Sure, but we know it's near equilibrium, at least on human time scales, or the climate would not be stable enough for humans to evolve. So it's not chaotic like weather is chaotic.
I politely disagree, but my non-expert arguments shouldn't carry much weight. Here's a quote from a 2018 IPCC document instead:
"The climate system is a coupled non-linear chaotic system,
and therefore the long-term prediction of future climate states
is not possible. Rather the focus must be upon the prediction
of the probability distribution of the system’s future possible
states by the generation of ensembles of model solutions." [0]
I'd kind of like to dive in to the topic of whether an "ensemble of model solutions" is a fair and sufficient sampling of the problem space to trust the statistics, but I don't have enough details. However, I have done particle filters before, and when you have more than a few parameters to estimate, you need a shit-ton of particles before you can trust the statistics you get out. And that's with well behaved and fairly linear systems.
We can't predict what will happen when tipping points are tripped, but while we're near the current (dynamic) equilibrium, we can use perturbative methods to predict what will happen with relative small forces, such as doubling or trippling the amount of CO2 in the atmosphere, i.e. global average temperatures will rise.
I politely disagree, but my non-expert arguments shouldn't carry much weight. Here's a quote from a 2018 IPCC document instead:
I'd kind of like to dive in to the topic of whether an "ensemble of model solutions" is a fair and sufficient sampling of the problem space to trust the statistics, but I don't have enough details. However, I have done particle filters before, and when you have more than a few parameters to estimate, you need a shit-ton of particles before you can trust the statistics you get out. And that's with well behaved and fairly linear systems.[0] https://www.ipcc.ch/site/assets/uploads/2018/03/TAR-14.pdf