NOAA High-Resolution Rapid Refresh (HRRR)
The NOAA HRRR is a real-time 3km 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-hour period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh (RAP) system.
This dataset is available on Azure thanks to the NOAA Big Data Program.
Data are stored in GRIB format; within each GRIB file are both data and Climate and Forecast v1.6 metadata.
GRIB files are stored as blobs in the East US Azure region, in the following blob container:
Within that container, files are named as:
yearis a four-digit year
monthis a two-digit month (one-indexed)
dayis a two-digit day (one-indexed)
regioncan be either “conus” or “alaska”
CCis the cycle run hour (00 to 23)
variableis the output variable (wrfprsf, wrfnatf, wrfsfcf, or wrfsubhf; see the HRRR documentation for definitions)
FHrepresents the forecast hour (00 to 18 for standard cycles, 00 to 48 for extended-forecast cycles (00, 06, 12, 18))
For example, for the file:
- Year: 2014
- Month: 12
- Day: 01
- Region: conus
- CC (cycle run): 18
- Variable: wrfsubh
- FH (forecast hour): 15
A complete Python example of accessing and plotting HRRR data is available in the accompanying sample notebook.
Large-scale processing is best performed in the East US Azure region, where the data are stored.
Mounting the container
We also provide a read-only SAS (shared access signature) token to allow access via, e.g., BlobFuse, which allows you to mount blob containers as drives:
Mounting instructions for Linux are here.
For questions, please contact the NOAA Big Data Program Team at
Microsoft provides this dataset on an “as is” basis. Microsoft makes no warranties (express or implied), guarantees, or conditions with respect to your use of the dataset. To the extent permitted under your local law, Microsoft disclaims all liability for any damages or losses - including direct, consequential, special, indirect, incidental, or punitive - resulting from your use of this dataset. This dataset is provided under the original terms that Microsoft received source data.