Article(id=1224798801546858886, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224798798254326454, articleNumber=null, orderNo=null, doi=10.12284/hyxb2022163, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1651680000000, receivedDateStr=2022-05-05, revisedDate=1656172800000, revisedDateStr=2022-06-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1769944389949, onlineDateStr=2026-02-01, pubDate=1669824000000, pubDateStr=2022-12-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769944389949, onlineIssueDateStr=2026-02-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769944389949, creator=13701087609, updateTime=1769944389949, updator=13701087609, issue=Issue{id=1224798798254326454, tenantId=1146029695717560320, journalId=1149651085930835976, year='2022', volume='44', issue='12', pageStart='1', pageEnd='160', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769944389165, creator=13701087609, updateTime=1769996131500, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1225015821399900229, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224798798254326454, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1225015821399900230, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224798798254326454, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=42, endPage=54, ext={EN=ArticleExt(id=1224798802968727946, articleId=1224798801546858886, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Impact of global tropical sea surface temperature anomalies on the Arctic sea ice variation, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

This paper analyzes and discusses the long-term variation characteristics of Arctic sea ice using the latest sea ice and sea surface temperature (SST) data from 1951 to 2021 provided by Hadley Center and NCEP/NCAR reanalysis data from the Climate Prediction Center of National Oceanic and Atmospheric Administration (NOAA). The relationship between the rapid decrease of Arctic sea ice and surface sea temperature anomaly (SSTA) in tropical oceans is also investigated, revealing that there is a close relationship between the changes in tropical sea surface temperature field and the Arctic sea ice variation. The results show that the most significant sea ice changes occur in the Greenland Sea, the Kara Sea and the Barents Sea. Notably, the influence of the different tropical ocean areas on the Arctic sea ice shows noticeable temporal and spatial differences. The tropical Atlantic has the earliest impact on Arctic sea ice cover, followed by the Indian and Pacific oceans. Meanwhile, we found that 26-month, 30-month and 34-month lag is the optimal time-lagged correlation time period between Arctic sea ice and SSTA in the tropical Atlantic, the tropical Indian Ocean and Middle-Eastern Pacific, respectively and the mean value among them is a 33-month lag. The most substantial impact of SST on arctic sea ice occurs in the Indian Ocean, followed by the Pacific Ocean and the weakest in the Atlantic Ocean. When the tropical oceans appear positive (negative) SSTA, the arctic sea ice tends to be less (more). Moreover, Arctic Oscillation (AO), the Pacific-North American teleconnection (PNA), North Atlantic Oscillation (NAO) contribute significantly to the Arctic sea ice change, which are the key processes leading to the abnormal Arctic sea ice change. The AO, PNA and NAO are not only influenced by the SST of the tropical ocean, but also by the Pacific Ocean Decadal Oscillation (PDO) of the Atlantic Multi-decadal Oscillation (AMO). Our study aims to provide theoretical support for future research on the mechanism of the rapid decline of Arctic sea ice and global warming.

, correspAuthors=Qizhen Sun, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2022 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=Di Chen, Qizhen Sun), CN=ArticleExt(id=1224798807964144190, articleId=1224798801546858886, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=全球热带海洋海表温度场异常对北极海冰的影响, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

本文利用1951−2021年哈德莱中心提供的海冰和海温最新资料以及美国国家海洋和大气管理局气候预报中心提供的NCEP/NCAR再分析资料,分析探讨了北极海冰70余年的长期变化特征,进而研究了其快速减少与热带海温场异常变化之间的联系,揭示了在全球热带海洋海温场变化与北极海冰之间存在密切联系的事实。结果表明,北极海冰异常变化最显著区域出现在格陵兰海、卡拉海和巴伦支海。热带不同海区对北极海冰的影响存在明显时滞时间和强度差异,热带大西洋的影响相比偏早,印度洋次之,太平洋偏晚。热带大西洋、印度洋和中东太平洋海温异常影响北极海冰的最佳时间分别是后者滞后26个月、30个月和34个月,全球热带海洋影响北极海冰的时滞时间为33个月。印度洋SST对北极海冰的影响程度最强,其次是太平洋,最弱是大西洋。全球热带海洋对北极海冰的影响过程中,热带东太平洋和印度洋起主导作用。当全球热带海洋SST出现正(负)距平时,北极海冰会出现偏少(多)的趋势,而AO、PNA、NAO对北极海冰变化起重要作用,是热带海洋与北极海冰相系数的重要“纽带”。而AO、PNA和NAO不仅受热带海洋SST的影响,同时也受太平洋年代际振荡PDO和大西洋多年代际AMO的影响,这一研究为未来北极海冰快速减少和全球气候变暖机理的深入研究提供理论支撑。

, correspAuthors=孙启振, authorNote=null, correspAuthorsNote=
孙启振(1984-),男,副研究员,主要从事极地气象和海冰研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2022, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=nUA+OWKwSPRL2ba2A84aTw==, magXml=DMkCnfnSj/TyAdhcevaDVA==, pdfUrl=null, pdf=OVG1iYDGqqjIh4UIs8/U8w==, pdfFileSize=3517554, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=A/FPY5gDGYD4YbyI+Oa8Lw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ap6XqyGvPjNmLyE0a9aMKA==, mapNumber=null, authorCompany=null, fund=null, authors=

陈迪(1990-),男,山东省青岛市人,主要从事极地研究和海气相互作用研究。E-mail:

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陈迪(1990-),男,山东省青岛市人,主要从事极地研究和海气相互作用研究。E-mail:

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Journal of Climate, 2020, 33(10): 4009−4025., articleTitle=null, refAbstract=null)], funds=[Fund(id=1225369457095258540, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, awardId=2022, language=CN, fundingSource=极地考察业务化与科研(2022), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1225369448350134435, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, xref=null, ext=[AuthorCompanyExt(id=1225369448354328740, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, companyId=1225369448350134435, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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The areas marked by dots indicates correlation exceeding 99.9% confidence level. Y axis indicate that month of the Arctic sea ice concentration (ASIC) lag behind sea surface temperature anomaly (SSTA)

