wxprofilers: Weather profiler instruments in Python¶

wxprofilers provides tools for working with weather profiler instruments such as wind lidars, microwave radiometers, and radiosondes in Python. It converts data files into xarray objects, and can derive or estimate weather variables such as wind speeds, PBL height, and CAPE.

Installation¶

Requirements¶

a fortran compiler, such as gfortran
Python 3
cython
numpy

Python 2 is not supported.

Installing with pip¶

After the requirements have been installed, wxprofilers can be installed from Github using pip:

pip install git+https://github.com/ASRCsoft/wxprofilers.git

Wind Lidars¶

Functions for converting wind lidar files to xarray datasets are in the wxprofilers.convert module.

import wxprofilers.convert as wxp

NYS Mesonet csv files¶

lidar = wxp.lidar_from_csv(rws='20170225_whole_radial_wind_data.csv',
                           scans='20170225_scan.xml',
                           wind='20170225_reconstruction_wind_data.csv')

Microwave Radiometers¶

Functions for converting microwave radiometer files to xarray datasets are in the wxprofilers.convert module.

import wxprofilers.convert as wxp

Radiometrics csv files¶

mwr = wxp.mwr_from_csv('2017-02-25_00-04-11_lv2.csv', resample='5T')

Radiosondes¶

Functions for converting radiosonde files to xarray datasets are in the wxprofilers.sonde module.

import wxprofilers.sonde as sonde

NWS BUFR files¶

wxprofilers includes the National Climatic Data Center (NCDC)’s RRS Decoder to extract text files from binary radiosonde BUFR files.

sonde.decode_rrs('94983_2005102412', '56')

Plotting¶

wxprofilers adds a few plotting options in addition to xarray’s excellent plotting capabilities.