Understanding the Role of Ocean Dynamics in Midlatitude Sea Surface Temperature Variability Using a Simple Stochastic Climate Model

Casey R. Patrizio aDepartment of Atmospheric Sciences, Colorado State University, Fort Collins, Colorado

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David W. J. Thompson aDepartment of Atmospheric Sciences, Colorado State University, Fort Collins, Colorado

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Abstract

In a recent paper, we argued that ocean dynamics increase the variability of midlatitude sea surface temperatures (SSTs) on monthly to interannual time scales, but act to damp lower-frequency SST variability over broad midlatitude regions. Here, we use two configurations of a simple stochastic climate model to provide new insights into this important aspect of climate variability. The simplest configuration includes the forcing and damping of SST variability by observed surface heat fluxes only, and the more complex configuration includes forcing and damping by ocean processes, which are estimated indirectly from monthly observations. It is found that the simple model driven only by the observed surface heat fluxes generally produces midlatitude SST power spectra that are too red compared to observations. Including ocean processes in the model reduces this discrepancy by whitening the midlatitude SST spectra. In particular, ocean processes generally increase the SST variance on <2-yr time scales and decrease it on >2-yr time scales. This happens because oceanic forcing increases the midlatitude SST variance across many time scales, but oceanic damping outweighs oceanic forcing on >2-yr time scales, particularly away from the western boundary currents. The whitening of midlatitude SST variability by ocean processes also operates in NCAR’s Community Earth System Model (CESM). That is, midlatitude SST spectra are generally redder when the same atmospheric model is coupled to a slab rather than dynamically active ocean model. Overall, the results suggest that forcing and damping by ocean processes play essential roles in driving midlatitude SST variability.

© 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: Casey Patrizio, casey.patrizio@colostate.edu

Abstract

In a recent paper, we argued that ocean dynamics increase the variability of midlatitude sea surface temperatures (SSTs) on monthly to interannual time scales, but act to damp lower-frequency SST variability over broad midlatitude regions. Here, we use two configurations of a simple stochastic climate model to provide new insights into this important aspect of climate variability. The simplest configuration includes the forcing and damping of SST variability by observed surface heat fluxes only, and the more complex configuration includes forcing and damping by ocean processes, which are estimated indirectly from monthly observations. It is found that the simple model driven only by the observed surface heat fluxes generally produces midlatitude SST power spectra that are too red compared to observations. Including ocean processes in the model reduces this discrepancy by whitening the midlatitude SST spectra. In particular, ocean processes generally increase the SST variance on <2-yr time scales and decrease it on >2-yr time scales. This happens because oceanic forcing increases the midlatitude SST variance across many time scales, but oceanic damping outweighs oceanic forcing on >2-yr time scales, particularly away from the western boundary currents. The whitening of midlatitude SST variability by ocean processes also operates in NCAR’s Community Earth System Model (CESM). That is, midlatitude SST spectra are generally redder when the same atmospheric model is coupled to a slab rather than dynamically active ocean model. Overall, the results suggest that forcing and damping by ocean processes play essential roles in driving midlatitude SST variability.

© 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: Casey Patrizio, casey.patrizio@colostate.edu
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  • Alexander, M. A., 2010: Extratropical air–sea interaction, sea surface temperature variability, and the Pacific decadal oscillation. Climate Dynamics: Why Does Climate Vary? Geophys. Monogr., Vol. 189, Amer. Geophys. Union, 123148, https://doi.org/10.1029/2008GM000794.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alexander, M. A., and C. Penland, 1996: Variability in a mixed layer ocean model driven by stochastic atmospheric forcing. J. Climate, 9, 24242442, https://doi.org/10.1175/1520-0442(1996)009<2424:VIAMLO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alexander, M. A., I. Bladé, M. Newman, J. R. Lanzante, N.-C. Lau, and J. D. Scott, 2002: The atmospheric bridge: The influence of ENSO teleconnections on air–sea interaction over the global oceans. J. Climate, 15, 22052231, https://doi.org/10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barsugli, J. J., and D. S. Battisti, 1998: The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. J. Atmos. Sci., 55, 477493, https://doi.org/10.1175/1520-0469(1998)055<0477:TBEOAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellomo, K., L. N. Murphy, M. A. Cane, A. C. Clement, and L. M. Polvani, 2018: Historical forcings as main drivers of the Atlantic multidecadal variability in the CESM large ensemble. Climate Dyn., 50, 36873698, https://doi.org/10.1007/s00382-017-3834-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellucci, A., and Coauthors, 2020: Air–sea interaction over the Gulf Stream in an ensemble of HighResMIP present climate simulations. Climate Dyn., 56, 20932111, https://doi.org/10.1007/s00382-020-05573-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bishop, S. P., R. J. Small, F. O. Bryan, and R. A. Tomas, 2017: Scale dependence of midlatitude air–sea interaction. J. Climate, 30, 82078221, https://doi.org/10.1175/JCLI-D-17-0159.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bitz, C. M., K. Shell, P. Gent, D. Bailey, G. Danabasoglu, K. Armour, M. Holland, and J. Kiehl, 2012: Climate sensitivity of the Community Climate System Model, version 4. J. Climate, 25, 30533070, https://doi.org/10.1175/JCLI-D-11-00290.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bjerknes, J., 1964: Atlantic air–sea interaction. Advances in Geophysics, Vol. 10, Elsevier, 182.

