Reconstructing the Ocean Interior from High-Resolution Sea Surface Information

Lei Liu State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

Search for other papers by Lei Liu in
Current site
Google Scholar
PubMed
Close
,
Huijie Xue State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, and Institution of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences, Guangzhou, China, and School of Marine Sciences, University of Maine, Orono, Maine

Search for other papers by Huijie Xue in
Current site
Google Scholar
PubMed
Close
, and
Hideharu Sasaki Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

Search for other papers by Hideharu Sasaki in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

When evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.

© 2019 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: Huijie Xue, huijiexue@scsio.ac.cn

Abstract

When evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.

© 2019 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: Huijie Xue, huijiexue@scsio.ac.cn
Save
  • Badin, G., 2013: Surface semi-geostrophic dynamics in the ocean. Geophys. Astrophys. Fluid Dyn., 107, 526540, https://doi.org/10.1080/03091929.2012.740479.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Badin, G., 2014: On the role of non-uniform stratification and short-wave instabilities in three-layer quasi-geostrophic turbulence. Phys. Fluids, 26, 096603, https://doi.org/10.1063/1.4895590.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bretherton, F. P., 1966: Critical layer instability in baroclinic flows. Quart. J. Roy. Meteor. Soc., 92, 325334, https://doi.org/10.1002/qj.49709239302.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charney, J. G., 1971: Geostrophic turbulence. J. Atmos. Sci., 28, 10871095, https://doi.org/10.1175/1520-0469(1971)028<1087:GT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chavanne, C. P., and P. Klein, 2010: Can oceanic submesoscale processes be observed with satellite altimetry? Geophys. Res. Lett., 37, L22602, https://doi.org/10.1029/2010GL045057.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chavanne, C. P., and P. Klein, 2016: Quasigeostrophic diagnosis of mixed layer dynamics embedded in a mesoscale turbulent field. J. Phys. Oceanogr., 46, 275287, https://doi.org/10.1175/JPO-D-14-0178.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chelton, D. B., M. G. Schlax, and R. M. Samelson, 2011: Global observations of nonlinear mesoscale eddies. Prog. Oceanogr., 91, 167216, https://doi.org/10.1016/j.pocean.2011.01.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chu, X., H. Xue, Y. Qi, G. Chen, Q. Mao, D. Wang, and F. Chai, 2014: An exceptional anticyclonic eddy in the South China Sea in 2010. J. Geophys. Res. Oceans, 119, 881897, https://doi.org/10.1002/2013JC009314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cooper, M., and K. Haines, 1996: Altimetric assimilation with water property conservation. J. Geophys. Res., 101, 10591077, https://doi.org/10.1029/95JC02902.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de La Lama, M. S., J. H. LaCasce, and H. Fuhr, 2016: The vertical structure of ocean eddies. Dyn. Stat. Climate Syst., 1, dzw001, https://doi.org/10.1093/climsys/dzw001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dibarboure, G., M.-I. Pujol, F. Briol, P.-Y. Le Traon, G. Larnicol, N. Picot, F. Mertz, and M. Ablain, 2011: Jason-2 in DUACS: Updated system description, first tandem results and impact on processing and products. Mar. Geod., 34, 214241, https://doi.org/10.1080/01490419.2011.584826.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Durand, M., L.-L. Fu, D. P. Lettenmaier, D. E. Alsdorf, E. Rodríguez, and D. Esteban-Fernandez, 2010: The surface water and ocean topography mission: Observing terrestrial surface water and oceanic submesoscale eddies. Proc. IEEE, 98, 766779, https://doi.org/10.1109/JPROC.2010.2043031.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ferrari, R., and C. Wunsch, 2010: The distribution of eddy kinetic and potential energies in the global ocean. Tellus, 62, 92108, https://doi.org/10.3402/tellusa.v62i2.15680.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fofonoff, N. P., and R. C. Millard Jr., 1983: UNESCO technical papers in marine science: Algorithms for computation of fundamental properties of seawater. UNESCO Tech. Paper in Marine Science 44, 58 pp.

