Downloading Archived Meteorology#

arl-met includes source classes for downloading ARL meteorology files from the NOAA ARL public archives.

Install the source dependencies first:

pip install "arlmet[sources]"

Choose a source class#

Each class knows the filename and archive layout for one product.

Available source classes#
Class	Product	Typical coverage
`arlmet.sources.HRRRSource`	HRRR 3 km	CONUS, 6-hour files
`arlmet.sources.NAMSource`	NAM 12 km	North America, daily files
`arlmet.sources.GDASSource`	GDAS 1 degree	Global, weekly files
`arlmet.sources.GFSSource`	GFS 0.25 degree	Global, daily files
`arlmet.sources.ReanalysisSource`	NCEP/NCAR Reanalysis	Global, monthly files

Download files for a time range#

from arlmet.sources import HRRRSource

source = HRRRSource()
files = source.fetch(
    "2024-07-18 00:00",
    "2024-07-19 00:00",
    local_dir="./met",
)

fetch() returns the local paths in chronological order. Duplicate archive keys are removed automatically when the requested time range spans multiple hours within the same ARL file.

Crop on download#

For large global products, pass bbox= so the downloaded file is cropped before it is cached locally.

from arlmet.sources import GFSSource

source = GFSSource()
files = source.fetch(
    "2024-07-18 00:00",
    "2024-07-19 00:00",
    local_dir="./met",
    bbox=(-114.0, 39.0, -110.0, 42.0),
)

This uses arlmet.extract_subset() internally after the raw file is downloaded.

Choose a backend#

The default backend is "s3" and is usually the fastest choice.

files = source.fetch(
    "2024-07-18",
    "2024-07-19",
    local_dir="./met",
    backend="ftp",
)

Supported backends are:

"s3": NOAA public S3 bucket via s3fs
"ftp": NOAA ARL FTP archive
"http": READY web archive

Caching and overwrite behavior#

Downloaded files are reused if a matching local file already exists. Pass overwrite=True to force a fresh download.

files = source.fetch(
    "2024-07-18",
    "2024-07-19",
    local_dir="./met",
    overwrite=True,
)