: With the incredible technology that we have today, why is it still impossible to have 100% accuracy on predicting the weather?
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Basically, some things (even some very simple things) are “chaotic” – they can behave vastly differently over time if their starting conditions are changed by even the *tiniest* amount. That makes them inherently unpredictable. And weather is one of them.
Here’s [a computer model of three double pendulums](https://www.youtube.com/watch?v=pEjZd-AvPco). They start within a degree of each other, but just 20 seconds in they’re starting to do very different things. If you build an actual double pendulum, and try to make it do the same things repeatedly by starting it “in the same position” each time – you’ll fail, simple as that.
(Don’t fall into the trap of thinking that, well, it’s just a question of getting the start positions “close enough”. It’s tempting to think that, but it’s not true. Chaotic systems simply don’t work like that. Make THE smallest change you can conceive of to a chaotic system, and it is perfectly capable of behaving radically differently.)
Here’s [a TED video of another chaotic system](https://www.youtube.com/watch?v=vFdZ9t4Y5hQ), this time a (real) pendulum and magnets.
Those are *really* simple things. The weather, by contrast, is huge and massively complex. And it, too, is chaotic. To predict it perfectly, we’d have to have full, perfectly accurate data on every last thing that comprises it – every molecule of air, every photon arriving from the sun, whether or not you choose to slightly stir the air around you by scratching that itch on your nose…). Oh, and a perfect model of how it all fits together, of course. We have neither. What should actually be astonishing is just how well we manage to do with the very limited amount of actual data we gather.
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