Arctic sea ice in CMIP5 climate model projections and their seasonal variability

HUANG Fei; ZHOU Xiao; WANG Hong

doi:10.1007/s13131-017-1029-8

CMIP5气候模式模拟的北极海冰特征及其季节变化

doi: 10.1007/s13131-017-1029-8

黄菲^1,,
周晓²,
王宏²

1.
中国海洋大学物理海洋教育部重点实验室, 中国青岛, 266100;青岛海洋科学与技术国家实验室, 中国青岛, 266200;宁波大学宁波市非线性海洋和大气灾害系统协同创新中心, 中国宁波, 315211
2.
中国海洋大学物理海洋教育部重点实验室, 中国青岛, 266100;青岛海洋科学与技术国家实验室, 中国青岛, 266200

基金项目: The National Basic Research Program of China (973 Program) under contract No. 2015CB953904; the National Natural Science Foundation of China under contract No. 41575067.

计量
- 文章访问数: 1303
- HTML全文浏览量: 56
- PDF下载量: 1123
- 被引次数: 0
出版历程
- 收稿日期: 2016-04-03

Arctic sea ice in CMIP5 climate model projections and their seasonal variability

1.
Physical Oceanography Laboratory/CIMST, Ocean University of China, Qingdao 266100, China;Qingdao National Laboratory for Marine Science and Technology, Qingdao 266200, China;Ningbo Collabrative Innovation Center of Nonlinear Harzard System of Ocean and Atmosphere, Ningbo University, Ningbo 315211, China
2.
Physical Oceanography Laboratory/CIMST, Ocean University of China, Qingdao 266100, China;Qingdao National Laboratory for Marine Science and Technology, Qingdao 266200, China

摘要

摘要: 本文采用最新的CMIP5的模拟结果分析了1979-2100年北极海冰范围的季节变化特征，建立了一个新的用来比较31个CMIP5模式模拟和观测的北极海冰范围的判别方法。这个判别基于四个描述北极海冰特征的因子，即海冰范围的气候平均值、线性趋势、融冰期时长和年较差。这个方法非常客观，可以应用到类似的其他模式模拟结果的比较中去。基于上述标准挑选出6个对北极海冰变化特征模拟得比较好的模式（GFDL-CM3，CESM1-BGC，MPI-ESM-LR，ACCESS-1.0，HadGEM2-CC和HadGEM2-AO），并基于这六个模式结果的集合平均，我们发现北极海冰范围将在未来一百年继续减少，并在RCP4.5（RCP8.5）情景下于2065年（2053年）9月降到1百万平方千米以下（即无冰的北冰洋）。同时我们还研究了海冰范围的季节变化特征，发现到本世纪末北极的夏季融冰期在RCP4.5情景下将增加大约100天，在RCP8.5情景下则增加约200天，北极秋季的结冰期推迟和春季融冰期提前的非对称季节变化特征将在未来北极气候达到临界点时，即北极出现无冰的北冰洋时变得更加显著。海冰范围的季节变化振幅（季节性融冰范围）将在未来的30-40年里继续增大，表明夏季融冰越多，冬季结冰也越多，暗示了未来冬季或夏季可能会出现更多的极端天气气候事件的发生。
- 北极海冰 /
- CMIP5 /
- 季节循环 /
- 融冰季节 /
- 年较差
Abstract: This paper is focused on the seasonality change of Arctic sea ice extent (SIE) from 1979 to 2100 using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). A new approach to compare the simulation metric of Arctic SIE between observation and 31 CMIP5 models was established. The approach is based on four factors including the climatological average, linear trend of SIE, span of melting season and annual range of SIE. It is more objective and can be popularized to other comparison of models. Six good models (GFDL-CM3, CESM1-BGC, MPI-ESM-LR, ACCESS-1.0, HadGEM2-CC, and HadGEM2-AO in turn) are found which meet the criterion closely based on above approach. Based on ensemble mean of the six models, we found that the Arctic sea ice will continue declining in each season and firstly drop below 1 million km² (defined as the ice-free state) in September 2065 under RCP4.5 scenario and in September 2053 under RCP8.5 scenario. We also study the seasonal cycle of the Arctic SIE and find out the duration of Arctic summer (melting season) will increase by about 100 days under RCP4.5 scenario and about 200 days under RCP8.5 scenario relative to current circumstance by the end of the 21st century. Asymmetry of the Arctic SIE seasonal cycle with later freezing in fall and early melting in spring, would be more apparent in the future when the Arctic climate approaches to "tipping point", or when the ice-free Arctic Ocean appears. Annual range of SIE (seasonal melting ice extent) will increase almost linearly in the near future 30-40 years before the Arctic appears ice-free ocean, indicating the more ice melting in summer, the more ice freezing in winter, which may cause more extreme weather events in both winter and summer in the future years.
- Arctic sea ice /
- CMIP5 /
- seasonal cycle /
- melting season /
- annual range

HTML全文

参考文献(30)

Barron E J. 1983. A warm, equable cretaceous:the nature of the problem. Earth Sci Rev, 19(4):305-338

Bekryaev R V, Polyakov I V, Alexeev V A. 2010. Role of polar amplification in long-term surface air temperature variations and modern arctic warming. J Climate, 23(14):3888-3906

