Herbie is a python package that downloads recent and archived numerical weather prediction (NWP) model output from different cloud archive sources. NWP data is usually in GRIB2 format and 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 and download data from:

• High Resolution Rapid Refresh (HRRR) | HRRR-Alaska
• Rapid Refresh (RAP)
• Global Forecast System (GFS)
• ECMWF Open Data Forecast Products (✨ new in Herbie 0.0.8)
• National Blend of Models (NBM)
• Rapid Refresh Forecast System - Prototype (RRFS)

📔 Herbie Documentation

Install

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

or, create the provided conda environment.

Capabilities

• Search different data sources for model output.
• 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
      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.archive 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. In the later half of 2020, this data was made available through the NOAA Big Data Program. This package organizes and expands my original download scripts into a more coherent package with the ability to download HRRR and RAP model data from different data sources. It will continue to evolve at my own leisure.

I originally released this package under the name "HRRR-B" because it only dealt with the HRRR data set, but I have addeed ability to download RAP data. Thus, it was rebranded with the name "Herbie" as a model download assistant. For now, it is still called "hrrrb" on PyPI because "herbie" is already taken. Maybe someday, with some time and an enticing reason, I'll add additional download capabilities.

✒ Pando HRRR Archive citation

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

Alternative Download Tools

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

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.