Measurement of Small-Scale Surface Velocity and Turbulent Kinetic Energy Dissipation Rates Using Infrared Imaging

Shelby Metoyer Texas A&M University Corpus Christi, Corpus Christi, Texas

Search for other papers by Shelby Metoyer in
Current site
Google Scholar
PubMed
Close
,
Mohammad Barzegar Texas A&M University Corpus Christi, Corpus Christi, Texas

Search for other papers by Mohammad Barzegar in
Current site
Google Scholar
PubMed
Close
,
Darek Bogucki Texas A&M University Corpus Christi, Corpus Christi, Texas

Search for other papers by Darek Bogucki in
Current site
Google Scholar
PubMed
Close
,
Brian K. Haus University of Miami, Miami, Florida

Search for other papers by Brian K. Haus in
Current site
Google Scholar
PubMed
Close
, and
Mingming Shao University of Miami, Miami, Florida

Search for other papers by Mingming Shao in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Short-range infrared (IR) observations of ocean surface reveal complicated spatially varying and evolving structures. Here we present an approach to use spatially correlated time series IR images, over a time scale of one-tenth of a second, of the water surface to derive underlying surface velocity and turbulence fields. The approach here was tested in a laboratory using grid-generated turbulence and a heater assembly. The technique was compared with in situ measurements to validate our IR-derived remote measurements. The IR-measured turbulent kinetic energy (TKE) dissipation rates were consistent with in situ–measured dissipation using a vertical microstructure profiler (VMP). We used measurements of the gradient of the velocity field to calculate TKE dissipation rates at the surface. Based on theoretical and experimental considerations, we have proposed two models of IR TKE dissipation rate retrievals and designed an approach for oceanic field IR applications.

© 2021 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: Shelby Metoyer, smetoyer1@islander.tamucc.edu

Abstract

Short-range infrared (IR) observations of ocean surface reveal complicated spatially varying and evolving structures. Here we present an approach to use spatially correlated time series IR images, over a time scale of one-tenth of a second, of the water surface to derive underlying surface velocity and turbulence fields. The approach here was tested in a laboratory using grid-generated turbulence and a heater assembly. The technique was compared with in situ measurements to validate our IR-derived remote measurements. The IR-measured turbulent kinetic energy (TKE) dissipation rates were consistent with in situ–measured dissipation using a vertical microstructure profiler (VMP). We used measurements of the gradient of the velocity field to calculate TKE dissipation rates at the surface. Based on theoretical and experimental considerations, we have proposed two models of IR TKE dissipation rate retrievals and designed an approach for oceanic field IR applications.

© 2021 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: Shelby Metoyer, smetoyer1@islander.tamucc.edu
Save
  • Babanin, A. V., and B. K. Haus, 2009: On the existence of water turbulence induced by nonbreaking surface waves. J. Phys. Oceanogr., 39, 26752679, https://doi.org/10.1175/2009JPO4202.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Birnir, B., 2013: The Kolmogorov-Obukhov-She-Leveque scaling in turbulence. University of California, Santa Barbara, Doc., 31 pp., https://escholarship.org/uc/item/5946z2wf.

  • Chickadel, C. C., S. A. Talke, A. R. Horner-Devine, and A. T. Jessup, 2011: Infrared-based measurements of velocity, turbulent kinetic energy, and dissipation at the water surface in a tidal river. IEEE Geosci. Remote Sens. Lett., 8, 849853, https://doi.org/10.1109/LGRS.2011.2125942.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • FLIR, 2010: The ultimate infrared handbook for R&D professionals. FLIR Systems Doc., 44 pp.

  • Garbe, C. S., H. Spies, and B. Jaehne, 2003: Estimation of complex motion from thermographic image sequences. J. Math. Imaging Vision, 19, 159174, https://doi.org/10.1023/A:1026233919766.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hart, D. P., 1998: The elimination of correlation errors in PIV processing. Ninth Int. Symp. on Applications of Laser Techniques to Fluid Mechanics, Lisbon, Portugal, Instituto Superior Técnico, 13–16.

