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Climatology of Wind-Seas and Swells in the China Seas from Wave Hindcast

  • Chengcheng Qian
  • Haoyu JiangEmail author
  • Xuan Wang
  • Ge Chen
Article
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Abstract

The wind-sea and swell climates in the China Seas are investigated by using the 27-yr Integrated Ocean Waves for Geophysical and other Applications (IOWAGA) hindcast data. A comparison is made between the significant wave height from the IOWAGA hindcasts and that from a jointly calibrated altimetry dataset, showing the good performance of the IOWAGA hindcasts in the China Seas. A simple but practical method of diagnosing whether the sea state is wind-sea-dominant or swell-dominant is proposed based on spectral partitioning. Different from the characteristics of wind-seas and swells in the open ocean, the wave fields in the enclosed seas such as the China Seas are predominated by wind-sea events in respect of both frequencies of occurrences and energy weights, due to the island sheltering and limited fetches. The energy weights of wind-seas in a given location is usually more significant than the occurrence probability of wind-sea-dominated events, as the wave energy is higher in the wind-sea events than in the swell events on average and extreme wave heights are mostly related to wind-seas. The most energetic swells in the China Seas (and other enclosed seas) are ‘local swells’, having just propagated out of their generation areas. However, the swells coming from the West Pacific also play an important role in the wave climate of the China Seas, which can only be revealed by partitioning different swell systems in the wave spectra as the energy of them is significantly less than the ‘local swells’.

Key words

the China Seas wind-sea swell wave climate WAVEWATCH III 

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Notes

Acknowledgements

The altimeter data and the IOWAGA data are both from IFREMER ftp (ftp.ifremer.fr). This work is jointly supported by the National Key R&D Program of China (No. 2017YFC1404700), the National Natural Science Foundation of China (No. 41806010), Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology (No. 2019A03), the Discipline Layout Project for Basic Research of Shenzhen Science and Technology Innovation Committee (No. 20170418), and the Guangdong Special Fund Program for Marine Economy Development (No. GDME-2018E001).

