open-meteo

1: Open-Meteo is an open-source weather API offering free, keyless access for non-commercial use. It combines global and regional forecasts, historical data, and specialized APIs, with privacy-focused service and self-hosting options. … open-meteo/open-meteo

2: Open-Meteo provides free, keyless weather data for non-commercial use, combining global and high-resolution regional models for forecasts up to 16 days and 80 years of history. Fast, privacy-focused APIs cover weather, air quality, marine conditions a… open-meteo/open-meteo

3: 🌤 Need weather data? Open-Meteo offers free, open-source forecasts for non-commercial use—no API key required. Get hourly forecasts, historical weather, air quality and more, powered by global and regional models. open-meteo/open-meteo open-meteo/open-meteo

G: Need reliable forecasts without the complexity? Open-Meteo offers a free, open-source weather API for non-commercial use—no API key required. Explore global forecasts, historical weather, air quality and more, or self-host the API. open-meteo/open-meteo

Open-Meteo: Free Weather Forecast API for non-commercial use (6.4k stars) What it does All text below is quoted directly from the project README. >Open-Meteo is an open-source weather API that offers free access for non-commercial use. No API key is required, so you can start using it immediately. Features: - Hourly weather forecast for up to 16 days - Global weather models with 11 km resolution and regional models with resolutions as fine as 1.5 km - Weather model updates every hour for Europe and North America - 80 years Historical Weather API - Marine Forecast API, Air Quality API, Geocoding API, Elevation API, Flood API - Lightning fast APIs with response times below 10 ms - No API key required, CORS supported, no ads, no tracking, not even cookies - Free for non-commercial use with data under Attribution 4.0 International (CC BY 4.0) >curl "api.open-meteo.com" Repository open-meteo/open-meteo Repository stats |Metric|Value| |:-|:-| |Stars|6,367| |Forks|451| |Last release|1.7.0 (2026-10-16)| |Languages|Swift 94%, C 6%| |Contributors|95| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|Copilot: 3, claude: 2| |AI co-authored commits|Claude: 2, Copilot: 4| Main contributor |Field|Value| |:-|:-| |Name|Patrick Zippenfenig| |GitHub|@patrick-zippenfenig| |Commits to this repo|2,185 (top contributor)| |Company / Location|@open-meteo / Switzerland| |Followers|178| |Public repos|36| |On GitHub since|2015-03-26|

[OC] I tried to visualize air pollutants data over the globe. (Copernicus CAMS) I'm aware this is like one of the most made project. But I thought it looked quite cool so I thought of sharing. I like that you can get a feel of the direction of flow of pollutants via this visualization. I chose dots over a general gradient to give that comic book esque feel. I'm thinking of adding major events as timestamps you can visit to see the change in pollutants. The inspiration for this project came as Diwali is coming in India and I wanted a visual way to see how much worse the air quality will get in Delhi. Which lead to this rabbit hole. PS. Please let me know if you would have liked to see something added to this. Source: Air quality: Copernicus Atmosphere Monitoring Service (CAMS) / ECMWF, via Open-Meteo (CC BY 4.0) Global forecasts, 15 fields at 0.4° (~45 km): ads.atmosphere.copernicus.eu Raw grids pulled from Open-Meteo’s open data archive: open-meteo/open-data Earth imagery: NASA Blue Marble Next Generation: science.nasa.gov