Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

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

doi:10.1175/MWR-D-17-0371.1

Title: Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

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Abstract

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-trackmore » forecast.« less

Authors:

Li, Guotu ^[1]; Curcic, Milan ^[2]; Iskandarani, Mohamed ^[2]; Chen, Shuyi S. ^[3]; Knio, Omar M. ^[1]

Duke University, Durham, North Carolina
University of Miami, Miami, Florida
University of Washington, Seattle, Washington

Publication Date:: Tue Jan 01 00:00:00 EST 2019

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Org.:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

OSTI Identifier:: 1488618

Alternate Identifier(s):: OSTI ID: 1544141

Grant/Contract Number:: SC0008789

Resource Type:: Published Article

Journal Name:: Monthly Weather Review

Additional Journal Information:: Journal Name: Monthly Weather Review Journal Volume: 147 Journal Issue: 1; Journal ID: ISSN 0027-0644

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    Li, Guotu, Curcic, Milan, Iskandarani, Mohamed, Chen, Shuyi S., and Knio, Omar M. Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010).  United States: N. p., 2019. 
Web.  doi:10.1175/MWR-D-17-0371.1.

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                    Li, Guotu, Curcic, Milan, Iskandarani, Mohamed, Chen, Shuyi S., & Knio, Omar M. Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010).  United States.  https://doi.org/10.1175/MWR-D-17-0371.1

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                    Li, Guotu, Curcic, Milan, Iskandarani, Mohamed, Chen, Shuyi S., and Knio, Omar M. Tue .  
"Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)".  United States.  https://doi.org/10.1175/MWR-D-17-0371.1.

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@article{osti_1488618,

  title        = {Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)},

  author       = {Li, Guotu and Curcic, Milan and Iskandarani, Mohamed and Chen, Shuyi S. and Knio, Omar M.},

  abstractNote = {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.},

  doi          = {10.1175/MWR-D-17-0371.1},

  journal      = {Monthly Weather Review},

  number       = 1,

  volume       = 147,

  place        = {United States},

  year         = {Tue Jan 01 00:00:00 EST 2019},

  month        = {Tue Jan 01 00:00:00 EST 2019}

}

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