Skip to main content

Advertisement

SpringerLink
Log in

Clusters of interannual sea ice variability in the northern hemisphere

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

We determine robust modes of the northern hemisphere (NH) sea ice variability on interannual timescales disentangled from the long-term climate change. This study focuses on sea ice thickness (SIT), reconstructed with an ocean–sea-ice general circulation model, because SIT has a potential to contain most of the interannual memory and predictability of the NH sea ice system. We use the K-means cluster analysis—one of clustering methods that partition data into groups or clusters based on their distances in the physical space without the typical constraints of other unsupervised learning statistical methods such as the widely-used principal component analysis. To adequately filter out climate change signal in the Arctic from 1958 to 2013 we have to approximate it with a 2nd degree polynomial. Using 2nd degree residuals of SIT leads to robust K-means cluster patterns, i.e. invariant to further increase of the polynomial degree. A set of clustering validity indices yields K = 3 as the optimal number of SIT clusters for all considered months and seasons with strong similarities in their cluster patterns. The associated time series of cluster occurrences exhibit predominant interannual persistence with mean timescale of about 2 years. Compositing analysis of the NH surface climate conditions associated with each cluster indicates that wind forcing seem to be the key factor driving the formation of interannual SIT cluster patterns during the winter. Climate memory in SIT with such interannual persistence could lead to increased predictability of the Artic sea ice cover beyond seasonal timescales.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Andeberg MR (1973) Cluster analysis for applications. Academic Press, London, p 359

    Google Scholar 

  • Balmaseda MA, Mogensen KS, Weaver AT (2012) Evaluation of the ECMWF Ocean Reanalysis ORAS4. Q J R Meteorol Soc. doi:10.1002/qj.2063

    Google Scholar 

  • Barry RG, Gan TY (2011) The global cryosphere. Cambridge University Press, New York, p 498

    Book  Google Scholar 

  • Belchansky GI, Douglas DC, Platonov NG (2005) Spatial and temporal variations in the age structure of Arctic sea ice. Geophys Res Lett 32:L18504. doi:10.1029/2005GL023976

    Google Scholar 

  • Blanchard-Wrigglesworth E, Bitz CM (2014) Characteristics of Arctic sea-ice thickness variability in GCMs. J Clim 27:8244–8258. doi:10.1175/JCLI-D-14-00345.1

    Article  Google Scholar 

  • Blanchard-Wrigglesworth E, Armour KC, Bitz CM, DeWeaver E (2011) Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations. J Clim 24:231–250. doi:10.1175/2010JCLI3775.1

    Article  Google Scholar 

  • Boer GJ, Yu B (2003) Climate sensitivity and response. Clim Dyn 20:415–429

    Google Scholar 

  • Brodeau L, Barnier B, Treguier AM, Penduff T, Gulev S (2010) An ERA40-based atmospheric forcing for global ocean circulation models. Ocean Model 31:88–104

    Article  Google Scholar 

  • Cassou C (2008) Intraseasonal interaction between the Madden–Julian oscillation and North Atlantic oscillation. Nature 455:523–527

    Article  Google Scholar 

  • Cassou S, Terray L, Hurrell JW, Deser C (2004) North Atlantic winter climate regimes: spatial asymmetry, stationarity with time, and oceanic forcing. J Clim 17:1055–1068. doi:10.1175/1520-0442

    Article  Google Scholar 

  • Cavalieri DC, Parkinson C, Gloersen P, Zwally HJ (1996) Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data. National Snow and Ice Data Center, Digital media, Boulder

    Google Scholar 

  • Charrad M, Ghazzali N, Boiteau V, Niknafs A (2014) NbClust: an R package for determining the relevant number of clusters in a data set. J Stat Softw 61(6):1–36

    Article  Google Scholar 

  • Cheng X, Wallace JM (1993) Cluster analysis of the Northern Hemisphere wintertime 500-hPa height field: spatial patterns. J Atmos Sci 50:2674–2696. doi:10.1175/1520-0469(1993)050<2674:CAOTNH>2.0.CO;2

