• Argo, 2000: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC). SEANOE, accessed 21 December 2020, http://doi.org/10.17882/42182.

    • Search Google Scholar
    • Export Citation
  • Bacmeister, J. T., M. F. Wehner, R. B. Neale, A. Gettelman, C. Hannay, P. H. Lauritzen, J. M. Caron, and J. E. Truesdale, 2014: Exploratory high-resolution climate simulations using the Community Atmosphere Model (CAM). J. Climate, 27, 30733099, https://doi.org/10.1175/JCLI-D-13-00387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellucci, A., and Coauthors, 2021: 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., P. R. Gent, F. O. Bryan, A. F. Thompson, M. C. Long, and R. Abernathey, 2016: Southern Ocean overturning compensation in an eddy-resolving climate simulation. J. Phys. Oceanogr., 46, 15751592, https://doi.org/10.1175/JPO-D-15-0177.1.

    • 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
  • Bishop, S. P., F. O. Bryan, and R. J. Small, 2020: The global sink of available potential energy by mesoscale air-sea interaction. J. Adv. Model. Earth Syst., 12, e2020MS002118, https://doi.org/10.1029/2020MS002118.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brambilla, E., L. D. Talley, and P. E. Robbins, 2008: Subpolar Mode Water in the northeastern Atlantic: 2. Origin and transformation. J. Geophys. Res., 113, C04026, https://doi.org/10.1029/2006JC004063.

    • Search Google Scholar
    • Export Citation
  • Cerovečki, I., and J. Marshall, 2008: Eddy modulation of air–sea interaction and convection. J. Phys. Oceanogr., 38, 6583, https://doi.org/10.1175/2007JPO3545.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cerovečki, I., and M. R. Mazloff, 2016: The spatiotemporal structure of processes governing the evolution of Subantarctic Mode Water in the Southern Ocean. J. Phys. Oceanogr., 46, 683710, https://doi.org/10.1175/JPO-D-14-0243.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cerovečki, I., L. D. Talley, and M. R. Mazloff, 2011: A comparison of Southern Ocean air–sea buoyancy flux from an ocean state estimate with five other products. J. Climate, 24, 62836306, https://doi.org/10.1175/2011JCLI3858.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cerovečki, I., L. D. Talley, M. R. Mazloff, and G. Maze, 2013: Subantarctic Mode Water formation, destruction and export in the eddy-permitting Southern Ocean state estimate. J. Phys. Oceanogr., 43, 14851511, https://doi.org/10.1175/JPO-D-12-0121.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chang, P., and Coauthors, 2020: An unprecedented set of high-resolution Earth system simulations for understanding multiscale interactions in climate variability and change. J. Adv. Model. Earth Syst., 12, e2020MS002298, https://doi.org/10.1029/2020MS002298.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Danabasoglu, G., S. C. Bates, B. P. Briegleb, S. R. Jayne, M. Jochum, W. G. Large, S. Peacock, and S. G. Yeager, 2012: The CCSM4 ocean component. J. Climate, 25, 13611389, https://doi.org/10.1175/JCLI-D-11-00091.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dennis, J., and Coauthors, 2012: CAM-SE: A scalable spectral element dynamical core for the community atmosphere model. Int. J. High Perform. Comput. Appl., 26, 7489, https://doi.org/10.1177/1094342011428142.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donlon, C., and Coauthors, 2007: The Global Ocean Data Assimilation Experiment High-Resolution Sea Surface Temperature Pilot Project. Bull. Amer. Meteor. Soc., 88, 11971214, https://doi.org/10.1175/BAMS-88-8-1197.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett, C., and A. Tandon, 1997: The effects on water mass formation of surface mixed layer time-dependence and entrainment fluxes. Deep-Sea Res., 44, 19912006, https://doi.org/10.1016/S0967-0637(97)00055-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Groeskamp, S., and D. Iudicone, 2018: The effect of air-sea flux products, shortwave radiation depth penetration, and albedo on the upper ocean overturning circulation. Geophys. Res. Lett., 45, 90879097, https://doi.org/10.1029/2018GL078442.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Groeskamp, S., R. P. Abernathey, and A. Klocker, 2016: Water mass transformation by cabbeling and thermobaricity. Geophys. Res. Lett., 43, 10 83510 845, https://doi.org/10.1002/2016GL070860.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Groeskamp, S., S. M. Griffies, D. Iudicone, R. Marsh, A. J. G. Nurser, and J. D. Zika, 2019: The water mass transformation framework for ocean physics and biogeochemistry. Annu. Rev. Mar. Sci., 11, 271305, https://doi.org/10.1146/annurev-marine-010318-095421.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hallberg, R., 2013: Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects. Ocean Modell., 72, 92103, https://doi.org/10.1016/j.ocemod.2013.08.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hanawa, K., 1987: Interannual variations of the winter-time outcrop area of subtropical mode water in the western North Pacific Ocean. Atmos.–Ocean, 25, 358374, https://doi.org/10.1080/07055900.1987.9649280.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hanawa, K., and L. D. Talley, 2011: Mode waters. Ocean Circulation and Climate: Observing and Modelling the Global Ocean, G. Seidler, J. Church, and J. Gould, Eds., International Geophysics, Vol. 77, Academic Press, 373386.

