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Effect of the drag coefficient on a typhoon wave model

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Abstract

The effect of the drag coefficient on a typhoon wave model is investigated. Drag coefficients for Pingtan Island are derived from the progress of nine typhoons using COARE 3.0 software. The wind parameters are obtained using the Weather Research and Forecasting model. The simulation of wind agrees well with observations. Typhoon wave fields are then simulated using the third-generation wave model SWAN. The wave model includes exponential and linear growths of the wind input, which determine the wave-growth mode. A triple triangular mesh is adopted with spatial resolution as fine as 100 m nearshore. The SWAN model performs better when using the new drag coefficient rather than the original coefficient.

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Data Availability Statement

The contents of this article are taken from the Research Data Archive. Further details can be viewed at the following websites.

1. NCEP/DOE Reanalysis 2 (R2): https://rda.ucar.edu/datasets/ds091.0/;

2. ETOPO1 Global Relief Model: https://www.ngdc.noaa.gov/mgg/global/.

References

  • Alves J H G M, Banner M L. 2003. Performance of a saturation-based dissipation-rate source term in modeling the fetch-limited evolution of wind waves. Journal of Physical Oceanography, 33(6): 1 274–1 298.

    Article  Google Scholar 

  • Booij N, Ris R C, Holthuijsen L H. 1999. A third-generation wave model for coastal regions: 1. Model description and validation. Journal of Geophysical Research: Oceans, 104(C4): 7 649–7 666.

    Article  Google Scholar 

  • Bricheno L M, Soret A, Wolf J, Jorba O, Baldasano J M. 2013. Effect of high-resolution meteorological forcing on nearshore wave and current model performance. Journal of Atmospheric and Oceanic Technology, 30(6): 1 021–1 037.

    Article  Google Scholar 

  • Cavaleri L, Malanotte Rizzoli P. 1981. Wind wave prediction in shallow water: theory and applications. Journal of Geophysical Research: Oceans, 86(C11): 10 961–10 973.

    Article  Google Scholar 

  • Chalikov D, Babanin A V. 2012. Simulation of wave breaking in one-dimensional spectral environment. Journal of Physical Oceanography, 42(11): 1 745–1 761.

    Article  Google Scholar 

  • Charnock H. 1955. Wind stress on a water surface. Quarterly Journal of the Royal Meteorological Society, 81(350): 639–640.

    Article  Google Scholar 

  • Decharme B. 2007. Influence of runoff parameterization on continental hydrology: comparison between the Noah and the ISBA land surface models. Journal of Geophysical Research: Atmospheres, 112(D19): D19108.

    Article  Google Scholar 

  • Dietrich J C, Zijlema M, Allier P E, Holthuijsen L H, Booij N, Meixner J D, Proft J K, Dawson C N, Bender C J, Naimaster A, Smith J M, Westerink J J. 2013. Limiters for spectral propagation velocities in SWAN. Ocean Modelling, 70: 85–102.

    Article  Google Scholar 

  • Donelan M A, Haus B K, Reul N, Plant W J, Stiassnie M, Graber H C, Brown O B, Saltzman E S. 2004. On the limiting aerodynamic roughness of the ocean in very strong winds. Geophysical Research Letters, 31(18): L18306.

    Article  Google Scholar 

  • Dudhia J. 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. Journal of the Atmospheric Sciences, 46(20): 3 077–3 107.

    Article  Google Scholar 

  • Eldeberky Y. 1996. Nonlinear Transformation of Wave Spectra in the Nearshore Zone. Ph. D. thesis, Delft University of Technology, Department of Civil Engineering, The Netherlands.

    Google Scholar 

  • Fairall C W, Bradley E F, Hare J E, Grachev A A, Edson J B. 2003. Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm. Journal of Climate, 16(4): 571–591.

    Article  Google Scholar 

  • Fan Y L, Rogers W E. 2016. Drag coefficient comparisons between observed and model simulated directional wave spectra under hurricane conditions. Ocean Modelling, 102: 1–13.

