These types of projects are great for stuff like home automation. I’m using to to improve my predictions for power generation (PV) and consumption (heat pump). Planning to is ergst to optimize home battery charging in the future.
(Disclaimer; open sourced a small go library for open meteo, but otherwise not affiliated)
In contrast to pirate weather, I am using compressed local files to more easily run API nodes, without getting a huge AWS bill. Compression is especially important for large historical weather datasets like ERA5 or the 10 km version ERA5-Land.
Let me know if you have any questions!
If you only want to analyse the weeks to get the date of last snowfall and how much power might be there, use the forecast API and the "past_days" parameter to get a continuous time-series of past high-resolution weather forecasts.
I've got a bunch of moving parts in my system, including realtime (5-minutely) energy pricing. If it looks like it's going to be cloudy tomorrow I put my thumb on the scales to make it more likely that my system will buy power from the grid to top off the battery so I can ride through any price spikes.
I don't have the stats chops to determine whether I'm actually saving any money with this approach, but it sure is a lot of fun.