基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究*

doi:10.11978/2024111

热带海洋学报 ›› 2025, Vol. 44 ›› Issue (2): 48-55.doi: 10.11978/2024111CSTR: 32234.14.2024111

基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究^*

任宇恒¹(), 高源¹(), 王运华¹, 孙建²

1.中国海洋大学信息科学与工程学部, 山东青岛 266100
2.中国海洋大学海洋与大气学院, 山东青岛 266100

收稿日期:2024-05-28 修回日期:2024-07-05 出版日期:2025-03-10 发布日期:2025-04-11
通讯作者: 高源
作者简介:
任宇恒(2002—), 男, 本科, 主要研究方向为海洋微波遥感。email: ryhopq@163.com
*感谢国家海洋卫星应用中心(https://osdds.nsoas.org.cn/)、欧洲中期天气预报中心(https://cds.climate.copernicus.eu)和美国国家飓风中心(https://www.nhc.noaa.gov/)提供数据支撑。
基金资助:
国家自然科学基金项目(42306196); 山东省自然科学基金项目(ZR2022QF069)

Data reconstruction of tropical cyclone significant wave height based on ocean wave spectrometer observations and reanalysis data^*

REN Yuheng¹(), GAO Yuan¹(), WANG Yunhua¹, SUN Jian²

1. Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
2. College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China

Received:2024-05-28 Revised:2024-07-05 Online:2025-03-10 Published:2025-04-11
Contact: GAO Yuan
Supported by:
National Natural Science Foundation of China(42306196); Natural Science Foundation of Shandong Province(ZR2022QF069)

摘要/Abstract

摘要：

有效波高数据是研究热带气旋海浪预测方法和反演技术的前提, 文章利用中法海洋卫星(China-France oceanography satellite, CFOSAT)波谱仪(surface waves investigation and monitoring, SWIM)高精度有效波高观测数据, 校正欧洲中期天气预报中心(European Center for Medium-range Weather Forecasts, ECMWF)第5代再分析资料(the fifth generation ECMWF reanalysis, ERA5)在高海况下低估有效波高的误差, 为构建高精度、大样本量的热带气旋海浪有效波高数据集提供了一种可靠方法。首先, 由于ERA5与SWIM数据存在时空分辨率差异, 文章利用经纬度变换和反距离加权法空间插值对两种数据进行时空匹配。然后, 通过数据对比得到了ERA5误差随SWIM有效波高增大而增大的相关关系, 进而使用线性回归方法构建了从ERA5到SWIM的有效波高重构方程。最后, 使用两处美国国家数据浮标中心(National Data Buoy Center, NDBC)浮标数据对重构方程进行了验证, 对于5m以上海浪, ERA5有效波高数据的均方根误差分别从重构前的1.65m和1.08m降低到重构后的1.18m和0.71m, 证明了重构方程的有效性。

关键词: 波谱仪, ERA5, 有效波高, 热带气旋

Abstract:

Data of significant wave heights (SWHs) is the basis of the investigations of tropical cyclone (TC) wave forecasting and retrieval technology. Based on the high-precision SWHs observed by the wave spectrometer of Surface Waves Investigation and Monitoring (SWIM) on board the China-France oceanography satellite (CFOSAT), this paper corrected the underestimation error of the SWHs under high sea state from the fifth generation reanalysis (ERA5) of European center for medium-range weather forecasts (ECMWF), providing a reliable support for the construction of a TC SWHs dataset with high accuracy and large sample quantity. Firstly, due to the temporal and spatial resolution differences between ERA5 and SWIM data, this paper utilized the latitude and longitude transformation and the inverse distance weighting method of spatial interpolation to match the two data spatially and temporally. Then, the correlation relationship that the ERA5 error increases with the increase of SWIM SWHs was obtained through data comparison. Based on this relationship, a reconstruction equation from ERA5 to SWIM was constructed using the linear regression method. Finally, the reconstruction equation was validated using the data from two (USA) National Data Buoy Center (NDBC) buoys. The results showed that for waves higher than 5 m, the Root Mean Square Error (RMSE) of the ERA5 SWHs reduced from 1.65 m and 1.08 m before the reconstruction to 1.18 m and 0.71 m after it, respectively, proving the effectiveness of the reconstruction equation.

Key words: wave spectrometer, ERA5, significant wave height, tropical cyclone

中图分类号:

P732.33

任宇恒, 高源, 王运华, 孙建. 基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究^*[J]. 热带海洋学报, 2025, 44(2): 48-55.

REN Yuheng, GAO Yuan, WANG Yunhua, SUN Jian. Data reconstruction of tropical cyclone significant wave height based on ocean wave spectrometer observations and reanalysis data^*[J]. Journal of Tropical Oceanography, 2025, 44(2): 48-55.

