Numerical simulation and preliminary analysis on ocean waves during Typhoon Nesat in South China Sea and adjacent areas

  • Jichao Wang (王际朝)
  • Jie Zhang (张杰)
  • Jungang Yang (杨俊钢)


Using the wave model WAVEWATCH III (WW3), we simulated the generation and propagation of typhoon waves in the South China Sea and adjacent areas during the passage of typhoon Nesat (2011). In the domain 100°–145°E and 0°–35°N, the model was forced by the cross-calibrated multi-platform (CCMP) wind fields of September 15 to October 5, 2011. We then validated the simulation results against wave radar data observed from an oil platform and altimeter data from the Jason-2 satellite. The simulated waves were characterized by five points along track using the Spectrum Integration Method (SIM) and the Spectrum Partitioning Method (SPM), by which wind sea and swell components of the 1D and 2D wave spectra are separated. There was reasonable agreement between the model results and observations, although the WW3 wave model may underestimate swell wave height. Significant wave heights are large along the typhoon track and are noticeably greater on the right of the track than on the left. Swells from the east are largely unable to enter the South China Sea because of the obstruction due to the Philippine Islands. During the initial stage and later period of the typhoon, swells at the five points were generated by the propagation of waves that were created by typhoons Haitang and Nalgae. Of the two methods, the 2D SPM method is more accurate than the 1D SIM which overestimates the separation frequency under low winds, but the SIM method is more convenient because it does not require wind speed and wave direction. When the typhoon left the area, the wind sea fractions decreased rapidly. Under similar wind conditions, the points located in the South China Sea are affected less than those points situated in the open sea because of the influence of the complex internal topography of the South China Sea. The results reveal the characteristic wind sea and swell features of the South China Sea and adjacent areas in response to typhoon Nesat, and provide a reference for swell forecasting and offshore structural designs.


typhoon WAVEWATCH III (WW3) cross-calibrated multi-platform (CCMP) South China Sea significant wave height swell 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Atlas R, Hoffman R A, Ardizzone J et al. 2011. A crosscalibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bulletin of American Meteorological Society, 92: 157–174.CrossRefGoogle Scholar
  2. Chao Y Y, Alves J-H G M, Tolman H L. 2005. An operational system for predicting hurricane-generated wind waves in North Atlantic Ocean. Weather and Forecasting, 20: 652–671.CrossRefGoogle Scholar
  3. Chu P C, Cheng K F. 2008. South China Sea wave characteristics during typhoon Muifa passage in winter 2004. Journal of Oceanography, 64: 1–21.CrossRefGoogle Scholar
  4. Chu P C, Qi Y Q, Chen Y C et al. 2004. South China Sea windwave characteristics. Part I: validation of WAVEWATCH III using TOPEX/Poseidon data. Journal of Atmospheric and Oceanic Technology, 21: 1 718–1 733.CrossRefGoogle Scholar
  5. Earle M D. 1984. Development of algorithms of wind sea and swell. National Data Buoy Center Tech. Rep. MEC-87-1. 53p.Google Scholar
  6. Feng X B, Zheng J H, Yan Y X. 2012. Wave spectra assimilation in typhoon wave modeling for East China Sea. Coastal Engineering, 69: 29–41.CrossRefGoogle Scholar
  7. Gerling T W. 1992. Partitioning sequences and arrays of directional wave spectra into component wave systems, Journal of Atmospheric and Oceanic Technology, 9: 444–558.CrossRefGoogle Scholar
  8. Guo Y Y, Hou Y J, Zhang C M, Yang J. 2012. A background error covariance model of significant wave height employing Monte Carlo simulation. Chinese Journal of Oceanology and Limnology, 30(5): 814–821.CrossRefGoogle Scholar
  9. Hanson J L, Phillips O M. 2001. Automated analysis of ocean surface directional wave spectra. Journal of Atmospheric and Oceanic Technology, 18: 277–293.CrossRefGoogle Scholar
  10. Hanson J L, Tracy B A, Tolman H L et al. 2009. Pacific hindcast of three numerical wave models. Journal of Atmospheric and Oceanic Technology, 26: 1 614–1 633.CrossRefGoogle Scholar
  11. Holthuijsen L H. 2007. Waves in Oceanic and Coastal Waters. Cambridge University Press, ISBN 0-521-86028-8. 387p.CrossRefGoogle Scholar
  12. Hwang P A. 2012. Wind sea and swell separation of 1D wave spectrum by a spectrum integration method. Journal of Atmospheric and Oceanic Technology, 29: 116–128.CrossRefGoogle Scholar
  13. Kumar B P, Stone G W. 2007. Numerical simulation of typhoon wind forcing in Korean seas using a spectral wave model. Journal of Coastal Research, 23(2): 362–373.CrossRefGoogle Scholar
  14. Moon I, Ginis I, Hara T et al. 2003. Numerical simulation of sea surface directional wave spectra under hurricane wind forcing. Journal of Physical Oceanography, 33: 1 680–1 706.CrossRefGoogle Scholar
  15. Portilla J F, Ocampo-Torres F J, Monbaliu J. 2009. Spectral partitioning and identification of wind sea and swell. Journal of Fluid Mechanical, 156: 505–531.Google Scholar
  16. Tolman H L, Alves J-H G M, Chao Y Y. 2005. Operational forecasting of wind-generated waves by hurricane Isabel at NCEP. Weather Forecast, 20: 544–557.CrossRefGoogle Scholar
  17. Tolman H L. 2009. User manual and system documentation of WAVEWATCH III version 3.14. Tech. Note 276, NOAA/NWS/NCEP/MMAB. 194p.Google Scholar
  18. Tracy B, Devaliere E, Hanson J et al. 2007. Wind sea and swell delineation for numerical wave modeling. 10th International Workshop on Wave Hindcasting and Forecasting Coastal Hazard Symposium. p.12.Google Scholar
  19. Voorrips A C, Makin V K, Hasselmann S. 1997. Assimilation of wave spectra from pitch-and-roll buoys in a North Sea wave model. Journal of Geophysical Research, 102: 5 829–5 849.CrossRefGoogle Scholar
  20. Wang D W, Hwang P A. 2001. An operational method for separating wind sea and swell from ocean wave spectra. Journal of Atmospheric and Oceanic Technology, 18: 2 052–2 062.CrossRefGoogle Scholar
  21. Xu F M, Perrie W, Zhang J L et al. 2005. Simulation of typhoon-driven waves in Yangtze waves in Yangtze Estuary with multiple-nested wave models. China Ocean Engineering, 19(4): 613–624.Google Scholar
  22. Zhao W, Guan S D, Hong X et al. 2011. Examination of windwave interaction source term in WAVEWATCH III with tropical cyclone wind forcing. Acta Oceanologica Sinica, 30(4): 1–13.CrossRefGoogle Scholar

Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jichao Wang (王际朝)
    • 1
    • 2
    • 4
  • Jie Zhang (张杰)
    • 3
  • Jungang Yang (杨俊钢)
    • 3
  1. 1.Institute of OceanologyChinese Academy of SciencesQingdaoChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.First Institute of OceanographyState Oceanic AdministrationQingdaoChina
  4. 4.College of ScienceChina University of PetroleumQingdaoChina

Personalised recommendations