  • Bryden, H. L., and S. Imawaki, 2001: Ocean heat transport. Ocean Circulation and Climate: Observing and Modelling the Global Ocean, G. Siedler, J. Church, and J. Gould, Eds., International Geophysics Series, Vol. 77, Elsevier, 455474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buckley, M. W., and J. Marshall, 2016: Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review. Rev. Geophys., 54, 563, https://doi.org/10.1002/2015RG000493.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buckley, M. W., R. M. Ponte, G. Forget, and P. Heimbach, 2014: Low-frequency SST and upper-ocean heat content variability in the North Atlantic. J. Climate, 27, 49965018, https://doi.org/10.1175/JCLI-D-13-00316.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buckley, M. W., R. M. Ponte, G. Forget, and P. Heimbach, 2015: Determining the origins of advective heat transport convergence variability in the North Atlantic. J. Climate, 28, 39433956, https://doi.org/10.1175/JCLI-D-14-00579.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cane, M. A., A. C. Clement, L. N. Murphy, and K. Bellomo, 2017: Low-pass filtering, heat flux, and Atlantic multidecadal variability. J. Climate, 30, 75297553, https://doi.org/10.1175/JCLI-D-16-0810.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., 1992a: Latent and sensible heat flux anomalies over the northern oceans: Driving the sea surface temperature. J. Phys. Oceanogr., 22, 859881, https://doi.org/10.1175/1520-0485(1992)022<0859:LASHFA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., 1992b: Latent and sensible heat flux anomalies over the northern oceans: The connection to monthly atmospheric circulation. J. Climate, 5, 354369, https://doi.org/10.1175/1520-0442(1992)005<0354:LASHFA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clement, A., K. Bellomo, L. N. Murphy, M. A. Cane, T. Mauritsen, G. Rädel, and B. Stevens, 2015: The Atlantic Multidecadal Oscillation without a role for ocean circulation. Science, 350, 320324, https://doi.org/10.1126/science.aab3980.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Czaja, A., and J. Marshall, 2000: On the interpretation of AGCMs response to prescribed time-varying SST anomalies. Geophys. Res. Lett., 27, 19271930, https://doi.org/10.1029/1999GL011322.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Coëtlogon, G., and C. Frankignoul, 2003: The persistence of winter sea surface temperature in the North Atlantic. J. Climate, 16, 13641377, https://doi.org/10.1175/1520-0442(2003)16<1364:TPOWSS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., F. Zeng, L. Zhang, R. Zhang, G. A. Vecchi, and X. Yang, 2017: The central role of ocean dynamics in connecting the North Atlantic Oscillation to the extratropical component of the Atlantic multidecadal oscillation. J. Climate, 30, 37893805, https://doi.org/10.1175/JCLI-D-16-0358.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., M. A. Alexander, and M. S. Timlin, 2003: Understanding the persistence of sea surface temperature anomalies in midlatitudes. J. Climate, 16, 5772, https://doi.org/10.1175/1520-0442(2003)016<0057:UTPOSS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., A. S. Phillips, and J. W. Hurrell, 2004: Pacific interdecadal climate variability: Linkages between the tropics and the North Pacific during boreal winter since 1900. J. Climate, 17, 31093124, https://doi.org/10.1175/1520-0442(2004)017<3109:PICVLB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., M. A. Alexander, S.