At SkiWeather.eu, our snow forecast maps are created using a robust statistical approach that combines meteorological data, geospatial modeling, and advanced statistical techniques. Our meteorological data represents approximately 20,000 points across the Alps, capturing diverse conditions at varying altitudes. This comprehensive dataset forms the foundation for precise and localized snow predictions.
Snow forecast levels are further adjusted based on altitude relative to the freezing level, allowing us to refine predictions to reflect elevation-dependent dynamics of snowfall. This adjustment ensures our forecasts accurately represent snow distribution patterns, particularly in areas near critical temperature thresholds.
Central to our methodology is the use of a Generalized Additive Model (GAM), which predicts snow accumulation patterns by considering non-linear relationships between snowfall intensity and key variables such as altitude, spatial location, and microclimate areas. The microclimate variable is constructed from extensive timeseries data on snow depth evolution, snowfall, and temperature observed at both lower and upper slopes. This variable enables us to capture localized climatic effects, adding another layer of precision to the predictions.
To enhance the spatial resolution of our forecasts, we apply kriging interpolation, a geostatistical technique that estimates snow accumulation at unmeasured locations, creating a continuous prediction surface. This ensures seamless integration of meteorological data across the region, even on locations where direct measurements are unavailable.
Our process also incorporates rigorous data filtering to remove anomalies and outliers, preserving the reliability and accuracy of the predictions. By combining these statistical methods with detailed geospatial and climatic data, SkiWeather.eu delivers highly localized and realistic snow forecasts, empowering users with precise insights into upcoming conditions across ski resorts of the Alps.