Detecting and tracking eddies in oceanic flow fields: a Lagrangian descriptor based on the modulus of vorticity

Abstract. Since eddies play a major role in the dynamics of oceanic flows, it is of great interest to detect them and gain information about their tracks, their lifetimes and their shapes. We present a Lagrangian descriptor based on the modulus of vorticity to construct an eddy tracking tool. In our approach we denote an eddy as a rotating region in the flow possessing an eddy core corresponding to a local maximum of the Lagrangian descriptor and enclosed by pieces of manifolds of distinguished hyperbolic trajectories (eddy boundary). We test the performance of the eddy tracking tool based on this Lagrangian descriptor using an convection flow of four eddies, a synthetic vortex street and a velocity field of the western Baltic Sea. The results for eddy lifetime and eddy shape are compared to the results obtained with the Okubo–Weiss parameter, the modulus of vorticity and an eddy tracking tool used in oceanography. We show that the vorticity-based Lagrangian descriptor estimates lifetimes closer to the analytical results than any other method. Furthermore we demonstrate that eddy tracking based on this descriptor is robust with respect to certain types of noise, which makes it a suitable method for eddy detection in velocity fields obtained from observation.

[1]  U. Gräwe,et al.  Anatomizing one of the largest saltwater inflows into the Baltic Sea in December 2014 , 2015 .

[2]  Stephen Wiggins,et al.  Distinguished hyperbolic trajectories in time-dependent fluid flows: analytical and computational approach for velocity fields defined as data sets , 2002 .

[3]  Frits H. Post,et al.  Detection, quantification, and tracking of vortices using streamline geometry , 2000, Comput. Graph..

[4]  A M Mancho,et al.  Distinguished trajectories in time dependent vector fields. , 2008, Chaos.

[5]  Stephen Wiggins,et al.  Lagrangian and Eulerian analysis of transport and mixing in the three dimensional, time dependent Hill’s spherical vortex , 2015 .

[6]  Edward R. Abraham,et al.  The generation of plankton patchiness by turbulent stirring , 1998, Nature.

[7]  George Haller,et al.  Forecasting sudden changes in environmental pollution patterns , 2012, Proceedings of the National Academy of Sciences.

[8]  Sébastien Leprince,et al.  Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[9]  G. Haller,et al.  Coherent Lagrangian vortices: the black holes of turbulence , 2013, Journal of Fluid Mechanics.

[10]  B. Hamann,et al.  A three‐dimensional eddy census of a high‐resolution global ocean simulation , 2013 .

[11]  K. Ide,et al.  Routes of Transport across the Antarctic Polar Vortex in the Southern Spring , 2012 .

[12]  John R Mahoney,et al.  Invariant manifolds and the geometry of front propagation in fluid flows. , 2012, Chaos.

[13]  Ferran Marqués,et al.  Automatic satellite image georeferencing using a contour-matching approach , 2003, IEEE Trans. Geosci. Remote. Sens..

[14]  Carolina Mendoza,et al.  Hidden geometry of ocean flows. , 2010, Physical review letters.

[15]  G. Haller,et al.  Defining coherent vortices objectively from the vorticity , 2015, Journal of Fluid Mechanics.

[16]  David Bastine,et al.  Dominance patterns of competing phytoplankton groups in the wake of an island , 2010 .

[17]  Ana M. Mancho,et al.  Review Article: "The Lagrangian description of aperiodic flows: a case study of the Kuroshio Current" , 2010, 1006.3496.

[18]  A. Provenzale,et al.  Mesoscale vortices and the paradox of the plankton , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[19]  George Haller,et al.  LCS Tool: A computational platform for Lagrangian coherent structures , 2014, J. Comput. Sci..

[20]  Knut Klingbeil,et al.  Quantification of spurious dissipation and mixing – Discrete variance decay in a Finite-Volume framework , 2014 .

