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

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


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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The altimeter data and the IOWAGA data are both from IFREMER ftp ( 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).


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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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