Abstract

The relative contribution and physical drivers of internal variability in recent Arctic sea ice loss remain open questions, leaving up for debate whether global climate models used for climate projection lack sufficient sensitivity in the Arctic to climate forcing. Here, through analysis of large ensembles of fully coupled climate model simulations with historical radiative forcing, we present an important internal mechanism arising from low-frequency Arctic atmospheric variability in models that can cause substantial summer sea ice melting in addition to that due to anthropogenic forcing. This simulated internal variability shows a strong similarity to the observed Arctic atmospheric change in the past 37 years. Through a fingerprint pattern matching method, we estimate that this internal variability contributes to about 40–50% of observed multi-decadal decline in Arctic sea ice. Our study also suggests that global climate models may not actually underestimate sea ice sensitivities in the Arctic, but have trouble fully replicating an observed linkage between the Arctic and lower latitudes in recent decades. Further improvements in simulating the observed Arctic–global linkage are thus necessary before the Arctic’s sensitivity to global warming in models can be quantified with confidence.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Data availability

All reanalysis data used in this study were obtained from publicly available sources: ERA-Interim reanalysis data can be obtained from the ECMWF public data sets web interface (http://apps.ecmwf.int/datasets/). Simulated global circulation, temperature and sea ice under anthropogenic forcing were obtained from the CMIP5 and LENS archives accessed through the Earth System Grid Federation data portal (http://esgf.llnl.gov).

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Serreze, M. C. & Barry, R. G. Processes and impacts of Arctic amplification: a research synthesis. Glob. Planet. Change 77, 85–96 (2011).

  2. 2.

    Bintanja, R., Graversen, R. & Hazeleger, W. Arctic winter warming amplified by the thermal inversion and consequent low infrared cooling to space. Nat. Geosci. 4, 758–761 (2011).

  3. 3.

    Lee, S. Testing of the tropically excited Arctic warming (TEAM) mechanism with traditional El Nino and La Nina. J. Clim. 25, 4015–4022 (2012).

  4. 4.

    Vaughan, D. G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) Ch. 4 (Cambridge Univ. Press, 2013).

  5. 5.

    Fyfe, J. C. et al. One hundred years of Arctic surface temperature variation due to anthropogenic influence. Sci. Rep. 3, 2645 (2013).

  6. 6.

    Cohen, J. et al. Recent Arctic amplification and extreme mid-latitude weather. Nat. Geosci. 7, 627–637 (2014).

  7. 7.

    Perlwitz, J., Hoerling, M. & Dole, R. Arctic tropospheric warming: causes and linkages to lower latitudes. J. Clim. 28, 2154–2167 (2015).

  8. 8.

    Screen, J. A. & Francis, J. A. Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability. Nat. Clim. Change 6, 856–860 (2016).

  9. 9.

    Overland, J. E. & Wang, M. Future regional Arctic sea ice declines. Geophys. Res. Lett. 34, L17705 (2007).

  10. 10.

    Barnes, E. A. & Polvani, L. M. CMIP5 projections of Arctic amplification, of the North American/North Atlantic circulation, and of their relationship. J. Clim. 28, 5254–5271 (2015).

  11. 11.

    Holland, M. M. & Landrum, L. Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models. Phil. Trans. R. Soc. A 373, 20140162 (2015).

  12. 12.

    Deser, C., Sun, L., Tomas, R. A. & Screen, J. Does ocean-coupling matter for the northern extra-tropical response to projected Arctic sea ice loss? Geophys. Res. Lett. 43, 2149–2157 (2016).

  13. 13.

    Niederdrenk, A. L. & Notz, D. Arctic sea ice in a 1.5 °C warmer world. Geophys. Res. Lett. 45, 1963–1971 (2018).

  14. 14.

    Stroeve, J., Holland, M. M., Meier, W., Scambos, T. & Serreze, M. Arctic sea ice decline: faster than forecast. Geophys. Res. Lett. 34, L09501 (2007).

  15. 15.

    Winton, M. Do climate models underestimate the sensitivity of Northern Hemisphere sea ice cover? J. Clim. 24, 3924–3934 (2011).

  16. 16.

    Kay, J. E., Holland, M. M. & Jahn, A. Inter-annual to multi-decadal Arctic sea ice extent trends in a warming world. Geophys. Res. Lett. 38, L15708 (2011).

  17. 17.

    Day, J. J., Hargreaves, J. C., Annan, J. D. & Abe-Ouchi, A. Sources of multi-decadal variability in Arctic sea ice extent. Environ. Res. Lett. 7, 034011 (2012).

  18. 18.

    Stroeve, J. C. et al. Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophys. Res. Lett. 39, L16502 (2012).

  19. 19.

    Mahlstein, I. & Knutti, R. September Arctic sea ice predicted to disappear near 2 °C global warming above present. J. Geophys. Res. 117, D06104 (2012).

  20. 20.

    Swart, N. C., Fyfe, J. C., Hawkins, E., Kay, J. E. & Jahn, A. Influence of internal variability on Arctic sea-ice trends. Nat. Clim. Change 5, 86–89 (2015).

  21. 21.

    Ding, Q. H. et al. Influence of the recent high-latitude atmospheric circulation change on summertime Arctic sea ice. Nat. Clim. Change 7, 289–295 (2017).

  22. 22.

    Notz, D. & Stroeve, J. Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission. Science 354, 747–750 (2016).

  23. 23.

    Rosenblum, E. & Eisenman, I. Sea ice trends in climate models only accurate in runs with biased global warming. J. Clim. 30, 6265–6278 (2017).

  24. 24.

    Jahn, A. Reduced probability of ice-free summers for 1.5 °C compared to 2 °C warming. Nat. Clim. Change 8, 409–413 (2018).

