A new open source implementation of Lagrangian filtering: A method to identify internal waves in high-resolution simulations

Lagrangian filtering-that is, temporal filtering in a frame of reference moving with the flow-is one proposed methodology for performing this separation. Here we (a) describe an improved implementation of the Lagrangian filtering methodology and (b) introduce a new freely available, parallelized Python package that applies the method.

We show that the package can be used to directly filter output from a variety of common ocean models including MITgcm, Regional Ocean Modeling System and MOM5 for both regional and global domains at high resolution. The Lagrangian filtering is shown to be a useful tool to both identify (and thereby quantify) internal waves, and to remove internal waves to isolate the non-wave flow field.