Chaos theory is about systems where tiny deviations in initial conditions cause large deviations in what happens in the future. My impression (though I don’t know much about the field) is that, assuming some model of a system (e.g. the weather), you can prove things about how far ahead you can predict the system given some uncertainty (normally about the initial conditions, though uncertainty brought about by limited compute that forces approximations should work similarly). Whether the weather corresponds to any particular model isn’t really susceptible to proofs, but that question can be tackled by normal science.
Chaos theory is about systems where tiny deviations in initial conditions cause large deviations in what happens in the future. My impression (though I don’t know much about the field) is that, assuming some model of a system (e.g. the weather), you can prove things about how far ahead you can predict the system given some uncertainty (normally about the initial conditions, though uncertainty brought about by limited compute that forces approximations should work similarly). Whether the weather corresponds to any particular model isn’t really susceptible to proofs, but that question can be tackled by normal science.