    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

  • Holmes, R. M., J. D. Zika, S. M. Griffies, A. McC. Hogg, A. E. Kiss, and M. H. England, 2021: The geography of numerical mixing in a suite of global ocean models. J. Adv. Model. Earth Syst., 13, e2020MS002333, https://doi.org/10.1029/2020MS002333.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hunke, E. C., and W. H. Lipscombe, 2010: CICE: The Los Alamos Sea Ice Model documentation and software user’s manual, version 4.1. Doc. LA-CC-06-012, 76 pp., http://csdms.colorado.edu/w/images/CICE_documentation_and_software_user′s_manual.pdf.

    • 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
  • Iudicone, D., G. Madec, and T. J. McDougall, 2008: Water mass transformation in a neutral density framework and the key role of light penetration. J. Phys. Oceanogr., 38, 13571376, https://doi.org/10.1175/2007JPO3464.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joyce, T. M., L. N. Thomas, W. K. Dewar, and J. B. Girton, 2013: Eighteen degree water formation within the Gulf Stream during CLIMODE. Deep-Sea Res. II, 91, 110, https://doi.org/10.1016/j.dsr2.2013.02.019.

    • 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
  • Large, W. G., and S. G. Yeager, 2009: The global climatology of an interannually varying air-sea flux data set. Climate Dyn., 33, 341364, https://doi.org/10.1007/s00382-008-0441-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Large, W. G., J. C. McWilliams, and S. C. Doney, 1994: Oceanic vertical mixing: A review and a model with nonlocal boundary layer parameterization. Rev. Geophys., 32, 363403, https://doi.org/10.1029/94RG01872.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Coauthors, 2011: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. J. Adv. Model. Earth Syst., 3, M03001, https://doi.org/10.1029/2011MS00045.

    • Search Google Scholar
    • Export Citation
  • Li, Z., M. H. England, S. Groeskamp, I. Cerovečki, and Y. Luo, 2021: The origin and fate of Subantarctic Mode Water in the Southern Ocean. J. Phys. Oceanogr., 51, 29512972, https://doi.org/10.1175/JPO-D-20-0174.1.

    • Search Google Scholar
    • Export Citation
  • Maltrud, M. E., and J. L. McClean, 2005: An eddy resolving global 1/10° ocean simulation. Ocean Modell., 8, 3154, https://doi.org/10.1016/j.ocemod.2003.12.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marshall, D., 1997: Subduction of water masses in an eddying ocean. J. Mar. Res., 55, 201222, https://doi.org/10.1357/0022240973224373.

