Try this notebook in .

!test -f ens_multi_subset_uncompressed.bufr || wget https://get.ecmwf.int/repository/test-data/pdbufr/test-data/ens_multi_subset_uncompressed.bufr

Generic: ENS point foreacast

import pdbufr

The input BUFR data contains ensemble forecast data for a given location. There is only one message in the file having 51 uncompressed subsets (one subset per ensemble member).

In this notebook we read this data with the generic reader, which is the default reader.

Example 1

Extracting forecast data for the control forecast member:

df = pdbufr.read_bufr("ens_multi_subset_uncompressed.bufr",
    columns=("ensembleMemberNumber", "latitude", "longitude", "timePeriod",
             "airTemperatureAt2M"),
    filters={"ensembleMemberNumber": 0})
df

	ensembleMemberNumber	latitude	longitude	timePeriod	airTemperatureAt2M
0	0	51.52	0.97	0	292.7
1	0	51.52	0.97	6	291.6
2	0	51.52	0.97	12	291.0
3	0	51.52	0.97	18	290.0
4	0	51.52	0.97	24	291.2
...	...	...	...	...	...
56	0	51.52	0.97	336	292.0
57	0	51.52	0.97	342	292.2
58	0	51.52	0.97	348	291.4
59	0	51.52	0.97	354	290.1
60	0	51.52	0.97	360	292.4

61 rows × 5 columns