• Allen, M. R., and S. F. B. Tett, 1999: Checking for model consistency in optimal fingerprinting. Climate Dyn., 15, 419434, doi:10.1007/s003820050291.

    • Search Google Scholar
    • Export Citation
  • Allen, M. R., and P. A. Stott, 2003: Estimating signal amplitudes in optimal fingerprinting, part I: Theory. Climate Dyn., 21, 477491, doi:10.1007/s00382-003-0313-9.

    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and Coauthors, 2011: Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett., 38, L05805, doi:10.1029/2010GL046270.

    • Search Google Scholar
    • Export Citation
  • Bindoff, N. L., and Coauthors, 2013: Detection and attribution of climate change: From global to regional. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 867–952. [Available online at https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter10_FINAL.pdf.]

  • Cannon, A. J., 2015: Selecting GCM scenarios that span the range of changes in a multimodel ensemble: Application to CMIP5 climate extremes indices. J. Climate, 28, 12601267, doi:10.1175/JCLI-D-14-00636.1.

    • Search Google Scholar
    • Export Citation
  • Christiansen, B., 2015: The role of the selection problem and non-Gaussianity in attribution of single events to climate change. J. Climate, 28, 98739891, doi:10.1175/JCLI-D-15-0318.1.

    • Search Google Scholar
    • Export Citation
  • Christidis, N., P. A. Stott, G. S. Jones, H. Shiogama, T. Nozawa, and J. Luterbacher, 2012: Human activity and anomalously warm seasons in Europe. Int. J. Climatol., 32, 225239, doi:10.1002/joc.2262.

    • Search Google Scholar
    • Export Citation
  • Christidis, N., P. A. Stott, A. A. Scaife, A. Arribas, G. S. Jones, D. Copsey, J. R. Knight, and W. J. Tennant, 2013: A new HadGEM3-A-based system for attribution of weather- and climate-related extreme events. J. Climate, 26, 27562783, doi:10.1175/JCLI-D-12-00169.1.

    • Search Google Scholar
    • Export Citation
  • Christidis, N., G. S. Jones, and P. A. Stott, 2015: Dramatically increasing chance of extremely hot summers since the 2003 European heatwave. Nat. Climate Change, 5, 4650, doi:10.1038/nclimate2468.

    • Search Google Scholar
    • Export Citation
  • Cody, W. J., 1993: Algorithm 715: SPECFUN—A portable FORTRAN package of special function routines and test drivers. ACM Trans. Math. Software, 19, 2232, doi:10.1145/151271.151273.

    • Search Google Scholar
    • Export Citation
  • Collins, M., and Coauthors, 2013: Long-term climate change: Projections, commitments and irreversibility. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 1029–1136. [Available online at http://www.climatechange2013.org/images/report/WG1AR5_Chapter12_FINAL.pdf.]

  • Comiso, J. C., C. L. Parkinson, R. Gersten, and L. Stock, 2008: Accelerated decline in the Arctic sea ice cover. Geophys. Res. Lett., 35, L01703, doi:10.1029/2007GL031972.

    • Search Google Scholar
    • Export Citation
  • Day, J. J., J. C. Hargreaves, J. D. Annan, and A. Abe-Ouchi, 2012: Sources of multi-decadal variability in Arctic sea ice extent. Environ. Res. Lett., 7, 034011, doi:10.1088/1748-9326/7/3/034011.

    • Search Google Scholar
    • Export Citation
  • Dufresne, J.-L., and Coauthors, 2013: Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, doi:10.1007/s00382-012-1636-1.

    • Search Google Scholar
    • Export Citation
  • Fetterer, F., K. Knowles, W. Meier, and M. Savoie, 2002: Sea Ice Index. National Snow and Ice Data Center, accessed 16 September 2015, doi:10.7265/N5QJ7F7W.

  • Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 741–866, doi:10.1017/CBO9781107415324.020.

