1072 / 2024-09-20 10:14:03
Lagrangian Versus Eulerian Spectral Estimates of Surface Kinetic Energy Over the Global Ocean
Lagrangian-Eulerian comparison,internal tide,near-inertial waves,kinetic energy,global ocean
Session 46 - Oceanic Mesoscale and Submesoscale Processes: Characteristics, Dynamics & Parameterizations
Abstract Accepted
In this study, we conducted a novel massive Lagrangian simulation experiment based on a global 1/48° tide-resolving numerical simulation of the ocean circulation. This first-time twin experiment enables a comparison between Eulerian (fixed-point) and Lagrangian (along-flow) estimates of kinetic energy (KE) across the global ocean, and the quantification of systematic differences between both types of estimations. This comparison represents an important step forward for the mapping of upper ocean high-frequency variability from Lagrangian observations of the Global Drifter Program. Eulerian KE rotary frequency spectra and band-integrated energy levels (e.g., tidal and near-inertial) serve as references and are compared to Lagrangian estimates. Our analysis reveals that, except for the near-inertial band, Lagrangian velocity spectra are systematically smoother, for example, with wider and lower spectral peaks compared to Eulerian counterparts. On average, Lagrangian KE levels derived from spectral band integrations tend to underestimate Eulerian KE levels at low-frequency and tidal bands, especially in regions with strong low-frequency KE. Better agreement between Lagrangian and Eulerian low-frequency and tidal KE levels is generally found in regions with weak low-frequency KE and/or convergent surface circulation, where Lagrangian particles tend to accumulate. Conversely, Lagrangian and Eulerian near-inertial spectra and energy levels are comparable. Our results demonstrate that Lagrangian estimates may provide a distorted view of low-frequency and tidal variance. To accurately map near-surface velocity climatology at these frequencies from drifter database, conversion methods accounting for the Lagrangian bias need to be developed.