  • Fresnay, S., A. L. Ponte, S. Le Gentil, and J. Le Sommer, 2018: Reconstruction of the 3-D dynamics from surface variables in a high-resolution simulation of North Atlantic. J. Geophys. Res. Oceans, 123, 16121630, https://doi.org/10.1002/2017JC013400.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fu, L.-L., and C. Ubelmann, 2014: On the transition from profile altimeter to swath altimeter for observing global ocean surface topography. J. Atmos. Oceanic Technol., 31, 560568, https://doi.org/10.1175/JTECH-D-13-00109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gaultier, L., C. Ubelmann, and L.-L. Fu, 2016: The challenge of using future SWOT data for oceanic field reconstruction. J. Atmos. Oceanic Technol., 33, 119126, https://doi.org/10.1175/JTECH-D-15-0160.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • González-Haro, C., and J. Isern-Fontanet, 2014: Global ocean current reconstruction from altimetric and microwave SST measurements. J. Geophys. Res. Oceans, 119, 33783391, https://doi.org/10.1002/2013JC009728.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., 1975: The geostrophic momentum approximation and the semi-geostrophic equations. J. Atmos. Sci., 32, 233242, https://doi.org/10.1175/1520-0469(1975)032<0233:TGMAAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Isern-Fontanet, J., B. Chapron, G. Lapeyre, and P. Klein, 2006: Potential use of microwave sea surface temperatures for the estimation of ocean currents. Geophys. Res. Lett., 33, L24608, https://doi.org/10.1029/2006GL027801.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Isern-Fontanet, J., G. Lapeyre, P. Klein, B. Chapron, and M. W. Hecht, 2008: Three dimensional reconstruction of oceanic mesoscale currents from surface information. J. Geophys. Res., 113, C09005, https://doi.org/10.1029/2007JC004692.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Isern-Fontanet, J., M. Shinde, and C. González-Haro, 2014: On the transfer function between surface fields and the geostrophic stream function in the Mediterranean Sea. J. Phys. Oceanogr., 44, 14061423, https://doi.org/10.1175/JPO-D-13-0186.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Isern-Fontanet, J., J. Ballabrera-Poy, A. Turiel, and E. García-Ladona, 2017: Remote sensing of ocean surface currents: A review of what is being observed and what is being assimilated. Nonlinear Processes Geophys., 24, 613643, https://doi.org/10.5194/npg-24-613-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, P., B. L. Hua, G. Lapeyre, X. Capet, S. L. Gentil, and H. Sasaki, 2008: Upper ocean turbulence from high-resolution 3D simulations. J. Phys. Oceanogr., 38, 17481763, https://doi.org/10.1175/2007JPO3773.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, P., J. Isern-Fontanet, G. Lapeyre, G. Roullet, E. Danioux, B. Chapron, S. Le Gentil, and H. Sasaki, 2009: Diagnosis of vertical velocities in the upper ocean from high resolution sea surface height. Geophys. Res. Lett., 36, L12603, https://doi.org/10.1029/2009GL038359.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Komori, N., K. Takahashi, K. Komine, T. Motoi, X. Zhang, and G. Sagawa, 2005: Description of sea-ice component of Coupled Sea-Ice Model for the Earth Simulator (OIFES). J. Earth Simul., 4, 3145.

    • Search Google Scholar
    • Export Citation
  • LaCasce, J. H., 2012: Surface quasigeostrophic solutions and baroclinic modes with exponential stratification. J. Phys. Oceanogr., 42, 569580, https://doi.org/10.1175/JPO-D-11-0111.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • LaCasce, J. H., 2017: The prevalence of oceanic surface modes. Geophys. Res. Lett., 44, 11 09711 105, https://doi.org/10.1002/2017GL075430.

  • LaCasce, J. H., and A. Mahadevan, 2006: Estimating subsurface horizontal and vertical velocities from sea surface temperature. J. Mar. Res., 64, 695721, https://doi.org/10.1357/002224006779367267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • LaCasce, J. H., and J. Wang, 2015: Estimating subsurface velocities from surface fields with idealized stratification. J. Phys. Oceanogr., 45, 24242435, https://doi.org/10.1175/JPO-D-14-0206.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lapeyre, G., 2009: What vertical mode does the altimeter reflect? On the decomposition in baroclinic modes and on a surface-trapped mode. J. Phys. Oceanogr., 39, 28572874, https://doi.org/10.1175/2009JPO3968.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lapeyre, G., 2017: Surface quasi-geostrophy. Fluids, 2, 7, https://doi.org/10.3390/fluids2010007.

