南海主要分潮振幅变化趋势再探

于茜; 潘海东; 吕咸青

doi:10.12284/hyxb2022083

南海主要分潮振幅变化趋势再探

doi: 10.12284/hyxb2022083

于茜^1,,
潘海东^{2, 3, 4, 5, ,},
吕咸青^{1, 5}

1.
中国海洋大学物理海洋学教育部重点实验室, 山东青岛 266100
2.
自然资源部第一海洋研究所, 山东青岛 266061
3.
自然资源部海洋环境科学与数值模拟重点实验室, 山东青岛 266061
4.
山东省海洋环境科学与数值模拟重点实验室, 山东青岛 266061
5.
青岛海洋科学与技术试点国家实验室区域海洋动力学与数值模拟功能实验室, 山东青岛 266237

基金项目: 国家重点研发计划(2019YFC1408405)；国家自然科学基金（42076011）；青岛市博士后应用研究项目。

详细信息

作者简介:
于茜（1996-），女，山东省烟台市人，主要从事潮汐非平稳变化研究。E-mail: yuqian@stu.ouc.edu.cn

通讯作者:
潘海东，博士，博士后科研人员，主要从事潮汐非平稳变化研究。E-mail：panhaidong_phd@qq.com

中图分类号: P722.4
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出版历程
- 收稿日期: 2021-07-18
- 修回日期: 2021-11-23
- 网络出版日期: 2022-03-25
- 刊出日期: 2022-06-15

The study of the trends of tidal amplitudes of major constituents in the South China Sea: A revisit

Yu Qian^1
,,
Pan Haidong^{2, 3, 4, 5
, ,},
Lü Xianqing^{1, 5}

1.
Key Laboratory of Physical Oceanography, Ministry of Education, Ocean University of China, Qingdao 266100, China
2.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
3.
Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China
4.
Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China
5.
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China

摘要

摘要: 潮汐变化研究对于沿海地区海洋工程、洪涝灾害预防和海洋资源开发利用等各方面都有着非常重要的意义。之前的潮汐变化研究主要基于多年逐时验潮站观测，而验潮站数据无论是站点的个数还是站点的位置，都存在很大的局限性，这对我们研究海盆尺度的潮汐变化规律形成了一定程度的阻碍。前人基于25年的T/P-Jason卫星高度计数据发现南海中央深海海盆主要分潮振幅存在异常大的趋势，这是由于中尺度海洋运动对潮汐调和分析干扰导致的虚假结果。本文首次使用了X-TRACK软件处理过的长达27年的T/P-Jason卫星高度计观测来研究整个南海的主要分潮振幅的长期趋势。经过X-TRACK处理后的卫星观测数据在整个南海的准确性和完整性都有了显著的提升。同时，我们使用了权重最小二乘法来消除长周期采样导致的潮汐混淆的影响。我们发现在南海大部分海域，4大主要分潮的振幅都存在显著的变化趋势。振幅和迟角变化的极值主要分布在吕宋海峡西部、马六甲海峡和台湾海峡等水深和岸线变化剧烈的近海海域，振幅最大的上升趋势可达2.75 mm/a，振幅最大的下降趋势可达–2.16 mm/a。南海主要分潮振幅的长期趋势与河流径流以及人类活动密切相关。
- 南海 /
- 潮汐长期趋势 /
- X-TRACK /
- 卫星高度计 /
- S_TIDE
Abstract: The research of tidal changes is vital to ocean engineering, the protection of flooding as well as the utilization of ocean resources in coastal areas. Previous studies are mainly based on long-term hourly tide gauges whose number and location are highly limited. Previous study indicated that the long-term trends of tidal amplitudes are abnormally large in the central deep basin of the South China Sea (SCS) based on 25-year satellite altimeter data, which is not realistic and the resultant of the interference of ocean mesoscale variability on tidal harmonic analysis. In this paper, we use 27-year T/P-Jason satellite altimeter data processed by X-TRACK software to study the long-term tidal trends in the SCS. The satellite altimeter data processed by X-TRACK obviously improves the accuracy and completeness of satellite data in the SCS. Meanwhile, the weighted least square method is used to eliminate the effect of tidal aliasing caused by long period sampling. We find that in most areas of the SCS, the amplitudes of four major tidal constituents have significant long-term trends. The significant positive and negative long-term trends of amplitudes and phases are mainly distributed in the coastal areas such as the western Luzon Strait, the Strait of Malacca and Taiwan Strait, where the water depth and shoreline change dramatically. The largest positive long-term trend of amplitudes can reach 2.75 mm/a and the largest negative long-term trend of amplitudes can reach −2.16 mm/a. The long-term trends of tidal amplitudes in the SCS should be related to river flow and human interference.
- South China Sea /
- the long-term trend of tides /
- X-TRACK /
- satellite altimeter /
- S_TIDE

