I am trying to create a program that calculates the ideal climate based on a set of inputs and weights. Something similar to 400 cities but based on more climate based options that the user can configure. Some example questions;
- What is your ideal daily mean temperature, answer must be between 0-40(celsius) ? how important is this, answer 1-5 with 5 being the most important ?
- How important is it for you to be near the mountains, answer 1-5 with 5 being the most important ?
One of the problems I am having is with the sunshine duration metric as calculated by the Campbell–Stokes recorder.
DISCLAIMER 1: All stats below are approximations / anecdotal DISCLAIMER 2: I may need some statistical calculations explained.
Taking some rough figures from wiki, Los Angeles has 3254 hours of sunshine and London has 1633 hours per year. Maximum sunshine duration in a day is approximately 4380 hours giving LA a sunshine 74% of the days on average and London sunshine 37% of the day on average so we could roughly say that LA has 2x the sunshine hours of London
This does not make sense to me. I want to initially create a metric that more accurately represents the quality of weather. I would then like to refine it to give a metric (configurable) like 'good days' that may need to pass params like > 25C, sunny > 70% of day, cloud coverage < 20%, UV strength > 4.
For example (my brother lives in LA) in August this year there were 25 days in LA that were 'sunny days', lets say sunny for > 70% of the day. In London there were 4, giving values of 83% and 13% approx so we could roughly say that LA has 6X more sunny days per month than London.
My questions are;
- Why do the number of sun hours in London seem so high when anecdotally the difference is much much larger.
- Where can I find data that is more suitable for my project or alter the data on sunshine hour to suit it.