Antarctic offshore polynyas linked to Southern Hemisphere climate anomalies

Abstract

Offshore Antarctic polynyas—large openings in the winter sea ice cover—are thought to be maintained by a rapid ventilation of deep-ocean heat through convective mixing. These rare phenomena may alter abyssal properties and circulation, yet their formation mechanisms are not well understood. Here we demonstrate that concurrent upper-ocean preconditioning and meteorological perturbations are responsible for the appearance of polynyas in the Weddell Sea region of the Southern Ocean. Autonomous profiling float observations—collected in 2016 and 2017 during the largest polynyas to form near the Maud Rise seamount since 1976—reveal that the polynyas were initiated and modulated by the passage of severe storms, and that intense heat loss drove deep overturning within them. Wind-driven upwelling of record strength weakened haline stratification in the upper ocean, thus favouring destabilization in 2016 and 2017. We show that previous Weddell polynyas probably developed under similarly anomalous conditions, which are associated with a mode of Southern Hemisphere climate variability that is predicted to strengthen as a result of anthropogenic climate change.

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Fig. 1: Polynyas of 1974, 2016 and 2017 in relation to profiling float trajectories near Maud Rise.
Fig. 2: Storms, sea ice concentration and mixed-layer salinity at Maud Rise in 2016 and 2017.
Fig. 3: Local meteorology and heat loss during the 2016 polynya.
Fig. 4: Hydrographic observations from Maud Rise from 2011–2018.
Fig. 5: Relationships between past polynyas near Maud Rise and climate forcing from 1972–2018.

Data availability

The data analysed in this article are all publicly available, with the exception of updates to the UW Calibrated O2 package, described below:

Ocean bathymetry data were obtained from the ETOPO1 1 Arc-Minute Global Relief Model114 at https://doi.org/10.7289/V5C8276M (accessed February 2017).

Sea ice concentration data were obtained for the period 1972–1977 from the NSIDC Nimbus-5 ESMR v1 product53 at https://doi.org/10.5067/W2PKTWMTY0TP (accessed February 2017); for the period 1978–2017 from the merged NASA Goddard v3 product54 at https://doi.org/10.7265/N59P2ZTG (accessed October 2018); for January 2018–February 2019 from the NOAA/NSIDC Near-Real-Time CDR v1 product56 at https://doi.org/10.7265/N5FF3QJ6 (accessed February 2019); and for the period 2002–2019 from the University of Bremen ASI AMSR-E and AMSR2 v5 products57,58 at https://seaice.uni-bremen.de/sea-ice-concentration/ (accessed February 2019).

Profiling float temperature and salinity measurements were obtained from the US-GODAE GDAC70 at http://www.usgodae.org/ftp/outgoing/argo (accessed October 2018). Dissolved oxygen measurements for floats 5904468 and 5904471 were obtained from the SOCCOM quality-controlled archive74 at https://doi.org/10.6075/J02J6968 (accessed January 2019) and for float 5903616 from the UW Calibrated O2 package, v1.175 at http://runt.ocean.washington.edu/o2 (accessed August 2016), with updated dissolved oxygen profiles provided by R. Drucker (personal communication, August 2017).

Shipboard and elephant seal temperature and salinity measurements were obtained from the World Ocean Database 2018 prerelease77 with August 2018 additions at http://www.nodc.noaa.gov/OC5/SELECT/dbsearch/dbsearch.html (accessed October 2018).

Gridded climatological ocean temperature fields were obtained from the 2018 WAGHC91 at http://icdc.cen.uni-hamburg.de/1/daten/ocean/waghc (accessed January 2018).

The monthly SAM index98 was obtained for the period 1972–2019 at http://legacy.bas.ac.uk/met/gjma/sam.html (accessed February 2019).

Monthly and daily ERA-I atmospheric reanalysis fields99 were obtained for the period 1979–2018 using the Python MARS API, described at https://confluence.ecmwf.int/display/WEBAPI/ (accessed February 2019).

Queen Maud Land pressure records (see Methods section ‘Meteorological station records’) were obtained from the READER archive110 at http://legacy.bas.ac.uk/met/READER (accessed February 2019) and the NOAA-NCEI ISD111 at http://www.ncdc.noaa.gov/isd (accessed February 2019).

Code availability

Analytical scripts used to generate the figures in this paper are available at https://github.com/ethan-campbell.

References

  1. 1.

    Gordon, A. L. Deep Antarctic convection west of Maud Rise. J. Phys. Oceanogr. 8, 600–612 (1978).

    ADS  Google Scholar 

  2. 2.

    Martinson, D. G., Killworth, P. D. & Gordon, A. L. A convective model for the Weddell Polynya. J. Phys. Oceanogr. 11, 466–488 (1981).

    ADS  Google Scholar 

  3. 3.

    Martinson, D. G. Evolution of the Southern Ocean winter mixed layer and sea ice: Open ocean deepwater formation and ventilation. J. Geophys. Res. 95, 11641–11654 (1990).

    ADS  Google Scholar 

  4. 4.

    Zanowski, H., Hallberg, R. & Sarmiento, J. L. Abyssal ocean warming and salinification after Weddell polynyas in the GFDL CM2G coupled climate model. J. Phys. Oceanogr. 45, 2755–2772 (2015).

    ADS  Google Scholar 

  5. 5.