  • Gillett, N. P., M. F. Wehner, S. F. B. Tett, and A. J. Weaver, 2004: Testing the linearity of the response to combined greenhouse gas and sulfate aerosol forcing. Geophys. Res. Lett., 31, L14201, doi:10.1029/2004GL020111.

    • Search Google Scholar
    • Export Citation
  • Gillett, N. P., D. A. Stone, P. A. Stott, T. Nozawa, A. Y. Karpechko, G. C. Hegerl, M. F. Wehner, and P. D. Jones, 2008: Attribution of polar warming to human influence. Nat. Geosci., 1, 750754, doi:10.1038/ngeo338.

    • Search Google Scholar
    • Export Citation
  • Goldstein, M., and J. Rougier, 2009: Reified Bayesian modelling and inference for physical systems. J. Stat. Plann. Inference, 139, 12211239, doi:10.1016/j.jspi.2008.07.019.

    • Search Google Scholar
    • Export Citation
  • Gregory, J. M., P. A. Stott, D. J. Cresswell, N. A. Rayner, C. Gordon, and D. M. H. Sexton, 2002: Recent and future changes in Arctic sea ice simulated by the HadCM3 AOGCM. Geophys. Res. Lett., 29, 2175, doi:10.1029/2001GL014575.

    • Search Google Scholar
    • Export Citation
  • Guemas, V., F. Doblas-Reyes, A. Germe, M. Chevallier, and D. Salas y Mélia, 2013: Discriminating between sea ice memory, the August 2012 extreme storm, and prevailing warm conditions [in “Explaining Extreme Events of 2012 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 94, S20S22.

    • Search Google Scholar
    • Export Citation
  • Hannart, A., J. Pearl, F. E. L. Otto, P. Naveau, and M. Ghil, 2016: Causal counterfactual theory for the attribution of weather and climate-related events. Bull. Amer. Meteor. Soc., 97, 99110, doi:10.1175/BAMS-D-14-00034.1.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and Coauthors, 2013: Observations: Atmosphere and surface. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 159–254. [Available online at http://www.climatechange2013.org/images/report/WG1AR5_Chapter02_FINAL.pdf.]

  • Hegerl, G. C., and F. Zwiers, 2011: Use of models in detection and attribution of climate change. Wiley Interdiscip. Rev.: Climate Change, 2, 570591, doi:10.1002/wcc.121.

    • Search Google Scholar
    • Export Citation
  • Hegerl, G. C., and Coauthors, 2010: Good practice guidance paper on detection and attribution related to anthropogenic climate change. Meeting Report of the Intergovernmental Panel on Climate Change Expert Meeting on Detection and Attribution of Anthropogenic Climate Change, T. F. Stocker et al., Eds., 9 pp. [Available online at http://www.ipcc-wg2.gov/meetings/EMs/IPCC_D%26A_GoodPracticeGuidancePaper.pdf.]

  • Herring, S., M. Hoerling, J. Kossin, T. Peterson, and P. Stott, Eds., 2015: Explaining extreme events of 2014 from a climate perspective. Bull. Amer. Meteor. Soc., 96 (Suppl.), S1S172, doi:10.1175/BAMS-ExplainingExtremeEvents2014.1.

    • Search Google Scholar
    • Export Citation
  • Hulme, M., 2014: Attributing weather extremes to ‘climate change’: A review. Prog. Phys. Geogr., 38, 499511, doi:10.1177/0309133314538644.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2014: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Cambridge University Press, 688 pp.

  • Jahn, A., and Coauthors, 2012: Late-twentieth-century simulation of Arctic sea ice and ocean properties in the CCSM4. J. Climate, 25, 14311452, doi:10.1175/JCLI-D-11-00201.1.

    • Search Google Scholar
    • Export Citation
  • Kay, J. E., M. M. Holland, and A. Jahn, 2011: Inter-annual to multi-decadal Arctic sea ice extent trends in a warming world. Geophys. Res. Lett., 38, L15708, doi:10.1029/2011GL048008.

