26th Conference on Hurricanes and Tropical Meteorology


A Decision Tree to Assess Forecast Track Confidence for Landfalling Gulf of Mexico Tropical Cyclones

Lance T. Wood, NOAA/NWSFO, Houston/Galveston, TX; and W. Read and G. Hafele

Once a tropical cyclone develops in or enters into the Gulf of Mexico, it is inevitable that many critical decisions will have to be made by various interests. Although tropical cyclone track forecasts have improved significantly over the past few decades, the state of this science is still not sufficiently accurate to provide definitive answers to decision maker dilemmas such as: evacuation, resource or aid pre-placement, and petrochemical plant shutdowns. The goal of this study is to aid in the decision making process by developing a decision tree for assessing the confidence of a track forecast for a landfalling tropical cyclone. If a decision maker is able to determine that the track forecast is one of high confidence, many critical decisions would become straight forward and could be made earlier than would normally occur. However, when faced with a low confidence forecast, key decisions might be delayed until a higher level of confidence can be reached. This decision tree could also be valuable to meteorologists as a briefing tool because it provides an objective, historically based, confidence level for any Gulf of Mexico landfall forecast.

Tropical cyclone best track data and National Hurricane Center forecast advisories and discussions have been analyzed for the period of 1998 to 2003. During these 6 years, 26 tropical cyclones made landfall along the Gulf of Mexico coastline. Once a landfall forecast was within the forecast period (72 hours) for any tropical cyclone, the above mentioned data were examined. Several characteristics of the tropical cyclone were analyzed in order to determine which factors affect the predictability, and what their relative importance is, when attempting to assess the confidence of a landfalling tropical storm or hurricane track forecast. Examples of these factors include: the degree of organization, speed of movement, initial location, persistence of the center location, and the degree of forecast track stability.

extended abstract  Extended Abstract (28K)

Poster Session 1, Posters
Wednesday, 5 May 2004, 1:30 PM-1:30 PM, Richelieu Room

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