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IMProToo is an improved processing method for Micro Rain radar. It is especially suited for snow observations and provides besides other things effective reflectivity, Doppler velocity and spectral width. The method features a noise removal based on recognition of the most significant peak and a dynamic dealiasing routine which allows observations even if the Nyquist velocity range is exceeded. To software requires MRR raw data, it does not work with Metek's standard products MRR Averaged Data or Processed Data.
The software can be used under the GPL license
The software is still beta, especially the documentation needs to be enhanced.
The software is developed for python 2.7 and should run on any recent Linux system (and most likely also Mac OS X). Windows is currently not supported, but probably only minor changes are necessary.
The following python packages are required:
An installation routine is not provided, Instead, save the included files in your working directory and import the package using “import IMProToo”. If you save the files in another directory, you have to add this directory to your python path. If you have root permissions, you can also put the files into your python library directory (usually /usr/lib/python).
To use the toolkit, import start python and import it:
read the raw data file (can be gzip-compressed)
rawData = IMProToo.mrrRawData("mrrRawFile.mrr.gz")
create the IMProToo object and load rawData
processedSpec = IMProToo.MrrZe(rawData)
average rawData to 60s
all settings (e.g. creator attribute of netCDF file, dealiasing) are available in the 'processedSpec.co' dictionary and must be set before calculating Ze etc.
processedSpec.co["ncCreator"] = "M.Maahn, IGM University of Cologne" processedSpec.co["ncDescription"] = "MRR data from Cologne" processedSpec.co["dealiaseSpectrum"] = True
calculate Ze and other moments
write all variables to a netCDF file.
In case of any questions, don't hesitate to contact Maximilian Maahn: mmaahn_(AT)_meteo_DOT_uni-koeln_DOT_de