Skip to main content

Evaluation of parametric wind models for more accurate modeling of storm surge: a case study of Hurricane Michael

Abstract

Storm surge induced by hurricane is a major threat to the Gulf Coasts of the United States. A numerical modeling study was conducted to simulate the storm surge during Hurricane Michael, a category 5 hurricane that landed on the Florida Panhandle in 2018. A high-resolution model mesh was used in the ADCIRC hydrodynamic model to simulate storm surge and tides during the hurricane. Two parametric wind models, Holland 1980 model and Holland 2010 model, have been evaluated for their effects on the accuracy of storm surge modeling by comparing simulated and observed maximum water levels along the coast. The wind model parameters are determined by observed hurricane wind and pressure data. Results indicate that both Holland 1980 and Holland 2010 wind models produce reasonable accuracy in predicting maximum water level in Mexico Beach, with errors between 1 and 3.7%. Comparing to the observed peak water level of 4.74 m in Mexico Beach, Holland 1980 wind model with radius of 64-knot wind speed for parameter estimation results in the lowest error of 1%. For a given wind model, the wind profiles are also affected by the wind data used for parameter estimation. Away from hurricane eye wall, using radius of 64-knot wind speed for parameter estimation generally produces weaker wind than those using radius of 34-knot wind speed for parameter estimation. Comparing model simulated storm tides with 17 water marks observed along the coast, Holland 2010 wind model using radius of 34-knot wind speed for parameter estimation leads to the minimum mean absolute error. The results will provide a good reference for researchers to improve storm surge modeling. The validated model can be used to support coastal hazard mitigation planning.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

References

  • Beven II JL, Berg R, Hagan A (2019). Tropical cyclone report: Hurricane Michael (AL 142018) 7–11 October 2018. National Hurricane Center

  • Bilskie MV, Hagen SC (2018) Defining flood zone transitions in low-gradient coastal region. Geophys Res Lett 45(6):2761–2770

    Article  Google Scholar 

  • Cheng J, Wang P (2019) Unusual beach changes induced by Hurricane Irma with a negative storm surge and post storm recovery. J Coastal Res 35(6):1185–1199

    Article  Google Scholar 

  • Ding Y, Ding T, Rusdin A, Zhang Y, Jia Y (2020) Simulation and prediction of storm surges and waves using a fully-integrated process model and a parametric cyclonic wind model. J Geophys Res Oceans. https://doi.org/10.1029/2019JC015793

    Article  Google Scholar 

  • FEMA Mitigation Assessment Team Report (2020) Hurricane Michael in Florida: building performance observations, recommendations and technical guidance

  • Florida Division of Emergency Management (2018) https://www.floridadisaster.org/news-media/news/20181009-gov.-scott-federal-pre-landfall-emergency-declaration-signed-by-the-president/

  • Fritz HM, Blount CD, Albusaidi FB, Al-Harthy AHM (2010) Cyclone Gonu storm surge in Oman. Estuar Coast Shelf Sci 86:102–106

    Article  Google Scholar 

  • Holland GJ (1980) An analytic model of the wind and pressure profiles in hurricanes. Mon Weather Rev 108:1212–1218

    Article  Google Scholar 

  • Holland GJ, Belanger JI, Fritz A (2010) A revised model for radial profiles of hurricane winds. Mon Weather Rev 138:4393–4401

    Article  Google Scholar 

  • Kerr PC, Martyr RC, Donahue AS, Hope ME, Westerink JJ, Luettich RA, Kennedy AB, Dietrich JC, Dawson C, Westerink HJ (2013) U.S. IOOS coastal and ocean modeling testbed: evaluation of tide, wave, and hurricane surge response sensitivities to mesh resolution and friction in the Gulf of Mexico. J Geophys Res Oceans 118:4633–4661. https://doi.org/10.1002/jgrc.20305

    Article  Google Scholar 

  • Landsea CW, Franklin JL (2013) Atlantic hurricane database uncertainty and presentation of a new database format. Mon Weather Rev 141:3576–3592

    Article  Google Scholar 

  • Li L, Yuan S, Amini F, Tang H (2015) Numerical study of combined wave overtopping and storm surge overflow of HPTRM strengthened levee. Ocean Eng 97:1–11

    Article  Google Scholar 

  • Li L, Yang J, Lin C-Y, Chua CT, Wang Y, Zhao K, Wu Y-T, Liu PL-F, Switzer AD, Mok KM, Wang P, Peng D (2018) Field survey of Typhoon Hato (2017) and a comparison with storm surge modeling in Macau. Nat Hazards Earth Syst Sci 18:3167–3178

    Article  Google Scholar 

  • Lin N, Emanuel KA, Smith JA, Vanmarcke E (2010) Risk assessment of hurricane storm surge for New York City. J Geophys Res Atmos. https://doi.org/10.1029/2009JD013630

    Article  Google Scholar 

  • Luettich RA Jr, Westerink JJ, Scheffner NW (1992) ADCIRC: an advanced three-dimensional circulation model for shelves, coasts, and estuaries. Report 1. Theory and methodology of adcirc-2ddi and adcirc-3dl; Dredging Research Program Technical Report DRP-92-6; US Army Corps of Engineers

