pangeo-forge / staged-recipes

A place to submit pangeo-forge recipes before they become fully fledged pangeo-forge feedstocks
https://pangeo-forge.readthedocs.io/en/latest/
Apache License 2.0
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Proposed Recipes for MAR Greenland output #204

Closed raf-antwerpen closed 1 year ago

raf-antwerpen commented 1 year ago

Dataset Name

MAR

Dataset URL

ftp.climato.be/fettweis/tmp/marco/

Description

This dataset contains daily Modèle Atmosphérique Régional (MAR) output over Greenland between 1950 and 2021 on 6.5km resolution. The output contains numerous meteorological and glaciological variables over the entire ice sheet that can benefit researchers that are working to understand processes governing ice melting on Greenland and everything that is associated with it.

License

MIT License

Data Format

NetCDF

Data Format (other)

No response

Access protocol

FTP

Source File Organization

72 NetCDF files, one for each year between 1950 and 2021. Each file contains output of all variables, formatted on the latlon grid of Greenland. Static variables such as latitude, longitude, surface height, soil type, etc. have only two dimensions representing latitude and longitude. Most variables have a third dimension representing time in days. Some other variables have a fourth dimension representing vertical layers.

Example URLs

ftp.climato.be/fettweis/tmp/marco/MARv3.12.1-6.5km-daily-ERA5-1950.nc
ftp.climato.be/fettweis/tmp/marco/MARv3.12.1-6.5km-daily-ERA5-2021.nc

Authorization

Username / Password

Transformation / Processing

The files should be concatenated along the time dimension, from 1 January 1950 to 31 December 2021. No cleaning necessary.

Target Format

Zarr

Comments

@jkingslake

jkingslake commented 1 year ago

I am helping @raf-antwerpen with this recipe. The only thing I am not sure about is the authentication. It isn't in a public archive. It's on an ftp server which requires a login.

jkingslake commented 1 year ago

Update: we have the MAR netcdfs in a google bucket to get around the authentication issue mentioned above. See here for more details.

import gcsfs
import xarray as xr
import hvplot.xarray

gcs = gcsfs.GCSFileSystem()
url = 'gs://ldeo-glaciology/MAR/6.5km/MARv3.12-6_5km-daily-ERA5-2000.nc'  
of = gcs.open(url, mode='rb')
ds = xr.open_dataset(of,chunks=-1)  

options = dict(x='x', y='y', clim=(0.2, 1), width=500, height=700, cmap='greys_r')
ds.AL2.hvplot(**options).  # this is the albdeo field

image.