Study on Separation Method for one-dimensional wind-sea and swell under different dominant wave conditions

Wei Yongliang; Pang Denglian; Gao zhiyi; Tang Zeyan

doi:10.12284/hyxb2025057

Article Contents

Article Navigation > Haiyang Xuebao > 2025 >

Wei Yongliang，Pang Denglian，Gao zhiyi, et al. Study on Separation Method for one-dimensional wind-sea and swell under different dominant wave conditions[J]. Haiyang Xuebao，2025, 47(6)：1–12 doi: 10.12284/hyxb2025057

Citation:

PDF( 2141 KB)

Study on Separation Method for one-dimensional wind-sea and swell under different dominant wave conditions

doi: 10.12284/hyxb2025057

1.
College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China
2.
National Marine Environmental Forecasting Center, Beijing 100081, China
3.
East China Sea Development Research Center, Ministry of Natural Resources, Shanghai 201306, China

Received Date: 2024-09-23
Rev Recd Date: 2025-04-22

Available Online: 2025-05-26

Abstract

Abstract

Mixed waves in the ocean typically consist of wind waves and swell in varying proportions. Due to research and application needs, it is often necessary to separate the wind waves from the swell. This paper focuses on four existing representative one-dimensional spectral wind-sea separation methods (1D methods): the PM method (Pierson-Moskowitz), the improved PM method, the JP method (Jesús-Portilla), and the spectral integral method. Using two-dimensional wave spectrum data provided by the spectrometer onboard the China-France Oceanography Satellite, a comparative analysis of the separation results under four wave-dominant conditions—pure wind waves, wind wave-dominant, swell-dominant, and pure swell—was conducted. The results show that: (1) The PM method and the improved PM method perform better under wind wave-dominant and swell-dominant conditions, respectively. (2) The JP method performs poorly overall and is insensitive to different wave-dominant conditions; the spectral integral method performs better when wind waves dominate. (3) As the proportion of swell in mixed waves increases, appropriately increasing the frequency ratio coefficient in the PM method can improve separation accuracy. Based on this, a piecewise PM method is proposed, which adjusts the frequency ratio coefficient. Under wind wave-dominant and swell-dominant conditions, using coefficients of 1.03 and 1.1, respectively, results in more accurate separation.
- wave-dominant conditions,
- wind-sea and swell separation,
- China-France Oceanography SATellite,
- wave spectrum

FullText(HTML)

References(20)

