• Banerjee, A., A. H. Butler, L. M. Polvani, A. Robock, I. R. Simpson, and L. Sun, 2021: Robust winter warming over Eurasia under stratospheric sulfate geoengineering—The role of stratospheric dynamics. Atmos. Chem. Phys., 21, 69856997, https://doi.org/10.5194/acp-21-6985-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baxter, I., and Coauthors, 2019: How tropical Pacific surface cooling contributed to accelerated sea ice melt from 2007 to 2012 as ice is thinned by anthropogenic forcing. J. Climate, 32, 85838602, https://doi.org/10.1175/JCLI-D-18-0783.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blanchard-Wrigglesworth, E., K. C. Armour, C. M. Bitz, and E. DeWeaver, 2011: Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations. J. Climate, 24, 231250, https://doi.org/10.1175/2010JCLI3775.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blanchard-Wrigglesworth, E., L. A. Roach, A. Donohoe, and Q. Ding, 2021: Impact of winds and Southern Ocean SSTs on Antarctic sea ice trends and variability. J. Climate, 34, 949965, https://doi.org/10.1175/JCLI-D-20-0386.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boeke, R. C., and P. C. Taylor, 2016: Evaluation of the Arctic surface radiation budget in CMIP5 models. J. Geophys. Res. Atmos., 121, 85258548, https://doi.org/10.1002/2016JD025099.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonan, D. B., and E. Blanchard‐Wrigglesworth, 2020: Nonstationary teleconnection between the Pacific Ocean and Arctic sea ice. Geophys. Res. Lett., 47, e2019GL085666, https://doi.org/10.1029/2019GL085666.

    • Crossref
    • Export Citation
  • Bonan, D. B., T. Schneider, I. Eisenman, and R. C. J. Wills, 2021a: Constraining the date of a seasonally ice-free Arctic using a simple model. Geophys. Res. Lett., 48, e2021GL094309, https://doi.org/10.1029/2021GL094309.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonan, D. B., F. Lehner, and M. M. Holland, 2021b: Partitioning uncertainty in projections of Arctic sea ice. Environ. Res. Lett., 16, 044002, https://doi.org/10.1088/1748-9326/abe0ec.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brennan, M. K., and G. J. Hakim, 2022: Reconstructing Arctic Sea ice over the common era using data assimilation. J. Climate, 35, 12311247, https://doi.org/10.1175/JCLI-D-21-0099.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bushuk, M., M. Winton, D. B. Bonan, E. Blanchard‐Wrigglesworth, and T. L. Delworth, 2020: A mechanism for the Arctic sea ice spring predictability barrier. Geophys. Res. Lett., 47, e2020GL088335, https://doi.org/10.1029/2020GL088335.

    • Crossref
    • Export Citation
  • Cavalieri, D. J., C. L. Parkinson, P. Gloersen, and H. J. Zwally, 1996: Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS passive microwave data, version 1 (NSIDC-0051). NASA/National Snow and Ice Data Center Distributed Active Archive Center, accessed 25 November 2020, https://doi.org/10.5067/8GQ8LZQVL0VL.

