pyDARN: A Python software for visualizing SuperDARN radar data

Xueling Shi, Marina Schmidt, Carley J. Martin, Daniel D. Billett, Emma Bland, Francis H. Tholley, Nathaniel A. Frissell, Krishna Khanal, Shane Coyle, Shibaji Chakraborty, Marci Detwiller, Bharat Kunduri, Kathryn McWilliams

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Article number1022690
JournalFrontiers in Astronomy and Space Sciences
Volume9
DOIs
StatePublished - Dec 1 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics

Keywords

  • Super Dual Auroral Radar Network
  • ionosphere
  • python
  • radar
  • space weather

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