Article(id=1211299029514850338, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, articleNumber=null, orderNo=null, doi=10.12284/hyxb2023036, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1633795200000, receivedDateStr=2021-10-10, revisedDate=1665158400000, revisedDateStr=2022-10-08, acceptedDate=null, acceptedDateStr=null, onlineDate=1766725793484, onlineDateStr=2025-12-26, pubDate=1677600000000, pubDateStr=2023-03-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766725793484, onlineIssueDateStr=2025-12-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766725793484, creator=13701087609, updateTime=1766725793484, updator=13701087609, issue=Issue{id=1211299024825611053, tenantId=1146029695717560320, journalId=1149651085930835976, year='2023', volume='45', issue='3', pageStart='1', pageEnd='158', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766725792365, creator=13701087609, updateTime=1766924576395, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1212132785515532522, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1212132785515532523, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=13, ext={EN=ArticleExt(id=1211299029795868716, articleId=1211299029514850338, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Two leading modes of environmental steering flow in the interannual time scale and their associations with tropical cyclone activity over the western North Pacific, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Using the tropical cyclone (TC) best track data from the Shanghai Typhoon Research Institute of the China Meteorological Administration (CMA-STI) and the monthly mean reanalysis data of NCEP/NCAR, the interannual variability of the basin-scale large-scale environmental steering flow and the tropical cyclone activity in the western North Pacific (WNP) during peak season from July to September from 1979−2016 are investigated. The results show that: (1) There are two typical modes of summer large-scale environmental steering flow in the WNP at the inter-annual scale. The first typical mode is a dipole circulation with a meridional distribution, which is closely related to the eastern ENSO and the sea-air coupling mode in the WNP region. (2) The TC activity (generation location, tracks, intensity and duration) differs significantly between the two typical interannual mode anomaly years of the large-scale environment steering flow, but the differences have distinctly different characteristics for the two typical inter-annual modes. (3) The spatial distribution of TC generation location shows significant differences from north to south between the years of the first typical interannual mode anomalies of large-scale environment steering flow; the TC tracks, especially the northwestward and westward prevailing tracks, also have significant differences, and their average duration and intensity also show their corresponding significant differences. In the second major interannual mode anomaly years, the TC generation locations show significant east-west distribution especially in the southeast quadrant, and the differences in TC tracks are mainly in the northwestward and offshore steering prevailing tracks, and their mean durations and intensities also show significant differences.

, correspAuthors=Haikun Zhao, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2023 Pratacultural Science. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xinwei Yang, Yuhang Shao, Haikun Zhao, Xiang Han, Yufeng Zhou, Mingbo Jiang), CN=ArticleExt(id=1211299032710910083, articleId=1211299029514850338, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=环境引导气流两类典型年际模态与西北太平洋热带气旋活动的联系, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

本文基于中国气象局上海台风研究所整编的热带气旋(Tropical Cyclone, TC)最佳路径资料及美国NCEP/NCAR月平均再分析资料,采用经验正交函数分解、合成分析、相关分析等统计方法,分析了1979−2016年7−9月西北太平洋地区海盆尺度大尺度环境引导气流的年际变化与热带气旋活动之间的联系。结果表明:(1)西北太平洋地区夏季大尺度环境引导气流在年际尺度上存在两个典型模态。其中第一典型模态大尺度环境引导气流呈现经向分布的偶极型环流型,该模态与东部型ENSO密切相关;第二典型模态大尺度环境引导气流呈明显的局地反气旋环流形态,其与中部型ENSO和热带大西洋海温异常紧密关联。(2)大尺度环境引导气流第一典型模态异常年份之间TC活动(生成位置、路径、强度和持续时间)具有显著差异,TC生成空间分布南北差异显著;TC路径尤其西北行和西行盛行路径也具有显著差异。(3)第二典型模态异常年份之间,TC生成位置和路径差异与第一模态呈现显著不同,TC生成位置呈现较为明显的东西向分布,在东南象限TC生成差异尤为显著,TC路径的差异主要体现在西北行和近海转向两类盛行路径。

, correspAuthors=赵海坤, authorNote=null, correspAuthorsNote=
*赵海坤,男,教授,研究方向为台风气候动力学与台风预测技术研制。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=duhC85N211VtK6hgM0wOoA==, magXml=/f2H4Q29ZqmhBihrkK6V7A==, pdfUrl=null, pdf=TurrvRYh76KPyfmRX9GMwA==, pdfFileSize=4423515, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=EsYelV/DzBx6qOu9FBj+ew==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=P0LQfxs9kTeiJeT8xPVqbw==, mapNumber=null, authorCompany=null, fund=null, authors=

杨昕玮(1999-),男,浙江省宁波市人,主要从事热带气旋研究。E-mail:

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杨昕玮(1999-),男,浙江省宁波市人,主要从事热带气旋研究。E-mail:

