9月北极海冰变率模态:驱动因素及其对海冰趋势和极端的贡献

M. Karami, T. Koenigk, B. Tremblay
{"title":"9月北极海冰变率模态:驱动因素及其对海冰趋势和极端的贡献","authors":"M. Karami, T. Koenigk, B. Tremblay","doi":"10.1088/2752-5295/accbe3","DOIUrl":null,"url":null,"abstract":"The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Variability modes of September Arctic sea ice: drivers and their contributions to sea ice trend and extremes\",\"authors\":\"M. Karami, T. Koenigk, B. Tremblay\",\"doi\":\"10.1088/2752-5295/accbe3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.\",\"PeriodicalId\":432508,\"journal\":{\"name\":\"Environmental Research: Climate\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Research: Climate\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/2752-5295/accbe3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Research: Climate","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2752-5295/accbe3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在人为强迫海冰减少的过程中,9月份北极海冰在年际到几十年时间尺度上的变率尚不完全清楚。了解北极海冰在不同时间尺度上的变化,对于更好地预测未来海冰状况和将外部强迫信号与内部变化区分开至关重要。本文采用时频分析方法,研究了100-150年北极海冰9月份的变率、极端事件和趋势模式。我们提取了海冰面积的非线性趋势,并提供了在20世纪80年代由人为变暖驱动的海冰损失的估估,其速率为每10年~ - 25万平方公里,并在2010年代加速到每10年~ - 47万平方公里。假设未来海冰损失的加速速度相同,并排除内部变率和反馈的贡献,北极可能在2060年左右出现9月无冰。结果还表明,由于内部变率引起的海冰变化几乎与强迫变化一样大。我们发现海冰变率的主要模态周期约为3、6、18、27和55年,并显示了它们对海冰变率和极值的贡献。海冰模态的主要大气和海洋驱动因子包括3年模态的北极涛动和北极偶极子异常、6年模态的墨西哥湾流海温变率、18年模态的北大西洋北部海温年代际变率、27年模态的太平洋年代际涛动和55年模态的大西洋多年代际涛动。最后,我们的分析表明,在1996年(极高)和2007年(极低)两个极端情况之间,超过70%的海冰面积损失是由内部变率引起的,其中一半的变率与年代际模态有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Variability modes of September Arctic sea ice: drivers and their contributions to sea ice trend and extremes
The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km2 per decade in the 1980s and accelerating to ∼−0.47 million km2 per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信