• Allan, J., and P. Komar, 2000: Are ocean wave heights increasing in the eastern North Pacific? Eos, Trans. Amer. Geophys. Union, 81, 561567, doi:10.1029/EO081i047p00561-01.

    • Search Google Scholar
    • Export Citation
  • Amante, C., and B. W. Eakins, 2009: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, data sources and analysis. NOAA Tech. Memo. NESDIS NGDC-24, 19 pp. [Available online at http://www.ngdc.noaa.gov/mgg/global/relief/ETOPO1/docs/ETOPO1.pdf.]

  • Andrews, O., N. Bindoff, P. Halloran, T. Ilyina, and C. Le Quéré, 2013: Detecting an external influence on recent changes in oceanic oxygen using an optimal fingerprinting method. Biogeosciences, 10, 17991813, doi:10.5194/bg-10-1799-2013.

    • Search Google Scholar
    • Export Citation
  • Baehr, J., H. Haak, S. Alderson, S. Cunningham, J. Jungclaus, and J. Marotzke, 2007: Timely detection of changes in the meridional overturning circulation at 26°N in the Atlantic. J. Climate, 20, 58275841, doi:10.1175/2007JCLI1686.1.

    • Search Google Scholar
    • Export Citation
  • Baehr, J., K. Keller, and J. Marotzke, 2008: Detecting potential changes in the meridional overturning circulation at 26°N in the Atlantic. Climatic Change, 91, 1127, doi:10.1007/s10584-006-9153-z.

    • Search Google Scholar
    • Export Citation
  • Bintanja, R., G. van Oldenborgh, S. Drijfhout, B. Wouters, and C. Katsman, 2013: Important role for ocean warming and increased ice-shelf melt in Antarctic sea-ice expansion. Nat. Geosci., 6, 376379, doi:10.1038/ngeo1767.

    • Search Google Scholar
    • Export Citation
  • Bouillon, S., M. Á. Morales Maqueda, V. Legat, and T. Fichefet, 2009: An elastic–viscous–plastic sea ice model formulated on Arakawa B and C grids. Ocean Modell., 27, 174184, doi:10.1016/j.ocemod.2009.01.004.

    • Search Google Scholar
    • Export Citation
  • Cavaleri, L., B. Fox-Kemper, and M. Hemer, 2012: Wind waves in the coupled climate system. Bull. Amer. Meteor. Soc., 93, 1651–1661, doi:10.1175/BAMS-D-11-00170.1.

    • Search Google Scholar
    • Export Citation
  • Chawla, A., D. M. Spindler, and H. L. Tolman, 2013: Validation of a thirty year wave hindcast using the Climate Forecast System Reanalysis winds. Ocean Modell., 70, 189206, doi:10.1016/j.ocemod.2012.07.005.

    • Search Google Scholar
    • Export Citation
  • Dobrynin, M., J. Murawsky, and S. Yang, 2012: Evolution of the global wind wave climate in CMIP5 experiments. Geophys. Res. Lett., 39, L18606, doi:10.1029/2012GL052843.

    • Search Google Scholar
    • Export Citation
  • ECMWF, 2006: IFS documentation CY31r1. [Available online at http://old.ecmwf.int/research/ifsdocs/CY31r1/index.html.]

  • Fichefet, T., and M. Maqueda, 1997: Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. J. Geophys. Res.,102, 12 609–12 646, doi:10.1029/97JC00480.

  • Hasselmann, K., 1993: Optimal fingerprints for the detection of time-dependent climate change. J. Climate,6, 1957–1971, doi:10.1175/1520-0442(1993)006<1957:OFFTDO>2.0.CO;2.

  • Hasselmann, K., 1997: Multi-pattern fingerprint method for detection and attribution of climate change. Climate Dyn., 13, 601611, doi:10.1007/s003820050185.

    • Search Google Scholar
    • Export Citation
  • Hazeleger, W., and Coauthors, 2012: EC-Earth V2.2: Description and validation of a new seamless earth system prediction model. Climate Dyn., 39, 2611–2629, doi:10.1007/s00382-011-1228-5.

    • Search Google Scholar
    • Export Citation
  • Hellmer, H. H., F. Kauker, R. Timmermann, J. Determann, and J. Rae, 2012: Twenty-first-century warming of a large Antarctic ice-shelf cavity by a redirected coastal current. Nature, 485, 225228, doi:10.1038/nature11064.

