Real-time Environmental Data for Academic and Research Purposes
Access observations from 170,000+ stations worldwide through a single platform.
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Powering Research and Academics with Data
A platform purpose-built for research workflows, whether your project is a short-term student assignment, a PhD thesis, or a large-scale environmental study. If you need real-time or historical weather data to power your research, Synoptic is the platform trusted by thousands of students and research professionals every year.
Two Ways to Access Rich, Real-Time Environmental Data That Powers World-Class Research
Weather API
Access data from the Synoptic platform with our Weather API, built for researchers who want to pull data directly into their working environment programmatically.
- Simple to use query structure allows for quick integration into projects
- Real-time and historical data from up to 170,000+ stations across 320+ networks and 160+ variables
- Advanced quality control applied in real time before data is served
Synoptic Data Viewer
The Data Viewer is an interactive, map-based platform for exploring real-time and historical environmental observations from stations worldwide. Built for quick exploration, analysis, and shareable insights.
- View granular station data and historical observations across the Synoptic platform
- Create graphs and visual representations of weather data for each chosen station
- Filter by station, variable, network, or region using the Metadata Explorer
A Public Benefit Corporation Committed to Supporting Research and Academics
Synoptic is proud to be a Public Benefit Corporation and certified B Corporation. We believe environmental data should be an accessible tool for research and discovery. As part of our mission, we offer eligible students short-term access to our platform through the Open Access Program.
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Research Powered by Synoptic Data
Synoptic has been cited in peer-reviewed publications and open-access research projects worldwide. Browse samples of the work our data has helped make possible.
WeatherReal
arXiv · 2024A Benchmark Based on In-Situ Observations for Evaluating Weather Models
A benchmark dataset derived from global near-surface in-situ observations for evaluating AI-based weather forecasting models. Synoptic Data PBC credited for data aggregation.
OMG-HD
arXiv · 2024A High-Resolution AI Weather Model for End-to-End Forecasts from Observations
A high-resolution AI weather forecasting model trained directly on observational data, including surface stations, radar, and satellite, without relying on traditional data assimilation. Station data sourced from the WeatherReal-Synoptic dataset. The model outperforms ECMWF IFS-HRES and HRRR at lead times up to 12 hours across the contiguous United States.
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