Probabilistic Quantitative Precipitation Forecasts Derived from PoPs and Conditional Precipitation Amount Climatologies

Abstract

Probabilistic quantitative precipitation forecasts (PQPFS) for discrete amount classes can be formulated as the product of precipitation probabilities (as issued in PoP forecasts) and the climatological probabilities of precipitation in specified categories conditional on the occurrence of measurable precipitation. Such forecasts, derived from historical subjective PoP forecasts, are investigated here for the 12?24 hour projection using two types of conditional climatologies. The first involves simply the conditional probabilities of precipitation in selected amount classes given that at least 0.254 mm (0.01?) occurred. The second conditional climatology involves three distributions for the same events, conditional both on the occurrence of measurable precipitation and on the magnitude of the PoP forecast. In this later case, separate conditional distributions are tabulated for occasions when ?low? (0%?20%), ?moderate? (30%?50%), and ?high? (60%?100%) subjective PoP forecast were issued. Comparison of the conditional climatological distributions shows clearly that forecast periods for which ?high? PoPs were issued are characterized by distributions having higher probabilities of larger amounts and lower probabilities of smaller amounts, as compared to both distributions conditioned on other PoP categories and distributions not conditioned on the PoP forecasts. The reverse is true of distributions conditioned on ?low? PoP values. These are seen to be general properties of PoP forecasts issued for the conterminous United states. Forecast results are presented for Brownsville, Houston, and San Antonio, Texas, and for the period February 1981 to June 1982. This choice allows comparison of the present results with those of a subjective PQPF experiment conducted at these stations during this period. Surprisingly, the present forecasts show skill comparable to or somewhat better than that exhibited by the subjective PQPFs in the Texas experiment and the corresponding model output statistics (MOS) PQPFS. Use of climatological precipitation amount distributions conditioned on the magnitude of the subjective PoP forecasts improves overall skill worn only modestly, but (importantly) in a way that allows more frequent use of higher probabilities for the larger precipitation amount categories.