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Change in destructiveness of landfalling tropical cyclones over China in recent decades[J]. 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5-point smoothing is denoted by the solid gray line; the linear tendency is denoted by the dashed gray line

, figureFileSmall=DWMPDxzg/pdvbrL0LHODYg==, figureFileBig=zKmf+OGOtdlwlI3u724XWg==, tableContent=null), ArticleFig(id=1215304248909287850, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=CN, label=图1, caption=引导气流EOF第一、第二主要年际空间模态(a,c)及标准化时间系数(b,d)

灰色实线为5点平滑处理结果,灰色虚线为线性倾向

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Dots denote areas that are significant at the 95% confidence level

, figureFileSmall=iOz6HTIreMx0StUcw4jKmg==, figureFileBig=w9UDAapLUT+LZBg3H1aLFw==, tableContent=null), ArticleFig(id=1215304249119003070, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=CN, label=图2, caption=EOF第一、第二主要年际模态时间系数与海表温度相关系数的空间分布和引导气流EOF第一、第二主要年际模态(绿色矢量箭头)

打点为通过90%显著性检验

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Significance: * represents >90%, ** represents >95%, *** represents >99%; the sea surface temperature is the standardized temprature

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显著性:*代表>90%、**代表>95%、***代表>99%;海表温度为标准化温度

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Black lines represent the prevailing TC tracks; lines with different colors represent the maximum 10 m wind speed

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黑色线为TC合成路径,不同颜色的线代表10 m最大风速

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Green counters are the density of TC tracks; dots are the value that is significant at a 95% confidence level

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绿色等值线为平均路径密度;打点为通过95%显著性检验

, figureFileSmall=B7B1y19TIg2Hx+utDgV8pw==, figureFileBig=pnjzJzp64YSH+QlwrBNGHg==, tableContent=null), ArticleFig(id=1215304251472007681, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=EN, label=Table 1, caption=

Positive and negative anomaly years of EOF1 and EOF2

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EOF第一主要年际模态
正异常年198819941998200020012008201020112012
负异常年198019821983198619871991199320142015
EOF第二主要年际模态
正异常年198319851988199519982003200820102014
负异常年198219861994199720022006201220152016
), ArticleFig(id=1215304251564282373, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=CN, label=表1, caption=

EOF第一、第二主要年际模态正负异常年年份

, figureFileSmall=null, figureFileBig=null, tableContent=
EOF第一主要年际模态
正异常年198819941998200020012008201020112012
负异常年198019821983198619871991199320142015
EOF第二主要年际模态
正异常年198319851988199519982003200820102014
负异常年198219861994199720022006201220152016
), ArticleFig(id=1215304251702694413, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=EN, label=Table 2, caption=

Annual TC frequency difference between positive and negative years of EOF1 and EOF2

, figureFileSmall=null, figureFileBig=null, tableContent=
模态Type AType BType C
注:*代表显著性大于90%,**代表显著性大于95%。
EOF1−1.33**1.78*0.78
EOF2−1.78**0−1.33
), ArticleFig(id=1215304251824329235, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=CN, label=表2, caption=

两个模态正负异常年各类年TC频数差值

, figureFileSmall=null, figureFileBig=null, tableContent=
模态Type AType BType C
注:*代表显著性大于90%,**代表显著性大于95%。
EOF1−1.33**1.78*0.78
EOF2−1.78**0−1.33
), ArticleFig(id=1215304251899826712, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=EN, label=Table 3, caption=

TC characteristic difference between positive and negative years of EOF1 and EOF2

, figureFileSmall=null, figureFileBig=null, tableContent=
个数生命周期/h初始纬度/(°)初始经度/(°)PDI/(106 m3·s−3最大风速/(m·s−1平均风速/(m·s−1
注:*代表显著性大于90%;**代表显著性大于95%;***代表显著性大于99%;初始纬度和经度以北纬和东经为基准。
EOF11.22−38.39**2.99***−4.60−6.06**−6.64***−3.30***
EOF2−3.11*−44.08***1.17−7.80**−9.51***−3.34*−1.50
), ArticleFig(id=1215304252029850149, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299029514850338, language=CN, label=表3, caption=

两个模态正负异常年TC特征差值

, figureFileSmall=null, figureFileBig=null, tableContent=
个数生命周期/h初始纬度/(°)初始经度/(°)PDI/(106 m3·s−3最大风速/(m·s−1平均风速/(m·s−1
注:*代表显著性大于90%;**代表显著性大于95%;***代表显著性大于99%;初始纬度和经度以北纬和东经为基准。
EOF11.22−38.39**2.99***−4.60−6.06**−6.64***−3.30***
EOF2−3.11*−44.08***1.17−7.80**−9.51***−3.34*−1.50
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环境引导气流两类典型年际模态与西北太平洋热带气旋活动的联系
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杨昕玮 1 , 邵宇行 1 , 赵海坤 1, * , 韩翔 2 , 周育锋 3 , 姜明波 3
海洋学报 | 论文 2023,45(3): 1-13
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海洋学报 | 论文 2023, 45(3): 1-13
环境引导气流两类典型年际模态与西北太平洋热带气旋活动的联系
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杨昕玮1 , 邵宇行1, 赵海坤1, * , 韩翔2, 周育锋3, 姜明波3
作者信息
  • 1 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心/太平洋台风研究中心,江苏 南京 210044
  • 2 浙江大学 海洋学院,浙江 舟山 316000
  • 3 北京应用气象研究所,北京 100082
  • 杨昕玮(1999-),男,浙江省宁波市人,主要从事热带气旋研究。E-mail:

