Abstract
Satellite observations show a small overall increase in Antarctic sea ice extent (SIE) over the period 1979–2015. However, this upward trend needs to be balanced against recent pronounced SIE fluctuations occurring there. In the space of 3 years, the SIE sank from its highest value ever reached in September 2014 to record low in February 2017. In this work, a set of six state-of-the-art global climate models is used to evaluate the potential predictability of the Antarctic sea ice at such timescales. This first multi-model study of Antarctic sea ice predictability reveals that the ice edge location can potentially be predicted up to 3 years in advance. However, the ice edge location predictability shows contrasted seasonal performances, with high predictability in winter and no predictability in summer. The reemergence of the predictability from one winter to next is provided by the ocean through its large thermal inertia. Sea surface heat anomalies are stored at depth at the end of the winter and influences the sea ice advance the following year as they resurface. The effectiveness of this mechanism across models is found to depend upon the depth of the mixed layer. One should be very cautious about these potential predictability estimates as there is evidence that the Antarctic sea ice predictability is promoted by deep Southern Ocean convection. We therefore suspect models with excessive convection to show higher sea ice potential predictability results due to an incorrect representation of the Southern Ocean.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alexander MA, Deser C (1995) A mechanism for the recurrence of wintertime midlatitude SST anomalies. J Phys Oceanogr 25(1):122–137. https://doi.org/10.1175/1520-0485(1995) 025\(<\)0122:amftro\(>\)2.0.co;2
Armour KC, Eisenman I, Blanchard-Wrigglesworth E, McCusker KE, Bitz CM (2011) The reversibility of sea ice loss in a state-of-the-art climate model. Geophys Res Lett. https://doi.org/10.1029/2011gl048739
Barthélemy A, Fichefet T, Goosse H, Madec G (2015) Modeling the interplay between sea ice formation and the oceanic mixed layer: limitations of simple brine rejection parameterizations. Ocean Model 86:141–152. https://doi.org/10.1016/j.ocemod.2014.12.009
Behrens E, Rickard G, Morgenstern O, Martin T, Osprey A, Joshi M (2016) Southern Ocean deep convection in global climate models: a driver for variability of subpolar gyres and Drake Passage transport on decadal timescales. J Geophys Res Oceans 121(6):3905–3925. https://doi.org/10.1002/2015jc011286
Bintanja R, van Oldenborgh GJ, Drijfhout SS, Wouters B, Katsman CA (2013) Important role for ocean warming and increased ice-shelf melt in Antarctic sea-ice expansion. Nat Geosci 6(5):376–379. https://doi.org/10.1038/ngeo1767
Bitz CM, Polvani LM (2012) Antarctic climate response to stratospheric ozone depletion in a fine resolution ocean climate model. Geophys Res Lett. https://doi.org/10.1029/2012GL053393
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(1):231–250. https://doi.org/10.1175/2010jcli3775.1
de Boyer Montégut C (2004) Mixed layer depth over the global ocean: an examination of profile data and a profile-based climatology. J Geophys Res. https://doi.org/10.1029/2004jc002378
Bushuk M, Msadek R, Winton M, Vecchi GA, Gudgel R, Rosati A, Yang X (2017) Skillful regional prediction of Arctic sea ice on seasonal timescales. Geophys Res Lett. https://doi.org/10.1002/2017gl073155
Chevallier M, Salas-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(8):3025–3038. https://doi.org/10.1175/jcli-d-11-00209.1