    Article  Google Scholar 

  • Chevallier M, Salas Y Mélia D (2012) The role of sea ice thickness distribution in the Arctic sea ice potential predictability: a diagnostic approach with a coupled GCM. J Clim 25:3025–3038. doi:10.1175/JCLI-D-11-00209.1

    Article  Google Scholar 

  • Coggins JHJ, McDonald AJ, Jolly B (2014) Synoptic climatology of the Ross Ice Shelf and Ross Sea region of Antarctica: k-means clustering and validation. Int J Climatol 34:2330–2348. doi:10.1002/joc.3842

    Article  Google Scholar 

  • Comiso JC, Hall DK (2014) Cimate trends in the Arctic as observed from space. WIREs Clim Change 5:389–409. doi:10.1002/wcc.277

    Article  Google Scholar 

  • Comiso JC, Parkinson CL, Gersten R, Stock L (2008) Accelerated decline in the Arctic sea ice cover. Geophy Res Lett 35:L01703. doi:10.1029/2007GL031972

    Article  Google Scholar 

  • Day JJ, Hawkins E, Tietsche S (2014) Will Arctic sea ice thickness initialization improve seasonal forecast skill? Geophys Res Lett 41:7566–7575. doi:10.1002/2014GL061694

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Holm EV, Isaksen L, Kallberg P, Kohler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thpaut JN, Vitart F (2011) The era-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Feldstein SB (2000) The timescale, power spectra, and climate noise properties of teleconnection patterns. J Clim 13:4430–4440. doi:10.1175/1520-0442(2000)013<4430:TTPSAC>2.0.CO;2

    Article  Google Scholar 

  • Francis JA, Vavrus SJ (2012) Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys Res Lett 39:L06801. doi:10.1029/2012GL051000

    Article  Google Scholar 

  • Francis JA, Chan W, Leathers D, Miller JR, Veron DE (2009) Winter Northern Hemisphere weather patterns remember summer Arctic sea ice extent. Geophys Res Lett 36:L07503. doi:10.1029/2009GL037274

    Article  Google Scholar 

  • Gordon ND, Norris JR (2010) Cluster analysis of mid-latitude oceanic cloud regimes—Part 1: mean cloud and meteorological properties. Atmos Chem Phys Discuss 10:1559–1593

    Article  Google Scholar 

  • Guemas V, Salas-Mélia D, Kageyama M, Giordani H, Voldoire A, Sanchez-Gomez E (2009) Winter interactions between weather regimes and marine surface in the North Atlantic European region. Geophys Res Lett 36:L09816. doi:10.1029/2009GL037551

    Article  Google Scholar 

  • Guemas V, Blanchard-Wrigglesworth E, Chevallier M, Day JJ, Déqué M, Doblas-Reyes FJ, Fučkar NS, Germe A, Hawkins E, Keeley S, Koenigk T, Salas y Mélia D, Tietsche S (2014a) A review on Arctic sea-ice predictability and prediction on seasonal to decadal time-scales. Q J R Meteorol Soc. doi:10.1002/qj.2401

    Google Scholar 

  • Guemas V, Doblas-Reyes FJ, Mogensen K, Tang Y, Keeley S (2014b) Ensemble of sea ice initial conditions for interannual climate predictions. Clim Dyn. doi:10.1007/s00382-014-2095-7

    Google Scholar 

  • Hall A (2004) The role of surface albedo feedback in climate. J Clim 17(7):1550–1568

    Article  Google Scholar 

  • Hannachi A, O’Neill A (2001) Atmospheric multiple equilibria and non-Gaussian behaviour in model simulations. Q J R Meteorol Soc 127:939–958. doi:10.1002/qj.v127:573

    Article  Google Scholar 

  • Hannachi A, Jolliffe IT, Stephenson DB (2007) Empirical orthogonal functions and related techniques in atmospheric science: a review. Int J Climatol 27:9

    Google Scholar 

  • Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning. Springer, Heidelberg, p 745

