洋山港海域一次冷锋型温带风暴潮特征及各影响因子贡献的对比分析
徐杰(1985—), 男, 籍贯内蒙古, 硕士, 主要从事海洋气象预报研究。email: |
Copy editor: 姚衍桃
收稿日期: 2021-11-05
修回日期: 2021-12-28
网络出版日期: 2022-01-04
基金资助
国家重点研发计划项目(2019YFC1510105)
上海市气象局科技开发项目(MS202011)
Comparative study on the contribution of various influential factors and characteristics analysis of an extra-tropical storm surge caused by cold front in the Yangshan Port and its adjacent area
Copy editor: YAO Yantao
Received date: 2021-11-05
Revised date: 2021-12-28
Online published: 2022-01-04
Supported by
National Key Research and Development Program of China(2019YFC1510105)
Science and Technology Development Foundation of Shanghai Meteorological Bureau(MS202011)
本文研究了由2020年12月29日至31日强冷锋引起的影响洋山港海域的温带风暴潮过程。通过气象观测数据分析了其天气过程, 并利用FVCOM-SWAVE波浪-风暴潮耦合模式对该过程进行了高分辨率的数值模拟, 同时结合潮位站及浮标站观测数据对模拟结果进行了验证, 分析模拟了波浪、潮流、风暴增减水特征。结果发现, 该次冷锋型温带风暴潮过程主要表现为先短时风暴增水后出现长时间风暴减水的特征, 最大风暴减水可达65~70cm, 其主要诱因包括研究海域气压的快速升高并维持、长时间持续的偏北大风及波流相互作用。相关敏感试验研究了3种因子对风暴增减水位的贡献大小, 发现风暴增水峰值期间风场贡献占比约为90%, 海平面气压场约为5%; 风暴减水峰值期间, 海平面气压场的贡献度约占55%, 风场约占40%, 而波浪的贡献均不足10%。洋山港航道内风暴期间潮流流速最大可达到2.6~2.8m•s-1, 落潮时为东南向离岸潮流, 涨潮时为西至西北方向的外海潮波传入潮流; 洋山港航道潮流始终是东南或西北向, 此处流速辐合, 是洋山海域流速最高的区域。
关键词: FVCOM-SWAVE波浪-风暴潮耦合模型; 温带风暴潮; 洋山港海域
徐杰 , 过霁冰 , 陈智强 , 朱智慧 , 王琴 , 唐燕玲 . 洋山港海域一次冷锋型温带风暴潮特征及各影响因子贡献的对比分析[J]. 热带海洋学报, 2022 , 41(4) : 126 -135 . DOI: 10.11978/2021152
In this paper, an extra-tropical storm surge in the Yangshan Port (YSP) and its coastal area caused by a strong cold front on 29th December, 2020 was investigated. Meteorological observation data was analyzed to study the development of the weather system. FVCOM-SWAVE model characterized by a high-resolution unstructured-grid with 10 m was used to simulate the storm surge. The observed tide data, wave data and current data were introduced to verify the result of simulation, and the result was proved to be accurate and credible. Maximum storm surge, maximum negative storm surge, current, total water level and wave were studied to describe the character of the extra-tropical storm surge of YSP and its coastal area. Finally, sensitive experiments were carried out to compare the contributions of mean sea level pressure (SLP), wind and wave to the maximum storm surge. The main conclusions can be summarized as follows: 1) affected by the topography of the channel, the main component of the tidal current was southeast or northwest, which was approximately parallel to the shoreline, the current velocity in the deep water channel of YSP was the highest with a value between 2.6~2.8 m·s-1; 2) due to the influence of long term northerly gale and high SLP, the storm surge behave as a characteristics of short-term positive storm surge and long-term negative storm surge; 3) during the peak period of storm surge, the contribution of wind field to storm surge was ~ 90%, and the contribution of sea-level pressure field was approximately 5%; while during the peak period of negative storm surge, the contribution of sea-level pressure field was about 55%, the contribution of wind field was ~ 40%, In addition, the contribution of wave to both was less than 10%.
