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A statistical evaluation of the accuracy of forecasts or the effectiveness of detection techniques.

Several simple formulations are commonly used in meteorology. The skill score (SS) is useful for evaluating predictions of temperatures, pressures, or the numerical values of other parameters. It compares a forecaster's root-mean-squared or mean-absolute prediction errors, Ef, over a period of time, with those of a reference technique, Erefr, such as forecasts based entirely on climatology or persistence, which involve no analysis of synoptic weather conditions:
If SS > 0, the forecaster or technique is deemed to possess some skill compared to the reference technique. For binary, yes/no kinds of forecasts or detection techniques, the probability of detection (POD), false alarm rate (FAR), and critical success index (CSI) may be useful evaluators. For example, if A is the number of forecasts that rain would occur when it subsequently did occur (forecast = yes, observation = yes), B is the number of forecasts of no rain when rain occurred (no, yes), and C is the number of forecasts of rain when rain did not occur (yes, no), then
For perfect forecasting or detection, POD = CSI =1.0 and FAR = 0.0. POD and FAR scores should be presented as a pair.

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