    • Search Google Scholar
    • Export Citation
  • Kay, J. E., and Coauthors, 2015: The Community Earth System Model (CESM) Large Ensemble Project: A community resource for studying climate change in the presence of internal climate variability. Bull. Amer. Meteor. Soc., 96, 13331349, doi:10.1175/BAMS-D-13-00255.1.

    • Search Google Scholar
    • Export Citation
  • Lutz, A., H. ter Maat, H. Biemans, A. Shrestha, P. Wester, and W. Immerzeel, 2016: Selecting representative climate models for climate change impact studies: An advanced envelope-based selection approach. Int. J. Climatol., 36, 39884005, doi:10.1002/joc.4608.

    • Search Google Scholar
    • Export Citation
  • Massonnet, F., T. Fichefet, H. Goosse, C. M. Bitz, G. Philippon-Berthier, M. M. Holland, and P. Y. Barriat, 2012: Constraining projections of summer Arctic sea ice. Cryosphere, 6, 13831394, doi:10.5194/tc-6-1383-2012.

    • Search Google Scholar
    • Export Citation
  • Min, S. K., X. Zhang, F. W. Zwiers, and T. Agnew, 2008: Human influence on Arctic sea ice detectable from early 1990s onwards. Geophys. Res. Lett., 35, L21701, doi:10.1029/2008GL035725.

    • Search Google Scholar
    • Export Citation
  • Mitchell, J. F. B., D. J. Karoly, G. C. Hegerl, F. W. Zwiers, M. R. Allen, and J. Marengo, 2001: Detection of climate change and attribution of causes. Climate Change 2001: The Scientific Basis, Cambridge University Press, 697–738.

  • Najafi, M. R., F. W. Zwiers, and N. P. Gillett, 2015: Attribution of Arctic temperature change to greenhouse-gas and aerosol influences. Nat. Climate Change, 5, 246249, doi:10.1038/nclimate2524.

    • Search Google Scholar
    • Export Citation
  • NASEM, 2016: Attribution of Extreme Weather Events in the Context of Climate Change. The National Academies Press, 186 pp., doi:10.17226/21852.

  • Notz, D., and J. Marotzke, 2012: Observations reveal external driver for Arctic sea-ice retreat. Geophys. Res. Lett., 39, L08502, doi:10.1029/2012GL051094.

    • Search Google Scholar
    • Export Citation
  • Otto, F. E. L., N. Massey, G. J. Van Oldenborgh, R. G. Jones, and M. R. Allen, 2012: Reconciling two approaches to attribution of the 2010 Russian heat wave. Geophys. Res. Lett., 39, L04702, doi:10.1029/2011GL050422.

    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., M. P. Hoerling, P. A. Stott, and S. C. Herring, Eds., 2013: Explaining extreme events of 2012 from a climate perspective. Bull. Amer. Meteor. Soc., 94 (Suppl.), S1S74, doi:10.1175/BAMS-D-13-00085.1.

    • Search Google Scholar
    • Export Citation
  • Ribes, A., S. Planton, and L. Terray, 2013: Application of regularised optimal fingerprinting to attribution. Part I: Method, properties and idealised analysis. Climate Dyn., 41, 28172836, doi:10.1007/s00382-013-1735-7.

    • Search Google Scholar
    • Export Citation
  • Rougier, J., M. Goldstein, and L. House, 2013: Second-order exchangeability analysis for multimodel ensembles. J. Amer. Stat. Assoc., 108, 852863, doi:10.1080/01621459.2013.802963.

