Herbie: Retrieve NWP Model Data#

Herbie is a python package that downloads recent and archived numerical weather prediction (NWP) model output from different cloud archive sources. NWP data is distributed in GRIB2 format and can be read with xarray+cfgrib.

Some models Herbie can retrieve data from include:

  • High-Resolution Rapid Refresh (HRRR)

  • Rapid Refresh (RAP)

  • Global Forecast System (GFS)

  • ECMWF open data forecast products (IFS and AIFS)

  • National Blend of Models (NBM)

  • Rapid Refresh Forecast System - Prototype (RRFS)

  • Real-Time/Un-Restricted Mesoscale Analysis (RTMA/URMA)

  • and many others (see 🗺 Model Tutorials)


The easiest way to install Herbie and its dependencies is with Conda.

conda install -c conda-forge herbie-data

More details at 🐍 Installation.


Herbie helps you discover and use data from many different numerical weather models and sources.


Specifically, Herbie can

  • Locate GRIB2 files in the cloud.

  • Explore the content of those files.

  • Download data to your computer.

  • Download subsets of the data.

  • Read the data with xarray.

  • Useful xarray accessors (see 🗃️ Xarray Accessors)

Using Herbie looks something like this…

from herbie import Herbie

# Create Herbie object for the HRRR model 6-hr surface forecast product
H = Herbie(
  '2021-01-01 12:00',

# Look at the GRIB2 file contents

# Download the full GRIB2 file

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

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

More details in the User Guide.