Comiso JC, Gersten RA, Stock LV, Turner J, Perez GJ, Cho K (2017) Positive trend in the Antarctic sea ice cover and associated changes in surface temperature. J Clim 30(6):2251–2267. https://doi.org/10.1175/JCLI-D-16-0408.1
Day JJ, Hawkins E, Tietsche S (2014a) Will Arctic sea ice thickness initialization improve seasonal forecast skill? Geophys Res Lett 41(21):7566–7575. https://doi.org/10.1002/2014GL061694
Day JJ, Tietsche S, Hawkins E (2014b) Pan-Arctic and regional sea ice predictability: initialization month dependence. J Clim 27(12):4371–4390. https://doi.org/10.1175/jcli-d-13-00614.1
Day JJ, Tietsche S, Collins M, Goessling HF, Guemas V, Guillory A, Hurlin WJ, Ishii M, Keeley SPE, Matei D, Msadek R, Sigmond M, Tatebe H, Hawkins E (2016) The Arctic predictability and prediction on seasonal-to-interannual TimEscales (apposite) data set version 1. Geosci Model Dev 9(6):2255–2270. https://doi.org/10.5194/gmd-9-2255-2016
Ding Q, Steig EJ, Battisti DS, Küttel M (2011) Winter warming in West Antarctica caused by central tropical Pacific warming. Nat Geosci 4(6):398–403. https://doi.org/10.1038/ngeo1129
Dommenget D, Latif M (2002) Analysis of observed and simulated SST spectra in the midlatitudes. Clim Dyn 19(3–4):277–288. https://doi.org/10.1007/s00382-002-0229-9
Dong S, Sprintall J, Gille ST, Talley L (2008) Southern Ocean mixed-layer depth from Argo float profiles. J Geophys Res. https://doi.org/10.1029/2006jc004051
Donner LJ, Wyman BL, Hemler RS, Horowitz LW, Ming Y, Zhao M, Golaz JC, Ginoux P, Lin SJ, Schwarzkopf MD, Austin J, Alaka G, Cooke WF, Delworth TL, Freidenreich SM, Gordon CT, Griffies SM, Held IM, Hurlin WJ, Klein SA, Knutson TR, Langenhorst AR, Lee HC, Lin Y, Magi BI, Malyshev SL, Milly PCD, Naik V, Nath MJ, Pincus R, Ploshay JJ, Ramaswamy V, Seman CJ, Shevliakova E, Sirutis JJ, Stern WF, Stouffer RJ, Wilson RJ, Winton M, Wittenberg AT, Zeng F (2011) The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J Clim 24(13):3484–3519. https://doi.org/10.1175/2011jcli3955.1
EUMETSAT Ocean and Sea Ice Satelitte Application Facility (2015) Global sea ice concentration climate data records 1978–2015 (v1.2) [Online]. Norwegian and Danish Meteorological Institutes. https://doi.org/10.15770/EUM_SAF_OSI_0001. https://doi.org/10.15770/EUM_SAF_OSI_0005
Ferreira D, Marshall J, Bitz CM, Solomon S, Plumb A (2015) Antarctic ocean and sea ice response to ozone depletion: a two-time-scale problem. J Clim 28(3):1206–1226. https://doi.org/10.1175/JCLI-D-14-00313.1
Goosse H, Zunz V (2014) Decadal trends in the Antarctic sea ice extent ultimately controlled by ice-ocean feedback. Cryosphere 8(2):453–470. https://doi.org/10.5194/tc-8-453-2014
Gordon AL, Taylor HW (1975) Seasonal change of Antarctic sea ice cover. Science 187(4174):346–347. https://doi.org/10.1126/science.187.4174.346
Griffies SM, Winton M, Donner LJ, Horowitz LW, Downes SM, Farneti R, Gnanadesikan A, Hurlin WJ, Lee HC, Liang Z, Palter JB, Samuels BL, Wittenberg AT, Wyman BL, Yin J, Zadeh N (2011) The GFDL CM3 coupled climate model: characteristics of the ocean and sea ice simulations. J Clim 24(13):3520–3544. https://doi.org/10.1175/2011jcli3964.1
Guemas V, Chevallier M, Déqué M, Bellprat O, Doblas-Reyes F (2016) Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales. Geophys Res Lett 43(8):3889–3896. https://doi.org/10.1002/2015GL066626
Hanawa K, Sugimoto S (2004) ‘reemergence’ areas of winter sea surface temperature anomalies in the world’s oceans. Geophys Res Lett. https://doi.org/10.1029/2004GL019904
Haumann FA, Notz D, Schmidt H (2014) Anthropogenic influence on recent circulation-driven Antarctic sea ice changes. Geophys Res Lett 41(23):8429–8437. https://doi.org/10.1002/2014GL061659,2014GL061659
