Predictability and dynamics of tropical cyclone rapid intensification deduced from high-resolution stochastic ensembles

Falko Judt, Shuyi S. Chen

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Rapid intensification (RI) of tropical cyclones (TCs) remains one of the most challenging issues in TC prediction. This study investigates the predictability of RI, the uncertainty in predicting RI timing, and the dynamical processes associated with RI. To address the question of environmental versus internal control of RI, five high-resolution ensembles of Hurricane Earl (2010) were generated with scale-dependent stochastic perturbations from synoptic to convective scales. Although most members undergo RI and intensify into major hurricanes, the timing of RI is highly uncertain. While environmental conditions including SST control the maximum TC intensity and the likelihood of RI during the TC lifetime, both environmental and internal factors contribute to uncertainty in RI timing. Complex interactions among environmental vertical wind shear, the mean vortex, and internal convective processes govern the TC intensification process and lead to diverse pathways to maturity. Although the likelihood of Earl undergoing RI seems to be predictable, the exact timing of RI has a stochastic component and low predictability. Despite RI timing uncertainty, two dominant modes of RI emerged. One group of members undergoes RI early in the storm life cycle; the other one later. In the early RI cases, a rapidly contracting radius of maximum wind accompanies the development of the eyewall during RI. The late RI cases have a well-developed eyewall prior to RI, while an upper-level warm core forms during the RI process. These differences indicate that RI is associated with distinct physical processes during particular stages of the TC life cycle.

Original languageEnglish (US)
Pages (from-to)4395-4420
Number of pages26
JournalMonthly Weather Review
Issue number11
StatePublished - 2016


  • Convective-scale processes
  • Ensembles
  • Numerical analysis/modeling
  • Numerical weather prediction/forecasting
  • Stochastic models
  • Tropical cyclones

ASJC Scopus subject areas

  • Atmospheric Science


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