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 3770 surface drifters from the Gulf of Mexico. The method, wavelet ridge analysis, is a general method for the analysis of modulated oscillations, here modified to be more suitable to the eddy-detection problem. 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 through a frequency-dependent 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 major 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 noncommercial use in future research.

中文翻译：

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使用小波脊线分析从大型拉格朗日数据集中提取具有统计意义的涡流信号，并将其应用于墨西哥湾

提出，完善并客观地从拉格朗日轨迹中提取与相干涡相关的位移信号的方法，并将其应用于来自墨西哥湾的3770个表面漂移物的大型数据集。小波脊线分析法是一种分析调制振荡的通用方法，在此进行了修改，使其更适合于涡流检测问题。引入了一种正式评估统计显着性的方法，以解决由于非结构化湍流背景而偶然产生的误报问题，并为将方法可靠地应用到非常大的数据集打开了大门。显着性是通过与随机数据集进行频率相关的比较来测量的，该随机数据集的统计和频谱特性与原始数据，但由于涡流或波浪而缺乏有组织的振荡。在墨西哥湾的应用揭示了旋风分离器和反旋风分离器之间的主要不对称性，其中反旋风分离器在半径大于约50 km时占主导地位，但出乎意料的高度非线性旋风分离器却在较小的半径中占主导地位。该方法和墨西哥湾涡流数据集均可免费提供给社区，以用于未来研究中的非商业用途。