• Barnes, E. A., 2013: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophys. Res. Lett., 40, 47344739, doi:10.1002/grl.50880.

    • Search Google Scholar
    • Export Citation
  • Bathiany, S., , D. Notz, , T. Mauritsen, , G. Raedel, , and V. Brovkin, 2016: On the potential for abrupt Arctic winter sea ice loss. J. Climate, 29, 27032719, doi:10.1175/JCLI-D-15-0466.1.

    • Search Google Scholar
    • Export Citation
  • Bintanja, R., , and E. C. van der Linden, 2013: The changing seasonal climate in the Arctic. Sci. Rep., 3, 1556, doi:10.1038/srep01556.

  • Bintanja, R., , R. G. Graversen, , and W. Hazeleger, 2011: Arctic winter warming amplified by the thermal inversion and consequent low infrared cooling to space. Nat. Geosci., 4, 758761, doi:10.1038/ngeo1285.

    • Search Google Scholar
    • Export Citation
  • Block, K., , and T. Mauritsen, 2013: Forcing and feedback in the MPI-ESM-LR coupled model under abruptly quadrupled CO2. J. Adv. Model. Earth Syst., 5, 676691, doi:10.1002/jame.20041.

    • Search Google Scholar
    • Export Citation
  • Boé, J., , A. Hall, , and X. Qu, 2009: September sea-ice cover in the Arctic Ocean projected to vanish by 2100. Nat. Geosci., 2, 341343, doi:10.1038/ngeo467; Corrigendum, 2, 444, doi:10.1038/ngeo548.

    • Search Google Scholar
    • Export Citation
  • Bony, S., and et al. , 2006: How well do we understand and evaluate climate change feedback processes? J. Climate, 19, 34453482, doi:10.1175/JCLI3819.1.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and et al. , 2014: Recent Arctic amplification and extreme mid-latitude weather. Nat. Geosci., 7, 627637, doi:10.1038/ngeo2234.

    • Search Google Scholar
    • Export Citation
  • Collins, M., and et al. , 2013: Long-term climate change: Projections, commitments and irreversibility. Climate Change 2013: The Physical Science Basis, Cambridge University Press, 1029–1136. [Available online at http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/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
  • Francis, J. A., , and S. J. Vavrus, 2012: Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys. Res. Lett., 39, L06801, doi:10.1029/2012GL051000.

    • Search Google Scholar
    • Export Citation
  • Francis, J. A., , and S. J. Vavrus, 2015: Evidence for a wavier jet stream in response to rapid Arctic warming. Environ. Res. Lett., 10, 014005, doi:10.1088/1748-9326/10/1/014005.

    • Search Google Scholar
    • Export Citation
  • Graversen, R. G., , P. L. Langen, , and T. Mauritsen, 2014: Polar amplification in CCSM4: Contributions from the lapse rate and surface albedo feedbacks. J. Climate, 27, 44334450, doi:10.1175/JCLI-D-13-00551.1.

    • Search Google Scholar
    • Export Citation
  • Hall, A., 2004: The role of surface albedo feedback in climate. J. Climate, 17, 15501568, doi:10.1175/1520-0442(2004)017<1550:TROSAF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hall, A., , and X. Qu, 2006: Using the current seasonal cycle to constrain snow albedo feedback in future climate change. Geophys. Res. Lett., 33, L03502, doi:10.1029/2005GL025127.

    • Search Google Scholar
    • Export Citation
  • Hansen, J., , A. Lacis, , D. Rind, , G. Russell, , P. Stone, , I. Fung, , R. Ruedy, , and J. Lerner, 1984: Climate sensitivity: Analysis of feedback mechanisms. Climate Processes and Climate Sensitivity, Geophys. Monogr., Vol. 29, Amer. Geophys. Union, 130–163, doi:10.1029/GM029p0130.

  • Hersbach, H., , C. Peubey, , A. Simmons, , P. Berrisford, , P. Poli, , and D. Dee, 2015: ERA-20CM: A twentieth-century atmospheric model ensemble. Quart. J. Roy. Meteor. Soc., 141, 23502375, doi:10.1002/qj.2528.

    • Search Google Scholar
    • Export Citation
  • Holland, M. M., , and C. M. Bitz, 2003: Polar amplification of climate change in coupled models. Climate Dyn., 21, 221232, doi:10.1007/s00382-003-0332-6.

    • Search Google Scholar
    • Export Citation
  • Krikken, F., , and W. Hazeleger, 2015: Arctic energy budget in relation to sea ice variability on monthly-to-annual time scales. J. Climate, 28, 63356350, doi:10.1175/JCLI-D-15-0002.1.

