NOAA High-Resolution Rapid Refresh (HRRR) Model

Description

The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh.

The HRRR ZARR formatted data was originally generated by the University of Utah under a grant provided by NOAA. They are are continuing to publish ZARR versions of HRRR data. For information about data in the s3://hrrrzarr/ please contact atmos-mesowest@lists.utah.edu.

Update Frequency

Hourly

License

NOAA data disseminated through NODD are open to the public and can be used as desired.

NOAA makes data openly available to ensure maximum use of our data, and to spur and encourage exploration and innovation throughout the industry. NOAA requests attribution for the use or dissemination of unaltered NOAA data. However, it is not permissible to state or imply endorsement by or affiliation with NOAA. If you modify NOAA data, you may not state or imply that it is original, unaltered NOAA data.

Documentation

https://github.com/awslabs/open-data-docs/tree/main/docs/noaa/noaa-hrrr

Managed By

See all datasets managed by NOAA.

Contact

For any questions regarding data delivery or any general questions regarding the NOAA Open Data Dissemination (NODD) Program, email the NODD Team at nodd@noaa.gov.
We also seek to identify case studies on how NOAA data is being used and will be featuring those stories in joint publications and in upcoming events. If you are interested in seeing your story highlighted, please share it with the NODD team by emailing nodd@noaa.gov

How to Cite

NOAA High-Resolution Rapid Refresh (HRRR) Model was accessed on DATE from https://registry.opendata.aws/noaa-hrrr-pds.

Usage Examples

Tutorials

• HRRR-B Python package: download and read HRRR grib2 files by Brian Blaylock
  
• The HRRR Zarr Archive Managed by MesoWest by Taylor Gowan
  

Publications

• Using Cloud Computing to Analyze Model Output Archived in Zarr Format by Taylor A. Gowan, John D. Horel, Alexander A. Jacques, and Adair Kovac
  
• Using the U.S. Climate Reference Network to Identify Biases in Near- and Sub-Surface Meteorological Fields in the High-Resolution Rapid Refresh (HRRR) Weather Prediction Model by Temple R. Lee, Ronald D. Leeper, Tim Wilson, Howard Diamond, Tilden P. Meyers, and David D. Turner