pccora 0.3

History

I was asked by a co-worker to look at some Python code with a PC-CORA parser. This co-worker also needed further analysis and processing, involving some data being created as CSV, netCDF, or plotted.

I decided to write a module for PC-CORA inspired by the original script, but using Python3, OO, and packaging as a Python package to be distributed to the PYPI.

This way we could use it in scripts, or other internal applications. And it would also be easier for others to find it and re-use.

The code in this repository was used on a Doctoral Thesis published in 2018, about radiosonde, GCOS, radio occultation, and weather prediction.

Example

>>> from pccora import PCCORAParser
>>> pccora_parser = PCCORAParser()
>>> pccora_parser.parse_file('./123456789.EDT')
>>> print(pccora_parser.get_header())
>>> print(pccora_parser.get_identification())
>>> print(pccora_parser.get_data())

Obtaining Data

There are datasets available at the CEDA website (Centre for Environmental Data Archival), however, access is restricted.

NOAA’s ESRL (Earth System Research Laboratory) has an FTP server with some data in the the old PC-CORA sounding data format. Just search for FTP for instructions on how to access the Physical Sciences Division FTP server. Some valid files can be found at /psd3/cruises/AERO_1999/RHB/balloon/Raw (accessed 2016-01-17).

Requirements

Python 3.6 or superior, and the construct library are the minimum requirements.

Installation

pip install pccora

Or, to use the bleeding edge version, git clone this repository, and have a look at the scripts folders for an example how to use the module from within a local folder. You may have to uninstall the pip module first.

python setup.py install

The PYPI URL is https://pypi.python.org/pypi/pccora.

License

Licensed under the MIT License.