通讯作者:

*赵海坤,男,教授,研究方向为台风气候动力学与台风预测技术研制。E-mail:
Two leading modes of environmental steering flow in the interannual time scale and their associations with tropical cyclone activity over the western North Pacific
Xinwei Yang1 , Yuhang Shao1, Haikun Zhao1, * , Xiang Han2, Yufeng Zhou3, Mingbo Jiang3
Affiliations
  • 1Key Laboratory of Meteorological Disaster, Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Pacific Typhoon Research Center, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 2Ocean College, Zhejiang Univeristy, Zhoushan 316000, China
  • 3Beijing Institute of Applied Meteorology, Beijing 100082, China
出版时间: 2023-03-01 doi: 10.12284/hyxb2023036
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本文基于中国气象局上海台风研究所整编的热带气旋(Tropical Cyclone, TC)最佳路径资料及美国NCEP/NCAR月平均再分析资料,采用经验正交函数分解、合成分析、相关分析等统计方法,分析了1979−2016年7−9月西北太平洋地区海盆尺度大尺度环境引导气流的年际变化与热带气旋活动之间的联系。结果表明:(1)西北太平洋地区夏季大尺度环境引导气流在年际尺度上存在两个典型模态。其中第一典型模态大尺度环境引导气流呈现经向分布的偶极型环流型,该模态与东部型ENSO密切相关;第二典型模态大尺度环境引导气流呈明显的局地反气旋环流形态,其与中部型ENSO和热带大西洋海温异常紧密关联。(2)大尺度环境引导气流第一典型模态异常年份之间TC活动(生成位置、路径、强度和持续时间)具有显著差异,TC生成空间分布南北差异显著;TC路径尤其西北行和西行盛行路径也具有显著差异。(3)第二典型模态异常年份之间,TC生成位置和路径差异与第一模态呈现显著不同,TC生成位置呈现较为明显的东西向分布,在东南象限TC生成差异尤为显著,TC路径的差异主要体现在西北行和近海转向两类盛行路径。

大尺度引导气流  /  西北太平洋  /  热带气旋移动  /  海温异常  /  年际尺度

Using the tropical cyclone (TC) best track data from the Shanghai Typhoon Research Institute of the China Meteorological Administration (CMA-STI) and the monthly mean reanalysis data of NCEP/NCAR, the interannual variability of the basin-scale large-scale environmental steering flow and the tropical cyclone activity in the western North Pacific (WNP) during peak season from July to September from 1979−2016 are investigated. The results show that: (1) There are two typical modes of summer large-scale environmental steering flow in the WNP at the inter-annual scale. The first typical mode is a dipole circulation with a meridional distribution, which is closely related to the eastern ENSO and the sea-air coupling mode in the WNP region. (2) The TC activity (generation location, tracks, intensity and duration) differs significantly between the two typical interannual mode anomaly years of the large-scale environment steering flow, but the differences have distinctly different characteristics for the two typical inter-annual modes. (3) The spatial distribution of TC generation location shows significant differences from north to south between the years of the first typical interannual mode anomalies of large-scale environment steering flow; the TC tracks, especially the northwestward and westward prevailing tracks, also have significant differences, and their average duration and intensity also show their corresponding significant differences. In the second major interannual mode anomaly years, the TC generation locations show significant east-west distribution especially in the southeast quadrant, and the differences in TC tracks are mainly in the northwestward and offshore steering prevailing tracks, and their mean durations and intensities also show significant differences.