  • Marshall, J., D. Jamous, and J. Nilsson, 1999: Reconciling thermodynamic and dynamic methods of computation of water mass transformation rates. Deep-Sea Res. I, 46, 545572, https://doi.org/10.1016/S0967-0637(98)00082-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Masuzawa, J., 1969: Subtropical mode water. Deep-Sea Res., 16, 463472, https://doi.org/10.1016/0011-7471(69)90034-5.

  • Maze, G., G. Forget, M. Buckley, J. Marshall, and I. Cerovecki, 2009: Using transformation and formation maps to study the role of air–sea heat fluxes in North Atlantic Eighteen Degree Water formation. J. Phys. Oceanogr., 39, 18181835, https://doi.org/10.1175/2009JPO3985.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mazloff, M. R., P. Heimbach, and C. Wunsch, 2010: An eddy-permitting Southern Ocean state estimate. J. Phys. Oceanogr., 40, 880899, https://doi.org/10.1175/2009JPO4236.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCartney, M. S., 1977: Subantarctic mode water. A Voyage of Discovery: George Deacon 70th Anniversary Volume, M. V. Angel, Ed., Pergammon Press, 103119.

    • Search Google Scholar
    • Export Citation
  • McCartney, M. S., 1982: The subtropical recirculation of mode waters. J. Mar. Res., 40 (Suppl.), 427464.

  • McCartney, M. S., and L. D. Talley, 1982: The subpolar mode water of the North Atlantic Ocean. J. Phys. Oceanogr., 12, 11691188, https://doi.org/10.1175/1520-0485(1982)012<1169:TSMWOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McClean, J. L., and Coauthors, 2011: A prototype two-decade fully-coupled fine resolution CCSM simulation. Ocean Modell., 39, 1030, https://doi.org/10.1016/j.ocemod.2011.02.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDougall, T. J., 1987: Thermobaricity, cabbeling, and water-mass conversion. J. Geophys. Res., 92, 54485464, https://doi.org/10.1029/JC092iC05p05448.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDougall, T. J., D. R. Jackett, D. R. Wright, and R. Feistel, 2003: Accurate and computationally efficient algorithms for potential density and density of seawater. J. Atmos. Oceanic Technol., 20, 730741, https://doi.org/10.1175/1520-0426(2003)20<730:AACEAF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McGillicuddy, D. J., and Coauthors, 2007: Eddy/wind interactions stimulate extraordinary mid-ocean plankton blooms. Science, 316, 10211026, https://doi.org/10.1126/science.1136256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melnichenko, O., P. Hacker, N. Maximenko, G. Lagerloef, and J. Potemra, 2016: Optimal interpolation of Aquarius sea surface salinity. J. Geophys. Res. Oceans, 121, 602616, https://doi.org/10.1002/2015JC011343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newsom, E. R., C. M. Bitz, F. O. Bryan, R. Abernathey, and P. R. Gent, 2016: Southern Ocean deep circulation and heat uptake in a high-resolution climate model. J. Climate, 29, 25972619, https://doi.org/10.1175/JCLI-D-15-0513.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nurser, A. J. G., R. Marsh, and R. G. Williams, 1999: Diagnosing water mass formation from air–sea fluxes and surface mixing. J. Phys. Oceanogr., 29, 14681487, https://doi.org/10.1175/1520-0485(1999)029<1468:DWMFFA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ogle, S. E., V. Tamsitt, S. A. Josey, S. T. Gille, I. Cerovečki, L. D. Talley, and R. A. Weller, 2018: Episodic Southern Ocean heat loss and its mixed layer impacts revealed by the farthest south multiyear surface flux mooring. Geophys. Res. Lett., 45, 50025010, https://doi.org/10.1029/2017GL076909.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ohlmann, J. C., 2003: Ocean radiant heating in climate models. J. Climate, 16, 13371351, https://doi.org/10.1175/1520-0442-16.9.1337.

