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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Informing radar retrieval algorithm development using an alterntaive soil moisture validation technique

Authors
item Crow, Wade
item Wolfgang, Wagner -
item Naeimi, Vahid -

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: November 1, 2009
Publication Date: December 15, 2009
Citation: Crow, W.T., Wolfgang, W., Naeimi, V. 2009. Informing radar retrieval algorithm development using an alternative soil moisture validation technique [abstract]. American Geophysical Union. 89(53):H11G-01.

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 soil moisture observations for validation purposes. Here, we apply an evaluation technique for remotely-sensed surface soil moisture retrievals that does not require ground based soil moisture observations to examine the sensitivity of retrieval skill in surface soil moisture retrievals to variations in radar incidence angle. Past results with the approach have shown that it is capable of detecting relative variations in the correlation between remotely-sensed surface soil moisture retrievals and ground-truth soil moisture measurements. Application of the evaluation approach to the TU-Wien European Remote Sensing (ERS) scatterometer data set over two regional-scale (10002 km2) domains in the Southern United States indicates a relative reduction in correlation-based skill of between 20% and 30% when moving between the lowest (<26 degrees.) and highest ERS (>50 degree) incidence angle ranges with statistically significant retrieval skill present within all ranges. The observed sensitivity of correlation-based skill with incidence angle is in approximate agreement with soil moisture retrieval uncertainty predictions made using the WARP 5 backscatter model. However, the coupling of a bare soil backscatter model with the so-called “vegetation water cloud” model is shown to overestimate the impact of radar incidence angle on retrieval skill – suggesting the need for additional ground/canopy interaction terms in radar backscatter models for vegetated surfaces. The implications of result for the development of applications for radar-based soil moisture products generated by the NASA Soil Moisture Active/Passive (SMAP) mission will be discussed.

Last Modified: 12/21/2014
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