Microwaves; Modeling; Pixels; Soil water; Soil water content; Vegetation
• ISSN: 1525-755X; 1525-7541
• DOI: 10.1175/2008JHM997.1

This paper presents a study undertaken in preparation of the work leading up to the assimilation of Soil Moisture and Ocean Salinity (SMOS) observations into the land surface model (LSM) Interaction Soil Biosphere Atmosphere (ISBA) at Météo-France. This study consists of an intercomparison experiment of different space-borne platforms providing surface soilmoisture information [Advanced Microwave Scanning Radiometer for Earth Observing (AMSR-E) and European Remote Sensing Satellite Scatterometer (ERS-Scat)] with the reanalysis soil moisture predictions over France from the model suite of Système d’analyse fournissant des renseignements atmosphériques à la neige (SAFRAN), ISBA, and coupled model (MODCOU; SIM) of Météo-France for the years of 2003–05. Both modeled and remotely sensed data are initially validated against in situ observations obtained at the experimental soil moisture monitoring site Surface Monitoring of the Soil Reservoir Experiment (SMOSREX) in southwestern France. Two different AMSR-E soil moisture products are compared in the course of this study—the official AMSR-E product from the National Snow and Ice Data Center (NSIDC) and a new product developed at the Vrije Universiteit Amsterdam and NASA (VUA–NASA)—which were obtained using two different retrieval algorithms. This allows for an additional assessment of the different algorithms while using identical brightness temperature datasets. This study shows that a good correlation generally exists between AMSR-E (VUA–NASA), ERS-Scat, and SIM for low altitudes and low-to-moderate vegetation covers (1.5–3 kg m−2vegetation water content), with a reduction in the correlation in mountainous regions. It also shows that the AMSR-E (NSIDC) soil moisture product has significant differences when compared to the other datasets.