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Assessment of Arctic sea ice simulations in CMIP5 models using a synthetical skill scoring method

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Abstract

The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.

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References

  • Alexeev V A, Langen P L, Bates J R. 2005. Polar amplification of surface warming on an aquaplanet in “ghost forcing” experiments without sea ice feedbacks. Climate Dynamics, 24(7–8): 655–666, doi: 10.1007/s00382-005-0018-3

    Article  Google Scholar 

  • Arzel O, Fichefet T, Goosse H. 2006. Sea ice evolution over the 20th and 21st centuries as simulated by current AOGCMs. Ocean Modelling, 12(3–4): 401–415, doi: 10.1016/j.ocemod.2005. 08.002

    Article  Google Scholar 

  • Bengtsson L, Semenov V A, Johannessen O M. 2004. The early twentieth-century warming in the Arctic—a possible mechanism. Journal of Climate, 17(20): 4045–4057, doi: 10.1175/1520-0442(2004)017<4045:TETWIT>2.0.CO;2

    Article  Google Scholar 

  • Chapman W L, Walsh J E. 2007. Simulations of arctic temperature and pressure by global coupled models. Journal of Climate, 20(4): 609–632, doi: 10.1175/jcli4026.1

    Article  Google Scholar 

  • Deser C, Tomas R, Alexander M, et al. 2010. The seasonal atmospheric response to projected Arctic sea ice loss in the late twenty-first century. Journal of Climate, 23(2): 333–351, doi: 10.1175/2009JCLI3053.1

    Article  Google Scholar 

  • Eyring V, Arblaster J M, Cionni I, et al. 2013. Long-term ozone changes and associated climate impacts in CMIP5 simulations. Journal of Geophysical Research: Atmospheres, 118(10): 5029–5060, doi: 10.1002/jgrd.50316

    Google Scholar 

  • Francis J A, Chan Weihan, Leathers D J, et al. 2009. Winter Northern Hemisphere weather patterns remember summer Arctic sea-ice extent. Geophysical Research Letters, 36(7): L07503, doi: 10.1029/2009gl037274

    Article  Google Scholar 

  • Francis J A, Vavrus S J. 2012. Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophysical Research Letters, 39(6): L06801, doi: 10.1029/2012gl051000

    Article  Google Scholar 

  • Graversen R G, Mauritsen T, Tjernström M, et al. 2008. Vertical structure of recent Arctic warming. Nature, 451(7174): 53–56, doi: 10.1038/nature06502

    Article  Google Scholar 

  • Holland M M, Bitz C M. 2003. Polar amplification of climate change in coupled models. Climate Dynamics, 21(3–4): 221–232, doi: 10.1007/s00382-003-0332-6

    Article  Google Scholar 

  • Huang Fei, Zhou Xiao, Wang Hong. 2017. Arctic sea ice in CMIP5 climate model projections and their seasonal variability. Acta Oceanologica Sinica, 36(8): 1–8, doi: 10.1007/s13131-017-1029-8

    Article  Google Scholar 

  • Kim K Y, Hamlington B D, Na Hanna, et al. 2016. Mechanism of seasonal Arctic sea ice evolution and Arctic amplification. The Cryosphere, 10(5): 2191–2202, doi: 10.5194/tc-10-2191-2016

    Article  Google Scholar 

  • Lamarque J F, Bond T C, Eyring V, et al. 2010. Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmospheric Chemistry and Physics, 10(15): 7017–7039, doi: 10.5194/acpd-10-4963-2010

    Article  Google Scholar 

  • Lamarque J F, Kyle G P, Meinshausen M, et al. 2011. Global and regional evolution of short-lived radiatively-active gases and aerosols in the Representative Concentration Pathways. Climate Change, 109: 191–212, doi: 10.1007/s10584-011-0155-0

    Article  Google Scholar 

  • Li Dawei, Zhang Rong, Knutson T R. 2017. On the discrepancy between observed and CMIP5 multi-model simulated Barents Sea winter sea ice decline. Nature Communications, 8: 14991, doi: 10.1038/ncomms14991

    Article  Google Scholar 

  • Liu Jiping, Song Mirong, Horton R M, et al. 2013. Reducing spread in climate model projections of a September ice-free Arctic. Proceedings of the National Academy of Sciences of the United States of America, 110(31): 12571–12576, doi: 10.1073/pnas. 1219716110

