Download numerical weather prediction datasets (HRRR, RAP, GFS, IFS, etc.) from NOMADS, NODD partners (Amazon, Google, Microsoft), ECMWF open data, and the Univ
Download numerical weather prediction datasets (HRRR, RAP, GFS, IFS, etc.) from NOMADS, NODD partners (Amazon, Google, Microsoft), ECMWF open data, and the Univ
Herbie is a Python package that makes downloading and working with numerical weather prediction (NWP) model data simple and fast. Whether you're a researcher, meteorologist, data scientist, or weather enthusiast, Herbie provides easy access to forecast data from NOAA, ECMWF, and other sources.
Key Features:
Keywords: weather data download, GRIB2, python, numerical weather prediction, meteorological data, weather forecast API, xarray, atmospheric data, research, academia, data science, machine learning,visualization
With conda or mamba:
conda install -c conda-forge herbie-datamamba install -c conda-forge herbie-dataWith pip:
pip install herbie-dataWith uv:
uv add herbie-dataNote: optional features require manual installation of wgrib2
from herbie import Herbie
# Create a Herbie object for HRRR model data
H = Herbie(
'2021-01-01 12:00', # Date and time
model='hrrr', # Model name
product='sfc', # Product type
fxx=6 # Forecast hour
)
# Show file contents
H.inventory()
# Download and read 2-meter temperature
temperature = H.xarray("TMP:2 m")# Download HRRR surface forecast
herbie download -m hrrr --product sfc -d "2023-03-15 12:00" -f 0
# Get specific variable (temperature at 850 mb)
herbie download -m gfs --product 0p25 -d 2023-03-15 -f 24 --subset ":TMP:850 mb:"
# View available variables
herbie inventory -m rap -d 2023031512 -f 0Herbie provides access to a wide range of numerical weather prediction models:
Much of this data is made available through the NOAA Open Data Dissemination (NODD) program.
View all models in the gallery →
Features:
graph TD;
d1[(HRRR)] -..-> H
d2[(RAP)] -.-> H
d3[(GFS)] -..-> H
d33[(GEFS)] -.-> H
d4[(IFS)] -..-> H
d44[(AIFS)] -..-> H
d5[(NBM)] -.-> H
d6[(RRFS)] -..-> H
d7[(RTMA)] -.-> H
d8[(URMA)] -..-> H
H((Herbie))
H --- .inventory
H --- .download
H --- .xarray
style H fill:#d8c89d,stroke:#0c3576,stroke-width:4px,color:#000000Herbie's Python API is used like this:
from herbie import Herbie
# Herbie object for the HRRR model 6-hr surface forecast product
H = Herbie(
'2021-01-01 12:00',
model='hrrr',
product='sfc',
fxx=6
)
# View all variables in a file
H.inventory()
# Download options
H.download() # Download full GRIB2 file
H.download(":500 mb") # Download subset (all 500 mb fields)
H.download(":TMP:2 m") # Download specific variable
# Read data into xarray
ds = H.xarray("TMP:2 m") # 2-meter temperature
ds = H.xarray(":500 mb") # All 500 mb level dataHerbie also has a command line interface (CLI) so you can use Herbie right in your terminal.
…Herbie automatically searches for data at multiple data sources:
Full Documentation - Comprehensive guides and API reference
️ Example Gallery - Browse code examples for each model
GitHub Discussions - Ask questions and share ideas
Report Issues - Found a bug? Let us know
If Herbie played an important role in your work, please tell us about it!
Blaylock, B. K. (YEAR). Herbie: Retrieve Numerical Weather Prediction Model Data (Version 20xx.x.x) [Computer software]. https://doi.org/10.5281/zenodo.4567540
A portion of this work used code generously provided by Brian Blaylock's Herbie python package (https://doi.org/10.5281/zenodo.4567540)
We welcome contributions! Here's how you can help:
Read the Contributing Guide for more details.
During my PhD at the University of Utah, I created, at the time, the only publicly-accessible archive of HRRR data. Over 1,000 research scientists and professionals used that archive.
Blaylock B., J. Horel and S. Liston, 2017: Cloud Archiving and Data Mining of High Resolution Rapid Refresh Model Output. Computers and Geosciences. 109, 43-50. https://doi.org/10.1016/j.cageo.2017.08.005.
Herbie was then developed to access HRRR data from that archive and was first used on the Open Science Grid.
Blaylock, B. K., J. D. Horel, and C. Galli, 2018: High-Resolution Rapid Refresh Model Data Analytics Derived on the Open Science Grid to Assist Wildland Fire Weather Assessment. J. Atmos. Oceanic Technol., 35, 2213–2227, https://doi.org/10.1175/JTECH-D-18-0073.1.
In 2020, the HRRR dataset was made available through the NOAA Open Data Dissemination Program. Herbie evolved from my original download scripts into a comprehensive package supporting multiple models and data sources.
Name Origin: I originally released this package under the name “HRRR-B” because it only worked with the HRRR dataset; the “B” was for Brian. Since then, I have added the ability to download many more models including RAP, GFS, ECMWF, GEFS, and RRFS with the potential to add more models in the future. Thus, this package was renamed Herbie, named after one of my favorite childhood movies.
The University of Utah MesoWest group now manages a HRRR archive in Zarr format. Maybe someday, Herbie will be able to take advantage of that archive.
Thanks for using Herbie, and happy racing!
Brian Blaylock
Personal Webpage
rclone: As an alternative to Herbie, you can use rclone to download files from remote archives. I love rclone. Here's a short rclone tutorial.
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