large-scale steering flow  /  western North Pacific  /  tropical cyclone activity  /  sea surface temperature anomaly  /  inter-annual scale
杨昕玮, 邵宇行, 赵海坤, 韩翔, 周育锋, 姜明波. 环境引导气流两类典型年际模态与西北太平洋热带气旋活动的联系. 海洋学报, 2023 , 45 (3) : 1 -13 . DOI: 10.12284/hyxb2023036
Xinwei Yang, Yuhang Shao, Haikun Zhao, Xiang Han, Yufeng Zhou, Mingbo Jiang. Two leading modes of environmental steering flow in the interannual time scale and their associations with tropical cyclone activity over the western North Pacific[J]. Haiyang Xuebao, 2023 , 45 (3) : 1 -13 . DOI: 10.12284/hyxb2023036
热带气旋(Tropical Cyclone, TC)是地球上最严重的自然灾害之一,它所伴随的风场和降水给TC活动区域内居民带来了严重的生命和财产威胁。TC路径的精准预报是TC预报中最重要的环节,在减少TC造成的灾害中起关键作用。西北太平洋(Western North Pacific, WNP)地区是TC活动最为频繁的区域,也是唯一一个全年均有TC活动的地方[1]。提高西北太平洋TC路径的预报水平,对于减少TC造成的生命财产损失有着重要意义。
TC路径主要由生成位置及随后的运动决定,从气候角度出发,TC运动主要由大尺度环境引导气流和Beta漂移两部分组成,其中大尺度环境引导气流被认为是影响TC路径变化更为重要的因子[2-4]。Wu和Wang[5]研究认为,虽然大尺度环流系统能够为TC的生成提供有利的环境条件,如低层辐合、气旋性相对涡度以及适宜的垂直风切[6-7],但是对TC路径变化的影响更为重要。Wu等[3]发现,在1965−2003年间,全球气候变化导致TC平均移动速度和大尺度引导气流发生变化,使东亚地区更容易受台风活动影响,并且TC路径北偏,南海地区TC活动减少。Liu和Chan[8]发现1960−2005年间WNP TC路径存在显著的年代际变化,并把这种变化归因于大尺度引导气流的变化。赵海坤[9]采用了自行完善的TC活动模式系统,从年际和年代际尺度分别定量考察了大尺度引导气流对WNP TC盛行路径的贡献。结果表明,年际尺度上,大尺度环境引导气流对近海转向型TC的影响更加显著[10],而在年代际尺度大尺度环境引导气流对3类盛行路径的影响呈现主导的地位,结果表明年际时间大尺度环境引导气流的影响呈现主导地位[11]。从天气尺度扰动的角度,Zhou等[12]发现了不同的扰动型下不同的TC路径特征主要是由大尺度引导气流和生成位置的变化造成的。苏源和吴立广[13]也从天气尺度和低频变化角度表明了大尺度引导气流在多时间尺度上的变化对台风“海棠”路径异常变化的重要影响。
在年代际时间尺度上,Clark和Chu[14]研究表明,太平洋年代际振荡(Pacific Decadal Oscillation, PDO)从20世纪后期由冷位相向暖位相转变,使得更强更频繁的ENSO事件发生,导致太平洋中部TC生成频数增加。何鹏程和江静[15]分别从PDO冷暖位相研究了WNP TC生成频数与海温分布差异的联系以及500 hPa高度场对TC频数和生成源地的影响,结果表明PDO对WNP TC活动与大尺度环流年际相关的年代际变化有重要影响。Li等[16]研究表明,由于引导气流的变化,在IPO(Inter-decadal Pacific Oscillation)不同位相上TC路径在稳定的西移过程中伴有较小的变化。最近也有结果显示,WNP TC活动的年代际变化与青藏高原积雪的变化紧密关联[17]。在年际时间尺度上,大量研究表明ENSO事件通过海温异常引起沃克环流变化从而改变大尺度引导气流的配置,进而改变西北太平洋TC的生成位置、路径和强度特征[18-24]。在El Niño年,TC生成个数在西北太平洋东南象限显著增多,TC生命周期也相对变长,La Niña年状况则相反[25-26]。在这过程中,西北太平洋异常反气旋起关键作用,赤道中东太平洋海表温度暖异常激发出罗斯贝波,其在西北太平洋形成的西北太平洋异常反气旋(Western North Pacific Anomalous Anticyclone, WNPAC)在印度洋和大西洋海温暖异常的相互作用下能够持续至翌年夏季[27-28]。WNPAC的产生导致下沉运动,低层涡度减小,抑制西北太平洋TC生成[29],且WNPAC南侧东风异常,无充足的水汽输送,使得西北太平洋TC生成个数减少[30]。此外,在El Niño年的10月,台风向北移动更为频繁[25]。也有研究利用聚类分析发现,El Niño和La Niña分别会对不同类别的路径个数产生影响,并进而影响台风的登陆情况[31-32]