    Article  Google Scholar 

  • Hasselmann K. 1974. On the spectral dissipation of ocean waves due to white capping. Boundary-Layer Meteorology, 6(1–2): 107–127.

    Article  Google Scholar 

  • Hasselmann S, Hasselmann K, Allender J H, Barnett T P. 1985. Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part II: parameterizations of the nonlinear energy transfer for application in wave models. Journal of Physical Oceanography, 15(11): 1 378–1 391.

    Article  Google Scholar 

  • Hong S Y, Noh Y, Dudhia J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Weather Review, 134(9): 2 318–2 341.

    Article  Google Scholar 

  • Janssen P A E M. 1991. Quasi-linear theory of wind-wave generation applied to wave forecasting. Journal of Physical Oceanography, 21(11): 1 631–1 642.

    Article  Google Scholar 

  • Kain J S, Fritsch J M. 1990. A one-dimensional entraining/detraining plume model and its application in convective parameterization. Journal of the Atmospheric Sciences, 47(23): 2 784–2 802.

    Article  Google Scholar 

  • Kim Y, Jang S C, Lim T J. 2015. Hazard analysis of typhoon-related external events using extreme value theory. Nuclear Engineering and Technology, 47(1): 59–65.

    Article  Google Scholar 

  • Komen G J, Hasselmann K, Hasselmann K. 1984. On the existence of a fully developed wind-sea spectrum. Journal of Physical Oceanography, 14(8): 1 271–1 285.

    Article  Google Scholar 

  • Lee H S. 2015. Evaluation of WAVEWATCH III performance with wind input and dissipation source terms using wave buoy measurements for October 2006 along the east Korean coast in the East Sea. Ocean Engineering, 100: 67–82.

    Article  Google Scholar 

  • Mlawer E J, Taubman S J, Brown P D, Iacono M J, Clough S A. 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14): 16 663–16 682.

    Article  Google Scholar 

  • Moeini M H, Etemad-Shahidi A, Chegini V. 2010. Wave modeling and extreme value analysis off the northern coast of the Persian Gulf. Applied Ocean Research, 32(2): 209–218.

    Article  Google Scholar 

  • Oost W A, Komen G J, Jacobs C M J, Van Oort C. 2002. New evidence for a relation between wind stress and wave age from measurements during ASGAMAGE. Boundary-Layer Meteorology, 103(3): 409–438.

    Article  Google Scholar 

  • Rascle N, Ardhuin F. 2013. A global wave parameter database for geophysical applications. Part 2: model validation with improved source term parameterization. Ocean Modelling, 70: 174–188.

    Article  Google Scholar 

  • Ris R C, Holthuysen L H, Booij N. 1999. A third-generation wave model for coastal regions: 2. verification. Journal of Geophysical Research: Oceans, 104(C4): 7 667–7 681.

    Article  Google Scholar 

  • Roland A, Ardhuin F. 2014. On the developments of spectral wave models: numerics and parameterizations for the coastal ocean. Ocean Dynamics, 64(6): 833–846.

    Article  Google Scholar 

  • Rusu E, Pilar P, Guedes Soares C. 2008. Evaluation of the wave conditions in Madeira archipelago with spectral models. Ocean Engineering, 35(13): 1 357–1 371.

    Article  Google Scholar 

  • Siadatmousavi S M, Jose F, Stone G W. 2012. On the importance of high frequency tail in third generation wave models. Coastal Engineering, 60: 248–260.

    Article  Google Scholar 

  • Skamarock W C, Klemp J B, Dudhia J, Gill D O, Barker D M, Duda M G, Huang X Y, Wang W, Powers J G. 2008. A Description of the Advanced Research WRF Version 3. NCAR/TN-475+STR NCAR/TN-475+STR. National Center for Atmospheric Research, Boulder, Colorado, USA. p. 1–113.