References

  1. Ardhuin, F., Chapron, B., and Collard, F., 2009. Observation of swell dissipation across oceans. Geophysical Research Letters, 36: L06607, DOI:  https://doi.org/10.1029/2008GL037030.CrossRefGoogle Scholar
  2. Ardhuin, F., Rogers, E., Babanin, A., Filipot, J., Magne, R., Roland, A., Van der Westhuysen, A., Queffeulou, P., Lefevre, J., Aouf, L., and Collard, F., 2010. Semi-empirical dissipation source functions for ocean wave. Part I: Definition, cali-bration and validation. Journal of Physical Oceanography, 40: 1917–1941.CrossRefGoogle Scholar
  3. Babanin, A. V., and Jiang, H., 2017. Ocean swell, how much do we know. Processing 36th International Conference on Ocean, Offshore and Arctic Engineering, Trondheim, DOI:  https://doi.org/10.1115/OMAE2017-61692.Google Scholar
  4. Chen, G., Chapron, B., Ezraty, R., and Vandemark, D., 2002. A global view of swell and wind sea climate in the ocean by satellite altimeter and scatterometer. Journal of Atmospheric and Oceanic Technology, 19: 1849–1859.CrossRefGoogle Scholar
  5. Delpey, M. T., Ardhuin, F., Collard, F., and Chapron, B., 2010. Space-time structure of long ocean swell fields. Journal of Geophysical Research, 115: C12037, DOI:  https://doi.org/10.1029/2009JC005885.CrossRefGoogle Scholar
  6. Drennan, W. M., Graber, H. C., Hauser, D., and Quentin, C., 2003. On the wave age dependence of wind stress over pure wind seas. Journal of Geophysical Research, 108: 8062, DOI:  https://doi.org/10.1029/2000JC000715.CrossRefGoogle Scholar
  7. Fan, Y., Lin, S., Griffies, S., and Hemer, M., 2014. Simulated global swell and wind-sea climate and their responses to anthropogenic climate change at the end of the twenty-first century. Journal of Climate, 27: 3516–3536.CrossRefGoogle Scholar
  8. Gulev, S. K., and Grigorieva, V., 2006. Variability of the winter wind waves and swell in the North Atlantic and North Pacific as revealed by the voluntary observing ship data. Journal of Climate, 19: 5667–5685.CrossRefGoogle Scholar
  9. Gulev, S. K., Grigorieva, V., Sterl, A., and Woolf, D., 2003. Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data. Journal of Geophysical Research, 108: 3236–3236.Google Scholar
  10. Hanley, K. E., Belcher, S. E., and Sullivan, P. P., 2010. A global climatology of wind-wave interaction. Journal of Physical Oceanography, 40: 1263–1282.CrossRefGoogle Scholar
  11. Hanson, J. L., and Phillips, O. M., 2001. Automated analysis of ocean surface directional wave spectra. Journal of Atmospheric and Oceanic Technology, 18: 277–293.CrossRefGoogle Scholar
  12. He, H., and Xu, Y., 2016. Wind-wave hindcast in the Yellow Sea and the Bohai Sea from the year 1988 to 2002. Acta Oceanologica Sinica, 35: 46–53.CrossRefGoogle Scholar
  13. He, H., Song, J., Bai, Y., Xu, Y., Wang, J., and Bi, F., 2018. Climate and extrema of ocean waves in the East China Sea. Science China–Earth Sciences, 61 (7): 980–994, DOI:  https://doi.org/10.1007/s11430-017-9156-7.CrossRefGoogle Scholar
  14. Huang, Y., Yin, B., William, P., and Hou, Y., 2008. Responses of summertime extreme wave heights to local climate variations in the East China Sea. Journal of Geophysical Research, 113: C09031, DOI:  https://doi.org/10.1029/2008JC004732.Google Scholar
  15. Janssen, P. A. E. M., 1989. Wave-induced stress and the drag of air flow over sea waves. Journal of Physical Oceanography, 19: 745–754.CrossRefGoogle Scholar
  16. Jiang, H., and Chen, G., 2013. A global view on the swell and wind sea climate by Jason-1 mission: A revisit. Journal of Atmospheric and Oceanic Technology, 30: 1833–1841.CrossRefGoogle Scholar
  17. Jiang, H., Mouche, A., Wang, H., Babanin, A. V., Chapron, B., and Chen, G., 2017. Limitation of SAR quasi-linear inversion data on swell climate: An example of global crossing swells. Remote Sensing, 9 (2): 107, DOI:  https://doi.org/10.3390/rs9020107.
  18. Jiang, H., Stopa, J. E., Wang, H., Husson, R., Mouche, A., Chapron, B., and Chen, G., 2016. Tracking the attenuation and nonbreaking dissipation of swells using altimeters. Journal of Geophysical Research: Oceans, 121: 1446–1458, DOI:  https://doi.org/10.1002/2015JC011536.Google Scholar
  19. Kinsman, B., 1965. Wind Wave. Prentice-Hall, New Jersey, 1–676.Google Scholar
  20. Li, J., Chen, Y., and Pan, S., 2016. Modelling of extreme wave climate in China Seas. Journal of Coastal Research, 32: 522–526.CrossRefGoogle Scholar
