Anisotropic statistics of Lagrangian structure functions and Helmholtz decomposition

Han Wang, Oliver Bühler

Research output: Contribution to journalArticlepeer-review


We present a new method to estimate second-order horizontal velocity structure functions, as well as their Helmholtz decomposition into rotational and divergent components, from sparse data collected along Lagrangian observations. The novelty compared to existing methods is that we allow for anisotropic statistics in the velocity field and also in the collection of the Lagrangian data. Specifically, we assume only stationarity and spatial homogeneity of the data and that the cross covariance between the rotational and divergent flow components is either zero or a function of the separation distance only. No further assumptions are made and the anisotropy of the underlying flow components can be arbitrarily strong. We demonstrate our new method by testing it against synthetic data and applying it to the Lagrangian Submesoscale Experiment (LASER) dataset. We also identify an improved statistical angle-weighting technique that generally increases the accuracy of structure function estimations in the presence of anisotropy.

Original languageEnglish (US)
Pages (from-to)1375-1393
Number of pages19
JournalJournal of Physical Oceanography
Issue number5
StatePublished - 2021


  • Data processing
  • Kinematics
  • Ocean dynamics
  • Sea/ocean surface
  • Statistics
  • Tracers
  • Trajectories

ASJC Scopus subject areas

  • Oceanography


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