NOAA deploys new generation of AI-driven global weather models

I've seen the Microsoft Aurora team make a compelling argument that weather is an interesting contradiction of the AI-energy-waste narrative. Once deployed at scale, inference with these models is actually a sizable energy/compute improvement over classical simulation and forecasting methods. Of course it is energy intensive to train the model, but the usage itself is more energy efficient.

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...

Interestingly, while this model is based on a Google Deepmind AI weather model, it's based on a model from 2023 (GraphCast) rather than the WeatherNext 2 model which has grabbed headlines as of late. I'd imagine it takes a while to integrate and test everything, explaining the gap.

I am dearly hoping that they are using the current "AI" craze to talk up the machine learning methods they have presumably been using for a decade at this point, and not that they have actually integrated an LLM into a weather model.

What does AI refer to here? Presumably weather models have been using all sorts of advanced machine learning for decades now, so what’s AI about this that wasn’t AI previously?

Working on AI driven weather predictions to make money on prediction markets. The accuracy of WeatherNext 2 is astounding.

It may be a fools errand but makes for an extremely interesting research project. http://climatesight.app if you’re interested in climate markets.

Is there a primer for reading these files?

https://www.nco.ncep.noaa.gov/pmb/products/gens/

https://www.emc.ncep.noaa.gov/emc/pages/numerical_forecast_s...

All these years later and we still don’t have the minute-accurate forecasts that Dark Sky had before Apple shut it down. Living in the future sucks.

How well do these predict extremes/outliers? Given that I expect these are more "ML" type models, these are somewhat limited to interpolation, rather than extrapolation?

These look like staging MVP releases with a full rollout planned for the future. They are only including a few parameters at every 6 hours which is barely interesting to anyone with their feet on the ground.

I wonder if the new models consider land use change and emissions from aggressive datacenter development and model training...

Apparently it seems to be impossible with these files and the best AI right now to answer the simple question, will it rain in midtown Manhattan tomorrow?

how about working with Weather Underground to validate predicted weather at ground level? Here in Southern CO would be a perfect place to try this. Weather Underground has thousands of volunteer backyard weather stations, including mine.

I understand that aviation safety is certainly a primary concern for NWS/NOAA but ground level forecasts are also very important for public safety.

Whatever it is, it seems like it might be roughly competitive with ECMWF, the state of the art when it comes to global weather models: https://www.epic.noaa.gov/ai/eagle-verification/

A quick search didn't turn up anything about the model's skill or resolution, though I'm sure the data exists.

Neil Jacobs, Ph.D

This makes me skeptical that it isn’t just politicized Trumpian nonsense.

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?