Using BUFR¶

In this notebook you will see how to:

• inspect BUFR data

• extract BUFR data into a Pandas dataframe

Getting the data¶

First we read some BUFR data from disk with from_source.

Featurelists and BUFR messages¶

To inspect BUFR data we need to convert it into a featureslist. It is a similar object to a fieldList, but it is an iterable of “features”, where a “feature” can be anything. In a BUFR featurelist each feature is a BUFR message.

The file contains 10 messages.

With the ls() method we can get a summary of the messages (using header keys).

BUFR messages¶

To dump the contents of a message (as a tree view) use describe().

Subsetting¶

With sel() we can select the messages matching the given metadata conditions.

Converting to pandas¶

BUFR data can be extracted into a Pandas dataframe using to_pandas(), which passes all the arguments to the read_bufr() method from pdbufr.

Please note it is also possible to call to_pandas() on the input data object “d”. It this case, first the data is converted to a featurelist under the hood, then to_pandas() is called on the featurelist.

Extra work¶

Get the “temp_10.bufr” radiosonde BUFR file as a sample and extract the latitude-longitude and the pressure-temperature profile from it for station “01415”.

Hints:

• use the “indent” key for the station ID

• use the “filters” kwarg in to_pandas() (for details about the format see here)

• use the “pressure” and “airTemperature” keys (use describe() to inspect the radiosonde message structure)