Retrieving data from the CDS

The cds data source provides access to the Copernicus Climate Data Store (CDS).

import earthkit.data as ekd

Getting GRIB data

d = ekd.from_source(
    "cds",
    "reanalysis-era5-single-levels",
    request=dict(
        variable=["2t", "msl"],
        product_type="reanalysis",
        area=[50, -10, 40, 10],  # N,W,S,E
        grid=[2, 2],
        date="2012-05-10",
        time="12:00",
    ),
)
d

GRIB file

---

path	/var/folders/93/w0p869rx17q98wxk83gn9ys40000gn/T/earthkit-data-cgr/cds-retriever-7906c1e5c1676b554722fc7f0eadee8aeadff9a6f8707fea79de39beb2fb21ca.cache
size	480
types	fieldlist, pandas, xarray, numpy, array

d.to_fieldlist().ls()

	parameter.variable	time.valid_datetime	time.base_datetime	time.step	vertical.level	vertical.level_type	ensemble.member	geography.grid_type
0	2t	2012-05-10 12:00:00	2012-05-10 12:00:00	0 days	0	surface	0	regular_ll
1	msl	2012-05-10 12:00:00	2012-05-10 12:00:00	0 days	0	surface	0	regular_ll

Getting NetCDF data

d1 = ekd.from_source(
    "cds",
    "reanalysis-era5-single-levels",
    request=dict(
        variable=["2t", "msl"],
        product_type="reanalysis",
        area=[50, -10, 40, 10],  # N,W,S,E
        grid=[2, 2],
        date="2012-05-10",
        time="12:00",
        format="netcdf",
    ),
)
d1

NetCDF file

---

path	/var/folders/93/w0p869rx17q98wxk83gn9ys40000gn/T/earthkit-data-cgr/cds-retriever-1782892e3a2c6b2a7f0a26a0cde23006146277f2519dd017f9c40986ffd37472.nc
size	33.3 KiB
types	xarray, pandas, fieldlist, numpy, array

d1.to_fieldlist().ls()

	parameter.variable	time.valid_datetime	time.base_datetime	time.step	vertical.level	vertical.level_type	ensemble.member	geography.grid_type
0	t2m	2012-05-10 12:00:00	2012-05-10 12:00:00	0 days	None	unknown	0	None
1	msl	2012-05-10 12:00:00	2012-05-10 12:00:00	0 days	None	unknown	0	None