Imagen de Portada

Deconfounding Multi-Cause Latent Confounders: A Factor-Model Approach to Climate Model Bias Correction

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gao, Wentao, Li, Jiuyong, Cheng, Debo, Liu, Lin, Liu, Jixue, Le, Thuc Duy, Du, Xiaojing, Chen, Xiongren, Zhao, Yanchang, Chen, Yun
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence Atmospheric and Oceanic Physics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Novel Dynamic Bias-Correction Framework for Hurricane Risk Assessment under Climate Change
por: Snaiki, Reda, et al.
Publicado: (2025)

Global Climate Model Bias Correction Using Deep Learning
por: Pasula, Abhishek, et al.
Publicado: (2025)

Mixed-Precision Computing in the GRIST Dynamical Core for Weather and Climate Modelling
por: Chen, Siyuan, et al.
Publicado: (2024)

Forecasting the Future with Yesterday's Climate: Temperature Bias in AI Weather and Climate Models
por: Landsberg, Jacob B., et al.
Publicado: (2025)

A Deep Learning Earth System Model for Efficient Simulation of the Observed Climate
por: Cresswell-Clay, Nathaniel, et al.
Publicado: (2024)

Hydrologic Cycle Weakening in Hothouse Climates
por: Liu, Jiachen, et al.
Publicado: (2024)

An Efficient Regional Storm Surge Surrogate Model Training Strategy Under Evolving Landscape and Climate Scenarios
por: Liu, Ziyue, et al.
Publicado: (2025)

Rapid Climate Model Downscaling to Assess Risk of Extreme Rainfall in Bangladesh in a Warming Climate
por: Saha, Anamitra, et al.
Publicado: (2024)

Origin and Limits of Invariant Warming Patterns in Climate Models
por: Giani, Paolo, et al.
Publicado: (2024)

Epistemic and Aleatoric Uncertainty Quantification in Weather and Climate Models
por: Mansfield, Laura A., et al.
Publicado: (2025)

Near-surface Extreme Wind Events and Their Responses to Climate Forcings in a Hierarchy of Global Climate Models
por: Zhang, G., et al.
Publicado: (2026)

Technical Report: Towards Unified Diffusion Models for Multi-Model Climate Emulation at Scale
por: Immorlano, Francesco, et al.
Publicado: (2025)

From Noise to Precision: A Diffusion-Driven Approach to Zero-Inflated Precipitation Prediction
por: Gao, Wentao, et al.
Publicado: (2025)

Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space
por: Fan, Hang, et al.
Publicado: (2025)

Weather Jiu-Jitsu: Climate Adaptation for the 21st Century
por: Huang, Qin, et al.
Publicado: (2025)

Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model
por: Shi, Jia-Rui, et al.
Publicado: (2026)

Do Climate Models Need Microphysical and Convective Parameterizations to Generate Accurate Precipitation Fields?
por: Moreno, Raul, et al.
Publicado: (2026)

Efficient and High-Accuracy Ray Tracing in Discretized Ionospheric Models
por: Li, Qinglin, et al.
Publicado: (2025)

Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model
por: Heuer, Helge, et al.
Publicado: (2025)

Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere
por: Brenowitz, Noah D., et al.
Publicado: (2025)

The Interdecadal Bipolar Oscillation: An Atmospheric Water Vapor Mode Driving Asynchronous Polar Climate Change
por: Wang, Hongyu, et al.
Publicado: (2026)

Latent Diffusion Model for Generating Ensembles of Climate Simulations
por: Meuer, Johannes, et al.
Publicado: (2024)

CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates
por: Liu, Shuchang, et al.
Publicado: (2025)

Learning Data-driven Surrogate and Correction Models for Satellite Observations in Numerical Weather Prediction
por: Buono, Gian Luca, et al.
Publicado: (2026)

Nonlocal, Pattern-aware Response and Feedback Framework for Regional Climate Change
por: Kooloth, Parvathi, et al.
Publicado: (2024)

Vertical Profile Corrected Satellite NH3 Retrievals Enable Accurate Agricultural Emission Characterization in China
por: Liu, Qiming, et al.
Publicado: (2025)

Data Driven Deep Learning for Correcting Global Climate Model Projections of SST and DSL in the Bay of Bengal
por: Pasula, Abhishek, et al.
Publicado: (2025)

Deciphering Super El Niño: Development of a Novel Predictive Model Integrating Local and Global Climatic Signals
por: Yoon, Chae-Hyun, et al.
Publicado: (2024)

Reduced Cloud Cover Errors in a Hybrid AI-Climate Model Through Equation Discovery And Automatic Tuning
por: Grundner, Arthur, et al.
Publicado: (2025)

Leveraging Climate Services to Build Climate Resilient Power Systems
por: Dubus, Laurent, et al.
Publicado: (2026)

Assessing Future Wind Energy Potential under Climate Change: The Critical Role of Multi-Model Ensembles in Robustness Assessment
por: Lira-Loarca, Andrea, et al.
Publicado: (2025)

Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
por: Orlova, Elena, et al.
Publicado: (2022)

LO-SDA: Latent Optimization for Score-based Atmospheric Data Assimilation
por: Sun, Jing-An, et al.
Publicado: (2025)

Livestock, Methane and Climate
por: Alexander, D., et al.
Publicado: (2026)

Accurate Column Moist Static Energy Budget in Climate Models. Part 1: Conservation Equation Formulation, Methodology, and Primary Results Demonstrated Using GISS ModelE3
por: Inoue, Kuniaki, et al.
Publicado: (2024)

Climate-Adaptive and Cascade-Constrained Machine Learning Prediction for Sea Surface Height under Greenhouse Warming
por: Zheng, Tianmu, et al.
Publicado: (2025)

BiXiao: An AI-Based Atmospheric Environment Forecasting Model Using Discontinuous Grids
por: Ji, Shengxuan, et al.
Publicado: (2025)

Organization of Historical Oceanic Overturnings on Cross-Sphere Climate Signals
por: Jiang, Yingjing, et al.
Publicado: (2025)

Intercomparison of a High-Resolution Regional Climate Model Ensemble for Catchment-Scale Water Cycle Processes under Human Influence
por: Roque, J. L., et al.
Publicado: (2025)

Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling
por: Mardani, Morteza, et al.
Publicado: (2023)