Hawkins E, Tietsche S, Day JJ, Melia N, Haines K, Keeley S (2016) Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems. Q J R Meteorol Soc 142(695):672–683. https://doi.org/10.1002/qj.2643
Hazeleger W, Wang X, Severijns C, Ştefănescu S, Bintanja R, Sterl A, Wyser K, Semmler T, Yang S, van den Hurk B, van Noije T, van der Linden E, van der Wiel K, (2011) EC-Earth V2.2: description and validation of a new seamless earth system prediction model. Clim Dyn 39(11):2611–2629. https://doi.org/10.1007/s00382-011-1228-5
Heuzé C, Heywood KJ, Stevens DP, Ridley JK (2013) Southern Ocean bottom water characteristics in CMIP5 models. Geophys Res Lett 40(7):1409–1414. https://doi.org/10.1002/grl.50287
Holland MM, Blanchard-Wrigglesworth E, Kay J, Vavrus S (2013) Initial-value predictability of Antarctic sea ice in the Community Climate System Model 3. Geophys Res Lett 40(10):2121–2124. https://doi.org/10.1002/grl.50410
Holland PR, Kwok R (2012) Wind-driven trends in Antarctic sea-ice drift. Nat Geosci 5(12):872–875. https://doi.org/10.1038/ngeo1627
Holte J, Talley L (2009) A new algorithm for finding mixed layer depths with applications to Argo data and Subantarctic Mode Water formation*. J Atmos Ocean Technol 26(9):1920–1939. https://doi.org/10.1175/2009jtecho543.1
Ivanova N, Pedersen LT, Tonboe RT, Kern S, Heygster G, Lavergne T, Sørensen A, Saldo R, Dybkjær G, Brucker L, Shokr M (2015) Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations. Cryosphere 9(5):1797–1817. https://doi.org/10.5194/tc-9-1797-2015
Johns TC, Durman CF, Banks HT, Roberts MJ, McLaren AJ, Ridley JK, Senior CA, Williams KD, Jones A, Rickard GJ, Cusack S, Ingram WJ, Crucifix M, Sexton DMH, Joshi MM, Dong BW, Spencer H, Hill RSR, Gregory JM, Keen AB, Pardaens AK, Lowe JA, Bodas-Salcedo A, Stark S, Searl Y (2006) The new Hadley Centre climate model (HadGEM1): evaluation of coupled simulations. J Clim 19(7):1327–1353. https://doi.org/10.1175/jcli3712.1
Jungclaus JH, Fischer N, Haak H, Lohmann K, Marotzke J, Matei D, Mikolajewicz U, Notz D, von Storch JS (2013) Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model. J Adv Model Earth Syst 5(2):422–446. https://doi.org/10.1002/jame.20023
Koenigk T, Mikolajewicz U (2008) Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model. Clim Dyn 32(6):783–798. https://doi.org/10.1007/s00382-008-0419-1
Latif M, Martin T, Park W (2013) Southern Ocean sector centennial climate variability and recent decadal trends. J Clim 26(19):7767–7782. https://doi.org/10.1175/JCLI-D-12-00281.1
Lecomte O, Goosse H, Fichefet T, de Lavergne C, Barthélemy A, Zunz V (2017) Vertical ocean heat redistribution sustaining sea-ice concentration trends in the Ross Sea. Nat Commun 8:258. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557847/. Accessed 12 Sept 2017
Li X, Holland DM, Gerber EP, Yoo C (2014) Impacts of the north and tropical Atlantic ocean on the Antarctic Peninsula and sea ice. Nature 505(7484):538–542. https://doi.org/10.1038/nature12945
Mahlstein I, Gent PR, Solomon S (2013) Historical Antarctic mean sea ice area, sea ice trends, and winds in CMIP5 simulations. J Geophys Res Atmos 118(11):5105–5110. https://doi.org/10.1002/jgrd.50443
Martinson DG (1990) Evolution of the Southern Ocean winter mixed layer and sea ice: open ocean deepwater formation and ventilation. J Geophys Res Oceans 95(C7):11641–11654. https://doi.org/10.1029/JC095iC07p11641
Meehl GA, Arblaster JM, Bitz CM, Chung CTY, Teng H (2016) Antarctic sea-ice expansion between 2000 and 2014 driven by tropical Pacific decadal climate variability. Nat Geosci 9(8):590–595. https://doi.org/10.1038/ngeo2751