-P. Xie, and A. S. Phillips, 2010: Sea surface temperature variability: Patterns and mechanisms. Annu. Rev. Mar. Sci., 2, 115143, https://doi.org/10.1146/annurev-marine-120408-151453.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., 1979: Stochastic forcing models of climate variability. Dyn. Atmos. Oceans, 3, 465479, https://doi.org/10.1016/0377-0265(79)90025-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., 1981: Low-frequency temperature fluctuations off Bermuda. J. Geophys. Res., 86, 65226528, https://doi.org/10.1029/JC086iC07p06522.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., 1985: Sea surface temperature anomalies, planetary waves, and air–sea feedback in the middle latitudes. Rev. Geophys., 23, 357390, https://doi.org/10.1029/RG023i004p00357.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., and K. Hasselmann, 1977: Stochastic climate models, Part II: Application to sea-surface temperature anomalies and thermocline variability. Tellus, 29, 289305, https://doi.org/10.3402/tellusa.v29i4.11362.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., and R. W. Reynolds, 1983: Testing a dynamical model for mid-latitude sea surface temperature anomalies. J. Phys. Oceanogr., 13, 11311145, https://doi.org/10.1175/1520-0485(1983)013<1131:TADMFM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., and E. Kestenare, 2002: The surface heat flux feedback. Part I: Estimates from observations in the Atlantic and the North Pacific. Climate Dyn., 19, 633647, https://doi.org/10.1007/s00382-002-0252-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., A. Czaja, and B. L’Heveder, 1998: Air–sea feedback in the North Atlantic and surface boundary conditions for ocean models. J. Climate, 11, 23102324, https://doi.org/10.1175/1520-0442(1998)011<2310:ASFITN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., E. Kestenare, and J. Mignot, 2002: The surface heat flux feedback. Part II: Direct and indirect estimates in the ECHAM4/OPA8 coupled GCM. Climate Dyn., 19, 649655, https://doi.org/10.1007/s00382-002-0253-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frenger, I., N. Gruber, R. Knutti, and M. Münnich, 2013: Imprint of Southern Ocean eddies on winds, clouds and rainfall. Nat. Geosci., 6, 608612, https://doi.org/10.1038/ngeo1863.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gelaro, R., and Coauthors, 2017: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). J. Climate, 30, 54195454, https://doi.org/10.1175/JCLI-D-16-0758.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gulev, S. K., M. Latif, N. Keenlyside, W. Park, and K. P. Koltermann, 2013: North Atlantic Ocean control on surface heat flux on multidecadal timescales. Nature, 499, 464467, https://doi.org/10.1038/nature12268.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, A., and S. Manabe, 1997: Can local linear stochastic theory explain sea surface temperature and salinity variability? Climate Dyn., 13, 167180, https://doi.org/10.1007/s003820050158.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, M. M., and H. L. Bryden, 1982: Direct estimates and mechanisms of ocean heat transport. Deep-Sea Res., 29A, 339359, https://doi.org/10.1016/0198-0149(82)90099-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hasselmann, K., 1976: Stochastic climate models part I. Theory. Tellus, 28, 473485, https://doi.org/10.3402/tellusa.v28i6.11316.

