This makes me wonder: How far back can weather be reliably predicted?
Google says AI weather model masters 15-day forecast
191–200 of 216 posts
Re: Google says AI weather model masters 15-day forecast
#192Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.
Seriously. Let's see an accurate forecast for Cleveland, Ohio. Even local forecasters can barely get the next day correct on any sort of consistent basis.
Re: Google says AI weather model masters 15-day forecast
#193This makes me wonder: How far back can weather be reliably predicted?
Does anyone have a nice website for looking at past weather? I often could use it.
Re: Google says AI weather model masters 15-day forecast
#194Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.
Here's the paper: https://www.nature.com/articles/s41586-024-08252-9
It was trained on global data, and makes global forecasts.
Re: Google says AI weather model masters 15-day forecast
#195Why not 16?
Re: Google says AI weather model masters 15-day forecast
#196Earlier quoted context omitted.
What a weird take. How is google using that much energy? Is it just for their own operations or are they providing a good or service that billions are consuming? By using a computer you are a consumer and are complicit. Your overall contribution might be small but it’s the same exact behavior that is absolutely part of the climate change problem.
You have zero knowledge of my consumption or my life. You also know nothing about my environmental care or actions. You’re extrapolating from my use of a computer to post comments to assume my use of energy is a net negative, which is as bad faith as it is wrong. It is possible to live in such a way that you reduce your impact to a minimum in some areas and then do a net positive in other. Additionally, the number of…
stop posting, bro - you're literally killing the planet. turn off your device and send it away to be recycled, so someone else's descendants 100 years from now will have a few extra grams of copper. dig a hole somewhere in the wilderness and live out the rest of your life consuming nothing but grass and rainwater for sustenance. also try to breathe in moderation - you exhale CO2 every time, bringing the doomsday a bit closer, inch by inch.
Re: Google says AI weather model masters 15-day forecast
#197This makes me wonder: How far back can weather be reliably predicted?
1: Previous conditions in fluids cannot be determined with any kind of accuracy except for really obvious cases like "did this wet ground come from a cloud?" or laminar flows (https://www.youtube.com/watch?v=p08_KlTKP50). Since weather is fluid mixing at high speeds with low viscosity, there is a huge amount of turbulence and entropy. Entropy means systems are not time-reversible.
2: Can we predict weather 2000 or 1M years ago based on estimates of temperature and geography? Yes, pretty reliably. Vegetation and albedo are some of the biggest variables- plant transpiration puts huge amounts of water into the air and changes surface temperatures. But we have a pretty good idea of the geography, and relatively small changes don't have a huge impact on general weather trends.
3: Can we predict the exact weather on a day 100 years ago, given available measurements? No, not really. Without satellites you need radar, and without radar you need weather balloons. Coal burning also had impacts on weather. Low pressures at the surface can tell you that the weather may get worse, but it doesn't tell you where its coming from or what the higher airflows are doing.
Re: Google says AI weather model masters 15-day forecast
#198Earlier quoted context omitted.
> Weather and climate models have their own physics, which at the very least means that the solution is physical for the universe that particular model inhabits. The boundary conditions are parameterized, and those can be tweaked as climate and land use changes. That really isn't true these days. The dynamical cores and physics packages in numerical weather prediction models and general circulation models have more-o…
> That really isn't true these days. The dynamical cores and physics packages in numerical weather prediction models and general circulation models have more-or-less converged over the past two decades. Ah, well, I did stop studying GCMs about 20 years ago so perhaps I should shut up and let other people post. I appreciate the detail in your explanation here, and I wouldn’t mind a link to papers explaining the curren…
I'm not sure I can point you to a single reference, but a good starting point would be the UK Met Office's "Unified Model", which provides a framework for configuring model simulations that scale from sub-mesoscale rapid refresh (e.g. the UKV system) to traditional global modeling (e.g. MOGREPS) and beyond into climate (latest versions of the Hadley Centre models, which I think the current production version is HadGEM3).
Re: Google says AI weather model masters 15-day forecast
#199Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.
There's a little cautionary story I like to tell about predictions and probabilities There is a man living near a volcano. He has put up a sign outside his house for travelers, proudly declaring: "Will not erupt today. Accuracy: 100%." One night, after thirty years of this, the volcano erupts for a few hours at night, oozing magma on its opposite side. The next morning, the man is grateful that his house is fine, but…
Re: Google says AI weather model masters 15-day forecast
#200This 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…
> It’s not hard to imagine a neural net learning a more efficient way to encode and forecast the underlying physical patterns.
And that is where your understanding breaks down.
What makes weather prediction difficult is the same thing that make fluid-dynamics difficult: the non-linearity of the equations involved.
With experience and understanding of the problem at hand, you can make some pretty good non-linear predictions on the response of your system. Until you cannot. And the beauty of the non-linear response is that your botched prediction will be way, way off.
It's the same for AI. It will see some nicely hidden pattern based on the data it is fed, and will generate some prediction based on it. Until it hits one of those critical moments when there is no substitute to solving the actual equations, and it will produce absolute rubbish.
And that problem will only get compounded by the increasing turbulence level in the atmosphere due to global warming, which is breaking down the long-term, fairly stable, seasonal trends.