GFS: A global model with ~13 km resolution, providing a broad overview of weather patterns over large areas and longer forecast periods.
HRRR: Focuses on the United States with very high-resolution forecasts (~3 km) over short periods (up to 48 hours). Particularly useful for detailed, near-term weather predictions.
The Canadian GEM model offers both global and regional forecasts, with its regional version providing high-resolution details similar to HRRR but for Canada and potentially surrounding areas.
All three models incorporate a wide range of data, including satellite and radar observations, and employ sophisticated data assimilation techniques. HRRR, in particular, is updated hourly, reflecting the latest atmospheric conditions.
Each model employs different strategies to simulate physical processes such as cloud formation, precipitation, and land-surface interactions. These differences can lead to variations in forecast details, especially in complex terrains and for specific weather events like storms or heatwaves.