offline zarr downloader
Project description
Zarr offline downloader
The idea is to have an option to download a zarr dataset for offline reuse or conversion to netcdf. The package is a command line tool and is not covering all kind of different zarr stores. It has been tested with Google Cloud Storage of ECMWF ERA5 reanalysis.
usage: zarr-downloader.py [-h] [--variable VARIABLE] [--offset OFFSET] [--verbose]
[--to-netcdf] [--overwrite] url output
Download a zarr Array / Group from a URL
positional arguments:
url URL to download from
output Output directory to save the zarr file
options:
-h, --help show this help message and exit
--variable VARIABLE Subset of variables to download. e.g. t2m,lon,lat,...
--offset OFFSET Offset for the chunk access pattern
--verbose, -v Verbose output
--to-netcdf Convert to netcdf
--overwrite, -o Overwrite existing files
Examples
How to download a zarr dataset for offline reuse?
# Download ERA 5 surface 2m temperature from Google zarr store.
# There is an offset (chunks: 1000000.0)
# note t2m has two chunk dimensions: time,values
# this will download all chunks
zarr-downloader.py --offset 1000000,0 --variable t2m \
https://storage.googleapis.com/gcp-public-data-arco-era5/co/single-level-reanalysis.zarr-v2 \
/tmp/t2m
# this will download one chunk
zarr-downloader.py --offset 1000000,0 --size 1,1 --variable t2m \
https://storage.googleapis.com/gcp-public-data-arco-era5/co/single-level-reanalysis.zarr-v2 \
/tmp/t2m
# coordinates need to be downloaded completely
zarr-downloader.py --variable time,longitude,latitude \
https://storage.googleapis.com/gcp-public-data-arco-era5/co/single-level-reanalysis.zarr-v2 \
/tmp/t2m
after downloading one can open the full zarr dataset again, but access the downloaded parts:
import zarr
import xarray as xr
ds = xr.open_zarr('/tmp/t2m')
ds
<xarray.Dataset>
Dimensions: (time: 1323648, values: 542080)
Coordinates:
depthBelowLandLayer float64 ...
entireAtmosphere float64 ...
latitude (values) float64 ...
longitude (values) float64 ...
number int64 ...
step timedelta64[ns] ...
surface float64 ...
* time (time) datetime64[ns] 1900-01-01 ... 2050-12-31T23:0...
valid_time (time) datetime64[ns] ...
Dimensions without coordinates: values
Data variables: (12/38)
cape (time, values) float32 ...
d2m (time, values) float32 ...
hcc (time, values) float32 ...
istl1 (time, values) float32 ...
istl2 (time, values) float32 ...
istl3 (time, values) float32 ...
... ...
tsn (time, values) float32 ...
u10 (time, values) float32 ...
u100 (time, values) float32 ...
v10 (time, values) float32 ...
v100 (time, values) float32 ...
z (time, values) float32 ...
Attributes: (12/14)
Conventions: CF-1.7
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forec...
GRIB_edition: 1
GRIB_subCentre: 0
history: 2023-08-27T15:04 GRIB to CDM+CF via cfgrib-0.9...
... ...
pangeo-forge:recipe_hash: 09c22f5fffc2fbe3742fbb38c8c2c761e1b41b50570f09...
pangeo-forge:version: 0.9.5.dev2+gd43015b
valid_time_start: 1940-01-01
last_updated: 2025-05-12 03:32:06.266520+00:00
valid_time_stop: 2025-02-28
valid_time_stop_era5t: 2025-04-30
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