    Martin, T., Park, W. & Latif, M. Multi-centennial variability controlled by Southern Ocean convection in the Kiel Climate Model. Clim. Dyn. 40, 2005–2022 (2013).

    Google Scholar 

  6. 6.

    Cheon, W. G., Park, Y.-G., Toggweiler, J. R. & Lee, S.-K. The relationship of Weddell Polynya and open-ocean deep convection to the Southern Hemisphere westerlies. J. Phys. Oceanogr. 44, 694–713 (2014).

    ADS  Google Scholar 

  7. 7.

    Heuzé, C., Ridley, J. K., Calvert, D., Stevens, D. P. & Heywood, K. J. Increasing vertical mixing to reduce Southern Ocean deep convection in NEMO3.4. Geosci. Model Dev. 8, 3119–3130 (2015).

    ADS  Google Scholar 

  8. 8.

    Behrens, E. et al. 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, 3905–3925 (2016).

    ADS  Google Scholar 

  9. 9.

    Pedro, J. B. et al. Southern Ocean deep convection as a driver of Antarctic warming events. Geophys. Res. Lett. 43, 2192–2199 (2016).

    ADS  Google Scholar 

  10. 10.

    Zhang, L., Delworth, T. L., Cooke, W. & Yang, X. Natural variability of Southern Ocean convection as a driver of observed climate trends. Nat. Clim. Change 9, 59–65 (2019).

    ADS  Google Scholar 

  11. 11.

    Bernardello, R., Marinov, I., Palter, J. B., Galbraith, E. D. & Sarmiento, J. L. Impact of Weddell Sea deep convection on natural and anthropogenic carbon in a climate model. Geophys. Res. Lett. 41, 7262–7269 (2014).

    ADS  CAS  Google Scholar 

  12. 12.

    Resplandy, L., Séférian, R. & Bopp, L. Natural variability of CO2 and O2 fluxes: what can we learn from centuries-long climate models simulations? J. Geophys. Res. Oceans 120, 384–404 (2015).

    ADS  CAS  Google Scholar 

  13. 13.

    Moore, G. W. K., Alverson, K. & Renfrew, I. A. A reconstruction of the air–sea interaction associated with the Weddell polynya. J. Phys. Oceanogr. 32, 1685–1698 (2002).

    ADS  Google Scholar 

  14. 14.

    Weijer, W. et al. Local atmospheric response to an open-ocean polynya in a high-resolution climate model. J. Clim. 30, 1629–1641 (2017).

    ADS  Google Scholar 

  15. 15.

    Cabré, A., Marinov, I. & Gnanadesikan, A. Global atmospheric teleconnections and multidecadal climate oscillations driven by Southern Ocean convection. J. Clim. 30, 8107–8126 (2017).

    ADS  Google Scholar 

  16. 16.

    Amblas, D. & Dowdeswell, J. A. Physiographic influences on dense shelf-water cascading down the Antarctic continental slope. Earth Sci. Rev. 185, 887–900 (2018).

    Google Scholar 

  17. 17.

    Smith, J. A., Hillenbrand, C.-D., Pudsey, C. J., Allen, C. S. & Graham, A. G. C. The presence of polynyas in the Weddell Sea during the Last Glacial Period with implications for the reconstruction of sea-ice limits and ice sheet history. Earth Planet. Sci. Lett. 296, 287–298 (2010).

    ADS  CAS  Google Scholar 

  18. 18.

    Broecker, W. S., Sutherland, S. & Peng, T.-H. A possible 20th-century slowdown of Southern Ocean deep water formation. Science 286, 1132–1135 (1999).

    CAS  PubMed  Google Scholar 

  19. 19.

    de Lavergne, C., Palter, J. B., Galbraith, E. D., Bernardello, R. & Marinov, I. Cessation of deep convection in the open Southern Ocean under anthropogenic climate change. Nat. Clim. Change 4, 278–282 (2014).

    Google Scholar 

  20. 20.

    Heuzé, C., Heywood, K. J., Stevens, D. P. & Ridley, J. K. Southern Ocean bottom water characteristics in CMIP5 models. Geophys. Res. Lett. 40, 1409–1414 (2013).

    ADS  Google Scholar 

  21. 21.

    Kjellsson, J. et al. Model sensitivity of the Weddell and Ross seas, Antarctica, to vertical mixing and freshwater forcing. Ocean Model. 94, 141–152 (2015).

    ADS  Google Scholar 

  22. 22.

    Reintges, A., Martin, T., Latif, M. & Park, W. Physical controls of Southern Ocean deep-convection variability in CMIP5 models and the Kiel Climate Model. Geophys. Res. Lett. 44, 6951–6958 (2017).

    ADS  Google Scholar 

  23. 23.

    Comiso, J. C. & Gordon, A. L. Recurring polynyas over the Cosmonaut Sea and the Maud Rise. J. Geophys. Res. 92, 2819–2833 (1987).

    ADS  Google Scholar 

  24. 24.

    Carsey, F. D. Microwave observation of the Weddell polynya. Mon. Weath. Rev. 108, 2032–2044 (1980).

    ADS  Google Scholar 

  25. 25.

    Lindsay, R. W., Holland, D. M. & Woodgate, R. A. Halo of low ice concentration observed over the Maud Rise seamount. Geophys. Res. Lett. 31, L13302 (2004).

    ADS  Google Scholar 

  26. 26.