  • National Centers for Environmental Information (NCEI) (2019) Assessing the U.S. climate in 2018

  • Pan Y, Chen Y, Li J, Ding X (2016) Improvement of wind field hindcasts for tropical cyclones. Water Sci Eng 9(1):58–66

    Article  Google Scholar 

  • Pan ZH, Liu H (2019) Extreme storm surge induced coastal inundation in Yangtze Estuary regions. J Hydrodyn 31(6):1127–1138. https://doi.org/10.1007/s42241-019-0086-1

    Article  Google Scholar 

  • Pan Z, Liu H (2020) Impact of human projects on storm surge in the Yangtze Estuary. Ocean Eng 196:106792

    Article  Google Scholar 

  • Shen Y, Deng G, Xu Z, Tang J (2020) Effects of sea level rise on storm surge and waves within the Yangtze River Estuary. Front Earth Sci 13:303–316. https://doi.org/10.1007/s11707-018-0746-4

    Article  Google Scholar 

  • Siverd CG, Hagen SC, Bilskie MV, Braud DH, Gao S, Peele RH, Twilley RR (2019) Assessment of the temporal evolution of storm surge across coastal Louisiana. Coast Eng 150:59–78

    Article  Google Scholar 

  • Siverd CG, Hagen SC, Bilskie MV, Braud DH, Twilley RR (2020) Quantifying storm surge and risk reduction costs: a case study for Lafitte, Louisiana. Clim Change. https://doi.org/10.1007/s10584-019-02636-x

    Article  Google Scholar 

  • Sun Z, Huang S, Nie H, Jiao J, Huang S, Zhu L, Xu D (2015) Risk analysis of seawall overflowed by storm surge during super typhoon. Ocean Eng 107:178–185

    Article  Google Scholar 

  • Ullman DS, Ginis I, Huang W, Nowakowski C, Chen X, Stempel P (2019) Assessing the multiple impacts of extreme hurricanes in Southern New England, USA. Geosciences 9(6):265

    Article  Google Scholar 

  • United States Environmental Protection Agency, Public Affairs (2019) https://response.epa.gov/site/site_profile.aspx?site_id=13982

  • Wang P, Adam JD, Cheng J, Vallée M (2020) Morphological and sedimentological impacts of Hurricane Michael along the northwest Florida coast. J Coastal Res 36(5):932–950

    Article  Google Scholar 

  • Wang T, Yang Z (2019) The nonlinear response of storm surge to sea-level rise: a modeling approach. J Coastal Res 35(2):287–294

    Article  Google Scholar 

  • Westerink JJ, Luettich RA, Feyen JC, Atkinson JH, Dawson C, Roberts HJ, Powell MD, Dunion JP, Kubatko EJ, Pourtaheri HA (2008) Basin-to channel-scale unstructured grid hurricane storm surge model applied to Southern Louisiana. Mon Weather Rev 136:833–864

    Article  Google Scholar 

  • Xiao H, Wang D, Medeiros SC, Bilskie MV, Hagen SC, Hall CR (2019) Exploration of the effects of storm surge on the extent of saltwater intrusion into the surficial aquifer in coastal east-central Florida (USA). Sci Total Environ 648:1002–1017. https://doi.org/10.1016/j.scitotenv.2018.08.199

    Article  Google Scholar 

  • Yang Z, Wang T, Castrucci L, Miller I (2020) Modeling assessment of storm surge in the Salish Sea. Estuar Coast Shelf Sci 238:106552

    Article  Google Scholar 

  • Yang Z, Wang T, Leung R, Hibbard K, Janetos T, Kraucunas I, Rice J, Preston B, Wilbanks T (2014) A modeling study of coastal inundation induced by storm surge, sea-level rise, and subsidence in the Gulf of Mexico. Nat Hazards 71:1771–1794

    Article  Google Scholar 

  • Yin K, Xu S, Huang W, Xie Y (2017) Effects of sea level rise and typhoon intensity on storm surge and waves in Pearl River estuary. Ocean Eng 136:80–93

    Article  Google Scholar 

  • Yuan S, Li L, Amini F, Tang H (2014) Numerical study of turbulence and erosion of an HPTRM strengthened levee under combined storm surge overflow and wave overtopping. J Coastal Res 30(1):142–157

    Google Scholar 

Website visited

Download references

Acknowledgements

This study was supported by National Science Foundation Award #1832068. Mr. Kai Yin conducted preliminary model development as a visiting student in FAMU-FSU College of Engineering sponsored by China Scholarship Council. The authors appreciate Rick Luettich’s help for providing the ADCIRC code to support our study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wenrui Huang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Vijayan, L., Huang, W., Yin, K. et al. Evaluation of parametric wind models for more accurate modeling of storm surge: a case study of Hurricane Michael. Nat Hazards 106, 2003–2024 (2021). https://doi.org/10.1007/s11069-021-04525-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-021-04525-y

Keywords

  • Storm surge modeling
  • ADCIRC
  • Parametric wind model
  • Hurricane Michael