    • Crossref
    • Export Citation
  • Cesana, G., J. E. Kay, H. Chepfer, J. M. English, and G. De Boer, 2012: Ubiquitous low-level liquid-containing Arctic clouds: New observations and climate model constraints from CALIPSO-GOCCP. Geophys. Res. Lett., 39, L20804, https://doi.org/10.1029/2012GL053385.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Christensen, M. W., A. Behrangi, T. S. L’ecuyer, N. B. Wood, M. D. Lebsock, and G. L. Stephens, 2016: Arctic observation and reanalysis integrated system: A new data product for validation and climate study. Bull. Amer. Meteor. Soc., 97, 907916, https://doi.org/10.1175/BAMS-D-14-00273.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Curry, J. A., J. L. Schramm, and E. E. Ebert, 1995: Sea ice–albedo climate feedback mechanism. J. Climate, 8, 240247, https://doi.org/10.1175/1520-0442(1995)008<0240:SIACFM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527546, https://doi.org/10.1007/s00382-010-0977-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., and Coauthors, 2020: Insights from Earth system model initial-condition large ensembles and future prospects. Nat. Climate Change, 10, 277286, https://doi.org/10.1038/s41558-020-0731-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diebold, F. X., and G. D. Rudebusch, 2021: Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections. J. Econometrics, https://doi.org/10.1016/j.jeconom.2020.12.007, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Q., and Coauthors, 2017: Influence of high-latitude atmospheric circulation changes on summertime Arctic sea ice. Nat. Climate Change, 7, 289295, https://doi.org/10.1038/nclimate3241.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Q., and Coauthors, 2019: Fingerprints of internal drivers of Arctic sea ice loss in observations and model simulations. Nat. Geosci., 12, 2833, https://doi.org/10.1038/s41561-018-0256-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Q., J. M. Wallace, D. S. Battisti, E. J. Steig, A. J. Gallant, H.-J. Kim, and L. Geng, 2014: Tropical forcing of the recent rapid Arctic warming in northeastern Canada and Greenland. Nature, 509, 209212, https://doi.org/10.1038/nature13260.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • England, M., A. Jahn, and L. Polvani, 2019: Nonuniform contribution of internal variability to recent Arctic sea ice loss. J. Climate, 32, 40394053, https://doi.org/10.1175/JCLI-D-18-0864.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fetterer, F., and K. Knowles, 2004: Sea ice index monitors polar ice extent. Eos, Trans. Amer. Geophys. Union, 85, 163–164, https://doi.org/10.1029/2004EO160007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Franke, J., S. Brönnimann, J. Bhend, and Y. Brugnara, 2017: A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations. Sci. Data, 4, 170076, https://doi.org/10.1038/sdata.2017.76.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graff, L. S., and Coauthors, 2019: Arctic amplification under global warming of 1.5° and 2°C in NorESM1-Happi. Earth Syst. Dyn., 10, 569598, https://doi.org/10.5194/esd-10-569-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graham, R. M., and Coauthors, 2019: Evaluation of six atmospheric reanalyses over Arctic sea ice from winter to early summer. J. Climate, 32, 41214143, https://doi.org/10.1175/JCLI-D-18-0643.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holland, M. M., and J. Stroeve, 2011: Changing seasonal sea ice predictor relationships in a changing Arctic climate. Geophys. Res. Lett., 38, L18501, https://doi.org/10.1029/2011GL049303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holland, M. M., L. Landrum, D. Bailey, and S. Vavrus , 2019: Changing seasonal predictability of Arctic summer sea ice area in a warming climate. J. Climate, 32, 49634979, https://doi.org/10.1175/JCLI-D-19-0034.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, Y., X. Dong, B. Xi, E. K. Dolinar, R. E. Stanfield, and S. Qiu, 2017: Quantifying the uncertainties of reanalyzed Arctic cloud and radiation properties using satellite surface observations. J. Climate, 30, 80078029, https://doi.org/10.1175/JCLI-D-16-0722.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, Y., Q. Ding, X. Dong, B. Xi and I. Baxter, 2021: Summertime low clouds mediate the impact of the large-scale circulation on Arctic sea ice. Commun. Earth Environ., 2, 38, https://doi.org/10.1038/s43247-021-00114-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., and Coauthors, 2013: The Community Earth System Model: A framework for collaborative research. Bull. Amer. Meteor. Soc., 94, 13391360, https://doi.org/10.1175/BAMS-D-12-00121.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jahn, A., 2018: Reduced probability of ice-free summers for 1.5°C compared to 2°C warming. Nat. Climate Change, 8, 409413, https://doi.org/10.1038/s41558-018-0127-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jahn, A., J. Kay, M. Holland, and D. Hall, 2016: How predictable is the timing of a summer ice-free Arctic? Geophys. Res. Lett., 43, 91139120, https://doi.org/10.1002/2016GL070067.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kay, J. E., T. L'Ecuyer, A. Gettelman, G. Stephens, and C. O’Dell, 2008: The contribution of cloud and radiation anomalies to the 2007 Arctic sea ice extent minimum. Geophys. Res. Lett., 35, L08503, https://doi.org/10.1029/2008GL033451.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kay, J. E., M. M. Holland, and A. Jahn, 2011: Inter‐annual to multi‐decadal Arctic sea ice extent trends in a warming world. Geophys. Res. Lett., 38, L15708, https://doi.org/10.1029/2011GL048008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kay, J. E., and Coauthors, 2015: The Community Earth System Model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull. Amer. Meteor. Soc., 96, 13331349, https://doi.org/10.1175/BAMS-D-13-00255.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kay, J. E., T. L’Ecuyer, H. Chepfer, N. Loeb, A. Morrison, and G. Cesana, 2016: Recent advances in Arctic cloud and climate research. Curr. Climate Change Rep., 2, 159169, https://doi.org/10.1007/s40641-016-0051-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keen, A., and Coauthors, 2021: An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models. Cryosphere, 15, 951982, https://doi.org/10.5194/tc-15-951-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Labe, Z., G. Magnusdottir, and H. Stern, 2018: Variability of Arctic sea ice thickness using PIOMAS and the CESM large ensemble. J. Climate, 31, 32333247, https://doi.org/10.1175/JCLI-D-17-0436.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Labe, Z., Y. Peings, and G. Magnusdottir, 2020: Warm Arctic, cold Siberia pattern: Role of full Arctic amplification versus sea ice loss alone. Geophys. Res. Lett., 47, e2020GL088583, https://doi.org/10.1029/2020GL088583.