    Swart, S. et al. Return of the Maud Rise polynya: climate litmus or sea ice anomaly? [in "State of the Climate in 2017"]. Bull. Am. Meteorol. Soc. 99, S188–S189 (2018).

  27. 27.

    Wang, G. et al. Compounding tropical and stratospheric forcing of the record low Antarctic sea-ice in 2016. Nat. Commun. 10, 13 (2019).

    ADS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nat. Commun. 10, 14 (2019).

    ADS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Gordon, A. L. & Huber, B. A. Southern Ocean winter mixed layer. J. Geophys. Res. 95, 11655–11672 (1990).

    ADS  Google Scholar 

  30. 30.

    Holland, D. M. Explaining the Weddell Polynya—a large ocean eddy shed at Maud Rise. Science 292, 1697–1700 (2001).

    ADS  CAS  PubMed  Google Scholar 

  31. 31.

    de Steur, L., Holland, D. M., Muench, R. D. & McPhee, M. G. The warm-water “Halo” around Maud Rise: properties, dynamics and impact. Deep Sea Res. Part I 54, 871–896 (2007).

    Google Scholar 

  32. 32.

    Kurtakoti, P., Veneziani, M., Stössel, A. & Weijer, W. Preconditioning and formation of Maud Rise polynyas in a high-resolution earth system model. J. Clim. 31, 9659–9678 (2018).

    ADS  Google Scholar 

  33. 33.

    Wilson, E. A., Riser, S. C., Campbell, E. C. & Wong, A. P. S. Winter upper-ocean stability and ice–ocean feedbacks in the sea ice-covered Southern Ocean. J. Phys. Oceanogr. 49, 1099–1117 (2019).

    ADS  Google Scholar 

  34. 34.

    Martinson, D. G. & Iannuzzi, R. A. in Antarctic Sea Ice: Physical Processes, Interactions and Variability (Antarctic Research Series) Vol. 74 (ed. Jeffries, M. O.) 243–271 (American Geophysical Union, 1998).

  35. 35.

    Timmermann, R., Lemke, P. & Kottmeier, C. Formation and maintenance of a polynya in the Weddell Sea. J. Phys. Oceanogr. 29, 1251–1264 (1999).

    ADS  Google Scholar 

  36. 36.

    McPhee, M. G. Marginal thermobaric stability in the ice-covered upper ocean over Maud Rise. J. Phys. Oceanogr. 30, 2710–2722 (2000).

    ADS  Google Scholar 

  37. 37.

    Itkin, P. et al. Thin ice and storms: sea ice deformation from buoy arrays deployed during N-ICE2015. J. Geophys. Res. Oceans 122, 4661–4674 (2017).

    ADS  Google Scholar 

  38. 38.

    McPhee, M. G. et al. The Antarctic Zone Flux Experiment. Bull. Am. Meteorol. Soc. 77, 1221–1232 (1996).

    ADS  Google Scholar 

  39. 39.

    Våge, K. et al. Surprising return of deep convection to the subpolar North Atlantic Ocean in winter 2007–2008. Nat. Geosci. 2, 67–72 (2009).

    ADS  Google Scholar 

  40. 40.

    Testor, P. et al. Multiscale observations of deep convection in the northwestern Mediterranean Sea during winter 2012–2013 using multiple platforms. J. Geophys. Res. Oceans 123, 1745–1776 (2018).

    ADS  Google Scholar 

  41. 41.

    Motoi, T., Ono, N. & Wakatsuchi, M. A mechanism for the formation of the Weddell Polynya in 1974. J. Phys. Oceanogr. 17, 2241–2247 (1987).

    ADS  Google Scholar 

  42. 42.

    Mantyla, A. W. & Reid, J. L. Abyssal characteristics of the World Ocean waters. Deep-Sea Res. A 30, 805–833 (1983).

    ADS  CAS  Google Scholar 

  43. 43.

    Jullion, L. et al. The contribution of the Weddell Gyre to the lower limb of the Global Overturning Circulation. J. Geophys. Res. Oceans 119, 3357–3377 (2014).

    ADS  Google Scholar 

  44. 44.

    Thompson, D. W. J. et al. Signatures of the Antarctic ozone hole in Southern Hemisphere surface climate change. Nat. Geosci. 4, 741–749 (2011).

    ADS  CAS  Google Scholar 

  45. 45.

    Fogt, R. L., Wovrosh, A. J., Langen, R. A. & Simmonds, I. The characteristic variability and connection to the underlying synoptic activity of the Amundsen-Bellingshausen Seas Low. J. Geophys. Res. Atmos. 117, D07111 (2012).

    ADS  Google Scholar 

  46. 46.

    Cheon, W. G. et al. Replicating the 1970s’ Weddell Polynya using a coupled ocean-sea ice model with reanalysis surface flux fields. Geophys. Res. Lett. 42, 5411–5418 (2015).

    ADS  Google Scholar 

  47. 47.

    Gordon, A. L., Visbeck, M. & Comiso, J. C. A possible link between the Weddell Polynya and the Southern Annular Mode. J. Clim. 20, 2558–2571 (2007).

    ADS  Google Scholar 

  48. 48.

    Dufour, C. O. et al. Preconditioning of the Weddell Sea polynya by the ocean mesoscale and dense water overflows. J. Clim. 30, 7719–7737 (2017).

