Why cost-of-living rankings ignore the weather — and what changes when they don't
Two cities can sit beside each other on a cost table and be nothing alike to live in. The tables have simply left out the variable everyone actually cares about.
By Adam Simmons-Spaans · Updated 2026-09-23
The variable every cost table omits
Cost-of-living tools rank places by what a month costs. Weather services rank them by climate. Nobody joins the two, so “cheapest place to live” quietly means “cheapest place, weather ignored” — and that is a materially different list from the one anyone actually wants.
A comfortable day here means a daily maximum between 18 and 27 °C with under 1 mm of rain, counted from ten years of reanalysis. It is a stated preference rather than a fact, and it is temperate-biased on purpose — so the average high and the rainfall sit beside every figure for anyone who disagrees with the band.
What the join actually shows
Lisbon records 130 comfortable days a year on that definition; Chiang Mai records 19, because its daily maximum sits above the band for most of the year. Chiang Mai is substantially cheaper. Whether that trade is worth making is exactly the judgement a single cost figure hides.
The more useful cut is monthly rather than annual. An annual total flattens a place that is pleasant for four months and punishing for eight into the same number as somewhere mild all year, and the real question people have is seasonal: where should I be in January?
Seasonality is the part that actually changes decisions
The people who get this wrong are rarely choosing between somewhere pleasant and somewhere grim. They are choosing between two places that are both fine on an annual average and completely different in the month they are actually going to arrive.
A northern European city and a Mediterranean one can land within a few days of each other on a yearly comfort count and be nothing alike in January, because one earns its total in a concentrated summer and the other spreads it. If the move is happening in winter, the annual figure is not merely unhelpful — it points the wrong way.
That is also why the seasonal view is worth more than the ranking. Somewhere with four excellent months is a strong answer for a fixed-term stay and a poor one for a permanent move, and only a month-by-month breakdown lets you tell which you are looking at.
What the comfort band does not capture
Temperature and rain are the two variables with clean, complete, comparable global coverage, which is why they are the two used here. They are not the only things that make a place pleasant to be in, and it would be dishonest to imply otherwise.
Humidity changes how a given temperature feels by a wide margin. Daylight hours matter enormously at high latitudes and are invisible in a temperature series. Air quality is a separate dataset entirely, reported elsewhere on this site precisely because folding it into a comfort score would hide it. None of that is in the figure.
Read it, then, as one measured input rather than a verdict on where is nice — useful mainly because it is measured consistently everywhere, which is more than can be said for most claims about weather in a relocation guide.
The honest caveat
Dividing cost by comfortable days gives a tidy figure and a misleading impression of precision. The climate half is measured. The cost half is modelled, and its error against published housing figures has been measured at between 0.64× and 1.61× depending on the country. A modelled cost over a measured climate is not a measured ratio, and it is not presented as one.
Used as a shortlist rather than a verdict, it does something no free tool does: it stops you moving somewhere cheap that you will not want to go outside in.
See the climate rankings
Every figure above is computed from published data and recomputed on each build. Run it against your own numbers rather than taking the example: see the climate rankings .
About the author
Adam Simmons-Spaans, Founder, Geo-Parity. Adam builds Geo-Parity single-handedly: the engines, the datasets and the fetchers that refresh them. Every figure on the site comes from a published source — World Bank, IMF, OECD, Eurostat, WHO, HUD, Cloudflare Radar — and where a number is modelled rather than measured, the page says so. More about the site.