Ocean-E2E: Hybrid Physics-Based and Data-Driven Global Forecasting of Extreme Marine Heatwaves with End-to-End Neural Assimilation
Fuente:
arXiv
Saved in:
| Main Authors: | Shu, Ruiqi, Gao, Yuan, Wu, Hao, Gou, Ruijian, Wang, Kun, Xiang, Yanfei, Xu, Fan, Wen, Qingsong, Huang, Xiaomeng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improved Forecasts of Global Extreme Marine Heatwaves Through a Physics-guided Data-driven Approach
by: Shu, Ruiqi, et al.
Published: (2024)
by: Shu, Ruiqi, et al.
Published: (2024)
NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation
by: Gao, Yuan, et al.
Published: (2025)
by: Gao, Yuan, et al.
Published: (2025)
An End-to-End Differentiable, Graph Neural Network-Embedded Pore Network Model for Permeability Prediction
by: Zhao, Qingqi, et al.
Published: (2025)
by: Zhao, Qingqi, et al.
Published: (2025)
Towards End-to-End Earthquake Monitoring Using a Multitask Deep Learning Model
by: Zhu, Weiqiang, et al.
Published: (2025)
by: Zhu, Weiqiang, et al.
Published: (2025)
End-to-End Mineral Exploration with Artificial Intelligence and Ambient Noise Tomography
by: Muir, Jack, et al.
Published: (2024)
by: Muir, Jack, et al.
Published: (2024)
Model Training, Data Assimilation, and Forecast Experiments with a Hybrid Atmospheric Model that Incorporates Machine Learning
by: Elliott, Dylan, et al.
Published: (2025)
by: Elliott, Dylan, et al.
Published: (2025)
HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Spatial Downscaling
by: Shu, Ruiqi, et al.
Published: (2026)
by: Shu, Ruiqi, et al.
Published: (2026)
Constructing Extreme Heatwave Storylines with Differentiable Climate Models
by: Whittaker, Tim, et al.
Published: (2025)
by: Whittaker, Tim, et al.
Published: (2025)
Forecasting Return Time of Extreme Precipitation by Large Deviation Theory
by: Xie, Haotian, et al.
Published: (2026)
by: Xie, Haotian, et al.
Published: (2026)
Diffusion-Inversion-Net (DIN): An End-to-End Direct Probabilistic Framework for Characterizing Hydraulic Conductivities and Quantifying Uncertainty
by: Zhang, Xun, et al.
Published: (2025)
by: Zhang, Xun, et al.
Published: (2025)
Diffusion-Based Probabilistic Modeling for Hourly Streamflow Prediction and Assimilation
by: Yang, Wencong, et al.
Published: (2025)
by: Yang, Wencong, et al.
Published: (2025)
Global River Forecasting with a Topology-Informed AI Foundation Model
by: Ren, Hancheng, et al.
Published: (2026)
by: Ren, Hancheng, et al.
Published: (2026)
Simulation and Data Assimilation in an Idealized Coupled Atmosphere-Ocean-Sea Ice Floe Model with Cloud Effects
by: Mou, Changhong, et al.
Published: (2024)
by: Mou, Changhong, et al.
Published: (2024)
An novel finite difference dispersion error elimination mechanism in the Lax–Wendroff high‐order time discretization
by: Wenquan Liang, et al.
Published: (2024)
by: Wenquan Liang, et al.
Published: (2024)
Exploring Ultra Rapid Data Assimilation Based on Ensemble Transform Kalman Filter with the Lorenz 96 Model
by: Kawasaki, Fumitoshi, et al.
Published: (2025)
by: Kawasaki, Fumitoshi, et al.
Published: (2025)
Neural Earthquake Forecasting with Minimal Information: Limits, Interpretability, and the Role of Markov Structure
by: Koehler, Jonas, et al.
Published: (2025)
by: Koehler, Jonas, et al.
Published: (2025)
D-SHIFT: Transferring High Spatial Information from GRACE Monthly TWSA Mascon to Daily Products Using Generative Adversarial Networks
by: Dombos, Andreas, et al.
Published: (2026)
by: Dombos, Andreas, et al.
Published: (2026)
Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination
by: Agata, Ryoichiro, et al.
Published: (2024)
by: Agata, Ryoichiro, et al.
Published: (2024)
Probabilistic and Alarm-Based Evaluation of a b-Value-Driven Deep Learning Earthquake Forecast
by: Köhler, Jonas, et al.
Published: (2026)
by: Köhler, Jonas, et al.
Published: (2026)
Downscaling GRACE-derived ocean bottom pressure anomalies using self-supervised data fusion
by: Gou, Junyang, et al.
Published: (2024)
by: Gou, Junyang, et al.
Published: (2024)
Modeling Global Surface Dust Deposition Using Physics-Informed Neural Networks
by: Catricheo, Constanza A. Molina, et al.
