Elements of a Science Infusion Strategy for NWS Probabilistic Quantitative Precipitation Forecasting (PQPF)

John Schaake and Pedro Restrepo

Office of Hydrologic Development
National Weather Service


The National Weather Service is following a science infusion and implementation strategy to produce probabilistic quantitative precipitation forecast (PQPF) information (and other hydrologic forcing variables) for the Advanced Hydrologic Prediction Services (AHPS) program. The PQPF process is an integrated approach to produce a seamless suite of consistent products for lead times ranging from now-casts out to a year. The strategy offers requires different laboratories and centers to work together to meet AHPS requirements. The PQPF process begins with precipitation ensemble forecasts from different atmospheric models. Then, statistical post-processing of NWS ensemble forecasts are used to remove biases, assure valid probabilities and possibly improve the resolution (i.e. skill or sharpness) of the forecasts. There is a role for forecasters (HPC, CPC and RFC/HAS) to add value to the forecasts and the man/machine interactive tools are needed to support the forecaster role. Local ensemble processing systems ingest the PQPF forecast information, do additional re-scaling and downscaling, and provide the detailed ensemble forcing data required by local hydrologic forecast procedures. Linkages with the USWRP, the Climate Program and other agencies are being developed and used to accelerate science infusion from the scientific community into NWS operations. The Office of Global Programs has provided substantial support to enable development and implementation of ensemble prediction for AHPS through its GAPP, RISA and CDEP research programs.

The figure below illustrates the importance of hydrologic preprocessing of model output products so that they can be used as input for AHPS hydrologic ensemble forecast models.