基于WAM6-GPU海浪模式的中国近海区域海浪预报精度评估-海洋预报

基于WAM6-GPU海浪模式的中国近海区域海浪预报精度评估

单位：1. 卫星海洋环境监测预警全国重点实验室(国家海洋环境预报中心), 北京 100086;
2. 自然资源部海洋灾害预报技术重点实验室, 北京 100086;
3. 中科星图维天信科技股份有限公司, 北京 100094

分类号：P731.33

出版年·卷·期（页码）：2026·43·第三期（7-19）

摘要：

利用中国近海的浮标观测数据，验证评估了基于WAM6-GPU海浪模式构建的西北太平洋海浪数值预报系统在中国近海的预报精度。结果表明：系统对中国近海的有效波高具有较好的预报精度，24 h平均绝对误差为0.25 m，均方根误差为0.38 m；有效波高预报误差随预报时效延长而增大，系统在高海况条件下的预报结果存在显著高估现象；有效波高预报误差存在时空差异，空间上表现为黄渤海预报误差最小，南海次之，东海误差相对较大；时间上表现为夏季预报误差相对较大。针对台风浪预报，系统可以准确预报出由台风过程引发的有效波高的变化过程，但对台风导致的有效波高数值存在明显高估，这一偏差主要是由驱动风场中台风路径与强度存在较大误差导致的。

This study evaluates wave forecast accuracy over China's offshore areas from a Northwest Pacific wave numerical prediction system based on the WAM6-GPU wave model against buoy observation data. Results demonstrate that the system exhibits a good forecast performance for significant wave height(SWH) in China's coastal seas: the 24-hour forecast has a mean absolute error of 0.25 m and a root mean square error of 0.38 m. The SWH forecast error increases with the prolongation of the forecast time, and the system tends to significantly overestimate the SWH under high sea conditions. Furthermore, the SWH forecast error displays notable spatiotemporal variations. Spatially, the error is smallest in the Bohai Sea and Yellow Sea, followed by the South China Sea, and relatively larger in the East China Sea. Temporally, forecast errors are higher in summer. For the forecast of typhoon waves, the system can accurately predict the changes in effective wave height caused by the typhoon process, but with significant overestimation. This is mainly due to the considerable errors in the typhoon track and intensity in the wind forcing.

