A retrieval of available water fraction (fAW) is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere-Land Exchange Inversion (ALEXI) model. Available water serves as a proxy for soil moisture conditions, where fAW can be converted to volumetric soil moisture through two soil texture dependents parameters - field capacity and permanent wilting point. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be largely dictated by soil moisture conditions, accommodates the retrieval of an average fAW over the surface to the rooting depth of the active vegetation. For this method, the fraction of actual to potential evapotranspiration (fPET) is computed from an ALEXI estimate of latent heat flux and potential evapotranspiration (PET). The ALEXI-estimated fPET can be related to fAW in the soil profile. Four unique fPET to fAW relationships are proposed and validated against Oklahoma Mesonet soil moisture observations within a series of composite periods during the warm seasons of 2002-04. Using the validation results, the most representative of the four relationships is chosen and shown to produce reasonable (mean absolute errors values less than 20%) fAW estimates when compared to Oklahoma Mesonet observations. Quantitative comparisons between ALEXI and modeled fAW estimates from the Eta Data Assimilation System (EDAS) are also performed to assess the possible advantages of using ALEXI soil moisture estimates within numerical weather predication (NWP) simulations. This TIR retrieval technique is advantageous over microwave techniques because of the ability to indirectly sense fAW-and hence soil moisture conditions-extending into the root-zone layer. Retrievals are also possible over dense vegetation cover and are available on spatial resolutions on the order of the native TIR imagery. A notable disadvantage is the inability to retrieve fAW conditions through cloud cover. © 2009 American Meteorological Society.
CITATION STYLE
Hain, C. R., Mecikalski, J. R., & Anderson, M. C. (2009). Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation. Journal of Hydrometeorology, 10(3), 665–683. https://doi.org/10.1175/2008JHM1024.1
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