Cavalieri D J, Gloersen P, Parkinson C L, et al. 1997. Observed hemispheric asymmetry in global sea ice changes. Science, 278(5340):1104-1106

Cavalieri D J, Parkinson C L, Gloersen P, et al. 1999. Deriving long-term time series of sea ice cover from satellite passive-microwave multisensor data sets. J Geophys Res, 104(C7):15803-15814

Chapman W L, Walsh J E. 1993. Recent variations of sea ice and air temperature in high latitudes. Bull Am Meteorol Soc, 74(1):33-48

Comiso J C, Parkinson C L, Gersten R, et al. 2008. Accelerated decline in the Arctic sea ice cover. Geophys Res Lett, 35(1):L01703

Easterling D R, Wehner M F. 2009. Is the climate warming or cooling?. Geophys Res Lett, 36(8):L08706

Francis J A, Vavrus S J. 2012. Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys Rev Lett, 39(6):L06801

Francis J A, Vavrus S J. 2015. Evidence for a wavier jet stream in response to rapid Arctic warming. Environ Res Lett, 10(1):014005

Holland M M, Bitz C M. 2003. Polar amplification of climate change in coupled models. Clim Dynam, 21(3-4):221-232

Huang Fei, Di Hui, Hu Beibei, et al. 2014. Decadal regime shift of Arctic sea ice and corresponding changes of extreme low temperature. Clim Change Res Lett (in Chinese), 3(2):39-45

Huang Fei, Shan Xiaolin, Fan Tingting. 2011. Decadal change of annual range for the Arctic sea ice in recent 30 years. In:Proceedings of the 21st International Offshore and Polar Engineering Conference. Maui, Hawaii, USA:International Society of Offshore and Polar Engineers, 978-985

Kosaka Y, Xie S P. 2013. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature, 501(7467):403-407

Lenton T M. 2012. Arctic climate tipping points. AMBIO, 41(1):10-22

Liu Jiping, Curry J, Wang Huijun, et al. 2012. Impact of declining Arctic sea ice on winter snowfall. Proc Natl Acad Sci U S A, 109(11):4074-4079

Liu Jiping, Song Mirong, Horton R M, et al. 2013. Reducing spread in climate model projections of a September ice-free Arctic. Proc Natl Acad Sci U S A, 110(31):12571-12576

Lu Jianhua, Cai Ming. 2009. Seasonality of polar surface warming amplification in climate simulations. Geophys Res Lett, 36(16):L16704

Manabe S, Wetherald R T. 1975. The effects of doubling the CO₂ concentration on the climate of a general circulation model. J Atmos Sci, 32(1):3-15

Masson-Delmotte V, Kageyama M, Braconnot P, et al. 2006. Past and future polar amplification of climate change:climate model intercomparisons and ice-core constraints. Climate Dyn, 26(5):513-529

Niu Lu, Huang Fei, Zhou Xiao. 2015. Decadal regime shift of Arctic sea ice and associated decadal variability of Chinese freezing rain. Haiyang Xuebao (in Chinese), 37(11):105-117

Parkinson C L, Cavalieri D J, Gloersen P, et al. 1999. Arctic sea ice extents, areas, and trends, 1978-1996. J Geophys Res, 104(C9):20837-20856

Polyakov I V, Alekseev G V, Bekryaev R V, et al. 2002. Observationally based assessment of polar amplification of global warming. Geophys Res Lett, 29(18):25-1-25-4

Screen J A, Simmonds I. 2010. The central role of diminishing sea ice in recent arctic temperature amplification. Nature, 464(7293):1334-1337

Serreze M C, Barry R G. 2011. Processes and impacts of Arctic amplification:a research synthesis. Glob Planetary Change, 77(1-2):85-96

Serreze M C, Francis J A. 2006. The Arctic amplification debate. Climate Change, 76(3-4):241-264

Serreze M C, Holl M M, Stroeve J. 2007. Perspectives on the Arctic's shrinking sea-ice cover. Science, 315(5818):1533-1536

Stroeve J, Holland M M, Meier W, et al. 2007. Arctic sea ice decline:faster than forecast. Geophys Res Lett, 34(9):L09501

Wadhams P. 2012. Arctic ice cover, ice thickness and tipping points. AMBIO, 41(1):23-33

Wang Hong, Zhou Xiao, Huang Fei. 2015. Response of dominant mode for atmospheric circulation in northern hemisphere to the accelerated decline of Arctic sea ice:I. The Arctic Oscillation. Haiyang Xuebao (in Chinese), 37(11):57-67

Zhu Chenyu, Huang Fei, Shi Yunhao, et al. 2014. Spatial-temporal patterns of the cold surge events in China in recent 50 years and its relationship with Arctic sea ice. Period Ocean Univ China, 44(12):12-20

施引文献

资源附件(0)

访问统计

点击查看大图

计量

文章访问数: 1303
HTML全文浏览量: 56
PDF下载量: 1123
被引次数: 0

CMIP5气候模式模拟的北极海冰特征及其季节变化

doi: 10.1007/s13131-017-1029-8

计量

出版历程

Arctic sea ice in CMIP5 climate model projections and their seasonal variability

计量

出版历程

目录