Improving Typhoon Predictions by Integrating Data-Driven Machine Learning Models with Physics Models Based on the Spectral Nudging and Data Assimilation
Fuente:
arXiv
Saved in:
| Main Authors: | Niu, Zeyi, Huang, Wei, Zhang, Lei, Deng, Lin, Wang, Haibo, Yang, Yuhua, Wang, Dongliang, Li, Hong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Machine Learning (ML)-Physics Fusion Model Outperforms Both Physics-Only and ML-Only Models in Typhoon Predictions
by: Niu, Zeyi, et al.
Published: (2025)
by: Niu, Zeyi, et al.
Published: (2025)
A Data-Driven Regional Model for Skillful Medium-Range Typhoon Prediction
by: Niu, Zeyi, et al.
Published: (2026)
by: Niu, Zeyi, et al.
Published: (2026)
ML-Physical Fusion Models Are Accelerating the Paradigm Shift in Operational Typhoon Forecasting
by: Niu, Zeyi
Published: (2025)
by: Niu, Zeyi
Published: (2025)
Intelligent Shanghai Typhoon Model (ISTM): A generative probabilistic emulator for typhoon hybrid modeling
by: Niu, Zeyi, et al.
Published: (2025)
by: Niu, Zeyi, et al.
Published: (2025)
Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space
by: Fan, Hang, et al.
Published: (2025)
by: Fan, Hang, et al.
Published: (2025)
Exploring the Use of Machine Learning Weather Models in Data Assimilation
by: Tian, Xiaoxu, et al.
Published: (2024)
by: Tian, Xiaoxu, et al.
Published: (2024)
Assimilating Observed Surface Pressure into ML Weather Prediction Models
by: Slivinski, Laura C., et al.
Published: (2024)
by: Slivinski, Laura C., et al.
Published: (2024)
LO-SDA: Latent Optimization for Score-based Atmospheric Data Assimilation
by: Sun, Jing-An, et al.
Published: (2025)
by: Sun, Jing-An, et al.
Published: (2025)
Jacobian-Enforced Neural Networks (JENN) for Improved Data Assimilation Consistency in Dynamical Models
by: Tian, Xiaoxu
Published: (2024)
by: Tian, Xiaoxu
Published: (2024)
XiHe: A Data-Driven Model for Global Ocean Eddy-Resolving Forecasting
by: Wang, Xiang, et al.
Published: (2024)
by: Wang, Xiang, et al.
Published: (2024)
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)
A Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model
by: Peng, Yuehua, et al.
Published: (2026)
by: Peng, Yuehua, et al.
Published: (2026)
Fuxi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations
by: Xu, Xiaoze, et al.
Published: (2024)
by: Xu, Xiaoze, et al.
Published: (2024)
3D-Var Data Assimilation using a Variational Autoencoder
by: Melinc, Boštjan, et al.
Published: (2023)
by: Melinc, Boštjan, et al.
Published: (2023)
Typhoon Tracks Regulated by Feedbacks of Fine-Scale Clouds to Environment
by: Zhao, Haoran, et al.
Published: (2025)
by: Zhao, Haoran, et al.
Published: (2025)
AI Models Still Lag Behind Traditional Numerical Models in Predicting Sudden-Turning Typhoons
by: Xu, Daosheng, et al.
Published: (2025)
by: Xu, Daosheng, et al.
Published: (2025)
Insights from Ex-Typhoon Halong (2025) -- An Arctic Cyclone of Tropical Origin
by: Yang, Mingshi, et al.
Published: (2026)
by: Yang, Mingshi, et al.
Published: (2026)
Impact of an Ensemble of Ocean Data Assimilations in ECMWF's next generation ocean reanalysis system
by: Chrust, Marcin, et al.
Published: (2024)
by: Chrust, Marcin, et al.
Published: (2024)
Enabling High-Accuracy Data Assimilation with Limited Ensembles via Machine Learning-Based Covariance Correction
by: Yao, Zhou, et al.
Published: (2026)
by: Yao, Zhou, et al.
Published: (2026)
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)
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation
by: Andry, Gérôme, et al.
Published: (2025)
by: Andry, Gérôme, et al.
Published: (2025)
Assessing the Risks of Typhoon-Induced Multi-Hazards in South Korea
by: Liu, Ziyue, et al.
Published: (2025)
by: Liu, Ziyue, et al.
Published: (2025)
Using Diffusion Models to do Data Assimilation
by: Hodyss, Daniel, et al.