    • Search Google Scholar
    • Export Citation
  • Lenton, T. M., , H. Held, , E. Kriegler, , J. W. Hall, , W. Lucht, , S. Rahmstorf, , and H. J. Schellnhuber, 2008: Tipping elements in the Earth’s climate system. Proc. Natl. Acad. Sci. USA, 105, 17861793, doi:10.1073/pnas.0705414105.

    • Search Google Scholar
    • Export Citation
  • Liu, J., , J. A. Curry, , H. Wang, , M. Song, , and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall. Proc. Natl. Acad. Sci., 109, 40744079, doi:10.1073/pnas.1114910109.

    • Search Google Scholar
    • Export Citation
  • Moss, R. H., and et al. , 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747756, doi:10.1038/nature08823.

    • Search Google Scholar
    • Export Citation
  • Perovich, D. K., 2003: Complex yet translucent: The optical properties of sea ice. Physica B, 338, 107114, doi:10.1016/S0921-4526(03)00470-8.

    • Search Google Scholar
    • Export Citation
  • Pithan, F., , and T. Mauritsen, 2014: Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nat. Geosci., 7, 181184, doi:10.1038/ngeo2071.

    • Search Google Scholar
    • Export Citation
  • Reichler, T., , and J. Kim, 2008: How well do coupled models simulate today’s climate? Bull. Amer. Meteor. Soc., 89, 303311, doi:10.1175/BAMS-89-3-303.

    • Search Google Scholar
    • Export Citation
  • Schauer, U., , E. Fahrbach, , S. Osterhus, , and G. Rohardt, 2004: Arctic warming through the Fram Strait: Oceanic heat transport from 3 years of measurements. J. Geophys. Res., 109, C06026, doi:10.1029/2003JC001823.

    • Search Google Scholar
    • Export Citation
  • Schmidt, G. A., and et al. , 2014: Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive. J. Adv. Model. Earth Syst., 6, 141184, doi:10.1002/2013MS000265.

    • Search Google Scholar
    • Export Citation
  • Screen, J. A., , and I. Simmonds, 2010: The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464, 13341337, doi:10.1038/nature09051.

    • Search Google Scholar
    • Export Citation
  • Screen, J. A., , and I. Simmonds, 2013: Exploring links between Arctic amplification and mid-latitude weather. Geophys. Res. Lett., 40, 959964, doi:10.1002/grl.50174.

    • Search Google Scholar
    • Export Citation
  • Senior, C. A., , and J. F. B. Mitchell, 2000: The time-dependence of climate sensitivity. Geophys. Res. Lett., 27, 26852688, doi:10.1029/2000GL011373.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., , and J. A. Francis, 2006: The Arctic amplification debate. Climatic Change, 76, 241264, doi:10.1007/s10584-005-9017-y.

    • 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
  • Shell, K. M., , J. T. Kiehl, , and C. A. Shields, 2008: Using the radiative kernel technique to calculate climate feedbacks in NCAR’s Community Atmospheric Model. J. Climate, 21, 22692282, doi:10.1175/2007JCLI2044.1.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., , and I. M. Held, 2006: An assessment of climate feedbacks in coupled ocean–atmosphere models. J. Climate, 19, 33543360, doi:10.1175/JCLI3799.1.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., , I. M. Held, , R. Colman, , K. M. Shell, , J. T. Kiehl, , and C. A. Shields, 2008: Quantifying climate feedbacks using radiative kernels. J. Climate, 21, 35043520, doi:10.1175/2007JCLI2110.1.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., , V. Kattsov, , A. Barrett, , M. Serreze, , T. Pavlova, , M. Holland, , and W. N. Meier, 2012: Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophys. Res. Lett., 39, L16502, doi:10.1029/2012GL052676.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., , R. J. Stouffer, , and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, doi:10.1175/BAMS-D-11-00094.1.

    • Search Google Scholar
    • Export Citation
  • Titchner, H. A., , and N. A. Rayner, 2014: The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations. J. Geophys. Res. Atmos., 119, 28642889, doi:10.1002/2013JD020316.

    • Search Google Scholar
    • Export Citation
  • Van der Linden, E. C., , R. Bintanja, , W. Hazeleger, , and C. A. Katsman, 2014: The role of the mean state of Arctic sea ice on near-surface temperature trends. J. Climate, 27, 28192841, doi:10.1175/JCLI-D-12-00617.1.

    • Search Google Scholar
    • Export Citation
  • Van Vuuren, D. P., and et al. , 2011: The representative concentration pathways: An overview. Climatic Change, 109, 531, doi:10.1007/s10584-011-0148-z.

    • Search Google Scholar
    • Export Citation
  • Viñas, M.-J., 2015: 2015 Arctic sea ice maximum annual extent is lowest on record. NASA, accessed 1 April 2015. [Available online at http://www.nasa.gov/content/goddard/2015-arctic-sea-ice-maximum-annual-extent-is-lowest-on-record.]

