AI4Earth Papers

Medium-range Global Weather Forecasting

• Is Artificial Intelligence Providing the Second Revolution for Weather Forecasting, arxiv 2024
• Challenges and design choices for global weather and climate models based on machine learning, GMD 2018
• Improving Data-Driven Global Weather Prediction UsingDeep Convolutional Neural Networks on a Cubed Sphere, JAMES 2020
• FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators, arxiv 2022
• Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast, Nature 2023
• GraphCast: Learning skillful medium-range global weather forecasting, Science 2023
• FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead, arxiv 2023
• FuXi: A cascade machine learning forecasting system for 15-day global weather forecast, arxiv 2023
• The rise of data-driven weather forecasting, arxiv 2023
• ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast, arxiv 2024
• FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting, arxiv 2024

End-to-End Global Weather Forecasting

• FENGWU-4DVAR: COUPLING THE DATA-DRIVEN WEATHER FORECASTING MODEL WITH 4D VARIATIONAL ASSIMILATION, ICML 2024
• Towards an End-to-End Artificial Intelligence Driven Global Weather Forecasting System, arixv 2023
• Aardvark Weather: end-to-end data-driven weather forecasting, arxiv 2024
• Deep Generative Data Assimilation in Multimodal Setting, arxiv 2024
• Fuxi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations, arxiv 2024
• Scalable Data Assimilation with Message Passing, Environmental Data Science, 2024
• Assessing the Feasibility of an NWP Satellite Data Assimilation System Entirely Based on AI Techniques, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024

Precipitation Nowcasting

• CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
• Skilful nowcasting of extreme precipitation with NowcastNet, Nature 2023

Climate Prediction

• Deep learning for multi-year ENSO forecasts
• Multi-task machine learning improves multi- seasonal prediction of the Indian Ocean Dipole
• Exploring dominant processes for multi-month MJO prediction using deep learning
• Seasonal Arctic sea ice forecasting with probabilistic deep learning
• Early warning signal for a tipping point suggested by a millennial Atlantic Multidecadal Variability reconstruction

Neural Network Parameterization

• Neural-Network Parameterization of Subgrid Momentum Transport in the Atmosphere, JAMES 2023
• Neural Network Parameterization of Subgrid-Scale Physics From a Realistic Geography Global Storm-Resolving Simulation, JAMES 2024

Ensembles

• Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44,

Downsampling

• High-resolution downscaling with interpretable deep learning: Rainfall extremes over New Zealand, Weather and Climate Extremes, 2022 (Q1).
• Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method, arxiv 2024

Uncertainty

• Uncertainty Quantification for Traffic Forecasting: A Unified Approach, ICDE 2023

Reviews

• Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions, Earth-Science Reviews, 2021 (Q1).

Satellite Images

Optimization

• auxiliary learning with joint task and data scheduling

Networks Architectures

• Reversible Column Networks

AAAI 2023 related (https://aaai-23.aaai.org/wp-content/uploads/2023/01/Updated_AAAI-23-Technical-Schedule-FEB09.pdf)

• Counterfactual Dynamics Forecasting - A New Setting of Quantitative Reasoning
• An Extreme-Adaptive Time Series Prediction Model Based on Probability
• Opposite Online Learning via Sequentially Integrated Stochastic Gradient
• Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting
• WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series
• Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
• Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis