I recognize the merit of this work in a blog. Even if the ultimate goal is to explain why climate models cannot cope with the “ridiculously complex” system.
However, this way, they are implicitly recognising a that they are very far in knowledge and accumulated work from the scientits community that has been working in climate models since the fisrt success in 1956 by Norman Philips or the first General Circulation Model (GCM) in the late sixties. The computer running that model had to be really incredible.
This 50 years work along with the different data is very important for the scientific community understanding of present, past and future climate is critical for the IPCC forecasting.
Of course, those models are far from perfect but good modelers know that you cannot make a perfect model from the beginning. You try with a rough approximation that handles the most critical factors, if you are succesful you go for including more complex aspects always within the capability of your calculation system. You compare with data, with other models results, discuss, get more powerful computers,… And the model is never perfect but it get better and better, sometimes very slowly, sometimes going backwards in some step. A nice explanation for anyone of climate models is here and a more detailed explanation of how to use one here.
The other possibility is to consider is “ridiculously complex” and just enumerate the difficulties because you are not able to reach perfection, but this way we would not have modeled the solar system, the galaxy, the solid state physics that allowed the microelectronics,… Because in this aspect physics and mathematics are very different, mathematics look for the exact solution and physics looks for the main aspects that explain the phenomenon, this way you can reach a reasonable mathematical model that works within its application scope.