综上,目前大多数研究都是基于TC路径气候异常变化的观测事实,定性分析对应的大尺度环境引导气流变化来理解其路径的变化,而很少直接从大尺度环境气流变化的角度来理解TC路径及其相伴随的TC活动的变化特征,在年际尺度上对于海温通过引导气流和大尺度环境场对于TC包括路径、生成位置以及强度在内活动变化特征的影响讨论相对较少。本文将着眼于TC活动异常活跃的WNP地区,在年际时间尺度讨论大尺度环境引导气流的典型模态及其对TC路径的影响及其相伴随的包括TC生成位置、强度以及路径长度在内的其他特征变化之间的联系,进一步深化大尺度环境引导气流对TC活动的整体认识,为台风活动的季节−年际预测提供理论参考。
TC 资料取自中国气象局上海台风研究所(Shanghai Typhoon Institute of China Meteorological Administration,CMA-STI)整编的1979−2016年7−9月“CMA热带气旋最佳路径数据集”,数据集包含TC中心每6 h一次的位置和强度信息,分析时只保留热带风暴级别及以上(近中心风速≥17.2 m/s)且生命周期达到24 h及以上的TC资料[33]。环境场数据来自美国国家环境预报中心/美国国家大气研究中心(National Centers for Environmental Prediction/ National Center for Atmospheric Research, NCEP/NCAR)月平均再分析资料,包括逐月垂直速度、比湿、纬向风、经向风、海表面温度及位势高度等,选取时间段为1979−2016年7−9月,空间网格分辨率为2.5°×2.5°[34]。海温数据来自哈德来中心海表温度月平均资料(HadlSST1),水平分辨率为1°×1°[35]
前人研究提出了多种环境引导气流的计算方法,但是目前仍然没有一个统一的“最佳引导气流”的定义。董克勤和刘治军[36]对地面到200 hPa各等压面基本气流进行分析后得出,利用上下两层进行引导气流计算相对采用单层等压面效果更为显著。有研究对比了多个高度的引导气流发现,500~700 hPa距台风中心5°~7°范围内的环境引导气流与台风移动方向最为贴近[37-38]。也有研究指出引导气流的选取与TC强度有关,对于强度较大的TC,可以采用偏高层引导气流。目前大量研究表明,将垂直平均风场作为平均引导气流对于解释TC的运动有着很好的效果[3, 11, 39]。因此,本文将采用300~850 hPa整层风场的算术平均作为环境引导气流,对其进行正交经验分解(Empirical Orthogonal Function,EOF),并基于North特征值显著性检验挑选典型模态[40],来获取大尺度环境引导气流典型年际模态。
为研究WNP TC盛行路径变化与大尺度环境引导气流主要模态之间的联系,采用常用的K-means聚类算法对WNP TC路径进行了分类[31, 41]。权重指标为2 min平均近中心风速的平方根,选取的参数为质心的经度位置、质心的纬度位置、经向方差、纬向方差以及对角线方向上的方差。K-means聚类过程中采用平方欧几里得距离并使用K-means++算法进行质心初始化。
经EOF得到的大尺度环境引导气流第一主要年际模态(EOF1)、第二主要年际模态(EOF2)及其对应的标准化时间系数如图1所示。第一主要年际模态方差贡献率为34.85%,第二主要年际模态方差贡献率为17.18%,前两个主要年际模态累计方差贡献率为52.03%,表明这两类年际模态能够反应西北太平洋大尺度环境引导气流的主要年际特征。前两类主要年际模态呈现出不同的环流特征,EOF1为经向分布的偶极型环流型,以20°N为分界线,以南区域(0°~20°N,125°~170°E)为反气旋性环流异常,以北区域(20°~40°N,130°E~180°)为气旋式环流异常,赤道附近为东风异常。EOF2在日本以南区域(10°~40°N,100°~145°E)为反气旋式环流,赤道附近为东风异常。
在年际时间尺度上,EOF1时间系数具有显著上升趋势,气候倾向率为0.78 a−1(达到97.3%置信水平),20世纪80年代末期到90年代中期以负位相为主,20世纪90年代中期以后以正位相为主,存在约以11 a为周期的年代际变化。EOF2的时间系数没有表现出明显的变化趋势。
为了能够更好地研究大尺度环境引导气流两类典型模态异常年份所对应大尺度环流变化、海温分布特征以及TC活动特征,将第一、第二主要年际模态时间系数位于前(后)25%的年份取为正(负)异常年份(表1)。
TC引导气流年际变化与热带大尺度海气相互作用密切相关。对两个模态时间系数与同期(7−9月)海温进行相关性分析(图2图3)发现,第一主要年际模态时间系数与赤道西太平洋和赤道大西洋海表温度的相关系数分别为0.63、0.52(均通过99%显著性检验),具有显著的正相关性,与赤道中东太平洋和赤道东太平洋海表温度的相关系数分别为−0.58、−0.45(均通过99%显著性检验),具有显著的负相关性。