  • Lapeyre, G., and P. Klein, 2006: Dynamics of the upper oceanic layers in terms of surface quasigeostrophy theory. J. Phys. Oceanogr., 36, 165176, https://doi.org/10.1175/JPO2840.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Z., J. Wang, and L.-L. Fu, 2019: An Observing System Simulation Experiment for ocean state estimation to assess the performance of the SWOT mission: Part 1-A twin experiment. J. Geophys. Res. Oceans, 124, 48384855, https://doi.org/10.1029/2018JC014869.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, L., S. Peng, J. Wang, and R. X. Huang, 2014: Retrieving density and velocity fields of the ocean’s interior from surface data. J. Geophys. Res. Oceans, 119, 85128529, https://doi.org/10.1002/2014JC010221.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, L., S. Peng, and R. X. Huang, 2017: Reconstruction of ocean’s interior from observed sea surface information. J. Geophys. Res. Oceans, 122, 10421056, https://doi.org/10.1002/2016JC011927.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Masumoto, Y., and Coauthors, 2004: A fifty-year eddy-resolving simulation of the World Ocean: Preliminary outcomes of OFES (OGCM for the Earth Simulator). J. Earth Simul., 1, 3556.

    • Search Google Scholar
    • Export Citation
  • Morrow, R., and Coauthors, 2019: Global observations of fine-scale ocean surface topography with the Surface Water and Ocean Topography (SWOT) mission. Front. Mar. Sci., 6, 232, https://doi.org/10.3389/fmars.2019.00232.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noh, Y., and H. J. Kim, 1999: Simulations of temperature and turbulence structure of the oceanic boundary layer with the improved near-surface process. J. Geophys. Res. Oceans, 104, 15 62115 634, https://doi.org/10.1029/1999JC900068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nonaka, M., Y. Sasai, H. Sasaki, B. Taguchi, and H. Nakamura, 2016: How potentially predictable are midlatitude ocean currents? Sci. Rep., 6, 20153, https://doi.org/10.1038/srep20153.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Onogi, K., and Coauthors, 2007: The JRA-25 Reanalysis. J. Meteor. Soc. Japan, 85, 369432, https://doi.org/10.2151/jmsj.85.369.

  • Pedlosky, J., 1987: Geophysical Fluid Dynamics. 2nd ed. Springer, 728 pp.

