Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates.
Geophys Res Lett
; 44(12): 6145-6153, 2017 Jun 28.
Article
em En
| MEDLINE
| ID: mdl-29657343
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 spatio-temporal 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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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Geophys Res Lett
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Bélgica