Improvements in the accuracy of quantitative precipitation forecasts (QPF) and in their spatial scale are crucial to sustained improvement in hydrologic forecasting, especially in small to medium-sized drainage basins with short response times. The resolution and physics of operational numerical weather prediction (NWP) models continue to improve, but are not yet at levels that make their direct output appropriate for hydrologic forecasting. In this work, an orographic precipitation forecasting model is nested within an operational NWP model in an effort to produce hydrologic forecasts that are of sufficient accuracy and scale to be of use in distributed hydrologic forecasting.
This model uses data from a digital elevation model (DEM) to produce fine-scale orographically-influenced wind fields, and then uses these wind fields for Lagrangian transport of air parcels, and subsequent production of condensate and rainfall. An operational forecasting model is used to provide the boundary and initial conditions for this model. Satellite and radar observations of cloud and precipitation fields are used to improve the representation of moisture fields at small scales. The performance of this model will be demonstrated by evaluating its gridded QPF output, and also by linking it with a spatially distributed hydrologic model and comparing the resulting runoff to observations