  • O’Reilly, C. H., and L. Zanna, 2018: The signature of oceanic processes in decadal extratropical SST anomalies. Geophys. Res. Lett., 45, 77197730, https://doi.org/10.1029/2018GL079077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, S., C. S. Bretherton, and P. J. Rasch, 2014: Integrating cloud processes in the Community Atmosphere Model, version 5. J. Climate, 27, 68216856, https://doi.org/10.1175/JCLI-D-14-00087.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, B., P. Hacker, S. Chen, K. A. Donohue, D. R. Watts, H. Mitsudera, N. G. Hogg, and S. R. Jayne, 2006: Observations of the subtropical mode water evolution from the Kuroshio Extension System Study. J. Phys. Oceanogr., 36, 457473, https://doi.org/10.1175/JPO2849.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, M. J., H. T. Hewitt, P. Hyder, D. Ferreira, S. A. Josey, M. Mizielinski, and A. Shelly, 2016: Impact of ocean resolution on coupled air-sea fluxes and large-scale climate. Geophys. Res. Lett., 43, 10 43010 438, https://doi.org/10.1002/2016GL070559.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roemmich, D., and J. Gilson, 2009: The 2004–2008 mean and annual cycle of temperature, salinity and steric height in the global ocean from the Argo program. Prog. Oceanogr., 82, 81100, https://doi.org/10.1016/j.pocean.2009.03.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roemmich, D., and Coauthors, 2009: The Argo program: Observing the global ocean with profiling floats. Oceanography, 22, 3443, https://doi.org/10.5670/oceanog.2009.36.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sallée, J.-B., E. Shuckburgh, N. Bruneau, A. J. S. Meijers, T. J. Barcegirdle, and Z. Wang, 2013: Assessment of Southern Ocean mixed-layer depths in CMIP5 models: Historical bias and forcing response. J. Geophys. Res. Oceans, 118, 18451862, https://doi.org/10.1002/jgrc.20157.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schulz, E. W., S. A. Josey, and R. Verein, 2012: First air-sea flux mooring measurements in the Southern Ocean. Geophys. Res. Lett., 39, L16606, https://doi.org/10.1029/2012GL052290.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Small, R. J., and Coauthors, 2014: A new synoptic scale resolving global climate simulation using the Community Earth System Model. J. Adv. Model. Earth Syst., 6, 10651094, https://doi.org/10.1002/2014MS000363.

    • 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
  • Small, R. J., A. K. duVivier, D. B. Whitt, M. C. Long, I. Grooms, and W. G. Large, 2021: On the control of the subantarctic stratification by the ocean circulation. Climate Dyn., 56, 299327, https://doi.org/10.1007/s00382-020-05473-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, R. D., and Coauthors, 2010: The Parallel Ocean Program (POP) reference manual. Los Alamos National Laboratory Tech. Rep. LAUR-10-01853, 141 pp., https://www.cesm.ucar.edu/models/cesm1.0/pop2/doc/sci/POPRefManual.pdf.

    • Search Google Scholar
    • Export Citation
  • Speer, K., and E. Tziperman, 1992: Rates of water mass formation in the North Atlantic Ocean. J. Phys. Oceanogr., 22, 93104, https://doi.org/10.1175/1520-0485(1992)022%3C0093:ROWMFI%3E2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Speer, K., and G. Forget, 2013: Global distribution and formation of mode waters. Ocean Circulation and Climate: A 21st Century Perspective, International Geophysics, Vol. 103, Elsevier, 211226.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamsitt, V., I. Cerovečki, S. A. Josey, S. T. Gille, and E. Schulz, 2020: Mooring observations of air–sea heat fluxes in two Subantarctic Mode Water formation regions. J. Climate, 33, 27572777, https://doi.org/10.1175/JCLI-D-19-0653.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Titchner, H. A., and N. A. Rayner, 2014: The Met Office Hadley Centre sea ice and sea surface temperature dataset, version 2: 1. Sea ice concentrations. J. Geophys. Res. Atmos., 119, 28642889, https://doi.org/10.1002/2013JD020316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tziperman, E., 1986: On the role of interior mixing and air–sea fluxes in determining the stratification and circulation of the oceans. J. Phys. Oceanogr., 16, 680693, https://doi.org/10.1175/1520-0485(1986)016<0680:OTROIM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Urakawa, L. S., and H. Hasumi, 2012: Eddy-resolving model estimate of the cabbeling effect on the water mass transformation in the Southern Ocean. J. Phys. Oceanogr., 42, 12881302, https://doi.org/10.1175/JPO-D-11-0173.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Walin, G., 1982: On the relation between sea-surface heat flow and thermal circulation in the ocean. Tellus, 34, 187195, https://doi.org/10.3402/tellusa.v34i2.10801.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weijer, W., and Coauthors, 2012: The Southern Ocean and its climate in CCSM4. J. Climate, 25, 26522675, https://doi.org/10.1175/JCLI-D-11-00302.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Worthington, L. V., 1959: The 18° water in the Sargasso Sea. Deep-Sea Res., 5, 297305, https://doi.org/10.1016/0146-6313(58)90026-1.

