Genuine question: What is the best evidence for the value of physics-based regional weather/climate modeling? WRF certainly "looks" more realistic, but when is it actually consistently quantitatively superior to statistical post-processing of global models?

Our new paper in Nature Machine Intelligence tells a story about how, and why, ML methods for solving PDEs do not work as well as advertised. We find that two reproducibility issues are widespread. As a result, we conclude that ML-for-PDE solving has reached overly optimistic conclusions.

Well, here we go --> 🦋

2025 is here tomorrow, so let's reflect on 2024. Even without the final counts and the new AMS and AGU ML journals, 2024 has eclipsed 10% of all papers and had over 600 papers mentioning neural networks in their abstracts 📈

Excited to announce our new experimental cyclone model and a partnership with National Hurricane Center! Traditionally, it's been hard for a model to predict tracks & intensities: one requires a global view, the other very high resolution. Our AI model achieves strong performance on both.