Tropical Cyclone Simulation and Seasonal
Prediction: towards regional and high-intensity
information

Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system, therefore understanding and predicting TC location, intensity and frequency is of both societal and scientific significance. Methodologies exist to predict basin-wide, seasonally-aggregated TC activity months, seasons and even years in advance. We show that a newly developed high-resolution global climate model (FLOR) can produce skillful forecasts of seasonal TC activity on spatial scales finer than basin-wide, from months and seasons in advance of the TC season. The climate model used here is targeted at intraseasonal-to-multiyear prediction of regional climate and the statistics of weather extremes on seasonal to decadal timescales. These results suggest that dynamical forecasts of seasonally-aggregated regional TC activity months in advance are feasible.

In order to target high-internsity tropical cyclones (Categories 4-5) further the high resolution model is further refined to a 25km x25km resolution (HiFLOR). . Compared with FLOR, HiFLOR yields a more realistic simulation of the structure, global distribution, and seasonal and interannual variations of TCs, and a comparable simulation of storm-induced cold wakes and TC-genesis modulation induced by the Madden Julian Oscillation (MJO). Moreover, HiFLOR is able to simulate and predict extremely intense TCs (categories 4 and 5) and their interannual variations, which represents the first time a global coupled model has been able to make seasonal predictions and multi-century simulations of such extremely intense TCs.

Gabriel Vecchi

<

 

<