    Article  Google Scholar 

  • Maslowski W, Clement K J, Higgins M, et al. 2012. The future of Arctic sea ice. Annual Review of Earth and Planetary Sciences, 40: 625–654, doi: 10.1146/annurev-earth-042711-105345

    Article  Google Scholar 

  • Massonnet F, Fichefet T, Goosse H, et al. 2012. Constraining projections of summer Arctic sea ice. The Cryosphere, 6(6): 1383–1394, doi: 10.5194/tc-6-1383-2012

    Article  Google Scholar 

  • Overland J E, Adams J M, Bond N A. 1997. Regional variation of winter temperatures in the Arctic. Journal of Climate, 10(5): 821–837, doi: 10.1175/1520-0442(1997)010<0821:RVOWTI>2.0.CO;2

    Article  Google Scholar 

  • Petoukhov V, Semenov V A. 2010. A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. Journal of Geophysical Research: Atmospheres, 115(D21): D21111, doi: 10.1029/2009jd013568

    Article  Google Scholar 

  • Rayner N A, Parker D E, Horton E B, et al. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research: Atmospheres, 108(D14): 1063–1082, doi: 10.1029/2002JD002670

    Article  Google Scholar 

  • Rogers K G, Goodbred S L Jr, Mondal D R. 2013. Monsoon sedimentation on the ‘abandoned’ tide-influenced Ganges-Brahmaputra delta plain. Estuarine, Coastal and Shelf Science, 131: 297–309, doi: 10.1016/j.ecss.2013.07.014

    Article  Google Scholar 

  • Rosenblum E, Eisenman I. 2016. Faster Arctic sea ice retreat in CMIP5 than in CMIP3 due to volcanoes. Journal of Climate, 29(24): 9179–9188, doi: 10.1175/JCLI-D-16-0391.1

    Article  Google Scholar 

  • Ruggieri P, Buizza R, Visconti G. 2016. On the link between Barents-Kara sea ice variability and European blocking. Journal of Geophysical Research: Atmospheres, 121(10): 5664–5679, doi: 10.1002/2015jd024021

    Google Scholar 

  • Screen J A, Simmonds I. 2010a. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464(7293): 1334–1337, doi: 10.1038/nature09051

    Article  Google Scholar 

  • Screen J A, Simmonds I. 2010b. Increasing fall-winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification. Geophysical Research Letters, 37(16): L16707, doi: 10.1029/2010GL044136

    Article  Google Scholar 

  • Semenov M A. 2008. Simulation of extreme weather events by a stochastic weather generator. Climate Research, 35(3): 203–212, doi: 10.3354/cr00731

    Article  Google Scholar 

  • Semenov V A, Bengtsson L. 2003. Modes of the wintertime Arctic temperature variability. Geophysical Research Letters, 30(15): 1787, doi: 10.1029/2003gl017112

    Article  Google Scholar 

  • Semenov M A, Halford N G. 2009. Identifying target traits and molecular mechanisms for wheat breeding under a changing climate. Journal of Experimental Botany, 60(10): 2791–2804, doi: 10.1093/jxb/erp164

    Article  Google Scholar 

  • Semenov V A, Martin T, Behrens L K, et al. 2015. Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles — variability and change. The Cryosphere Discussions, 9(1): 1077–1131, doi: 10.5194/tcd-9-1077-2015

    Article  Google Scholar 

  • Serreze M, Barrett A, Stroeve J, et al. 2009. The emergence of surface-based Arctic amplification. The Cryosphere, 3: 11–19, doi: 10.5194/tc-3-11-2009

    Article  Google Scholar 

  • Shu Qi, Song Zhenya, Qiao Fangli. 2015. Assessment of sea ice simulations in the CMIP5 models. The Cryosphere, 9(1): 399–409, doi: 10.5194/tc-9-399-2015

    Article  Google Scholar 

  • Sigmond M, Fyfe J C. 2010. Has the ozone hole contributed to increased Antarctic sea ice extent?. Geophysical Research Letters, 37(18): L18520, doi: 10.1029/2010gl044301