  • Phillips, N. A., 1954: Energy transformations and meridional circulations associated with simple baroclinic waves in a two-level, quasi-geostrophic model. Tellus, 6, 273286, https://doi.org/10.1111/j.2153-3490.1954.tb01123.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ponte, A. L., and P. Klein, 2013: Reconstruction of the upper ocean 3D dynamics from high resolution sea surface height. Ocean Dyn., 63, 777791, https://doi.org/10.1007/s10236-013-0611-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ponte, A. L., P. Klein, X. Capet, P.-Y. Le Traon, B. Chapron, and P. Lherminier, 2013: Diagnosing surface mixed layer dynamics from high-resolution satellite observations: Numerical insights. J. Phys. Oceanogr., 43, 13451355, https://doi.org/10.1175/JPO-D-12-0136.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, B., S. Chen, P. Klein, C. Ubelmann, L.-L. Fu, and H. Sasaki, 2016: Reconstructability of three-dimensional upper-ocean circulation from SWOT sea surface height measurements. J. Phys. Oceanogr., 46, 947963, https://doi.org/10.1175/JPO-D-15-0188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ragone, F., and G. Badin, 2016: A study of surface semi-geostrophic turbulence: Freely decaying dynamics. J. Fluid Mech., 792, 740774, https://doi.org/10.1017/jfm.2016.116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rocha, C. B., A. Tandon, I. C. A. da Silveira, and J. A. M. Lima, 2013: Traditional quasi-geostrophic modes and surface quasi-geostrophic solutions in the Southwestern Atlantic. J. Geophys. Res. Oceans, 118, 27342745, https://doi.org/10.1002/jgrc.20214.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sasaki, H., and P. Klein, 2012: SSH wavenumber spectra in the North Pacific from a high-resolution realistic simulation. J. Phys. Oceanogr., 42, 12331241, https://doi.org/10.1175/JPO-D-11-0180.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sasaki, H., P. Klein, B. Qiu, and Y. Sasai, 2014: Impact of oceanic-scale interactions on the seasonal modulation of ocean dynamics by the atmosphere. Nat. Commun., 5, 5636, https://doi.org/10.1038/ncomms6636.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sasaki, H., P. Klein, Y. Sasai, and B. Qiu, 2017: Regionality and seasonality of submesoscale and mesoscale turbulence in the North Pacific Ocean. Ocean Dyn., 67, 11951216, https://doi.org/10.1007/s10236-017-1083-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, K. S., 2007: The geography of linear baroclinic instability in Earth’s oceans. J. Mar. Res., 65, 655683, https://doi.org/10.1357/002224007783649484.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, K. S., and G. K. Vallis, 2001: The scales and equilibration of midocean eddies: Freely evolving flow. J. Phys. Oceanogr., 31, 554571, https://doi.org/10.1175/1520-0485(2001)031<0554:TSAEOM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, K. S., and J. Vanneste, 2013: A surface-aware projection basis for quasigeostrophic flow. J. Phys. Oceanogr., 43, 548562, https://doi.org/10.1175/JPO-D-12-0107.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stammer, D., 1997: Global characteristics of ocean variability estimated from regional TOPEX/Poseidon altimeter measurements. J. Phys. Oceanogr., 27, 17431769, https://doi.org/10.1175/1520-0485(1997)027<1743:GCOOVE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Su, Z., J. Wang, P. Klein, A. F. Thompson, and D. Menemenlis, 2018: Ocean submesoscales as a key component of the global heat budget. Nat. Commun., 9, 775, https://doi.org/10.1038/s41467-018-02983-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Torres, H. S., P. Klein, D. Menemenlis, B. Qiu, Z. Su, J. Wang, S. Chen, and L.-L. Fu, 2018: Partitioning ocean motions into balanced motions and internal gravity waves: A modeling study in anticipation of future space missions. J. Geophys. Res. Oceans, 123, 80848105, https://doi.org/10.1029/2018JC014438.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tulloch, R., J. Marshall, C. Hill, and K. S. Smith, 2011: Scales, growth rates, and spectral fluxes of baroclinic instability in the ocean. J. Phys. Oceanogr., 41, 10571076, https://doi.org/10.1175/2011JPO4404.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., and L.-L. Fu, 2019: On the long-wavelength validation of the SWOT KaRIn measurement. J. Atmos. Oceanic Technol., 36, 843848, https://doi.org/10.1175/JTECH-D-18-0148.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., G. Flierl, J. LaCasce, J. McClean, and A. Mahadevan, 2013: Reconstructing the ocean’s interior from surface data. J. Phys. Oceanogr., 43, 16111626, https://doi.org/10.1175/JPO-D-12-0204.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., L.-L. Fu, B. Qiu, D. Menemenlis, T. Farrar, Y. Chao, A. Thompson, and M. Flexas, 2018: An observing system simulation experiment for the calibration and validation of the Surface Water Ocean Topography sea surface height measurement using in-situ platforms. J. Atmos. Oceanic Technol., 35, 281297, https://doi.org/10.1175/JTECH-D-17-0076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., L.-L. Fu, H. Torres, S. Chen, B. Qiu, and D. Menemenlis, 2019: On the spatial scales to be resolved by the Surface Water and Ocean Topography Ka-band radar interferometer. J. Atmos. Oceanic Technol., 36, 8799, https://doi.org/10.1175/JTECH-D-18-0119.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wortham, C., and C. Wunsch, 2014: A multi-dimensional spectral description of ocean variability. J. Phys. Oceanogr., 44, 944966, https://doi.org/10.1175/JPO-D-13-0113.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wunsch, C., 1997: The vertical partition of oceanic horizontal kinetic energy. J. Phys. Oceanogr., 27, 17701794, https://doi.org/10.1175/1520-0485(1997)027<1770:TVPOOH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wunsch, C., 2015 :Modern Observational Physical Oceanography: Understanding the Global Ocean. Princeton University Press, 511 pp.

  • Zhang, Z., W. Wang, and B. Qiu, 2014: Oceanic mass transport by mesoscale eddies. Science, 345, 322324, https://doi.org/10.1126/science.1252418.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 892 284 16
PDF Downloads 816 198 7