    ADS  Google Scholar 

  49. 49.

    Sigman, D. M., Hain, M. P. & Haug, G. H. The polar ocean and glacial cycles in atmospheric CO2 concentration. Nature 466, 47–55 (2010).

    ADS  CAS  PubMed  Google Scholar 

  50. 50.

    Chang, E. K. M., Guo, Y. & Xia, X. CMIP5 multimodel ensemble projection of storm track change under global warming. J. Geophys. Res. Atmos. 117, D23118 (2012).

    ADS  Google Scholar 

  51. 51.

    Muench, R. D. et al. Maud Rise revisited. J. Geophys. Res. 106, 2423–2440 (2001).

    ADS  Google Scholar 

  52. 52.

    Meier, W. N., Gallaher, D. & Campbell, G. G. New estimates of Arctic and Antarctic sea ice extent during September 1964 from recovered Nimbus I satellite imagery. Cryosphere 7, 699–705 (2013).

    ADS  Google Scholar 

  53. 53.

    Parkinson, C. L., Comiso, J. C. & Zwally, H. J. Nimbus-5 ESMR Polar Gridded Sea Ice Concentrations v.1 https://doi.org/10.5067/W2PKTWMTY0TP (National Snow and Ice Data Center, 2004).

  54. 54.

    Meier, W. N. et al. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration v.3 https://doi.org/10.7265/N59P2ZTG (National Snow and Ice Data Center, 2017).

  55. 55.

    Meier, W. N., Peng, G., Scott, D. J. & Savoie, M. H. Verification of a new NOAA/NSIDC passive microwave sea-ice concentration climate record. Polar Res. 33, https://doi.org/10.3402/polar.v33.21004 (2014).

    Google Scholar 

  56. 56.

    Meier, W. N., Fetterer, F. & Windnagel, A. K. Near-Real-Time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration v.1 https://doi.org/10.7265/N5FF3QJ6 (National Snow and Ice Data Center, 2017).

  57. 57.

    Spreen, G., Kaleschke, L. & Heygster, G. Sea ice remote sensing using AMSR-E 89-GHz channels. J. Geophys. Res. Oceans 113, 1–14 (2008).

    Google Scholar 

  58. 58.

    Beitsch, A., Kaleschke, L. & Kern, S. Investigating high-resolution AMSR2 sea ice concentrations during the February 2013 fracture event in the Beaufort Sea. Remote Sens. 6, 3841–3856 (2014).

    ADS  Google Scholar 

  59. 59.

    JCOMM Expert Team on Sea Ice. Sea-Ice Nomenclature. WMO No. 259 (World Meteorological Organization, 2014).

  60. 60.

    Comiso, J. C., Cavalieri, D. J., Parkinson, C. L. & Gloersen, P. Passive microwave algorithms for sea ice concentration: a comparison of two techniques. Remote Sens. Environ. 60, 357–384 (1997).

    ADS  Google Scholar 

  61. 61.

    Comiso, J. C. & Steffen, K. Studies of Antarctic sea ice concentrations from satellite data and their applications. J. Geophys. Res. Oceans 106, 31361–31385 (2001).

    ADS  Google Scholar 

  62. 62.

    Comiso, J. C. & Gordon, A. L. Cosmonaut polynya in the Southern Ocean: structure and variability. J. Geophys. Res. Oceans 101, 18297–18313 (1996).

    ADS  CAS  Google Scholar 

  63. 63.

    Arbetter, T. E., Lynch, A. H. & Bailey, D. A. Relationship between synoptic forcing and polynya formation in the Cosmonaut Sea: 1. Polynya climatology. J. Geophys. Res. 109, C04022 (2004).

    ADS  Google Scholar 

  64. 64.

    Gordon, A. L. in Elsevier Oceanography Series: Deep Convection and Deep Water Formation in the Oceans Vol. 57 (eds. Chu, P. C. & Gascard, J.-C.) 17–35 (Elsevier, 1991).

  65. 65.

    Venegas, S. A. & Drinkwater, M. R. Sea ice, atmosphere and upper ocean variability in the Weddell Sea, Antarctica. J. Geophys. Res. 106, 16747–16765 (2001).

    ADS  Google Scholar 

  66. 66.

    Riser, S. C. et al. Fifteen years of ocean observations with the global Argo array. Nat. Clim. Change 6, 145–153 (2016).

    ADS  Google Scholar 

  67. 67.

    Riser, S. C., Swift, D. & Drucker, R. Profiling floats in SOCCOM: technical capabilities for studying the Southern Ocean. J. Geophys. Res. Oceans 123, 4055–4073 (2018).

    ADS  Google Scholar 

  68. 68.

    Klatt, O., Boebel, O. & Fahrbach, E. A profiling float’s sense of ice. J. Atmos. Ocean. Technol. 24, 1301–1308 (2007).

    ADS  Google Scholar 

  69. 69.

    Wong, A. P. S. & Riser, S. C. Profiling float observations of the upper ocean under sea ice off the Wilkes Land coast of Antarctica. J. Phys. Oceanogr. 41, 1102–1115 (2011).

    ADS  Google Scholar 

  70. 70.

    Carval, T. et al. Argo User’s Manual v. 3.2 (Argo, 2017).

  71. 71.

