|
|
|
|
|
by pfisherman
558 days ago
|
|
This is still on retrospective data. The machine learning graveyard is filled with models that worked well on retrospective data, but did not hold up in a live inference setting. Just ask Zillow. The real test is whether they can predict the weather 14 days out in 2025. I am guessing they did not want to set up the data pipeline to run inference in a live setting. But that is what I would need to see to be a true believer. Still a cool result and article though. |
|
The Google model is probably the best so far but ECMWF's own diffusion model was already on par with ENS and many point-forecast models (graph transformers, not diffusion) outperform state-of-the-art physical models.
What is missing is initialization directly from observations. All the best-performing models initialize from ERA5 or other reconstruction.