Preprints
https://doi.org/10.5194/npg-2024-10
https://doi.org/10.5194/npg-2024-10
11 Apr 2024
 | 11 Apr 2024
Status: this preprint is currently under review for the journal NPG.

Inferring flow energy, space and time scales: freely-drifting vs fixed point observations

Aurelien Luigi Serge Ponte, Lachlan Astfalck, Matthew Rayson, Andrew Zulberti, and Nicole Jones

Abstract. A novel method for the inference of spatiotemporal decomposition of oceanic variability is presented and its performance assessed in a synthetic idealized configuration. The method is designed here to ingest velocity observation. The abilities of networks of reduced number of surface drifters and moorings at inferring spatiotemporal scales of ocean variability are quantified and contrasted. The sensitivities of inference performances for both types of platforms to the number of observation, geometrical configurations, flow regimes are presented. Because they simultaneously sample spatial and temporal variability, drifters are shown to be able to capture both spatial and temporal flow properties even when deployed in isolation. Moorings are particularly adequate for the characterization of the flow temporal variability, and may also capture spatial scales provided they are multiplied and the financial and environmental costs of associated deployments can be assumed. We show in particular that the method correctly identifies whether drifters are sampling preferentially spatial vs temporal variability. This method opens novel avenues for the analysis of existing datasets as well as the design of future experimental campaigns targeting the characterization of small scale (e.g. <100 km) Ocean variability.

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Aurelien Luigi Serge Ponte, Lachlan Astfalck, Matthew Rayson, Andrew Zulberti, and Nicole Jones

Status: open (until 07 Jun 2024)

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Aurelien Luigi Serge Ponte, Lachlan Astfalck, Matthew Rayson, Andrew Zulberti, and Nicole Jones
Aurelien Luigi Serge Ponte, Lachlan Astfalck, Matthew Rayson, Andrew Zulberti, and Nicole Jones

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Short summary
We propose a novel method for the estimation of ocean flow properties in terms of its energy, spatial and temporal scales. The method relies on flow observations that are either collected at a fixed location or along the flow as they would if inferred from the trajectory of freely-drifting platforms. The accuracy of the method is quantified in different experimental configurations. We demonstrate freely drifting platforms can, even in isolation, enable to capture flow properties is a first.