    Chamberlain, P. M. et al. Observing the ice-covered Weddell Gyre with profiling floats: position uncertainties and correlation statistics. J. Geophys. Res. Oceans 123, 8383–8410 (2018).

    ADS  Google Scholar 

  72. 72.

    Meredith, M. P. et al. Circulation, retention, and mixing of waters within the Weddell-Scotia Confluence, Southern Ocean: The role of stratified Taylor columns. J. Geophys. Res. Oceans 120, 547–562 (2015).

    ADS  Google Scholar 

  73. 73.

    Talley, L. D. et al. Southern Ocean biogeochemical float deployment strategy, with example from the Greenwich Meridian line (GO-SHIP A12). J. Geophys. Res. Oceans 124, 403–431 (2019).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  74. 74.

    Johnson, K. S. et al. Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Float Data Archive - Snapshot 2018-12-31, https://doi.org/10.6075/J02J6968 (UC San Diego, 2019).

  75. 75.

    Drucker, R. & Riser, S. C. In situ phase-domain calibration of oxygen Optodes on profiling floats. Methods Oceanogr. 17, 296–318 (2016).

    Google Scholar 

  76. 76.

    Johnson, K. S. et al. Biogeochemical sensor performance in the SOCCOM profiling float array. J. Geophys. Res. Oceans 122, 6416–6436 (2017).

    ADS  Google Scholar 

  77. 77.

    Boyer, T. P. et al. World Ocean Database 2018. NOAA Atlas NESDIS 87 (NOAA, 2018).

  78. 78.

    Roquet, F. et al. A Southern Indian Ocean database of hydrographic profiles obtained with instrumented elephant seals. Sci. Data 1, 140028 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79.

    Boehme, L. et al. Animal-borne CTD-Satellite Relay Data Loggers for real-time oceanographic data collection. Ocean Sci. 5, 685–695 (2009).

    ADS  Google Scholar 

  80. 80.

    Siegelman, L. et al. Correction and accuracy of high- and low-resolution CTD data from animal-borne instruments. J. Atmos. Ocean. Technol. 36, 745–760 (2019).

    ADS  Google Scholar 

  81. 81.

    de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A. & Iudicone, D. Mixed layer depth over the global ocean: an examination of profile data and a profile-based climatology. J. Geophys. Res. 109, C12003 (2004).

    ADS  Google Scholar 

  82. 82.

    Dong, S., Sprintall, J., Gille, S. T. & Talley, L. Southern Ocean mixed-layer depth from Argo float profiles. J. Geophys. Res. 113, C06013 (2008).

    ADS  Google Scholar 

  83. 83.

    Marshall, J. & Schott, F. Open-ocean convection: observations, theory, and models. Rev. Geophys. 37, 1–64 (1999).

    ADS  Google Scholar 

  84. 84.

    Margirier, F. et al. Characterization of convective plumes associated with oceanic deep convection in the northwestern Mediterranean from high-resolution in situ data collected by gliders. J. Geophys. Res. Oceans 122, 9814–9826 (2017).

    ADS  Google Scholar 

  85. 85.

    Haumann, F. A., Gruber, N., Münnich, M., Frenger, I. & Kern, S. Sea-ice transport driving Southern Ocean salinity and its recent trends. Nature 537, 89–92 (2016).

    ADS  CAS  PubMed  Google Scholar 

  86. 86.

    Charrassin, J.-B. et al. Southern Ocean frontal structure and sea-ice formation rates revealed by elephant seals. Proc. Natl Acad. Sci. USA 105, 11634–11639 (2008).

    ADS  CAS  PubMed  Google Scholar 

  87. 87.

    Bailey, D. A., Rhines, P. B. & Häkkinen, S. Formation and pathways of North Atlantic Deep Water in a coupled ice–ocean model of the Arctic–North Atlantic Oceans. Clim. Dyn. 25, 497–516 (2005).

    Google Scholar 

  88. 88.

    Frajka-Williams, E., Rhines, P. B. & Eriksen, C. C. Horizontal stratification during deep convection in the Labrador Sea. J. Phys. Oceanogr. 44, 220–228 (2014).

    ADS  Google Scholar 

  89. 89.

    Pellichero, V., Sallée, J.-B., Schmidtko, S., Roquet, F. & Charrassin, J.-B. The ocean mixed layer under Southern Ocean sea-ice: seasonal cycle and forcing. J. Geophys. Res. Oceans 122, 1608–1633 (2017).

    ADS  Google Scholar 

  90. 90.

    Talley, L. D., Pickard, G. L., Emery, W. J. & Swift, J. H. Descriptive Physical Oceanography: An Introduction Ch. 7, 187–222 (Elsevier, 2011).

  91. 91.

    Gouretski, V. World Ocean Circulation Experiment – Argo Global Hydrographic Climatology. Ocean Sci. 14, 1127–1146 (2018).

    ADS  Google Scholar 

  92. 92.

    Fahrbach, E. et al. Warming of deep and abyssal water masses along the Greenwich meridian on decadal time scales: the Weddell gyre as a heat buffer. Deep Sea Res. Part II 58, 2509–2523 (2011).

    ADS  Google Scholar 

  93. 93.

    Ryan, S., Schröder, M., Huhn, O. & Timmermann, R. On the warm inflow at the eastern boundary of the Weddell Gyre. Deep Sea Res. Part I 107, 70–81 (2016).

    Google Scholar 

  94. 94.

