Lagrangian Geography of the Deep Gulf of Mexico

P. Miron Department of Atmospheric Sciences, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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F. J. Beron-Vera Department of Atmospheric Sciences, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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M. J. Olascoaga Department of Ocean Sciences, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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G. Froyland School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia

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P. Pérez-Brunius Departamento de Oceanografía Física, Centro de Investigación Científica y Educación Superior de Ensenada, Ensenada, Mexico

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J. Sheinbaum Departamento de Oceanografía Física, Centro de Investigación Científica y Educación Superior de Ensenada, Ensenada, Mexico

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Abstract

Using trajectories from acoustically tracked (RAFOS) floats in the Gulf of Mexico, we construct a geography of its Lagrangian circulation within the 1500–2500-m layer. This is done by building a Markov-chain representation of the Lagrangian dynamics. The geography is composed of weakly interacting provinces that constrain the connectivity at depth. The main geography includes two provinces of near-equal areas separated by a roughly meridional boundary. The residence time is about 4.5 (3.5) years in the western (eastern) province. The exchange between these provinces is effected through a slow cyclonic circulation, which is well constrained in the western basin by preservation of f/H, where f is the Coriolis parameter and H is depth. Secondary provinces of varied shapes covering smaller areas are identified with residence times ranging from about 0.4 to 1.2 years or so. Except for the main provinces, the deep Lagrangian geography does not resemble the surface Lagrangian geography recently inferred from satellite-tracked drifter trajectories. This implies disparate connectivity characteristics with potential implications for pollutant (e.g., oil) dispersal at the surface and at depth. Support for our results is provided by a Markov-chain analysis of satellite-tracked profiling (Argo) floats, which, while forming a smaller dataset and having seemingly different water-following characteristics than the RAFOS floats, replicate the main aspects of the Lagrangian geography. Our results find further validation in independent results from a chemical tracer release experiment.

© 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: P. Miron, pmiron@rsmas.miami.edu

Abstract

Using trajectories from acoustically tracked (RAFOS) floats in the Gulf of Mexico, we construct a geography of its Lagrangian circulation within the 1500–2500-m layer. This is done by building a Markov-chain representation of the Lagrangian dynamics. The geography is composed of weakly interacting provinces that constrain the connectivity at depth. The main geography includes two provinces of near-equal areas separated by a roughly meridional boundary. The residence time is about 4.5 (3.5) years in the western (eastern) province. The exchange between these provinces is effected through a slow cyclonic circulation, which is well constrained in the western basin by preservation of f/H, where f is the Coriolis parameter and H is depth. Secondary provinces of varied shapes covering smaller areas are identified with residence times ranging from about 0.4 to 1.2 years or so. Except for the main provinces, the deep Lagrangian geography does not resemble the surface Lagrangian geography recently inferred from satellite-tracked drifter trajectories. This implies disparate connectivity characteristics with potential implications for pollutant (e.g., oil) dispersal at the surface and at depth. Support for our results is provided by a Markov-chain analysis of satellite-tracked profiling (Argo) floats, which, while forming a smaller dataset and having seemingly different water-following characteristics than the RAFOS floats, replicate the main aspects of the Lagrangian geography. Our results find further validation in independent results from a chemical tracer release experiment.

© 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: P. Miron, pmiron@rsmas.miami.edu
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  • Beron-Vera, F. J., and J. H. LaCasce, 2016: Statistics of simulated and observed pair separations in the Gulf of Mexico. J. Phys. Oceanogr., 46, 21832199, https://doi.org/10.1175/JPO-D-15-0127.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bracco, A., J. Choi, K. Joshi, H. Luo, and J. C. McWilliams, 2016: Submesoscale currents in the northern Gulf of Mexico: Deep phenomena and dispersion over the continental slope. Ocean Modell., 101, 4358, https://doi.org/10.1016/j.ocemod.2016.03.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camilli, R., and Coauthors, 2010: Tracking hydrocarbon plume transport and biodegradation at Deepwater Horizon. Science, 330, 201204, https://doi.org/10.1126/science.1195223.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeHaan, C. J., and W. Sturges, 2005: Deep cyclonic circulation in the Gulf of Mexico. J. Phys. Oceanogr., 35, 18011812, https://doi.org/10.1175/JPO2790.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dellnitz, M., and O. Junge, 1999: On the approximation of complicated dynamical behavior. SIAM J. Numer. Anal., 36, 491515, https://doi.org/10.1137/S0036142996313002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dellnitz, M., G. Froyland, C. Horenkam, K. Padberg-Gehle, and A. Sen Gupta, 2009: Seasonal variability of the subpolar gyres in the southern ocean: A numerical investigation based on transfer operators. Nonlinear Processes Geophys., 16, 655663, https://doi.org/10.5194/npg-16-655-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Verdiere, A. C., 1979: Mean flow generation by topographic Rossby waves. J. Fluid Mech., 94, 3964, https://doi.org/10.1017/S0022112079000938.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donohue, K., D. Watts, P. Hamilton, R. Leben, and M. Kennelly, 2016: Loop current eddy formation and baroclinic instability. Dyn. Atmos. Oceans, 76, 195216, https://doi.org/10.1016/j.dynatmoce.2016.01.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froyland, G., 1997: Computer-assisted bounds for the rate of decay of correlations. Commun. Math. Phys., 189, 237257, https://doi.org/10.1007/s002200050198.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froyland, G., 2005: Statistically optimal almost-invariant sets. Physica D, 200, 205219, https://doi.org/10.1016/j.physd.2004.11.008.

