Local Climatic Guidance for Probabilistic Quantitative Precipitation Forecasting

Abstract

The predictand of a probabilistic quantitative precipitation forecast (PQPF) for a river basin has two parts: (i) the basin average precipitation amount accumulated during a fixed period and (ii) the temporal disaggregation of the total amount into subperiods. To assist field forecasters in the preparation of well-calibrated (reliable) and informative PQPFs, local climatic guidance (LCG) was developed. LCG provides climatic statistics of the predictand for a particular river basin, month, and period (e.g., 24-h period beginning at 1200 UTC and divided into four 6-h subperiods). These statistics can be conditioned on information entered by the forecaster such as the probability of precipitation occurrence and various hypotheses regarding the precipitation amount and timing. This article describes two probability models of the predictand, details guidance products, and illustrates them for the Lower Monongahela River basin in Pennsylvania. The first model provides marginal climatic statistics of the predictand on an “average” day of the month. The second model conditions the statistics on the timing of precipitation within the diurnal cycle. The resultant characterization of the precipitation process allows the forecaster to decompose the complex assessment of a multivariate PQPF into a sequence of feasible judgmental tasks.