If chaos is not a problem for computation, why do we always hear weather simulations needing better and better supercomputers? If simulating/computing chaos is

If chaos is not a problem for computation, why do we always hear weather simulations needing better and better supercomputers? If simulating/computing chaos is just about getting precise enough initial measurements, then that wouldn't seem to be a need for weather simulating right? I was thinking along the lines of running current observed data backwards to fine tuned initial conditions. That must require lots of computational power. Are we sure quantum computers and quantum algorithms wont speed this part up. That has to be somwewhat isomorphic to factoring large numbers, which I thought QC does have a potential advantage. But maybe chaos is distinct from factoring, I don't know much about how it would be modeled computationally. I realize most of the battle is getting proper initial conditions. But quantum computing is also coming at time when quantum sensing is growing. To me with quantum computing speed ups and quantum sensors, we have the two ingredients necessary to make progress on chaotic systems. Better initial conditions and better computational methods. That was my thought. Sorry for the ramble