  • Hausmann, U., A. Czaja, and J. Marshall, 2016: Estimates of air–sea feedbacks on sea surface temperature anomalies in the Southern Ocean. J. Climate, 29, 439454, https://doi.org/10.1175/JCLI-D-15-0015.1.

    • 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
  • Jin, F.-F., 1997: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54, 811829, https://doi.org/10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2.

    • 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
  • Kim, W. M., S. G. Yeager, and G. Danabasoglu, 2018: Key role of internal ocean dynamics in Atlantic multidecadal variability during the last half century. Geophys. Res. Lett., 45, 13449, https://doi.org/10.1029/2018GL080474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., and Coauthors, 2012: Impact of ocean model resolution on CCSM climate simulations. Climate Dyn., 39, 13031328, https://doi.org/10.1007/s00382-012-1500-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kleeman, R., and S. B. Power, 1995: A simple atmospheric model of surface heat flux for use in ocean modeling studies. J. Phys. Oceanogr., 25, 92105, https://doi.org/10.1175/1520-0485(1995)025<0092:ASAMOS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kwon, Y.-O., and C. Deser, 2007: North Pacific decadal variability in the Community Climate System Model version 2. J. Climate, 20, 24162433, https://doi.org/10.1175/JCLI4103.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kwon, Y.-O., M. A. Alexander, N. A. Bond, C. Frankignoul, H. Nakamura, B. Qiu, and L. A. Thompson, 2010: Role of the Gulf Stream and Kuroshio–Oyashio systems in large-scale atmosphere–ocean interaction: A review. J. Climate, 23, 32493281, https://doi.org/10.1175/2010JCLI3343.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, X., and Coauthors, 2015: Distant influence of Kuroshio eddies on North Pacific weather patterns? Sci. Rep., 5, 17785, https://doi.org/10.1038/srep17785.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, X., and Coauthors, 2016: Western boundary currents regulated by interaction between ocean eddies and the atmosphere. Nature, 535, 533537, https://doi.org/10.1038/nature18640.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marshall, J., H. Johnson, and J. Goodman, 2001: A study of the interaction of the North Atlantic Oscillation with ocean circulation. J. Climate, 14, 13991421, https://doi.org/10.1175/1520-0442(2001)014<1399:ASOTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., S. E. Zebiak, and M. H. Glantz, 2006: ENSO as an integrating concept in Earth science. Science, 314, 17401745, https://doi.org/10.1126/science.1132588.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mignot, J., and C. Frankignoul, 2003: On the interannual variability of surface salinity in the Atlantic. Climate Dyn., 20, 555565, https://doi.org/10.1007/s00382-002-0294-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, L. N., K. Bellomo, M. A. Cane, and A. C. Clement, 2017: The role of historical forcings in simulating the observed Atlantic multidecadal oscillation. Geophys. Res. Lett., 44, 24722480, https://doi.org/10.1002/2016GL071337.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, L. N., J. M. Klavans, A. C. Clement, and M. A. Cane, 2021: Investigating the roles of external forcing and ocean circulation on the Atlantic multidecadal SST variability in a large ensemble climate model hierarchy. J. Climate, 34, 48354849, https://doi.org/10.1175/JCLI-D-20-0167.1.

    • Search Google Scholar
    • Export Citation
  • Myers, T. A., and C. R. Mechoso, 2020: Relative contributions of atmospheric, oceanic, and coupled processes to North Pacific and North Atlantic variability. Geophys. Res. Lett., 47, e2019GL086321, https://doi.org/10.1029/2019GL086321.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M., G. P. Compo, and M. A. Alexander, 2003: ENSO-forced variability of the Pacific decadal oscillation. J. Climate, 16, 38533857, https://doi.org/10.1175/1520-0442(2003)016<3853:EVOTPD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M., and Coauthors, 2016: The Pacific decadal oscillation, revisited. J. Climate, 29, 43994427, https://doi.org/10.1175/JCLI-D-15-0508.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Reilly, C. H., M. Huber, T. Woollings, and L. Zanna, 2016: The signature of low-frequency oceanic forcing in the Atlantic multidecadal oscillation. Geophys. Res. Lett., 43, 28102818, https://doi.org/10.1002/2016GL067925.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, S., C. Deser, and M. A. Alexander, 2005: Estimation of the surface heat flux response to sea surface temperature anomalies over the global oceans. J. Climate, 18, 45824599, https://doi.org/10.1175/JCLI3521.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Patrizio, C. R., and D. W. Thompson, 2021: Quantifying the role of ocean dynamics in ocean mixed-layer temperature variability. J. Climate, 34, 25672589, https://doi.org/10.1175/JCLI-D-20-0476.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philander, S. G. H., 1983: El Niño Southern Oscillation phenomena. Nature, 302, 295301, https://doi.org/10.1038/302295a0.