  • Von der Heydt, A. S., , P. Köhler, , R. S. W. van de Wal, , and H. A. Dijkstra, 2014: On the state dependency of fast feedback processes in (paleo) climate sensitivity. Geophys. Res. Lett., 41, 64846492, doi:10.1002/2014GL061121.

    • Search Google Scholar
    • Export Citation
  • Wang, M., , and J. E. Overland, 2009: A sea ice free summer Arctic within 30 years? Geophys. Res. Lett., 36, L07502, doi:10.1029/2009GL037820.

    • Search Google Scholar
    • Export Citation
  • Williams, K. D., , W. J. Ingram, , and J. M. Gregory, 2008: Time variation of effective climate sensitivity in GCMs. J. Climate, 21, 50765090, doi:10.1175/2008JCLI2371.1.

    • Search Google Scholar
    • Export Citation
  • Winton, M., 2006a: Does the Arctic sea ice have a tipping point? Geophys. Res. Lett., 33, L23504, doi:10.1029/2006GL028017.

  • Winton, M., 2006b: Amplified Arctic climate change: What does surface albedo feedback have to do with it? Geophys. Res. Lett., 33, L03701, doi:10.1029/2005GL025244.

    • Search Google Scholar
    • Export Citation
  • Winton, M., , K. Takahashi, , and I. M. Held, 2010: Importance of ocean heat uptake efficacy to transient climate change. J. Climate, 23, 23332344, doi:10.1175/2009JCLI3139.1.

    • Search Google Scholar
    • Export Citation
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Time-Dependent Variations in the Arctic’s Surface Albedo Feedback and the Link to Seasonality in Sea Ice

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  • 1 Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
  • | 2 Royal Netherlands Meteorological Institute (KNMI), De Bilt, and Meteorology and Air Quality, Department of Environmental Sciences, Wageningen University, Wageningen, and Netherlands eScience Center, Amsterdam, Netherlands
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Abstract

The Arctic is warming 2 to 3 times faster than the global average. Arctic sea ice cover is very sensitive to this warming and has reached historic minima in late summer in recent years (e.g., 2007 and 2012). Considering that the Arctic Ocean is mainly ice covered and that the albedo of sea ice is very high compared to that of open water, any change in sea ice cover will have a strong impact on the climate response through the radiative surface albedo feedback. Since sea ice area is projected to shrink considerably, this feedback will likely vary considerably in time. Feedbacks are usually evaluated as being constant in time, even though feedbacks and climate sensitivity depend on the climate state. Here the authors assess and quantify these temporal changes in the strength of the surface albedo feedback in response to global warming. Analyses unequivocally demonstrate that the strength of the surface albedo feedback exhibits considerable temporal variations. Specifically, the strength of the surface albedo feedback in the Arctic, evaluated for simulations of the future climate (CMIP5 RCP8.5) using a kernel method, shows a distinct peak around the year 2100. This maximum is found to be linked to increased seasonality in sea ice cover when sea ice recedes, in which sea ice retreat during spring turns out to be the dominant factor affecting the strength of the annual surface albedo feedback in the Arctic. Hence, changes in sea ice seasonality and the associated fluctuations in surface albedo feedback strength will exert a time-varying effect on Arctic amplification during the projected warming over the next century.

Corresponding author e-mail: Olivier Andry, olivier.andry@knmi.nl

Abstract

The Arctic is warming 2 to 3 times faster than the global average. Arctic sea ice cover is very sensitive to this warming and has reached historic minima in late summer in recent years (e.g., 2007 and 2012). Considering that the Arctic Ocean is mainly ice covered and that the albedo of sea ice is very high compared to that of open water, any change in sea ice cover will have a strong impact on the climate response through the radiative surface albedo feedback. Since sea ice area is projected to shrink considerably, this feedback will likely vary considerably in time. Feedbacks are usually evaluated as being constant in time, even though feedbacks and climate sensitivity depend on the climate state. Here the authors assess and quantify these temporal changes in the strength of the surface albedo feedback in response to global warming. Analyses unequivocally demonstrate that the strength of the surface albedo feedback exhibits considerable temporal variations. Specifically, the strength of the surface albedo feedback in the Arctic, evaluated for simulations of the future climate (CMIP5 RCP8.5) using a kernel method, shows a distinct peak around the year 2100. This maximum is found to be linked to increased seasonality in sea ice cover when sea ice recedes, in which sea ice retreat during spring turns out to be the dominant factor affecting the strength of the annual surface albedo feedback in the Arctic. Hence, changes in sea ice seasonality and the associated fluctuations in surface albedo feedback strength will exert a time-varying effect on Arctic amplification during the projected warming over the next century.

Corresponding author e-mail: Olivier Andry, olivier.andry@knmi.nl
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