  • Herlina, H., and J. Wissink, 2019: Simulation of air–water interfacial mass transfer driven by high-intensity isotropic turbulence. J. Fluid Mech., 860, 419440, https://doi.org/10.1017/jfm.2018.884.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jessup, A., and K. Phadnis, 2005: Measurement of the geometric and kinematic properties of microscale breaking waves from infrared imagery using a PIV algorithm. Meas. Sci. Technol., 16, 19611969, https://doi.org/10.1088/0957-0233/16/10/011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kitaigorodskii, S., M. Donelan, J. Lumley, and E. Terray, 1983: Wave–turbulence interactions in the upper ocean. Part II. Statistical characteristics of wave and turbulent components of the random velocity field in the marine surface layer. J. Phys. Oceanogr., 13, 19881999, https://doi.org/10.1175/1520-0485(1983)013<1988:WTIITU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kolmogorov, A. N., 1962: A refinement of previous hypotheses concerning the local structure of turbulence in a viscous incompressible fluid at high Reynolds number. J. Fluid Mech., 13, 8285, https://doi.org/10.1017/S0022112062000518.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lozovatsky, I., H. Fernando, J. Planella-Morato, Z. Liu, J.-H. Lee, and S. Jinadasa, 2017: Probability distribution of turbulent kinetic energy dissipation rate in ocean: Observations and approximations. J. Geophys. Res. Oceans, 122, 82938308, https://doi.org/10.1002/2017JC013076.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lueck, R. G., F. Wolk, and H. Yamazaki, 2002: Oceanic velocity microstructure measurements in the 20th century. J. Oceanogr., 58, 153174, https://doi.org/10.1023/A:1015837020019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oakey, N., 1985: Statistics of mixing parameters in the upper ocean during JASIN phase 2. J. Phys. Oceanogr., 15, 16621675, https://doi.org/10.1175/1520-0485(1985)015<1662:SOMPIT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Okamoto, T., M. Sanjou, and I. Nezu, 2016: Relationship between surface velocity divergence and turbulence microscale in open-channel flows with submerged strip roughness. IOP Conf. Ser. Earth Environ. Sci., 35, 012015, https://doi.org/10.1088/1755-1315/35/1/012015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, P. M., 1967: The temperature at the ocean-air interface. J. Atmos. Sci., 24, 269273, https://doi.org/10.1175/1520-0469(1967)024<0269:TTATOA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siddiqui, M. K., M. R. Loewen, C. Richardson, W. E. Asher, and A. T. Jessup, 2001: Simultaneous particle image velocimetry and infrared imagery of microscale breaking waves. Phys. Fluids, 13, 18911903, https://doi.org/10.1063/1.1375144.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thielicke, W., and E. Stamhuis, 2014: PIVlab—Towards user-friendly, affordable and accurate digital particle image velocimetry in MATLAB. J. Open Res. Software, 2, e30, https://doi.org/10.5334/jors.bl.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turney, D. E., and S. Banerjee, 2013: Air–water gas transfer and near-surface motions. J. Fluid Mech., 733, 588624, https://doi.org/10.1017/jfm.2013.435.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Veron, F., W. K. Melville, and L. Lenain, 2008: Infrared techniques for measuring ocean surface processes. J. Atmos. Oceanic Technol., 25, 307326, https://doi.org/10.1175/2007JTECHO524.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wieliczka, D. M., S. Weng, and M. R. Querry, 1989: Wedge shaped cell for highly absorbent liquids: Infrared optical constants of water. Appl. Opt., 28, 17141719, https://doi.org/10.1364/AO.28.001714.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woods, S. F., 2010: Optical depolarization from turbulent convective flow: A laboratory study. Ph.D. dissertation, University of Miami, 104 pp.

  • Xue, Z., J. J. Charonko, and P. P. Vlachos, 2014: Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification. Meas. Sci. Tech., 25, 115301, https://doi.org/10.1088/0957-0233/25/11/115301.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 300 0 0
Full Text Views 501 205 10
PDF Downloads 290 108 7