The creators of CCWeatherGen unfortunately never shared their source code despite multiple attempts to contact them. Also, their papers unfortunately were not enough for me to reimplement their methods in a Python environment. Additionally, I have come to realize that the methods used in the tool were not very sophisticated in that they were not accounting for the change in weather variation well (they we’re mostly concerned with accounting for the average shift in temperature for the worst-case secenarios).
The state of the art these days is to use methods like that currently developed in the open source Indra project:
However, making use of Indra takes a huge time investment and at least 10 TB of hard drive space to hold the relevant parts of the IPCC dataset. So, while the CCWeatherGen Excel tool may seem like it takes a lot to get running, it’s a lot less than Indra and it is still probably the best thing that I can recommend right now.
I know that Parag Rastogi who developed Indra is currently trying to make a web service to better make use of his work (and so he has some revenue stream to continue supporting the project). I hope to help him make some GH components connecting to such a service if he gets it up and running.