Leveraging GNN to Enhance MEF Method in Predicting ENSO
Fuente:
arXiv
Saved in:
| Main Authors: | Ganji, Saghar, Labibzadeh, Ahmad Reza, Hassani, Alireza, Naisipour, Mohammad |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Distillation of CNN Ensemble Results for Enhanced Long-Term Prediction of the ENSO Phenomenon
by: Ganji, Saghar, et al.
Published: (2025)
by: Ganji, Saghar, et al.
Published: (2025)
Global kilometre-scale tropical cyclone inner-core vector winds from sparse scalar CYGNSS observations
by: Han, Xinhai, et al.
Published: (2026)
by: Han, Xinhai, et al.
Published: (2026)
Increasing NWP Thunderstorm Predictability Using Ensemble Data and Machine Learning
by: Yousefnia, Kianusch Vahid, et al.
Published: (2025)
by: Yousefnia, Kianusch Vahid, et al.
Published: (2025)
A machine-learning approach to thunderstorm forecasting through post-processing of simulation data
by: Yousefnia, Kianusch Vahid, et al.
Published: (2023)
by: Yousefnia, Kianusch Vahid, et al.
Published: (2023)
Physical Scales Matter: The Role of Receptive Fields and Advection in Satellite-Based Thunderstorm Nowcasting with Convolutional Neural Networks
by: Metzl, Christoph, et al.
Published: (2025)
by: Metzl, Christoph, et al.
Published: (2025)
Inferring Thunderstorm Occurrence from Vertical Profiles of Convection-Permitting Simulations: Physical Insights from a Physical Deep Learning Model
by: Yousefnia, Kianusch Vahid, et al.
Published: (2024)
by: Yousefnia, Kianusch Vahid, et al.
Published: (2024)
Developing a Sequential Deep Learning Pipeline to Model Alaskan Permafrost Thaw Under Climate Change
by: Rahaman, Addina
Published: (2025)
by: Rahaman, Addina
Published: (2025)
Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function
by: Subich, Christopher, et al.
Published: (2025)
by: Subich, Christopher, et al.
Published: (2025)
Improving Oil Slick Trajectory Simulations with Bayesian Optimization
by: Accarino, Gabriele, et al.
Published: (2025)
by: Accarino, Gabriele, et al.
Published: (2025)
Numerical models outperform AI weather forecasts of record-breaking extremes
by: Zhang, Zhongwei, et al.
Published: (2025)
by: Zhang, Zhongwei, et al.
Published: (2025)
Uncertainty Quantification for Reduced-Order Surrogate Models Applied to Cloud Microphysics
by: Katona, Jonas E., et al.
Published: (2025)
by: Katona, Jonas E., et al.
Published: (2025)
Attention-based Models for Snow-Water Equivalent Prediction
by: Thapa, Krishu K., et al.
Published: (2023)
by: Thapa, Krishu K., et al.
Published: (2023)
LASSE: Learning Active Sampling for Storm Tide Extremes in Non-Stationary Climate Regimes
by: Jiang, Grace, et al.
Published: (2024)
by: Jiang, Grace, et al.
Published: (2024)
Physics-Informed Diffusion Model for Generating Synthetic Extreme Rare Weather Events Data
by: Yakout, Marawan, et al.
Published: (2026)
by: Yakout, Marawan, et al.
Published: (2026)
Accurate typhoon intensity forecasts using a non-iterative spatiotemporal transformer model
by: Qu, Hongyu, et al.
Published: (2025)
by: Qu, Hongyu, et al.
Published: (2025)
Spatiotemporal Predictions of Toxic Urban Plumes Using Deep Learning
by: Wang, Yinan, et al.
Published: (2024)
by: Wang, Yinan, et al.
Published: (2024)
DEF: Diffusion-augmented Ensemble Forecasting
by: Millard, David, et al.
Published: (2025)
by: Millard, David, et al.
Published: (2025)
Research on Dangerous Flight Weather Prediction based on Machine Learning
by: Liu, Haoxing, et al.
Published: (2024)
by: Liu, Haoxing, et al.
Published: (2024)
Physics-Informed Residual Neural Ordinary Differential Equations for Enhanced Tropical Cyclone Intensity Forecasting
by: Meng, Fan
Published: (2025)
by: Meng, Fan
Published: (2025)
A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport
by: Fernández-Godino, M. Giselle, et al.
Published: (2024)
by: Fernández-Godino, M. Giselle, et al.
Published: (2024)
Enhanced predictions of the Madden-Julian oscillation using the FuXi-S2S machine learning model: Insights into physical mechanisms
by: Cao, Can, et al.
Published: (2025)
by: Cao, Can, et al.
