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View article: Growth Rate and Energy Dissipation in Wind‐Forced Breaking Waves
Growth Rate and Energy Dissipation in Wind‐Forced Breaking Waves Open
We investigate the energy growth and dissipation of wind‐forced breaking waves at high wind speed using direct numerical simulations of the coupled air–water Navier–Stokes equations. A turbulent wind boundary layer drives the growth of a p…
View article: Neural ocean forecasting from sparse satellite-derived observations: a case-study for SSH dynamics and altimetry data
Neural ocean forecasting from sparse satellite-derived observations: a case-study for SSH dynamics and altimetry data Open
We present an end-to-end deep learning framework for short-term forecasting of global sea surface dynamics based on sparse satellite altimetry data. Building on two state-of-the-art architectures: U-Net and 4DVarNet, originally developed f…
View article: A data-driven wind-to-current response function and application to ocean surface current estimates
A data-driven wind-to-current response function and application to ocean surface current estimates Open
This study investigates the reconstruction of wind-driven currents based on an empirical impulse response function. Surface current observations derived from drifting buoy data and wind-stress from the ERA5 reanalyses are used to derive th…
View article: Sentinel-1 wave mode SAR monitoring of icebergs around Antarctica
Sentinel-1 wave mode SAR monitoring of icebergs around Antarctica Open
The high-quality global wave mode synthetic aperture radar (SAR) vignettes routinely collected by Sentinel-1 is today extensively exploited for various oceanic and atmospheric phenomena. Yet, these observations still remain largely untappe…
View article: Distance Learning for Analog Methods (1st revision)
Distance Learning for Analog Methods (1st revision) Open
Analogs are similar states of a system, occurring at remote times within independent numerical simulations or previous observations. This concept has emerged in atmospheric sciences and was further used in ocean sciences for forecasting, d…
View article: WV-Net: A Foundation Model for SAR Ocean Satellite Imagery
WV-Net: A Foundation Model for SAR Ocean Satellite Imagery Open
The European Space Agency’s Sentinel-1 (S-1) satellite mission has captured more than 10 million images of the ocean surface using C-band synthetic aperture radar (SAR WV mode). While machine learning is a promising approach for detecting …
View article: Wind‐Driven Control of Shelf‐Sea CO<sub>2</sub> Sinks
Wind‐Driven Control of Shelf‐Sea CO<sub>2</sub> Sinks Open
Continental shelf surface waters are considered a variable but increasing sink of atmospheric carbon dioxide (CO 2 ), but the mechanisms controlling these increasing sinks are unclear. We identify that the winter wind‐driven surface atmosp…
View article: Enhanced Computational Complexity in Continuous-Depth Models: Neural Ordinary Differential Equations With Trainable Numerical Schemes
Enhanced Computational Complexity in Continuous-Depth Models: Neural Ordinary Differential Equations With Trainable Numerical Schemes Open
Neural Ordinary Differential Equations (NODEs) serve as continuous-time analogs of residual networks. They provide a system-theoretic perspective on neural network architecture design and offer natural solutions for time series modeling, f…
View article: A Particle‐in‐Cell Wave Model for Efficient Sea‐State Estimates in Earth System Models—PiCLES
A Particle‐in‐Cell Wave Model for Efficient Sea‐State Estimates in Earth System Models—PiCLES Open
Ocean surface waves have been demonstrated to be an important component of coupled Earth System Models (ESMs), influencing atmosphere‐ocean momentum transfer; ice floe breakage; CFC, carbon, and energy uptake; and mixed‐layer depth. Modest…
View article: Distance Learning for Analog Methods
Distance Learning for Analog Methods Open
Analogs are similar states of a system, occurring at remote times within independent numerical simulations or previous observations. This concept has emerged in atmospheric sciences and was further used in ocean sciences for forecasting, d…
View article: Turbulence and Energy Dissipation from Wave Breaking
Turbulence and Energy Dissipation from Wave Breaking Open
Wave breaking is a critical process in the upper ocean: an energy sink for the surface wave field and a source for turbulence in the ocean surface boundary layer. We apply a novel multilayer numerical solver resolving upper-ocean dynamics …
View article: Neural Variational Data Assimilation with Uncertainty Quantification Using SPDE Priors
Neural Variational Data Assimilation with Uncertainty Quantification Using SPDE Priors Open
The spatiotemporal interpolation of large geophysical datasets has historically been addressed by optimal interpolation (OI) and more sophisticated equation-based or data-driven data assimilation (DA) techniques. Recent advances in the dee…
View article: The Internal Waves Service Workshop: Observing Internal Waves Globally with Deep Learning and Synthetic Aperture Radar
The Internal Waves Service Workshop: Observing Internal Waves Globally with Deep Learning and Synthetic Aperture Radar Open
The Internal Waves Service Workshop What: This workshop gathered leading experts in satellite remote sensing, oceanography, and artificial intelligence to advance the development of the Internal Waves Service (IWS)-the first global, operat…
