Quantifying and predicting the accuracy of radar-based quantitative precipitation forecasts

On the basis that hydrological users need to know the forecast uncertainty at the time that the forecast is issued, we computed distributions of radar rainfall forecast uncertainty as a function of forecast lead time, basin size, and forecasted rainfall intensity using data from the US 3-D National Mosaic of radar data. We document how exceptional forecasts such as those of heavy rainfall are generally biased. Since forecast uncertainty is also weather dependent, we tried to find good predictors to help either reduce the forecast uncertainty or better define it. These predictors were based either on characteristics of the current precipitation field or on the performance of the nowcast in the immediate past. The value of some predictors, especially those based on the properties of large-scale rainfall patterns, was significant though modest, the predictors being generally more skillful at characterizing forecast uncertainty than at improving forecast accuracy.