Hyperlocal forecasting for high-resolution weather insights
Nowcasting for short-term, dynamically updating forecasts.
Multi-model fusion which combines different global and local models to enhance accuracy, fill gaps, and reduce errors
100m
Resolution
Global
Coverage
10min
data updates
OpenWeather is a leading provider of weather data and forecasts, leveraging proprietary weather modeling and high-load technologies to deliver accurate and real-time meteorological insights. By integrating advanced numerical weather prediction (NWP) models, artificial intelligence (AI), and big data processing, OpenWeather enhances traditional forecasting methods to provide hyperlocal and dynamic weather updates.
As technology evolves, OpenWeather remains at the forefront of weather intelligence, ensuring that businesses and individuals have access to the most reliable weather data available.
Deep learning models analyze historical and real-time data, detecting patterns to enhance forecasting. Anomaly detection algorithms identify extreme weather events, providing early warnings. AI-driven parameter optimization fine-tunes forecast models dynamically, improving accuracy. Nowcasting with AI delivers real-time updates by processing satellite, radar, and sensor data. Predictive climate modeling helps simulate long-term trends, aiding researchers and policymakers.
Technologies
We store decades of weather forecasts and measurements history all around the world in a unique multi-dimensional raster data storage solution DEKER™, a petabyte-scale database framework delivering enhanced security and robust multidimensional arrays storage, ensuring top-tier data protection, advanced analytics, and optimal performance. It supports unlimited storage cluster horizontal scalability combined with instant access to any location, time or weather parameter requested.
In addition to serving our pre-calculated forecast and historical data we implement on-demand real-time data processing that enables a more precise and rich set of weather parameters to be returned for particular geographical locations.
Our main goal is to deliver weather data to our customers in the most reliable way exactly at the moment they need it, so we developed uniquely flexible architecture for our API servers, multi-level intermediate caches and backend data storage which allows both to sustain tens of thousands requests from all over the world and rapidly scale out to handle peak loads which may be 2-3 times higher than average.
OpenWeather provides accurate weather data by drawing on trusted sources such as weather stations, satellites, radar systems, and advanced models like GFS, ECMWF, and its own OWHL™️. These partnerships with the UK Met Office and other national meteorological agencies boost reliability, with updates released every 10 minutes to ensure precision. Remarkably, the OWHL™️ model reports less than 1% of temperature predictions deviating by more than 5°C. Widely recognised as a leading provider of short-term forecasts, OpenWeather acknowledges that accuracy diminishes over longer periods due to atmospheric complexity. Thus, while short-term forecasts remain highly reliable, it is prudent to view predictions beyond a week with a degree of caution.
Continuously refining its models using real-time data, OpenWeather delivers reliable forecasts worldwide, covering both remote and densely populated areas. It also offers minute-by-minute precipitation data and hyperlocal insights, establishing itself as a trusted choice for businesses across the globe.