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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 #297053
Title: Towards improving the NASA standard soil moisture retrieval algorithm and product

Author
item Mladenova, Iliana
item Jackson, Thomas
item NJOKU, ENI - Jet Propulsion Laboratory
item BINDLISH, R - Science Systems, Inc
item Cosh, Michael
item CHAN, STEVEN - Jet Propulsion Laboratory

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 10/1/2013
Publication Date: 12/9/2013
Citation: Mladenova, I., Jackson, T.J., Njoku, E., Bindlish, R., Cosh, M.H., Chan, S. 2013. Towards improving the NASA standard soil moisture retrieval algorithm and product [abstract]. American Geophysical Union. 2013 CDROM.

Interpretive Summary:

Technical Abstract: Soil moisture mapping using passive-based microwave remote sensing techniques has proven to be one of the most effective ways of acquiring reliable global soil moisture information on a routine basis. An important step in this direction was made by the launch of the Advanced Microwave Scanning Radiometer on the NASA’s Earth Observing System Aqua satellite (AMSR-E). Along with the standard NASA algorithm and operational AMSR-E product, the easy access and availability of the AMSR-E data promoted the development and distribution of alternative retrieval algorithms and products. Several evaluation studies have demonstrated issues with the standard NASA AMSR-E product such as dampened temporal response and limited range of the final retrievals and noted that the available global passive-based algorithms, even though based on the same electromagnetic principles, produce different results in terms of accuracy and temporal dynamics. Our goal is to identify the theoretical causes that determine the reduced sensitivity of the NASA AMSR-E product and outline ways to improve the operational NASA algorithm, if possible. Properly identifying the underlying reasons that cause the above mentioned shortcomings of the NASA AMSR-E product and differences between the alternative algorithms requires a careful examination of the theoretical basis of each approach. Specifically, the simplifying assumptions and parameterization approaches adopted by each algorithm to reduce the dimensionality of unknowns and characterize the observing system. Statistically-based error analyses, which are useful and necessary, provide information on the relative accuracy of each product but give very little information on the theoretical causes, knowledge that is essential for algorithm improvement. Thus, we are currently examining the possibility of improving the standard NASA AMSR-E global soil moisture product by conducting a thorough theoretically-based review of and inter-comparisons between several well established global retrieval techniques. A detailed discussion focused on the theoretical basis of each approach and algorithms sensitivity to assumptions and parameterization approaches will be presented.