  21. Liang, B., Liu, X., Li, H., Wu, Y., and Lee, D., 2016. Wave climate hindcasts for the Bohai Sea, Yellow Sea, and East China Sea. Journal of Coastal Research, 32: 172–180.Google Scholar
  22. Pierson, W. J., 1991. Comment on ‘effects of sea maturity on satellite altimeter measurements’ by Roman E. Glazman and Stuart H. Pilorz. Journal of Geophysical Research, 96: 4973–4977.CrossRefGoogle Scholar
  23. Queffeulou, P., Ardhuin, F., and Lefèvre, J. M., 2011. Wave height measurements from altimeters: Validation status and applications. OSTST Meeting, Ocean Surface Topography Science Team. San Diego, 19–21.Google Scholar
  24. Rascle, N., and 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.CrossRefGoogle Scholar
  25. Semedo, A., Sušelj, K., Rutgersson, A., and Sterl, A., 2011. A global view on the wind sea and swell climate and variability from ERA-40. Journal of Climate, 24: 1461–1479.CrossRefGoogle Scholar
  26. Semedo, A., Vettor, R., Breivik, Ø., Sterl, A., Reistad, M., and Lima, D., 2015. The wind sea and swell waves climate in the Nordic Seas. Ocean Dynamics, 65: 233–240, DOI:  https://doi.org/10.1007/s10236-014-0788-4.CrossRefGoogle Scholar
  27. Stopa, J. E., Ardhuin, F., Bababin, A. V., and Zieger, S., 2016a. Comparison and validation of physical wave parameterizations in spectral wave models. Ocean Modelling, 103: 2–17, DOI:  https://doi.org/10.1016/j.ocemod.2015.09.003.CrossRefGoogle Scholar
  28. Stopa, J. E., Ardhuin, F., Husson, R., Jiang, H., Chapron, B., and Collard, F., 2016b. Swell dissipation from 10 years of Envisat advanced synthetic aperture radar in wave mode. Geophysical Research Letters, 43 (7): 3423–3430.CrossRefGoogle Scholar
  29. Tolman, H. L., and the WAVEWATCH III® Development Group, 2014. User manual and system documentation of WAVEWATCH III® version 4.18. Technical Note 316. NOAA/NWS/NCEP/MMAB, U. S. Department of Commerce, National Oceanic and Atmospheric Administration, College Park, Md, 1–282.Google Scholar
  30. Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Van De Berg, L., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., McNally, A. P., Mahfouf, J. F., Morcrette, J. J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J., 2005. The ERA-40 re-analysis. Quarterly Journal of the Royal Meteorological Society, 131: 2961–3012.CrossRefGoogle Scholar
  31. Wan, Y., Zhang, J., Meng, J., and Wang, J., 2015. A wave energy resource assessment in the China’s seas based on multisatellite merged radar altimeter data. Acta Oceanologica Sinica, 34: 115–124.CrossRefGoogle Scholar
  32. Young, I. R., Babanin, A. V., and Zieger, S., 2013. The decay rate of ocean swell observed by altimeter. Journal of Physical Oceanography, 43: 2322–2333.CrossRefGoogle Scholar
  33. Young, I. R., Sanina, E., and Babanin, A. V., 2017. Calibration and cross validation of a global wind and wave database of altimeter, radiometer, and scatterometer measurements. Journal of Atmospheric and Oceanic Technology, 34 (6): 1285–1306, DOI:  https://doi.org/10.1175/JTECH-D-16-0145.1.CrossRefGoogle Scholar
  34. Zheng, C., Pan, J., and Li, J., 2013. Assessing the China Sea wind energy and wave energy resources from 1988 to 2009. Ocean Engineering, 65: 39–48.CrossRefGoogle Scholar
  35. Zheng, C., Zhuang, H., Li, X., and Li, X., 2012. Wind energy and wave energy resources assessment in the East China Sea and South China Sea. Science China–Technological Sciences, 55: 163–173.CrossRefGoogle Scholar
  36. Zieger, S., Vinoth, J., and Young, I. R., 2009. Joint calibration of multiplatform altimeter measurements of wind speed and wave height over the past 20 Years. Journal of Atmospheric and Oceanic Technology, 26: 2549–2564.CrossRefGoogle Scholar

Copyright information

© Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2020

Authors and Affiliations

  • Chengcheng Qian
    • 1
    • 2
    • 3
  • Haoyu Jiang
    • 2
    • 4
    Email author
  • Xuan Wang
    • 5
  • Ge Chen
    • 2
    • 3
  1. 1.North China Sea Marine Forecasting Center of State Oceanic AdministrationQingdaoChina
  2. 2.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.College of Information Science and EngineeringOcean University of ChinaQingdaoChina
  4. 4.College of Marine Science and TechnologyChina University of GeosciencesWuhanChina
  5. 5.College of Ocean Science and EngineeringShanghai Maritime UniversityShanghaiChina

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