Organizing Committee


Poster Presentations


Poster Presentations


Improving the accuracy of a meteorological model for soybean rust forecasting applications

Presenter: J. C. Wimberley

All authors and affiliations: J. C. WIMBERLEY and R. W. Pasken. Department of Earth and Atmospheric Sciences, St. Louis University, St. Louis, MO

Previous research has shown that a meteorological model (Penn State University-National Center for Atmospheric Research Mesoscale Model version 5, hereafter MM5) combined with an atmospheric dispersion and transport model (Hybrid Single-Particle Lagrangian Integrated Trajectory, hereafter HYSPLIT_4) forms an effective system for forecasting the spread of soybean rust. It has also been shown that the accuracy of particulate (e.g., soybean rust spore) dispersion forecasts produced in this method is strongly dependent on the accuracy of the meteorological forecasts used as input to the dispersion model. It is thus in our best interest to work to make the meteorological portion of the system as accurate as possible. The MM5 model features the ability to be tuned for specific applications via the selection of different parameterization and modeling schemes for individual meteorological processes. Our project seeks to determine which combinations of parameters enable the model to create the best meteorological forecast, in turn enabling it to create the most accurate prediction of soybean rust dispersion. Forecasts from 18 model configurations, each using a different combination of parameterization choices but all valid for the same time, are compared to corresponding analysis fields from the North American Mesoscale (NAM) model, and the differences are assessed. Research is ongoing.

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