A statistical hail prediction product
Daniel T. Lindsey, NOAA/NESDIS, Fort Collins, CO
A product is currently being developed which uses a statistical model to objectively predict the probability of severe hail across much of the continental U.S. The model was built by using observed severe hail reports from 2 warm seasons, along with data from GOES-12 and the Rapid Update Cycle (RUC) model. Using discriminate analysis, a number of satellite and near-storm-environment predictors were tested, and the best predictors were weighted accordingly to produce the best forecast for hail.
Although cold cloud tops are obviously correlated with severe hail observations, the model is actually designed to forecast hail in the 0-3-hour time window, as opposed to being used to issue severe thunderstorm warnings. Data from the Storm Prediction Center's (SPC) surface mesoanalysis is combined with RUC 1-, 2-, and 3-hour forecasts and current GOES-East imagery to produce the forecast in real time. The output is then sent to the SPC, and was evaluated during the 2010 Hazardous Weather Testbed Spring Experiment. This presentation will explain how the product works and will show a number of examples from the 2010 severe weather season.
The views, opinions, and findings contained in this article are those of the author(s) and should not be construed as an official National Oceanic and Atmospheric Administration or U.S. Government position, policy, or decision.
Poster Session 4, Forecasting Techniques and Warning Decision Making Posters I
Tuesday, 12 October 2010, 3:00 PM-4:30 PM, Grand Mesa Ballroom ABC
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