arXiv subjects

Shane Elipot

Publications and source records attributed to Shane Elipot.

5 recordsLinked to original sources

arXiv2026

Density and sea level changes weaken the Atlantic Meridional Overturning Circulation through ocean bottom pressure

Observations from the RAPID array at 26.5$^\circ$N indicate a linear decline in the Atlantic Meridional Overturning Circulation (AMOC) over the past two decades, linked to contrasting boundary changes: a weakening western-boundary contribution that is partly compensated by strengthening at the eastern boundary. Yet it remains unclear whether this partial compensation reflects a basin-wide adjustment or a regional feature, and what processes drive it. Here we use a high-resolution ocean model to investigate the spatial structure and underlying mechanisms of the AMOC change across the mid-latitude North Atlantic. The model reproduces a meridionally coherent decline in western-boundary deep overturning transport together with a partially compensating strengthening at the eastern boundary, consistent with observations at 26.5$^\circ$N. These opposing trends arise from a vertically coherent ocean bottom pressure trend shaped by two competing drivers: rising coastal sea level and decreasing interior density. Through geostrophic balance, this mechanism produces partial boundary compensation across latitudes, yielding a basin-wide AMOC decline throughout the mid-latitude North Atlantic.

physics.ao-ph↗

arXiv2026

Estimating the Kinetic Energy Spectrum from the Second-Order Velocity Structure Function using a Regularized Fitting Approach

Ocean turbulence plays a key role in shaping large-scale circulation, heat uptake, and biogeochemical processes. The kinetic energy (KE) wavenumber spectrum is a fundamental diagnostic, quantifying how KE is distributed across spatial scales. The second-order structure function -- computed from velocity differences between spatially separated observations -- provides a complementary measure, but unlike the KE spectrum, it reflects a non-local, weighted integral of KE over all scales. Analytic relationships link the two metrics, permitting forward and inverse transformations between them. However, recovering the KE spectrum from the structure function via the inverse relationship is highly sensitive to sampling limitations and numerical discretization errors. Here we propose a regularized approach in which the spectrum is assumed to consist of a finite number of segments with distinct slopes and amplitudes, and the inversion is formulated as an optimization problem. The approach is first validated in an idealized setting; for a number of idealized KE spectra with prescribed sets of spectral slopes and amplitudes, the corresponding structure functions are computed by numerically evaluating the forward relationship. These structure functions are then used to determine the underlying parameters using our proposed approach, which shows that we are able to perfectly recover the parameters and consequently the KE spectra. The method is further evaluated on high-resolution ocean model output, where it reconstructs the underlying spectra well even in the presence of noise. Finally, we apply the method to surface drifter observations (GLAD and LASER experiments). The results show that the framework enables estimation of the KE spectrum from sparse Lagrangian data, extending spectral diagnostics beyond gridded Eulerian measurements.

physics.ao-ph↗

arXiv2022

A Dataset of Hourly Sea Surface Temperature From Drifting Buoys

A dataset of sea surface temperature (SST) estimates is generated from the temperature observations of surface drifting buoys of NOAA's Global Drifter Program. Estimates of SST at regular hourly time steps along drifter trajectories are obtained by fitting to observations a mathematical model representing simultaneously SST diurnal variability with three harmonics of the daily frequency, and SST low-frequency variability with a first degree polynomial. Subsequent estimates of non-diurnal SST, diurnal SST anomalies, and total SST as their sum, are provided with their respective standard uncertainties. This Lagrangian SST dataset has been developed to match the existing hourly dataset of position and velocity from the Global Drifter Program.

physics.ao-ph↗

arXiv2022

Frequency dependence of near-surface oceanic kinetic energy from drifter observations and global high-resolution models

The geographical variability, frequency content, and vertical structure of near-surface oceanic kinetic energy (KE) are important for air-sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high-resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and 15 m, are respectively compared with KE from undrogued and drogued surface drifters. Global maps and zonal averages are computed for low-frequency ($<$ 0.5 cpd), near-inertial, diurnal, and semi-diurnal bands. Both models exhibit low-frequency equatorial KE that is low relative to drifter values. HYCOM near-inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semi-diurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is non-tidal. We compute a simple proxy of near-surface vertical structure, the ratio of 0 m KE to 0 m KE plus 15 m KE in model outputs, and undrogued KE to undrogued KE plus drogued KE in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low-frequency bands.

physics.ao-ph↗

arXiv2020

Measuring global mean sea level changes with surface drifting buoys

Combining ocean model data and in-situ Lagrangian data, I show that an array of surface drifting buoys tracked by a Global Navigation Satellite System (GNSS), such as the Global Drifter Program, could provide estimates of global mean sea level (GMSL) and its changes, including linear decadal trends. For a sustained array of 1250 globally distributed buoys with a standardized design, I demonstrate that GMSL decadal linear trend estimates with an uncertainty less than 0.3 mm yr$^{-1}$ could be achieved with GNSS daily random error of 1.6 m or less in the vertical direction. This demonstration assumes that controlled vertical position measurements could be acquired from drifting buoys, which is yet to be demonstrated. Development and implementation of such measurements could ultimately provide an independent and resilient observational system to infer natural and anthropogenic sea level changes, augmenting the on-going tide gauge and satellites records.

physics.ao-ph↗