View article: A Generalized Stochastic Formulation of the Ekman–Stokes Model with Statistical Analyses
A Generalized Stochastic Formulation of the Ekman–Stokes Model with Statistical Analyses Open
To describe the upper-ocean Ekman boundary layer, a novel stochastic model is formulated to better capture the interplay between random components associated with the numerically unresolved physical process induced by wind, waves, and curr…
View article: Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation
Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation Open
Self-supervised learning (SSL) has enabled the development of vision foundation models for Earth Observation (EO), demonstrating strong transferability across diverse remote sensing tasks. While much research has focused on network archite…
View article: Disentangling density and geometry in weather regime dimensions using stochastic twins
Disentangling density and geometry in weather regime dimensions using stochastic twins Open
Large-scale atmospheric variability can be summarized by recurring patterns called weather regimes. Their properties, including predictability, have been studied using the local dimension, a geometrical estimate of degrees of freedom from …
View article: Momentum fluxes in wind-forced breaking waves
Momentum fluxes in wind-forced breaking waves Open
We investigate the momentum fluxes between a turbulent air boundary layer and a growing–breaking wave field by solving the air–water two-phase Navier–Stokes equations through direct numerical simulations. A fully developed turbulent airflo…
View article: A Stochastic Ekman-Stokes Model for Coupled Ocean-Wave-Atmosphere Dynamics
A Stochastic Ekman-Stokes Model for Coupled Ocean-Wave-Atmosphere Dynamics Open
Accurate representation of atmosphere-ocean boundary layers, including the interplay of turbulence, surface waves, and air-sea fluxes, remains a challenge in geophysical fluid dynamics, particularly for climate simulations. This study intr…
View article: Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation
Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation Open
Self-supervised learning (SSL) has enabled the development of vision foundation models for Earth Observation (EO), demonstrating strong transferability across diverse remote sensing tasks. While prior work has focused on network architectu…
View article: VarDyn: Dynamical Joint‐Reconstructions of Sea Surface Height and Temperature From Multi‐Sensor Satellite Observations
VarDyn: Dynamical Joint‐Reconstructions of Sea Surface Height and Temperature From Multi‐Sensor Satellite Observations Open
The VarDyn hybrid methodology, which combines minimal physically based constraints with a variational scheme, is demonstrated to enhance the mapping of sea surface height (SSH) and sea surface temperature (SST). By synthesizing multi‐modal…
View article: CFOSAT : A step forward for operational oceanography and better understanding of ocean waves climate
CFOSAT : A step forward for operational oceanography and better understanding of ocean waves climate Open
The CFOSAT (China-France Oceanography SATellite) satellite mission, a successful cooperation between China and France, launched in 28 October 2018 has revealed the importance of directional observations of waves and winds at the ocean surf…
View article: A data-driven wind-to-current response function and application to Ocean surface current estimates
A data-driven wind-to-current response function and application to Ocean surface current estimates Open
This study investigates modeling the wind-driven current using observed wind stress and an empirically estimated impulse response function for the wind-driven current response to wind forcing. Convolution of the data-driven impulse respons…
View article: OceanBench - Short-Term Global Ocean Forecasting
OceanBench - Short-Term Global Ocean Forecasting Open
The increasing adoption of AI-based approaches in Earth system sciences has led to breakthroughs in modeling and forecasting, exemplified by state-of-the-art performance of neural weather forecasting systems [Bi et al., 2023, Lam et al., 2…
View article: Internal Waves Observations from the Surface Water Ocean Topography Mission: Combined sea surface height and roughness measurements
Internal Waves Observations from the Surface Water Ocean Topography Mission: Combined sea surface height and roughness measurements Open
International audience
View article: Density-Induced Variations of Local Dimension Estimates for Absolutely Continuous Random Variables
Density-Induced Variations of Local Dimension Estimates for Absolutely Continuous Random Variables Open
For any multi-fractal dynamical system, a precise estimate of the local dimension is essential to infer variations in its number of degrees of freedom. Following extreme value theory, a local dimension may be estimated from the distributio…
View article: Disentangling Density and Geometry in Weather Regime Dimensions using Stochastic Twins
Disentangling Density and Geometry in Weather Regime Dimensions using Stochastic Twins Open
Large-scale atmospheric variability can be summarised using a small number of recurring patterns called \say{weather regimes}. The properties of weather regimes have been widely investigated in the literature, including through the \say{lo…