    Smedsrud, L. H. Warming of the deep water in the Weddell Sea along the Greenwich meridian: 1977–2001. Deep Sea Res. Part I 52, 241–258 (2005).

    ADS  Google Scholar 

  95. 95.

    Fahrbach, E., Hoppema, M., Rohardt, G., Schröder, M. & Wisotzki, A. Causes of deep-water variation: comment on the paper by L.H. Smedsrud “Warming of the deep water in the Weddell Sea along the Greenwich meridian: 1977–2001”. Deep Sea Res. Part I 53, 574–577 (2006).

    Google Scholar 

  96. 96.

    Gordon, A. L. Weddell Deep Water variability. J. Mar. Res. 40, 199–217 (1982).

    Google Scholar 

  97. 97.

    Zanowski, H. & Hallberg, R. Weddell Polynya transport mechanisms in the abyssal ocean. J. Phys. Oceanogr. 47, 2907–2925 (2017).

    ADS  Google Scholar 

  98. 98.

    Marshall, G. J. Trends in the Southern Annular Mode from observations and reanalyses. J. Clim. 16, 4134–4143 (2003).

    ADS  Google Scholar 

  99. 99.

    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).

    ADS  Google Scholar 

  100. 100.

    Sumata, H. et al. An intercomparison of Arctic ice drift products to deduce uncertainty estimates. J. Geophys. Res. Oceans 119, 4887–4921 (2014).

    ADS  Google Scholar 

  101. 101.

    Martinson, D. G. & Wamser, C. Ice drift and momentum exchange in winter Antarctic pack ice. J. Geophys. Res. 95, 1741–1755 (1990).

    ADS  Google Scholar 

  102. 102.

    Wang, Z., Turner, J., Sun, B., Li, B. & Liu, C. Cyclone-induced rapid creation of extreme Antarctic sea ice conditions. Sci. Rep. 4, 5317 (2015).

    Google Scholar 

  103. 103.

    Kottmeier, C. & Sellmann, L. Atmospheric and oceanic forcing of Weddell Sea ice motion. J. Geophys. Res. Oceans 101, 20809–20824 (1996).

    ADS  Google Scholar 

  104. 104.

    Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B. & Young, G. S. Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere Coupled-Ocean Atmosphere Response Experiment. J. Geophys. Res. Oceans 101, 3747–3764 (1996).

    ADS  Google Scholar 

  105. 105.

    Renfrew, I. A., Moore, G. W. K., Guest, P. S. & Bumke, K. A comparison of surface layer and surface turbulent flux observations over the Labrador Sea with ECMWF analyses and NCEP reanalyses. J. Phys. Oceanogr. 32, 383–400 (2002).

    ADS  Google Scholar 

  106. 106.

    Holland, P. R. & Kwok, R. Wind-driven trends in Antarctic sea-ice drift. Nat. Geosci. 5, 872–875 (2012).

    ADS  CAS  Google Scholar 

  107. 107.

    Jullion, L., Jones, S. C., Naveira Garabato, A. C. & Meredith, M. P. Wind-controlled export of Antarctic Bottom Water from the Weddell Sea. Geophys. Res. Lett. 37, L09609 (2010).

    ADS  Google Scholar 

  108. 108.

    Meijers, A. J. S. et al. Wind-driven export of Weddell Sea slope water. J. Geophys. Res. Oceans 121, 7530–7546 (2016).

    ADS  Google Scholar 

  109. 109.

    Armitage, T. W. K., Kwok, R., Thompson, A. F. & Cunningham, G. Dynamic topography and sea level anomalies of the Southern Ocean: variability and teleconnections. J. Geophys. Res. Oceans 123, 613–630 (2018).

    ADS  Google Scholar 

  110. 110.

    Turner, J. et al. The SCAR READER project: toward a high-quality database of mean Antarctic meteorological observations. J. Clim. 17, 2890–2898 (2004).

    ADS  Google Scholar 

  111. 111.

    Smith, A., Lott, N. & Vose, R. The Integrated Surface Database: recent developments and partnerships. Bull. Am. Meteorol. Soc. 92, 704–708 (2011).

    ADS  Google Scholar 

  112. 112.

    Bracegirdle, T. J. Climatology and recent increase of westerly winds over the Amundsen Sea derived from six reanalyses. Int. J. Climatol. 33, 843–851 (2013).

    Google Scholar 

  113. 113.

    Patoux, J., Yuan, X. & Li, C. Satellite-based midlatitude cyclone statistics over the Southern Ocean: 1. Scatterometer-derived pressure fields and storm tracking. J. Geophys. Res. 114, D04105 (2009).

    ADS  Google Scholar 

  114. 114.

    Amante, C. & Eakins, B. W. ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. NOAA Technical Memorandum NESDIS NGDC-24 (National Geophysical Data Center, 2009) https://doi.org/10.7289/V5C8276M.

