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Generally, categorical forecasts have to be biased, either positively (i.e. over-forecasting the event, for end-users with low cost-loss ratios) or negatively (i.e. under-forecasting, for end- users with high cost-loss ratios). A good NWP model should not over-forecast nor under-forecast at any forecast range. This is another example of how computer-based forecasts differ from forecaster-interpreted, customer-orientated, forecasts.
An Extension of the Contingency Table – the “SEEPS” score
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