Tropical Cycle Genesis Prediction Index

Predicting tropical cyclogenesis is one of the major challenges in numerical weather prediction. Tropical disturbances with different origins and characteristics serve as tropical cyclone (TC) precursors exist all the time, but only a small percentage of them became TCs. Using NOGAPS daily analysis and TRMM rainfall rates, Peng et al. (2011) and Fu et al. (2011) identified key meteorological parameters that distinguish developing from non-developing disturbances for tropical cyclone formation. These studies indicate that TC genesis is controlled more by thermodynamic variables in the North Atlantic while it is more controlled by dynamic variables in the western North Pacific. Use these early finding, a TC genesis prediction index (GPI) is constructed. A nonlinear regression formulation was used to combine optimally key meteorological variables that control the TC formation. Basin-dependent relationships between large-scale forcing and TC genesis require that separate formulations be constructed for different basins. The Bayesian Information Criterion is applied to further refine the formula. The TC genesis index based on 2003-2010 data was applied to global analysis fields in hindcast mode to provide the probability forecast of TC genesis events for individual disturbances.

The GPI for the western Pacific was tested in the real-time environment in the 2011 season at the Joint Typhoon Warning Center (JTWC). Based on the NOGAPS analysis, the genesis index successfully predicted 9 out of the 10 genesis events in the western Pacific during the study period covering August and September. Distinct trends in GPI for developers and non-developers were noted. Most developing systems tended to show either an increasing trend in GPI, particularly between 48 and 24 hours prior to formation, or a steady upward trend over several days at values exceeding the 0.2 development threshold. The study indicates that GPI trends, in addition to individual values, may have greater utility as an operation forecasting tool.