Scientists develop an open-source radar toolkit to advance the analysis of research radar data.
Cloud and precipitation radars provide abundant data for the weather and climate communities, but considerable effort is required to extract scientifically meaningful parameters. Converting raw voltage measurements to geophysical parameters requires a combination of signal processing techniques, quality control and correction routines, and application of scientific algorithms. The Python ARM Radar Toolkit (Py-ART) enables scientists to work effectively with radar data and extract scientific insights from these large datasets.
Development of a flexible, open-source software package for working with radar data has enabled a wide range of users to analyze radar data from the Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program. Py-ART provides an environment for researchers to visualize, correct, and analyze data from all types of radars used by the weather and climate communities. Py-ART has over 100 users who participate in mailing list discussions and has been downloaded over 6,000 times. The library is used to create visualization for a number of websites and has been used for analysis in multiple peer-reviewed publications.
Originally started by ARM scientists, a community of scientists, software engineers, and open-source enthusiasts has come together to develop Py-ART, a library for reading, visualizing, correcting, and analyzing data from weather and climate radars. The toolkit provides a platform for scientists to examine data from cloud and precipitation radars operated by DOE’s ARM program as well as radars operated by other groups.
Py-ART comes with a number of built-in, computationally efficient processing and analysis routines that can be used to process radar data and retrieve meaningful geophysical parameters from the moments collected by the radar. Specific processing routines include modules that convert between azimuth and Cartesian coordinates, unfold radar Doppler velocities, correct attenuation using polarimetric variables, and process differential phase using a linear programming method. Additionally, the toolkit can be used as a platform to rapidly design and test new techniques for analyzing radar data. The toolkit is written in the Python programming language and is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib. The package is open-source software and can be used, modified, and extended by anyone free of charge. Development is coordinated on the social coding website, GitHub, where others are encouraged to contribute and participate.
Contacts (BER PM)
ARM Program Manager
Argonne National Laboratory
Funding for this work was provided by the Department of Energy’s Atmospheric Radiation Measurement program.
Helmus, J. J., and S. M. Collis. 2016. “The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language,” Journal of Open Research Software 4(1), e25. DOI: 10.5334/jors.119. (Reference link)
SC-23.1 Climate and Environmental Sciences Division, BER
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