  • Putrasahan, D., I. Kamenkovich, M. Le Hénaff, and B. Kirtman, 2017: Importance of ocean mesoscale variability for air–sea interactions in the Gulf of Mexico. Geophys. Res. Lett., 44, 63526362, https://doi.org/10.1002/2017GL072884.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, B., N. Schneider, and S. Chen, 2007: Coupled decadal variability in the North Pacific: An observationally constrained idealized model. J. Climate, 20, 36023620, https://doi.org/10.1175/JCLI4190.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., 1978: Sea surface temperature anomalies in the North Pacific Ocean. Tellus, 30, 97103, https://doi.org/10.3402/tellusa.v30i2.10321.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 54735496, https://doi.org/10.1175/2007JCLI1824.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, C. D., M. D. Palmer, R. P. Allan, D. G. Desbruyeres, P. Hyder, C. Liu, and D. Smith, 2017: Surface flux and ocean heat transport convergence contributions to seasonal and interannual variations of ocean heat content. J. Geophys. Res. Oceans, 122, 726744, https://doi.org/10.1002/2016JC012278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saravanan, R., and P. Chang, 2019: Midlatitude mesoscale ocean–atmosphere interaction and its relevance to S2S prediction. Sub-Seasonal to Seasonal Prediction, Elsevier, 183200.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siqueira, L., and B. P. Kirtman, 2016: Atlantic near-term climate variability and the role of a resolved Gulf Stream. Geophys. Res. Lett., 43, 39643972, https://doi.org/10.1002/2016GL068694.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Small, R. J., and Coauthors, 2008: Air–sea interaction over ocean fronts and eddies. Dyn. Atmos. Oceans, 45, 274319, https://doi.org/10.1016/j.dynatmoce.2008.01.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Small, R. J., F. O. Bryan, S. P. Bishop, and R. A. Tomas, 2019: Air–sea turbulent heat fluxes in climate models and observational analyses: What drives their variability? J. Climate, 32, 23972421, https://doi.org/10.1175/JCLI-D-18-0576.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Small, R. J., F. O. Bryan, S. P. Bishop, S. Larson, and R. A. Tomas, 2020: What drives upper-ocean temperature variability in coupled climate models and observations? J. Climate, 33, 577596, https://doi.org/10.1175/JCLI-D-19-0295.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smirnov, D., M. Newman, and M. A. Alexander, 2014: Investigating the role of ocean–atmosphere coupling in the North Pacific Ocean. J. Climate, 27, 592606, https://doi.org/10.1175/JCLI-D-13-00123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Talley, L., 1984: Meridional heat transport in the Pacific Ocean. J. Phys. Oceanogr., 14, 231241, https://doi.org/10.1175/1520-0485(1984)014<0231:MHTITP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • von Storch, J.-S., 2000: Signatures of air–sea interactions in a coupled atmosphere–ocean GCM. J. Climate, 13, 33613379, https://doi.org/10.1175/1520-0442(2000)013<3361:SOASII>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wills, R. C., K. C. Armour, D. S. Battisti, and D. L. Hartmann, 2019a: Ocean–atmosphere dynamical coupling fundamental to the Atlantic multidecadal oscillation. J. Climate, 32, 251272, https://doi.org/10.1175/JCLI-D-18-0269.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wills, R. C., D. S. Battisti, C. Proistosescu, L. Thompson, D. L. Hartmann, and K. C. Armour, 2019b: Ocean circulation signatures of North Pacific decadal variability. Geophys. Res. Lett., 46, 16901701, https://doi.org/10.1029/2018GL080716.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, R., B. P. Kirtman, and K. Pegion, 2006: Local air–sea relationship in observations and model simulations. J. Climate, 19, 49144932, https://doi.org/10.1175/JCLI3904.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yamamoto, A., H. Tatebe, and M. Nonaka, 2020: On the emergence of the Atlantic multidecadal SST signal: A key role of the mixed layer depth variability driven by North Atlantic Oscillation. J. Climate, 33, 35113531, https://doi.org/10.1175/JCLI-D-19-0283.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yan, X., R. Zhang, and T. R. Knutson, 2018: Underestimated AMOC variability and implications for AMV and predictability in CMIP models. Geophys. Res. Lett., 45, 43194328, https://doi.org/10.1029/2018GL077378.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, L., X. Jin, and R. A. Weller, 2008: Multidecade global flux datasets from the objectively analyzed air–sea fluxes (OAFlux) project: Latent and sensible heat fluxes, ocean evaporation, and related surface meteorological variables. OAFlux Project Tech. Rep. OA-2008-01, 74 pp.

    • Search Google Scholar
    • Export Citation
  • Zhang, L., and C. Wang, 2013: Multidecadal North Atlantic sea surface temperature and atlantic meridional overturning circulation variability in CMIP5 historical simulations. J. Geophys. Res. Oceans, 118, 57725791, https://doi.org/10.1002/jgrc.20390.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R., 2017: On the persistence and coherence of subpolar sea surface temperature and salinity anomalies associated with the Atlantic multidecadal variability. Geophys. Res. Lett., 44, 78657875, https://doi.org/10.1002/2017GL074342.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R., R. Sutton, G. Danabasoglu, Y.-O. Kwon, R. Marsh, S. G. Yeager, D. E. Amrhein, and C. M. Little, 2019: A review of the role of the Atlantic Meridional Overturning Circulation in Atlantic multidecadal variability and associated climate impacts. Rev. Geophys., 57, 316375, https://doi.org/10.1029/2019RG000644.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zuo, H., M. A. Balmaseda, S. Tietsche, K. Mogensen, and M. Mayer, 2019: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: A description of the system and assessment. Ocean Sci., 15, 779808, https://doi.org/10.5194/os-15-779-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
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