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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #290185
Title: Analysis and validation of SMOS brightness temperature data with airborne and spaceborne observations

Author
item ZHAO, T - Chinese Academy Of Sciences
item SHI, J - University Of California
item BINDLISH, R - Science Systems, Inc
item Jackson, Thomas
item CUI, Q - Chinese Academy Of Sciences
item LI, Y - Chinese Academy Of Sciences
item CHE, T - Collaborator
item LI, X - Collaborator
item KERR, Y - Collaborator

Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 3/14/2013
Publication Date: 7/21/2013
Citation: Zhao, T., Shi, J., Bindlish, R., Jackson, T.J., Cui, Q., Li, Y., Che, T., Li, X., Kerr, Y. 2013. Analysis and validation of SMOS brightness temperature data with airborne and spaceborne observations [abstract]. International Geoscience and Remote Sensing Symposium (IGARSS). 2013 CDROM.

Interpretive Summary:

Technical Abstract: ESA’s soil moisture and ocean salinity (SMOS) [1] launched in Nov. 2009 is the first space-borne synthetic aperture passive microwave instrument. It provides L-band brightness temperature globally for a range of incidence angles (from 0° to 60°) at a resolution of about 43 km. This approach supports the retrieval of more accurate information on soil moisture and vegetation biomass. However, the well-known radio frequency interference (RFI) issues have significantly affected the quality of brightness temperatures in some regions of the world. A complicating factor for using the brightness temperature data is that the multiple incidence angle observations are not obtained at fixed values. This requires additional processing for soil moisture retrieval algorithms that require observations at specific angles. In addition, RFI can vary with incidence angle, which compounds the issue. In this study, we present a SMOS L1c brightness temperature processing chain that uses a mixed objective function to fit brightness temperatures to fixed incidence angles. This approach filters out outliers and reduces the some of the bias found in the observations. The results are more consistent with theoretical expectations. The resulting brightness temperatures were then compared with airborne observations over a site in China. Intercomparisons with WindSat observations were also conducted, since WindSat has similar overpass time as SMOS.