    • Search Google Scholar
    • Export Citation
  • Sato, M., J. E. Hansen, M. P. McCormick, and J. B. Pollack, 1993: Stratospheric aerosol optical depths, 1850–1990. J. Geophys. Res., 98, 22 98722 994, doi:10.1029/93JD02553.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., and R. G. Barry, 2011: Processes and impacts of Arctic amplification: A research synthesis. Global Planet. Change, 77, 8596, doi:10.1016/j.gloplacha.2011.03.004.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., M. M. Holland, and J. Stroeve, 2007: Perspectives on the Arctic’s shrinking sea-ice cover. Science, 315, 15331536, doi:10.1126/science.1139426.

    • Search Google Scholar
    • Export Citation
  • Shepherd, T. G., 2016: A common framework for approaches to extreme event attribution. Curr. Climate Change Rep., 2, 2838, doi:10.1007/s40641-016-0033-y.

    • Search Google Scholar
    • Export Citation
  • Shu, Q., Z. Song, and F. Qiao, 2015: Assessment of sea ice simulations in the CMIP5 models. Cryosphere, 9, 399409, doi:10.5194/tc-9-399-2015.

    • Search Google Scholar
    • Export Citation
  • Stone, D. A., and M. R. Allen, 2005: The end-to-end attribution problem: From emissions to impacts. Climatic Change, 71, 303318, doi:10.1007/s10584-005-6778-2.

    • Search Google Scholar
    • Export Citation
  • Stott, P. A., D. A. Stone, and M. R. Allen, 2004: Human contribution to the European heatwave of 2003. Nature, 432, 610614, doi:10.1038/nature03089.

    • Search Google Scholar
    • Export Citation
  • Stott, P. A., N. P. Gillett, G. C. Hegerl, D. J. Karoly, D. A. Stone, X. Zhang, and F. Zwiers, 2010: Detection and attribution of climate change: A regional perspective. Wiley Interdiscip. Rev.: Climate Change, 1, 192211, doi:10.1002/wcc.34.

    • Search Google Scholar
    • Export Citation
  • Stott, P. A., and Coauthors, 2016: Attribution of extreme weather and climate-related events. Wiley Interdiscip. Rev.: Climate Change, 7, 2341, doi:10.1002/wcc.380.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., M. M. Holland, W. Meier, T. Scambos, and M. Serreze, 2007: Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett., 34, L09501, doi:10.1029/2007GL029703.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., M. Serreze, S. Drobot, S. Gearheard, M. Holland, J. Maslanik, W. Meier, and T. Scambos, 2008: Arctic sea ice extent plummets in 2007. Eos, Trans. Amer. Geophys. Union, 89, 1314, doi:10.1029/2008EO020001.

    • Search Google Scholar
    • Export Citation
  • Sun, Y., X. Zhang, F. W. Zwiers, L. Song, H. Wan, T. Hu, and H. Yin, 2014: Rapid increase in the risk of extreme summer heat in eastern China. Nat. Climate Change, 4, 10821085, doi:10.1038/nclimate2410.

    • Search Google Scholar
    • Export Citation
  • Swart, N. C., J. C. Fyfe, E. Hawkins, J. E. Kay, and A. Jahn, 2015: Influence of internal variability on Arctic sea-ice trends. Nat. Climate Change, 5, 8689, doi:10.1038/nclimate2483.

    • Search Google Scholar
    • Export Citation
  • Tebaldi, C., and R. Knutti, 2007: The use of the multi-model ensemble in probabilistic climate projections. Philos. Trans. Roy. Soc. London, A365, 20532075, doi:10.1098/rsta.2007.2076.

    • Search Google Scholar
    • Export Citation
  • Tett, S., P. Stott, M. Allen, W. Ingram, and J. Mitchell, 1999: Causes of twentieth-century temperature change near the Earth’s surface. Nature, 399, 569572, doi:10.1038/21164.

    • Search Google Scholar
    • Export Citation
  • Van Huffel, S., and J. Vandewalle, 1991: The Total Least Squares Problem: Computational Aspects and Analysis. Society for Industrial and Applied Mathematics, 300 pp.