    • Crossref
    • Export Citation
  • Lehner, F., F. Joos, C. C. Raible, J. Mignot, A. Born, K. M. Keller, and T. F. Stocker, 2015: Climate and carbon cycle dynamics in a CESM simulation from 850 to 2100 CE. Earth Syst. Dyn., 6, 411434, https://doi.org/10.5194/esd-6-411-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Z., Q. Ding, M. Steele, and A. Schweiger, 2022: Recent upper Arctic Ocean warming expedited by summertime atmospheric processes. Nat. Commun., 13, 362, https://doi.org/10.1038/s41467-022-28047-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lindsay, R., and J. Zhang, 2005: The thinning of Arctic sea ice, 1988–2003: Have we passed a tipping point? J. Climate, 18, 48794894, https://doi.org/10.1175/JCLI3587.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lindsay, R., M. Wensnahan, A. Schweiger, and J. Zhang, 2014: Evaluation of seven different atmospheric reanalysis products in the Arctic. J. Climate, 27, 25882606, https://doi.org/10.1175/JCLI-D-13-00014.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, J., M. Song, R. Horton, and Y. Hu, 2013: Reducing spread in climate model projections of a September ice-free Arctic. Proc. Natl. Acad. Sci. USA., 110, 12 57112 576, https://doi.org/10.1073/pnas.1219716110.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luo, R., Q. Ding, Z. Wu, I. Baxter, M. Bushuk, Y. Huang and X. Dong, 2021: Summertime atmosphere–sea ice coupling in the Arctic simulated by CMIP5/6 models: Importance of large-scale circulation. Climate Dyn., 56, 14671485, https://doi.org/10.1007/s00382-020-05543-5.

    • Search Google Scholar
    • Export Citation
  • McIlhattan, E. A., J. E. Kay, and T. S. L’Ecuyer, 2020: Arctic clouds and precipitation in the Community Earth System Model version 2. J. Geophys. Res. Atmos., 125, e2020JD032521, https://doi.org/10.1029/2020JD032521.

    • Crossref
    • Export Citation
  • Meehl, G. A., C. T. Chung, J. M. Arblaster, M. M. Holland, and C. M. Bitz, 2018: Tropical decadal variability and the rate of Arctic sea ice decrease. Geophys. Res. Lett., 45, 11 326–11 333, https://doi.org/10.1029/2018GL079989.

