Uncertainty of Reference Pixel Soil Moisture Averages Sampled at SMAP Core Validation Sites

Author:

Chen Fan1,Crow Wade T.2,Cosh Michael H.2,Colliander Andreas3,Asanuma Jun4,Berg Aaron5,Bosch David D.6,Caldwell Todd G.7,Collins Chandra Holifield8,Jensen Karsten Høgh9,Martínez-Fernández Jose10,McNairn Heather11,Starks Patrick J.12,Su Zhongbo13,Walker Jeffrey P.14

Affiliation:

1. SSAI/Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland

2. Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland

3. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

4. University of Tsukuba, Tsukuba, Japan

5. Department of Geography, Environment and Geomatics, University of Guelph, Guelph, Ontario, Canada

6. Southeast Watershed Research Lab, Agricultural Research Service, USDA, Tifton, Georgia

7. Nevada Water Science Center, U.S. Geological Survey, Carson City, Nevada

8. Southwest Watershed Research Center, Agricultural Research Service, USDA, Tucson, Arizona

9. Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark

10. University of Salamanca, Villamayor, Spain

11. Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada

12. Grazinglands Research Laboratory, Agricultural Research Service, USDA, El Reno, Oklahoma

13. Faculty of Geo-Information Science and Earth Observations (ITC), University of Twente, Enschede, Netherlands

14. Monash University, Clayton, Victoria, Australia

Abstract

Abstract Despite extensive efforts to maximize ground coverage and improve upscaling functions within core validation sites (CVS) of the NASA Soil Moisture Active Passive (SMAP) mission, spatial averages of point-scale soil moisture observations often fail to accurately capture the true average of the reference pixels. Therefore, some level of pixel-scale sampling error from in situ observations must be considered during the validation of SMAP soil moisture retrievals. Here, uncertainties in the SMAP core site average soil moisture (CSASM) due to spatial sampling errors are examined and their impact on CSASM-based SMAP calibration and validation metrics is discussed. The estimated uncertainty (due to spatial sampling limitations) of mean CSASM over time is found to be large, translating into relatively large sampling uncertainty levels for SMAP retrieval bias when calculated against CSASM. As a result, CSASM-based SMAP bias estimates are statistically insignificant at nearly all SMAP CVS. In addition, observations from temporary networks suggest that these (already large) bias uncertainties may be underestimated due to undersampled spatial variability. The unbiased root-mean-square error (ubRMSE) of CSASM is estimated via two approaches: classical sampling theory and triple collocation, both of which suggest that CSASM ubRMSE is generally within the range of 0.01–0.02 m3 m−3. Although limitations in both methods likely lead to underestimation of ubRMSE, the results suggest that CSASM captures the temporal dynamics of the footprint-scale soil moisture relatively well and is thus a reliable reference for SMAP ubRMSE calculations. Therefore, spatial sampling errors are revealed to have very different impacts on efforts to estimate SMAP bias and ubRMSE metrics using CVS data.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

ESA MOST Dragon IV programme

Ministerio de Economía y Competitividad

National Aeronautics and Space Administration

Villum Fonden

Publisher

American Meteorological Society

Subject

Atmospheric Science

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