海洋环流与波动重点实验室知识库

风暴潮和海浪对山东半岛沿海海洋经济发展、居民人身安全以及海洋基础设施建设构成很大威胁。所以，研究风暴潮和海浪灾害对于提升海洋预报技术和提高海洋防灾减灾能力至关重要。本文针对山东半岛区域，对风暴潮过程进行模拟，并且评估了风暴增水以及海浪的危险性。主要研究内容及结果如下：

针对山东半岛区域，基于精细化的非结构三角形网格，建立了ADCIRC - SWAN耦合模式。针对耦合模式的输入风场模型Holland模型以及SWAN海浪模式的参数进行对比实验，并且采用各验潮站和浮标点的实测水位及波高数据，验证了耦合模式对于风暴潮、天文潮以及海浪模拟结果的准确性。

同时针对山东半岛沿岸进行敏感性实验，研究风暴增水、流场以及波高之间的相互影响。对9711台风和0703温带气旋的分析结果表明，在近岸区域，波浪效应主要表现为增水，且增水主要发生在波浪向岸传播区域；在考虑水位的情况下，有效波高的值是增加的；而流场对有效波高的影响很小。在远离海岸的区域，波浪效应的增减水很小；同样水位对波高的作用也较弱；流场对波高的影响大于水位的影响，当波向与流向夹角为锐角时，表现为波高减小，当波向与流向夹角为钝角时，表现为波高的增加，当二者垂直时，影响作用最小。

统计并采用耦合模式模拟了影响山东半岛的台风风暴潮和温带风暴潮过程，对风暴增水及海浪的危险性进行评估。对58次台风和110次温带气旋的研究结果表明，山东半岛沿岸台风浪危险性总体上南岸要大于北岸，而气旋浪危险性北岸大于南岸；风暴增水的危险性总体上北岸要大于南岸，环莱州湾沿岸附近的风暴增水危险性最高。

采用耦合模式进行了连续40年的模拟，对山东半岛沿岸海浪和风暴潮增水危险性进行评估。采用二元Gumbel逻辑模型计算风暴增水及其伴随波高的联合概率和联合重现期，评估了山东半岛两次温带风暴潮和两次台风风暴潮过程的风暴潮-海浪联合强度等级。结果表明，山东半岛沿岸风暴潮-海浪综合危险性整体上南北差异明显，北部沿岸的危险性要大于南部沿岸。温带风暴潮主要影响山东半岛北部地区，联合强度的确定以风暴增水为主导作用，而台风风暴潮更容易侵袭山东半岛南部地区，海浪对联合强度等级的决定作用更大。

Storm surges and waves pose a great threat to the coastal marine economic development of the Shandong Peninsula, the personal safety of residents and the construction of marine infrastructure. Therefore, studying the coupling effect of storm surge and ocean wave disasters is crucial for improving marine forecasting technology and improving marine disaster prevention and mitigation capabilities. In this paper, the storm surge process is simulated for the Shandong Peninsula region, and the hazard of storm surges and ocean waves is evaluated. The main research contents and results are as follows:

For the Shandong Peninsula region, based on the refined unstructured triangular mesh, an ADCIRC-SWAN coupling model is established. Comparing the parameters of the input wind field model Holland model of the coupled model and the SWAN wave model, it is verified that the combination of the Powell formula of the Holland parameter B and the Jiang formula of the maximum wind speed radius R has a better simulation effect in the research area of this paper. Meanwhile, the SWAN model wind input and whitecapping term and bottom friction term are determined as Komen scheme and JONSWAP method, respectively. In addition, the measured water level and wave height data of each tide station and buoy point are used to verify the accuracy of the coupled model for the simulation results of storm surge, astronomical tide and ocean waves.

At the same time, sensitivity experiments were carried out on the coast of Shandong Peninsula to study the interaction among storm surge, current field and wave height. The results show that in the nearshore area, the wave effect is mainly manifested as water increase, and the water increase caused by waves accounts for about 15% of the total storm surge. In the case of considering the water level, the value of the significant wave height is increased, and the significant wave height generated by the water level can reach 0.9-1.3 meters. The current field has little effect on the significant wave height. In the area far from the coast, the increase and decrease of the water level caused bu wave is very small; the effect of the water level on the wave height is also weak; the influence of the flow field on the wave height is greater than that of the water level. When the angle between the wave direction and the flow direction is an acute angle, the wave height is expressed as decrease. When the angle between the wave direction and the flow direction is an obtuse angle, the wave height increases, and when the two are perpendicular, the effect is minimal. Therefore, it is more reasonable and necessary to consider the interaction between storm surge and ocean waves for the numerical simulation of storm surge and ocean waves.

