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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #314491
Title: Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

Author
item Coopersmith, Evan
item Cosh, Michael
item BINDLISH, R. - Science Systems, Inc
item BELL, JESSE - National Oceanic & Atmospheric Administration (NOAA)

Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/2/2015
Publication Date: 11/30/2015
Citation: Coopersmith, E.J., Cosh, M.H., Bindlish, R., Bell, J. 2015. Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN). Advances in Water Resources. 85:79-85. doi: 10.1016/j.advwatres.2015.09.003.

Interpretive Summary: Large scale networks are frequently used in remote sensing calibration and validation efforts. The U.S. Climate Reference Network (USCRN) recently added soil moisture sensors to their instrument suite, beginning in 2008. In a recent study, a model was applied to these soil moisture records, using the precipitation records of the stations, to extend the soil moisture record backward in time. By extending backward to 2002, the new data record coincides with the performance period of the Advanced Microwave Scanning Radiomater (AMSR-E). Comparisons were made between the AMSR-E soil mositure data record and the new USCRN data record. This is the first time this type of analysis was conducted on an in situ network. Network managers will benefit from this work, because it lays out a method for increasing time series data using simple hydrologic models for application in remote sensing validation.

Technical Abstract: Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only occurred within the past decade through a combination of in situ networks and satellite-driven remote sensing. The U.S. Climate Reference Network (USCRN) has provided a nationwide in situ resource since 2009. Comparisons are ongoing between this network and satellite resources. The Advanced Microwave Scanning Radiometer (AMSR-E), launched in 2002, is one of the earliest satellite products available for comparison, but there are a limited number of years where the data records overlap. This study compares the results of the modeled soil moisture estimates from USCRN to the remotely sensed estimates provided by the AMSR-E satellite between 2002 and 2011. In turn, the performance of the model against satellite estimates are measured against the performance of AMSR-E against in situ measurements at USCRN locations as well as the calibrated model’s performance against in situ values. The analysis reveals comparable levels of performance between satellite estimates and model estimates, suggesting that it may be possible to utilize modeled estimates at times and locations where satellite estimates are unavailable and further extend the soil moisture record spatially and temporally.