Talks and Poster Presentations (with Proceedings-Entry):

W. Crow, W. Wagner, V. Naeimi:
"Inferring the impact of radar incidence angle on soil moisture retrieval skill using data assimilation";
Talk: IEEE International Geoscience and Remote Sensing Symposium 2010, Honolulu, Hawaii, U.S.A.; 2010-07-25 - 2010-07-30; in: "IGARSS 2010", (2010), ISBN: 978-1-4244-9564-1; 1261 - 1264.

English abstract:
The impact of measurement incidence angle (θ) on the accuracy
of radar-based surface soil moisture (Θs) retrievals is
largely unknown due to discrepancies in theoretical backscattermodels
as well as limitations in the availability of sufficientlyextensive
ground-based Θs observations for validation. Here,
we apply a data assimilation-based evaluation technique for
remotely-sensed Θs retrievals that does not require groundbased
soil moisture observations to examine the sensitivity of
skill in surface Θs retrievals to variations in θ. Application
of the evaluation approach to the TU-Wien European Remote
Sensing (ERS) scatterometer Θs data set over regional-scale
(∼10002 km2) domains in the Southern Great Plains (SGP)
and Southeastern (SE) regions of the United States indicate
a relative reduction in correlation-based skill of 23% to 30%
for Θs retrievals obtained from far-field (θ > 50◦) ERS observations
relative to Θs estimates obtained at θ < 26◦. Such
relatively modest sensitivity to θ is consistent with Θs 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 backscattermodelwith a "vegetationwater
cloud" canopy model is shown to overestimate the impact of
θ on Θs retrieval skill.

Created from the Publication Database of the Vienna University of Technology.