Notz D, Haumann FA, Haak H, Jungclaus JH, Marotzke J (2013) Arctic sea-ice evolution as modeled by Max Planck Institute for Meteorology’s Earth system model. J Adv Model Earth Syst 5(2):173–194. https://doi.org/10.1002/jame.20016
Okumura YM, Schneider D, Deser C, Wilson R (2012) Decadal-interdecadal climate variability over Antarctica and linkages to the tropics: analysis of ice core, instrumental, and tropical proxy data. J Clim 25(21):7421–7441. https://doi.org/10.1175/jcli-d-12-00050.1
Park YH, Charriaud E, Fieux M (1998) Thermohaline structure of the Antarctic Surface Water/Winter Water in the Indian sector of the Southern Ocean. J Mar Syst 17(1–4):5–23. https://doi.org/10.1016/s0924-7963(98)00026-8
Parkinson CL, Cavalieri DJ (2012) Antarctic sea ice variability and trends, 1979–2010. Cryosphere 6(4):871–880. https://doi.org/10.5194/tc-6-871-2012
Pauling AG, Bitz CM, Smith IJ, Langhorne PJ (2016) The response of the Southern Ocean and Antarctic sea ice to freshwater from ice shelves in an earth system model. J Clim 29(5):1655–1672. https://doi.org/10.1175/jcli-d-15-0501.1
Pellichero V, Sallée JB, Schmidtko S, Roquet F, Charrassin JB (2017) The ocean mixed layer under Southern Ocean sea-ice: seasonal cycle and forcing. J Geophys Res Oceans 122(2):1608–1633. https://doi.org/10.1002/2016jc011970
Pohlmann H, Botzet M, Latif M, Roesch A, Wild M, Tschuck P (2004) Estimating the decadal predictability of a coupled AOGCM. J Clim 17(22):4463–4472. https://doi.org/10.1175/3209.1
Polvani LM, Smith KL (2013) Can natural variability explain observed Antarctic sea ice trends? New modeling evidence from CMIP5. Geophys Res Lett 40(12):3195–3199. https://doi.org/10.1002/grl.50578
Purich A, Cai W, England MH, Cowan T (2016) Evidence for link between modelled trends in Antarctic sea ice and underestimated westerly wind changes. Nat Commun 7:10409. https://doi.org/10.1038/ncomms10409
Raphael MN, Marshall GJ, Turner J, Fogt RL, Schneider D, Dixon DA, Hosking JS, Jones JM, Hobbs WR (2016) The Amundsen Sea Low: variability, change, and impact on Antarctic climate. Bull Am Meteorol Soc 97(1):111–121. https://doi.org/10.1175/BAMS-D-14-00018.1
Sallée JB, Wienders N, Speer K, Morrow R (2006) Formation of subantarctic mode water in the southeastern Indian Ocean. Ocean Dyn 56(5–6):525–542. https://doi.org/10.1007/s10236-005-0054-x
Shaffrey LC, Stevens I, Norton WA, Roberts MJ, Vidale PL, Harle JD, Jrrar A, Stevens DP, Woodage MJ, Demory ME, Donners J, Clark DB, Clayton A, Cole JW, Wilson SS, Connolley WM, Davies TM, Iwi AM, Johns TC, King JC, New AL, Slingo JM, Slingo A, Steenman-Clark L, Martin GM (2009) U.K. HiGEM: The new U.K. high-resolution global environment model–model description and basic evaluation. J Clim 22(8):1861–1896. https://doi.org/10.1175/2008jcli2508.1
Sidorenko D, Rackow T, Jung T, Semmler T, Barbi D, Danilov S, Dethloff K, Dorn W, Fieg K, Goessling HF, Handorf D, Harig S, Hiller W, Juricke S, Losch M, Schröter J, Sein DV, Wang Q (2014) Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part i: model formulation and mean climate. Clim Dyn 44(3–4):757–780. https://doi.org/10.1007/s00382-014-2290-6
Sigmond M, Fyfe JC (2014) The Antarctic sea ice response to the ozone hole in climate models. J Clim 27(3):1336–1342. https://doi.org/10.1175/JCLI-D-13-00590.1
Simpkins GR, McGregor S, Taschetto AS, Ciasto LM, England MH (2014) Tropical connections to climatic change in the Extratropical Southern Hemisphere: the role of Atlantic SST trends. J Clim 27(13):4923–4936. https://doi.org/10.1175/jcli-d-13-00615.1
Stammerjohn SE, Martinson DG, Smith RC, Yuan X, Rind D (2008) Trends in Antarctic annual sea ice retreat and advance and their relation to ElNño–Southern Oscillation and Southern Annular Mode variability. J Geophys Res Oceans. https://doi.org/10.1029/2007JC004269
