基于温跃层温度异常对登陆华东及华南地区热带气旋频数的预测研究

郑嵘; 刘春雷; 吴胜安; 曹宁; 金梁; 鲍瑞娟; 廖晓晴; 陈海亮; 杨可; 苏千叶; 梁志婷

doi:10.16032/j.issn.1004-4965.2026.018

基于温跃层温度异常对登陆华东及华南地区热带气旋频数的预测研究

doi: 10.16032/j.issn.1004-4965.2026.018

郑嵘^{1, 2, 3, 4},
刘春雷^{1, 2, 3, 4},
吴胜安^4, ,,
曹宁^{1, 2, 3},
金梁^{5, 6},
鲍瑞娟⁷,
廖晓晴^{1, 8},
陈海亮⁹,
杨可^{1, 2, 3},
苏千叶^{1, 2, 3},
梁志婷^{1, 2, 3}

1.
广东海洋大学海洋与气象学院，广东湛江 524088
2.
中国气象局广东海洋大学海洋气象联合实验室，广东湛江 524088
3.
广东海洋大学南海海洋气象研究院，广东湛江 524088
4.
海南省南海气象防灾减灾重点实验室，海南海口 570203
5.
温岭市气象局，浙江温岭 317500
6.
台州市台风海洋气象重点实验室，浙江台州 318000
7.
福建省灾害天气重点实验室，福建福州 350028
8.
中山大学海洋科学学院，广东珠海 519082
9.
湛江市气象局，广东湛江 510080

基金项目:

海南省南海气象防灾减灾重点实验室开放基金 SCSF202405

中国国家自然科学基金 42075036

中国国家自然科学基金 42275017

中国国家自然科学基金 72293604

中国国家自然科学基金 42130605

广东海洋大学研究生教育创新项目 202532

详细信息

通讯作者:
吴胜安，男，湖南省人，研究员级高级工程师，主要从事气候变化研究。E-mail：wsa01@sohu.com

中图分类号: P444
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- 文章访问数: 2
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- 被引次数: 0
出版历程
- 收稿日期: 2024-12-26
- 修回日期: 2025-11-21
- 刊出日期: 2026-04-20

Predicting the Frequency of Landfalling Tropical Cyclones in East and South China Using Thermocline Temperature Anomalies

ZHENG Rong^{1, 2, 3, 4},
LIU Chunlei^{1, 2, 3, 4},
WU Shengan^{4
, ,},
CAO Ning^{1, 2, 3},
JIN Liang^{5, 6},
BAO Ruijuan⁷,
LIAO Xiaoqing^{1, 8},
CHEN Hailiang⁹,
YANG Ke^{1, 2, 3},
SU Qianye^{1, 2, 3},
LIANG Zhiting^{1, 2, 3}

1.
College of Oceanography and Meteorology, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China
2.
CMA-GDOU Joint Laboratory for Marine Meteorology, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China
3.
South China Sea Institute of Marine Meteorology, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China
4.
Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570203, China
5.
Wenling Meteorological Office, Wenling, Zhejiang 317500, China
6.
Taizhou Key Laboratory of Typhoon and Marine Meteorology, Taizhou, Zhejiang 318000, China
7.
Fujian Key Laboratory of Severe Weather, Fuzhou 350028, China
8.
School of Marine Sciences, Sun Yat-sen University, Zhuhai, Guangdong 519082, China
9.
Zhanjiang Meteorological Office, Zhanjiang, Guangdong 510080, China

摘要

摘要: 热带气旋(Tropical Cyclone, TC) 的登陆会给中国沿海地区带来巨大的经济损失，提前预测TC登陆频数对防灾减灾工作有重大意义。本文基于1993—2019年四套海洋再分析数据集，研究不同月份、不同经度赤道温跃层温度异常与中国华南及华东地区TC登陆频数之间的相关关系。结果显示, 在部分特定经度上两者存在显著相关性。由于海洋热能沿着太平洋赤道温跃层自西向东传输，特定区域的温度异常可以超前数月甚至更长时间指示TC的登陆频数。另外，西太平洋副热带高压脊线的南北位置变化不仅与华东地区TC登陆频数密切相关，还与不同经度温跃层温度变化存在显著关联。
- 热带气旋登陆频数 /
- 温跃层温度异常 /
- 海洋热能传输 /
- 长期预报
Abstract: Landfalling Tropical Cyclones (TCs) cause huge economic losses in China's coastal areas. Predicting the frequency of TC landfall in advance is of great significance for disaster prevention and mitigation. In this study, four ocean reanalysis datasets from 1993 to 2019 were utilized to investigate the correlations between the thermocline temperature anomalies at different longitudes across different months and the frequency of TCs making landfall in South and East China. The results reveal significant correlations at specific longitudes, with temperature anomalies leading the frequency of landfalling TCs by several months or even longer. This predictive capability is attributed to the eastward transport of upper-ocean heat content along the equatorial Pacific thermocline. In addition, the meridional shift of the western Pacific subtropical high ridge is closely related not only with the frequency of landfalling TCs in East China but also with the thermocline temperature anomalies at varying longitudes.
- tropical cyclone landfall frequency /
- thermocline temperature anomaly /
- ocean heat transport /
- long-range forecast

HTML全文

图 1 1993—2019年TC季的登陆TC频数时间序列

实线和虚线分别为IBTrACS和CMABST的统计结果。红色与粉色线代表华南地区（S China），黑色与灰色线代表华东地区（E China）。

下载: 全尺寸图片幻灯片

图 2 左列是热带海洋温跃层温度异常与登陆华南地区TC频数的相关系数(r)随着经度在超前时间为NOV(-1)（a）和AUG(-1)（d）时的变化，中列是各数据集在[NOV(-1)，169 °W]（b）和[AUG(-1)，169 °E]（e）温跃层温度异常与登陆华南地区TC频数的时间序列，右列是各数据集温跃层温度异常平均值与登陆TC频数的散点拟合图与相关系数（c、f）(b)和(e)中的温度异常均为×（-1）后的结果；（c）和（f）中的红色圆圈和三角形分别为2020年和2021年的登陆TC频数观测值

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图 3 各数据集在[JUN(-1)，28 °W]（a、b）和[JUN(-2), 80 °W]（c、d）温跃层温度异常与登陆华南地区TC频数的时间序列（a、c），各数据集温跃层温度异常平均值与登陆TC频数的散点拟合图与相关系数（b、d）

（b）和（d）中的红色圆圈和三角形点分别为2020年和2021年的观测值。(c)中的温度异常为×（-1）后的结果。

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图 4 海洋温度异常在2015年El Niño事件期间沿温跃层的传输

（a）2015年1月、（b）2015年5月、（c）2015年9月、（d）2016年1月、（e）2016年5月和（f）2016年8月。纬度选取范围为5 °S~5 °N，图中灰色区域为陆地。黑色实线和虚线分别代表多年平均的逐月气候态温跃层（即20 ℃等温线）深度与实际温跃层深度。

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图 5 WPSH脊线位置与登陆华东TC频数的时间序列（a）和散点分布（b）

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图 6 副高脊线指数与不同经度和超前月份的赤道温跃层温度异常之间相关系数Hovmöller图

黑色打点区域表示相关系数通过95%置信度检验。（a）ORASS、（b）CGLORS、（c）GLORY和（d）FOAM。

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