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Lightning causes most wildfires in the western United States, and is a major cause of fire elsewhere in the U.S. Because most lightning occurs with significant precipitation, however, simple predictions of Lightning Activity Level (LAL) do not accurately determine fire ignition potential. We propose to incorporate existing weather predictions into tactical fire preparedness and planning by adapting a methodology to assess the risk of 'dry' lightning (that which occurs without accompanying rainfall). Based on atmospheric moisture and stability variables, we will develop discriminant rules that assign a probability of dry lightning over the United States, using a method that we created and tested in the northwestern U.S. (Rorig and Ferguson 1999). The results will be presented on maps and in tables that will be available via the Internet. In addition, we will apply and test the rule to mesoscale weather models (MM5) that currently operate in real-time support of fire weather predictions in Florida and the northwestern US, making the nile available for regional fire-weather modeling with MM5 being planned in other parts of the country Fire weather forecasters will be able to use these results to improve predictions of lightning-caused fire ignitions.
Cataloging Information
- LAL - lightning activity level
- lightning
- MM5 - Mesoscale Model generation 5
- models
- weather
- 01-1-6-08