89th American Meteorological Society Annual Meeting

Monday, 12 January 2009
Lightning prediction by WFO Grand Junction using model data and graphical forecast editor smart tools
Hall 5 (Phoenix Convention Center)
P. Frisbie, NOAA/NWSFO, Grand Junction, CO; and J. D. Colton and M. P. Meyers
Poster PDF (142.0 kB)
The leading weather related killer in the states of Colorado and Utah is lightning. Nationwide, lightning is the number two killer, exceeding the number of fatalities from hurricanes and tornadoes combined. Lightning injures 1000 people a year in the nation, inflicting severe lifelong debilitating injuries. In addition to public safety, lightning sparks many large complexes of wildfires. Given the societal impacts from lightning, there's a strong need for accurate lightning prediction. Unfortunately, lightning prediction is a challenge because of its high spatial and temporal variability. The causes of lightning are fairly well understood; the separation of charges created by strong electric fields within a thunderstorm. Understanding how these charges separate may help lightning forecasting, but this is a subject of continuing research as the charge separation is not fully understood. Studies have shown that Convective Available Potential Energy (CAPE) is a useful meteorological parameter for forecasting lightning. Recent research suggests that high relative humidity and temperatures in the -12C to -18C range promote stronger negative charging. WFO Grand Junction has made an attempt in forecasting lightning by factoring CAPE and relative humidity at the -10C level. By combining these two meteorological parameters in AWIPS Display Two Dimensions (D-2D) and the Graphical Forecast Editor (GFE), an algorithm has been developed on lightning potential. Using model data for CAPE and relative humidity at -10C, there is improved skill in forecasting the location and frequency of lightning strikes. Also, there are drawbacks to the lightning algorithm, most notably it relies on model data. If the model data does not verify well, then the lightning forecast will not be accurate. Currently the algorithm does not consider slantwise convection. This poster will look at the WFO Grand Junction methodology and show why lightning forecasting skill is improved. The creation of such a product may lead to better lightning forecast in the future and provide valuable information to the public and the fire weather community.

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