    Book  Google Scholar 

  • Holland MM (2010) Arctic sea ice and the potential for abrupt loss. In: Sun D-Z, Bryan F (eds) Climate dynamics: Why does climate vary? Geophysical Monograph Series, vol 189. AGU, Washington, DC, pp 181–192

    Chapter  Google Scholar 

  • Honda M, Inoue J, Yamane S (2009) Influence of low Arctic sea-ice minima on anomalously cold Eurasian winters. Geophys Res Lett 36:L08707. doi:10.1029/2008GL037079

    Article  Google Scholar 

  • Hwang Y-T, Frierson DMW, Kay JE (2011) Coupling between Arctic feedbacks and changes in pole-ward energy transport. Geophys Res Lett 38:L17704. doi:10.1029/2011GL048546

    Google Scholar 

  • Johnson NC, Feldstein SB (2010) The continuum of North Pacific sea level pressure patterns: intraseasonal, interannual, and interdecadal variability. J Clim 23:851–867. doi:10.1175/2009JCLI3099.1

    Article  Google Scholar 

  • Jung T, Kasper MA, Semmler T, Serrar S (2014) Arctic influence on subseasonal midlatitude prediction. Geophys Res Lett 41:3676–3680. doi:10.1002/2014GL059961

    Article  Google Scholar 

  • Jungclaus JH, Koenigk T (2010) Low-frequency variability of Arctic climate: the role of oceanic and atmospheric heat transport. Clim Dyn 34:265–279. doi:10.1007/s00382-009-0569-9

    Article  Google Scholar 

  • Kay JE, Holland MM, Bitz CM, Blanchard-Wrigglesworth E, Gettelman A, Conley A, Bailey D (2012) The influence of local feedbacks and northward heat transport on the equilibrium Arctic climate response to increased greenhouse gas forcing. J Clim 25:5433–5450. doi:10.1175/JCLI-D-11-00622.1

    Article  Google Scholar 

  • Kwok R, Cunningham GF (2008) ICESat over Arctic sea ice: estimation of snow depth and ice thickness. J Geophys Res 113:C08010. doi:10.1029/2008JC004753

    Google Scholar 

  • Kwok R, Rothrock DA (2009) Decline in Arctic sea ice thickness from submarine and IceSat records: 1958–2008. Geophys Res Lett 36:L15501. doi:10.1029/2009gl039035

    Article  Google Scholar 

  • Kwok R, Sulsky D (2010) Arctic Ocean sea ice thickness and kinematics: satellite retrievals and modeling. Oceanography 23(4):134–143. doi:10.5670/oceanog.2010.11

    Article  Google Scholar 

  • Kwok R, Spreen G, Pang S (2013) Arctic sea ice circulation and drift speed: decadal trends and ocean currents. J Geophy Res: Oceans 118:2408–2425. doi:10.1002/jgrc.v118.5

    Article  Google Scholar 

  • Large W, Yeager S (2004) Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. Tech Note NCAR/TN-460?STR, Natl Cent for Atmos Res, Boulder, USA

  • Laxon S, Peacock N, Smith D (2003) High interannual variability of sea ice thickness in the Arctic region. Nature 425:947–950

    Article  Google Scholar 

  • Laxon SW, Giles KA, Ridout AL, Wingham DJ, Willatt R, Cullen R, Kwok K, Schweiger A, Zhang J, Haas C, Hendricks S, Krishfield R, Kurtz N, Farrell S, Davidson M (2013) CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophys Res Lett 40:732–737. doi:10.1002/grl.5019

    Article  Google Scholar 

  • Liu Z, Alexander M (2007) Atmospheric bridge, oceanic tunnel, and global climatic teleconnections. Rev Geophys 45:RG2005. doi:10.1029/2005RG000172

    Article  Google Scholar 

  • Maslanik JA, Fowler C, Stroeve J, Drobot S, Zwally J, Yi D, Emery W (2007) A younger, thinner Arctic ice cover: increased potential for rapid, extensive sea-ice loss. Geophys Res Lett 34:L24501. doi:10.1029/2007GL032043

