41 ms·
Yet another example of people blaming chaos when it’s not the relevant limiting factor. If chaotic behavior manifested at a sufficient level on the 18 month tim
by ummonk 2y ago
Yet another example of people blaming chaos when it’s not the relevant limiting factor. If chaotic behavior manifested at a sufficient level on the 18 month time scale to preclude forecasting El Niño, neither the back of AI models nor the new improved physics-based model would be capable of making such predictions.
- zer00eyz 2y ago> Yet another example of people blaming chaos This isn't how this works, at all. We are talking about large scale systems on long timelines that have massive momentum and energy. Predicting something 18 months out isn't hard (Florida will have a hurricane in the next 18 months). Predicting "will crops get enough water in the mid west in any given year" is impossible because of "chaos" because of complexity. This result is not surprising to any one who pays attention to how the math for these systems works.
- ummonk 2y agoPrecisely the point. Chaos wasn't impactful on the relevant timescale for large scale dynamics like El Nino, and shouldn't be blamed for our previous inability to predict beyond 12 months.
- defrost 2y agoChaos comes in degrees, people still catch tumbling tennis rackets despite the Dzhanibekov Effect | intermediate axis theorem. Not every horseshoe map is folded to infinity and beyond. Creeks flow predictably enough and yet still contain turbulent vortexes. Dynamic systems aren't an all or nothing proposition wrt chaos, there are often contained embeddings an portions that are difficult to predict but not impossible subject to error bounds.