A global TC development pathway climatology

A recent climatology of TC development in the North Atlantic basin (1948-2004) showed that more than half of tropical cyclogenesis events occur in environments that do not conform to the classic conceptual models of the process. Using a pair of dynamically-based metrics (Q-vector forcing for ascent and lower-level thermal gradient), cases of TC development in the HURDAT dataset were classified using a latent class analysis (LCA) based on metric values computed from the NCEP/NCAR Reanalysis dataset. Almost a quarter of North Atlantic TCs formed following a tropical transition (TT) pathway over the period, while a further 35% experienced some combination of trough and/or baroclinic influence during their development.

The complexity of the LCA technique - which stratifies cases based on the evolution of the metrics over the 36 h period prior to cyclogenesis - precludes its use in a real-time context for TC development classification. The "latent" aspect of the technique implies that the categories are not prescribed a priori, but rather depend on the dataset being analyzed. While providing the flexibility required for the initial study, an LCA-based approach needs to be simplified before an extension of the climatology to other basins or periods can be undertaken. In this presentation, a linear discriminant analysis (LDA) using instantaneous values of the Q-vector and thermal metrics is shown to reproduce both the results of the full LCA climatology and a pair of short subjective climatologies to within a reasonable level of accuracy (>80% of the full climatology is reproduced, with higher values for the subjective results).

The LDA approach allows for the extension of the climatology to other basins and to real-time analysis. This presentation focuses on the results of the global climatology by investigating the preferred development pathways in different regions, and the impact of the development mode on the subsequent evolution of TCs in different basins. An analysis of "preferred development pathway" will also be presented, which may provide guidance for the prediction of TC development along non-traditional pathways in real time.