Results 161 to 170 of about 14,618 (217)

Basal Force Probability Distributions in Thin‐Layer Granular Flows

open access: yesJournal of Geophysical Research: Earth Surface, Volume 131, Issue 8, August 2026.
Abstract Extreme geophysical flows, such as granular and debris flows, can significantly shape the landscape in steep lands and generate seismic signals that can be recorded over long distances. However, direct field measurements needed to constrain the granular physics remain difficult due to the damage potential of those flows.
Jun Fang   +5 more
wiley   +1 more source

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

open access: yesJournal 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   +6 more
wiley   +1 more source

Virtual Soil Simulator—Finite Volume Method Implementation for the Unsaturated Porous Media Water Transport Model Including Film Flow and Isothermal Vapor Transport Phenomena

open access: yesJournal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Modeling unsaturated water transport in porous media traditionally relies on the Richards equation (RE) with hydraulic conductivity formulations to consider only capillary liquid water flow. However, this simplification neglects thin water films adsorbed onto particle surfaces, which can contribute significantly to flow under medium to dry ...
M. Kozyra, K. Lamorski, C. Sławiński
wiley   +1 more source

Learning Vertical Coordinates via Automatic Differentiation of a Dynamical Core

open access: yesJournal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Terrain‐following coordinates in atmospheric models often imprint their grid structure onto the solution, particularly over steep topography, where distorted coordinate layers can generate spurious horizontal and vertical motion. Standard formulations, such as hybrid or SLEVE coordinates, mitigate these errors by using analytic decay functions
Tim Whittaker   +4 more
wiley   +1 more source

CESAR: A Convolutional Echo State AutoencodeR for High‐Resolution Wind Forecasting

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract An accurate and timely assessment of wind speed and energy output allows an efficient planning and management of this resource on the power grid. Wind energy, especially at high resolution, calls for the development of nonlinear statistical models able to capture complex dependencies in space and time. This work introduces a Convolutional Echo
Matthew Bonas   +3 more
wiley   +1 more source

A Hybrid ML‐PDE Framework for Predicting Breaking Ocean Waves

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Wave breaking plays a central role in ocean dynamics, dissipating wave energy and shaping the evolution of the sea surface. Yet, breaking remains difficult to model: envelope‐based models efficiently capture nonlinear wave evolution and are interpretable but exclude breaking, while high‐fidelity direct numerical simulations resolve breaking ...
Y. Liu   +3 more
wiley   +1 more source

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