Incorporating misclassification error in skill assessment

It is desirable to account for misclassification error of meteorological observations so that the true skill of the forecast can be assessed. Errors in observations can occur, among other places, in pilot reports of icing and in tornado spotting. Not accounting for misclassification error gives a misleading picture of the forecast's true performance. An extension to the climate skill score test developed in Briggs and Ruppert is presented to account for possible misclassification error of the meteorological observation. This extension supposes a statistical misclassification-error model where gold standard data, or expert opinion, is available to characterize the misclassification-error characteristics of the observation. These model parameters are then inserted into the Briggs and Ruppert skill score for which a statistical test of significance can be performed.

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Copyright 2005 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.
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Author Briggs, W.
Pocernich, Matthew
Ruppert, D.
Publisher UCAR/NCAR - Library
Publication Date 2005-11-01T00:00:00
Digital Object Identifier (DOI) Not Assigned
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:27:57.259158
Metadata Record Identifier edu.ucar.opensky::articles:9372
Metadata Language eng; USA
Suggested Citation Briggs, W., Pocernich, Matthew, Ruppert, D.. (2005). Incorporating misclassification error in skill assessment. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7bg2psd. Accessed 21 June 2025.

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