NOAA RRFS: Prototype High-Resolution Weather Forecasts for North America
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Description
A prototype of NOAA's next-generation Rapid Refresh Forecast System (RRFS), scheduled for operational implementation in 2026. The system provides hourly deterministic forecasts on a 3 km grid covering North America, Alaska, Hawaii, and Puerto Rico, out to 84 hours. It is underpinned by the Unified Forecast System (UFS) and developed collaboratively across NOAA, academia, and research institutions.
Use Cases
Developing and testing initialization methods for RRFSv2 based on the prototype gridded data.
Analyzing severe convective weather patterns based on the 3 km resolution, rapidly-updated forecasts.
Forecasting renewable energy output based on high-frequency weather guidance for specific regions.
Studying heavy precipitation and winter weather events using the ensemble prediction outputs.
Strengths
Provides forecasts on a high-resolution 3 km grid covering multiple geographic domains.
Offers hourly deterministic forecasts out to 84 hours at four main cycles per day.
Data is provided in the standard GRIB2 format for meteorological data.
Limitations
The prototype output is not operational, is not under 24x7 monitoring, and may be delayed or missing.
Outputs will change, and the dataset description states significant changes will be updated.
Column-level documentation is absent; field semantics must be inferred from file naming conventions.
Provenance
Source
National Oceanic and Atmospheric Administration (NOAA).
Collection Method
Output from the prototype Rapid Refresh Forecast System (RRFS) model.
Time Range
Real-time and retrospective parallel output; cycles include a prototype date of 14 January 2026.
Freshness
Real-time prototype data; update frequency is tied to forecast cycles (00, 06, 12, 18 UTC).
Geography
North America, with subsets for the contiguous United States (CONUS), Alaska, Hawaii, and Puerto Rico.
Data is hosted on AWS S3. The 'rrfs_a/' subdirectory contains a fuller set of products intended primarily for model developers.