    • Crossref
    • Export Citation
  • Middlemas, E. A., J. E. Kay, B. M. Medeiros, and E. A. Maroon, 2020: Quantifying the influence of cloud radiative feedbacks on Arctic surface warming using cloud locking in an Earth system model. Geophys. Res. Lett., 47, e2020GL089207, https://doi.org/10.1029/2020GL089207.

    • Crossref
    • Export Citation
  • Mori, M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades. Nat. Geosci., 7, 869873, https://doi.org/10.1038/ngeo2277.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, A., J. E. Kay, W. Frey, H. Chepfer, and R. Guzman, 2019: Cloud response to Arctic sea ice loss and implications for future feedback in the CESM1 climate model. J. Geophys. Res. Atmos., 124, 10031020, https://doi.org/10.1029/2018JD029142.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Msadek, R., G. A. Vecchi, M. Winton, and R. Gudgel, 2014: Importance of initial conditions in seasonal predictions of Arctic sea ice extent. Geophys. Res. Lett., 41, 52085215, https://doi.org/10.1002/2014GL060799.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakamura, T., K. Yamazaki, K. Iwamoto, M. Honda, Y. Miyoshi, Y. Ogawa, and J. Ukita, 2015: A negative phase shift of the winter AO/NAO due to the recent Arctic Sea‐ice reduction in late autumn. J. Geophys. Res. Atmos., 120, 32093227, https://doi.org/10.1002/2014JD022848.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Notz, D., and J. Marotzke, 2012: Observations reveal external driver for Arctic Sea‐ice retreat. Geophys. Res. Lett., 39, L08502, https://doi.org/10.1029/2012GL051094.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Notz, D., and SIMIP Community, 2020: Arctic sea ice in CMIP6. Geophys. Res. Lett., 47, e2019GL086749, https://doi.org/10.1029/2019GL086749.