    Google Scholar 

  • Smith S D, Banke E G. 1975. Variation of the sea surface drag coefficient with wind speed. Quarterly Journal of the Royal Meteorological Society, 101(429): 665–673.

    Article  Google Scholar 

  • Smith S D. 1988. Coefficients for sea surface wind stress, heat flux, and wind profiles as a function of wind speed and temperature. Journal of Geophysical Research: Oceans, 93(C12): 15 467–15 472.

    Article  Google Scholar 

  • Takagaki N, Komori S, Suzuki N, Iwano K, Kurose R. 2016. Mechanism of drag coefficient saturation at strong wind speeds. Geophysical Research Letters, 43(18): 9 829–9 835.

    Article  Google Scholar 

  • Taylor P K, Yelland M J. 2001. The dependence of sea surface roughness on the height and steepness of the waves. Journal of Physical Oceanography, 31(2): 572–590.

    Article  Google Scholar 

  • Tolman H L. 1992. Effects of numerics on the physics in a third-generation wind-wave model. Journal of Physical Oceanography, 22(10): 1 095–1 111.

    Article  Google Scholar 

  • Tsai Y S, Chang W T, Yu C M, Yang W C. 2018. General sea state and drag coefficient observed near shore in Taiwan Strait. Procedia IUTAM, 26: 204–213.

    Article  Google Scholar 

  • Vickers D, Mahrt L, Andreas E L. 2013. Estimates of the 10-m neutral sea surface drag coefficient from aircraft eddy-covariance measurements. Journal of Physical Oceanography, 43(2): 301–310.

    Article  Google Scholar 

  • WAMDI Group 1988. The WAM ModelA third gen-eration ocean wave prediction model. Journal of Physical Oceanography, 18(12): 1 775–1 810.

    Article  Google Scholar 

  • Wang Y, Jiang X W. 2012. Improvement and application of a saturation based wave dissipation function in SWAN model. Acta Oceanologica Sinica, 31(1): 24–32.

    Article  Google Scholar 

  • Wu J. 1982. Wind-stress coefficients over sea surface from breeze to hurricane. Journal of Geophysical Research: Oceans, 87(C12): 9 704–9 706.

    Article  Google Scholar 

  • Yan L. 1987. An Improved Wind Input Source Term for Third Generation Ocean Wave Modelling. Scientific Report WR-No87-8, KNMI, De Bilt, The Netherlands.

    Google Scholar 

  • Zhao D L, Li M X. 2018. Dependence of wind stress across an air-sea interface on wave states. Journal of Oceanography, 1–17. (in press)

  • Zijlema M, van der Westhuysen A J. 2005. On convergence behaviour and numerical accuracy in stationary SWAN simulations of nearshore wind wave spectra. Coastal Engineering, 52(3): 237–256.

    Article  Google Scholar 

  • Zijlema M, van Vledder G P, Holthuijsen L H. 2012. Bottom friction and wind drag for wave models. Coastal Engineering, 65: 19–26.

    Article  Google Scholar 

Download references

Acknowledgement

We thank Glenn Pennycook, MSc, from Liwen Bianji, Edanz Group China (http://www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.

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Authors and Affiliations

  1. Ocean University of China, Qingdao, 266100, China

    Zhifeng Wang, Yijie Gong, Junnan Cui, Sheng Dong & Kejian Wu

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  1. Zhifeng Wang
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  2. Yijie Gong
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  3. Junnan Cui
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  4. Sheng Dong
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  5. Kejian Wu
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Correspondence to Kejian Wu.

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Supported by the National Key Research and Development Program of China (No. 2016YFC1402000) and the National Natural Science Foundation of China (Nos. 51509226, 51779236)

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Wang, Z., Gong, Y., Cui, J. et al. Effect of the drag coefficient on a typhoon wave model. J. Ocean. Limnol. 37, 1795–1804 (2019). https://doi.org/10.1007/s00343-019-8228-4

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  • DOI: https://doi.org/10.1007/s00343-019-8228-4

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