NOAA deploys new generation of AI-driven global weather models

https://www.noaa.gov/news-release/noaa-deploys-new-generation-of-ai-driven-global-weather-models

40•hnburnsy•1d ago

Comments

margalabargala•1h ago

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.

username223•1h ago

Same. I hope this was written by hardened greybeards who have dedicated their lives to weather prediction and atmospheric modeling, and have "weathered" a few funding cycles.

akdev1l•1h ago

inb4 it’s actually an intern maintaining a 3000+ line markdown file

RHSeeger•34m ago

I can see it now

    The following snippet highlights the algorithm used to determine <thing>
    ```fortran
    .....

idontwantthis•1h ago

Hopefully they weren’t all forced out this year. The NOAA had massive cuts.

trueismywork•22m ago

NCAR is being dismantled as we speak.

sigmar•31m ago

Graphcast (the model this is based on) has been validated in weather models for a while[1]. It uses transformers, much like LLMs. Transformers are really impressive at modeling a variety of things and have become very common throughout a lot of ML models, there's no reason to besmirch these methods as "integrating an LLM into a weather model"

[1] https://github.com/google-deepmind/graphcast

lynndotpy•19m ago

A lot of shiny new "AI" features being shipped are language models being placed where they don't belong. It's reasonable to be skeptical here, not just because of the AI label, but especially for the troubled history of neural-network based ML methods for weather prediction.

Even before LLMs got big, a lot of machine learning research being published were models which underperformed SOTA (which was the case for weather modeling for a long time!) or models which are far far larger than they need to be (e.g. this [1] Nature paper using 'deep learning' for aftershock prediction being bested by this [2] Nature paper using one neuron.

[1] https://www.nature.com/articles/s41586-018-0438-y

[2] https://www.nature.com/articles/s41586-019-1582-8

Legend2440•27m ago

It’s not an LLM, but it is genAI. It’s based on the same idea of predict-the-next-thing, but instead of predicting words it predicts the next state of the atmosphere from the current state.

adamweld•6m ago

It is in fact one of the least generalized forms of "AI" out there. A model focused solely on predicting weather.

astrange•56s ago

"gen" stands for "generative". If you read the GenCast paper they call it a generative AI.

(It's an autoregressive GNN plus a diffusion model.)

lukeschlather•27m ago

The GraphCast paper says "GraphCast is implemented using GNNs" without explaining that the acronym stands for Graph Neural Networks. It contrasts GNNs to the " convolutional neural network (CNN)" and "graph attention network." (GAN?) It doesn't really explain the difference between GAN and a GNN. I think LLMs are GANs. So no, it's not an LLM in a weather model, but it's very similar to an LLM in terms of how it is trained.

Workaccount2•1h ago

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.

sigmar•1h ago

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

username223•1h ago

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.

ryuuchin•31m ago

They run at 0.25 degree resolution (same as ECMWF AIFS models).

apawloski•40m ago

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.

ryuuchin•32m 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 and ensemble AIGFS 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].

[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/

padjo•32m ago

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?

tomww•12m ago

They're using a graph neural network. From the article - "The team leveraged Google DeepMind's GraphCast model as an initial foundation and fine-tuned the model using NOAA's own Global Data Assimilation System analyses".

> so what’s AI about this that wasn’t AI previously?

The weather models used today are physics-based numerical models. The machine learning models from DeepMind, ECMWF, Huawei and others are a big shift from the standard, numerical approach used for the last decades.

CalChris•24m ago

Neil Jacobs, Ph.D

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

luc_•16m ago

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

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Buteyko Method

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The FreeBSD Foundation's Laptop Support and Usability Project

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Lite^3, a JSON-compatible zero-copy serialization format

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NOAA deploys new generation of AI-driven global weather models

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