Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories
Drifters deployed in close proximity collectively provide a unique observational data set with which to separate mesoscale and submesoscale flows. In this paper we provide a principled approach for doing so by fitting observed velocities to a local Taylor expansion of the velocity flow field. We dem...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-12-01
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| Series: | Fluids |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2311-5521/6/1/14 |
| _version_ | 1827698771714113536 |
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| author | Sarah Oscroft Adam M. Sykulski Jeffrey J. Early |
| author_facet | Sarah Oscroft Adam M. Sykulski Jeffrey J. Early |
| author_sort | Sarah Oscroft |
| collection | DOAJ |
| description | Drifters deployed in close proximity collectively provide a unique observational data set with which to separate mesoscale and submesoscale flows. In this paper we provide a principled approach for doing so by fitting observed velocities to a local Taylor expansion of the velocity flow field. We demonstrate how to estimate mesoscale and submesoscale quantities that evolve slowly over time, as well as their associated statistical uncertainty. We show that in practice the mesoscale component of our model can explain much first and second-moment variability in drifter velocities, especially at low frequencies. This results in much lower and more meaningful measures of submesoscale diffusivity, which would otherwise be contaminated by unresolved mesoscale flow. We quantify these effects theoretically via computing Lagrangian frequency spectra, and demonstrate the usefulness of our methodology through simulations as well as with real observations from the LatMix deployment of drifters. The outcome of this method is a full Lagrangian decomposition of each drifter trajectory into three components that represent the background, mesoscale, and submesoscale flow. |
| first_indexed | 2024-03-10T13:36:51Z |
| format | Article |
| id | doaj.art-7cfc78d18267495e954d9fe347936404 |
| institution | Directory Open Access Journal |
| issn | 2311-5521 |
| language | English |
| last_indexed | 2024-03-10T13:36:51Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fluids |
| spelling | doaj.art-7cfc78d18267495e954d9fe3479364042023-11-21T07:27:58ZengMDPI AGFluids2311-55212020-12-01611410.3390/fluids6010014Separating Mesoscale and Submesoscale Flows from Clustered Drifter TrajectoriesSarah Oscroft0Adam M. Sykulski1Jeffrey J. Early2STOR-i Centre for Doctoral Training, Lancaster University, Lancaster LA1 4YW, UKDepartment of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YW, UKNorthWest Research Associates, Redmond, WA 98052, USADrifters deployed in close proximity collectively provide a unique observational data set with which to separate mesoscale and submesoscale flows. In this paper we provide a principled approach for doing so by fitting observed velocities to a local Taylor expansion of the velocity flow field. We demonstrate how to estimate mesoscale and submesoscale quantities that evolve slowly over time, as well as their associated statistical uncertainty. We show that in practice the mesoscale component of our model can explain much first and second-moment variability in drifter velocities, especially at low frequencies. This results in much lower and more meaningful measures of submesoscale diffusivity, which would otherwise be contaminated by unresolved mesoscale flow. We quantify these effects theoretically via computing Lagrangian frequency spectra, and demonstrate the usefulness of our methodology through simulations as well as with real observations from the LatMix deployment of drifters. The outcome of this method is a full Lagrangian decomposition of each drifter trajectory into three components that represent the background, mesoscale, and submesoscale flow.https://www.mdpi.com/2311-5521/6/1/14driftersmesoscalesubmesoscalediffusivitystrainvorticity |
| spellingShingle | Sarah Oscroft Adam M. Sykulski Jeffrey J. Early Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories Fluids drifters mesoscale submesoscale diffusivity strain vorticity |
| title | Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories |
| title_full | Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories |
| title_fullStr | Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories |
| title_full_unstemmed | Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories |
| title_short | Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories |
| title_sort | separating mesoscale and submesoscale flows from clustered drifter trajectories |
| topic | drifters mesoscale submesoscale diffusivity strain vorticity |
| url | https://www.mdpi.com/2311-5521/6/1/14 |
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