    Article  Google Scholar 

  • Massonnet F, Mathiot P, Fichefet T, Goosse H, König CB, Vancoppenolle M, Lavergne T (2013) A model reconstruction of the Antarctic sea ice thickness and volume changes over 1980–2008 using data assimilation. Ocean Modeling 64(2013):67–75. doi:10.1016/j.ocemod.2013.01.003

    Article  Google Scholar 

  • Michelangeli P-A, Vautard R, Legras B (1995) Weather regimes: recurrence and quasi stationarity. J Atmos Sci 52:1237–1256. doi:10.1175/1520-0469(1995)052<1237:WRRAQS>2.0.CO;2

    Article  Google Scholar 

  • Mogensen KS, Balmaseda MA, Weaver A (2011) The NEMOVAR ocean data assimilation as implemented in the ECMWF ocean analysis for system 4. ECMWF Technical, Memorandum 668

  • Monahan AH, Fyfe JC, Ambaum MHP, Stephenson DB, North GR (2009) Empirical orthogonal functions: the medium is the message. J Clim 22:6501–6514. doi:10.1175/2009JCLI3062.1

    Article  Google Scholar 

  • Overland J, Francis JA, Hall R, Hanna E, Kim S-J, Vihma T (2015) The melting arctic and mid-latitude weather patterns: are they connected?. J Clim 28:7917–7932. doi:10.1175/JCLI-D-14-00822.1

    Article  Google Scholar 

  • Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407. doi:10.1029/2002JD002670

    Article  Google Scholar 

  • Riddle EE, Stoner MB, Johnson NC, L’Heureux ML, Collins DC, Feldstein SB (2013) The impact of the MJO on clusters of wintertime circulation anomalies over the North American region. Clim Dyn 40:1749–1766

    Article  Google Scholar 

  • Rigor IG, Wallace JM (2004) Variations in the age of Arctic sea-ice and summer sea-ice extent. Geophys Res Lett 31:L09401. doi:10.1029/2004GL019492

    Article  Google Scholar 

  • Rigor IG, Wallace JM, Colony RL (2002) Response of sea ice to the Arctic oscillation. J Clim 15:2648–2663

    Article  Google Scholar 

  • Rossow WB, Tselioudis G, Polak A, Jakob C (2005) Tropical climate described as a distribution of weather states indicated by distinct mesoscale cloud property mixtures. Geophys Res Lett 32:L21812. doi:10.1029/2005GL024584

    Article  Google Scholar 

  • Sakov P, Counillon F, Bertino L, Lisæter KA, Oke PR, Korablev A (2012) TOPAZ4: an ocean–sea ice data assimilation system for the North Atlantic and Arctic. Ocean Sci 8:633–656. doi:10.5194/os-8-633-2012

    Article  Google Scholar 

  • Serreze MC, Barry RG (2005) The Arctic climate system. Cambridge University Press, New York, p 385

    Book  Google Scholar 

  • Serreze MC, Holland MM, Stroeve JC (2007a) Perspectives on the Arctic’s shrinking sea-ice cover. Science 315:1533–1536

    Article  Google Scholar 

  • Serreze MC, Barrett AP, Slater AG, Steele M, Zhang J, Trenberth KE (2007b) The large-scale energy budget of the Arctic. J Geophys Res 112:D11122. doi:10.1029/2006JD008230

    Article  Google Scholar 

  • Stroeve JC, Serreze MC, Holland MM, Kay JE, Malanik J, Barrett AP (2012) The Arctic’s rapidly shrinking sea ice cover: a research synthesis. Clim Change 110:1005–1027

    Article  Google Scholar 

  • Thompson DJ, Li Y (2015) Baroclinic and barotropic annular variability in the Northern Hemisphere. J Atmos Sci 72:1117–1136

    Article  Google Scholar 

  • Thompson DWJ, Wallace JM (1998) The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett 25:1297–1300

    Article  Google Scholar 

  • Toole JM, Krishfield RA, Timmermans M-L, Proshutinsky A (2011) The ice-tethered profiler: Argo of the Arctic. Oceanography 24(3):126–135. doi:10.5670/oceanog.2011.64

