Surface soil moisture estimation over the AMMA Sahelian site in 3 Mali using ENVISAT / ASAR data

8 Abstract 9 This paper focuses on different methods for estimating soil moisture in a Sahelian environment by comparing ENVISAT/ASAR and ground data 10 at the same spatial scale. The analysis is restricted to Wide Swath data in order to take advantage of their high temporal repetitivity (about 3–4 days) 11 corresponding to a moderate spatial resolution (150 m). On the one hand, emphasis is put on the characterization of Surface Soil Moisture (SSM) at a 12 spatial scale compatible with the derivation of the backscattering coefficients, and a transfer function is developed for up-scaling local measurements 13 to the 1 km scale. On the other hand, three different approaches are used to normalize the angular variation of the observed backscattering coefficients. 14 The results show a strong linear relationship between the HH normalized backscattering coefficients and SSM. The best result is obtained when 15 restricting the ASAR data to low incidence angles and by taking into account vegetation effects using multi-angular radar data. For this case, the rms 16 error of the SSM retrieval is 2.8%. These results highlight the capabilities of the ASAR instrument to monitor SSM in a semiarid environment. West Africa and more specifically the Sahelian zone has 23 been identified by Koster et al. (2004) to be one among several a 24 regions of the world with the most significant feedback between 25 soil moisture and precipitation. This hot spot " indicates where 26 the routine monitoring of soil moisture, with both ground-based 27 and space-based systems, will yield the greatest return in boreal 28 summer seasonal forecasting ". Monitoring the spatial and 29 temporal variability of soil moisture is also critical for 30 understanding soil–vegetation–atmosphere interactions and to 31 address the role of soil moisture on West African Monsoon