You can run this notebook in Binder, in Colab, in Deepnote or in Kaggle.

[20]:
!pip install --quiet climetlab

Access ECMWF Open Data feed

[21]:
import climetlab as cml
[22]:
source = cml.load_source(
    "ecmwf-open-data",
    param=["2t", "msl"],
)
for s in source:
    cml.plot_map(s, title=True)
../_images/examples_05-source-open-data_3_0.png
../_images/examples_05-source-open-data_3_1.png
[23]:
source.to_xarray()
[23]:
<xarray.Dataset>
Dimensions:            (latitude: 451, longitude: 900)
Coordinates:
    time               datetime64[ns] 2022-02-06
    step               timedelta64[ns] 00:00:00
    heightAboveGround  float64 2.0
  * latitude           (latitude) float64 90.0 89.6 89.2 ... -89.2 -89.6 -90.0
  * longitude          (longitude) float64 -180.0 -179.6 -179.2 ... 179.2 179.6
    valid_time         datetime64[ns] 2022-02-06
    meanSea            float64 0.0
Data variables:
    t2m                (latitude, longitude) float32 ...
    msl                (latitude, longitude) float32 ...
Attributes:
    GRIB_edition:            2
    GRIB_centre:             ecmf
    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts
    GRIB_subCentre:          0
    Conventions:             CF-1.7
    institution:             European Centre for Medium-Range Weather Forecasts
    history:                 2022-02-06T12:42 GRIB to CDM+CF via cfgrib-0.9.1...