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Lievens, H., R. H. Reichle, Q. Liu, G. J. M. De Lannoy, R. S. Dunbar, S. B. Kim, N. N. Das, M. Cosh, J. P. Walker, and W. Wagner:
"Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates"
Geophysical Research Letters, 44, 6145-6153, doi:10.1002/2017GL073904, 2017.

Abstract:
SMAP (Soil Moisture Active and Passive) radiometer observations at ∼40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9 km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatiotemporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations.


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NASA-GSFC / GMAO / Rolf Reichle