2020
DOI: 10.5194/npg-2020-36
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Extracting statistically significant eddy signals from large Lagrangian datasets using wavelet ridge analysis, with application to the Gulf of Mexico

Abstract: 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 ass… Show more

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Cited by 3 publications
(2 citation statements)
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“…A further non-objective, single-particle diagnostics for LCS identification is the Lagrangian spin parameter [43], which relies on the calibration of an additional stochastic model for the velocity field. Yet another approach adapts the wavelet ridge analysis method of [7] to Lagrangian trajectory analysis [29,30]. While physically insightful, this technique is non-objective either, as it fits a time-varying ellipse model to identify signatures of coherent eddies based on the looping characteristics of trajectories.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…A further non-objective, single-particle diagnostics for LCS identification is the Lagrangian spin parameter [43], which relies on the calibration of an additional stochastic model for the velocity field. Yet another approach adapts the wavelet ridge analysis method of [7] to Lagrangian trajectory analysis [29,30]. While physically insightful, this technique is non-objective either, as it fits a time-varying ellipse model to identify signatures of coherent eddies based on the looping characteristics of trajectories.…”
Section: Introductionmentioning
confidence: 99%
“…Answering this question would enable, for instance, a mathematically justifiable and physically self-consistent extraction of Lagrangian jets, fronts and eddies from NOAA's Global Drifter Program, which comprises more than 20,000 trajectories [32]. Such an extraction should then lead to a systematic assessment of the performance of promising nonobjective trajectory-based methods, such as [30], in avoiding false positives and negatives in elliptic LCS detection.…”
Section: Introductionmentioning
confidence: 99%