Topical analysis of fine-scale Numerical Weather Prediction on NASCAR racetracks and event venues

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Monday, 18 January 2010
Elliot M. Tardif, University of North Carolina at Charlotte, Charlotte, NC

Fine-scale numerical weather prediction (NWP) is a continuously evolving science, one that has become especially useful for predicting weather conditions in specific locations. Such specific locations include racetracks, where accurate prediction of surface-layer environmental variables are critical to the competitive welfare of race teams throughout the race weekend. Some variables of particular importance to race teams, such as air density, include variables not given in typical MOS forecasts. Weather affects how the car handles through the amount of grip offered by the racetrack and by the tires, through the density of air affecting the aerodynamics of the body, and through the power and overall efficiency of the engine. However, the principle of point-specific fine-scale NWP has potential for a number of other events besides racing, including any variety of outdoor event.

Thus, a fine-scale nested WRF model was developed, using a number of different physics scheme combinations, to determine which combinations provide better forecasts for specific surface locations, of varying geography, throughout the United States. A single-nested, 1.5km resolution WRF model was utilized to forecast for every track and every race on the 2009 NASCAR Sprint Cup schedule. A tri-nested WRF model, utilizing many different physics combinations, was used to analyze specific race weekends from the 2009 season. A tri-nested model was also centered over the UNC-Charlotte campus to provide point-specific forecasting for UNC-Charlotte Athletics events. Output from each of those events were compared against observed conditions taken trackside and on campus and analyzed for their accuracy and shortcomings for a variety of environmental variables, including temperature, winds, and precipitation.

It is believed that fine-scale NWP benefits entities who choose to use it; race teams have a broader palette of atmospheric conditions to work with and thus gain themselves a competitive advantage; venues who use fine-scale NWP can potentially become safer by identifying times of adverse weather in the forecast and preparing themselves as such.