Help/Suggest: Climate Metric/Score

[isaacbinding]

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

[isaacbinding]

What's an appropriate amount of time to wait before bumping.

Yolo. Bump.

[isaacbinding]

Incoming helpful reply in 3...2...1...

[Ellinwood]

This is too subjective of a question to answer.

If you want a "general idea" of the ideal climate, conduct a survey of the "general" people. Asking such questions on a weather-centric board, which is biased towards cold and snow due to the nature of the board and its 10+ years of existence, is not the best approach to making a coherent solution to the topic at hand.

Or just move everyone in the world to southern California and be done with it.

[isaacbinding]

17 hours ago, Ellinwood said:

This is too subjective of a question to answer.

conduct a survey of the "general" people.

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.

[Ellinwood]

5 minutes ago, isaacbinding said:

the creation of that formula is subjective

Exactly. Different variables mean different things to people, would get weighed differently, and would be included/not included based on who is giving the suggestions. The result could mean a high score for a place like Denver and a very low score for a place like Los Angeles, or vice versa. Hence my questioning of using a weather board biased toward cold and snow to make a standardized index.

Now, if you wanted to make several standardized indexes for different groups of interests (ie loves cold+snow, or wants lots of sun+warmth), that could be more interesting.

If this is just a thought experiment for making one standardized formula, then it's fine. I can dig it being a "fun problem to think about." The "Help/Suggest" in the topic and the general tone of the original post implies that you might try to implement this in some form or another.

[isaacbinding]

Will probably use the Koppen climate classification instead of reinventing the wheel.

[adamovic]

I have a similar problem and stumbled upon this question. 
We tried a machine formula based from the data we can catch from Weatherunderground Planner.

This is how we setup the weights:
https://www.numbeo.com/climate/indices_explained.jsp

And than we sumbled to this problem:
https://www.quora.com/How-reliable-is-numbeo/answer/Dzikra-Handika?srid=TRA

So we have to change our formula. 
Opinions about how our formula can be improved are welcomed, as we cannot get survey for climate results in less than 12 months (and have to change formula this month).

 

 

[MegaMike]

I agree with Brony Ellinwood. This would be a very subjective model that would vary from person to person.

That being said/written!!! 

I'd use variables that correlate weather to physical and psychological health. Therefore, you'd have a standardized, universal method to calculate "what the weather is like" at a certain location via health.

Some variables that I'd consider:

Coefficient of Pressure (fluctuates blood pressure///can cause joint pain///headaches///sinuses)

Coefficient of Temperature (narrowing of blood vessels///dehydration///hypothermia///heart attacks)...

Coefficient of Temperature wrt (with respect to) Time (may cause illness [could look at Pressure and DP Temp change too for this])

Coefficient of Dew Point Temperature (difficulty to breath/cool off under high humidity)

Coefficient of Heat Index (Combination of Temp and DP Temp [might be unnecessary or vise versa])

Coefficient of FROPAs (thinning and thickening of blood vessels via cold or warm fronts [diabetics])

Coefficient of Cloud Cover (depression///migraines on bright days)

Coefficient of Precipitation (i.e... 'Cloud Cover')

Coefficient of Precipitation Type (shoveling snow can cause deaths for a number of reasons///ice can cause fatalities due to knocking out power (exposure), driving accidents, etc...)

Coefficient of Air Quality (respiratory problems[asthma])...

Coefficient of Insurance Claims (from weather related damages)

Sum Value Coefficients (one, overall value to determine "what the weather is like" wrt health)...

The Köppen climate classification categorizes regions of similar climate. It doesn't numerically calculate the livability of a given location. If you can derive something to numerically portray livability, you'll create a model that's useful/helpful imo. Admittedly, if you choose to create a model similar to what I mentioned above, it will likely resemble the Köppen climate classification. 

I hope my template gives you some ideas!!! 

You can always choose to create a model that determines the livability wrt weather enthusiasts, snow lovers, etc... basically anything. This is where things become subjective though.