Stuecker MF, Bitz CM, Armour KC (2017) Conditions leading to the unprecedented low Antarctic sea ice extent during the 2016 austral spring season. Geophys Res Lett 44(17):9008–9019. https://doi.org/10.1002/2017gl074691
Swart NC, Fyfe JC (2013) The influence of recent Antarctic ice sheet retreat on simulated sea ice area trends. Geophys Res Lett 40(16):4328–4332. https://doi.org/10.1002/grl.50820
Thompson DWJ, Solomon S, Kushner PJ, England MH, Grise KM, Karoly DJ (2011) Signatures of the Antarctic ozone hole in Southern Hemisphere surface climate change. Nat Geosci 4(11):741–749. https://doi.org/10.1038/ngeo1296
Tietsche S, Day JJ, Guemas V, Hurlin WJ, Keeley SPE, Matei D, Msadek R, Collins M, Hawkins E (2014) Seasonal to interannual Arctic sea ice predictability in current global climate models. Geophys Res Lett 41(3):1035–1043. https://doi.org/10.1002/2013GL058755
Timlin MS, Alexander MA, Deser C (2002) On the reemergence of North Atlantic SST anomalies. J Clim 15(18):2707–2712. https://doi.org/10.1175/1520-0442(2002) 015\(<\)2707:OTRONA\(>\)2.0.CO;2
Timmermann R, Danilov S, Schröter J, Böning C, Sidorenko D, Rollenhagen K (2009) Ocean circulation and sea ice distribution in a finite element global sea ice-ocean model. Ocean Model 27(3–4):114–129. https://doi.org/10.1016/j.ocemod.2008.10.009
Turner J, Bracegirdle TJ, Phillips T, Marshall GJ, Hosking JS (2013a) An initial assessment of Antarctic sea ice extent in the CMIP5 models. J Clim 26(5):1473–1484. https://doi.org/10.1175/JCLI-D-12-00068.1
Turner J, Phillips T, Hosking JS, Marshall GJ, Orr A (2013b) The Amundsen Sea low. Int J Climatol 33(7):1818–1829. https://doi.org/10.1002/joc.3558
Turner J, Phillips T, Marshall GJ, Hosking JS, Pope JO, Bracegirdle TJ, Deb P (2017) Unprecedented springtime retreat of Antarctic sea ice in 2016. Geophys Res Lett 44(13):6868–6875. https://doi.org/10.1002/2017gl073656
Watanabe M, Suzuki T, Oishi R, Komuro Y, Watanabe S, Emori S, Takemura T, Chikira M, Ogura T, Sekiguchi M, Takata K, Yamazaki D, Yokohata T, Nozawa T, Hasumi H, Tatebe H, Kimoto M (2010) Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity. J Clim 23(23):6312–6335. https://doi.org/10.1175/2010JCLI3679.1
Wong APS, Riser SC (2011) Profiling float observations of the upper ocean under sea ice off the Wilkes Land coast of Antarctica. J Phys Oceanogr 41(6):1102–1115. https://doi.org/10.1175/2011jpo4516.1
Yang CY, Liu J, Hu Y, Horton RM, Chen L, Cheng X (2016) Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts. Cryosphere 10(5):2429–2452. https://doi.org/10.5194/tc-10-2429-2016
Zunz V, Goosse H, Massonnet F (2013) How does internal variability influence the ability of CMIP5 models to reproduce the recent trend in Southern Ocean sea ice extent? Cryosphere 7(2):451–468. https://doi.org/10.5194/tc-7-451-2013
Zunz V, Goosse H, Dubinkina S (2014) Impact of the initialisation on the predictability of the Southern Ocean sea ice at interannual to multi-decadal timescales. Clim Dyn. https://doi.org/10.1007/s00382-014-2344-9
Acknowledgements
We thank the two referees for their very helpful comments on an earlier version of this manuscript. Hugues Goosse is Research Director within the Fonds National de la Recherche Scientifique (F.R.S.-FNRS-Belgium).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Marchi, S., Fichefet, T., Goosse, H. et al. Reemergence of Antarctic sea ice predictability and its link to deep ocean mixing in global climate models. Clim Dyn 52, 2775–2797 (2019). https://doi.org/10.1007/s00382-018-4292-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-018-4292-2