第二主要年际模态时间系数与海温的显著正相关区域位于赤道西太平洋和赤道大西洋,相关系数分别为0.37、0.36(均通过95%显著性检验),显著负相关区域位于赤道中东太平洋,相关系数为−0.46(通过99%显著性检验)。两模态时间系数与海表温度的显著相关区域分布特征与La Niña分布特征较为类似,但海表温度冷异常区域不同,第一主要年际模态对应的海表温度分布与WNP地区的海气耦合模态和东部型ENSO密切相关,第二主要年际模态对应的海表温度分布与中部型ENSO紧密关联,两类ENSO类型会造成大尺度环境场的变化从而影响WNP TC特征变化[42]
考虑到海表温度异常对WNP大尺度环流具有一定的滞后影响,对两模态下正负异常年份前一年秋季(SON)、冬季(DJF)、同年春季(MAM)、夏季(JJA)海温进行了差值分析(图4),第一主要年际模态赤道海表温度异常分布从前一年秋季至同一年夏季表现为赤道西太平洋暖异常、赤道中东太平洋冷异常,在该时段内赤道中东太平洋冷异常不断加强,与La Niña发展年特征基本一致。对于第二主要年际模态,前一年秋季至冬季期间赤道中东太平洋存在显著的暖异常且不断加强,同一年春季至夏季期间该暖异常逐渐减弱,转化为赤道中太平洋冷异常,与El Niño衰减并过渡到La Niña的过程相类似。
第一主要年际模态下20°N以南的反气旋式环流主要是由中东太平洋冷海温异常通过Gill响应形成的,20°N以北的气旋环流可能与南侧反气旋式环流造成的Hadley上升支减弱以及北侧下沉支减弱有一定的关系。对于第二主要年际模态,在El Niño发展年,中东太平洋暖异常以及赤道北大西洋冷异常对WNPAC的重新加强起着一定的作用,一方面中东太平洋暖异常激发出的罗斯贝波有利于WNPAC的产生,另一方面,赤道北大西洋冷异常所产生的开尔文波及有关的埃克曼辐散过程对于WNPAC的产生和加强起到重要的贡献作用。WNPAC的存在使得第二主要年际模态下西太平洋副热带高压(Western Pacific Subtropical High,WPSH)面积偏大、强度偏强,此外,赤道太平洋海表温度东冷西暖的分布使得沃克环流上升支西移,被抑制的上升气流所激发出的罗斯贝波有利于副热带高压增强[43]在赤道西太平洋附近造成东风异常,对WPSH也起着一定的加强作用,较强的WPSH使得第二主要年际模态呈现出明显的反气旋式环流。
基于TC盛行路径分析方法[5],对1979−2016年7−9月TC路径和生成位置在2°×2°空间网格点的出现频次进行计算获得两模态下正负异常年TC路径密度差异(图5a图5b)和生成位置密度差异(图5c图5d),其中生成位置为TC近地面最大风速第一次达到或超过17.2 m/s时刻时的位置。对两模态下正负异常年TC路径(图6)和TC路径密度差异(图5a图5b)进行分析,TC合成路径为将各路径生命周期等分成21个时间点后各时间点的位置平均(图7集群中心以相同方式获得),分析发现,两模态正负异常年份TC路径均表现为:向西北方向移动后在25°N附近向东北方向转向,正异常年份相较于负异常年份TC移动路径偏短,强度偏弱。在TC路径密度差异方面,第一主要年际模态呈现明显的南北差异,在正异常年份下,台风路径南少北多,第二主要年际模态呈现海盆一致变化,除南海海域外,正异常年台风路径密度整体小于负异常年。
第一主要年际模态正、负异常年份TC活动频繁区域呈现以22°N为分界的分布特征(图5a),在负异常年份,TC在菲律宾以东(10°~22°N,120°~160°E)有一呈东西向分布的活动频繁区域,正异常年份TC在日本以南区域(25°~35°N,115°~165°E)活动频繁,且大值区位于我国以东海域(24°~30°N,120°~130°E)。
第二主要年际模态下WNP大部分区域表现为TC在负异常年份活动频繁,且有3个大值中心,分别位于台湾以东(22°N,125°E)、日本以南(25°N,135°E)和西北太平洋东南侧海域(18°N,155°E),在南海北侧海域则表现为TC在正异常年活动频繁。
类似地,Zhao等[20]利用聚类分析得到了3类热带气旋移动路径,并考察了两类ENSO下路径分布的年代际变化,发现与类ENSO有关的EOF第一主要年际模态,WNP台风活动呈一致性,并与南海北侧TC活动呈相反关系。本文第二主要年际模态对应的路径密度分布与其依据路径EOF得到的第一主要年际模态路径密度相一致,但是在利用聚类方法得到的西行路径并没有显示出类La Niña年减少的特征,这主要可能是从大尺度引导气流的变化不仅仅来自于ENSO变化,为此可直接从大尺度引导气流变化角度展开分析,认识除ENSO以外的其他主要海洋模态对台风活动年际变化的影响。
为进一步比较大尺度环境引导气流的两个主要模态下TC路径特征,采用K-means聚类方法将TC路径分成3类(图8)。Type A为西北行路径,生成位置主要位于140°E以东的洋面,平均生成中心为14.5°N,158.4°E,生成位置距离我国最远,该类TC生成后向西北方向直行,多数TC移动至我国东部海域附近后向东北方向转折,生命周期在3类路径中最长。Type B为西行型,主要生成于南海及菲律宾附近海域(10°~25°N,110°~150°E),平均生成中心为17.3°N,125.8°E,生成位置距离我国最近,移动路径最短,多数TC向西北方向移动至我国沿海,登陆后迅速消亡,相较于Type A,其活动区域纬度偏低。Type C为近海转向路径,其生成位置主要分布在菲律宾以东区域(10°~30°N,120°~170°E),平均生成位置为20.5°N,144.7°E,在3类路径中纬度最高,多数TC向西方向移动至30°N附近后偏转向东北方向。
