粤西陆架温度锋三维结构与季节变化机制分析

谭可易; 谢玲玲; 李明明; 李敏; 李君益

doi:10.12284/hyxb2023053

粤西陆架温度锋三维结构与季节变化机制分析

doi: 10.12284/hyxb2023053

谭可易^{1, 2},
谢玲玲^{1, 2, 3},
李明明^{1, 2, 3, ,},
李敏^{1, 2, 3},
李君益^{1, 2, 3}

1.
广东海洋大学海洋与气象学院近海海洋变化与灾害预警实验室，广东湛江 524088
2.
陆架及深远海气候资源与环境广东省高等学校重点实验室，广东湛江 524088
3.
自然资源部空间海洋遥感与应用重点实验室，北京 100081

基金项目: 国家自然科学基金面上项目（42276019）。

详细信息

作者简介:
谭可易（1994—），女，广西壮族自治区贵港市人，博士研究生，主要从事海洋中小尺度过程研究。E-mail：tkyddd@163.com

通讯作者:
李明明（1984—），女，山东省泰安市人，博士，讲师，主要从事海洋混合和近岸动力过程的研究。E-mail：limm@gdou.edu.cn

中图分类号: P731
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出版历程
- 收稿日期: 2022-09-29
- 修回日期: 2022-12-20
- 网络出版日期: 2023-11-09
- 刊出日期: 2023-10-30

3D structure and seasonal variation of temperature fronts in the shelf sea west of Guangdong

Tan Keyi^{1, 2},
Xie Lingling^{1, 2, 3},
Li Mingming^{1, 2, 3
, ,},
Li Min^{1, 2, 3},
Li Junyi^{1, 2, 3}

1.
Laboratory of Coastal Ocean Variation and Disaster Prediction, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China
2.
Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Ocean, Zhanjiang 524088, China
3.
Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China

摘要

摘要: 基于2018–2019年现场高分辨率温度观测和1993–2021年的CMEMS再分析海表温度（SST）和风场数据，分析粤西陆架海温盐锋的三维结构、季节变化和影响机制。多年SST数据显示，海表温度锋冬季最强、出现概率和覆盖宽度最大，量值分别为0.049℃/km、75%和66 km。春季和夏季次之，而秋季则几乎完全消失。冬季锋面平均离岸50 km，夏季则向岸靠近为23.1 km。2018年春季、夏季和2019年夏季的现场观测进一步给出锋面在次表层的三维结构，结果显示春、夏季20 m等深线以浅处均有锋面存在，该锋面是沿岸高温海水与离岸低温海水辐聚而成，随着深度的增加锋面强度减小，覆盖范围向岸收缩。20 m以深水域锋面在次表层中强于表层，随深度增加而增强并向岸偏移。相关性和信息流分析发现，海表面风应力旋度和沿岸风是影响粤西陆架海表温度锋面的重要因素。该温度锋存在年际变化，PDO负位相时的La Niña年锋面强度出现极大值，而PDO正位相时的El Niño年则对应极小值。
- 海洋锋 /
- 季节分布 /
- 三维结构 /
- 信息流 /
- 粤西陆架
Abstract: Using reanalysis sea surface data and in-situ high-resolution observations in spring, summer 2018, and summer 2019, this study analyzes the 3D structure and seasonal variation of temperature fronts in the shelf sea west of Guangdong. The results show that the sea surface temperature (SST) fronts reach the strongest intensity up to 0.049°C/km in winter, with the largest occurrence probability of 75% and coverage of 66 km. The SST fronts weaken in spring and summer, and almost disappear in autumn. The average offshore distance of the front is 50 km in winter and 23.1 km in summer. The in-situ observations show a strong thermal front in coastal areas shallower than 20 m in both spring and summer. The front gets weaker and closer to the coast in deeper layers and is associated with warm coastal water and cold shelf water. In shelf areas deeper than 20 m, the fronts in the subsurface layer are stronger than in the surface layer and shift shoreward in deeper layers. The correlation coefficient and information flow between the surface wind and frontal parameters reveal that the surface wind stress curl and along-coast wind are the most important factors affecting the surface thermal front. These thermal fronts also have interannual variations, with maximum intensity in La Niña years with negative PDO and minimum intensity in El Niño years with positive PDO.
- ocean front /
- seasonal variation /
- 3D structure /
- information flow /
- shelf west of Guangdong

