The only problematic thing I can see here is the granularity of your report.
Your rain chances are 50% because the conditions at your station say that half the time these conditions exists it rains at your station. From what I remember about the weather report (when I was a radio announcer), the likelihood at each locality also figures into that percentage.
For a larger forecast reporting center (TV, NWS, Radio), the area is much larger. For them, the percentage chance of rain isn't just the likelihood that the rain will fall at a specific location, it's that "within the sound of my voice", the rain will fail as a percentage.
So, if 20% of the listening area is "100%" going to get rain, the percentage was 20%. If it's 50% in 50% of the listening area, it was "30%" (we always rounded up to 10s instead of using the things like "20-30%"). The trick, then, is for your prediction aggregater to take all of the "50%"s and bring them into a model that takes your data and the data from other stations like yours pull it into a forecast that works for them. The larger the reporting area, the more stations would need to be contacted.
Other than that, this has been a fascinating process to watch.