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Acknowledgements

We thank A. Wong, R. Drucker, J. Plant, T. Maurer and K. Johnson for assistance with float data calibration, and all others involved in float and sensor design, construction, calibration and deployment for their contributions. Data were collected and made freely available by the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project, which is funded by the US National Science Foundation, Division of Polar Programs (NSF PLR-1425989), supplemented by NASA, and by the International Argo Program and the NOAA programmes that contribute to it. The Argo Program is part of the Global Ocean Observing System. E.C.C. acknowledges funding from the University of Washington (UW) Program on Climate Change, ARCS Foundation, and US Department of Defense through the National Defense Science & Engineering Graduate (NDSEG) Fellowship Program. E.A.W., S.C.R., M.R.M. and L.D.T. acknowledge funding from NSF PLR-1425989, and S.C.R. from NOAA grant NA15OAR4320063. G.W.K.M. acknowledges the support of the Canada Fulbright Foundation, UW Jackson School of International Studies, and the Natural Sciences and Engineering Research Council of Canada. C.E.B. was supported by the Scripps Undergraduate Research Fellowship (SURF) programme.

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E.C.C., E.A.W. and S.C.R. conceived the study and E.C.C. wrote the initial manuscript. E.C.C. and E.A.W. analysed the hydrographic data and together with G.W.K.M. analysed the sea ice and reanalysis data. S.C.R. led the float design and construction and together with L.D.T. coordinated SOCCOM float deployments. All authors interpreted results and provided input to the final manuscript.

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Correspondence to Ethan C. Campbell.

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Extended data figures and tables

Extended Data Fig. 1 Locations of observations used to construct hydrographic climatologies for the Maud Rise and eastern Weddell regions.

Observations from 1970 to 2001 are shown together (top left); observations from 2002 to 2018 are represented by one panel per year. Included are float profiles from the Argo GDAC (filled circles) as well as shipboard (open squares) and instrumented seal (open triangles) casts from the World Ocean Database (see Methods section ‘Hydrographic data’). Colours indicate seasons. Bathymetric contours (intervals of 750 m) highlight Maud Rise and the Antarctic continental shelf. Concentric circles represent radii of 250 km and 500 km from Maud Rise, encompassing the Maud Rise and eastern Weddell regions, respectively (see Methods section ‘Regions’).

Extended Data Fig. 2 Sea ice concentration during the 2016 polynya.

Daily SIC from AMSR2-ASI around Maud Rise from 24 July to 17 August 2016, encompassing the main polynya event, followed by selected SIC fields from AMSR2-ASI during the late-winter 2016 polynya south of Maud Rise (bottom row; note different map area). Estimated locations of SOCCOM profiling floats 5904471 and 5904468 (see Methods section ‘Hydrographic data’) are marked in blue; a circle marker and profile number indicate that a hydrographic profile was obtained on that date. Bathymetry shallower than 3,500 m is contoured at intervals of 500 m to highlight Maud Rise (centre of July–August images) as well as Astrid Ridge (bottom right of October–November images), an extension of the Antarctic continental shelf.

Extended Data Fig. 3 Evolution of sea ice concentration, air temperature and upper ocean properties at Maud Rise in 2016 and 2017.

Marked at the top are intense winter storm events near Maud Rise, as in Fig. 2 (also see Extended Data Fig. 4 and Methods section ‘Storm identification’). a, Average daily SIC within the Maud Rise region (63°–67° S, 0°–10° E) from NSIDC Merged (solid black line) and AMSR2-ASI (dashed black line) in 2016 and 2017, as in Fig. 2a. SIC climatology from NSIDC Merged (1978–2019) is shown as median (grey line) and 25–75% interquartile range (IQR; grey shading). Note the stretched y axis. Polynya extent is quantified (blue lines) during the 2016 and 2017 events (vertical blue shading). b, Six-hourly 2-m air temperature around Maud Rise (within 63°–67° S, 0°–10° E) from ERA-I reanalysis (black line). Climatology for 1979–2018 is shown as mean (grey line) and IQR (grey shading). c, Composite of average MLD in 2016 and 2017 measured by floats 5903616, 5904468 and 5904471 (black line; see Methods sections ‘Derived oceanographic quantities’ and ‘Composites of float time series’). MLD climatology for the Maud Rise region (R < 250 km from 65° S, 3° E) is shown as median (grey line) and IQR (grey shading); climatology for the eastern Weddell region away from Maud Rise (250 < R < 500 km) is presented for comparison (light brown dashed and dotted lines for median and IQR, respectively; see Methods section ‘Hydrographic climatologies’). d, Composite of average mixed-layer potential temperature (MLT) and MLT climatology presented as in c. e, Composite of the lowest observed upper-250-m freshwater anomaly (or ‘salt deficit’; see Methods sections ‘Derived oceanographic quantities’ and ‘Composites of float time series’) and freshwater anomaly climatology for the Maud Rise region presented as in c. Note the reversed y axis. Key changes quantified, from left to right, are 2016 freeze, climatological melt, 2016 melt, anomaly from climatology in January 2017, 2017 freeze, and change between 2017 freeze and 2017 polynya appearance.

Extended Data Fig. 4 Correspondence of sea ice loss episodes and major storms near Maud Rise.

a, b, Time series are shown for 2016 (a) and 2017 (b). Average daily SIC within the Maud Rise region (63°–67° S, 0°–10° E) from NSIDC Merged (solid black line) and AMSR2-ASI (dashed black line) is presented at the top for each year, as in Fig. 2a. SIC climatology from NSIDC Merged (1978–2019) is shown as median (grey line) and 25–75% interquartile range (grey shading). Note the stretched y axis. Daily changes in SIC are presented in the centre for each year, with negative changes in NSIDC Merged highlighted (dark yellow shading); both NSIDC Merged and AMSR2-ASI time series are smoothed using a 3-day right-edge running-mean filter. At the bottom for each year are the minimum daily sea-level pressure and maximum daily 10-m wind speed near Maud Rise (within 63–67° S, 0–10° E) from ERA-I reanalysis. Mean climatological values of these minimum/maximum metrics are shown (grey lines) to highlight the lack of a pronounced seasonal cycle. The most intense winter polar lows, as shown in Figs. 2, 3, Extended Data Fig. 3, are identified here using pressure and wind speed thresholds (dark yellow shading from dashed lines), and aggregated ‘storm days’ are numbered at the top and marked with vertical yellow bars (see Methods section ‘Storm identification’).