    Article  Google Scholar 

  • Uppala SM, KÅllberg PW, Simmons AJ, Andrae U, Bechtold VDC, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Berg LVD, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hólm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, Mcnally AP, Mahfouf J-F, Morcrette J-J, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012. doi:10.1256/qj.04.176

    Article  Google Scholar 

  • Vihma T (2014) Effects of Arctic sea ice decline on weather and climate: a review. Surv Geophys 35:1175–1214. doi:10.1007/s10712-014-9284-0

    Article  Google Scholar 

  • von Storch H, Zwiers FW (1999) Statistical analysis in climate research. Cambridge University Press, Cambridge, p 484

    Book  Google Scholar 

  • Wallace JM, Hobbs PV (2006) Atmospheric science: an introductory survey, 2nd edn. Academic Press, London, p 504

    Google Scholar 

  • Walsh JE (1978) Temporal and spatial scales of Arctic circulation. Mon Weather Rev 106(11):1532–1544

    Article  Google Scholar 

  • Wilks D (2011) Statistical methods in the atmospheric sciences, 3rd edn. Academic Press, London, p 704

    Google Scholar 

  • Yiou P, Servonnat J, Yoshimori M, Swingedouw D, Khodri M, Abe-Ouchi A (2012) Stability of weather regimes during the last millennium from climate simulations. Geophys Res Lett 39:L08703. doi:10.1029/2012GL051310

    Article  Google Scholar 

  • Zhang JL, Rothrock DA (2003) Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Mon Weather Rev 131:845–861

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge funding support for this study from the PICA-ICE (CGL2012-31987) project funded by the Ministry of Economy and Competitiveness of Spain and the SPECS (ENV-2012-308378) project funded by the Seventh Framework Programme (FP7) of the European Commission. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación through the Barcelona Supercomputing Center in Barcelona, Spain, and by the European Centre for Medium–Range Weather Forecasts in Reading, UK. The authors thank the reviewers for their constructive input, and Matthieu Chevallier, Ed Hawkins, Jonathan J. Day, Steffen Tietsche, Edward Blanchard-Wrigglesworth and Javier Garcia-Serrano for valuable discussions. Analyzed sea ice cover reconstructions with ORCA1 NEMO-LIM2 are available upon request. The new developed R functions, by Neven S. Fučkar and Virginie Guemas, used in this study are publicly available in the s2dverification package from the CRAN (http://cran.r-project.org). The s2dverification package has been continuously developed at the Climate Forecasting Unit of the Catalan Institute of Climate Sciences (IC3) and now at the Earth Sciences Department at the Barcelona Supercomputing Center (BSC-ES).

Author information

Authors and Affiliations

  1. Climate Forecasting Unit, Institut Català de Ciències del Clima (IC3), Doctora Trueta 203, 3a, 08005, Barcelona, Spain

    Neven S. Fučkar, Virginie Guemas, François Massonnet & Francisco J. Doblas-Reyes

  2. Centre National de Recherches Météorologiques/Groupe d’Etude de l’Atmosphère Météorologique, Météo-France, CNRS, Toulouse, France

    Virginie Guemas

  3. Cooperative Institute for Climate Science, Princeton University, Princeton, NJ, USA

    Nathaniel C. Johnson

  4. Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute (ELI), Université catholique de Louvain, Louvain-la-Neuve, Belgium

    François Massonnet

  5. Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS), Earth Sciences Department, Barcelona, Spain

    Neven S. Fučkar, Virginie Guemas & Francisco J. Doblas-Reyes

  6. Instituciò Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

    Francisco J. Doblas-Reyes

Authors
  1. Neven S. Fučkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Virginie Guemas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nathaniel C. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. François Massonnet
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Francisco J. Doblas-Reyes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Neven S. Fučkar.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 11310 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fučkar, N.S., Guemas, V., Johnson, N.C. et al. Clusters of interannual sea ice variability in the northern hemisphere. Clim Dyn 47, 1527–1543 (2016). https://doi.org/10.1007/s00382-015-2917-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-015-2917-2

Keywords

Search

Navigation