, figureFileSmall=VBgLhLoNZY2sLS2X8rNSJg==, figureFileBig=/61nyG72f9tyydkVgFnvSg==, tableContent=null), ArticleFig(id=1225369452959674681, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图5, caption=热带海洋10°S~10°N平均海表面温度与北极海冰变化的纬向−时滞相关图(1951−2021年)

图中点状分布表示相关区域达到99.9%信度检验水平,Y轴表示北极海冰密集度(ASIC)滞后异常海表面温度(SSTA)的时间

, figureFileSmall=VBgLhLoNZY2sLS2X8rNSJg==, figureFileBig=/61nyG72f9tyydkVgFnvSg==, tableContent=null), ArticleFig(id=1225369453060337981, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 6, caption=Time lag correlation curves (1951–2021) between Arctic sea ice change and sea surface temperature in tropical oceans (Indian Ocean, East Pacific Ocean, Atlantic Ocean, and the average of the three oceans)

Tropical oceans mean SST (10°S–10°N, 0°–180°–0°); Tropical Indian Ocean SST (10°S–10°N, 50°–110°E); Tropical Atlantic SST (10°S–10°N, 0°–50°W); Tropical East Pacific SST (10°S–10°N, 180°–80°W). Dotted lines are correlated exceed 99.9% confidence test level

, figureFileSmall=tMBeMvehy4ikgzzCaJcaBg==, figureFileBig=NlN7KOh63jToUVwZaCeJCA==, tableContent=null), ArticleFig(id=1225369453169389888, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图6, caption=北极海冰变化与热带海洋(印度洋、东太平洋、大西洋以及三大洋平均)海表面温度时滞相关曲线(1951–2021年)

热带三大洋平均SST(10°S~10°N,0°~180°~0°);热带印度洋SST(10°S~10°N,50°~110°E);热带大西洋SST (10°S~10°N,0°~50°W);热带东太平洋SST (10°S~10°N,180°~80°W);点线是相关达到 99.9%信度检验水平

, figureFileSmall=tMBeMvehy4ikgzzCaJcaBg==, figureFileBig=NlN7KOh63jToUVwZaCeJCA==, tableContent=null), ArticleFig(id=1225369453257470277, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 7, caption=Lag correlation curves of the effects of Arctic Oscillation (AO) index, North Atlantic Oscillation (NAO) index and Pacific-North American telecorrelation (PNA) index on Arctic ice (1951–2021), figureFileSmall=xbyMTLYyqzzrEnL4liIGPQ==, figureFileBig=ZupguNRwEcP8fWVoYVgFsg==, tableContent=null), ArticleFig(id=1225369453332967754, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图7, caption=北极涛动(AO)指数、太平洋–北美遥相关(PNA)指数和北大西洋涛动(NAO)指数与北极海冰时滞相关曲线(1951–2021年), figureFileSmall=xbyMTLYyqzzrEnL4liIGPQ==, figureFileBig=ZupguNRwEcP8fWVoYVgFsg==, tableContent=null), ArticleFig(id=1225369454700310858, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 8, caption=Lag correlation curve of the sea surface temperature (SST) with Arctic Oscillation (AO) (red) and Pacific-North American telecorrelation (PNA) (blue) in the eastern tropical Pacific

Dashed is that correlation exceed 99.9% significance level

, figureFileSmall=G2I3AZrQRvyFP4J2hKlrLw==, figureFileBig=CEvySin5VfWU75GAS0DTuQ==, tableContent=null), ArticleFig(id=1225369454834528591, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图8, caption=热带中东太平洋海表面温度(SST)与北极涛动(AO)(红线)和太平洋–北美遥相关(PNA)(蓝线)时滞相关图

虚线表示相关性超过99.9%显著性水平

, figureFileSmall=G2I3AZrQRvyFP4J2hKlrLw==, figureFileBig=CEvySin5VfWU75GAS0DTuQ==, tableContent=null), ArticleFig(id=1225369454972940627, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 9, caption=Time lag correlation curves of tropical Indian Ocean sea surface temperature (SST) with Arctic Oscillation (AO) (red line) and Pacific-North American telecorrelation (PNA) (blue line), figureFileSmall=wzJxIUptSC4LoFcJ4ee9NQ==, figureFileBig=Lb79kF7/0Gwd1/R5xpA2bA==, tableContent=null), ArticleFig(id=1225369455107158360, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图9, caption=热带印度洋海表面温度(SST)与北极涛动(AO)(红线)和太平洋–北美遥相关(PNA)(蓝线)时滞相关曲线, figureFileSmall=wzJxIUptSC4LoFcJ4ee9NQ==, figureFileBig=Lb79kF7/0Gwd1/R5xpA2bA==, tableContent=null), ArticleFig(id=1225369455191044443, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 10, caption=Time lag correlation curves of tropical Atlantic sea surface temperature (SST) with Arctic Oscillation (AO) (red line) and North Atlantic Oscillation (NAO) (blue line), figureFileSmall=f1PxTYZMimxDC7pN/mCjqA==, figureFileBig=8Sr8DHUoWyjzcxZp/gnNOQ==, tableContent=null), ArticleFig(id=1225369455300096354, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图10, caption=热带大西洋海表面温度(SST)与北极涛动(AO)(红线)和北大西洋涛动(NAO)(蓝线)时滞相关曲线, figureFileSmall=f1PxTYZMimxDC7pN/mCjqA==, figureFileBig=8Sr8DHUoWyjzcxZp/gnNOQ==, tableContent=null), ArticleFig(id=1225369455400759654, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 11, caption=Time lag correlation curves of global tropical ocean sea surface temperature (SST) with Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Pacific-North American telecorrelation (PNA), figureFileSmall=snmU/rmIYu1pZCG7a46x9w==, figureFileBig=BYHDYhvjq2DO0ykgt3j9Aw==, tableContent=null), ArticleFig(id=1225369455497228649, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图11, caption=全球热带海洋海表面温度(SST)与北极涛动(AO)、北大西洋涛动 (NAO)和太平洋−北美遥相关(PNA)时滞相关曲线, figureFileSmall=snmU/rmIYu1pZCG7a46x9w==, figureFileBig=BYHDYhvjq2DO0ykgt3j9Aw==, tableContent=null), ArticleFig(id=1225369455581114733, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 12, caption=Time lag correlation profiles of tropical ocean surface temperature and Northern Hemisphere geopotential height

a. Longitudinal-time-lag correlation profiles (latitudinal average); b. latitudinal-time-lag correlation profiles (35°−50°N average). Sample N=852; correlation coefficient r=0.092 reaches 95% confidence level