Published: (2025)
Resolving the Paradox of Changing ENSO-Monsoon Relation through Global-ENSO
by: Sharma, Devabrat, et al.
Published: (2026)
by: Sharma, Devabrat, et al.
Published: (2026)
Integrating Weather Station Data and Radar for Precipitation Nowcasting: SmaAt-fUsion and SmaAt-Krige-GNet
by: Shi, Jie, et al.
Published: (2025)
by: Shi, Jie, et al.
Published: (2025)
GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting
by: Reulen, Eloy, et al.
Published: (2024)
by: Reulen, Eloy, et al.
Published: (2024)
Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift
by: Shin, Bong Gyun, et al.
Published: (2026)
by: Shin, Bong Gyun, et al.
Published: (2026)
Leveraging an Atmospheric Foundational Model for Subregional Sea Surface Temperature Forecasting
by: Medina, Víctor, et al.
Published: (2025)
by: Medina, Víctor, et al.
Published: (2025)
Neural Dynamic Modes: Computational Imaging of Dynamical Systems from Sparse Observations
by: SaraerToosi, Ali, et al.
Published: (2025)
by: SaraerToosi, Ali, et al.
Published: (2025)
Deep learning the sources of MJO predictability: a spectral view of learned features
by: Yao, Lin, et al.
Published: (2025)
by: Yao, Lin, et al.
Published: (2025)
Generative artificial intelligence improves projections of climate extremes
by: Tie, Ruian, et al.
Published: (2025)
by: Tie, Ruian, et al.
Published: (2025)
Towards Multi-Agent Autonomous Reasoning in Hydrodynamics
by: Zhao, Jinpai, et al.
Published: (2026)
by: Zhao, Jinpai, et al.
Published: (2026)
Data-driven ensemble prediction of the global ocean
by: Huang, Qiusheng, et al.
Published: (2026)
by: Huang, Qiusheng, et al.
Published: (2026)
Multi-Fidelity Emulation of Atmospheric Correction Coefficients with Physics-Guided Kolmogorov-Arnold Networks
by: Mazid, Md Abdullah Al, et al.
Published: (2026)
by: Mazid, Md Abdullah Al, et al.
Published: (2026)
Two Hebrew folk meteorological proverbs tested: rainfall on Rosh Chodesh and Shabbat Mevarechim as predictors of monthly precipitation (Israel, 1950-2024)
by: Weinberg, Abraham Itzhak
Published: (2026)
by: Weinberg, Abraham Itzhak
Published: (2026)
Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery
by: Lagerquist, Ryan, et al.
Published: (2024)
by: Lagerquist, Ryan, et al.
Published: (2024)
A multi-scale loss formulation for learning a probabilistic model with proper score optimisation
by: Lang, Simon, et al.
Published: (2025)
by: Lang, Simon, et al.
Published: (2025)
Improving ensemble extreme precipitation forecasts using generative artificial intelligence
by: Sha, Yingkai, et al.
Published: (2024)
by: Sha, Yingkai, et al.
Published: (2024)
Community Research Earth Digital Intelligence Twin (CREDIT)
by: Schreck, John, et al.
Published: (2024)
by: Schreck, John, et al.
Published: (2024)
Multi-Objective Optimization of Water Resource Allocation for Groundwater Recharge and Surface Runoff Management in Watershed Systems
by: Sharifi, Abbas, et al.
Published: (2025)
by: Sharifi, Abbas, et al.
Published: (2025)
Impact of geophysical fields on Deep Learning-based Lagrangian drift simulations
by: Botvynko, Daria, et al.
Published: (2026)
by: Botvynko, Daria, et al.
Published: (2026)
AI for operational methane emitter monitoring from space
by: Vaughan, Anna, et al.
Published: (2024)
by: Vaughan, Anna, et al.
Published: (2024)
Similar Items
-
Distillation of CNN Ensemble Results for Enhanced Long-Term Prediction of the ENSO Phenomenon
by: Ganji, Saghar, et al.
Published: (2025) -
Global kilometre-scale tropical cyclone inner-core vector winds from sparse scalar CYGNSS observations
by: Han, Xinhai, et al.
Published: (2026) -
Increasing NWP Thunderstorm Predictability Using Ensemble Data and Machine Learning
by: Yousefnia, Kianusch Vahid, et al.
Published: (2025) -
A machine-learning approach to thunderstorm forecasting through post-processing of simulation data
by: Yousefnia, Kianusch Vahid, et al.
Published: (2023) -
Physical Scales Matter: The Role of Receptive Fields and Advection in Satellite-Based Thunderstorm Nowcasting with Convolutional Neural Networks
by: Metzl, Christoph, et al.
Published: (2025)