Looking at the variance as a single datapoint doesn't capture temperature information very well. A single rare outlier data will make a city look bad even if most days are milkd.
I hacked together a little program to try something different. My rule was to look at the daily average temperature for a bunch of cities on a single year. Then count up the number of "good temperature" days which I defined to be within 60°F-80°F. The best cities are the ones with the most good days.
Based on that, looking at US cities, the top and bottom ten are:
282 : San Diego, California
256 : Los Angeles, California
236 : Orlando, Florida
203 : Honolulu, Hawaii
202 : Jacksonville, Florida
199 : West Palm Beach, Florida
193 : Tampa St. Petersburg, Florida
189 : Asheville, North Carolina
179 : Charleston, South Carolina
...
92 : Duluth, Minnesota
91 : Casper, Wyoming
89 : Concord, New Hampshire
89 : Great Falls, Montana
87 : Sault Ste Marie, Michigan
80 : Caribou, Maine
76 : Salt Lake City, Utah
64 : Anchorage, Alaska
63 : Fairbanks, Alaska
41 : Juneau, Alaska
That looks about right to me.
I hacked together a little program to try something different. My rule was to look at the daily average temperature for a bunch of cities on a single year. Then count up the number of "good temperature" days which I defined to be within 60°F-80°F. The best cities are the ones with the most good days.
Based on that, looking at US cities, the top and bottom ten are:
That looks about right to me.