HTML全文

图 1 粤西陆架地形及2018和2019年观测站位分布

所有实心点为2018年观测站位，黑色实心点为2019年观测站位（红色点在2019年未观测）

Fig. 1 Bathymetry and observation stations on the shelf west of Guangdong in 2018 and 2019

All dots represent stations of which all are in 2018 and the black ones are in 2019 (the red dots were not observed in 2019)

下载: 全尺寸图片幻灯片

图 2 海表面温度梯度的季节分布

a. 冬天；b. 春天；c. 夏天；d. 秋天。灰色等值线为水深，蓝色箭头为海面10 m风矢量

Fig. 2 Seasonal distribution of sea surface temperature gradient

a. Winter; b. spring; c. summer; d. autumn. Gray isolines represent the unter depth and blue arrows represent the wind vectors of 10 m on the sea surface

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图 3 锋面出现概率的季节分布

a. 冬天；b. 春天；c. 夏天；d. 秋天。灰色等值线为水深，蓝色箭头为海面10 m风矢量，洋红色实线为锋面中心线

Fig. 3 Seasonal distribution of mean occurrence probabilities of the front at the sea surface

a. Winter; b. spring; c. summer; d. autumn. Gray isolines represent the unter depth and blue arrows represent the wind vectors of 10 m on the sea surface. The solid magenta line is the centerline of the front

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图 4 锋面指数I的季节分布

a. 冬天；b. 春天；c. 夏天；d. 秋天。灰色等值线为水深，蓝色箭头为海面10 m风矢量，洋红色实线为锋面中心线

Fig. 4 Seasonal distribution of front index I at the sea surface

a. Winter; b. spring; c. summer; d. autumn. Gray isolines represent the unter depth and blue arrows represent the surface wind vectors of 10 m on the sea surface. The solid magenta line is the centerline of the front

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图 5 归一化后的5个锋面参量的月平均分布（a）、锋面参量的归一化FFT频率谱（b）和时间平均后锋面强度的FFT空间波数谱（c）

Fig. 5 Normalized monthly average distribution of the five frontal covariates (a), normalized FFT frequency spectrum of frontal covariates (b), omnidirectional time-average FFT spectra of frontal intensity (c)

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图 6 现场观测航次期间平均CMEMS再分析SST和ECWMF再分析风场分布

a. 2018年春季；b. 2018年夏季；c. 2019年夏季。黑色实心点为站位，白色箭头为海面风矢量

Fig. 6 Sea surface temperature (SST) from CMEMS reanalysis data and sea surface wind field from ECWMF reanalysis data during the cruise observations

a. Spring 2018; b. summer 2018; c. summer 2019. The black dots represent stations, and the white arrows represent the surface wind vectors

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图 7 2018年春季（a, d, g）、2018年夏季（b, e, h）和2019年夏季（c, f, i）观测温度水平分布

a–c为2 m，d–f为8 m，g–i为12 m。蓝色实线和灰色实线分别为海岸线和等深线

Fig. 7 Horizontal distribution of temperature in spring 2018 (a, d, g) , summer 2018 (b, e, h), and summer 2019 (c, f, i)

a–c at 2 m, d–f at 8 m, and g–i at 12 m. The blue and gray solid lines represent the coastline and isobaths, respectively

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图 8 2018年春季（a, d, g）、2018年夏季（b, e, h）和2019年夏季（c, f, i）观测温度水平梯度分布

a–c为2 m，d–f 为8 m，g–i为12 m。蓝色实线和灰色实线分别为海岸线和等深线

Fig. 8 Horizontal distribution of temperature gradient in spring 2018 (a, d, g) , summer 2018 (b, e, h), and summer 2019 (c, f, i)

a–c at 2 m, d–f at 8 m, and g–i at 12 m. The blue and gray solid lines represent the coastline and isobaths, respectively

