Published February 7, 2026 | Version 3.0

SuperDARN data in netCDF format (2017-Jan)

  • 1. JHU/APL

Description

2017-Jan SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.

The RST is available here: https://github.com/SuperDARN/rst

The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.

Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)

Recommended form of acknowledgement for the use of SuperDARN data:

'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'

Files

20170101.nc.zip

Files (7.7 GB)

Name Size
md5:c885fcc7a00ccec1709ab8e77ea52feb
228.7 MB Preview Download
md5:a74728e3e297d0abcfff93c2b3fde11b
220.2 MB Preview Download
md5:c77f983258786b5691298b946569aa91
250.6 MB Preview Download
md5:ff0f00a9afcf4f9f5bf4ac231f0bd3b3
191.1 MB Preview Download
md5:daa9f9394b7577be64c0650f9a370e63
242.6 MB Preview Download
md5:db8b16268f5e90c2c15e4eb389a19729
187.0 MB Preview Download
md5:0a3cc57ac973bdc03d5e8b806e6fbc17
252.0 MB Preview Download
md5:e0e2308b60a55d4e3e13369699a4a9c7
242.8 MB Preview Download
md5:663d14ba742a44e749869d9ea4f3c816
260.5 MB Preview Download
md5:a8bc6e008b2e9989cb440c8c65112a71
261.4 MB Preview Download
md5:1e9185ab7908e024dd0c315180ffcb1a
261.7 MB Preview Download
md5:7dc1c0e2673882942aa2292613a697fa
277.9 MB Preview Download
md5:f2eaaf3821ebd53ae414a1240c881fe0
205.5 MB Preview Download
md5:436504098df187860278679b5babda39
212.5 MB Preview Download
md5:a1bf9c796cfe53957b4cc86bd5fafe8d
221.6 MB Preview Download
md5:961fa7199b5c190794303fd862794462
251.0 MB Preview Download
md5:c70087151a19266be8582c50e33ed086
261.7 MB Preview Download
md5:d15254a4f0c5fcb1373a72f6c45fe3b2
279.3 MB Preview Download
md5:d471c319ea2bd5855f5e66d28c61d00e
228.7 MB Preview Download
md5:575969b1b380d9c86b7b9b3718f033da
231.7 MB Preview Download
md5:4d3d3b3793a995bd3cb9c1608bb08bfc
272.7 MB Preview Download
md5:59390c87309ad2e574c7784a2dc649b1
234.7 MB Preview Download
md5:77865071029f11c3d29b1661ad313988
249.0 MB Preview Download
md5:60ad1b788bfb64884ee3837bd763a562
235.6 MB Preview Download
md5:9875fd2a04db5f31c530537b9b291742
272.8 MB Preview Download
md5:82a8b55be2222d395550292b50d8a4d7
274.2 MB Preview Download
md5:9798ce7dccc8fdc90cb17c4149ad3f9d
272.2 MB Preview Download
md5:e21ebaee46e2abedb30ab515c2ab4256
267.0 MB Preview Download
md5:d8bf1d45e0c3bbdc0ebf0d83d3a69794
285.0 MB Preview Download
md5:74080f83dc07f4a1125218d8a0cf4a0c
272.2 MB Preview Download
md5:a4505882feb377b5b88c8ee65b9fdabf
276.7 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/101.0289 (DOI)