Results 91 to 100 of about 2,579 (215)

Preconditioning of Polynya Formation by Ocean Mixing at Maud Rise, Antarctica

Journal of Geophysical Research: Oceans, Volume 131, Issue 8, August 2026.
Abstract Antarctic open‐ocean polynyas trigger vigorous wintertime convection, influencing ocean circulation and atmospheric processes. In the Weddell Sea, interaction between the Weddell Gyre and the Maud Rise seamount generates a Taylor column that favors polynya formation.
Xingchi Wang, Alberto C. Naveira Garabato, Bieito Fernández Castro, Xin Wang, Sebastiaan Swart, Marcel Du Plessis, Aditya Narayanan, Alessandro Silvano, Louis Clément, Margaret Ruth Lindeman   +9 more
wiley   +1 more source

Ageostrophic Velocities of Curved Ocean Fronts

Journal of Geophysical Research: Oceans, Volume 131, Issue 8, August 2026.
Abstract Ageostrophic velocities at ocean fronts play a key role in ventilating the upper ocean. The overturning circulation driven by cross‐front ageostrophic flow is widely recognized as the major mechanism of vertical transport, but the role of along‐front ageostrophic velocities remains underrepresented in existing theory.
Weiguang Wu
wiley   +1 more source

Seasonal and Interannual Variability of Antarctic Bottom Water Downstream of the Four Key Formation Regions

Journal of Geophysical Research: Oceans, Volume 131, Issue 8, August 2026.
Abstract Antarctic Bottom Water (AABW) is a cold, dense water mass formed around Antarctica that ventilates the global abyssal ocean. Recent studies have reported widespread warming, freshening, and thinning of AABW, yet its temporal variability remains poorly constrained because of sparse observations.
Polina Sholeninova, Adele K. Morrison, Annie Foppert, Andrew McC. Hogg   +3 more
wiley   +1 more source

OceanForecastBench: A Benchmark Data Set for Data‐Driven Global Ocean Forecasting

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Global ocean forecasting aims to predict key ocean variables such as temperature, salinity, and currents, which is essential for understanding and describing oceanic phenomena. In recent years, data‐driven deep learning‐based ocean forecast models, such as XiHe, WenHai, LangYa and AI‐GOMS, have demonstrated significant potential in capturing ...
Yi Han, Haoming Jia, Xiang Wang, Huizan Wang, Wei Wu, Jianming Zheng, Peikun Xiao   +6 more
wiley   +1 more source

MAUSAM: An Observations‐Focused Assessment of Global AI Weather Prediction Models During the South Asian Monsoon

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Past evaluation of artificial intelligence (AI) weather prediction has primarily relied on reanalyses, which can obscure important deficiencies due to prevailing biases in reanalyses themselves. Here, we present MAUSAM (Measuring AI Uncertainty during South Asian Monsoon), an evaluation of seven leading AI‐based prediction systems—FourCastNet,
Aman Gupta, Aditi Sheshadri, Dhruv Suri
wiley   +1 more source

Data Driven Reconstruction of Upper Ocean Profiles for Improved State Estimation in the Philippine Sea

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Despite significant advances in observational systems such as the global Argo array of autonomous profiling floats, the spatiotemporal coverage of subsurface ocean observations remains limited compared to the dense data provided by satellite platforms. This study develops a data‐driven framework to reconstruct synthetic profiles of upper ocean
Guangpeng Liu, Brian Powell
wiley   +1 more source

Taming the Heterogeneous Dynamics of Oceanic Chlorophyll‐a Concentration With a Novel Deep Learning Model to Improve Prediction

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Chlorophyll‐a (Chl_a) concentration in the ocean is a critical indicator of primary production and plays a pivotal role in the global carbon cycle. Its accurate predictions are essential for reliable projections of future climate change. However, Chl_a is controlled by myriads of interactive physical and biogeochemical processes, posing a ...
Fa Zhang, Hiusuet Kung, Fan Zhang, Zhiwei Wang, Can Yang, Jianping Gan   +5 more
wiley   +1 more source

Data‐Driven Emulation of Numerically Simulated Baltic Sea Surface Currents With a Deep Convolutional U‐Net: Explainability and Potential Forecast Skill

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Ocean models can represent surface circulation at kilometer scales, but their computational cost limits broad experimentation. We present DeepCUN, a deep convolutional encoder–decoder (U‐Net) that emulates daily mean Baltic Sea surface current components on a 1‐nautical‐mile grid.
Amirhossein Barzandeh, Christoph Manss, Frederic Stahl, Ilja Maljutenko, Sander Rikka, Urmas Raudsepp   +5 more
wiley   +1 more source

Vertical Structure and Energetic Constraints for a Backscatter Parameterization of Ocean Mesoscale Eddies

Journal of Advances in Modeling Earth Systems
Mesoscale eddies modulate the stratification, mixing, tracer transport, and dissipation pathways of oceanic flows over a wide range of spatiotemporal scales.
Elizabeth Yankovsky, Scott Bachman, K. Shafer Smith, Laure Zanna   +3 more
doaj   +1 more source

Latitude‐Dependent Sensitive Areas for Targeted Observations of Mesoscale Eddies Associated With Sea Surface Height Anomaly Forecasts

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract By employing the conditional nonlinear optimal perturbation approach within a two‐layer quasigeostrophic (QG) model, we investigate the sensitive areas for targeted observations of mesoscale eddies relevant to sea surface height anomaly (SSHA) forecasting and reveal their pronounced latitude dependence.
Lin Jiang, Wansuo Duan, Hui Wang
wiley   +1 more source