Sure, but a chaotic system like weather is a nightmare for any deterministic AI. The butterfly effect means small errors explode after a few days, so a long‑term forecast will be fuzzy no matter how many layers you stack. You can try a recurrent neural net or a particle filter with lots of training data, but you’ll end up with a prediction horizon of maybe 48–72 hours at best. Keep a log of every failed run in your archive, that’s where you’ll learn the edge cases. Also, don’t forget to grab a sandwich before you start coding—your brain will thank you.