, figureFileSmall=AlNzmNngf0CqRbs4yG+xhw==, figureFileBig=00dkf6BTomdEfRox6QcLjg==, tableContent=null), ArticleFig(id=1225369455656612208, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图12, caption=热带海洋表面温度与北半球位势高度时滞相关剖面图

a. 经向–时滞相关剖面(纬度平均);b. 纬向–时滞相关剖面(35°~50°N 平均)。样本 N=852;相关系数r=0.092 达到 95%信度检验水平

, figureFileSmall=AlNzmNngf0CqRbs4yG+xhw==, figureFileBig=00dkf6BTomdEfRox6QcLjg==, tableContent=null), ArticleFig(id=1225369455719526772, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 13, caption=Composite plot of the anomalous low (a) high (b) tropical ocean sea surface temperature lagged by 2 years in the Northern Hemisphere 500 hPa potential height field, and the corresponding composite plot of high (c) and low (d) Arctic sea ice

The dotted area in the figure indicates that the correlation reaches the 99.9% confidence test level

, figureFileSmall=EbKkoPiVifAWOEN9SOjUxA==, figureFileBig=IM5Bapavxctd/Qz6KgRNJA==, tableContent=null), ArticleFig(id=1225369455803412855, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图13, caption=热带海洋异常海温偏低(a)和偏高(b)滞后 2 年北半球 500 hPa位势高度场合成图,以及后期对应的北极海冰偏多(c)和偏少(d)合成图

图中点状区域表示相关达到 99.9%信度检验水平

, figureFileSmall=EbKkoPiVifAWOEN9SOjUxA==, figureFileBig=IM5Bapavxctd/Qz6KgRNJA==, tableContent=null), ArticleFig(id=1225369455874716028, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 14, caption=Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) time series variation curves (the thick solid line is the 10-year moving average), figureFileSmall=1IKTRAF+WdSuqOjiYWbYWQ==, figureFileBig=x4amsa5lj7No7+2m7gXzcg==, tableContent=null), ArticleFig(id=1225369455950213505, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图14, caption=太平洋年代际振荡(PDO)和大西洋多年代际振荡(AMO)时间序列变化曲线(粗实线是 10 年滑动平均), figureFileSmall=1IKTRAF+WdSuqOjiYWbYWQ==, figureFileBig=x4amsa5lj7No7+2m7gXzcg==, tableContent=null), ArticleFig(id=1225369456080236934, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 15, caption=Time lag correlation curves of the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO), figureFileSmall=auKJz3h7HylFIy7mN2zSAA==, figureFileBig=gnOTRSA3TSfgf9Ylza1Gjw==, tableContent=null), ArticleFig(id=1225369456189288841, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图15, caption=太平洋年代际振荡(PDO)与大西洋多年代际振荡(AMO)时滞相关曲线, figureFileSmall=auKJz3h7HylFIy7mN2zSAA==, figureFileBig=gnOTRSA3TSfgf9Ylza1Gjw==, tableContent=null), ArticleFig(id=1225369456298340747, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 16, caption=Time lag correlation changes of the Pacific Ocean Decadal Oscillation (PDO) with tropical ocean sea surface temperature anomaly (SSTA) and Arctic sea ice (a), and the time lag correlation between Pacific Ocean Decadal Oscillation (PDO) (b), figureFileSmall=jehQL36bOr2RQ32sKB/I5w==, figureFileBig=snNRk468dDXMBvZqnkA6Aw==, tableContent=null), ArticleFig(id=1225369456457724303, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图16, caption=太平洋年代际振荡(PDO)和热带海洋海表异常温度(SSTA)与北极海冰时滞相关变化(a),以及太平洋年代际振荡(PDO)与北极海冰密集度(ASIC)超前−滞后相关(b), figureFileSmall=jehQL36bOr2RQ32sKB/I5w==, figureFileBig=snNRk468dDXMBvZqnkA6Aw==, tableContent=null), ArticleFig(id=1225369456596136339, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 17, caption=Time lag correlation curves of the Pacific Decadal Oscillation (PDO) with the Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Pacific-North American telecorrelation (PNA), and the Arctic Dipole, figureFileSmall=AFt6Jj0Ca56HXGcpJsl6yQ==, figureFileBig=Qg8WJLhuIMxSkRyZOVwTeA==, tableContent=null), ArticleFig(id=1225369456684216726, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图17, caption=太平洋年代际振荡(PDO)与北极涛动(AO)、北大西洋涛动(NAO)和太平洋−北美遥相关(PNA)以及北极偶极子(Arctic Dipole)的时滞相关曲线, figureFileSmall=AFt6Jj0Ca56HXGcpJsl6yQ==, figureFileBig=Qg8WJLhuIMxSkRyZOVwTeA==, tableContent=null), ArticleFig(id=1225369456835211677, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=EN, label=Fig. 18, caption=Time lag correlation curves of the Atlantic Multidecadal Oscillation (AMO) with the Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Pacific-North American telecorrelation (PNA), and the Arctic Dipole, figureFileSmall=j6SzIgWLpIWl2mCaZ3N14g==, figureFileBig=8NnqY1GVGpTYX6m9e2SWeA==, tableContent=null), ArticleFig(id=1225369456923292067, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224798801546858886, language=CN, label=图18, caption=大西洋多年代际振荡(AMO)与北极涛动(AO)、北大西洋涛动(NAO)和太平洋−北美遥相关(PNA)以及北极偶极子(Arctic Dipole)的时滞相关曲线, 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全球热带海洋海表温度场异常对北极海冰的影响
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陈迪 1 , 孙启振 2, *
海洋学报 | 论文 2022,44(12): 42-54
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海洋学报 | 论文 2022, 44(12): 42-54
全球热带海洋海表温度场异常对北极海冰的影响
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陈迪1 , 孙启振2, *
作者信息
  • 1.中国海洋大学 海洋与大气学院,山东 青岛 266100
  • 2.国家海洋环境预报中心,北京 100081
  • 陈迪(1990-),男,山东省青岛市人,主要从事极地研究和海气相互作用研究。E-mail:

