Incorporating misclassification error in skill assessment

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.