    • Search Google Scholar
    • Export Citation
  • Hemer, M. A., Y. Fan, N. Mori, A. Semedo, and X. L. Wang, 2013: Projected changes in wave climate from a multi-model ensemble. Nat. Climate Change, 3, 471476, doi:10.1038/nclimate1791.

    • Search Google Scholar
    • Export Citation
  • Khon, V. C., I. I. Mokhov, F. A. Pogarskiy, A. Babanin, K. Dethloff, A. Rinke, and H. Matthes, 2014: Wave heights in the 21st century Arctic Ocean simulated with a regional climate model. Geophys. Res. Lett.,41, 2956–2961, doi:10.1002/2014GL059847.

  • Koenigk, T., and L. Brodeau, 2014: Ocean heat transport into the Arctic in the twentieth and twenty-first century in EC-Earth. Climate Dyn., 42, 31013120, doi:10.1007/s00382-013-1821-x.

    • Search Google Scholar
    • Export Citation
  • Kohout, A., M. Williams, S. Dean, and M. Meylan, 2014: Storm-induced sea-ice breakup and the implications for ice extent. Nature, 509, 604607, doi:10.1038/nature13262.

    • Search Google Scholar
    • Export Citation
  • Komen, G., L. Cavaleri, M. Donelan, K. Hasselmann, S. Hasselmann, and P. A. E. M. Janssen, 1994: Dynamics and Modelling of Ocean Waves. Cambridge University Press, 554 pp.

  • Madec, G., 2008: NEMO ocean engine. L’Institut Pierre-Simon Laplace Tech. Rep. 27, 209 pp.

  • Santer, B. D., U. Mikolajewicz, W. Brüggemann, U. Cubasch, K. Hasselmann, H. Höck, E. Maier-Reimer, and T. M. L. Wigley, 1995: Ocean variability and its influence on the detectability of greenhouse warming signals. J. Geophys. Res., 100, 10 69310 725, doi:10.1029/95JC00683.

    • Search Google Scholar
    • Export Citation
  • Semedo, A., R. Weisse, A. Behrens, A. Sterl, L. Bengtsson, and H. Günther, 2013: Projection of global wave climate change toward the end of the twenty-first century. J. Climate, 26, 82698288, doi:10.1175/JCLI-D-12-00658.1.

    • Search Google Scholar
    • Export Citation
  • Shimura, T., N. Mori, and H. Mase, 2013: Ocean waves and teleconnection patterns in the Northern Hemisphere. J. Climate, 26, 86548670, doi:10.1175/JCLI-D-12-00397.1.

    • Search Google Scholar
    • Export Citation
  • Sterl, A., and Coauthors, 2012: A look at the ocean in the EC-Earth climate model. Climate Dyn., 39, 26312657, doi:10.1007/s00382-011-1239-2.

    • Search Google Scholar
    • Export Citation
  • Stocker, T. F., and Coauthors, 2013: Climate Change 2013: The Physical Science Basis. Cambridge University Press, 1535 pp. [Available online at http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_ALL_FINAL.pdf.]

  • Taylor, K., R. Stouffer, and G. 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
  • Thomson, J., and W. E. Rogers, 2014: Swell and sea in the emerging Arctic Ocean. Geophys. Res. Lett., 41, 3136–3140, doi:10.1002/2014GL059983.

    • Search Google Scholar
    • Export Citation
  • Tokinaga, H., and S.-P. Xie, 2011: Wave- and Anemometer-Based Sea Surface Wind (WASWind) for climate change analysis. J. Climate, 24, 267285, doi:10.1175/2010JCLI3789.1.

    • Search Google Scholar
    • Export Citation
  • Turner, J., and J. Overland, 2009: Contrasting climate change in the two polar regions. Polar Res., 28, 146164, doi:10.1111/j.1751-8369.2009.00128.x.

    • Search Google Scholar
    • Export Citation
  • Valcke, S., 2006: OASIS3 user guide prism_2-5. CERFACS Tech. Rep. TR/CMGC/06/73, 64 pp. [Available online at http://www.prism.enes.org/Publications/Reports/oasis3_UserGuide_T3.pdf.]