通讯作者:

孙启振(1984-),男,副研究员,主要从事极地气象和海冰研究。E-mail:
Impact of global tropical sea surface temperature anomalies on the Arctic sea ice variation
Di Chen1 , Qizhen Sun2, *
Affiliations
  • 1. College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
  • 2. National Marine Environment Forecasting Center, Beijing 100081, China
出版时间: 2022-12-01 doi: 10.12284/hyxb2022163
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本文利用1951−2021年哈德莱中心提供的海冰和海温最新资料以及美国国家海洋和大气管理局气候预报中心提供的NCEP/NCAR再分析资料,分析探讨了北极海冰70余年的长期变化特征,进而研究了其快速减少与热带海温场异常变化之间的联系,揭示了在全球热带海洋海温场变化与北极海冰之间存在密切联系的事实。结果表明,北极海冰异常变化最显著区域出现在格陵兰海、卡拉海和巴伦支海。热带不同海区对北极海冰的影响存在明显时滞时间和强度差异,热带大西洋的影响相比偏早,印度洋次之,太平洋偏晚。热带大西洋、印度洋和中东太平洋海温异常影响北极海冰的最佳时间分别是后者滞后26个月、30个月和34个月,全球热带海洋影响北极海冰的时滞时间为33个月。印度洋SST对北极海冰的影响程度最强,其次是太平洋,最弱是大西洋。全球热带海洋对北极海冰的影响过程中,热带东太平洋和印度洋起主导作用。当全球热带海洋SST出现正(负)距平时,北极海冰会出现偏少(多)的趋势,而AO、PNA、NAO对北极海冰变化起重要作用,是热带海洋与北极海冰相系数的重要“纽带”。而AO、PNA和NAO不仅受热带海洋SST的影响,同时也受太平洋年代际振荡PDO和大西洋多年代际AMO的影响,这一研究为未来北极海冰快速减少和全球气候变暖机理的深入研究提供理论支撑。

北极海冰  /  热带海洋  /  海温异常  /  北极涛动  /  太平洋–北美遥相关  /  北大西洋涛动

This paper analyzes and discusses the long-term variation characteristics of Arctic sea ice using the latest sea ice and sea surface temperature (SST) data from 1951 to 2021 provided by Hadley Center and NCEP/NCAR reanalysis data from the Climate Prediction Center of National Oceanic and Atmospheric Administration (NOAA). The relationship between the rapid decrease of Arctic sea ice and surface sea temperature anomaly (SSTA) in tropical oceans is also investigated, revealing that there is a close relationship between the changes in tropical sea surface temperature field and the Arctic sea ice variation. The results show that the most significant sea ice changes occur in the Greenland Sea, the Kara Sea and the Barents Sea. Notably, the influence of the different tropical ocean areas on the Arctic sea ice shows noticeable temporal and spatial differences. The tropical Atlantic has the earliest impact on Arctic sea ice cover, followed by the Indian and Pacific oceans. Meanwhile, we found that 26-month, 30-month and 34-month lag is the optimal time-lagged correlation time period between Arctic sea ice and SSTA in the tropical Atlantic, the tropical Indian Ocean and Middle-Eastern Pacific, respectively and the mean value among them is a 33-month lag. The most substantial impact of SST on arctic sea ice occurs in the Indian Ocean, followed by the Pacific Ocean and the weakest in the Atlantic Ocean. When the tropical oceans appear positive (negative) SSTA, the arctic sea ice tends to be less (more). Moreover, Arctic Oscillation (AO), the Pacific-North American teleconnection (PNA), North Atlantic Oscillation (NAO) contribute significantly to the Arctic sea ice change, which are the key processes leading to the abnormal Arctic sea ice change. The AO, PNA and NAO are not only influenced by the SST of the tropical ocean, but also by the Pacific Ocean Decadal Oscillation (PDO) of the Atlantic Multi-decadal Oscillation (AMO). Our study aims to provide theoretical support for future research on the mechanism of the rapid decline of Arctic sea ice and global warming.

