Development and evaluation of mesoscale lightning threat guidance for operational use at NWS forecast offices

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 20 January 2010: 1:30 PM
B305 (GWCC)
Pete Saunders, Florida State University, Tallahassee, FL; and H. E. Fuelberg

We have developed a perfect prognosis technique for forecasting warm-season lightning over three diverse regions of the United States. The National Weather Service forecast offices for these regions are Pendleton, OR, Pueblo, CO, and Sterling, VA. The statistical technique implemented in this study originally was developed by Shafer and Fuelberg (2007) for forecasting lightning over Florida. The current study uses four warm seasons of RUC (Rapid Update Cycle) analysis data and lightning data from the National Lightning Detection Network to develop separate 3-hourly, 10 km x 10 km gridded forecast guidance products for warm-season lightning over each region. Since NWP models often have difficulty resolving small scale regions of convection, a map-typing technique was applied in which five dominant low-level flow regimes are identified for each region and used to capture lightning enhancements due to local forcing. Binary logistic regression is used to develop equations for forecasting one or more flashes, while a negative binomial statistical model is used to predict the amount of lightning, conditional on one or more flashes occurring. The perfect prognosis scheme is evaluated using independent data from mesoscale models during the 2008 warm season. Output from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13) and the NCEP 12-km North American Mesoscale Model is used to evaluate the performance of the new lightning guidance products. The goal is to beat lightning forecasts that are attained from climatology and persistence alone for each region, and to make the technique a fully operational guidance product that can be used for NWS offices in these three regions.