For the AI4ES Journal Club sessions, we propose a template here which follows a simple structure:

• title and authors
• context
• methods
• results
• conclusions
• critique

For those sessions with invited speakers, we will make sure to add below the corresponding slides.

• 2020-12-16 Davide Faranda (University of Paris-Saclay): “Boosting performance in machine learning of geophysical flows via scale separation” (https://doi.org/10.5194/npg-2020-39)
  • Slides of the session

• 2020-11-25 Chris Kadow (DKRZ): “AI image inpainting technology re-fills missing values in HadCRUT4 - a research journey” (https://doi.org/10.1038/s41561-020-0582-5)
  • Slides of the session

• 2020-10-14 Lluís Palma García: “Improving subseasonal forecasting in the western U.S. With machine learning” (Arxiv) “Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances” (Arxiv)
  • Slides of the session

• 2020-04-21 Núria Pérez-Zanón: “Lightning Prediction for Australia Using Multivariate Analyses of Large-Scale Atmospheric Variables” (AMETSOC)
  • Slides of the session

• 2020-03-17 Jesus Peña: “Deep learning for physical processes: incorporating prior scientific knowledge” (IOPSCience)
  • Slides of the session

• 2020-03-03 Carlos Gómez-Gonzalez: “WeatherBench: A benchmark dataset for data-driven weather forecasting” (Arxiv, GitHub)
  • Slides of the session