Based on the Gemini release it’s hard to take what Google claims at face value.
They released the work as open source to Github. I guess you could validate their findings?
Google says AI weather model masters 15-day forecast
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Re: Google says AI weather model masters 15-day forecast
#122It does seem like this is one of those domains where new AI models could thrive. From my understanding, the amount and variety of data necessary to make these models work is huge. In addition to historical data, you've got constant satellite data, weather stations on the ground for data collection, weather balloons going high into the atmosphere multiple times daily per location, Doppler radars tracking precipitation…
That's part of the story.
The real reason why this is a domain where AI models can thrive is actually because we already have extremely complex, well-developed, physics-based simulations of the atmosphere which can take all of these observations and do useful things with them. So the task we currently ask AI models to do with regards to weather forecasting is actually much, much simpler than what you're proposing - we're simply asking the AI models to emulate what these existing models are capable of doing.
Actually doing useful things with the observations alone is a different story altogether. It's the fact that we've been developing computer simulations of the weather and climate since the 1950's that is the key enabler here.
Re: Google says AI weather model masters 15-day forecast
#123It takes 8 minutes to produce a 15 day forecast. That's actually quite a long time for an AI model. I should probably read the paper to find out why but does anyone know? Is the model predicting the weather in 10 minutes time and just run iteratively 2000 times for a 14 day forecast?
> That's actually quite a long time for an AI model.
Sure, but it's several orders of magnitudes smaller than the parent, physics-based weather model it's emulating, which may take 2-3 hours of wallclock time on an HPC system with a few thousand cores allocated to running it.
> I should probably read the paper to find out why but does anyone know? Is the model predicting the weather in 10 minutes time and just run iteratively 2000 times for a 14 day forecast?
Basically, yes. It's run autoregressively but in 6-hour forecast intervals. The added complexity is the iterative nature of the diffusion process used to generate each of those forecast intervals.
Re: Google says AI weather model masters 15-day forecast
#124Obviously this team knows way more about this donain than me but I have to ask, wouldnt this only be able to predict weather which is in line with past weather patterns/indicators? I can imagine a weather analyst might be able to see "between the data" and recognise when some anomaly might be brewing, but an AI model would not
Yup. There's fundamentally no way to automatically verify predictive accuracy, the assumptions in ML papers about such accuracy is (the almost always false presumption) that there are no distributional shifts in the data generating process. Here, since weather certainly changes its fundamental patterns over time, there is no way of reliably predicting out-sample performance. It's highly likely that in 1-2 years time…
> Here, since weather certainly changes its fundamental patterns over time, there is no way of reliably predicting out-sample performance.
This seems overly pessimistic.
The weather doesn't change its fundamental patterns over time; those are governed by the fluid dynamics of the atmosphere, and are largely forced (to first order) by things like the amount of solar radiation received by the sun and the the configuration of the continents - neither of which change much at all on timescales of a few thousand or tens of thousands of years. The total manifold of "realistic" weather patterns - especially trajectories of weather patterns conditioned on one or more prior weather sates - is vastly smaller than it would seem at first glance (there's only so much variation in how a Rossby wave can evolve and there is clear asymptotic behavior with regards to amplitude).
I think if you wanted an "ultimate stress test" of an AI weather forecasting system, you could run a a high-fidelity general circulation model equilibrated to the current climate freely for a several thousand year cycle, and randomly draw initial conditions to branch off a 10-day forecast. It shouldn't be _perfect_ (there is likely meaningful skew between the atmospheric state trajectories that arise in this free running simulation compared to reanalysis cycled over the historical observation record for a few decades), but the trends in error growth should be meaningful and directly interpretable in the context of a real-world forecast.
Re: Google says AI weather model masters 15-day forecast
#125Earlier quoted context omitted.
do you want a causal weather model or one that can predict the weather well?
When climate change occurs (which it is), we're going to want a causal one so we can actually make a forecast instead of predicting only based on past (unchanged) data.
Nothing prevents people from training new models.
And note that these new models based on machine learning are already better at predicting extreme events. This is because existing models are not built entirely from first principles but rather include a lot of heuristics to describe important phenomena like cloud formation and albedo effects. That means that traditional models are just as rooted in weather-as-it-was as the machine learning models are. The big difference is that it takes a lot of work to identify the dependencies in traditional models while it takes less work to retrain the machine learning model.
Re: Google says AI weather model masters 15-day forecast
#126They can say what they want, but I get rained on by surprise rain more than I ever have in my life, now that I'm practically forced to use the built-in Google weather due to them and Apple catching and killing all the good weather apps.
https://www.weather.gov/ It you are in the US and while it still exists. (I found out about it when private weather companies were mad they were giving out forecasts for free.. )
Even better: www.weather.gov/{zip_code}
Re: Google says AI weather model masters 15-day forecast
#127Earlier quoted context omitted.
A hard science Nobel is very different from the peace prize, obviously.
> obviously It's not obvious to me. Care to elaborate? The only one that strikes me as "obviously" different is the Nobel prize that isn't really a Nobel prize, the one for economics.
It is not obvious to me either.
I will point out that Physics and Chemistry are awarded by the Royal Swedish Academy of Sciences while the Peace Prize is awarded by a separate Norwegian committee, so it is plausible that one would be more respectable than the other. Literature is a completely different institution as is Physiology/Medicine.
The Peace prize and Literature prizes have far more questionable winners in my view than the Physics and Chemistry ones.
Economics wasn't added until the 1970s, and has had some extremely suspect winners.
Re: Google says AI weather model masters 15-day forecast
#128Turns out the Google AI's 15-day forecasts are for the weather in Mountain View.
Which I can forecast 15 days out, too.
Re: Google says AI weather model masters 15-day forecast
#129Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.
Lemme guess:
Night and morning low clouds, burning off in the afternoon.
Source: lived in Los Angeles for a dozen years, saw the weather forecast a few times
Re: Google says AI weather model masters 15-day forecast
#130This is great from a practical standpoint (being able to predict weather), but does it actually improve our understanding of the weather, or WHY those predictions are better? That is my issue with some of these AI advances. With these, we won't have actually gotten better at understanding the weather patterns, since it's all just a bunch of weights which nobody really understands.
I’m by no means an expert in weather forecasting, but I have some familiarity with the methods. My understanding is that non-“AI” weather models basically subdivide the atmosphere into a 3d grid of cells that are on the order of hundreds to thousands of meters in each dimension, treat each cell as atomic/homogeneous at a given point in time, and then advance the relevant differential equations deterministically to fo…
FWIW, the UK Met Office's models are described here: https://www.metoffice.gov.uk/research/approach/modelling-sys...