tndl (u/tndl) - Readit News

tndl commented on NOAA deploys new generation of AI-driven global weather models noaa.gov/news-release/noa... · Posted by u/hnburnsy

ryandrake · 3 days ago

Protip: Any time you read "AI" in a news article, substitute the phrase "faster, more numerous, and confidently incorrect." I don't think we need "confidently incorrect" weather models. Who is asking for this?

tndl · 3 days ago

These models actually outperform traditional methods on many fronts, including accuracy a lot of the time. They are technically generative AI models, but they're definitely not LLMs.

tndl commented on NOAA deploys new generation of AI-driven global weather models noaa.gov/news-release/noa... · Posted by u/hnburnsy

ryuuchin · 3 days ago

These are available on Weatherbell[1] (which requires a subscription) now except for the HGEFS ensemble model which I'm guessing will probably be added later. AIGFS is on tropical tidbits which should be free for some stuff[5]. I believe some of the research on this is mentioned in these two[2][3] videos from NOAA weather partners site. They also talk about some of the other advances in weather model research.

One of the big benefits of both the single run (AIGFS) and ensemble (AIGEFS) models is the speed and (less) computation time required. Weather modeling is hard and these models should be used as complementary to deterministic models as they all have their own strengths and weaknesses. They run at the same 0.25 degree resolution as the ECMWF AIFS models which were introduced earlier this year and have been successful[4].

Edit: Spring 2025 forecasting experiment results is available here[6].

[1] https://www.weatherbell.com/

[2] https://www.youtube.com/watch?v=47HDk2BQMjU

[3] https://www.youtube.com/watch?v=DCQBgU0pPME

[4] https://www.ecmwf.int/en/forecasts/dataset/aifs-machine-lear...

[5] https://www.tropicaltidbits.com/analysis/models/

[6] https://repository.library.noaa.gov/view/noaa/71354/noaa_713...

tndl · 3 days ago

Really exciting to see NOAA finally make some progress on this front, but the AIGFS suite likely won't outperform ECMWF's AIFS suite any time soon. The underlying architecture between AIFS and GraphCast/AIGFS is pretty similar (both GNNs), so there won't likely be a model-level improvement. And most of ECMWF's edge lies in its superior 4DVar data assimilation process. AIGFS is still being initialized on NOAA's hybrid 4DEnVar assimilation process as far as I understand it, which is still not as good as straight up 4DVar unfortunately.

tndl commented on NOAA deploys new generation of AI-driven global weather models noaa.gov/news-release/noa... · Posted by u/hnburnsy

sigmar · 3 days ago

I've been assuming that, unlike graphcast, they have no intention to make weathernext 2 open source.

tndl · 3 days ago

That seems to be the case from what I've heard.

tndl commented on Aurora, a foundation model for the Earth system nytimes.com/2025/05/21/cl... · Posted by u/rmason

sieste · 7 months ago

Impressive. However, I don't like how AI foundation models are always advertised as alternatives to "traditional" (physics based) forecasting. Virtually all AI weather models are trained on ERA5 reanalysis, which is a blend of observations and numerical model forecasts. Without a good global numerical model of the atmosphere there would be no AI model. I wish this synergy were emphasised more, rather than always going straight for the easy "AI beats physics!!1!" headline.

tndl · 7 months ago

Things are changing quickly in this area. Several projects/companies working on AI data assimilation (an alternative route to creating analysis data like ERA5)[0].

Also a lot of companies working on the data collection side, replacing/augmenting government data collection. Spire's an example of this in the space domain, and Windborne and Sorcerer (my company) do weather balloons.

[0]: E.g. Brightband's AIDA (https://www.brightband.com/blog/aida/) and Project Aardvark (https://www.turing.ac.uk/blog/project-aardvark-reimagining-a...)