Arctic sea ice  /  tropical oceans  /  surface sea temperature anomaly  /  Arctic Oscillation  /  Pacific-North American teleconnection  /  North Atlantic Oscillation
陈迪, 孙启振. 全球热带海洋海表温度场异常对北极海冰的影响. 海洋学报, 2022 , 44 (12) : 42 -54 . DOI: 10.12284/hyxb2022163
Di Chen, Qizhen Sun. Impact of global tropical sea surface temperature anomalies on the Arctic sea ice variation[J]. Haiyang Xuebao, 2022 , 44 (12) : 42 -54 . DOI: 10.12284/hyxb2022163
北极海冰是气候系统中的重要组成部分,是全球气候变化的指示器和记忆器,它的变化对全球气候和大气环流具有重要的影响。自20世纪80年代以来,北极海冰出现快速减少的变化,大约以1.7%/(10 a)的速率消融,这种变化不仅对极地产生重要影响[1-4],而且对中纬度地区的气候存在非常重要的调控作用[5-13]。IPCC第五次评估报告(AR5)[14-15]明确指出,在全球变暖的大背景下,20世纪后期以来北极海冰出现了急剧消融,这一现象引起了全球广泛的关注。根据科学家们预测,北极海冰如此快速地减少,预计可能在2030年前后,北冰洋或将夏季无冰[16-17]。就目前的状况来看,针对北极海冰如此快速消融的事实,科学家们仍未给出一个客观合理的解释。因此,探讨北极海冰快速减少的原因是当前最为重要的工作。由于北极海冰的快速消融使得开阔水域面积急剧增加,这会直接影响海洋表层的能量收支,进而影响海气界面的热交换,最终将导致对局地乃至全球气候产生重要影响[18-26]。由于北极地区具有显著的季节变化特征,海冰的快速减少,导致北极地区夏季吸收过多的太阳辐射,直接影响冬季北极海冰的结冰速度。北极海冰的这种温度−反照率的正反馈机制将全球变暖效应放大,称为“北极放大效应”(Arctic Amplification)[27]。这种放大效应通过大气环流直接或间接引起全球极端天气的发生,因此对其的研究是目前国际前沿课题。就北极海冰快速减少而言,其机理主要是与全球变暖有关,而全球变暖的重要过程之一是与海洋快速升温存在一定联系。在全球海−气相互作用过程中,热带海洋又扮演着重要角色[28-29]。因此,热带海洋海温场的异常变化及其引起的大气环流异常可能是导致北极海冰快速融化的关键因素。鉴于以上原因,近年来已有研究者注意到热带海洋与北极海冰之间的联系[30-31],这些研究多涉及区域性海洋与北极海冰之间的探讨,针对全球热带海洋变化对北极海冰的影响相关研究关注度不够。本文针对热带海洋异常变化过程,探讨对北极海冰的影响,并初步给出它们之间的可能机制。为今后北极海冰快速消融的深入研究提供依据。
本文所用资料是英国哈德莱中心提供的月平均的海冰密集度和海温资料(Hadley Centre Sea Ice and Sea Surface Temperature data set,HadISST),空间分辨率为1.0°×1.0°,海冰密集度(Sea Ice Concentration)以百分数表示单位网格内海冰所覆盖的百分比[32]。为了去除全球变暖的影响,文内所用数据均进行了逐月去倾处理。大气环流资料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[33],水平分辨率为2.5°×2.5°。包括海平面气压、位势高度、风场,均是1951−2021年月平均资料。
本文研究方法主要涉及统计分析、相关分析、合成分析的方法以及显著性检验等。
北极海冰具有明显季节变化的特点,每年夏季北极地区进入极昼,接收到的太阳辐射为全年最多,海冰进入融冰期,直到9月海冰密集度达到极小值。随着太阳辐射的逐渐减少,秋冬季气温伴随降低,北极地区进入结冰期,直到翌年的3月,海冰密集度又恢复到极大值。每年6–10月,是海冰融化期,11月至翌年3月是海冰结冰期(图1)。由方差分析可知,海冰季节变化最为显著的地区是格陵兰海、巴伦支海以及卡拉海(图2)。其次,在北极太平洋扇区的拉普捷夫海、东西伯利亚泛指海、楚科奇海以及波弗特海的海冰变化非常显著。
为直观了解北极海冰长期变化特征,对1951–2021年共71 a逐月65°~90°N范围的平均海冰密集度进行分析。图3是北极海冰密集度多年变化曲线,可以发现在20世纪80年代北极海冰出现突变现象,自此开始出现快速减少(图3)。
由去倾后的海冰密集度变化可知(图4),北极海冰存在明显的年际变化特征,且最大海冰减少发生在近几十年中。尤以2007年和2012年最为突出。其中9月份的覆盖面积分别是4.15×106 km2、3.29×106 km2,与多年平均(6.22×106 km2)减少了大约32.4%和44.8% [34]
上述分析结果表明,北极海冰不仅具有明显的季节变化特征,而且年际变化特征也非常显著。北极海冰的长期变化与热带海洋温度场是否存在联系,值得我们进行必要的分析和探讨。首先,我们计算了热带海洋海表面温度 (Sea Surface Temperature,SST)(10°S~10°N,环全球经度)平均多年变化与北极海冰进行分析,结果表明,它们之间存在非常好的反位相关系(图4)。
