Open-Meteo
Open-source weather API with no API key required, for forecasts and historical data.
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What is Open-Meteo?
Open-Meteo is a free, open-source weather API that provides real-time and historical weather data to users worldwide. Built on a suite of global meteorological models from organizations like ECMWF, NOAA, and MeteoSwiss, it offers high-resolution forecasts and climate data without requiring API keys or user authentication. Developers, researchers, and hobbyists use it to access weather patterns, climate analysis, and environmental monitoring tools. The tool addresses the challenge of obtaining reliable weather data by aggregating multiple models, ensuring accessibility for non-commercial and academic applications. Its historical dataset, spanning back to 1940, enables long-term climate studies and trend analysis, while its hourly resolution supports detailed short-term planning.
How it works
Open-Meteo is a web-based API that delivers weather forecasts and historical data through a simple HTTP GET request. It aggregates data from over 30 global weather models, including ECMWF, NOAA, and DWD, to provide comprehensive weather insights. The project adheres to the AGPL-3.0 license, allowing free use for non-commercial and commercial purposes as long as derivative works share their modifications. Its primary purpose is to democratize access to high-quality weather data. By eliminating the need for API keys or registration, it users to integrate real-time and historical weather information into applications, research projects, or personal use without barriers. The API supports forecasts up to 1 km resolution, historical data from 1940, and ERA5 reanalysis for climate modeling. Users can retrieve current weather metrics like temperature and wind speed, or access hourly, daily, or monthly datasets. For example, a query might fetch temperature and humidity data for a specific location over a 10-day period, with timestamps and numerical values in JSON format.
How to use it
- 1Construct a URL with latitude, longitude, and desired variables (e.g., temperature, wind speed). 2. Append parameters like `current=temperature_2m` or `hourly=wind_speed_10m` to specify data types. 3. Send an HTTP GET request to `https://api.open-meteo.com/v1/forecast`. 4. Parse the JSON response, which includes timestamps and numerical values for each metric. Practical tips: Use the `historical` endpoint for past data, adjust timeframes via `start_date` and `end_date`, and prioritize models with higher resolution for critical applications. The API automatically handles missing values in historical datasets.
What it can do
- weather API
Use cases
Assumptions and limitations
Assumptions
- source: https://github.com/open-meteo/open-meteo
- license: AGPL-3.0 — free to use
- privacy: Self-hosted — you control your data
Limitations
- Limited support for subnational regions with sparse model coverage
- Resolution varies by model, with some datasets available only at 10 km granularity
- No real-time updates for models with delayed data processing pipelines
- Historical data may contain biases due to model-specific assumptions
- No authentication restricts access to basic data formats without advanced parsing
Understanding the result
Open-source weather API with no API key required, for forecasts and historical data.
Tool details
- Clearly flagged when a network request is needed.
- No account, no sign-up, and no tracking of your content.
- Powered by (MIT).
- Built with
- (open-meteo/open-meteo)
- License
- MIT
- Runs locally
- No — requires a network request
- Verification
- Not yet verified
- Input
- Query
- Output
- Text
Built with open-meteo/open-meteo. OpenToolVault provides the discovery and browser interface while crediting the original project maintainers.
- Built with
- License
- MIT
Open-source project
OpenToolVault is an independent directory. We are not affiliated with or endorsed by this project.
References
- / — GitHub Repository
Upstream project · GitHub
- AGPL-3.0 License
Upstream project
Frequently asked
What types of data does Open-Meteo provide?
Open-Meteo offers current weather metrics, hourly/daily forecasts, and historical data spanning 1940. It includes variables like temperature, humidity, wind speed, precipitation, solar radiation, and atmospheric pressure. The ERA5 reanalysis dataset provides consistent, spatially complete climate data for model training and validation.
How does Open-Meteo aggregate weather models?
The API combines data from over 30 global models, including ECMWF IFS HRES, NOAA GFS, and DWD ICON. Each model contributes unique data points, which are then compiled into a unified JSON format. Users can select specific models or rely on the default aggregation, which prioritizes models with higher resolution and updated processing pipelines.
How do I retrieve historical weather data for a specific location?
Use the `historical` endpoint with parameters like `latitude=40.71`, `longitude=-74.01`, `start_date=2023-01-01`, and `end_date=2023-01-31`. Include variables such as `temperature_2m` or `precipitation_sum`. The response will return hourly data in a structured JSON format, with timestamps and numerical values for each metric.
How does Open-Meteo compare to commercial weather APIs?
Unlike commercial services like OpenWeatherMap or AccuWeather, Open-Meteo provides free, open-source access to high-resolution data without API keys. It excels in historical climate analysis and model diversity but lacks the localized, hyper-accurate forecasts of proprietary services. Its AGPL-3.0 license requires derivative works to share modifications, distinguishing it from closed-source alternatives.
How do I handle missing data in historical responses?
The API ensures no missing values in historical datasets by using spatially complete models like ERA5. If gaps occur, they typically result from model-specific limitations. To mitigate this, use the `model` parameter to select a model with higher resolution, or combine data from multiple models to fill gaps. Always validate data against the source model's documentation.