  • Froyland, G., 2013: An analytic framework for identifying finite-time coherent sets in time-dependent dynamical systems. Physica D, 250, 119, https://doi.org/10.1016/j.physd.2013.01.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froyland, G., K. Padberg, M. H. England, and A. M. Treguier, 2007: Detection of coherent oceanic structures via transfer operators. Phys. Rev. Lett., 98, 224503, https://doi.org/10.1103/PhysRevLett.98.224503.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froyland, G., C. González-Tokman, and A. Quas, 2014a: Detecting isolated spectrum of transfer and Koopman operators with Fourier analytic tools. J. Comput. Dyn., 1, 249278, https://doi.org/10.3934/jcd.2014.1.249.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froyland, G., R. M. Stuart, and E. van Sebille, 2014b: How well-connected is the surface of the global ocean? Chaos, 24, 033126, https://doi.org/10.1063/1.4892530.

    • Crossref
    • Export Citation
  • Gill, A. E., 1982: Atmosphere-Ocean Dynamics. Academic Press, 662 pp.

  • Hamilton, P., A. Bower, H. Furey, R. Leben, and P. Pérez-Brunius, 2016: Deep circulation in the Gulf of Mexico: A Lagrangian study. OCS Study BOEM 2016-081 Tech. Rep., Bureau of Ocean Energy Management, 289 pp.

  • Hamilton, P., R. Leben, A. Bower, H. Furey, and P. Pérez-Brunius, 2018: Hydrography of the Gulf of Mexico using autonomous floats. J. Phys. Oceanogr., 48, 773794, https://doi.org/10.1175/JPO-D-17-0205.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Horn, R. A., and C. R. Johnson, 1990: Matrix Analysis. Cambridge University Press, 561 pp.

  • Hsu, C. S., 1987: Cell-to-Cell Mapping: A Method of Global Analysis for Nonlinear Systems. Applied Mathematical Sciences, Vol. 64, Springer, 354 pp.

  • Hurlburt, H. E., and J. D. Thompson, 1980: A numerical study of Loop Current intrusions and eddy shedding. J. Phys. Oceanogr., 10, 16111651, https://doi.org/10.1175/1520-0485(1980)010<1611:ANSOLC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kaufman, L., and P. J. Rousseeuw, 1990: Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, 342 pp.

    • Crossref
    • Export Citation
  • Khatiwala, S., M. Visbeck, and M. A. Cane, 2005: Accelerated simulation of passive tracers in ocean circulation models. Ocean Modell., 9, 5169, https://doi.org/10.1016/j.ocemod.2004.04.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koltai, P., 2011: A stochastic approach for computing the domain of attraction without trajectory simulation. Proc. Eighth AIMS Int. Conf., Dresden, Germany, American Institute of Mathematical Sciences, 854–863, https://doi.org/10.3934/proc.2011.2011.854.

    • Crossref
    • Export Citation
  • LaCasce, J. H., 2008: Statistics from Lagrangian observations. Prog. Oceanogr., 77, 129, https://doi.org/10.1016/j.pocean.2008.02.002.

  • Lasota, A., and M. C. Mackey, 1994: Chaos, Fractals, and Noise: Stochastic Aspects of Dynamics. 2nd ed. Applied Mathematical Sciences, Vol. 97, Springer, 474 pp.

