A Real-Time, Mesoscale Numerical Weather-Prediction System Used for Research, Teaching, and Public Service at The Pennsylvania State University

Abstract

A mesoscale modeling system is being applied on an experimental basis at The Pennsylvania State University (Penn State) for production of real-time, high resolution, numerical weather forecasts for the northeastern United States. The initial model experimentation is being supported by Penn State. It is believed to be the first time that a real-time, three-dimensional mesoscale model has been run routinely at an American university, although mesoscale models have been run in real time in government laboratories. A version of the Penn State/NCAR mesoscale model is employed, using a two-way interacting nested grid with a fine-grid increment of 30 km, a coarse-grid increment of 90 km, and 15 computational levels. The forecast cycle is initiated automatically by the Department of Meteorology's Digital Equipment Corporation VAX 8350 system when all the required 0000 UTC surface and upper-air National Weather Service (NWS) data have been received, quality checked, and archived. Lateral boundary conditions are extracted from the current or previous NWS nested-grid model forecast. The dataset constructed on the VAX system is then transmitted by a fiber-optic data network to an IBM 3090 located on the Penn State campus, where the model is initialized and run for a 24- to 36-h forecast. By about 0600 UTC, well before the beginning of the work day, a short-range mesoscale forecast is available in the Meteorology Department's weather station. These forecasts can be performed routinely on a daily basis, or they can be initiated when large-scale numerical guidance from the NWS indicates the possible development of significant mesoscale disturbances. Regular inspection of the fine-mesh model forecasts is serving as a catalyst for further improvements in the model and is stimulating the development of techniques for evaluation of mesoscale-model forecast skill and/or utilization of mesoscale numerical guidance in an operational setting. We are also finding that this real-time forecast capability is making significant contributions to the mesoscale-meteorology research program as well as to the teaching and public-service responsibilities of the Department of Meteorology at Penn State.