Published: (2024)
by: Catricheo, Constanza A. Molina, et al.
Published: (2024)
A Computationally Efficient Hybrid Neural Network Architecture for Porous Media: Integrating Convolutional and Graph Neural Networks for Improved Property Predictions
by: Zhao, Qingqi, et al.
Published: (2023)
by: Zhao, Qingqi, et al.
Published: (2023)
Using Convolutional Neural Networks for Denoising and Deblending of Marine Seismic Data
by: Slang, Sigmund, et al.
Published: (2024)
by: Slang, Sigmund, et al.
Published: (2024)
Deep Learning-Driven Downscaling for Climate Risk Assessment of Projected Temperature Extremes in the Nordic Region
by: Loganathan, Parthiban, et al.
Published: (2025)
by: Loganathan, Parthiban, et al.
Published: (2025)
Diffusion Models Bridge Deep Learning and Physics in ENSO Forecasting
by: Xu, Weifeng, et al.
Published: (2025)
by: Xu, Weifeng, et al.
Published: (2025)
A Review of Modeling and Waveform Inversion for Marine Seismic Data
by: Chen, Guoxin
Published: (2026)
by: Chen, Guoxin
Published: (2026)
Axial Seamount Eruption Forecasting Experiment
by: Lei, Qinghua, et al.
Published: (2025)
by: Lei, Qinghua, et al.
Published: (2025)
CIDR interpolation: an enhanced SSA-based temporal filling framework for restoring continuity in downscaled GRACE(-FO) TWSA products
by: Gao, Yu, et al.
Published: (2025)
by: Gao, Yu, et al.
Published: (2025)
Part 1: Disruption of Water-Carbon Cycle under Wet Climate Extremes
by: Neelam, Maheshwari, et al.
Published: (2024)
by: Neelam, Maheshwari, et al.
Published: (2024)
A nodal discontinuous Galerkin method for wave propagation in coupled acoustic–elastic media
by: Ruiqi Li, et al.
Published: (2024)
by: Ruiqi Li, et al.
Published: (2024)
Exploiting Free-Surface Ghosts as Mirror Observations in Marine Seismic Data
by: Mikada, Hitoshi
Published: (2026)
by: Mikada, Hitoshi
Published: (2026)
What Can We Learn from Marine Geophysics to Study Rifted Margins?
by: Autin, Julia, et al.
Published: (2024)
by: Autin, Julia, et al.
Published: (2024)
A Framework for Automatic Validation and Application of Lossy Data Compression in Ensemble Data Assimilation
by: Keller, Kai, et al.
Published: (2024)
by: Keller, Kai, et al.
Published: (2024)
High‐Accuracy Modelling of 3D Frequency‐Domain Elastic‐Wave Equation Based on One‐Direction Composition of the Average‐Derivative Optimal Method
by: Hao Wang, et al.
Published: (2025)
by: Hao Wang, et al.
Published: (2025)
Likelihood-Free Inference and Hierarchical Data Assimilation for Geological Carbon Storage
by: Teng, Wenchao, et al.
Published: (2024)
by: Teng, Wenchao, et al.
Published: (2024)
Improving Global Weather and Ocean Wave Forecast with Large Artificial Intelligence Models
by: Ling, Fenghua, et al.
Published: (2024)
by: Ling, Fenghua, et al.
Published: (2024)
EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes
by: Stockman, Samuel, et al.
Published: (2024)
by: Stockman, Samuel, et al.
Published: (2024)
Data-Driven Dynamic Friction Models based on Recurrent Neural Networks
by: Cortes, Gaëtan, et al.
Published: (2024)
by: Cortes, Gaëtan, et al.
Published: (2024)
Marine vibrator source motion correction for strictly monotonic sweeps
by: Stephen Secker, et al.
Published: (2024)
by: Stephen Secker, et al.
Published: (2024)
High‐Accuracy Reconstruction of 3D Seismic Data Constrained by Frequency Domain Priors
by: Xiang Zikun, et al.
Published: (2026)
by: Xiang Zikun, et al.
Published: (2026)
Similar Items
-
Improved Forecasts of Global Extreme Marine Heatwaves Through a Physics-guided Data-driven Approach
by: Shu, Ruiqi, et al.
Published: (2024) -
NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation
by: Gao, Yuan, et al.
Published: (2025) -
An End-to-End Differentiable, Graph Neural Network-Embedded Pore Network Model for Permeability Prediction
by: Zhao, Qingqi, et al.
Published: (2025) -
Towards End-to-End Earthquake Monitoring Using a Multitask Deep Learning Model
by: Zhu, Weiqiang, et al.
Published: (2025) -
End-to-End Mineral Exploration with Artificial Intelligence and Ambient Noise Tomography
by: Muir, Jack, et al.
Published: (2024)