    • Search Google Scholar
    • Export Citation
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Surface Water Mass Transformation in the Southern Ocean: The Role of Eddies Revisited

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  • 1 aNational Center for Atmospheric Research, Boulder, Colorado
  • | 2 bNorth Carolina State University, Raleigh, North Carolina
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Abstract

The water mass transformation (WMT) framework describes how water of one class, such as a discrete interval of density, is converted into another class via air–sea fluxes or interior mixing processes. This paper investigates how this process is modified at the surface when mesoscale ocean eddies are present, using a state-of-the-art high-resolution climate model with reasonable fidelity in the Southern Ocean. The method employed is to coarse-grain the high-resolution model fields to remove eddy signatures, and compare the results with those from the full model fields. This method shows that eddies reduced the WMT by 2–4 Sv (10%–20%; 1 Sv ≡ 106 m3 s−1) over a wide range of densities, from typical values of 20 Sv in the smoothed case. The corresponding water mass formation was reduced by 40% at one particular density increment, namely, between 1026.4 and 1026.5 kg m−3, which corresponds to the lighter end of the range of Indian Ocean Mode Water in the model. The effect of eddies on surface WMT is decomposed into three terms: direct modulation of the density outcrops, then indirectly, by modifying the air–sea density flux, and the combined effect of the two, akin to a covariance. It is found that the first and third terms dominate, i.e., smoothing the outcrops alone has a significant effect, as does the combination of smoothing both outcrops and density flux distributions, but smoothing density flux fields alone has little effect. Results from the coarse-graining method are compared to an alternative approach of temporally averaging the data. Implications for climate model resolution are also discussed.

© 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: R. Justin Small, jsmall@ucar.edu

Abstract

The water mass transformation (WMT) framework describes how water of one class, such as a discrete interval of density, is converted into another class via air–sea fluxes or interior mixing processes. This paper investigates how this process is modified at the surface when mesoscale ocean eddies are present, using a state-of-the-art high-resolution climate model with reasonable fidelity in the Southern Ocean. The method employed is to coarse-grain the high-resolution model fields to remove eddy signatures, and compare the results with those from the full model fields. This method shows that eddies reduced the WMT by 2–4 Sv (10%–20%; 1 Sv ≡ 106 m3 s−1) over a wide range of densities, from typical values of 20 Sv in the smoothed case. The corresponding water mass formation was reduced by 40% at one particular density increment, namely, between 1026.4 and 1026.5 kg m−3, which corresponds to the lighter end of the range of Indian Ocean Mode Water in the model. The effect of eddies on surface WMT is decomposed into three terms: direct modulation of the density outcrops, then indirectly, by modifying the air–sea density flux, and the combined effect of the two, akin to a covariance. It is found that the first and third terms dominate, i.e., smoothing the outcrops alone has a significant effect, as does the combination of smoothing both outcrops and density flux distributions, but smoothing density flux fields alone has little effect. Results from the coarse-graining method are compared to an alternative approach of temporally averaging the data. Implications for climate model resolution are also discussed.

© 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: R. Justin Small, jsmall@ucar.edu

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