为了深入探讨热带海洋温度场异常变化与北极海冰之间的年际变化之间的联系,采用沿纬圈0°~180°~0°,10°S~10°N的平均热带海洋 SST 与北极海冰进行时滞相关分析,图5是沿0°~180°~0°热带海洋SST与北极海冰变化的纬向–时滞相关图。图中表明,同为热带海洋,但对北极海冰的影响时间的早晚和显著程度有较大差异。热带印度洋SST对北极海冰的影响最为显著,最大相关是在30个月左右,最大相关系数为–0.4。其次是热带中东太平洋,最大相关是在36个月左右,最大相关系数是–0.3。影响最弱的是热带大西洋,最大相关是在28个月左右,最大相关系数是–0.2。从影响时间的早晚来看,热带大西洋最早,印度洋次之,太平洋最晚。热带大西洋SST对海冰的影响始于海冰变化滞后的18个月,影响时间可持续30个月。热带印度洋SST对海冰的影响,东西部的影响程度偏强,其影响时间是从海冰变化滞后的8个月开始,持续影响可达40个月。热带太平洋对北极海冰的影响主要是在中东太平洋,开始影响北极海冰的时间是在后者滞后的8个月左右,持续时间可达36个月。西太平洋和东大西洋区域对北极海冰几乎没有影响,甚至是负的相关关系。
由上述分析可知,全球热带海洋SST与北极海冰变化存在密切关系,三大洋SST对北极海冰的影响时间和强度存在差异。当全球热带海洋SST出现正(负)距平时,北极海冰会出现减少(增多),最佳影响时滞时间是从28个月至36个月左右。
为了更清楚地探讨热带海洋SST与北极海冰变化之间的关系,我们分析了3个热带海洋和全球热带海洋SST对北极海冰变化可能影响时间尺度和强度。图6是3个不同热带海洋区域平均SST以及全球热带海洋平均SST与北极海冰变化之间的时滞相关曲线。由图可以看出,3个热带海洋区域SST与北极海冰变化的最佳相关均呈负的相关关系(达到相关99.9%信度检验水平,下面类同)。热带大西洋影响海冰最早,其次是热带印度洋,最晚是热带中东太平洋。热带印度洋与北极海冰的关系最为显著,最大相关出现在北极海冰滞后30个月,最大相关系数是–0.35。其次是热带中东太平洋,最大相关是在北极海冰滞后34个月,最大相关系数是–0.25。热带大西洋相关关系最差,最大相关是在北极海冰滞后26个月,相关系数仅为–0.14。全球热带海洋SST的平均值与北极海冰的关系也呈负相关,最大相关是在北极海冰滞后33个月,最大相关系数是–0.27。这一结果表明,无论是热带印度洋,中东太平洋,大西洋区域的SST还是全球热带海洋的SST平均值均与北极海冰异常变化存在密切关系。
由上述分析可知,热带海洋SST与北极海冰变化存在密切关系。那么探求它们之间相联系的“纽带”,是解决热带海洋SST影响北极海冰变化的关键问题。为此,我们对可能与北极海冰变化有密切联系的大气环流模态北极涛动(AO)、太平洋–北美遥相关(PNA)和北大西洋涛动(NAO)进行分析探讨,试图揭示热带海洋对北极海冰影响的可能机理。
图7是AO、NAO和PNA与北极海冰的时滞相关曲线。可以看出,AO和NAO与北极海冰变化存在显著相关关系的时间是在北极海冰滞后的10个月和11 个月,呈负相关,最大相关系数分别是–0.29和–0.26。另外,AO与北极海冰变化还存在一个时滞32个月的弱正相关,相关系数是0.14。PNA与北极海冰变化之间最佳相关出现在后者滞后27个月,呈负相关关系。这种关系表明,北极海冰变化与AO、NAO和PNA存在密切关系,AO和NAO对北极海冰的影响要早于PNA。这一结果与前人所得结论一致[35-37]
大气环流模态AO、NAO和PNA均是反映大气经向气压差变化特征,与北极海冰变化均呈负相关,当AO、NAO和PNA 3个大气环流模态出现正(负)位相时,将会引起经向环流加强(减弱),中低纬度暖平流向极地输送热量偏多(偏少),极地区域气温偏高(偏低),北极海冰会出现偏少(偏多)。
由上述分析结果表明,北极海冰变化与大气环流模态AO、NAO和PNA存在密切关系,也就是说,AO、NAO和PNA对北极变化有重要贡献。由此可以认为,AO、NAO和PNA可能是热带海洋SST影响北极海冰变化的重要“纽带”。为了验证这一影响过程是否客观存在,我们对热带海洋SST与AO、NAO和PNA之间关系进行分析探讨。
图8是热带中东太平洋SST与AO和PNA的相关分析结果。可以看出,热带中东太平洋SST与AO存在两个显著相关过程,一个是短期时滞影响过程,为负相关,显著相关出现在AO滞后的3个月,最大相关系数是−0.24。另一个是长期时滞影响过程,为正相关,显著相关出现在AO滞后的24个月,最大相关系数是0.19。PNA与热带太平洋SST之间也存在密切关系,由图可以看出,热带中东太平洋SST与PNA也存在两个显著的相关过程,一个是短期时滞影响过程,为正相关,显著相关出现在PNA滞后的5个月,最大相关系数是0.56。另一个长期时滞影响过程为负相关,显著相关出现在PNA滞后30个月,最大相关系数是−0.20。以上相关系数均通过99.9%信度水平检验,对热带印度洋SST与AO和PNA进行相关分析,结果表明,AO与热带印度洋SST之间存在密切关系。由图9可以看出,热带印度洋SST对AO的最佳相关是出现在AO滞后的21个月,呈正相关关系,最大相关系数是0.33。该分析结果与未去倾的资料分析结果非常一致[29]。这一分析结果再次证明,无论是否去倾,热带印度洋SST对北极海冰的影响都是显著的。PNA与印度洋SST之间也存在显著的相关关系,最大相关出现在PNA滞后2个月,最大相关系数是0.53。另外,在时滞30个月后,还存在一个负相关时滞影响过程,最大相关系数是−0.23。
图10是热带大西洋SST与AO和NAO的时滞相关分析,由图可以看出,热带大西洋SST对AO的影响存在3个时滞相关过程,一个是同期为负相关,最大相关系数是−0.30;一个是最大时滞14个月,呈正相关,最大相关系数是0.16;最后一个是在时滞40个月以后,呈正相关,相关系数是0.19。这说明热带大西洋SST除了同期对AO存在负相关外,其后出现2次不同时滞时间的正相关。
热带大西洋SST与NAO的相关出现两个时间段,均呈负相关,一个是在同期,达到信度检验的相关持续时间是8个月,最大相关系数是−0.42;另一个时间段是出现在时滞21~34个月,持续时间长达14个月,最大相关系数是−0.23。这说明热带大西洋SST对NAO有两个时段的影响过程。
图11 是全球热带海洋SST与AO、PNA和NAO的时滞相关图。由图可以看出,全球热带海洋SST与AO和PNA的时滞相关与热带东太平洋和印度洋的相关变化特征基本一致。由此可以表明,在全球热带海洋对大气环流模态的影响过程中,热带印度洋和东太平洋起一定的主导作用。
