The PI of the NSSC SuperDARN group, Dr. Jiaojiao Zhang, has announced that the deadline for submission of items has been extended for the 2022 edition of the SuperDARN Workshop. The workshop will be hosted by the National Space Science Center (NSSC), Chinese Academy of Sciences (CAS). The format will be virtual. Dr. Zhang adds that the pre-recorded presentations will be available May 23-June 3 through the Pre-recorded Conference Entrance. Note that May 15, 2022 is the deadline for submission of your pre-recorded presentation as well as registration and abstract submission.

The conference web site is: https://superdarn2022.swl.ac.cn

For a synopsis of the SuperDARN Workshop, see 'Read More'

On behalf of the SuperDARN Data Visualization Working Group (DVWG) Carley Martin has announced the release of pyDARN v3.0.

In this release, we include the optional cartopy dependency for underlaid maps and convection maps in magnetic coordinates. Along with a number of other bug fixes and improvements.

To install:
pip3 install --upgrade pydarn​

Or you can download the zip on Zenodo: https://zenodo.org/record/6473574

Any information on using pyDARN can be found in our documentation here: https://pydarn.readthedocs.io/en/main/

On behalf of the SuperDARN Data Analysis Working Group (DAWG), Co-chairs Emma Bland and Kevin Sterne have announced a minor release of the Radar Software Toolkit, RST 4.7. It is available for download from Zenodo: https://doi.org/10.5281/zenodo.6473603

Key updates in RST 4.7 include:
New routine to list the transmission frequency bands present in a fitacf file (find_freqband)
New functionality and documentation for the data simulator (make_sim)
Updated C and IDL code for reading the new hardware file format (Note: the old hardware file format is incompatible with RST 4.7. The new hardware files are included in this release)
Bug fixes that affected compilation on some systems
Bug fixes in various analysis and plotting routines

To cite the software in publications:
SuperDARN Data Analysis Working Group, Burrell, A.G., Thomas, E.G., Schmidt, M.T., Bland, E.C., Coco, I., Ponomarenko, P.V., Sterne, K.T., & Walach, M.-T. (2022). SuperDARN Radar Software Toolkit (RST) (Version 4.7). https://doi.org/10.5281/zenodo.6473603

On behalf of the SuperDARN Data Visualization Working Group, Marina Schmidt of the University of Saskatchewan has announced the release of version 2.2 of pyDARN, a python library used for data visualization of SuperDARN data. It can be downloaded from pip via:

pip install pydarn
or upgrade if you already have it
pip install --upgrade pydarn
or Zenodo: https://zenodo.org/record/5605069

Please cite in any publications when using pyDARN.
The documentation for pyDARN includes tutorials for the new features: https://pydarn.readthedocs.io/en/main/index.html
For a description of the new features and additional information, click 'Read More'

SuperDARN founder Ray Greenwald has published the first of a planned 3-part series on the history of SuperDARN in the journal 'History of Geo- and Space Sciences'. The paper covers the pre-SuperDARN era from experiments using HF coherent radar in Alaska with Jean-Paul Villain through the construction of radars at Goose Bay, Schefferville, and Halley Station and the development of techniques critical to the development of SuperDARN. The article is available for download from the site 'SuperDARN+https://hgss.copernicus.org/articles/12/77/2021/'

Ray dedicated this history to the memory of three SuperDARN pioneers who made significant contributions that demonstrated the value of HF radar measurements of the ionosphere and magnetosphere, particularly at high latitudes. They are John C. Samson, Jean-Paul Villain, and A. David M. Walker.

Congratulations, Ray! We look forward to the next installment.

On behalf of the SuperDARN Data Analysis Working Group, Co-chairs Emma Bland (UNIS) and Kevin Sterne (Virginia Tech) have announced a new minor release of the Radar Software Toolkit, RST4.6. The new release can be downloaded here: https://doi.org/10.5281/zenodo.5156752. Users are encouraged to contact WG members if they have questions or find problems with the software. New contributions to the software are also most welcome. The WG can be contacted by opening an "issue" on Github (https://github.com/SuperDARN/rst/issues), or alternatively by email. For more information, click 'Read More'.
Emma and Kevin say 'Many thanks to everyone who has contributed to the development and testing of this release!'

To cite the software in publications: SuperDARN Data Analysis Working Group, Schmidt, M.T., Bland, E.C., Thomas, E.G., Burrell, A.G., Coco, I., Ponomarenko, P.V., Reimer, A.S., Sterne, K.T., & Walach, M.-T. (2021). SuperDARN Radar Software Toolkit (RST) (Version 4.6). Zenodo. https://doi.org/10.5281/zenodo.5156752