A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations
Abstract Identifying internal waves in complex flow fields is a long‐standing problem in fluid dynamics, oceanography and atmospheric science, owing to the overlap of internal waves temporal and spatial scales with other flow regimes. Lagrangian filtering—that is, temporal filtering in a frame of re...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2021-10-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021MS002616 |
| _version_ | 1818407678944215040 |
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| author | Callum J. Shakespeare Angus H. Gibson Andrew McC. Hogg Scott D. Bachman Shane R. Keating Nick Velzeboer |
| author_facet | Callum J. Shakespeare Angus H. Gibson Andrew McC. Hogg Scott D. Bachman Shane R. Keating Nick Velzeboer |
| author_sort | Callum J. Shakespeare |
| collection | DOAJ |
| description | Abstract Identifying internal waves in complex flow fields is a long‐standing problem in fluid dynamics, oceanography and atmospheric science, owing to the overlap of internal waves temporal and spatial scales with other flow regimes. 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. |
| first_indexed | 2024-12-14T09:31:40Z |
| format | Article |
| id | doaj.art-9a8433d25e424dd08718c5c0cceb4d43 |
| institution | Directory Open Access Journal |
| issn | 1942-2466 |
| language | English |
| last_indexed | 2024-12-14T09:31:40Z |
| publishDate | 2021-10-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj.art-9a8433d25e424dd08718c5c0cceb4d432022-12-21T23:08:03ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662021-10-011310n/an/a10.1029/2021MS002616A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution SimulationsCallum J. Shakespeare0Angus H. Gibson1Andrew McC. Hogg2Scott D. Bachman3Shane R. Keating4Nick Velzeboer5Research School of Earth Sciences Australian National University Canberra ACT AustraliaResearch School of Earth Sciences Australian National University Canberra ACT AustraliaResearch School of Earth Sciences Australian National University Canberra ACT AustraliaNational Center for Atmospheric Research Boulder CO USASchool of Mathematics and Statistics University of New South Wales Sydney NSW AustraliaResearch School of Earth Sciences Australian National University Canberra ACT AustraliaAbstract Identifying internal waves in complex flow fields is a long‐standing problem in fluid dynamics, oceanography and atmospheric science, owing to the overlap of internal waves temporal and spatial scales with other flow regimes. 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.https://doi.org/10.1029/2021MS002616internal wavesmodelingfilteringbalanced flowLagrangianEulerian |
| spellingShingle | Callum J. Shakespeare Angus H. Gibson Andrew McC. Hogg Scott D. Bachman Shane R. Keating Nick Velzeboer A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations Journal of Advances in Modeling Earth Systems internal waves modeling filtering balanced flow Lagrangian Eulerian |
| title | A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations |
| title_full | A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations |
| title_fullStr | A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations |
| title_full_unstemmed | A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations |
| title_short | A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations |
| title_sort | new open source implementation of lagrangian filtering a method to identify internal waves in high resolution simulations |
| topic | internal waves modeling filtering balanced flow Lagrangian Eulerian |
| url | https://doi.org/10.1029/2021MS002616 |
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