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

    Source: Monthly Weather Review:;2018:;volume 147:;issue 001::page 221
    Author:
    Li, Guotu
    ,
    Curcic, Milan
    ,
    Iskandarani, Mohamed
    ,
    Chen, Shuyi S.
    ,
    Knio, Omar M.
    DOI: 10.1175/MWR-D-17-0371.1
    Publisher: American Meteorological Society
    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-track forecast.
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      Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4262692
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    contributor authorLi, Guotu
    contributor authorCurcic, Milan
    contributor authorIskandarani, Mohamed
    contributor authorChen, Shuyi S.
    contributor authorKnio, Omar M.
    date accessioned2019-09-22T09:04:01Z
    date available2019-09-22T09:04:01Z
    date copyright11/5/2018 12:00:00 AM
    date issued2018
    identifier otherMWR-D-17-0371.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4262692
    description abstractThis 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.
    publisherAmerican Meteorological Society
    titleUncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)
    typeJournal Paper
    journal volume147
    journal issue1
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-17-0371.1
    journal fristpage221
    journal lastpage245
    treeMonthly Weather Review:;2018:;volume 147:;issue 001
    contenttypeFulltext
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