[21]  Igor Mezić,et al.  A New Mixing Diagnostic and Gulf Oil Spill Movement , 2010, Science.

[22]  Ulrike Feudel,et al.  Kinematic studies of transport across an island wake, with application to the Canary islands , 2006, nlin/0605051.

[23]  Annalisa Bracco,et al.  Patchy productivity in the open ocean , 2002 .

[24]  M. Rio,et al.  The turnstile mechanism across the Kuroshio current: analysis of dynamics in altimeter velocity fields , 2010, 1003.0377.

[25]  D. Chelton,et al.  Global observations of nonlinear mesoscale eddies , 2011 .

[26]  Vincent Rossi,et al.  The reduction of plankton biomass induced by mesoscale stirring: A modeling study in the Benguela upwelling , 2011, 1112.3760.

[27]  Gerik Scheuermann,et al.  Detection and Visualization of Closed Streamlines in Planar Flows , 2001, IEEE Trans. Vis. Comput. Graph..

[28]  Jerrold E. Marsden,et al.  Lagrangian coherent structures in the planar elliptic restricted three-body problem , 2009 .

[29]  C. Donlon,et al.  The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system , 2012 .

[30]  James C. McWilliams,et al.  Global heat and salt transports by eddy movement , 2014, Nature Communications.

[31]  Knut Klingbeil,et al.  Advantages of vertically adaptive coordinates in numerical models of stratified shelf seas , 2015 .

[32]  J. Weiss The dynamics of entropy transfer in two-dimensional hydrodynamics , 1991 .

[33]  John R Mahoney,et al.  Finite-time barriers to front propagation in two-dimensional fluid flows. , 2015, Chaos.

[34]  George Haller,et al.  Automated detection of coherent Lagrangian vortices in two-dimensional unsteady flows , 2014, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[35]  G. Haller,et al.  Lagrangian coherent structures and mixing in two-dimensional turbulence , 2000 .

[36]  E. Hernandez-Garcia,et al.  Plankton blooms in vortices: The role of biological and hydrodynamic time scales , 2007, 0802.3973.

[37]  Yuping Guan,et al.  Three‐dimensional oceanic eddy analysis in the Southern California Bight from a numerical product , 2012 .

[38]  Tommy D. Dickey,et al.  A Vector Geometry–Based Eddy Detection Algorithm and Its Application to a High-Resolution Numerical Model Product and High-Frequency Radar Surface Velocities in the Southern California Bight , 2010 .

[39]  Adrian P. Martin Phytoplankton patchiness: the role of lateral stirring and mixing , 2003 .

[40]  G. Haller Lagrangian Coherent Structures , 2015 .

[41]  Stephen Wiggins,et al.  The dynamical systems approach to lagrangian transport in oceanic flows , 2005 .

[42]  Assimilating 20 years of Atlantic XBT data into HYCOM: a first look , 2004 .

[43]  Stephen Wiggins,et al.  Lagrangian descriptors: A method for revealing phase space structures of general time dependent dynamical systems , 2011, Commun. Nonlinear Sci. Numer. Simul..

[44]  J. McWilliams,et al.  Circulation and multiple-scale variability in the Southern California Bight , 2009 .

[45]  Rosemary Morrow,et al.  Recent advances in observing mesoscale ocean dynamics with satellite altimetry , 2012 .

[46]  John O Dabiri,et al.  Lagrangian coherent structures in low Reynolds number swimming , 2009, Journal of physics. Condensed matter : an Institute of Physics journal.

[47]  Susana Nascimento,et al.  Automatic identification of oceanic eddies in infrared satellite images , 2011, Comput. Geosci..

[48]  Stephen Wiggins,et al.  Eulerian indicators for predicting and optimizing mixing quality , 2009 .

[49]  V. J. García-Garrido,et al.  A dynamical systems approach to the surface search for debris associated with the disappearance of flight MH370 , 2015, Nonlinear Processes in Geophysics.

