Glad you like Weather Lab, Matt!

We also look at all responses we get via the feedback button if you have ideas about how we can make the site more useful.

Welcome, Jeff, and thanks for the links!

dynamical tests would be in my top 3 too :-)

See: twitter.com/elonmusk/sta...

Yeah ofc there are indirect benefits from crewed space exploration and non-Earth-related spacecraft, even if just for the sake of knowledge

I’m speaking more to a shift in myself while at uni, realising there are too many urgent problems on Earth for some Muskian Mars colonisation project lol

See you at AMS!

It's @ecmwf.bsky.social keeping the tradition this year 😉

bsky.app/profile/rasp...

I ran into this as well - there is a separate button for uploading animations (next to the static image one).

Nice work by the way!

My personal opinion (and I think general consensus) is that while purely data-driven modelling already excels from nowcasting to medium-range timescales, it is not the right paradigm for climate forecasting. Very fast ML/physics hybrid GCMs like NeuralGCM will be the way to go.
cc @stephanhoyer.com

Actual rollout schematic animation here:

Looks like Bluesky has a separate button for videos that I missed 🙃 Actual Milton animation here:

It's been an honour to work on this study led by Ilan Price with such a talented team ✨: Alvaro Sanchez Gonzalez, Ferran Puig, Andrew El-Kadi, Dominic Masters, Timo Ewalds, Jacklynn Stott, @shakirm.bsky.social, Peter Battaglia, Rémi Lam, & Matthew Willson

Like its predecessor (GraphCast), the weights & code of GenCast have been made publicly available: github.com/google-deepm...

We’re looking forward to seeing how the community builds on this!

A GenCast ensemble member takes 8 minutes on a TPU chip, versus hours on a supercomputer for physics-based models. This opens up the possibility of large ensembles (eg 1000s of members), which could better estimate risks of extreme events. We don't yet know how much this will help.

Cyclone max wind speeds are still underestimated, but this performance on tracks is really promising.

One recent devastating cyclone was Hurricane Milton, which caused >$85 billion in damages. GenCast predicted ~70% probability of landfall in Florida 8.5 days before it struck.

We also extracted cyclone tracks from GenCast and ENS and compared them with ~100 cyclones observed in 2019. GenCast's ensemble mean cyclone track has a 12-hour position error advantage over ENS out to 4 days, and more actionable track probability fields out to 7 days.