Verification
Rainfall forecasts can be verified a number of ways. Rain gauge observations can be gridded into areal averages, which are then compared to the grids for the forecast models. Weather radar estimates can be used outright, or corrected for rain gauge observations.
Several statistical scores can be based on the observed and forecast fields. One, known as a bias, compares the size of the forecast field to the observed field, with the goal of a score of 1. The threat score involves the intersection of the forecast and observed sets, with a maximum possible verification score of 1. The probability of detection, or POD, is found by dividing the overlap between the forecast and observed fields by the size of the observed field: the goal here is a score of 1. The critical success index, or CSI, divides the overlap between the forecast and observed fields by the combined size of the forecast and observed fields: the goal here is a score of 1. The false alarm rate, or FAR, divides the area of the forecast which does not overlap the observed field by the size of the forecasted area. The goal value in this measure is zero.
With tropical cyclones which impact the United States, the GFS global forecast model performed best in regards to its rainfall forecasts over the last few years, outperforming the NAM and ECMWF forecast models.
Read more about this topic: Quantitative Precipitation Forecast
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