Scale Dependence of Midlatitude Air–Sea Interaction

Stuart P. Bishop North Carolina State University, Raleigh, North Carolina

Search for other papers by Stuart P. Bishop in
Current site
Google Scholar
PubMed
Close
,
R. Justin Small National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by R. Justin Small in
Current site
Google Scholar
PubMed
Close
,
Frank O. Bryan National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Frank O. Bryan in
Current site
Google Scholar
PubMed
Close
, and
Robert A. Tomas National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Robert A. Tomas in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

It has traditionally been thought that midlatitude sea surface temperature (SST) variability is predominantly driven by variations in air–sea surface heat fluxes (SHFs) associated with synoptic weather variability. Here it is shown that in regions marked by the highest climatological SST gradients and SHF loss to the atmosphere, the variability in SST and SHF at monthly and longer time scales is driven by internal ocean processes, termed here “oceanic weather.” This is shown within the context of an energy balance model of coupled air–sea interaction that includes both stochastic forcing for the atmosphere and ocean. The functional form of the lagged correlation between SST and SHF allows us to discriminate between variability that is driven by atmospheric versus oceanic weather. Observations show that the lagged functional relationship of SST–SHF and SST tendency–SHF correlation is indicative of ocean-driven SST variability in the western boundary currents (WBCs) and the Antarctic Circumpolar Current (ACC). By applying spatial and temporal smoothing, thereby dampening the signature SST anomalies generated by eddy stirring, it is shown that the oceanic influence on SST variability increases with time scale but decreases with increasing spatial scale. The scale at which SST variability in the WBCs and the ACC transitions from ocean to atmosphere driven occurs at scales less than 500 km. This transition scale highlights the need to resolve mesoscale eddies in coupled climate models to adequately simulate the variability of air–sea interaction. Away from strong SST fronts the lagged functional relationships are indicative of the traditional paradigm of atmospherically driven SST variability.

© 2017 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: Stuart P. Bishop, spbishop@ncsu.edu

Abstract

It has traditionally been thought that midlatitude sea surface temperature (SST) variability is predominantly driven by variations in air–sea surface heat fluxes (SHFs) associated with synoptic weather variability. Here it is shown that in regions marked by the highest climatological SST gradients and SHF loss to the atmosphere, the variability in SST and SHF at monthly and longer time scales is driven by internal ocean processes, termed here “oceanic weather.” This is shown within the context of an energy balance model of coupled air–sea interaction that includes both stochastic forcing for the atmosphere and ocean. The functional form of the lagged correlation between SST and SHF allows us to discriminate between variability that is driven by atmospheric versus oceanic weather. Observations show that the lagged functional relationship of SST–SHF and SST tendency–SHF correlation is indicative of ocean-driven SST variability in the western boundary currents (WBCs) and the Antarctic Circumpolar Current (ACC). By applying spatial and temporal smoothing, thereby dampening the signature SST anomalies generated by eddy stirring, it is shown that the oceanic influence on SST variability increases with time scale but decreases with increasing spatial scale. The scale at which SST variability in the WBCs and the ACC transitions from ocean to atmosphere driven occurs at scales less than 500 km. This transition scale highlights the need to resolve mesoscale eddies in coupled climate models to adequately simulate the variability of air–sea interaction. Away from strong SST fronts the lagged functional relationships are indicative of the traditional paradigm of atmospherically driven SST variability.

© 2017 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: Stuart P. Bishop, spbishop@ncsu.edu
Save
  • Barsugli, J., and D. Battisti, 1998: The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. J. Atmos. Sci., 55, 477493, doi:10.1175/1520-0469(1998)055<0477:TBEOAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bishop, S. P., F. O. Bryan, and R. J. Small, 2015: Bjerknes-like compensation in the wintertime North Pacific. J. Phys. Oceanogr., 45, 13391355, doi:10.1175/JPO-D-14-0157.1.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cronin, M. F., and Coauthors, 2013: Formation and erosion of the seasonal thermocline in the Kuroshio Extension recirculation gyre. Deep-Sea Res. II, 85, 6274, doi:10.1016/j.dsr2.2012.07.018.

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

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., N. Sennéchael, Y.-O. Kwon, and M. A. Alexander, 2011: Influence of the meridional shifts of the Kuroshio and Oyashio Extensions on the atmospheric circulation. J. Climate, 24, 762777, doi:10.1175/2010JCLI3731.1.

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

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

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

  • Kelly, K., 2004: The relationship between oceanic heat transport and surface fluxes in the western North Pacific: 1970–2000. J. Climate, 17, 573588, doi:10.1175/1520-0442(2004)017<0573:TRBOHT>2.0.CO;2.

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

    • 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, doi:10.1038/nature18640.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, B., and S. Chen, 2005: Variability of the Kuroshio Extension jet, recirculation gyre, and mesoscale eddies on decadal time scales. J. Phys. Oceanogr., 35, 20902103, doi:10.1175/JPO2807.1.

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

  • Reynolds, R., T. M. Smith, C. Liu, D. Chelton, K. Casey, and M. Schlax, 2007: Daily high-resolution-blended analysis for sea surface temperature. J. Climate, 20, 54735496, doi:10.1175/2007JCLI1824.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, C., M. Palmer, R. Allan, D. 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, doi:10.1002/2016JC012278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, A., and K. Richards, 2011: Low frequency variability of Southern Ocean jets. J. Geophys. Res., 116, C09022, doi:10.1029/2010JC006749.

    • Search Google Scholar
    • Export Citation
  • Thompson, A., P. Haynes, C. Wilson, and K. Richards, 2010: Rapid Southern Ocean front transitions in an eddy-resolving ocean GCM. Geophys. Res. Lett., 37, L23602, doi:10.1029/2010GL045386.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, R., and B. P. Kirtman, 2007: Regimes of seasonal air–sea interaction and implications for performance of forced simulations. Climate Dyn., 29, 393410, doi:10.1007/s00382-007-0246-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, R., and J. L. Kinter, 2010: Atmosphere-ocean relationship in the midlatitude North Pacific: Seasonal dependence and east-west contrast. J. Geophys. Res., 115, D06101, doi:10.1029/2009JD012579.

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

    • 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. Woods Hole Oceanographic Institution Rep. OA-2008-1, 64 pp.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2385 839 58
PDF Downloads 2000 581 56