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isaacbinding

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About isaacbinding

  1. Will probably use the Koppen climate classification instead of reinventing the wheel.
  2. A surprisingly unscientific answer for a scientist, albeit a brony one. Conducting a survey of people -> subjective results Using the same formula on every city -> standardized objective climate score result As meteorologists, all I'm asking for are metrics that can be used to build said formula (and even suggest a formula if you're up to it). Yes, the creation of that formula is subjective, but that doesn't concern me because as long as that same formula is used across all the data, then all the resulting climate scores will be relative to each other and you can compare them. Which would be pretty cool. I'll start: perhaps ClimateScore = AverageAnnualLowTemp + Average(AverageAnnualHighTemp,AverageAnnualHighTemp), and then some other operation involving humidity, or perhaps rainfall. Or even % cloudy/sunny days in a given year. See? It can be a fun problem to think about.
  3. Incoming helpful reply in 3...2...1...
  4. What's an appropriate amount of time to wait before bumping. Yolo. Bump.
  5. Imagine you have a big list of cities and wanted to concisely get an idea of what the weather is like over there. If conciseness and speed wasn't a problem, you could look at a graph like this (below) for each city, but that's not fast. So what metrics would you need to accurately capture the climate of that area? Less is better, so all I can think of is: average lowest temp, average highest temp. Or maybe you could build a score/index using some formula that took into account Average Annual Cloudy Days along with Average Low/High Temps, maybe humidity too. Any other ideas? *Buzz* Times up. https://en.wikipedia.org/wiki/Köppen_climate_classification