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Title:   Author  item
                                            Crow, Wadeitem
                                            WAGNER, WOLFGANG - Collaboratoritem
                                            NAEMI, VAHID - Collaboratoritem
                                            WIEN, TU - Collaborator
  Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
                                    Publication Type: Proceedings
                                    Publication Acceptance Date: 7/15/2010
                                    Publication  Date: 7/30/2010
                                    Citation: Crow, W.T., Wagner, W., Naemi, V., Wien, T. 2010. Inferring the impact of radar incidence angle on soil moisture retrieval skill using data assimilation. In: Proceedings of the International Geoscience and Remote Sensing Symposium Proceedings, July 25-30, 2010, Honolulu, Hawaii. 2010 CDROM.Interpretive Summary:
                                Technical Abstract: The impact of measurement incidence angle (') on the accuracy of radar-based surface soil moisture (') retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently extensive ground-based ' observations for validation. Here, we apply a data assimilation-based evaluation technique for remotely-sensed _s retrievals that does not require ground-based soil moisture observations to examine the sensitivity of skill in surface ' retrievals to variations in '. Application of the evaluation approach to the TU-Wien European Remote Sensing (ERS) scatterometer ' data set over regional-scale (10002 km2) domains in the Southern Great Plains (SGP) and Southeastern (SE) regions of the United States indicates a relative reduction in correlation-based skill of 23% to 30% for ' retrievals obtained from far-field (' > 50 degrees) ERS observations relative to ' estimates obtained at ' < 26 degrees.  Such relatively modest sensitivity to ' is consistent with ' retrieval noise predictions made using the TU-Wien ERS Water Retrieval Package 5 (WARP5) backscatter model. However, over moderate vegetation cover in the SE domain, the coupling of a bare soil backscatter model with a vegetation water cloud canopy model is shown to overestimate the impact of ' on ' retrieval skill.


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