I'm interested in predicting when the local schools will be closed due to snow and other winter weather. I have a list of school closure dates and a rough sense of the criteria used to determine the closing of schools including, temperature, wind, precipitation, and their interactions. Using a statistical technique (classical, Bayesian, or machine learning), I'd like to use both the actual weather the day before (t-1) and the predicted weather for the the day (t) to predict the county's decision.
I want to use the predicted weather at t and not the actual because that's the information known to the deciders when they have to make their decisions. For the actual, realized weather for t-1, I was planning on using the NOAA API. But I'm at a loss on where to find weather prediction data. While I could do what @MarkRovetta suggests in the question on Statistical weather prediction and roll my own prediction model, that is harder than using a database and my lousy prediction model won't compare with the National Weather Service predictions available to the country officials. At best that will act like noise that will reduce the quality of my predictions. My primary question is therefore what sources are available for local weather predictions at various lags to the realized weather?
Additionally, are there tables of the predictive quality of forecasts at various time horizons? If, for example, the daily weather was predicted with 99% accuracy by 4 am that day, maybe there isn't an important difference between the predictions and the realized values.