郑桥¹, 张继才¹, 车助镁², 朱业²
1.浙江大学海洋学院物理海洋与遥感研究所, 浙江 舟山 316000;2.浙江省海洋监测预报中心, 浙江 杭州 310000

摘要:
本文选用第三代海浪模式SWAN （SimulatingWAveNearshore），以CCMP （Cross-Calibrated Multi-Platform）风场作为驱动风场，数值模拟了2015年3月份和2016年1月份影响浙江省的两次典型寒潮，并将模拟结果与实测数据进行了对比，模拟误差均在20%之内，属于可以接受的范围，表明SWAN模型和CCMP风场能够满足此次寒潮浪数值模拟的需要。本文从风场的强度、最值风速、风向、持续时间等方面，对比了两次寒潮期间的寒潮风场；从寒潮浪的强度、最值波高分布、持续时间、涌浪分布区域等方面，对两次典型寒潮期间的寒潮浪时空分布的异同进行了研究。总体而言，2015年3月份寒潮的风场从强度上弱于2016年1月份寒潮，3月份寒潮风场的主流大风是6~7级风，风向偏正北风；1月份寒潮风场的主流大风是6~8级风，风向偏西北风。2015年3月份的寒潮浪强度上弱于2016年1月份寒潮浪，3月份寒潮浪波高变化剧烈的区域位于研究区域的东北部，1月份寒潮浪波高变化剧烈的区域位于研究区域的中部和东部；3月份寒潮浪的大浪主要是5级浪，1月份寒潮浪的大浪主要是5、6级浪。当寒潮对研究区域的波浪场影响最为显著时，2015年3月份寒潮期间研究区域的北部多为涌浪，2016年1月份寒潮期间研究区域的南部多为涌浪。
关键词:SWAN模式|CCMP风场|寒潮浪|数值模拟|分布规律|对比研究
DOI：10.11759/hykx20181009001
分类号:P733
基金项目:国家重点研发计划（2017YFA0604100，2017YFC1404000）；国家自然科学基金项目（41876086）；浙江省海洋与渔业局资助项目（CTZB-F170918LWZ-SHYJC2）；中央高校基本科研业务费专项资金资助（2019QNA4052）

Numerical simulation of typical cold waves in seas adjacent to Zhejiang Province with examples from March 2015 and Jan-uary 2016
ZHENG Qiao¹, ZHANG Ji-cai¹, CHE Zhu-mei², ZHU Ye²
1.Institute of Physical Oceanography, Ocean College, Zhejiang University, Zhoushan 316000, China;2.The Ocean and Fisheries Bureau, Zhejiang Province, Hangzhou 310000, China
Abstract:
In this study, we used the third-generation wave simulation model SWAN (Simulating Waves Nearshore) tostudy the waves induced by cold fronts, and the CCMP (Cross-Calibrated Multi-Platform) wind field as the wind forcing field. We simulated two typical cold fronts that affected the seas adjacent to Zhejiang Province in March 2015 and January 2016, and then we compared the simulation results with the observation data.The error was controlled to within 20%, which iswithin the normal range and indicates that the SWAN model and CCMP can satisfy the requirementsfor numericallymodelling ocean waves caused by the cold fronts. We compared the wind fields in two typical cold-front eventswith respect to intensity, maximum wind speed, wind direction, and wind duration.In addition, we also compared the corresponding waves in two eventswith respect totheir intensity, maximum wave height, duration, and surge distribution. On the whole, we found the wind fields in the cold-front event during January 2016 to be stronger than thoseduring March 2015 event. The main wind speedsin March 2015 were of Grades 6-7 and theirprevailing direction was mainly north, whereasthe main wind speeds in January 2016 were Grades 6-8 and their prevailing direction was mainly northwest.The resulting wave intensity in January 2016 was stronger than that in March 2015. In March 2015, the wave height changed drastically in the northeast of the study region, whereas it did so in the middle and eastern parts of the study regionin January 2016.The largerwavesin the cold eventin March 2015were mainly Grade 5, whereasthe larger waves in January 2016were mainly in the range of Grades 5-6. We also studied the distribution of swell in these two cold events, and found that when the cold fronts had the most significant impact on the study region, the northernpart of the study region during March 2015 wasswell; on the contrary, the southernpart of the study region during January 2016 was swell.
Key words:SWAN modelCCMPcold-front wavesnumerical simulationdistributioncomparative study





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