I'm working on an application makes calls to a weather API for different coordinates across the United States.
Instead of getting the weather at each and every point, I'm planning on clustering coordinates together based on how close they are to each other. That way, I can take an average of coordinates and get a single weather forecast that is representative for the group.
This raises the question, how close do these points need to be? Would a cluster of radius 50 Miles be sufficient? What about 250?
I'm really only gathering these features from my Weather source:
- Category (Rain, Cloudy, Hail, etc.)
I don't really need a high degree of precision. In fact, the coordinates I'm using are going to have a 25-50 mile variation from their "true position."
I'm not a climate scientist, so I apologize if this question is a little rudimentary. I just wanted a second opinion on the topic so I can balance the trade-off between number of API Calls and fidelity to regional weather.