UW-Atmos-MLJC

Machine-Learning Journal Club Meeting Collection

Department of Atmospheric and Climate Science at the University of Washington

This is the collection of all the MLJC meeting materials.

(Thanks, Dominik)

BoltCast: Deep Learning for Medium-Range Lightning Prediction
- Leads: Brandon McClung, July 17
- Paper: Under Review, Check Email

A foundation model for the Earth system
- Leads: Elliot Kim, May 26
- Paper: Bodnar et al. (2025): https://www.nature.com/articles/s41586-025-09005-y
Reanalysis-based Global Radiative Response to Sea Surface Temperature Patterns: Evaluating the Ai2 Climate Emulator
- Leads: Andy Liu, May 13
- Paper: Van Loon et al. (2025): https://arxiv.org/pdf/2502.10893
- Slides: Reanalysis-based Global Radiative Response to Sea Surface Temperature Patterns_ Evaluating the Ai2 Climate Emulator.pdf
- Additional Paper:
  - Green’s Function MIP (Bloch-Johnson et al, 2024): https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS003700
  - ACE2+E3SM (Wu et al., 2025): https://arxiv.org/pdf/2505.08742
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
- Leads: Will Yik, April 29
- Paper: Bonev et al. (2023): https://proceedings.mlr.press/v202/bonev23a/bonev23a.pdf
Dynamical-generative downscaling of climate model ensembles
- Leads: Raúl Moreno, April 15
- Paper: Lopez-Gomez et al. (2024): https://arxiv.org/pdf/2410.01776

OMG-HD: A High-Resolution AI Weather Model for End-to-End Forecasts from Observations
- Leads: Geraint Webb, February 26
- Paper: Zhao et al. (2024) https://arxiv.org/pdf/2412.18239
Learning Propagators for Sea Surface Height Forecasts Using Koopman Autoencoders
- Leads: Eric Mei, January 29
- Paper: Brettin et al. (2024): https://doi.org/10.22541/essoar.172801453.37313793/v1
WoFSCast: A machine learning model for predicting thunderstorms at watch-to-warning scales
- Leads: Miles Epstein, January 15
- Paper: Flora and Potvin (2024): https://doi.org/10.22541/essoar.172574503.30734251/v1

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications
- Leads: Elliot Kim, Andy Liu, November 19
- Paper: Schreck et al. (2024): https://doi.org/10.1175/AIES-D-23-0093.1
- Slides: MLJC_ Evidential DL (110924).pdf
A Review of Machine Learning for Convective Weather
- Leads: Alex Anderson-Frey, November 5
- Paper: McGovern et al. (2023): https://doi.org/10.1175/AIES-D-22-0077.1
Physics-informed deep convolutional network for combined sea ice concentration and velocity prediction
- Leads: Sky Gale, October 29
- Paper: Liu et al. (2024): https://doi.org/10.1016/j.oceaneng.2024.119440
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling
- Leads: Raúl Moreno, October 15
- Paper: Pathak et al. (2024): https://arxiv.org/pdf/2408.10958
Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
- Leads: Trent Vonich, October 1
- Paper: Vonich and Hakim (2024): https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024GL110651

Can Artificial Intelligence-Based Weather Prediction Models Simulate the Butterfly Effect?
- Leads: Mu-Ting Chien, May 31
- Paper: Selz and Craig (2023): https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023GL105747
Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh
- Leads: Raúl Moreno, May 17
- Paper: Karlbauer et al. (2023): https://arxiv.org/pdf/2311.06253
Learning skillful medium-range global weather forecasting
- Leads: Dominik Stiller, May 3
- Paper: Lam et al. (2023): https://www.science.org/doi/10.1126/science.adi2336

Elements of Statistical Learning
- Leads:
- Book: Trevor Hastie, Robert Tibshirani, Jerome Friedman: https://hastie.su.domains/ElemStatLearn/
- Additional Material:
  - https://cs229.stanford.edu/section/cs229-prob.pdf

Score-Based Generative Model
- Leads: All, February 12
- Video:
  - Diffusion Models, Outlier: https://youtu.be/HoKDTa5jHvg?si=ZnEdaS2-gSCRnDTO
  - Diffusion Models From Scratch, Derivations: https://youtu.be/B4oHJpEJBAA?si=KcooBZQOuaeIAOBv

[Spring 2025] Ai2 Climate Emulator: https://arxiv.org/pdf/2502.10893
[Spring 2025] Spherical Fourier Neural Operators: https://proceedings.mlr.press/v202/bonev23a/bonev23a.pdf
[Spring 2024] Simulate the Butterfly Effect: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023GL105747
[Spring 2024] Weather Prediction using the HEALPix Mesh: https://arxiv.org/pdf/2311.06253
[Spring 2024] Learning skillful medium-range global weather forecasting: https://www.science.org/doi/10.1126/science.adi2336
[Autumn 2024] CNN for sea ice concentration and velocity prediction: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023GL105747
[Autumn 2024] A Review of Machine Learning for Convective Weather: https://doi.org/10.1175/AIES-D-22-0077.1
[Winter 2025] WoFSCast and Thunderstorm: https://doi.org/10.22541/essoar.172574503.30734251/v1
[Winter 2025] OMG-HD: A High-Resolution AI Weather Model Forecasts from Observations: https://arxiv.org/pdf/2412.18239
[Summer 2025] BoltCast: Deep Learning for Medium-Range Lightning Prediction: (Missing Link)

[Autumn 2024] Kilometer-Scale Convection using Generative Diffusion Modeling: https://arxiv.org/pdf/2408.10958
[Winter 2025] Score-Based Generative Model Derivation: https://youtu.be/HoKDTa5jHvg?si=ZnEdaS2-gSCRnDTO
[Spring 2025] Dynamical-generative downscaling: https://arxiv.org/pdf/2410.01776

[Spring 2025] A foundation model for the Earth system: https://www.nature.com/articles/s41586-025-09005-y

[Autumn 2024] Predictability Limit of the 2021 Pacific Northwest Heatwave: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024GL110651

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