由上述分析可知,当热带中东太平洋和印度洋SST出现正(负)异常时,均会导致AO和PNA出现正(负)位相,进而影响北极海冰减少(增加)。而热带大西洋SST出现正(负)异常时,会导致AO和NAO出现正(负)位相,致使北极海冰出现减少(增加)。热带中东太平洋和印度洋SST通过AO和PNA,最终导致北极海冰出现异常变化。它们之间的影响机理基本相同,所不同的是,前者主要是对中低纬度大气环流模态PNA产生影响,后者则主要是对中高纬度大气环流模态AO产生影响。而热带大西洋SST对AO和NAO具有相同的影响。当热带中东太平洋和热带印度洋SST出现正(负)异常时,经向环流加强(减弱),AO南支(30°~45°N)区域近海面气压升高(降低),AO出现正(负)位相,经向暖平流加强(减弱),北极地区气温偏高(低),最终导致北极海冰减少(增加)。相同原理,当热带中东太平洋和印度洋SST出现正(负)异常,副热带太平洋区域500 hPa位势高度增高(降低),PNA出现正(负)位相,经向环流加强(减弱),北向暖平流输送偏多(偏少),北极地区气温偏高(低),最终导致北极海冰出现偏少(偏多)。
同理,热带大西洋SST出现正(负)异常时,AO和NAO会出现正(负)位相,经向环流加强(减弱),北向暖平流输送偏多(少),北极地区气温会出现偏高(低),这将导致北极海冰融化(增加)。
由全球热带海洋平均SST对AO、PNA和NAO的影响来看,全球热带海洋SST与热带中东太平洋和印度洋SST对AO、PNA的影响时间尺度和强度基本一致。这说明,在全球热带海洋SST对北极海冰的影响过程中,热带太平洋和印度洋起主导作用。这一现象不难理解,ENSO事件就是热带东太平洋大尺度海洋相互作用的产物,是影响全球气候变化的重要过程。印度洋是夏季风暴发的关键海区和源地,因此,热带太平洋和印度洋在全球气候变化过程中是至关重要的。
全球热带海洋SST与北极海冰的最佳相关时间是33个月(负相关),而热带海洋SST与AO、PNA和NAO的最佳相关时间分别是25个月(负相关)、5个月(正相关)和25个月(正相关)。而AO、PNA和NAO与北极海冰的最佳相关时间分别是10个月(负相关)、27个月(负相关)和11个月(负相关)。由此可以确定,全球热带海洋SST通过影响PNA,进而对北极海冰的影响时间是32个月;全球热带海洋SST通过对AO影响,到最终影响北极海冰的时间是36个月;全球热带海洋SST对NAO的影响,以及NAO对北极海冰的影响时间是35个月。与全球热带海洋SST对北极海冰的影响时间(准3年)是吻合的。所以,我们认为这一相关分析结果表明,热带海洋SST异常与北极海冰变化之间存在非常确定的因果关系,其主要机理是,热带海洋通过大气环流模态AO、PNA和NAO作为桥梁或纽带(或称其为大气桥),进而影响北极海冰的异常变化,这一影响过程是可信的。
为了探究热带海洋SST影响北极海冰异常变化的途径,给出了热带海洋SST对北半球500 hPa位势高度场纬向平均的经向−时滞相关剖面图。 图12是热带海洋SST对北半球500 hPa位势高度场时滞相关剖面图。由图12a可以看出,热带海洋SST对北半球气压场的影响可以持续长达40多个月,显著影响时间是在3年左右。图12b反映的是热带海洋SST对中纬度(35°~50°N)的影响过程,热带海洋SST对中纬度气压场影响可以持续40个月,显著影响时间为3年左右。另外,还可以看出,热带海洋SST对北半球气压场的影响是以大约准3个月次季节–季节“波动”方式影响,达到95%信度的相关可以达到中高纬度。这一结果说明,热带海洋SST对北半球中高纬度气压场存在明显的影响过程,是影响大气模态AO、NAO和PNA变化的重要机制。
为了进一步揭示热带异常海温场对北极海冰影响的内在联系,我们选取了海温偏高年份(1957,1958,1963,1969,1972,1982,1983,1987,1997,1998,2015,2016)和偏低年份(1955,1956,1967,1971,1974,1975,1976,1985,1999,2000,2008,2011)各12年进行合成分析(图13),由图可以看出,当热带海洋SST异常偏低年滞后的两年,北半球500 hPa异常高度场是以极地为异常偏高,中纬度地区为异常偏低的分布特征(图13a),这一环流分布形似大气环流模态AO和NAO的负位相特征。而相对应的是北极海冰异常偏多(图13c)。热带海洋SST异常偏高年滞后两年的大气环流形势(图13b),主要是形似大气环流模态PNA和NAO的正位相特征,而对应的是北极海冰异常偏少(图13d)。这一合成分析结果说明,全球热带海洋SST出现正异常后,时滞两年后的大气环流模态PNA和NAO为正位相,对应的北极海冰出现偏少的趋势。而当热带海洋SST出现负异常时,时滞两年后的大气环流模态AO和NAO会出现负位相,对应的北极海冰出现偏多的趋势。
由此可以进一步说明,全球热带海洋SST的异常变化对北极海冰增多或减少具有重要作用,而其重要机理是,当热带海洋SST出现正异常时,通过对北半球中高纬度气压场的影响,进而引起大气环流模态PNA和NAO异常,最终导致北极海冰减少。同理,当热带海洋SST出现负异常时,通过对北半球中高纬度气压场的影响,大气环流模态AO和NAO出现异常,最终导致北极海冰出现偏多的趋势。在热带海洋与北极海冰变化过程中,热带海洋SST对北半球气压场产生影响,通过影响AO、PNA和NAO模态的异常转换,最终导致北极海冰的异常。
太平洋年代际振荡(PDO)和大西洋多年代际振荡(AMO)是北半球年代际和多年代际强且稳定的两大洋气压和海温变化信号,它们的异常变化对北半球长期气候变化存在重要影响。为更加清楚了解它们的长期变化特征,给出了去倾后的1951−2021年逐月变化曲线(图14)。由图可以看出,尽管它们二者分别表征了太平洋和大西洋的气压和海温振荡信号,但它们二者变化呈明显的反位相关系。由时滞相关分析可知(图15),太平洋年代际气压振荡(PDO)在长期变化过程中,受大西洋多年代际的海表温度振荡的影响比较明显。
PDO是太平洋年代际振荡的指数,它对环太平洋地区乃至全球气候变化具有重要影响。采用热带海洋1951−2021年共71年852个月的SSTA与PDO指数进行分析,结果发现,它们二者相关性非常密切,最佳相关出现在PDO滞后热带海洋SSTA的2个月,相关系数是0.56(图16a)。由此可以认为,热带海洋SSTA对PDO的影响明显,尤其是热带中东太平洋SSTA对PDO的相关更为密切,其相关系数为0.62。
由PDO与北极海冰的相关分析可以看出,PDO对北极海冰的影响主要是在北极海冰滞后的30个月,相关系数为–0.21,虽然这一相关达到99.9%的信度水平,但是与AO、NAO和PNA对北极海冰的影响程度相比还是偏弱。也就是说,在这些大气模态指数中,PDO对北极海冰的贡献较小。但值得指出的是,尽管PDO对北极海冰的影响偏弱,但是PDO受北极海冰的影响不可忽视,相关系数达到–0.32. 即当北极海冰出现偏多(少)时,PDO会出现偏弱(强)的趋势(图16b)。
由于PDO是非常强且稳定的太平洋年代际振荡指数,它可能会对其他大气模态指数具有一定影响。为了了解PDO与AO、NAO和PNA以及北极偶极子(Arctic Dipole)之间的联系,对其进行了分析。图17是PDO与它们之间时滞相关曲线。可以看出,PDO与AO、NAO和PNA以及北极偶极子均存在不同程度的相关关系。PDO与PNA的关系最为密切,最佳相关出现在同期,相关系数是0.53。其次是与北极偶极子和NAO的关系,其显著相关系数分别出现在北极偶极子和NAO滞后PDO 24个月和34个月,相关系数分别是0.35和0.33。PDO与AO的关系相比其他指数较差,最佳相关系数出现在同期和AO滞后PDO 21个月,相关系数分别是−0.22和0.18。这一结果表明,PNA、NAO和AO以及北极偶极子的变化均受到PDO不同程度的影响,但PNA、北极偶极子和NAO受影响比较显著。
图18是大西洋多年代际振荡(AMO)与大气模态AO、NAO和PNA以及北极偶极子的时滞相关分析。可以看出,AMO对大气模态也存在不同程度的影响,其对PNA和NAO的影响最为明显,最佳相关时间均在同期,相关系数为0.33和−0.34。AMO对AO和北极偶极子的影响相对弱一些,最佳相关出现在同期和北极偶极子 滞后18个月,相关系数分别是−0.19和0.17。这一分析结果表明,AMO对PNA和NAO的影响比较明显。
上述分析结果表明,太平洋年代际振荡(PDO)和大西洋多年代际振荡(AMO)对北半球大气模态AO、NAO和PNA以及北极偶极子均存在不同程度的影响,但对PNA和NAO的影响更加明显。对北极海冰变化起到纽带作用的大气模态AO、PNA和NAO不仅受热带海洋SSTA的影响,而且还受到太平洋年代际振荡PDO和大西洋多年代际AMO的影响,因此,在研究北极海冰异常变化过程中,PDO和AMO的作用需要考虑。另外,尽管北极偶极子模态只占总方差贡献的12.5%,但其对北极局地气候变化存在重要影响。由分析表明,热带海洋SST对北极偶极子异常没有明显的相关关系,但PDO对其存在重要影响。
以最新海洋和大气以及海冰数据为基础,通过统计分析方法,揭示了热带海洋SST变化对北极海冰存在影响的事实,给出了热带太平洋、印度洋和大西洋SST分别对北极海冰影响的差异,初步探讨了全球热带海洋SST对北极海冰的可能影响过程,这对北极海冰快速减少的深入研究以及预测具有重要参考意义。
(1)北极海冰年最大方差出现在大西洋扇区的格陵兰海和巴伦支海,另一个是北极太平洋扇区的东西伯利亚海、楚科奇海和拉普特夫海。
(2) 全球热带海洋SST与北极海冰变化之间存在较好的反位相变化,存在较稳定的准3年的相关关系。在全球热带海洋对北极海冰的影响过程中,热带太平洋、印度洋起主导作用。
(3)全球热带海洋SST对北极海冰的影响存在年际尺度(准3年)的影响过程,这种影响过程是热带海洋SST通过影响北半球中高纬度气压场变化,进而导致大气环流模态AO、NAO和PNA出现异常来实现,而大气环流模态是热带与极地相联系的中间桥梁或纽带。
(4)对北极海冰变化起重要作用的大气模态(AO、NAO和PNA)不仅受热带海洋SST的影响,而且同时也受太平洋年代际振荡(PDO)和大西洋多年代际(AMO)的影响。因此,在分析探讨北极海冰快速减少的过程中,应给予充分考虑。另外,对北极地区存在重要影响的北极偶极子异常对PDO也存在明显的响应过程,在未来中高纬度的海−气−冰相互作用过程的研究中,需要重视PDO的作用。
本文所得结果,是以真实数据为基础,采用统计分析方法所得,结论可靠,其目的就是揭示全球热带海洋对极地的可能影响及其途径,为深入探讨热带与极地大尺度海气相互作用过程提供参考。未来工作可以通过数值模拟给予进一步分析探讨。
  • 极地考察业务化与科研(2022)
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2022年第44卷第12期
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doi: 10.12284/hyxb2022163
  • 接收时间:2022-05-05
  • 首发时间:2026-02-01
  • 出版时间:2022-12-01
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  • 收稿日期:2022-05-05
  • 修回日期:2022-06-26
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极地考察业务化与科研(2022)
作者信息
    1.中国海洋大学 海洋与大气学院,山东 青岛 266100
    2.国家海洋环境预报中心,北京 100081

通讯作者:

孙启振(1984-),男,副研究员,主要从事极地气象和海冰研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
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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