Monitoring surface soil moisture and freeze-thaw state with the high-resolution radar of the Soil Moisture Active/Passive (SMAP) mission

Abstract

An approach is described for retrieving surface soil moisture and freeze/thaw state using 3-km resolution L-band radar data of the planned Soil Moisture Active and Passive (SMAP) mission. SMAP radar backscatter coefficients are simulated using radar scattering models and land surface hydrology model output generated over the contiguous United States (CONUS). A Monte-Carlo simulation is performed to assess the error budget of the soil moisture retrievals in the presence of radar measurement error and error in surface roughness. The estimated soil moisture retrieval accuracy is better than 0.06 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> for vegetation water content less than 1.2 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and soil moisture in the range of 0 to 0.3 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . The retrieval performance improves if radar speckle is reduced by additional observations (e.g., including both fore- and aft-scan data). It is currently assumed that the surface roughness is known with 10% error, but a time-series method is under development to estimate the roughness. The surface freeze/thaw state retrieval is simulated using a surface hydrology process model forced with climatology. The simulation illustrates a SMAP daily composite freeze/thaw product derived using a time-series algorithm applied to the SMAP high-resolution radar data.