  25. 25.

    Kay, J. E. et al. The Community Earth System Model (CESM) Large Ensemble Project: a community resource for studying climate change in the presence of internal climate variability. Bull. Am. Meteorol. Soc. 96, 1333–1349 (2015).

  26. 26.

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

  27. 27.

    Tandon, N. F., Kushner, P. J., Docquier, D., Wettstein, J. & Li, C. Reassessing sea ice drift and its relationship to long-term Arctic sea ice loss in coupled climate models. J. Geophys. Res. Oceans 2017, JC013697 (2017).

  28. 28.

    Ding, Q. H. et al. Tropical forcing of the recent rapid Arctic warming in northeastern Canada and Greenland. Nature 509, 209–212 (2014).

  29. 29.

    Trenberth, K. E., Fasullo, J. T., Branstator, G. & Phillips, A. S. Seasonal aspects of the recent pause in surface warming. Nat. Clim. Change 4, 911–916 (2014).

  30. 30.

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

  31. 31.

    Meehl, G. A., Teng, H. & Arblaster, J. M. Climate model simulations of the observed early-2000s hiatus of global warming. Nat. Clim. Change 4, 898–902 (2014).

  32. 32.

    Gregory, J. M. et al. Recent and future changes in Arctic sea ice simulated by the HadCM3 AOGCM. Geophys. Res. Lett. 29, 2175 (2002).

  33. 33.

    Graversen, R. G., Langen, P. L. & Mauritsen, T. Polar amplification in CCSM4: contributions from the lapse rate and surface Albedo feedbacks. J. Clim. 27, 4433–4450 (2014).

  34. 34.

    McCusker, K. E. et al. Remarkable separability of circulation response to Arctic sea ice loss and greenhouse gas forcing. Geophys. Res. Lett. 44, 7955–7964 (2017).

  35. 35.

    Screen, J. A. Arctic sea ice at 1.5 and 2 °C. Nat. Clim. Change 8, 362–363 (2018).

  36. 36.

    Rienecker, M. M. et al. MERRA—NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011).

  37. 37.

    Kanamitsu, M. et al. The NCEP‐DOE AMIP‐II reanalysis (R‐2). Bull. Amer. Meteorol. Soc. 83, 1631–1643 (2002).

  38. 38.

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

  39. 39.

    Kobayashi, S. et al. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteor. Soc. Jpn 93, 5–48 (2015).

  40. 40.

    Saha, S. et al. The NCEP climate forecast system reanalysis. Bull. Amer. Meteorol. Soc. 91, 1015–1057 (2010).

  41. 41.

    Comiso, J. C., Meier, W. N. & Gersten, R. Variability and trends in the Arctic Sea ice cover: results from different techniques. J. Geophys. Res. Oceans 122, 6883–6900 (2017).

  42. 42.

    Schweiger, A. J. et al. Uncertainty in modeled Arctic sea ice volume. J. Geophys. Res. 116, C00D06 (2011).

  43. 43.

    Plumb, R. A. On the three-dimensional propagation of stationary waves. J. Atmos. Sci. 42, 217–229 (1985).

  44. 44.

    Bretherton, C. S., Smith, C. & Wallace, J. M. An intercomparison of methods for finding coupled patterns in climate data. J. Clim. 5, 541–560 (1992).

  45. 45.

    Wallace, J. M., Smith, C. & Bretherton, C. S. Singular value decomposition of wintertime sea surface temperature and 500-mb height anomalies. J. Clim. 5, 561–576 (1992).

Download references

Acknowledgements

This study was supported by NOAA’s Climate Program Office, Climate Variability and Predictability Program (NA15OAR4310162) and Ocean Observing and Monitoring Division (NA18OAR4310424), and by NSF’s Polar Programs (OPP1744598 and ARC1203425). The authors acknowledge support from the CESM Large Ensemble Community Project and supercomputing resources provided by NSF/CISL/Yellowstone.

Author information

Affiliations

  1. Department of Geography, and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA

    • Qinghua Ding
    • , Bradley Markle
    •  & Ian Baxter
  2. Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA

    • Axel Schweiger
  3. NOAA Climate Prediction Center, College Park, MD, USA

    • Michelle L’Heureux
    • , Qin Zhang
    •  & Kirstin Harnos
  4. Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA

    • Eric J. Steig
  5. Department of Atmospheric Sciences, University of Washington, Seattle, WA, USA

    • David S. Battisti
    •  & Eduardo Blanchard-Wrigglesworth
  6. Cooperative Institute for Climate Science, Princeton University, Princeton, NJ, USA

    • Nathaniel C. Johnson
  7. Lawrence Livermore National Laboratory, Livermore, CA, USA

    • Stephen Po-Chedley
  8. Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

    • Mitchell Bushuk

Authors

  1. Search for Qinghua Ding in:

  2. Search for Axel Schweiger in:

  3. Search for Michelle L’Heureux in:

  4. Search for Eric J. Steig in:

  5. Search for David S. Battisti in:

  6. Search for Nathaniel C. Johnson in:

  7. Search for Eduardo Blanchard-Wrigglesworth in:

  8. Search for Stephen Po-Chedley in:

  9. Search for Qin Zhang in:

  10. Search for Kirstin Harnos in:

  11. Search for Mitchell Bushuk in:

  12. Search for Bradley Markle in:

  13. Search for Ian Baxter in:

Contributions

Q.D. and A.S. led this work with contributions from all authors. Q.D. carried out the calculations and created the figures. Q.D and A.S. led analyses, interpreted results and wrote the paper.

Competing interests

The authors declare no competing interests

Corresponding author

Correspondence to Qinghua Ding.

Supplementary information

  1. Supplementary Information

    Supplementary Figures and Tables

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/s41561-018-0256-8