Dear SuperDARN users,
The Data Analysis Working Group is pleased to announce the new minor release of the Radar Software Toolkit, RST4.6.
The new release can be downloaded here: https://doi.org/10.5281/zenodo.5156752
Key updates in RST 4.6 include:
> Routine for removing non-gaussian noise/interference from fitacf files (fit_speck_removal)
> Routine to display the contents of old-format dat files (datdump)
> Shepherd (2017) elevation angle algorithm added to FITACF3.0
> Ability to plot multiple fields of view with fov_plot
> Added missing mlt2mlon keyword to MLT_v2 IDL/DLM code
> make_grid detects and concatenates multiple input files automatically (deprecates -c flag)
> Check that the search noise is nonzero before using it to replace the skynoise in FITACF3.0
> Check whether interferometer array is in front or behind main array when calculating elv_low/elv_high in FITACF2.5
> Fixed bugs in plotting libraries, cdf file reading, make_grid and trim_raw
> Update hardware files for DCE and DCN, and PI institution information in radar.dat
> Improved compliance with GPLv3 license requirements
> Documentation updates
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
Installation instructions and RST tutorials are available in the documentation: https://radar-software-toolkit-rst.readthedocs.io/en/latest/
We encourage users to contact us if they have questions or find problems with the software. New contributions to the software are also most welcome. You can contact us by opening an "issue" on Github (https://github.com/SuperDARN/rst/issues), or alternatively by email.
Many thanks to everyone who has contributed to the development and testing of this release!
Best regards,
Emma Bland & Kevin Sterne
Co-chairs, SuperDARN Data Analysis Working Group
https://superdarn.github.io/dawg/
