AUTHOR=Shi Xueling , Schmidt Marina , Martin Carley J. , Billett Daniel D. , Bland Emma , Tholley Francis H. , Frissell Nathaniel A. , Khanal Krishna , Coyle Shane , Chakraborty Shibaji , Detwiller Marci , Kunduri Bharat , McWilliams Kathryn TITLE=pyDARN: A Python software for visualizing SuperDARN radar data JOURNAL=Frontiers in Astronomy and Space Sciences VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/astronomy-and-space-sciences/articles/10.3389/fspas.2022.1022690 DOI=10.3389/fspas.2022.1022690 ISSN=2296-987X ABSTRACT=

The Super Dual Auroral Radar Network (SuperDARN) is an international network of high frequency coherent scatter radars that are used for monitoring the electrodynamics of the Earth’s upper atmosphere at middle, high, and polar latitudes in both hemispheres. pyDARN is an open-source Python-based library developed specifically for visualizing SuperDARN radar data products. It provides various plotting functions of different types of SuperDARN data, including time series plot, range-time parameter plot, fields of view, full scan, and global convection map plots. In this paper, we review the different types of SuperDARN data products, pyDARN’s development history and goals, the current implementation of pyDARN, and various plotting and analysis functionalities. We also discuss applications of pyDARN, how it can be combined with other existing Python software for scientific analysis, challenges for pyDARN development and future plans. Examples showing how to read, visualize, and interpret different SuperDARN data products using pyDARN are provided as a Jupyter notebook.