Results 111 to 120 of about 20,887 (256)

Enhancing event stratigraphic correlations in the ultra‐deep Japan Trench using XRF‐CS cluster‐based chemostratigraphy

open access: yesThe Depositional Record, Volume 12, Issue 1, February 2026.
Cluster‐based chemostratigraphy using XRF‐CS enables high‐resolution correlation of event deposits across contrasting depositional settings in the Japan Trench. This approach reveals previously unrecognised events and compositional heterogeneity, offering new insights into sediment provenance and earthquake‐triggered deposition, with implications for ...
Jyh‐Jaan Steven Huang   +4 more
wiley   +1 more source

Tectono‐Magmatic Processes of the Western Parece Vela Basin: Insights Derived From Seismic Imaging and Gravity Modeling

open access: yesGeochemistry, Geophysics, Geosystems
The western Parece Vela Basin (PVB) contains three distinct geomorphological zones aligned with the seafloor spreading direction: the west abyssal hill zone, the central Chaotic Terrain zone, and the east abyssal hill zone.
Changliang Chen   +9 more
doaj   +1 more source

Differentiating hyperpycnal, hypopycnal and turbidity current deposits in late Quaternary glaciogenic mud

open access: yesThe Depositional Record, Volume 12, Issue 1, February 2026.
X‐ray CT and microscopic analysis of glaciogenic mud provide insight into the deposits of sediment‐laden density flows and reveal that strata comprise two microtextural motifs. The deposits of bottom‐hugging hyperpycnal flows and slope‐failure‐related turbidity currents are characterised by laterally continuous, sharply bounded silt‐rich and clay‐rich ...
Omar N. Al‐Mufti   +3 more
wiley   +1 more source

From Symmetric Rifting to Asymmetric Spreading—Insights Into Back‐Arc Formation in the Central Mariana Trough

open access: yesGeochemistry, Geophysics, Geosystems
The Mariana Trough is the youngest back‐arc basin in a series of basins and arcs that developed behind the Mariana subduction zone in the western Pacific.
H.‐S. Hilbert   +6 more
doaj   +1 more source

Taking machine learning with a grain of sand: Sediment Analysis Neural‐network Data‐engine (SAND‐e) reveals sedimentological differences between turbid and clear‐water reefs

open access: yesThe Depositional Record, Volume 12, Issue 1, February 2026.
Using machine learning, researchers can count and crudely identify sand grains from coral reefs automatically. This will allow us to generate larger datasets to answer sedimentological questions. Abstract Sediment is an important facet of sand cay reefs as it is responsible for reef accretion and island formation, with shifts in the proportions of ...
G. William M. Harrison   +5 more
wiley   +1 more source

Anthropogenically Stimulated Carbonate Dissolution in the Global Shelf Seafloor Is Potentially an Important and Fast Climate Feedback

open access: yesAGU Advances, Volume 7, Issue 1, February 2026.
Abstract Carbonate mineral production and dissolution regulate atmospheric carbon dioxide (CO2) concentrations via modulation of the ocean alkalinity content. The anthropogenic rise in atmospheric CO2 reduces calcification rates and enhances calcium carbonate dissolution, which increases ocean alkalinity, counteracts acidification, and stimulates ocean
Sebastiaan J. van de Velde   +4 more
wiley   +1 more source

Seafloor spreading modes across the Charlie Gibbs transform system (52°N, Mid Atlantic Ridge)

open access: gold, 2022
Alessio Sanfilippo   +4 more
openalex   +1 more source

Surfzone Water Depth Estimation From Surface Flows Using a Data‐Driven and Physics‐Informed Deep Conditional Generative Model

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract A physics‐informed deep conditional generative model driven with remotely sensed surface currents is shown to estimate surfzone water depths (bathymetry). The model encodes measured flow data as latent Gaussian parameters and decodes these distributions to estimate water depths over the domain, progressively refining its predictions via a loss‐
Reza Salatin   +2 more
wiley   +1 more source

Experimental Verification of a Two‐Dimensional Inverse Method for Turbidity Currents Using a Deep Neural Network

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Turbidites have been widely studied as indicators of the occurrences and magnitudes of paleo‐tsunamis and paleo‐earthquakes. Inversion to estimate flow conditions from turbidites offers valuable insights into the magnitudes of paleo‐seismic and tsunami events.
Seiya Fujishima, Hajime Naruse
wiley   +1 more source

Home - About - Disclaimer - Privacy