You don't need any of that, all you need to do is collect personal weather station data and use it to statistically post-process/correct numerical model output

You don't need any of that, all you need to do is collect personal weather station data and use it to statistically post-process/correct numerical model output that is already freely available. This has already been done several times over in the weather industry; it doesn't lead to much of an improvement in forecast quality. Trying to run your own model with nearby inputs is kind of pointless because to actually assimilate measurements in your neighborhood, you'd have to run at an absurdly high resolution that makes it way too expensive to run an operational forecast as a commodity. You'd be limited in the size of the forecast domain, so within a few hours (maybe a day at most), your forecast would be dominated by boundary conditions from the parent regional/global models you force it with, and there would be no further propagation of information from your local observations to refine the forecast.