Abstract
The behavior of satellite footprint‐scale surface soil moisture probability density functions (PDF) was analyzed using 50‐km‐scale samples taken from soil moisture images collected during the Southern Great Plains 1997 (SGP97) hydrology experiment. Under the observed wetness conditions, soil moisture variability generally peaked in the midrange of mean soil moisture content and decreased toward the wet and dry ends, while in the midrange it was more widely distributed. High variability in the midrange is attributed to the multimodality of soil moisture PDFs, which apparently results from fractional precipitation within the footprint‐scale fields. Single Gaussian, single beta, and mixtures of two Gaussian distributions were utilized to fit observed footprint‐scale soil moisture distributions. As a single‐component density, the Gaussian PDF was shown to be a good choice, compared to the beta distribution, for representing spatial variability, particularly under wet conditions. The performance of the Gaussian PDF was greatly improved by using a mixture of two Gaussian distributions. Implications of this study for the validating spaceborne remotely sensed soil moisture estimates and for parameterization of subgrid‐scale surface soil moisture content in land surface models are discussed.
Highlights
The relationship between mean soil moisture content and the standard deviation of moisture content measurements within an area has been an important topic of the research that can provide insight into identification of a representative probability density functions (PDF) and its parameters
A consistent picture is emerging that soil moisture variance peaks in the midrange of mean soil moisture content as suggested by Owe et al [1982] due to subfootprint-scale variations in precipitation, and heterogeneity in soil hydraulic properties that result in differing rates of drying [Peters-Lidard and Pan, 2002]
Using extensive ground-based soil moisture measurements taken during Southern Great Plains 1997 (SGP97), Famiglietti et al [1999] observed that PDFs of surface (0 –6 cm) soil moisture content evolve systematically from negatively skewed under very wet conditions, to normal in the midrange, to positively skewed under dry conditions at the aircraft remote sensing footprint-scale (800 m by 800 m) fields
Summary
[2] Landscape- to regional-scale spatial-temporal variations in surface soil water content are important for a range of hydrological, ecological, and biogeochemical processes Proper characterization of this variability is important for improved understanding of Earth system interactions, and for enhancing terrestrial process models. [4] While these sensors will provide regionalscale monitoring of spatial patterns of surface moisture content at the specified resolutions, they will not provide information on subfootprint-scale variations that are so important to the processes and interactions mentioned previously. Understanding this subfootprint-scale spatial variability is an important step toward enabling the full utilization of remotely sensed soil moisture data by the Earth system science community. The implications of these results are discussed in the context of Earth system modeling and of validating satellite-derived soil moisture estimates
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