|BERG, A - University Of Guelph|
|LOEW, A - Collaborator|
|MOHANTY, B - Texas A&M University|
|PANCIERA, R - University Of Melbourne|
|DE ROSNAY, P - Collaborator|
|RYU, D - University Of Melbourne|
|WALKER, J - Monash University|
Submitted to: Review Article
Publication Type: Review Article
Publication Acceptance Date: 2/5/2012
Publication Date: 4/19/2012
Citation: Crow, W.T., Berg, A., Cosh, M.H., Loew, A., Mohanty, B., Panciera, R., De Rosnay, P., Ryu, D., Walker, J. 2012. Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products. Review of Geophysics. DOI: 10.1029/2011RG000372.
Interpretive Summary: All satellite-based retrievals of land surface variables must first be validated against ground-based observations before they can be used with confidence. For satellite-base surface soil moisture retrievals, such validation is difficult due to the large scale contrast between point-scale ground observations of soil moisture and the coarse-scale resolution of satellite-based surface soil moisture retrievals. Consequently, researchers have had difficulty accurately assessing the reliability of satellite-based surface soil moisture retrievals which, in turn, has slowed their application to key agricultural problems like drought monitoring and irrigation scheduling. This review article describes the current state of the art in terms of efforts to "upscale" ground-based observations so that they can be directly compared to satellite-based retrievals and describes several new research paths to maximize the accuracy of these upscaling strategies. The ultimate goal of the review is to facilitate the development of better validation tools to assess, and ultimately improve, satellite-based soil moisture data products.
Technical Abstract: The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions such as SMOS (Soil Moisture Ocean Salinity), Aquarius and SMAP (Soil Moisture Active Passive). Given typical levels of observed spatial variability in soil moisture fields, this mismatch confounds mission validation goals by introducing significant sampling uncertainty in footprint-scale soil moisture estimates obtained from sparse ground-based observations. During validation activities based on comparisons between ground observations and satellite retrievals, this sampling error can be misattributed to retrieval uncertainty and spuriously degrade the perceived accuracy of satellite soil moisture products. Sections 2, 3 and 4 of this paper describe the magnitude of the soil moisture upscaling problem and measurement density requirements for ground-based soil moisture networks. Since many large-scale networks do not meet these requirements, Section 5 summarizes a number of existing soil moisture upscaling strategies which can reduce the detrimental impact of spatial sampling errors on the reliability of satellite soil moisture validation using spatially sparse ground-based observations.