参考文献：

[1] 吕睿,徐瑞,王娟娟,等.中国近海2023年灾害性海浪分析及2024年预测[J].海洋预报, 2025, 42(2):39-45.LYU R, XU R, WANG J J, et al. Disastrous wave of China seas in 2023 and prediction for 2024[J]. Marine Forecasts, 2025, 42(2):39-45.
[2] 王华,姚圣康,龚茂珣,等.东海区域灾害性海浪长期预测方法研究[J].海洋通报, 2007, 26(5):35-42.WANG H, YAO S K, GONG M X, et al. Study on the long-term predicting way of disastrous sea wave of East China Sea[J]. Marine Science Bulletin, 2007, 26(5):35-42.
[3] 刘凡,陆小敏,徐丹,等.海浪预报方法研究进展[J].河海大学学报(自然科学版), 2021, 49(5):387-393.LIU F, LU X M, XU D, et al. Research progress of ocean waves forecasting method[J]. Journal of Hohai University(Natural Sciences), 2021, 49(5):387-393.
[4] 袁业立,潘增弟,华锋,等. LAGFD-WAM海浪数值模式Ⅰ:基本物理模型[J].海洋学报, 1992, 14(5):1-7.YUAN Y L, PAN Z D, HUA F, et al. LAGFD-WAM ocean wave numerical model Ⅰ:basic physical model[J]. Acta Oceanologica Sinica, 1992, 14(5):1-7.
[5] TOLMAN H L, BALASUBRAMANIYAN B, BURROUGHS L D,et al. Development and implementation of wind-generated ocean surface wave modelsat NCEP[J]. Weather and Forecasting, 2002,17(2):311-333.
[6] BOOIJ N, RIS R C, HOLTHUIJSEN L H. A third-generation wave model for coastal regions:1. Model description and validation[J].Journal of Geophysical Research:Oceans, 1999, 104(C4):7649-7666.
[7] 张永垂,陈诗尧,王宁,等.全球业务化海洋预报系统进展[J].地球科学进展, 2022, 37(4):344-357.ZHANG Y C, CHEN S Y, WANG N, et al. Progress of global operational ocean forecasting systems[J]. Advances in Earth Science, 2022, 37(4):344-357.
[8] FENG B Y, WANG Z Y, ZHANG Y, et al. Numerical simulation of the northwest pacific based on the MaCOM[J]. Journal of Physics:Conference Series, 2024, 2718(1):012029.
[9] 曹赛超,高志一,赵栋梁. WAVEWATCH Ⅲ第三代海浪数值模式在中国东海的应用和改进[J].中国海洋大学学报, 2023, 53(8):8-15.CAO S C, GAO Z Y, ZHAO D L. Application and improvement of WAVEWATCH Ⅲ third generation wave numerical model in the East China Sea[J]. Periodical of Ocean University of China, 2023,53(8):8-15.
[10] QIAO F L, SONG Z Y, BAO Y, et al. Development and evaluation of an Earth System Model with surface gravity waves[J]. Journal of Geophysical Research:Oceans, 2013, 118(9):4514-4524.
[11] SANDHYA K G, BALAKRISHNAN NAIR T M, BHASKARAN P K, et al. Wave forecasting system for operational use and its validation at coastal Puducherry, east coast of India[J]. Ocean Engineering, 2014, 80:64-72.
[12] CAMPOS R M, GUEDES SOARES C. Comparison and assessment of three wave hindcasts in the North Atlantic Ocean[J].Journal of Operational Oceanography, 2016, 9(1):26-44.
[13] UMESH P A, PARVATHY K G, FERNANDEZ D R, et al. Global sea state prediction using OSCAT winds:a statistical assessment of WAM and WWIII hindcasts with NDBC-NOAA buoys and satellite altimeter data[J]. Pure and Applied Geophysics, 2023, 180(1):509-549.
[14] 周媛媛,周林,关皓,等.基于Jason-1和Jason-2卫星资料的中国东部海域海浪模拟结果的检验[J].海洋预报, 2018, 35(6):40-47.ZHOU Y Y, ZHOU L, GUAN H, et al. Verification of wave simulation results based on Jason-1 and Jason-2 data in the East China Sea[J]. Marine Forecasts, 2018, 35(6):40-47.
[15] 梁颖瑜,徐丽丽,徐婷婷,等.常规海浪预报定量化检验评估方法研究[J].海洋预报, 2024, 41(1):10-20.LIANG Y Y, XU L L, XU T T, et al. Study on quantitative test and evaluation method of conventional sea wave forecasts[J].Marine Forecasts, 2024, 41(1):10-20.
[16] 陈雅雅,邹仲水,赵栋梁.基于SWAN模式的台风浪数值模拟初步研究[J].海洋湖沼通报, 2017(6):1-10.CHEN Y Y, ZOU Z S, ZHAO D L. A preliminary study of typhoon wave based on numerical simulationsusing SWAN model[J]. Transactions of Oceanology and Limnology, 2017(6):1-10.
[17] 谢明炎,魏立新,高元勇,等.球面质心泰森多边形网格海浪预报的向量化检验方法[J].海洋预报, 2024, 41(2):34-43.XIE M Y, WEI L X, GAO Y Y, et al. Vectorized verification method for Spherical Centroid Voronoi Tessellation grid ocean wave forecasting[J]. Marine Forecasts, 2024, 41(2):34-43.
[18] OWENS J D, HOUSTON M, LUEBKE D, et al. GPU computing[J]. Proceedings of the IEEE, 2008, 96(5):879-899.
[19] 孙家文,朱桐,房克照,等.基于GPU加速的Boussinesq类波浪传播变形数值模型[J].海洋工程, 2020, 38(2):111-119.SUN J W, ZHU T, FANG K Z, et al. A GPU accelerated Boussinesq wave propagation model[J]. The Ocean Engineering,2020, 38(2):111-119.
[20] LOU Q, WU C M, DONG C M, et al. APPLE-MASNUM:accelerating parallel processing for lightweight expansion of MASNUM on a single multi-GPU node[J]. Ocean Modelling,2025, 196:102557.
[21] YUAN Y, YU F J, CHEN Z, et al. Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0[J]. Geoscientific Model Development,2024, 17(16):6123-6136.
[22] WANG Y N, LI B T, ZHOU W, et al. Parallel Princeton Ocean model based on OpenACC[J]. Environmental Modelling&Software, 2025, 187:106370.
[23] IKUYAJOLU O J, VAN ROEKEL L, BRUS S R, et al. Porting the WAVEWATCH III(v6.07)wave action source terms to GPU[J].Geoscientific Model Development, 2023, 16(4):1445-1458.
[24] GROUP T W. The WAM model-a third generation ocean wave prediction model[J]. Journal of Physical Oceanography, 1988, 18(12):1775-1810.
[25] MACFERRIN M, AMANTE C, CARIGNAN K, et al. The Earth Topography 2022(ETOPO 2022)global DEM dataset[J]. Earth System Science Data, 2025, 17(5):1835-1849.
[26] 刘艳贵,徐瑞,侯放,等.福建省海浪灾害危险性评估[J].海洋预报, 2024, 41(1):21-30.LIU Y G, XU R, HOU F, et al. Hazard assessment of wave disasters in Fujian Province[J]. Marine Forecasts, 2024, 41(1):21-30.
[27] HERSBACH H, BELL B, BERRISFORD P, et al. The ERA5global reanalysis[J]. Quarterly Journal of the Royal Meteorological Society, 2020, 146(730):1999-2049.
[28] 尹汉军,谢波涛,黄必桂,等.渤海中部海浪的同步观测与数值预报检验[J].海岸工程, 2023, 42(2):131-139.YIN H J, XIE B T, HUANG B G, et al. Synchronous observation and numerical forecast product test of ocean waves in the Central Bohai Sea[J]. Coastal Engineering, 2023, 42(2):131-139.
[29] 武双全.东中国海波高分布特征研究[D].青岛:中国海洋大学,2010.WU S Q. The distributional character of the wave height in the East China Sea[D]. Qingdao:Ocean University of China, 2010.
[30] 国家市场监督管理总局,国家标准化管理委员会. GB/T 42176-2022海浪等级[S].北京:中国标准出版社, 2022.State Administration for Market Regulation, National Standardization Administration. GB/T 42176-2022 The grade of wave height[S]. Beijing:Standards Press of China, 2022.
[31] 李文博,李锐,王彬,等.不同海浪数值预报产品在渤海和黄海的预报水平评估[J].海洋预报, 2023, 40(4):10-21.LI W B, LI R, WANG B, et al. Evaluation of different wave numerical forecast products in the Bohai Sea and the Yellow Sea[J]. Marine Forecasts, 2023, 40(4):10-21.
[32] CHEN S, JIANG W Z, XUE Y H, et al. A new wave-state-based drag coefficient parameterization for coastal regions[J]. Journal of Physical Oceanography, 2024, 54(3):809-821.

服务与反馈：

【文章下载】【发表评论】【查看评论】【加入收藏】