NOAA GFS: Global Weather Forecast Data in netCDF Format

The Global Forecast System (GFS) model from the National Centers for Environmental Prediction provides dozens of atmospheric and land-soil variables. Data is provided at approximately 13x13 km horizontal resolution with 127 vertical levels and hourly temporal resolution. This dataset includes netCDF files for the 12Z forecast cycle updated daily, plus supplemental climatological Global Land Surface Datasets.

Use Cases

• Drive air quality models like the U.S. EPA's CMAQ based on the comprehensive atmospheric variables.
• Study land-atmosphere interactions by combining GFS meteorological data with supplemental vegetation canopy data.
• Perform numerical weather prediction research using the high spatiotemporal resolution global forecast outputs.
• Analyze soil moisture and precipitation patterns for hydrological modeling applications.

Strengths

• High spatiotemporal resolution: approximately 13x13 km horizontal, 127 vertical levels, and hourly output.
• Data is in the widely supported, self-describing netCDF format, described as scalable and community-friendly.
• Includes supplemental Global Land Surface Datasets gridded to match the GFS resolution, providing vegetation canopy variables.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and total dataset size are unknown, which may limit suitability assessment.
• The canopy data variables are climatological, based on satellite data from 2020 combined with 2022 meteorology, not real-time.

Provenance

Source

National Centers for Environmental Prediction (NCEP), NOAA.

Collection Method

Operational weather forecast model output.

Time Range

The canopy data is based on 2020 satellite data and 2022 meteorology; forecast data is ongoing.

Freshness

Updated daily for the 12Z forecast cycle.

Geography

Global.