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Herbie: Retrieve NWP Model Data 🏁

DOI Code style: black

Herbie is a python package that downloads recent and archived numerical weather prediction (NWP) model output from different cloud archive sources. NWP data in GRIB2 format can be read with xarray+cfgrib. Much of this data is made available through the NOAA Big Data Program which has made weather data more accessible than ever before.

Herbie helps you discover, download, and read data from:

📓 Herbie Documentation

Install

Herbie requires cURL and Python 3.8+ with requests, numpy, pandas, xarray, and cfgrib. Optional packages are matplotlib, cartopy, and Carpenter Workshop.

pip install herbie-data

or

pip install git+https://github.com/blaylockbk/Herbie.git

You may also create the provided conda environment.

Capabilities

  • Search for model output from different data sources.
  • Download full GRIB2 files
  • Download subset GRIB2 files (by grib field)
  • Read data with xarray
  • Read index file with Pandas
  • Plot data with Cartopy (very early development)
  graph TD;
      d1[(HRRR)] -.-> H
      d2[(RAP)] -.-> H
      d3[(GFS)] -.-> H
      d33[(GEFS)] -.-> H
      d4[(ECMWF)] -.-> H
      d5[(NBM)] -.-> H
      d6[(RRFS)] -.-> H
      H((Herbie))
      H --- .download
      H --- .xarray
      H --- .read_idx

      style H fill:#d8c89d,stroke:#0c3576,stroke-width:4px,color:#000000
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
)

# Download the full GRIB2 file
H.download()

# Download a subset, like all fields at 500 mb
H.download(":500 mb")

# Read subset with xarray, like 2-m temperature.
H.xarray("TMP:2 m")

Data Sources

Herbie downloads model data from the following sources, but can be extended to include others:

  • NOMADS
  • Big Data Program Partners (AWS, Google, Azure)
  • ECMWF Open Data Azure storage
  • University of Utah CHPC Pando archive

History

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.

✒ I wrote a paper about archiving HRRR data in the cloud

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

In the later half of 2020, the HRRR dataset from 2014 to present was made available through the NOAA Big Data Program. Herbie organizes and expands my original download scripts into a more coherent package with the extended ability to download data for other models from many different archive sources.

I originally released this package under the name “HRRR-B” because it only dealt with the HRRR dataset; the “B” was for my first-name initial. Since then, I have added the ability to download RAP, GFS, ECMWF, GEFS, RRFS, and others with potentially more models in the future. Thus, this package was renamed Herbie, named after one of my favorite childhood movie characters.

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


👨🏻‍💻 Contributing Guidelines
💬 GitHub Discussions
🚑 GitHub Issues
🌐 Personal Webpage
🌐 University of Utah HRRR archive

P.S. If you like Herbie, check out my other repos:

  • 🌎 GOES-2-go: A python package to download GOES-East/West data and make RGB composites.
  • 🌡 SynopticPy: A python package to download mesonet data from the Synoptic API.
  • 🔨 Carpenter Workshop: A python package with various tools I made that are useful (like easy funxtions to build Cartopy maps).
  • 💬 Bubble Print: A silly little python package that gives your print statement's personality.
  • 📜 MET Syntax: An extension for Visual Studio Code that gives syntax highlighting for Model Evaluation Tools (MET) configuration files.

Alternative Download Tools

As an alternative to Herbie, you can use rclone to download files from AWS or GCP. I quite like rclone. Here is a short rclone tutorial

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