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图 1 南海RADS数据沿轨缺测百分比（a）和X-TRACK数据沿轨缺测百分比（b）

Fig. 1 Percentage of passes with missing RADS data (a) and percentage of passes with missing X-TRACK data (b) in the South China Sea

下载: 全尺寸图片幻灯片

图 2 南海M₂分潮振幅线性趋势

a. 空间分布图；b. 直方图

Fig. 2 The linear trends of M₂ amplitudes in the South China Sea

a. Spatial pattern; b. histogram

下载: 全尺寸图片幻灯片

图 5 南海O₁分潮振幅线性趋势

a. 空间分布图；b. 直方图

Fig. 5 The linear trends of O₁ amplitudes in the South China Sea

a. Spatial pattern; b. histogram

下载: 全尺寸图片幻灯片

图 6 南海中尺度校正后4大分潮振幅趋势极值的空间分布

Fig. 6 Spatial distribution of the extreme trend of four tidal amplitudes after mesoscale correction in the South China Sea

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图 3 南海S₂分潮振幅线性趋势

a. 空间分布图；b. 直方图

Fig. 3 The linear trends of S₂ amplitudes in the South China Sea

a. Spatial pattern; b. histogram

下载: 全尺寸图片幻灯片

图 4 南海K₁分潮振幅线性趋势

a. 空间分布图；b. 直方图

Fig. 4 The linear trends of K₁ amplitudes in the South China Sea

a. Spatial pattern; b. histogram

下载: 全尺寸图片幻灯片

表 1 S_TIDE分辨的分潮的基本信息

Tab. 1 Tidal constituents resolved in S_TIDE

分潮	杜德森数						频率/h⁻¹
M_n	0	0	0	0	1	0	0.000 006 129
Sa	0	0	1	0	0	–1	0.000 114 074
Ssa	0	0	2	0	0	0	0.000 228 159
M_f	0	2	0	0	0	0	0.003 050 092
Q_1n	1	–2	0	1	–1	0	0.037 212 374
Q₁	1	–2	0	1	0	0	0.037 218 503
O_1n	1	–1	0	0	–1	0	0.038 724 526
O₁	1	–1	0	0	0	0	0.038 730 654
P₁	1	1	–2	0	0	0	0.041 552 587
K₁	1	1	0	0	0	0	0.041 780 746
K_1n	1	1	0	0	1	0	0.041 786 875
J₁	1	2	0	–1	0	0	0.043 292 898
N₂	2	–1	0	1	0	0	0.078 999 249
M_2n	2	0	0	0	–1	0	0.080 505 272
M₂	2	0	0	0	0	0	0.080 511 401
S₂	2	2	–2	0	0	0	0.083 333 333
K₂	2	2	0	0	0	0	0.083 561 492
K_2n	2	2	0	0	1	0	0.083 567 624
M₄	4	0	0	0	0	0	0.161 022 801

下载: 导出CSV

表 2 从T/P-Jason卫星高度计观测得到的南海主要分潮振幅的长期趋势统计结果

Tab. 2 The long-term trends of major constituents in the South China Sea obtained from T/P-Jason satellite altimeter data

分潮	趋势不显著的观测点百分比/%	上升趋势的观测点百分比/%	下降趋势的观测点百分比/%	所有观测点趋势平均值 /(mm·a⁻¹)	所有观测点趋势最大值 /(mm·a⁻¹)	所有观测点趋势最小值 /(mm·a⁻¹)
M₂	19.07	37.60	40.96	0.05	2.20	–1.23
S₂	17.39	52.00	30.61	0.12	2.44	–1.63
K₁	19.92	40.75	39.33	0.01	2.75	–2.16
O₁	20.71	36.53	42.76	–0.05	1.48	–2.15

下载: 导出CSV

表 3 从T/P-Jason卫星高度计观测得到的南海主要分潮的迟角长期趋势统计结果

Tab. 3 The long-term trends of major tidal constituents’ phase in the South China Sea obtained from T/P-Jason satellite altimeter data

分潮	趋势不显著的观测点百分比/%	上升趋势的观测点百分比/%	下降趋势的观测点百分比/%	所有观测点趋势最小值/（（°）·a⁻¹）	所有观测点趋势平均值/（（°）·a⁻¹）	所有观测点趋势最大值/（（°）·a⁻¹）	趋势最大值出现区域	趋势最小值出现区域
M₂	45.32	32.69	21.99	−0.92	0.04	1.01	新加坡东部	泰国湾
S₂	25.89	43.88	30.23	−17.71	0.18	6.38	新加坡东部	新加坡东部
K₁	44.82	24.64	30.51	−10.76	−10.01	0.58	泰国湾	泰国湾
O₁	53.90	19.26	26.84	−10.70	0.002	3.53	马六甲海峡	马六甲海峡

下载: 导出CSV

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