    • Crossref
    • Export Citation
  • Ogi, M., Y. Tachibana, and K. Yamazaki, 2003: Impact of the wintertime North Atlantic Oscillation (NAO) on the summertime atmospheric circulation. Geophys. Res. Lett., 30, 1704, https://doi.org/10.1029/2003GL017280.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Olonscheck, D., T. Mauritsen, and D. Notz, 2019: Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations. Nat. Geosci., 12, 430434, https://doi.org/10.1038/s41561-019-0363-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Otto-Bliesner, B. L., and Coauthors, 2016: Climate variability and change since 850 CE: An ensemble approach with the Community Earth System Model. Bull. Amer. Meteor. Soc., 97, 735754, https://doi.org/10.1175/BAMS-D-14-00233.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Overland, J. E., and M. Wang, 2013: When will the summer Arctic be nearly sea ice free? Geophys. Res. Lett., 40, 20972101, https://doi.org/10.1002/grl.50316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Papritz, L., 2020: Arctic lower-tropospheric warm and cold extremes: Horizontal and vertical transport, diabatic processes, and linkage to synoptic circulation features. J. Climate, 33, 9931016, https://doi.org/10.1175/JCLI-D-19-0638.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perlwitz, J., M. Hoerling, and R. Dole, 2015: Arctic tropospheric warming: Causes and linkages to lower latitudes. J. Climate, 28, 21542167, https://doi.org/10.1175/JCLI-D-14-00095.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polyakov, I. V., and Coauthors, 2020: Weakening of cold halocline layer exposes sea ice to oceanic heat in the eastern Arctic Ocean. J. Climate, 33, 81078123, https://doi.org/10.1175/JCLI-D-19-0976.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rampal, P., J. Weiss, C. Dubois, and J.-M. Campin, 2011: IPCC climate models do not capture Arctic sea ice drift acceleration: Consequences in terms of projected sea ice thinning and decline. J. Geophys. Res., 116, C00D07, https://doi.org/10.1029/2011JC007110.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roach, L. A., and E. Blanchard-Wrigglesworth, 2022: Observed winds crucial for September Arctic Sea ice loss. Geophys. Res. Lett., 49, e2022GL097884, https://doi.org/10.1029/2022GL097884.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenblum, E., and I. Eisenman, 2016: Faster Arctic sea ice retreat in CMIP5 than in CMIP3 due to volcanoes. J. Climate, 29, 91799188, https://doi.org/10.1175/JCLI-D-16-0391.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Screen, J. A., and C. Deser, 2019: Pacific Ocean variability influences the time of emergence of a seasonally ice‐free Arctic Ocean. Geophys. Res. Lett., 46, 22222231, https://doi.org/10.1029/2018GL081393.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shepherd, T. G., 2014: Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci., 7, 703708, https://doi.org/10.1038/ngeo2253.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sigmond, M., J. C. Fyfe, and N. C. Swart, 2018: Ice-free Arctic projections under the Paris Agreement. Nat. Climate Change, 8, 404408, https://doi.org/10.1038/s41558-018-0124-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simmonds, I., and I. Rudeva, 2012: The great Arctic cyclone of August 2012. Geophys. Res. Lett., 39, L23709, https://doi.org/10.1029/2012GL054259.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smedsrud, L. H., M. H. Halvorsen, J. C. Stroeve, R. Zhang, and K. Kloster, 2017: Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years. Cryosphere, 11, 6579, https://doi.org/10.5194/tc-11-65-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smirnova, J., and P. Golubkin, 2017: Comparing polar lows in atmospheric reanalyses: Arctic system reanalysis versus ERA-Interim. Mon. Wea. Rev., 145, 23752383, https://doi.org/10.1175/MWR-D-16-0333.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, A., and A. Jahn, 2019: Definition differences and internal variability affect the simulated Arctic sea ice melt season. Cryosphere, 13, 120, https://doi.org/10.5194/tc-13-1-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sotiropoulou, G., J. Sedlar, R. Forbes, and M. Tjernström, 2016: Summer Arctic clouds in the ECMWF forecast model: An evaluation of cloud parametrization schemes. Quart. J. Roy. Meteor. Soc., 142, 387400, https://doi.org/10.1002/qj.2658.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spreen, G., L. de Steur, D. Divine, S. Gerland, E. Hansen, and R. Kwok, 2020: Arctic sea ice volume export through Fram Strait from 1992 to 2014. J. Geophys. Res. Oceans, 125, e2019JC016039, https://doi.org/10.1029/2019JC016039.

    • Crossref
    • Export Citation
  • Steiger, N. J., J. E. Smerdon, E. R. Cook, and B. I. Cook, 2018: A reconstruction of global hydroclimate and dynamical variables over the Common Era. Sci. Data, 5, 180086, https://doi.org/10.1038/sdata.2018.86.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., M. M. Holland, W. Meier, T. Scambos, and M. Serreze, 2007: Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett., 34, L09501, https://doi.org/10.1029/2007GL029703.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., V. Kattsov, A. Barrett, M. Serreze, T. Pavlova, M. Holland, and W. N. Meier, 2012: Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012GL052676.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., T. Markus, L. Boisvert, J. Miller, and A. Barrett, 2014: Changes in Arctic melt season and implication for sea ice loss. Geophys. Res. Lett., 41, 12161225, https://doi.org/10.1002/2013GL058951.

    • Search Google Scholar
    • Export Citation
  • Swart, N. C., J. C. Fyfe, E. Hawkins, J. E. Kay, and A. Jahn, 2015: Influence of internal variability on Arctic sea-ice trends. Nat. Climate Change, 5, 8689, https://doi.org/10.1038/nclimate2483.

    • Search Google Scholar
    • Export Citation
  • Tan, I., and T. Storelvmo, 2019: Evidence of strong contributions from mixed‐phase clouds to Arctic climate change. Geophys. Res. Lett., 46, 28942902, https://doi.org/10.1029/2018GL081871.

