Data Sources & Methodology
Transparency is critical. Here is exactly where our data comes from and how we process it.
Weather Data: HRRR & Open-Meteo
Our primary meteorological input is the High-Resolution Rapid Refresh (HRRR) model provided by NOAA. HRRR is a real-time, 3km resolution atmospheric model, updated hourly. We use it to capture dynamic weather variables like precipitation, temperature, and wind vectors. Open-Meteo serves as a robust supplementary source for extended forecasts and gap filling.
Terrain Data: SRTM DEM
To accurately model how weather interacts with the landscape, we rely on the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) provided by NASA and the USGS. This high-resolution topographical data allows our engine to calculate exact slope angles, aspects, and localized terrain effects.
Snow Physics Methodology
Our proprietary engine processes the intersection of weather and terrain. By running continuous physics simulations on variables like solar radiation and loading across the DEM, we classify the snowpack into 14 distinct states. This deterministic approach avoids the black-box nature of pure machine learning models, ensuring our outputs are grounded in established physical principles.
Mapping & Visualization: MapLibre & MapTiler
To deliver our 3D snow state forecasts smoothly in your browser, we leverage MapLibre GL JS, an open-source library for rendering interactive maps using WebGL. Our base maps and satellite imagery are provided by MapTiler, ensuring high-performance, beautiful terrain visualization even in remote backcountry areas.