[50]  Travis A. Smith,et al.  Ocean processes underlying surface clustering , 2016 .

[51]  A. Oschlies,et al.  An eddy‐permitting coupled physical‐biological model of the North Atlantic: 1. Sensitivity to advection numerics and mixed layer physics , 1999 .

[52]  F. d’Ovidio,et al.  Mixing structures in the Mediterranean Sea from finite‐size Lyapunov exponents , 2004, nlin/0404041.

[53]  A. Vulpiani,et al.  Dispersion of passive tracers in closed basins: Beyond the diffusion coefficient , 1997, chao-dyn/9701013.

[54]  Mark Kingsbury,et al.  Invariant barriers to reactive front propagation in fluid flows , 2011, 1108.1142.

[55]  V. Garçon,et al.  Comparative study of mixing and biological activity of the Benguela and Canary upwelling systems , 2008 .

[56]  Dependence of advection-diffusion-reaction on flow coherent structures , 2013 .

[57]  Alexis Chaigneau,et al.  Mesoscale eddies off Peru in altimeter records: Identification algorithms and eddy spatio-temporal patterns , 2008 .

[58]  G. Froyland,et al.  Almost-invariant sets and invariant manifolds — Connecting probabilistic and geometric descriptions of coherent structures in flows , 2009 .

[59]  Guido Boffetta,et al.  Detecting barriers to transport: a review of different techniques , 2001, nlin/0102022.

[60]  Vicente Pérez-Muñuzuri,et al.  The impact of advective transport by the South Indian Ocean Countercurrent on the Madagascar plankton bloom , 2012 .

[61]  Stephen Wiggins,et al.  A Lagrangian description of transport associated with a front–eddy interaction: Application to data from the North-Western Mediterranean Sea , 2011 .

[62]  S. Wiggins,et al.  Finite-Time Lagrangian Transport Analysis: Stable and Unstable Manifolds of Hyperbolic Trajectories and Finite-Time Lyapunov Exponents , 2009, 0908.1129.

[63]  Stephen Wiggins,et al.  A tutorial on dynamical systems concepts applied to Lagrangian transport in oceanic flows defined as finite time data sets: Theoretical and computational issues , 2006 .

[64]  Bernard Legras,et al.  Hyperbolic lines and the stratospheric polar vortex. , 2002, Chaos.

[65]  Qing Yang,et al.  Detection of vortices and saddle points in SST data , 2001 .

[66]  C. L'opez,et al.  Oceanic three-dimensional Lagrangian coherent structures: A study of a mesoscale eddy in the Benguela upwelling region , 2011, 1111.3792.

[67]  Stephen Wiggins,et al.  Barriers to transport in aperiodically time-dependent two-dimensional velocity fields: Nekhoroshev's theorem and "Nearly Invariant" tori , 2014 .

[68]  A. Ōkubo Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences , 1970 .

[69]  J. Richman,et al.  Analysis of ageostrophy in strong surface eddies in the Atlantic Ocean , 2015 .

[70]  M. Botur,et al.  Lagrangian coherent structures , 2009 .

[71]  E. Oran,et al.  Optimizing mixing in lid-driven flow designs through predictions from Eulerian indicators , 2011 .

[72]  A. Oschlies,et al.  An eddy‐permitting coupled physical‐biological model of the North Atlantic: 2. Ecosystem dynamics and comparison with satellite and JGOFS local studies data , 2000 .

[73]  Stephen Wiggins,et al.  Eulerian indicators under continuously varying conditions , 2012 .

[74]  Jordi Font,et al.  Vortices of the Mediterranean Sea: An Altimetric Perspective , 2006 .

[75]  E. Ziemniak,et al.  Application of scattering chaos to particle transport in a hydrodynamical flow. , 1993, Chaos.

[76]  Katja Fennel,et al.  The generation of phytoplankton patchiness by mesoscale current patterns , 2001 .