Uncertainty propagation in coupled atmosphere-wave-ocean prediction system: A study of Hurricane Earl (2010)

Guotu Li, Milan Curcic, Mohamed Iskandarani, Shuyi S. Chen, Omar M. Knio*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm's initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere-wave-ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.

Original languageEnglish (US)
Pages (from-to)221-245
Number of pages25
JournalMonthly Weather Review
Issue number1
StatePublished - Jan 1 2019

Bibliographical note

Publisher Copyright:
© 2018 American Meteorological Society.


  • Bayesian methods
  • Empirical orthogonal functions
  • General circulation models
  • Statistical techniques

ASJC Scopus subject areas

  • Atmospheric Science


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