Editorial Type:
Article
Article Type:
Research Article

On Characterizing Ocean Kinematics from Surface Drifters

Sebastian Essink aApplied Physics Laboratory, University of Washington, Seattle, Washington

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Verena Hormann bLagrangian Drifter Laboratory, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Luca R. Centurioni bLagrangian Drifter Laboratory, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Amala Mahadevan cWoods Hole Oceanographic Institution, Woods Hole, Massachusetts

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Online Publication:
11 Aug 2022
Print Publication:
01 Aug 2022
Collections:
Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics
DOI:
https://doi.org/10.1175/JTECH-D-21-0068.1
Page(s):
1183–1198
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Abstract

Horizontal kinematic properties, such as vorticity, divergence, and lateral strain rate, are estimated from drifter clusters using three approaches. At submesoscale horizontal length scales O(1–10) km, kinematic properties become as large as planetary vorticity f, but challenging to observe because they evolve on short time scales O(hours to days). By simulating surface drifters in a model flow field, we quantify the sources of uncertainty in the kinematic property calculations due to the deformation of cluster shape. Uncertainties arise primarily due to (i) violation of the linear estimation methods and (ii) aliasing of unresolved scales. Systematic uncertainties (iii) due to GPS errors, are secondary but can become as large as (i) and (ii) when aspect ratios are small. Ideal cluster parameters (number of drifters, length scale, and aspect ratio) are determined and error functions estimated empirically and theoretically. The most robust method—a two-dimensional, linear least squares fit—is applied to the first few days of a drifter dataset from the Bay of Bengal. Application of the length scale and aspect-ratio criteria minimizes errors (i) and (ii), and reduces the total number of clusters and so computational cost. The drifter-estimated kinematic properties map out a cyclonic mesoscale eddy with a surface, submesoscale fronts at its perimeter. Our analyses suggest methodological guidance for computing the two-dimensional kinematic properties in submesoscale flows, given the recently increasing quantity and quality of drifter observations, while also highlighting challenges and limitations.

Significance Statement

The purpose of this study is to provide insights and guidance for computing horizontal velocity gradients from clusters (i.e., three or more) of Lagrangian surface ocean drifters. The uncertainty in velocity gradient estimates depends strongly on the shape deformation of drifter clusters by the ocean currents. We propose criteria for drifter cluster length scales and aspect ratios to reduce uncertainties and develop ways of estimating the magnitude of the resulting errors. The findings are applied to a real ocean dataset from the Bay of Bengal.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sebastian Essink, sessink@uw.edu

Abstract

Horizontal kinematic properties, such as vorticity, divergence, and lateral strain rate, are estimated from drifter clusters using three approaches. At submesoscale horizontal length scales O(1–10) km, kinematic properties become as large as planetary vorticity f, but challenging to observe because they evolve on short time scales O(hours to days). By simulating surface drifters in a model flow field, we quantify the sources of uncertainty in the kinematic property calculations due to the deformation of cluster shape. Uncertainties arise primarily due to (i) violation of the linear estimation methods and (ii) aliasing of unresolved scales. Systematic uncertainties (iii) due to GPS errors, are secondary but can become as large as (i) and (ii) when aspect ratios are small. Ideal cluster parameters (number of drifters, length scale, and aspect ratio) are determined and error functions estimated empirically and theoretically. The most robust method—a two-dimensional, linear least squares fit—is applied to the first few days of a drifter dataset from the Bay of Bengal. Application of the length scale and aspect-ratio criteria minimizes errors (i) and (ii), and reduces the total number of clusters and so computational cost. The drifter-estimated kinematic properties map out a cyclonic mesoscale eddy with a surface, submesoscale fronts at its perimeter. Our analyses suggest methodological guidance for computing the two-dimensional kinematic properties in submesoscale flows, given the recently increasing quantity and quality of drifter observations, while also highlighting challenges and limitations.

Significance Statement

The purpose of this study is to provide insights and guidance for computing horizontal velocity gradients from clusters (i.e., three or more) of Lagrangian surface ocean drifters. The uncertainty in velocity gradient estimates depends strongly on the shape deformation of drifter clusters by the ocean currents. We propose criteria for drifter cluster length scales and aspect ratios to reduce uncertainties and develop ways of estimating the magnitude of the resulting errors. The findings are applied to a real ocean dataset from the Bay of Bengal.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sebastian Essink, sessink@uw.edu
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