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图 9 2018年春季（a, d）、夏季（b, e）和2019年夏季（c, f）C断面的温度（a–c），及温度梯度（d–f）垂直分布

Fig. 9 Vertical distribution of temperature (a–c) and gradient of temperature (d–f) at Section C in spring (a, d), summer 2018 (b, e), and summer 2019 (c, f)

下载: 全尺寸图片幻灯片

图 10 1993–2021年月平均序列

虚线为原始月平均时间序列，实线为13个月低通滤波后的时间序列

Fig. 10 Time series of monthly-mean in 1993−2021

The dashed line is the original monthly-mean time series, and the solid line is the 13-month low-pass filtered time series

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图 11 1993–2021年锋面强度（a）、NINO3指数（b）、 PDO指数（c）的时间序列

红色框为El Niño + PDO正位相，蓝色框为La Niña + PDO负位相

Fig. 11 Time series of frontal intensity (a), NINO3 index (b), and PDO index (c) in 1993–2021

Red boxes are El Niño + positive phase of PDO, and blue boxes are La Niña + negative phase of PDO

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图 12 1993–2021年ENSO事件发生期间的SST分布

a. 1997–1998年El Niño；b. 2009–2010年El Niño；c. 2015–2016年El Niño；d. 2018–2019年El Niño；e. 1999–2000年La Niña；f. 2007–2008年La Niña；g. 2010–2011年La Niña；h. 2020–2021年La Niña。白色箭头为表面流速，黑色箭头为海上10 m风矢量，黑色实心点位置为锋面位置

Fig. 12 Distribution of SST during the 1993–2021 ENSO events

a. 1997–1998 El Niño; b. 2009–2010 El Niño; c. 2015–2016 El Niño; d. 2018–2019 El Niño; e. 1999–2000 La Niña; f. 2007–2008 La Niña; g. 2010–2011 La Niña; h. 2020–2021 La Niña. White arrows are surface currents, black arrows are offshore 10 m wind vector and the black solid dot position is the frontal areas

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表 1 锋面参量与风参量的相关系数

Tab. 1 Correlation coefficient between frontal parameters and wind parameters

	沿岸风应力总体（冬，夏）	向岸风应力总体（冬，夏）	风应力旋度总体（冬，夏）	风应力散度总体（冬，夏）	沿岸流总体（冬，夏）
锋面强度	0.45^(0.54*, 0.50)	0.25^(0.55*, 0.15)	0.47^*(0.57, 0.3)	0.37^(0.13*, 0.52)	0.42^* (0.66, 0.56)
出现概率	0.42^(0.67*, 0.51)	0.1(0.29, 0.1)	0.32^(0.65*, 0.43)	0.32^(0.15*, 0.46)	0.25^* (0.59, 0.56)
覆盖宽度	0.52^(0.55*, 0.58)	0.35^(0.45*, 0.03)	0.51^(0.54*, 0.47)	0.32^(0.51*, 0.53)	0.13(0.62, 0.51)
离岸距离	0.38^(0.60*, 0.53)	–0.55^(–0.5*, 0.24)	0.2^(0.36*, 0.42)	0.2^(0.33*, 0.1)	0.1(0.26, 0.22)
注：*表示相关系数通过95%的置信度检验，括号内分别为冬季（斜体）和夏季的相关系数。

下载: 导出CSV

表 2 锋面参量和风参量的信息流计算结果

Tab. 2 Information flow calculation results between frontal parameters and wind parameters

	锋面强度	出现概率	覆盖宽度	离岸距离	沿岸风	向岸风	风应力旋度
锋面强度	–	–	–	–	0.1	0.03	0.28
出现概率	–	–	–	–	0.12	–0.002	0.14
覆盖宽度	–	–	–	–	0.1	0.05	0.23
离岸距离	–	–	–	–	0.22	0.29	0.09
沿岸风	–0.045	–0.017	–0.02	–0.08	–	–	–
向岸风	–0.03	–0.002	–0.05	0.008	–	–	–
风应力旋度	–0.14	–0.1	–0.12	–0.11	–	–	–
注：表中“–”为相同变量之间的结果，无意义。

下载: 导出CSV

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