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Evaluation of mesoscale lightning threat guidance for the State of Colorado

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Wednesday, 26 January 2011
Evaluation of mesoscale lightning threat guidance for the State of Colorado
Washington State Convention Center
Stephen J. Hodanish, NOAA/NWS, Pueblo, CO; and P. Wolyn, P. Saunders, H. E. Fuelberg, and A. Gibbs

This poster will evaluate a Mesoscale Lightning Guidance (MLG) product which was the result of a COMET lightning research project between the Florida State University and the National Weather Service. A perfect prognosis guidance technique for forecasting warm-season lightning was developed for the State of Colorado, and has been made recently available for NWS forecasters to evaluate. Details of the MLG product can be found in a companion paper in the conference (Fuelberg and Saunders). In summary, a map-typing technique in which five dominant low-level flow regimes were identified for the Centennial State to locate lightning enhancements due to local forcing mechanisms that generally are related to the lower level flow. Binary logistic regression was then used to develop equations for forecasting one or more flashes, while a negative binomial statistical model was used to predict the amount of lightning, conditional on one or more flashes occurring. The scheme were evaluated using independent mesoscale model data during the 2008 warm season. Computer simulations utput from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13) and the NCEP 12-km North American Mesoscale Model were used to create the guidance products.

During the Warm Season of 2010, the output from the RUC13 model output was being analyzed to observe how useful this MLG will be to forecasting lightning activity over the State of Colorado. Comparisons will be made between the 3 hourly forecast MLG output to the 3 hourly NLDN flash density product in the Graphical Forecast Editor (GFE). If the data is found useful, we hope to incorporate this data in the GFE so the MLG can be incorporated into the National Digital Forecast Database.