  • van Vuuren, D., 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
  • WAMDI Group, 1988: The WAM Model—A third generation ocean wave prediction model. J. Phys. Oceanogr., 18, 17751810, doi:10.1175/1520-0485(1988)018<1775:TWMTGO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, X., and V. Swail, 2006: Climate change signal and uncertainty in projections of ocean wave heights. Climate Dyn.,26, 109–126, doi:10.1007/s00382-005-0080-x.

  • Weisse, R., and H. Günther, 2007: Wave climate and long-term changes for the Southern North Sea obtained from a high-resolution hindcast 1958–2002. Ocean Dyn.,57, 161–172, doi:10.1007/s10236-006-0094-x.

  • Yin, J., J. T. Overpeck, S. M. Griffies, A. Hu, J. L. Russell, and R. J. Stouffer, 2011: Different magnitudes of projected subsurface ocean warming around Greenland and Antarctica. Nat. Geosci., 4, 524528, doi:10.1038/ngeo1189.

    • Search Google Scholar
    • Export Citation
  • Young, I. R., S. Zieger, and A. V. Babanin, 2011: Global trends in wind speed and wave height. Science, 332, 451455, doi:10.1126/science.1197219.

    • Search Google Scholar
    • Export Citation
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Detection and Attribution of Climate Change Signal in Ocean Wind Waves

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  • 1 Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Germany
  • | 2 Danish Meteorological Institute, Copenhagen, Denmark
  • | 3 Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Germany
  • | 4 Max Planck Institute for Meteorology, Hamburg, Germany
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Abstract

Surface waves in the ocean respond to variability and changes of climate. Observations and modeling studies indicate trends in wave height over the past decades. Nevertheless, it is currently impossible to discern whether these trends are the result of climate variability or change. The output of an Earth system model (EC-EARTH) produced within phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used here to force a global Wave Model (WAM) in order to study the response of waves to different climate regimes. A control simulation was run to determine the natural (unforced) model variability. A simplified fingerprint approach was used to calculate positive and negative limits of natural variability for wind speed and significant wave height, which were then compared to different (forced) climate regimes over the historical period (1850–2010) and in the future climate change scenario RCP8.5 (2010–2100). Detectable climate change signals were found in the current decade (2010–20) in the North Atlantic, equatorial Pacific, and Southern Ocean. Until the year 2060, climate change signals are detectable in 60% of the global ocean area. The authors show that climate change acts to generate detectable trends in wind speed and significant wave height that exceed the positive and the negative ranges of natural variability in different regions of the ocean. Moreover, in more than 3% of the ocean area, the climate change signal is reversible such that trends exceeded both positive and negative limits of natural variability at different points in time. These changes are attributed to local (due to local wind) and remote (due to swell) factors.

Corresponding author address: Mikhail Dobrynin, Institute of Oceanography, Universität Hamburg, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: mikhail.dobrynin@zmaw.de

Abstract

Surface waves in the ocean respond to variability and changes of climate. Observations and modeling studies indicate trends in wave height over the past decades. Nevertheless, it is currently impossible to discern whether these trends are the result of climate variability or change. The output of an Earth system model (EC-EARTH) produced within phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used here to force a global Wave Model (WAM) in order to study the response of waves to different climate regimes. A control simulation was run to determine the natural (unforced) model variability. A simplified fingerprint approach was used to calculate positive and negative limits of natural variability for wind speed and significant wave height, which were then compared to different (forced) climate regimes over the historical period (1850–2010) and in the future climate change scenario RCP8.5 (2010–2100). Detectable climate change signals were found in the current decade (2010–20) in the North Atlantic, equatorial Pacific, and Southern Ocean. Until the year 2060, climate change signals are detectable in 60% of the global ocean area. The authors show that climate change acts to generate detectable trends in wind speed and significant wave height that exceed the positive and the negative ranges of natural variability in different regions of the ocean. Moreover, in more than 3% of the ocean area, the climate change signal is reversible such that trends exceeded both positive and negative limits of natural variability at different points in time. These changes are attributed to local (due to local wind) and remote (due to swell) factors.

Corresponding author address: Mikhail Dobrynin, Institute of Oceanography, Universität Hamburg, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: mikhail.dobrynin@zmaw.de
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