Extended Abstract (308K)9.2
A model to predict red flag warning days
Randall P. Benson, South Dakota School of Mines and Technology, Rapid City, SD; and G. W. Carbin
Red Flag Warnings and Fire Weather Watches are issued by local National Weather Service offices when wildfire danger is high and weather conditions will adversely affect the ability to manage a wildfire if it occurs. The issuance of a Red Flag Warning initiates an increased demand for fire-fighting resources at the federal, state, and/or county level. We have developed a model to predict potential red flag conditions to 10 days based on historical weighted red flag weather conditions and a predicted Energy Release Component (ERC). Critical thresholds for temperature, relative humidity, wind speed, and the potential for dry thunderstorms determine the red flag weather variables. Dry thunderstorm probability is calculated from the probability difference between the likelihood of thunder minus the likelihood of a wetting rain (>0.10 inch). The locations involved in our study include Casper, Wyoming; Rapid City, South Dakota; and Scottsbluff, Nebraska. Output from the Map Analog Retrieval System (MARS) forecast system developed at the Storm Prediction Center (SPC) in Norman, Oklahoma serves as the basis for the predictor variables used in this analysis. MARS is a prefect prog approach that is a unique version of the GFS ensemble mean being tested at SPC. The ensemble includes weighted time-lags from prior operational Global Forecast System (GFS) and GFS ensemble runs. There are 19 GFS members and MARS uses the overall mean for the height fields and the precipitable water field at each forecast hour. Only three components go into the MARS prediction system: 500 height gradient, 850 height gradient, and precipitable water. MARS uses the NCEP Reanalysis data with a somewhat course grid resolution of 2.5 degrees. The level of detail is less than what is required to discern typical mesoscale features that contribute to fire behavior; however, synoptically apparent cases may be captured if the ensemble forecast contains good analog fits. To construct the site-specific Red Flag Warning potential, the top ten analogs or matches are identified from the MARS output and ranked according to Root-Mean-Squared (RMS) error. The red flag probabilities are constructed from the MARS analogs using archived Automated Surface Observation Stations (ASOS) climate data containing the red flag criteria from 1979 to 2004. The MARS RMS error numbers describe the essence of the match between the MARS output and the Reanalysis data. A computer program ingests the twice-daily (00z and 12z) MARS forecasts and user input forecast ERC values and computes the 10-day red flag potential based on a weighted average of the red flag weather and the input ERC percentile rank. Testing of the model will occur during the 2007 wildfire season and verification will be completed at the conclusion of the coming fire season.
Session 9, Improvements to Fire Danger and Fire Behavior Systems II
Thursday, 25 October 2007, 10:30 AM-11:45 AM, The Turrets
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