    • Crossref
    • Export Citation
  • Ledwell, J. R., R. He, Z. Xue, S. F. DiMarco, L. J. Spencer, and P. Chapman, 2016: Dispersion of a tracer in the deep Gulf of Mexico. J. Geophys. Res. Oceans, 121, 11101132, https://doi.org/10.1002/2015JC011405.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lehoucq, R. B., D. C. Sorensen, and C. Yang, 1998: ARPACK Users’ Guide: Solution of Large-Scale Eigenvalue Problems by Implicitly Restarted Arnoldi Methods. Society for Industrial and Applied Mathematics, 160 pp.

    • Crossref
    • Export Citation
  • Lubchenco, J., M. K. McNutt, G. Dreyfus, S. A. Murawski, D. M. Kennedy, P. T. Anastas, S. Chu, and T. Hunter, 2012: Science in support of the Deepwater Horizon response. Proc. Natl. Acad. Sci. USA, 109, 20 21221 221, https://doi.org/10.1073/pnas.1204729109.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lumpkin, R., and M. Pazos, 2007: Measuring surface currents with Surface Velocity Program drifters: The instrument, its data and some recent results. Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics, A. Griffa et al., Eds., Cambridge University Press, 39–67, https://doi.org/10.1017/CBO9780511535901.003.

    • Crossref
    • Export Citation
  • Maximenko, A. N., J. Hafner, and P. Niiler, 2012: Pathways of marine debris derived from trajectories of Lagrangian drifters. Mar. Pollut. Bull., 65, 5162, https://doi.org/10.1016/j.marpolbul.2011.04.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McAdam, R., and E. van Sebille, 2018: Surface connectivity and interocean exchanges from drifter-based transition matrices. J. Geophys. Res. Oceans, 123, 514532, https://doi.org/10.1002/2017JC013363.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miron, P., F. J. Beron-Vera, M. J. Olascoaga, J. Sheinbaum, P. Pérez-Brunius, and G. Froyland, 2017: Lagrangian dynamical geography of the Gulf of Mexico. Sci. Rep., 7, 7021, https://doi.org/10.1038/s41598-017-07177-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mizuta, G., and N. G. Hogg, 2004: Structure of the circulation induced by a shoaling topographic wave. J. Phys. Oceanogr., 34, 17931810, https://doi.org/10.1175/1520-0485(2004)034<1793:SOTCIB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Norris, J., 1998: Markov Chains. Cambridge University Press, 254 pp., https://doi.org/10.1017/CBO9780511810633.

    • Crossref
    • Export Citation
  • Novelli, G., C. Guigand, C. Cousin, E. H. Ryan, N. J. Laxague, H. Dai, B. K. Haus, and T. M. Özgökmen, 2017: A biodegradable surface drifter for ocean sampling on a massive scale. J. Atmos. Oceanic Technol., 34, 25092532, https://doi.org/10.1175/JTECH-D-17-0055.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nowlin, W., A. E. Jochens, S. F. DiMarco, R. O. Reid, and M. K. Howard, 2001: Deepwater physical oceanography reanalysis and synthesis of historical data: Synthesis report. OCS Study MMS 2001-064, Minerals Management Service, 528 pp., https://www.boem.gov/ESPIS/3/3129.pdf.

  • Oey, L.-Y., and H.-C. Lee, 2002: Deep eddy energy and topographic Rossby waves in the Gulf of Mexico. J. Phys. Oceanogr., 32, 34993527, https://doi.org/10.1175/1520-0485(2002)032<3499:DEEATR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ohlmann, J. C., and P. P. Niiler, 2005: A two-dimensional response to a tropical storm on the Gulf of Mexico shelf. J. Mar. Syst., 29, 8799, https://doi.org/10.1016/S0924-7963(01)00011-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Okubo, A., 1971: Oceanic diffusion diagrams. Deep-Sea Res. Oceanogr. Abstr., 18, 789802, https://doi.org/10.1016/0011-7471(71)90046-5.

  • Olascoaga, M. J., and G. Haller, 2012: Forecasting sudden changes in environmental pollution patterns. Proc. Natl. Acad. Sci. USA, 109, 47384743, https://doi.org/10.1073/pnas.1118574109.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Olascoaga, M. J., and Coauthors, 2013: Drifter motion in the Gulf of Mexico constrained by altimetric Lagrangian Coherent Structures. Geophys. Res. Lett., 40, 61716175, https://doi.org/10.1002/2013GL058624.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Orszag, S. A., 1977: Lectures on the statistical theory of turbulence. Fluid Dynamics, R. Balian and J.-L. Peube, Eds., Gordon and Breach, 235–374.

