Climate preference finder: find where to live by weather criteria
Problem
People considering relocation or travel have very specific climate preferences (e.g. snow in November-January, long arid summers, stormy autumns, temperature bands per month) but no tool maps those preferences to real-world locations. The few websites that attempt this account for only a couple of variables, so users resort to manually comparing Wikipedia climate tables.
Opportunity
A web app that lets users tune sliders and toggle seasonal weather criteria, then ranks countries/regions on a map that match their personal climate profile, powered by historical weather station data.
Market analysis
The gap is real but narrower than the Reddit poster thinks: myPerfectWeather already maps US places against adjustable temperature, precipitation and snowfall filters, and BestPlaces publishes per-city climate stats with a comfort index. What neither does is match on monthly or seasonal criteria (snow specifically Nov-Jan, stormy autumns, per-month temperature bands), which is exactly what the requester wants and is a genuine data-pipeline edge over annual-average filters.
Market · Relocation planners, retirees, remote workers and climate-migration researchers; recurring organic demand (NOAA's Climate Normals tools and myPerfectWeather both cite relocation planners among their users).
Pricing · Comparables are free or ad-supported (BestPlaces, myPerfectWeather, NOAA); monetization would come from relocation affiliate leads (moving, insurance, real estate) rather than subscriptions.
Pros
- + Monthly-band matching is a real differentiator over annual-average filters like myPerfectWeather.
- + NOAA Normals and ERA5 give free, station-grade historical data; a static site with precomputed scores is cheap to run.
- + Strong SEO potential: every 'best place to live if you like X' query is a landing page.
Cons
- − myPerfectWeather and BestPlaces already own the head of this niche with established traffic.
- − Global coverage (ERA5 processing, worldwide geocoding) is a significant data engineering lift for a solo builder.
- − One-and-done usage pattern: users find their answer and leave, which suits ads/affiliates but kills subscription revenue.
- − 'Stormy autumns' and similar fuzzy criteria are hard to formalize into indexable metrics.
Existing / similar tools
Source
r/Doesthisexist (Reddit)
The build strategy matters more than the idea here. The winning shape is a precomputed matching index, not a live query engine: score every populated place once against criteria vectors (monthly temperature bands, snow days per month, precipitation seasonality), store the results as static JSON, and let the frontend do slider-filtering client-side. That keeps hosting near zero and makes each city a crawlable, shareable page, which is how this kind of tool actually acquires users. The non-obvious risk is data licensing: NOAA Normals are free for US stations, but credible global coverage means processing ERA5 or similar reanalysis data, which is a different commitment in both compute and debugging. Starting US-only with the monthly granularity nobody else offers is the honest MVP.