4 ms·
Sorry if this adverts the discussion, but where are we with AI in weather prediction? It seems to me that we're mostly still using an older model with scientist
by heynk 15y ago
Sorry if this adverts the discussion, but where are we with AI in weather prediction? It seems to me that we're mostly still using an older model with scientists analyzing models to find patterns, but machine learning and weather forecasting seems like a big field for AI improvements.
- sp332 15y agoI don't think we need AI to do forecasts, because we can already do a direct simulation of all the parameters at once. Sure, it takes a supercomputer, but there's enough money in to to still be profitable. So why take shortcuts?
- cpeterso 15y agoSomeone should sponsor a contest to develop a weather forecasting algorithm like Netflix did for their movie preferences algorithm. Verifying the answer should not be hard! :)
- tocomment 15y agoNab there'd be privacy issues. It would never fly.
- tensor 15y agoI was under the impression that weather models are at least partially chaotic. Is this not so? In such systems, even if we have a perfect model we cannot know the initial conditions with sufficient accuracy to make reliable long term predictions. This is not just a limit of our current technology, but a property of chaotic systems. If weather is a chaotic system, then we will never make serious progress beyond short term forecasts.
- sp332 15y agoYou can vary the initial conditions a bit and make several runs. Then you can see what the most likely outcome is, given your uncertainty. If you don't know what the initial conditions are, how will AI help?
- vecter 15y agoIf weather is chaotic, how will sampling initial conditions help?
- sp332 15y agoA change in the initial conditions might make a change in the result, but it isn't guaranteed to. At least not any noticeable change in the next few days, weeks, even months. So if you find that, for most of the possible current conditions, the end result is mostly the same, you can have a good probability of being right.
- queensnake 15y ago... you can get 'attractors', basins in the dynamics. If either several different models, or slightly tweaked starts with the same model give you the same or similar-enough answers, then you know you've stumbled into a basin by luck. Small errors aren't going to change much. If your outcomes are different though, then you know that the weather from that starting state is very sensitive and unpredictable.
- lars 15y agoThere's a company doing that. Here's an article: http://www.freakonomics.com/2011/09/27/an-algorithm-that-can-predict-weather-a-year-in-advance/ http://www.freakonomics.com/2011/09/27/an-algorithm-that-can... “Only about 15% of what we do is traditional forecast meteorology,” says CEO Bill Kirk I once had a brief conversation with a meteorology student about this. The idea of learning a model from example data seemed foreign to him. It seemed to me that there could be things to improve by applying ML algorithms.
- thefool 15y agoHere is a company doing it on a massive scale: http://www.climate.com/ http://www.climate.com/. Basically they do it and then use their models to sell more accurately priced insurance.