  • van Vuuren, D. P., and Coauthors, 2011: The representative concentration pathways: An overview. Climatic Change, 109, 531, doi:10.1007/s10584-011-0148-z.

    • Search Google Scholar
    • Export Citation
  • Vaughan, D., and Coauthors, 2013a: Observations: Cryosphere. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 317–382, doi:10.1017/CBO9781107415324.012.

  • Vaughan, D., and Coauthors, 2013b: Observations: Cryosphere supplementary material. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., 4SM-1–4SM-10. [Available online at https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/supplementary/WG1AR5_Ch04SM_FINAL.pdf.]

  • Vinnikov, K. Y., and Coauthors, 1999: Global warming and Northern Hemisphere sea ice extent. Science, 286, 19341937, doi:10.1126/science.286.5446.1934.

    • Search Google Scholar
    • Export Citation
  • Zhang, R., 2015: Mechanisms for low-frequency variability of summer Arctic sea ice extent. Proc. Natl. Acad. Sci. USA, 112, 45704575, doi:10.1073/pnas.1422296112.

    • Search Google Scholar
    • Export Citation
  • Zhang, R., and T. R. Knutson, 2013: The role of global climate change in the extreme low summer Arctic sea ice extent in 2012 [in “Explaining Extreme Events of 2012 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 94, S23S26.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1547 809 40
PDF Downloads 1365 605 33

Attribution of Extreme Events in Arctic Sea Ice Extent

View More View Less
  • 1 Pacific Climate Impacts Consortium, and Canadian Centre for Climate Modelling and Analysis, University of Victoria, Victoria, British Columbia, Canada
  • | 2 Pacific Climate Impacts Consortium, University of Victoria, Victoria, British Columbia, Canada
  • | 3 Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
Restricted access

Abstract

Arctic sea ice extent (SIE) has decreased over recent decades, with record-setting minimum events in 2007 and again in 2012. A question of interest across many disciplines concerns the extent to which such extreme events can be attributed to anthropogenic influences. First, a detection and attribution analysis is performed for trends in SIE anomalies over the observed period. The main objective of this study is an event attribution analysis for extreme minimum events in Arctic SIE. Although focus is placed on the 2012 event, the results are generalized to extreme events of other magnitudes, including both past and potential future extremes. Several ensembles of model responses are used, including two single-model large ensembles. Using several different metrics to define the events in question, it is shown that an extreme SIE minimum of the magnitude seen in 2012 is consistent with a scenario including anthropogenic influence and is extremely unlikely in a scenario excluding anthropogenic influence. Hence, the 2012 Arctic sea ice minimum provides a counterexample to the often-quoted idea that individual extreme events cannot be attributed to human influence.

Denotes Open Access content.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0412.s1.

Corresponding author e-mail: Megan Kirchmeier-Young, mkirch@uvic.ca

Abstract

Arctic sea ice extent (SIE) has decreased over recent decades, with record-setting minimum events in 2007 and again in 2012. A question of interest across many disciplines concerns the extent to which such extreme events can be attributed to anthropogenic influences. First, a detection and attribution analysis is performed for trends in SIE anomalies over the observed period. The main objective of this study is an event attribution analysis for extreme minimum events in Arctic SIE. Although focus is placed on the 2012 event, the results are generalized to extreme events of other magnitudes, including both past and potential future extremes. Several ensembles of model responses are used, including two single-model large ensembles. Using several different metrics to define the events in question, it is shown that an extreme SIE minimum of the magnitude seen in 2012 is consistent with a scenario including anthropogenic influence and is extremely unlikely in a scenario excluding anthropogenic influence. Hence, the 2012 Arctic sea ice minimum provides a counterexample to the often-quoted idea that individual extreme events cannot be attributed to human influence.

Denotes Open Access content.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0412.s1.

Corresponding author e-mail: Megan Kirchmeier-Young, mkirch@uvic.ca

Supplementary Materials

    • Supplemental Materials (PDF 1.69 MB)
Save