图1 海平面气压场分析a. 2020年12月29日0300UTC; b. 2020年12月29日1800UTC。蓝色等值线为等压线地面分析场(单位: hPa), 蓝色三角线段表示冷锋, 绿色数字表示降水量(单位: mm), 黑色符号代表天气现象; D代表低压, G代表高压。该图基于国家测绘地理信息局标准地图服务网站下载的审图号为GS(2016)1665的标准地图制作 Fig. 1 Weather maps at 0300UTC (a) and 1800UTC (b) on 29th December 2020 at sea level pressure |
图2 洋山站气象观测站点实况时序图横轴上的风向杆指向代表风的来向, 其长线代表风速4m•s-1, 短线代 Fig. 2 Time series of sea level pressure (solid, hPa), hourly wind gust (dash, m•s-1) and wind barb (long line represents the wind speed 4 m•s-1, short line represents 2 m•s-1, the flag represents 20 m•s-1) from the Yangshan observatory |
图4 模拟区的网格、水深和观测站点分布图a. 模拟区域网格分布; b. 模拟区域的水深分布; c. 洋山港海域网格分布; d. 洋山港海域水深分布。图中E为南港验潮站, F为东海大桥北浮标站, G为长江口灯船、H为海礁浮标位置, K为洋山气象观测站位置, B为航道研究点位置。该图基于国家测绘地理信息局标准地图服务网站下载的审图号为GS(2016)1665的标准地图制作 Fig. 4 Designed mesh and water depth for model domain (a, b), and real grid and water depth at the Yangshan port (c, d) |
表1 模型关键设置Tab. 1 Model parameter settings |
模型参数 | 参数配置 |
---|---|
网格范围 | 120°—123°18′E, 29°12′— 32°12′N |
分辨率 | 最大网格9km, 最小网格10m |
节点/单元 | 节点148375个, 三角形单元286204个 |
垂向分层 | 10层 |
积分时间 | 2020年12月24日0000UTC—2021年1月2日0000UTC |
FVCOM时间步长 | 内模2s, 外模0.2s, 时间分裂模比10 |
SWAVE时间步长 | 2s |
谱方向分辨率 | 10° |
边界海浪谱型 | JONSWAP |
边界径流 | 大通、富春江水文站径流量 |
边界水位 | TPXO模型模拟输出的M2、S2、K1、O1、N2、P1、Q1、K2 |
初始条件 | 冷启动(温度10℃; 盐度30‰) |
风场 | WARMS2.1数据集10m风场的U、V分量(水平分辨率9km) |
气压场 | WARMS2.1海平面气压数据 |
表2 敏感试验设计方案Tab. 2 Design details of sensitive experiments |
要素 | CASE0 | CASE1 | CASE2 | CASE3 | Control |
---|---|---|---|---|---|
潮位 | √ | √ | √ | √ | √ |
海平面气压场 | √ | √ | √ | ||
风场 | √ | √ | √ | ||
波浪 | √ |
注: “√”表示试验所需的输入场 |
图5 观测资料(点)与模式模拟值(线)对比的时间序列a. 南港潮位; b. 东海大桥北浮标流向; c. 东海大桥北浮标流速; d. 海礁浮标有效波高; e. 长江口灯船有效波高 Fig. 5 Time series of model results and observational data of the Nangang tide (a), current direction (b), current speed from the Donghai Bridge buoy (c), significant wave height from the Haijiao buoy (d) and Yangtze River Estuary observational boat (e) |
