Processor of Output for Probabilistic Quantitative
Processor of Output (BPO) is a new, theoretically-based technique for probabilistic
forecasting of weather variates. It processes output from a
numerical weather prediction
model and optimally fuses it with climatic data in order to quantify
uncertainty about a predictand.
There are three versions, for binary predictands, multi-category
predictands, and continuous
predictands. The first version of the BPO was developed and tested for
of precipitation (PoP) occurrence forecast.
This will be a tutorial introduction to the third version of the BPO
that produces the probabilistic quantitative
precipitation forecast (PQPF), conditional on precipitation occurrence.
PQPF is in the form of a continuous distribution function of the
precipitation amount. The talk
will explain the forecasting equation, present examples of forecasts,
and report preliminary
performance comparisons of the BPO with the Model Output Statistics
(MOS) technique; then it will point to future research on the
Bayesian Processor of Ensemble (BPE).