The process of typhoon storm surge and extratropical storm surge affecting Shandong Peninsula was counted and simulated by coupling model. Then, the hazard of storm surge and ocean waves was evaluated. The results show that extratropical cyclones occur all year round, mainly in spring and autumn, while typhoons only occur in summer. The events are sorted by storm surge and wave height. Among the top events with large storm surge and wave height, typhoon events account for about 40% on the south coast of Shandong Peninsula. On the north coast, typhoons account for only 20%. The hazard of waves along the coast of Shandong Peninsula is generally higher on the south coast than on the north coast, and the waves along the east coast of Weihai and Qingdao are the most dangerous. In general, the hazard of storm surge is greater on the north coast than on the south coast, and the risk of storm surge near the coast of Laizhou Bay is the highest.

The coupled model was used for 40 consecutive years of simulations to evaluate the hazard of waves and storm surges along the Shandong Peninsula. A binary Gumbel logistic model was used to calculate the joint probability and joint return period of storm surge and its accompanying wave heights, and to evaluate the combined storm surge and wave intensity levels of two extratropical storm surges and two typhoon storm surges in Shandong Peninsula. The results show that the comprehensive hazard of storm surge-wave is larger on the northern coast than on the southern coast. Hekou, Shouguang, Hanting, Changyi and northern Rongcheng are at the highest risk, with a hazard index above 0.8. The comparison of the distribution of storm surge-wave combined intensity grades in the two types of storm surge processes shows that the temperate storm surge mainly affects the northern part of the Shandong Peninsula, and the determination of the combined intensity is dominated by the stoem surge, while the southern part of the Shandong Peninsula is more prone to typhoon storm surges. And the wave height has a greater role in determining the joint strength level.

第1章 绪论... 1

1.1 研究背景与意义... 1

1.1.1 风暴潮简介... 3

1.1.2 海浪简介... 5

1.2 国内外研究现状... 6

1.2.1 风暴潮数值模式研究进展... 6

1.2.2 海浪数值模式研究进展... 7

1.2.3 风暴潮-海浪相互作用研究进展... 8

1.2.4 风暴潮和海浪危险性研究进展... 8

1.2.5 山东省风暴潮和海浪灾害研究进展... 9

1.3 本文主要研究内容... 11

第2章 耦合数值模式构建与验证... 13

2.1 数值模式介绍... 13

2.1.1 风场模型... 13

2.1.2 SWAN模式... 14

2.1.3 ADCIRC模式... 15

2.1.4 ADCIRC-SWAN耦合模式... 17

2.2 数据介绍... 18

2.3 模式参数及配置... 20

2.3.1 Holland风场模型参数... 20

2.3.2 SWAN模式参数... 27

2.3.3 耦合模式参数设置... 30

2.3.4 耦合模式网格建立... 31

2.4 耦合数值模式验证... 32

2.4.1 天文潮验证... 32

2.4.2 风暴潮增水验证... 34

2.4.3海浪有效波高验证... 37

2.5本章小结... 38

第3章 风暴潮-海浪相互作用特征机理研究... 40

3.1典型过程风暴潮和海浪分布特征... 41

3.2敏感性实验设置... 44

3.3风暴潮和海浪的相互作用... 45

3.3.1波浪对增水的影响... 45

3.3.2 水位对波高的影响... 50

3.3.3 流场对波高的影响... 53

3.4 本章小结... 55

第4章 台风和温带气旋下海浪和风暴潮的危险性评估... 56

4.1 台风及温带气旋统计特征... 56

4.1.1 时空分布... 56

4.1.2 台风风暴潮和温带风暴潮强度对比... 60

4.1.3 典型风暴潮过程对比... 63

4.2 海浪及增水分布特征... 65

4.2.1 台风风场和海浪场空间分布特征... 65

4.2.2 山东半岛沿岸海浪分布特征... 68

4.2.3 山东半岛沿岸风暴增水分布特征... 72

4.3 危险性评估方法... 75

4.3.1 海浪和风暴潮强度等级划分... 75

4.3.2 海浪和风暴潮危险性指数计算... 76

4.4 海浪和风暴潮危险性评估... 77

4.4.1 海浪危险性分布... 77

4.4.2 风暴潮危险性分布... 82

4.5 本章小结... 86

第5章 基于长期连续模拟的风暴潮-海浪综合危险性评估... 87

5.1 数据及网格调整... 88

5.2 重现期计算... 89

5.2.1 风暴增水重现期计算... 89

5.2.2 风暴增水-海浪联合重现期计算... 92

5.3 风暴潮-海浪综合危险性评估... 95

5.3.1 风暴潮-海浪综合危险性计算方法... 95

5.3.2 风暴潮-海浪综合危险性分布... 95

5.4 单过程风暴潮-海浪联合危险性评估... 99

5.4.1 风暴潮-海浪联合强度等级划分... 99

5.4.2 典型过程风暴潮-海浪联合危险性评估... 99

5.5 极端过程的危险性... 104

5.6 本章小结... 105

第6章 结论与未来工作展望... 107

6.1 结论... 107

6.2 未来工作展望... 108

参考文献... 110

致 谢... 117

作者简历及攻读学位期间发表的学术论文与研究成果... 119