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Relative accuracy of HWRF reanalysis and a parametric wind model during the landfall of Hurricane Florence and the impacts on storm surge simulations

Author

Listed:
  • Md Arifur Rahman

    (The University of Texas at Arlington
    Bangladesh University of Engineering and Technology (BUET))

  • Yu Zhang

    (The University of Texas at Arlington)

  • Lixin Lu

    (Colorado State University)

  • Saeed Moghimi

    (NOAA National Ocean Service)

  • Kelin Hu

    (Tulane University)

  • Ali Abdolali

    (NOAA National Weather Service
    Lynker
    University of Maryland)

Abstract

Prediction and reanalysis of storm surge rely on wind and pressure fields from either parametric tropical cyclone wind models or numerical weather model reanalysis, and both are subject to large errors during landfall. This study assesses two sets of wind/pressure fields for Hurricane Florence that made landfall along the Carolinas in September 2018 and appraises the impacts of differential structural errors in the two suites of modeled wind fields on the predictive accuracy of storm surge driven thereby. The first set was produced using Holland 2010 (H10), and the second set is the Hurricane Weather Research and Forecasting (HWRF) reanalysis created by the NWS National Centers for Environmental Prediction (NCEP). Each is validated using a large surface data set collected at public and commercial platforms and then is used as input forcing to a 2-D coastal hydrodynamic model (Delft3D Flexible Mesh) to produce storm surge along the Carolina coasts and major sounds. Major findings include the following. First, wind fields from HWRF are overall more accurate than those based on H10 for the periphery of the storm, though they exhibit limitations in resolving high wind speeds near the center. Second, applying H10 to the best track data for Florence yields an erroneously spike in wind speed on September 15th when the storm reduced to a tropical depression. Third, HWRF wind fields exhibit a progressively negative bias after landfall, likely due to deficiencies of the model in representing boundary layer processes, and to the lack of assimilation of surface product after landfall for compensating for these deficiencies. Fourth, using HWRF reanalysis as the forcings to Delft3D yields more accurate peak surges simulations, though there is severe underestimation of surge along the shoreline close to the track center. The peak surge simulations by Delft3D are biased low when driven by H10, even though over several locations the H10 model clearly overpredicts surface wind speeds. This contrast highlights the importance of resolving wind fields further away from the center in order to accurately reproduce storm surge and associated coastal flooding.

Suggested Citation

  • Md Arifur Rahman & Yu Zhang & Lixin Lu & Saeed Moghimi & Kelin Hu & Ali Abdolali, 2023. "Relative accuracy of HWRF reanalysis and a parametric wind model during the landfall of Hurricane Florence and the impacts on storm surge simulations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 869-904, March.
  • Handle: RePEc:spr:nathaz:v:116:y:2023:i:1:d:10.1007_s11069-022-05702-3
    DOI: 10.1007/s11069-022-05702-3
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    References listed on IDEAS

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    1. V. Cardone & A. Cox, 2009. "Tropical cyclone wind field forcing for surge models: critical issues and sensitivities," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 51(1), pages 29-47, October.
    2. Donald T. Resio & Nancy Powell & Mary Cialone & Himangshu S. Das & Joannes J. Westerink, 2017. "Quantifying impacts of forecast uncertainties on predicted storm surges," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1423-1449, September.
    3. Kelin Hu & Qin Chen & Sytske Kimball, 2012. "Consistency in hurricane surface wind forecasting: an improved parametric model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(3), pages 1029-1050, April.
    4. Mark D. Powell & Peter J. Vickery & Timothy A. Reinhold, 2003. "Reduced drag coefficient for high wind speeds in tropical cyclones," Nature, Nature, vol. 422(6929), pages 279-283, March.
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