    Article  Google Scholar 

  • Smedsrud L H, Esau I, Ingvaldsen R B, et al. 2013. The role of the Barents Sea in the Arctic climate system. Review of Geophysics, 51(3): 415–449, doi: 10.1002/rog.20017

    Article  Google Scholar 

  • Stroeve J C, Notz D. 2015. Insights on past and future sea-ice evolution from combining observations and models. Global and Planetary Change, 135: 119–132, doi: 10.1016/j.gloplacha. 2015.10.011

    Article  Google Scholar 

  • Stroeve J C, Serreze M C, Holland M M, et al. 2012. The Arctic’s rapidly shrinking sea ice cover: a research synthesis. Climatic Change, 110(3–4): 1005–1027, doi: 10.1007/s10584-011-0101-1

    Article  Google Scholar 

  • Taylor K E, Stouffer R J, Meehl G A. 2012. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4): 485–498, doi: 10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  • Turner J, Comiso J C, Marshall G J, et al. 2009. Non-annular atmospheric circulation change induced by stratospheric ozone depletion and its role in the recent increase of Antarctic sea ice extent. Geophysical Research Letters, 36(8): L08502, doi: 10.1029/2009GL037524

    Article  Google Scholar 

  • Venegas S A, Mysak L A. 2000. Is there a dominant timescale of natural climate variability in the Arctic?. Journal of Climate, 13(19): 3412–3434, doi: 10.1175/1520-0442(2000)013<3412:ITADTO>2.0.CO;2

    Article  Google Scholar 

  • Walsh J E. 2014. Intensified warming of the Arctic: Causes and impacts on middle latitudes. Global and Planetary Change, 117: 52–63, doi: 10.1016/j.gloplacha.2014.03.003

    Article  Google Scholar 

  • Warner J C, Geyer W R, Lerczak J A. 2005. Numerical modeling of an estuary: A comprehensive skill assessment. Journal of Geophysical Research: Oceans, 110(C5): C05001, doi: 10.1029/2004JC002691

    Article  Google Scholar 

  • Willmott C J. 1981. On the validation of models. Physical Geography, 2(2): 184–194, doi: 10.1080/02723646.1981.10642213

    Article  Google Scholar 

  • Yang Xiaoyi, Yuan Xiaojun. 2014. The early winter sea ice variability under the recent Arctic climate shift. Journal of Climate, 27(13): 5092–5110, doi: 10.1175/jcli-d-13-00536.1

    Article  Google Scholar 

  • Yang Xiaoyi, Yuan Xiaojun, Ting Mingfang. 2016. Dynamical link between the Barents-Kara sea ice and the Arctic Oscillation. Journal of Climate, 29: 5103–5122, doi: 10.1175/JCLI-D-15-0669.1

    Article  Google Scholar 

  • Zhang Xiangdong, Walsh J E. 2006. Toward a seasonally ice-covered Arctic Ocean: Scenarios from the IPCC AR4 model simulations. Journal of Climate, 19(9): 1730–1747, doi: 10.1175/JCLI3767.1

    Article  Google Scholar 

  • Zunz V, Goosse H, Massonnet F. 2013. How does internal variability influence the ability of CMIP5 models to reproduce the recent trend in Southern Ocean sea ice extent?. The Cryosphere, 7(2): 451–468, doi: 10.5194/tc-7-451-2013

    Article  Google Scholar 

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Acknowledgements

We acknowledge the climate modelling groups, the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling (WGCM), and the Met Office Hadley Centre’s sea ice for the open datasets used in this study.

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Authors and Affiliations

  1. State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China

    Liping Wu, Xiao-Yi Yang & Jianyu Hu

  2. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China

    Jianyu Hu

Authors
  1. Liping Wu
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  2. Xiao-Yi Yang
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Corresponding author

Correspondence to Xiao-Yi Yang.

Additional information

Foundation item: The National Natural Science Foundation of China under contract Nos 41576178 and 41630963; the National Basic Research Program (973 program) of China under contract No. 2015CB954004.

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Wu, L., Yang, XY. & Hu, J. Assessment of Arctic sea ice simulations in CMIP5 models using a synthetical skill scoring method. Acta Oceanol. Sin. 38, 48–58 (2019). https://doi.org/10.1007/s13131-019-1474-0

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