表3 模拟结果的Skill检验Tab. 3 Error analysis of Skill test |
站点 (要素) | 长江口灯船 (有效波高) | 海礁浮标 (有效波高) | 南港验潮站 (水位) | 东海大桥北浮标 (流向) | 东海大桥北浮标 (流速) |
---|---|---|---|---|---|
Skill值 | 0.97 | 0.98 | 0.95 | 0.92 | 0.90 |
表4 模拟结果的平均绝对误差和均方根误差Tab. 4 Mean absolute deviation and root mean square error |
站点 (要素) | 长江口灯船 (有效波高) | 海礁浮标 (有效波高) | 南港验潮站 (水位) | 东海大桥北浮标 (流向) | 东海大桥北浮标 (流速) |
---|---|---|---|---|---|
平均绝对误差 | 0.19m | 0.21m | 0.28m | 12.57° | 0.24m•s-1 |
均方根误差 | 0.23m | 0.25m | 0.34m | 17.18° | 0.30m•s-1 |
图7 洋山港及其附近海域2020年12月30日0120UTC(a)、0320UTC(b)、0900UTC(c)、1000UTC(d)的流场分布(箭头)及流速大小(填色)该图基于国家测绘地理信息局标准地图服务网站下载的审图号为GS(2016)1665的标准地图制作 Fig. 7 Current field of the Yangshan port and its adjacent area at (a)0120, (b)0320, (c)0900, (d)1000UTC on 30th December 2020, shaded part represents current speed |
[1] |
陈长胜, 2003. 海洋生态系统动力学与模型[M]. 北京: 高等教育出版社: 1-10.
|
[2] |
丁平兴, 葛建忠, 2013. 长江口横沙浅滩及邻近海域灾害性天气分析[J]. 华东师范大学学报(自然科学版), (4): 72-78.
|
[3] |
付元冲, 2016. 长江口沿海地区温带风暴潮预报模式的建立及应用[D]. 上海: 华东师范大学: 2-20.
|
[4] |
黄静, 2012. 沿海重要港口风暴潮灾害危险性研究——以上海洋山深水港为例[D]. 上海: 华东师范大学: 30-60.
|
[5] |
林小刚, 罗荣真, 张娟, 等, 2020. 浪流耦合对汕尾港台风风暴潮模拟的影响[J]. 海洋预报, 37(4): 30-37.
|
[6] |
罗志发, 黄本胜, 谭超, 等, 2021. 珠江河口波浪-风暴潮耦合数值模拟[J]. 广东水利水电, (7): 1-6, 17.
|
[7] |
宋德海, 鲍献文, 朱学明, 2009. 基于FVCOM的钦州湾三维潮流数值模拟[J]. 热带海洋学报, 28(2): 7-14.
|
[8] |
宋德海, 鲍献文, 张少峰, 等, 2012. 基于FVCOM的廉州湾及周边海域三维潮汐潮流数值模拟[J]. 海洋通报, 31(2): 136-145.
|
[9] |
唐燕玲, 徐卢笛, 贺治国, 等, 2019. 洋山海域三维潮流和余流特征的数值模拟[J]. 浙江大学学报(工学版), 53(2): 315-324.
|
[10] |
王喜年, 2005. 关于温带风暴潮[J]. 海洋预报, 22(S1): 17-23.
|
[11] |
吴修广, 刘光生, 程文龙, 2011. 基于FVCOM的杭州湾三维泥沙数值模拟[J]. 水利水运工程学报, (4): 86-96.
|
[12] |
徐秀芳, 戴建华, 尹红萍, 2009. 近20年影响上海的寒潮特点[J]. 大气科学研究与应用, (1): 73-80.
|
[13] |
张光宇, 2017. 渤海风暴潮特征及增水影响因素数值模拟研究[D]. 天津: 天津大学: 20-88.
|
[14] |
郑立松, 2010. 风暴潮-天文潮-波浪耦合模型及其在杭州湾的应用[D]. 北京: 清华大学: 30-99.
|
[15] |
朱婧, 叶龙彬, 陈德花, 等, 2020. 1614号台风“莫兰蒂”在厦门湾及其周边海域引发风暴潮的数值模拟[J]. 海洋预报, 37(6): 20-30.
|
[16] |
|
[17] |
|
[18] |
|
[19] |
|
[20] |
|
/
〈 | 〉 |