References

[1]	冯士筰, 李凤歧, 李少菁. 海洋科学导论[M]. 北京: 高等教育出版社, 1999: 198. Feng Shizuo, Li Fengqi, Li Shaojing. An Introduction to Marine Science[M]. Beijing: Higher Education Press, 1999: 198.
[2]	周延东, 雷震名, 孙国民, 等. 涌浪基本理论研究综述[J]. 水道港口, 2016, 37(1): 1−6. doi: 10.3969/j.issn.1005-8443.2016.01.001 Zhou Yandong, Lei Zhenming, Sun Guomin, et al. A review on basic theory research of swell[J]. Journal of Waterway and Harbor, 2016, 37(1): 1−6. doi: 10.3969/j.issn.1005-8443.2016.01.001
[3]	汪炳祥, 常瑞芳, 王一飞. 风浪与涌浪的划分判据[J]. 黄渤海海洋, 1990, 8(1): 16−24. Wang Bingxiang, Chang Ruifang, Wang Yifei. Criteria of differentiating swell from wind waves[J]. Journal of Oceanography of Huanghai & Bohai Seas, 1990, 8(1): 16−24.
[4]	郭佩芳, 施平, 王华, 等. 划分风浪与涌浪的一个新判据——海浪成份及其在南海的应用[J]. 青岛海洋大学学报, 1997, 27(2): 131−137. Guo Peifang, Shi Ping, Wang Hua, et al. A new criterion between wind wave and swell wave —by mixed wave composition factors and its application to the south China sea[J]. Journal of Ocean University of Qingdao, 1997, 27(2): 131−137.
[5]	郭佩芳, 施平, 王华, 等. 混合浪成分及其在西北太平洋海域的应用[J]. 海洋湖沼通报, 1996(3): 1−6. Guo Peifang, Shi Ping, Wang Hua, et al. Wave composition and its application on north-western pacific[J]. Transactions of Oceanology and Limnology, 1996(3): 1−6.
[6]	Hanley K E, Belcher S E, Sullivan P P. A global climatology of wind–wave interaction[J]. Journal of Physical Oceanography, 2010, 40(6): 1263−1282. doi: 10.1175/2010JPO4377.1
[7]	Earle M D. Development of algorithms for separation of sea and swell[J]. National Data Buoy Center Tech Rep MEC-87-1, Hancock County, 1984, 53: 1−53.
[8]	李水清, 赵栋梁. 风浪和涌浪分离方法的比较[J]. 海洋学报, 2012, 34(2): 23−29 Li Shuiqing, Zhao Dongliang. Comparisons on partitioning techniques to identify wind-wave and swell[J]. Haiyang Xuebao, 2012, 34(2): 23−29
[9]	Wang D W, Hwang P A. An operational method for separating wind sea and swell from ocean wave spectra[J]. Journal of Atmospheric and Oceanic Technology, 2001, 18(12): 2052−2062. doi: 10.1175/1520-0426(2001)018<2052:AOMFSW>2.0.CO;2
[10]	Hwang P A, Ocampo-Torres F J, García-Nava H. Wind sea and swell separation of 1D wave spectrum by a spectrum integration method[J]. Journal of Atmospheric and Oceanic Technology, 2012, 29(1): 116−128. doi: 10.1175/JTECH-D-11-00075.1
[11]	Portilla J, Ocampo-Torres F J, Monbaliu J. Spectral partitioning and identification of wind sea and swell[J]. Journal of Atmospheric and Oceanic Technology, 2009, 26(1): 107−122. doi: 10.1175/2008JTECHO609.1
[12]	林伊楠, 陶爱峰, 李雪丁, 等. 台湾海峡风涌浪分离方法研究[J]. 海洋学报, 2019, 41(11): 25−34. doi: 10.3969/j.issn.0253-4193.2019.11.004 Lin Yinan, Tao Aifeng, Li Xueding, et al. Study on separation method of wind-wave and swell in the Taiwan Strait[J]. Haiyang Xuebao, 2019, 41(11): 25−34. doi: 10.3969/j.issn.0253-4193.2019.11.004
[13]	Liu Yan, Hao Zengzhou, Gong Fang, et al. Spectral separation of wind sea and swell based on buoy observations[C]//Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015. Toulouse: SPIE, 2015, 9638: 185−197.
[14]	Tison C, Hauser D. SWIM products users guide[R]. Toulouse: CNES, 2019. CF-GSFR-MU-2530-CNES.
[15]	Jiang Haoyu, Song Yuhao, Mironov A, et al. Accurate mean wave period from SWIM instrument on-board CFOSAT[J]. Remote Sensing of Environment, 2022, 280: 113149. doi: 10.1016/j.rse.2022.113149
[16]	Xu Ying, Hauser D, Liu Jiangqiang, et al. Statistical comparison of ocean wave directional spectra derived from SWIM/CFOSAT satellite observations and from buoy observations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1−20.
[17]	Aouf L, Dalphinet A, Hauser D, et al. On the assimilation of CFOSAT wave data in the wave model MFWAM: Verification phase[C]//IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium. Yokohama: IEEE, 2019: 7959−7961.
[18]	Jiang Haoyu, Mironov A, Ren Lin, et al. Validation of wave spectral partitions from SWIM instrument on-board CFOSAT against in situ data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 60: 1−13.
[19]	文圣常, 余宙文. 海浪理论与计算原理[M]. 北京: 科学出版社, 1984: 135. Wen Shengchang, Yu Zhouwen. Hailang lilun yu jisuan yuanli[M]. Beijing: Science Press, 1984: 135. (查阅网上资料, 未找到本条文献的英文信息, 请确认)
[20]	Hanson J L, Phillips O M. Automated analysis of ocean surface directional wave spectra[J]. Journal of Atmospheric and Oceanic Technology, 2001, 18(2): 277−293. doi: 10.1175/1520-0426(2001)018<0277:AAOOSD>2.0.CO;2