Thursday, 31 August 2023: 4:30 PM
Great Lakes A (Hyatt Regency Minneapolis)
Adam Theisen, Argonne National Laboratory, Lemont, IL; and K. Kehoe, M. Grover, and S. M. Collis
For every research radar (vertical and scanning), there is a need to monitor, assess, and track the quality of that radar’s data and its calibration. While there are a number of tools available for working with radar data (Py-ART, Wradlib, etc..), there is not a core library for easily assessing the quality and calibration of a research radar. The Radar Tracking of Quality (RadTraQ) toolkit is a python library with the goal of bringing together the radar research community through the use of standard and open tools and processes across organizations in the quality assessment of research radar data. It is currently a work in progress, housing routines that the Department of Energy Atmospheric Radiation Measurement user facility’s (ARM) Data Quality Office uses for monitoring the suite of vertically pointing and scanning radars in ARM’s radar facility.
RadTraQ functionality extends to analyzing and visualizing corner reflector scans, creating cloud masks (Kollias et al 2014), calculating noise floors (Kollias et al 2014), performing profile comparisons between radars and more. Expanding this toolkit through workflows could provide significant benefit for many organizations and accelerate scientific discovery for scientists and student researchers alike. Contributors to this library will automatically be included in the DOI. Each function, if available, will include a “Reference” section in the code and documentation to make it easier for users to include references to the papers behind these algorithms in their own research.
Supplementary URL: https://github.com/ARM-Development/RadTraQ

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