表2为两模态下正负异常年份各类年TC频数的差异,第一主要年际模态下,正异常年份西北型路径TC频数相对于负异常年份显著偏少(通过95%显著性检验),对比引导气流可以发现,该类路径频数偏少与该模态所对应的WNP中部区域西北气流的抑制作用有关,而西行路径TC频数相对于负异常年份显著偏多(通过90%显著性检验),这主要与该模态下南海至台湾东侧TC生成频数较多有关。正异常年份近海转向路径TC偏多,但未通过显著性检验。
对于第二主要年际模态,正异常年份西北行路径TC频数相对于负异常年份显著偏少(通过95%显著性检验),该类路径频数偏少与该模态下WNP东南侧TC生成频数偏少有关。西行路径TC频数正负异常年份没有差异,正异常年份近海转向的TC频数相对于负异常年份偏少,未通过显著性检验,该类路径TC频数偏少与该模态所对应的WPSH东侧偏北气流影响有关。
对两模态正负异常年份TC平均生成个数、生命周期、生成位置经纬度以及用于表示强度的破坏潜力指数(Power Dissipation Index, PDI)[44]、路径最大风速、路径平均风速差异进行分析(表3)发现,对于第一主要年际模态,正异常年份相较于负异常年份,TC生命周期、初始纬度、PDI、最大风速、平均风速具有显著的差异(均通过95%显著性检验)。正异常年份相较于负异常年份TC平均生命周期短38.39 h,初始时刻位置纬度高2.99°,PDI低6.06×106 m3/s3,最大风速和平均风速低6.64 m/s和3.30 m/s。此外,正异常年份TC生成个数偏多、初始时刻位置偏西,但未通过显著性检验。
对于第二主要年际模态,正异常年份相较于负异常年份,TC生成个数、生命周期、初始经度、PDI、最大风速具有显著的差异(均通过90%显著性检验)。正异常年份平均相较于负异常年份TC生成个数少3.11个,生命周期短44.08 h,初始位置偏西7.80°,PDI低9.51×106 m3/s3,最大风速低3.34 m/s。
比较两个主要模态发现,在个数方面,第一主要年际模态正异常年相对于负异常年TC频数偏多而第二主要年际模态正异常年TC频数偏少。在生成位置方面,第一主要年际模态正负异常年TC生成位置在南北方向上具有显著差异,而第二模态正负异常年TC生成位置差异主要体现在东西方向上。另外第二主要年际模态正负异常年生命周期和PDI差异相较于第一主要年际模态更为显著。在强度方面,两模态下正异常年份相较于负异常年份TC强度显著偏弱,这是由于两模态TC生成位置更接近大陆,生命周期减少,在海上移动距离偏短,从海表面吸收能量增强的时间减短[45]。不同于前人研究得到的西北太平洋夏季台风生成个数在ENSO发展或衰减年差异不显著的结论[25, 30],本文第二主要年际模态TC生成个数显示出了显著差异,这可能是该模态同时包含了El Niño衰减和La Niña发展阶段所造成的。
TC生成位置是影响TC路径的重要因子之一,图5c图5d显示了大尺度环境引导气流第一、第二主要年际模态下正负异常年份TC生成位置密度合成差异,其中TC生成频数为2°×2°网格内TC生成的个数。第一主要年际模态下WNP东南部(5°~15°N,140°~170°E)表现为TC生成频数负异常区域,南海海域、WNP北部(15°~30°N,120°~145°E)则为TC生成频数正异常区域,该正异常区域呈东西向带状分布。进一步分析发现,第一主要年际模态正、负异常年TC生成频数分布特征呈现以15°N为分界的南北方向差异,在正异常年份TC多生成于15°N以北区域,负异常年份TC多生成于15°N以南区域,此分布特征与大尺度环境引导气流共同作用使得该主要模态下西北行TC在正异常年份出现频数偏少,而西行TC出现频数偏多有关。
第二主要年际模态TC生成频数在WNP东部(10°~30°N,135°~170°E)呈现负异常分布特征,在台湾东部海域(15°~30°N,115°~135°E)呈现正异常分布特征,整体呈现以135°E为分界的东西方向分布差异,在正异常年TC多生成于135°E以西,负异常年TC多生成于135°E以东,尤其在东南象限(10°~20°N,140°~170°E),TC频数显著偏少,这使得正异常年份西北行TC路径频数显著偏少。
TC生成位置分布与大尺度环境要素分布密切相关。两模态各环境要素正负异常年份差值如图8所示。对于第一主要年际模态,低层850 hPa涡度整体呈现南北向对称分布,WNP南部为显著的负涡度异常,并有500 hPa高度处下沉运动与之相对应,在WNP北部为正涡度异常及其对应的上升运动,由于上升运动有利于TC生成,该模态下正异常年TC生成频数呈现北多南少的分布特征。此外WNP北部700 hPa较为充足的水汽条件同样有利于TC生成。
