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Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons37243

Löw,  A.
Terrestrial Remote Sensing / HOAPS, The Land in the Earth System, MPI for Meteorology, Max Planck Society;
CRG Terrestrial Remote Sensing, Research Area A: Climate Dynamics and Variability, The CliSAP Cluster of Excellence, External Organizations;

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Zitation

Crow, W., Berg, A., Cosh, M., Löw, A., Mohanty, B., Panciera, R., et al. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Reviews of Geophysics, 50: RG2002. doi:10.1029/2011RG000372.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-89E7-3
Zusammenfassung
The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the ground resolution (typically >10 2 km 2) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from current and upcoming soil moisture satellite missions. 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. This review paper describes 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, it also summarizes a number of existing soil moisture upscaling strategies which may reduce the detrimental impact of spatial sampling errors on the reliability of satellite soil moisture validation using spatially sparse ground-based observations. © 2012 by the American Geophysical Union.