Extended Data Fig. 5 Winds and wind-induced sea ice divergence during the 2016 polynya.

50% SIC contours (black) from AMSR2-ASI show the daily polynya evolution from 22 July to 17 August 2016. Bathymetry shallower than 3,500 m is contoured at intervals of 500 m (light grey) to highlight Maud Rise (centre). Daily mean 10-m wind vectors from ERA-I reanalysis, subsampled as every fifth u-wind and every second v-wind vector, are plotted with a 20 m s−1 key as reference. Estimated daily mean wind-induced sea ice divergence (see Methods section ‘Atmospheric reanalysis’) is shaded such that red represents divergence and blue represents convergence.

Extended Data Fig. 6 Full set of profiling float hydrographic observations from Maud Rise from 2011–2018.

ae, Complete depth sections of potential temperature (a), salinity (b), dissolved oxygen (c), buoyancy frequency squared (N2) (d) and convection resistance (see Methods section ‘Derived oceanographic quantities’) (e) from profiling floats 5903616 (left), 5904468 (centre) and 5904471 (right), as shown in Fig. 4. Individual profiles are marked at the top (black ticks). Mixed-layer depth is indicated in white. Vertical lines in each panel mark the start and end dates of the 2016 and 2017 polynyas. Along-trajectory SIC, primarily from AMSR2-ASI, is shaded at the top in black (see Methods section ‘Sea ice concentration data’).

Extended Data Fig. 7 Heat loss during the 2016 polynya estimated from hydrographic observations.

Heat flux estimates (n = 31; diamonds at the bottom correspond to histogram above) computed using potential temperature profiles from floats 5904468 and 5904471 following the opening of the 2016 polynya (see Methods section ‘Polynya heat flux estimates’). The dashed red line marks the average open-water ocean-atmosphere turbulent heat flux within the 2016 opening, estimated using a bulk flux algorithm as 252 W m−2 (see Methods section ‘Atmospheric reanalysis’).

Extended Data Fig. 8 Sea ice concentration during the 2017 polynya.

SIC from AMSR2-ASI around Maud Rise is shown every other day from 30 August to 2 December 2017. Estimated locations of SOCCOM profiling floats 5904471 and 5904468 are marked in blue; locations of profiling floats following an ice-free profile with a known position fix are marked in pink (see Methods section ‘Hydrographic data’). A circle marker and profile number indicate that a hydrographic profile was obtained on that date. Bathymetry shallower than 3,500 m is contoured at intervals of 500 m to highlight Maud Rise (centre) as well as Astrid Ridge (bottom right), an extension of the Antarctic continental shelf.

Extended Data Fig. 9 Additional relationships between past polynyas near Maud Rise, climate forcing, and sub-pycnocline temperatures.

a, Annual maximum polynya extent (bars) and number of polynya days (red diamonds; see Methods section ‘Polynya identification’), as in Fig. 5a. Maximum polynya extent is calculated for three SIC thresholds representing increasingly strict polynya definitions: 60%, 50% and 40%. Polynya days are quantified using the 60% threshold. Stars indicate years with incomplete or absent SIC records. Years with polynya activity at the 50% threshold are shaded vertically in red in b, c, and likewise in d, e, except vertical shading delimits the actual major polynya events. b, Mean sea-level pressure records from Queen Maud Land meteorological stations, 1972–2018 (see legend and Methods section ‘Meteorological station records’). c, Eastern Weddell average precipitation from ERA-I reanalysis between 1979 and 2018, shaded below its mean value to indicate years with polynya-favourable conditions (that is, lower atmosphere–ocean freshwater flux), consistent with Fig. 5. Time series in b and c are filtered using a two-year centred running mean to highlight longer-term fluctuations. d, Biannually binned eastern Weddell region (within 500 km of Maud Rise) shipboard, float and instrumented seal temperature observations at 258 m from 2002 to 2017, expressed as anomalies from WAGHC gridded hydrographic climatology (see Methods section ‘Sub-pycnocline temperature records’). Error bars denote median and 25–75% IQR. Violin plots summarize the data distribution for n > 10, and individual anomalies are shown for 5 ≤ n ≤ 10. Periods with n < 5 are not plotted. e, As in d, but showing average temperature anomalies from WAGHC climatology between 250–1,000 m (see Methods section ‘Sub-pycnocline temperature records’). See Extended Data Table 1 for trends and significance for ce.

Extended Data Table 1 Correlations and trends for climate indices and sub-pycnocline temperature records

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Campbell, E.C., Wilson, E.A., Moore, G.W.K. et al. Antarctic offshore polynyas linked to Southern Hemisphere climate anomalies. Nature 570, 319–325 (2019). https://doi.org/10.1038/s41586-019-1294-0

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