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Parameter sensitivity of soil moisture retrievals from airborne C- and X-band radiometer measurements in SMEX02

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3 Author(s)
W. L. Crosson ; Global Hydrology & Climate Center, Space Res. Assoc., Huntsville, AL, USA ; A. S. Limaye ; C. A. Laymon

Among passive microwave frequencies, sensors operating at C- and X-band frequencies have been used with some success to estimate near-surface soil moisture from aircraft and satellite platforms. The objective of this paper is to quantify the sensitivities of soil moisture retrieved via a single-channel single-polarization algorithm to the observed brightness temperature and to retrieval algorithm parameters of surface roughness, vegetation B parameter, and single-scattering albedo. Examination of the regions within the parameter space that produce accurate soil moisture retrievals reveals that reasonably accurate retrievals can be made over a range of conditions using a fixed set of input parameters. Retrievals with horizontally polarized brightness temperature observations are more consistent than with vertically polarized observations. At horizontal polarization, sensitivity to the input parameters is much greater for wet soils than for dry soils, whereas for vertical polarization the moisture dependence is much weaker. At vertical polarization, sensitivities to variations in all parameters are much lower. To ensure that retrieval accuracy specifications are consistently met, high soil moisture conditions should be used in defining parameter accuracy requirements. Given the spatial and temporal variability of vegetation and soil conditions, it seems unlikely that, for regions with substantial rapidly growing vegetation, the accuracy requirements for model parameters in a single-frequency, single-polarization retrieval algorithm can be met with current satellite products. For such conditions, any soil moisture retrieval algorithm using parameterizations similar to those of this study may require multiple frequencies, polarizations, or look angles to produce stable, reliable soil moisture estimates.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:43 ,  Issue: 12 )