The National Weather Service is currently undergoing an extensive modernization and restructuring which should greatly improve its ability to serve the need for accurate and timely forecasts. As the NWS modernization progresses, the operational emphasis will shift toward enhanced short-term and small-scale phenomena forecasts. This shift in focus will require a better understanding of mesoscale processes as well as create a need for numerical weather prediction models with better spacial and temporal resolution.

As part of the local modernization effort, the National Weather Service Forecast Office in Raleigh, NC, will begin using the Mesoscale Atmospheric Simulation System (MASS), a mesoscale weather prediction model. The model, developed by Meso, Inc., is a three-dimensional, hydrostatic, primitive equation numerical model which has been used for over ten years in a variety of research projects. It will be run by the meteorology department at North Carolina State University on a workstation collocated with the NWS on the Centennial Campus of NCSU. The MASS output products will be created using GEMPAK, a set of application programs, libraries and graphics routines developed by NASA for analysis, display and diagnosis of meteorological data.

The purpose of using the MASS model at the forecast office is twofold. First, it will be used as a teaching tool. Through a combination of briefings, tutorials and workshops, forecasters will be introduced to the model output, initially consisting of fields with which they are already familiar (500mb heights and vorticity, mean relative humidity, sea level pressure, etc.). Once comfortable with the model itself, other derived fields, such as Q-vectors, isentropic fields, ageostrophic circulation fields, potential vorticity, etc., will be introduced and taught to the forecasters, giving them a firm foundation from which to begin using the mesoscale model output operationally.

Second, the model will be used as an operational forecast and research tool. The model will be available in real-time for use in formulating daily forecasts. During this period, forecasters will become more familiar with the model and use it to address local and regional forecast problems (e.g. cold air damming, thermal-moisture boundaries, precipitation type), to refine current forecast schemes and to develop new diagnosis techniques and forecast methodologies.