    • Search Google Scholar
    • Export Citation
  • Tardif, R., and Coauthors, 2019: Last millennium reanalysis with an expanded proxy database and seasonal proxy modeling. Climate Past, 15, 12511273, https://doi.org/10.5194/cp-15-1251-2019.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., M. Crucifix, P. Braconnot, C. D. Hewitt, C. Doutriaux, A. J. Broccoli J. F. B. Mitchell, and M. J. Webb, 2007: Estimating shortwave radiative forcing and response in climate models. J. Climate, 20, 25302543, https://doi.org/10.1175/JCLI4143.1.

    • Search Google Scholar
    • Export Citation
  • Thorndike, A. S., and R. Colony, 1982: Sea ice motion in response to geostrophic winds. J. Geophys. Res., 87, 58455852, https://doi.org/10.1029/JC087iC08p05845.

    • Search Google Scholar
    • Export Citation
  • Tietsche, S., D. Notz, J. H. Jungclaus, and J. Marotzke, 2011: Recovery mechanisms of Arctic summer sea ice. Geophys. Res. Lett., 38, L02707, https://doi.org/10.1029/2010GL045698.

    • Search Google Scholar
    • Export Citation
  • Topál, D., Q. Ding, J. Mitchell, I. Baxter, M. Herein, T. Haszpra, R., Luo, and Q. Li, 2020: An internal atmospheric process determining summertime Arctic sea ice melting in the next three decades: Lessons learned from five large ensembles and multiple CMIP5 climate simulations. J. Climate, 33, 74317454, https://doi.org/10.1175/JCLI-D-19-0803.1.

    • Search Google Scholar
    • Export Citation
  • Wang, B., X. Zhou, Q. Ding, and J. Liu, 2021: Increasing confidence in projecting the Arctic ice-free year with emergent constraints. Environ. Res. Lett., 16, 094016, https://doi.org/10.1088/1748-9326/ac0b17.

    • Search Google Scholar
    • Export Citation
  • Wang, C., R. M. Graham, K. Wang, S. Gerland, and M. A. Granskog, 2019: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: Effects on sea ice thermodynamics and evolution. Cryosphere, 13, 16611679, https://doi.org/10.5194/tc-13-1661-2019.

    • Search Google Scholar
    • Export Citation
  • Wang, W., M. Chen, and A. Kumar, 2013: Seasonal prediction of Arctic sea ice extent from a coupled dynamical forecast system. Mon. Wea. Rev., 141, 13751394, https://doi.org/10.1175/MWR-D-12-00057.1.

    • Search Google Scholar
    • Export Citation
  • Wernli, H., and L. Papritz, 2018: Role of polar anticyclones and mid-latitude cyclones for Arctic summertime sea-ice melting. Nat. Geosci., 11, 108113, https://doi.org/10.1038/s41561-017-0041-0.

    • Search Google Scholar
    • Export Citation
  • Wettstein, J. J., and C. Deser, 2014: Internal variability in projections of twenty-first-century Arctic sea ice loss: Role of the large-scale atmospheric circulation. J. Climate, 27, 527550, https://doi.org/10.1175/JCLI-D-12-00839.1.

    • Search Google Scholar
    • Export Citation
  • Winton, M., 2011: Do climate models underestimate the sensitivity of Northern Hemisphere sea ice cover? J. Climate, 24, 39243934, https://doi.org/10.1175/2011JCLI4146.1.

    • Search Google Scholar
    • Export Citation
  • Yamagami, A., M. Matsueda, and H. L. Tanaka, 2017: Extreme Arctic cyclone in August 2016. Atmos. Sci. Lett., 18, 307314, https://doi.org/10.1002/asl.757.

    • Search Google Scholar
    • Export Citation
  • Yang, W., G. A. Vecchi, S. Fueglistaler, L. W. Horowitz, D. J. Luet, Á. G. Muñoz, D. Paynter, and S. Underwood, 2019: Climate impacts from large volcanic eruptions in a high‐resolution climate model: The importance of forcing structure. Geophys. Res. Lett., 46, 76907699, https://doi.org/10.1029/2019GL082367.