对于第二主要年际模态,WPSH的强度和面积异常对环境要素分布起着重要作用。WPSH强度偏强,面积偏大,一方面使WNP大部分区域呈现显著的负涡度分布,低层辐散使得菲律宾以东区域(10°~20°N,120°E~180°)500 hPa以下沉运动为主,TC发生发展从而受到抑制,另一方面,WPSH南部的东风异常有助于输送赤道中部的干冷空气至WNP东南区域,使得该区域低层水汽含量降低,配合区域(10°~20°N,150°E~180°)垂直风切变正异常,造成正异常年份WNP东南区域TC生成频数显著偏低。
利用中国气象局上海台风研究所整编的热带气旋最佳路径资料及NCEP/NCAR月平均再分析资料探究了1979−2016年7−9月西北太平洋地区两类典型大尺度引导气流年际模态与西北太平洋热带气旋活动年际变化的联系,得出以下主要结论。
(1)WNP地区夏季大尺度环境引导气流在年际尺度上存在两个主要模态。第一主要年际模态以20°N为界,南北两侧分别为反气旋式环流和气旋式环流,二者为经向分布的偶极型环流,该模态以20世纪90年代中期为节点前后呈正反位相变化,其时间系数具有显著的上升趋势。第一主要年际模态对应位于中东赤道太平洋的冷海温异常,即东部型ENSO,其环流特征与Gill响应存在一定的联系;第二主要年际模态以中心位于25°N,135°E的反气旋式环流为主,对应了位于中赤道太平洋的冷海温异常,即中部型ENSO,并与赤道大西洋的暖海温异常有关。从海温对大尺度环流的滞后影响来看,第一主要年际模态下从前一年春季到当年夏季海温异常分布特征表现为类La Niña发展为从类东部型El Niño;第二主要年际模态则对应类东部型El Niño衰减并演变为从类中部型La Niña的过程。
(2)对于第一主要年际模态,WNP北部为气旋式环流,有垂直上升运动以及较为充足的水汽条件,使得该模态下正异常年份TC在15°N以北生成个数偏多,15°N以南生成个数偏少。在北多南少的TC生成位置分布特征与WNP北部偏西引导气流的共同作用下,正异常年份相较于负异常年份西北行路径TC频数显著偏少,西行路径TC频数显著偏多。此外,由于TC生命周期偏短,从海表面吸收能量增强的时间较短,第一主要年际模态正异常年份相对于负异常年PDI、最大风速和平均风速均显著偏小。
(3)对于第二主要年际模态,WPSH南部的东风异常有助于输送赤道中部受到海表温度冷异常影响所形成的干冷空气至WNP东南区域,导致WNP东南区域低层水汽含量异常偏少,配合垂直风切变正异常及显著的负涡度异常,造成该模态下正异常年份相较于负异常年份TC在WNP东南象限(10°~20°N,140°~170°E)生成频数显著偏少,对应西北行路径TC频数显著偏少,此外由于WPSH东部偏北方向引导气流的抑制作用,该模态下正异常年份近海转向型路径TC频数较少。在TC强度方面,第二主要年际模态PDI和最大风速显著偏小,造成TC路径和强度变化的主要原因是TC生成位置和大尺度环境引导气流存在明显差异,靠近西北方向的TC生成位置使得TC移动距离和生命周期偏短,不利于TC的加强发展。
本文主要考察了在不同大尺度环境引导气流的影响下,TC路径之间的年际特征差异及其对应的气候模态。不同于从ENSO等主要气候变率的角度,本文从大尺度环境引导气流这一角度出发,揭示了更多可能影响西北太平洋TC路径年际变化的海温模态,进一步凸显了不同海盆在其中的可能作用。
  • 国家自然科学基金优秀青年项目(41922033);江苏省大学生创新创业训练计划(201910300096Y)
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doi: 10.12284/hyxb2023036
  • 接收时间:2021-10-10
  • 首发时间:2025-12-26
  • 出版时间:2023-03-01
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  • 收稿日期:2021-10-10
  • 修回日期:2022-10-08
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国家自然科学基金优秀青年项目(41922033);江苏省大学生创新创业训练计划(201910300096Y)
作者信息
    1 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心/太平洋台风研究中心,江苏 南京 210044
    2 浙江大学 海洋学院,浙江 舟山 316000
    3 北京应用气象研究所,北京 100082

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*赵海坤,男,教授,研究方向为台风气候动力学与台风预测技术研制。E-mail:
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2种不同金属材料的力学参数

Family
属数
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genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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