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参考文献 20

[1]	陈小燕, 杨劲松, 黄韦艮, 等, 2009. 多源卫星高度计有效波高数据融合方法研究[J]. 海洋学报, 31(4): 51-57.
	CHEN XIAOYAN, YANG JINSONG, HUANG WEIGEN, et al, 2009. Research on the fusion methods of significant wave height data from multisatellite altimeters[J]. Haiyang Xuebao, 31(4): 51-57 (in Chinese with English abstract).
[2]	储小青, 2011. 海浪波谱仪海浪遥感方法及应用基础研究[D]. 青岛: 中国科学院研究生院(海洋研究所).
	CHU XIAOQING, 2011. The algorithm and applied basic study on remote sensing of ocean wave spectrum for ocean wave spectrometer[D]. Qingdao: Institute of Oceanology, Chinese Academy of Sciences (in Chinese with English abstract).
[3]	李爱莲, 刘泽, 洪新, 等, 2021. 台风条件下ERA5再分析数据对中国近海适用性评估[J]. 海洋科学, 45(10): 71-80.
	LI AILIAN, LIU ZE, HONG XIN, et al, 2021. Applicability of the ERA5 reanalysis data to China adjacent Sea under typhoon condition[J]. Marine Sciences, 45(10): 71-80 (in Chinese with English abstract).
[4]	徐广珺, 杨劲松, 徐圆, 等, 2013. “海洋二号”有效波高数据在多源卫星高度计数据融合中的应用[J]. 海洋学报, 35(4): 208-213.
	XU GUANGJUN, YANG JINSONG, XU YUAN, et al, 2013. The data fusion of the significant wave height measured with “HY-2” satellite altimeter[J]. Haiyang Xuebao, 35(4): 208-213 (in Chinese with English abstract).
[5]	BRUNO M F, MOLFETTA M G, TOTARO V, et al, 2020. Performance assessment of era5 wave data in a swell dominated region[J]. Journal of Marine Science and Engineering, 8(3): 214.
[6]	CAIRES S, STERL A, 2005. A new nonparametric method to correct model data: application to significant wave height from the ERA-40 re-analysis[J]. Journal of Atmospheric and Oceanic Technology, 22(4): 443-459.
[7]	CHEN RUI, TOUMI R, SHI XINJIE, et al, 2023. An adaptive learning approach for tropical cyclone intensity correction[J]. Remote Sensing, 15(22): 5341.
[8]	COSTA M O, CAMPOS R M, SOARES C G, 2023. Enhancing the accuracy of metocean hindcasts with machine learning models[J]. Ocean Engineering, 287: 115724.
[9]	HAUSER D, TOURAIN C, HERMOZO L, et al, 2021. New observations from the SWIM radar on-board CFOSAT: instrument validation and ocean wave measurement assessment[J]. IEEE Transactions on Geoscience and Remote Sensing, 59(1): 5-26.
[10]	HERMOZO L, SUQUET R R, TOURAIN C, et al, 2022. CFOSAT: latest improvements in the swim products and contributions in oceanography[C]// Proceedings of 2022 IEEE international geoscience and remote sensing symposium. Kuala Lumpur, Malaysia: IEEE: 6768-6771.
[11]	HERSBACH H, BELL B, BERRISFORD P, et al, 2020. The ERA5 global reanalysis[J]. Quarterly Journal of the Royal Meteorological Society, 146(730): 1999-2049.
[12]	KUMAR V S, NASEEF T, 2015. Performance of ERA-interim wave data in the nearshore waters around India[J]. Journal of Atmospheric and Oceanic Technology, 32(6): 1257-1269.
[13]	LI BO, LI JUNMIN, LIU JUNLIANG, et al, 2022. Calibration experiments of CFOSAT wavelength in the Southern South China Sea by artificial neural networks[J]. Remote Sensing, 14(3): 773.
[14]	LI SONGLIN, YU HUAMING, WU KEJIAN, et al, 2023. Validation of the ocean wave spectrum from the remote sensing data of the Chinese-French oceanography satellite[J]. Remote Sensing, 15(16): 3918.
[15]	LI XIUZHONG, XU YING, LIU BAOCHANG, et al, 2021. Validation and calibration of nadir SWH products from CFOSAT and HY-2B with satellites and in situ observations[J]. Journal of Geophysical Research: Oceans, 126(2): e2020JC016689.
[16]	LIANG GUOZHOU, YANG JUNGANG, WANG JICHAO, 2021. Accuracy evaluation of CFOSAT SWIM L2 products based on NDBC Buoy and jason-3 altimeter data[J]. Remote Sensing, 13(5): 887.
[17]	LODISE J, MERRIFIELD S, COLLINS C, et al, 2024. Performance of ERA5 wind speed and significant wave height within extratropical cyclones using collocated satellite radar altimeter measurements[J]. Coastal Engineering Journal, 66(1): 89-114.
[18]	STOPA J E, CHEUNG K F, 2014. Intercomparison of wind and wave data from the ECMWF reanalysis interim and the NCEP climate forecast system reanalysis[J]. Ocean Modeling, 75: 65-83.
[19]	WANG JICHAO, WANG YUE, 2022. Evaluation of the ERA5 significant wave height against NDBC buoy data from 1979 to 2019[J]. Marine Geodesy, 45(2): 151-165.
[20]	ZHU XIAOLIN, CAI FANGYI, TIAN JIAQI, et al, 2018. Spatiotemporal fusion of multisource remote sensing data: literature survey, taxonomy, principles, applications, and future directions[J]. Remote Sensing, 10(4): 527.

验证参数	重构前	重构后
均方根误差/m	0.24	0.23
平均绝对误差/m	0.18	0.18
相关系数	0.94	0.94

验证参数	重构前	重构后
均方根误差/m	0.32	0.31
平均绝对误差/m	0.26	0.20
相关系数	0.95	0.96

验证参数	重构前	重构后
均方根误差/m	1.65	1.18
平均绝对误差/m	1.43	0.89
相关系数	0.72	0.91

验证参数	重构前	重构后
均方根误差/m	1.08	0.71
平均绝对误差/m	0.94	0.54
相关系数	0.78	0.90

基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究^*

Data reconstruction of tropical cyclone significant wave height based on ocean wave spectrometer observations and reanalysis data^*

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基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究*

Data reconstruction of tropical cyclone significant wave height based on ocean wave spectrometer observations and reanalysis data*

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基于波谱仪观测和再分析数据的热带气旋海浪有效波高数据重构研究^*

Data reconstruction of tropical cyclone significant wave height based on ocean wave spectrometer observations and reanalysis data^*