    • Search Google Scholar
    • Export Citation
  • Zhang, R., 2015: Mechanisms for low-frequency variability of summer Arctic sea ice extent. Proc. Natl. Acad. Sci. USA, 112, 45704575, https://doi.org/10.1073/pnas.1422296112.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 626 626 60
Full Text Views 371 371 16
PDF Downloads 414 414 16

An Optimal Atmospheric Circulation Mode in the Arctic Favoring Strong Summertime Sea Ice Melting and Ice–Albedo Feedback

Ian BaxteraDepartment of Geography, University of California, Santa Barbara, Santa Barbara, California
bEarth Research Institute, University of California, Santa Barbara, Santa Barbara, California

Search for other papers by Ian Baxter in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-1702-2471
and
Qinghua DingaDepartment of Geography, University of California, Santa Barbara, Santa Barbara, California
bEarth Research Institute, University of California, Santa Barbara, Santa Barbara, California

Search for other papers by Qinghua Ding in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The rapid decline of summer Arctic sea ice over the past few decades has been driven by a combination of increasing greenhouse gases and internal variability of the climate system. However, uncertainties remain regarding spatial and temporal characteristics of the optimal internal atmospheric mode that most favors summer sea ice melting on low-frequency time scales. To pinpoint this mode, we conduct a suite of simulations in which atmospheric circulation is constrained by nudging tropospheric Arctic (60°–90°N) winds within the Community Earth System Model, version 1 (CESM1), to those from reanalysis. Each reanalysis year is repeated for over 10 model years using fixed greenhouse gas concentrations and the same initial conditions. Composites show the strongest September sea ice losses are closely preceded by a common June–August (JJA) barotropic anticyclonic circulation in the Arctic favoring shortwave absorption at the surface. Successive years of strong wind-driven melting also enhance declines in Arctic sea ice through enhancement of the ice–albedo feedback, reaching a quasi-equilibrium response after repeated wind forcing for over 5–6 years, as the effectiveness of the wind-driven ice–albedo feedback becomes saturated. Strong melting favored by a similar wind pattern as observations is detected in a long preindustrial simulation and 400-yr paleoclimate reanalysis, suggesting that a summer barotropic anticyclonic wind pattern represents the optimal internal atmospheric mode maximizing sea ice melting in both the model and natural world over a range of time scales. Considering strong contributions of this mode to changes in Arctic climate, a better understanding of its origin and maintenance is vital to improving future projections of Arctic sea ice.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ian Baxter, itbaxter@ucsb.edu

Abstract

The rapid decline of summer Arctic sea ice over the past few decades has been driven by a combination of increasing greenhouse gases and internal variability of the climate system. However, uncertainties remain regarding spatial and temporal characteristics of the optimal internal atmospheric mode that most favors summer sea ice melting on low-frequency time scales. To pinpoint this mode, we conduct a suite of simulations in which atmospheric circulation is constrained by nudging tropospheric Arctic (60°–90°N) winds within the Community Earth System Model, version 1 (CESM1), to those from reanalysis. Each reanalysis year is repeated for over 10 model years using fixed greenhouse gas concentrations and the same initial conditions. Composites show the strongest September sea ice losses are closely preceded by a common June–August (JJA) barotropic anticyclonic circulation in the Arctic favoring shortwave absorption at the surface. Successive years of strong wind-driven melting also enhance declines in Arctic sea ice through enhancement of the ice–albedo feedback, reaching a quasi-equilibrium response after repeated wind forcing for over 5–6 years, as the effectiveness of the wind-driven ice–albedo feedback becomes saturated. Strong melting favored by a similar wind pattern as observations is detected in a long preindustrial simulation and 400-yr paleoclimate reanalysis, suggesting that a summer barotropic anticyclonic wind pattern represents the optimal internal atmospheric mode maximizing sea ice melting in both the model and natural world over a range of time scales. Considering strong contributions of this mode to changes in Arctic climate, a better understanding of its origin and maintenance is vital to improving future projections of Arctic sea ice.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ian Baxter, itbaxter@ucsb.edu

Supplementary Materials

    • Supplemental Materials (PDF 2.23 MB)
Save