Performance metrics for soil moisture retrievals and application requirements
Name
Entekhabi_Performance Metrics.pdf
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806.29 KB
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Author(s)
Entekhabi, Dara
Reichle, Rolf H.
Koster, Randal D.
Crow, Wade T.
Date Issued
December 2009
Journal
Journal of Hydrometeorology
Publisher
American Meteorological Society
Citation
Entekhabi, Dara et al. “Performance Metrics for Soil Moisture Retrievals and Application Requirements.” Journal of Hydrometeorology 11 (2010): 832-840. Web. 19 Oct. 2011. © 2010 American Meteorological Society
Version
Final published version
Abstract
Quadratic performance metrics such as root-mean-square error (RMSE) and time series correlation are often used to assess the accuracy of geophysical retrievals (satellite measurements) with respect to true fields. These metrics are related; nevertheless, each has advantages and disadvantages. In this study the authors explore the relation between the RMSE and correlation metrics in the presence of biases in the mean as well as in the amplitude of fluctuations (standard deviation) between estimated and true fields. Such biases are common, for example, in satellite retrievals of soil moisture and impose constraints on achievable and meaningful RMSE targets. Last, an approach is introduced for converting a requirement in an application’s product into a corresponding requirement for soil moisture accuracy. The approach can help with the formulation of soil moisture measurement requirements. It can also help determine the utility of a given retrieval product for applications.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Parsons Laboratory for Environmental Science and Engineering (Massachusetts Institute of Technology)
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1175/2010JHM1223.1
