Tutorial: Discovering, loading and plotting data with intake and xarray¶

We need to have intake installed (see https://server-howto.readthedocs.io/en/latest/data_organization.html#discover-data-with-intake).

[1]:

import intake

Display figures inside notebook

[2]:

%matplotlib inline

The observation datasets interpolated on the ASTE grid are listed in the following catalog:

[3]:

cat = intake.Catalog('/local/data/artemis/catalogs/ASTE_catalog.yml')

You can see what datasets are available in the catalog with:

[4]:

list(cat)

[4]:

['MLD_deBoyerMontegut',
 'Biomes_FayMcKinley',
 'NPP_CBPM_MODIS',
 'NPP_CBPM_SeaWIFS',
 'NPP_CBPM_VIIRS',
 'NPP_EppleyVGPM_MODIS',
 'NPP_EppleyVGPM_SeaWIFS',
 'NPP_EppleyVGPM_VIIRS']

The intake catalog provides all the necessary information on the data location, type,… so the loading process can be done easily with:

[5]:

npp_obs = cat.NPP_EppleyVGPM_MODIS.to_dask()

The dataset obtained can be plotted using xarray functions.

[6]:

npp_obs['npp'].sel(time='2007-6', face=1).plot(vmax=2000)

[6]:

<matplotlib.collections.QuadMesh at 0x7f2fdc06a438>