The Köppen–Geiger climate classification made simpler (I hope so)

[TheSquareRootOf2]

I have thrown together a temperature generator, but instead of an expert systems/analytical approach I just built a neural net classifier for temperature bands that takes the elevation map as input and outputs January and July temperature band maps. I haven't put it out publicly on Github or anything yet because 1) it's pretty slow still (takes ~45 minutes to run on a 4000x2000 image) and 2) I wasn't sure under what conditions I'm allowed to distribute the training dataset I trained the classifier on (that's become more clear recently, but I'm somewhat novice at all the license details and so I've been reluctant to proceed).

That's an interesting approach! How did you manage to feed your neural network enough standardized temperature maps to make it effective?

There's also a software program called Clima-Sim, from Weather Graphics, which is aimed for simulating Earth but can apparently also be finagled to work for other arbitrary geographies and lets you edit a variety of relevant variables including axial tilt and so on. From what little I know about it it actually crunches a bunch of the equations to compute climatological predictions given those input items. That said, it's not free and I don't know all that much about it in detail, and it might be tricky to use in the sense of requiring a lot of climatological knowledge to get the best results. You can search it online if you're curious about it.

Yeah, I've heard of it and gave the demo version a try, but not being able to save your model is too much of a drawback for me. Essentially, this is a model like this -although simplified- I'd like to build. I have no deep climatological knowledge, but I've got some understanding of fluid mechanics and thermodynamics so I guess it's a start.

I have done some work on a mathematical model for temperature here. I took a lot of inspiration and knowledge from this thread but I'm not using GIMP or PS to do the actual work, so there would have to be some tweaks. But I've found this gives a reasonable baseline for temperature and a smoother, more precise transition between zones. Exact numbers can also help if for whatever reason you're interested in the temperatures at other times of the year and yearly precipitation/temperature values. I hope this helps somewhat!

Wow, how come I did not find that blog earlier? The research paper linked in the first article is also particularly interesting, since it pretty much follows the approach I had in mind and goes much further in depth than I could on my own.