Beta Test of the Systematic Approach Expert System Prototype as a Tropical Cyclone Track Forecasting Aid

Abstract

The authors have developed error mechanism conceptual models with characteristic track departures and anomalous wind or sea level pressure patterns for dynamical tropical cyclone track predictions primarily occurring in tropical regions or those associated with midlatitude circulation patterns. These conceptual models were based on a retrospective study in which it was known that the 72-h track error exceeded 300 n mi (555 km). A knowledge-based expert system module named the Systematic Approach Forecast Aid (SAFA) has been developed to assist the forecaster in the information management, visualization, and proactive investigation of the frequently occurring error mechanisms. A beta test of the SAFA module was carried out for all available track forecasts for the western North Pacific cyclones 19W?30W during 1999. The objective was to determine if the SAFA module could guide the team to apply the conceptual models in a real-time scenario to detect dynamical model tracks likely to have 72-h errors greater than 300 n mi. The metric was a selective consensus from the remaining model tracks that had smaller errors than the nonselective consensus track of all dynamical model tracks. This beta test demonstrated that the prototype SAFA module with the large-error mechanism conceptual models could be effectively applied in real-time conditions. The beta-test team recognized 14 cases in which elimination of one or more dynamical model forecasts before calculating the consensus track resulted in a 10% improvement over the nonselective consensus track. A number of lessons learned from the beta test are described, including that rejecting a specific model track is not normally successful if the tracks are tightly clustered, that the availability of the model-predicted fields is critical to the error detection, and that at least three of the five model tracks need to be available.