31 Aug 2020

31 Aug 2020

Review status: a revised version of this preprint is currently under review for the journal NPG.

Extracting statistically significant eddy signals from large Lagrangian datasets using wavelet ridge analysis, with application to the Gulf of Mexico

Jonathan M. Lilly1 and Paula Perez-Brunius2 Jonathan M. Lilly and Paula Perez-Brunius
  • 1Theiss Research, La Jolla, California, USA
  • 2Departamento de Oceanografía, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Ensenada, Mexico

Abstract. A method for objectively extracting the displacement signals associated with coherent eddies from Lagrangian trajectories is presented, refined, and applied to a large dataset of 3761 surface drifters from the Gulf of Mexico. The method, wavelet ridge analysis, is modified to exclude the possibility of features changing from rotating in the cyclonic sense to rotating in the anticyclonic sense or vice-versa, transitions that would be physically unrealistic for a coherent eddy. A means for formally assessing statistical significance is introduced, addressing the issue of "false positives" arising by chance from an unstructured turbulent background, and opening the door to confident application of the method to very large datasets. Significance is measured in a two-dimensional parameter space by comparison with a stochastic dataset having statistical and spectral properties that match the original, but lacking organized oscillations due to eddies or waves. The application to the Gulf of Mexico reveals massive asymmetries between cyclones and anticyclones, with anticyclones dominating at radii larger than about 50 km, but an unexpectedly rich population of highly nonlinear cyclones dominating at smaller radii. Both the method and the Gulf of Mexico eddy dataset are made freely available to the community for use in future research.

Jonathan M. Lilly and Paula Perez-Brunius

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Status: final response (author comments only)
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Jonathan M. Lilly and Paula Perez-Brunius

Data sets

GulfDrifters: A consolidated surface drifter dataset for the Gulf of Mexico Jonathan M. Lilly and Paula Pérez-Brunius

The Gulf of Mexico Eddy Dataset (GOMED), a census of statistically significant eddy-like events from all available surface drifter data Jonathan M. Lilly and Paula Pérez-Brunius

Jonathan M. Lilly and Paula Perez-Brunius


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Short summary
Long-lived eddies are an important part of the ocean circulation. Here a dataset for studying eddies in the Gulf of Mexico is created through the analysis of trajectories of drifting instruments. The method involves the identification of quasi-periodic signals, characteristic of particles trapped in eddies, from the displacement records, followed by the creation of a measure of statistical significance. It is expected that this dataset will be of use to other authors studying this region.