The examples in this directory use the ERA5 surface dataset (as assembled by Pangeo), which consists of 19 data variables stored in float32 precision. It totals 24.8 TB in size:
>>> xarray.open_zarr('gs://pangeo-era5/reanalysis/spatial-analysis', consolidated=True)
<xarray.Dataset>
Dimensions: (latitude: 721, longitude: 1440, time: 350640)
Coordinates:
* latitude (latitude) float32 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0
* longitude (longitude) float32 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8
* time (time) datetime64[ns] 1979-01-01 ... 2018-12-31T23:00:00
Data variables: (12/17)
asn (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
d2m (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
e (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
mn2t (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
mx2t (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
ptype (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
... ...
tcc (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
tcrw (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
tp (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
tsn (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
u10 (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
v10 (time, latitude, longitude) float32 dask.array<chunksize=(31, 721, 1440), meta=np.ndarray>
Attributes:
Conventions: CF-1.6
history: 2019-09-20 05:15:01 GMT by grib_to_netcdf-2.10.0: /opt/ecmw...
TODO(shoyer): add instructions for running these examples using Google Cloud DataFlow.