Published: (2025)
by: Hodyss, Daniel, et al.
Published: (2025)
Training-Free Data Assimilation with GenCast
by: Savary, Thomas, et al.
Published: (2025)
by: Savary, Thomas, et al.
Published: (2025)
Unsupervised Super-Resolution Data Assimilation Using Conditional Variational Autoencoders with Estimating Background Covariances via Super-Resolution
by: Yasuda, Yuki, et al.
Published: (2023)
by: Yasuda, Yuki, et al.
Published: (2023)
FuXi-TC: A generative framework integrating deep learning and physics-based models for improved tropical cyclone forecasts
by: Guo, Shan, et al.
Published: (2025)
by: Guo, Shan, et al.
Published: (2025)
U-Net Kalman Filter (UNetKF): An Example of Machine Learning-assisted Ensemble Data Assimilation
by: Lu, Feiyu
Published: (2024)
by: Lu, Feiyu
Published: (2024)
Align-DA: Align Score-based Atmospheric Data Assimilation with Multiple Preferences
by: Sun, Jing-An, et al.
Published: (2025)
by: Sun, Jing-An, et al.
Published: (2025)
Accurate and Efficient Hybrid-Ensemble Atmospheric Data Assimilation in Latent Space with Uncertainty Quantification
by: Fan, Hang, et al.
Published: (2026)
by: Fan, Hang, et al.
Published: (2026)
Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model
by: Shi, Jia-Rui, et al.
Published: (2026)
by: Shi, Jia-Rui, et al.
Published: (2026)
DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants
by: Andrae, Martin, et al.
Published: (2025)
by: Andrae, Martin, et al.
Published: (2025)
Learning Data-driven Surrogate and Correction Models for Satellite Observations in Numerical Weather Prediction
by: Buono, Gian Luca, et al.
Published: (2026)
by: Buono, Gian Luca, et al.
Published: (2026)
Data Assimilation using ERA5, ASOS, and the U-STN model for Weather Forecasting over the UK
by: Wang, Wenqi, et al.
Published: (2024)
by: Wang, Wenqi, et al.
Published: (2024)
Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning
by: Ferretti, Savannah L., et al.
Published: (2026)
by: Ferretti, Savannah L., et al.
Published: (2026)
Uncertainty-Aware Spatiotemporal Super-Resolution Data Assimilation with Diffusion Models
by: Ayapilla, Aditya Sai Pranith, et al.
Published: (2026)
by: Ayapilla, Aditya Sai Pranith, et al.
Published: (2026)
Error Growth Dynamic and Predictability of Tropical Cyclone in Machine Learning Weather Prediction Model
by: Pu, Jingchen, et al.
Published: (2026)
by: Pu, Jingchen, et al.
Published: (2026)
Volador 1.0: A Data-Driven Air-Sea Full-Coupling Regional Forecast Model with Submesoscale-Permitting Based on MOE-Swin-Transformer Framework
by: Zhu, Yuhang, et al.
Published: (2026)
by: Zhu, Yuhang, et al.
Published: (2026)
A Physics-Informed Machine Learning Approach utilizing Multiband Satellite Data for Solar Irradiance Estimation
by: Sasaki, Jun, et al.
Published: (2024)
by: Sasaki, Jun, et al.
Published: (2024)
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
by: Xiao, Yi, et al.
Published: (2023)
by: Xiao, Yi, et al.
Published: (2023)
StormDiT: A generative AI model bridges the 2-6 hour 'gray zone' in precipitation nowcasting
by: Sun, Haofei, et al.
Published: (2026)
by: Sun, Haofei, et al.
Published: (2026)
Similar Items
-
Machine Learning (ML)-Physics Fusion Model Outperforms Both Physics-Only and ML-Only Models in Typhoon Predictions
by: Niu, Zeyi, et al.
Published: (2025) -
A Data-Driven Regional Model for Skillful Medium-Range Typhoon Prediction
by: Niu, Zeyi, et al.
Published: (2026) -
ML-Physical Fusion Models Are Accelerating the Paradigm Shift in Operational Typhoon Forecasting
by: Niu, Zeyi
Published: (2025) -
Intelligent Shanghai Typhoon Model (ISTM): A generative probabilistic emulator for typhoon hybrid modeling
by: Niu, Zeyi, et al.
Published: (2025) -
Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space
by: Fan, Hang, et al.
Published: (2025)