  • Pérez-Brunius, P., H. Furey, A. Bower, P. Hamilton, J. Candela, P. García-Carrillo, and R. Leben, 2018: Dominant circulation patterns of the deep Gulf of Mexico. J. Phys. Oceanogr., 48, 511529, https://doi.org/10.1175/JPO-D-17-0140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pikovsky, A., and O. Popovych, 2003: Persistent patterns in deterministic mixing flows. Europhys. Lett., 61, 625631, https://doi.org/10.1209/epl/i2003-00117-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poje, A. C., and Coauthors, 2014: The nature of surface dispersion near the Deepwater Horizon oil spill. Proc. Natl. Acad. Sci. USA, 111, 12 69312 698, https://doi.org/10.1073/pnas.1402452111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rivas, D., A. Badan, and J. Ochoa, 2005: The ventilation of the deep Gulf of Mexico. J. Phys. Oceanogr., 35, 17631781, https://doi.org/10.1175/JPO2786.1.

    • 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
  • Rossby, T., D. Dorson, and J. Fontaine, 1986: The RAFOS system. J. Atmos. Oceanic Technol., 3, 672679, https://doi.org/10.1175/1520-0426(1986)003<0672:TRS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rossi, V., E. Ser-Giacomi, C. Lopez, and E. Hernandez-Garcia, 2014: Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves. Geophys. Res. Lett., 41, 28832891, https://doi.org/10.1002/2014GL059540.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rousseeuw, P. J., 1987: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math., 20, 5365, https://doi.org/10.1016/0377-0427(87)90125-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ser-Giacomi, E., V. Rossi, C. Lopez, and E. Hernandez-Garcia, 2015: Flow networks: A characterization of geophysical fluid transport. Chaos, 25, 036404, https://doi.org/10.1063/1.4908231.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheinbaum, J., J. Candela, A. Badan, and J. Ochoa, 2002: Flow structure and transport in the Yucatan Channel. Geophys. Res. Lett., 29, 1040, https://doi.org/10.1029/2001GL013990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheinbaum, J., G. Athié, J. Candela, J. Ochoa, and A. Romero-Arteaga, 2016: Structure and variability of the Yucatan and loop currents along the slope and shelf break of the Yucatan channel and Campeche bank. Dyn. Atmos. Oceans, 76, 217239, https://doi.org/10.1016/j.dynatmoce.2016.08.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sturges, W., and A. Lugo-Fernandez, 2005: Circulation in the Gulf of Mexico: Observations and Models. Geophys. Monogr., Vol. 161, Amer. Geophys. Union, 347 pp., https://doi.org/10.1029/GM161.

    • Crossref
    • Export Citation
  • Sturges, W., P. P. Niiler, and R. H. Weisberg, 2001: Northeastern Gulf of Mexico inner shelf circulation study. OCS Rep. MMS 2011-103, Minerals Management Service, 69 pp., https://www.boem.gov/ESPIS/3/3216.pdf.

  • Tarjan, R., 1972: Depth-first search and linear graph algorithms. SIAM J. Comput., 1, 146160, https://doi.org/10.1137/0201010.

  • Tenreiro, M., J. Candela, E. P. Sanz, J. Sheinbaum, and J. Ochoa, 2018: Near-surface and deep circulation coupling in the western Gulf of Mexico. J. Phys. Oceanogr., 48, 145161, https://doi.org/10.1175/JPO-D-17-0018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ulam, S., 1960: A Collection of Mathematical Problems. Interscience Tracts in Pure and Applied Mathematics, No. 8, Interscience, 150 pp.

  • van Sebille, E., E. H. England, and G. Froyland, 2012: Origin, dynamics and evolution of ocean garbage patches from observed surface drifters. Environ. Res. Lett., 7, 044040, https://doi.org/10.1088/1748-9326/7/4/044040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vardner, J., and B. Loose, 2016: Molecular diffusion of CF3SF5 in pure water and artificial seawater. Mar. Chem., 180, 5156, https://doi.org/10.1016/j.marchem.2016.01.005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weatherly, G. L., N. Wienders, and A. Romanou, 2005: Intermediate-depth circulation in the Gulf of Mexico estimated from direct measurements. Circulation in the Gulf of Mexico: Observations and Models, Geophys. Monogr., Vol. 161, Amer. Geophys. Union, 315–324, https://doi.org/10.1029/161GM22.

    • Crossref
    • Export Citation
  • Zhurbas, V., and I. S. Oh, 2004: Drifter-derived maps of lateral diffusivity in the Pacific and Atlantic Oceans in relation to surface circulation patterns. J. Geophys. Res., 109, C05015, https://doi.org/10.1029/2003JC002241.

    • Crossref
    • Search Google Scholar
    • Export Citation
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