Published February 9, 2026 | Version 3.0

SuperDARN data in netCDF format (2017-Dec)

  • 1. JHU/APL

Description

2017-Dec 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

20171201.nc.zip

Files (9.9 GB)

Name Size
md5:27014ecf947aa6cd253a271cce1a996c
350.9 MB Preview Download
md5:442f67cac9fb939495c1682823c8d851
310.2 MB Preview Download
md5:44fd6a2b008ae4db05aaa374b4d04290
301.6 MB Preview Download
md5:80adc1d2c9653d418e1fb9d8328b2264
335.6 MB Preview Download
md5:80548beb9c217d8424d1bb2c2c2b2a8b
301.5 MB Preview Download
md5:5c54c02c8b2fb9dd20d94dc2fcba4911
284.6 MB Preview Download
md5:711157d188aafbe69c237b59562d26f7
299.2 MB Preview Download
md5:fad362f8419feafe3d66aa382caa06bb
284.6 MB Preview Download
md5:d1d9099f4c55c78516fb6d00f5394eba
279.6 MB Preview Download
md5:74d9997e0ef0db157d70841baa307edf
296.6 MB Preview Download
md5:cce8b41211166d59c98d88fa4e458e6f
336.1 MB Preview Download
md5:def28e8909d383084affc36b69028718
319.7 MB Preview Download
md5:0d1c645641daab9d6c47d9770ca7896c
308.1 MB Preview Download
md5:117a689c607c4f298128437557bbb9f1
287.0 MB Preview Download
md5:482dd6cc533a44fb1df8fa06061e9aed
292.9 MB Preview Download
md5:b882a552fa721d78b447cef2b3372a2d
330.5 MB Preview Download
md5:ab295fb1d4ca03a6f7f3378d1490b673
344.1 MB Preview Download
md5:4faed4dff7180d0201dd075172da1fc7
262.7 MB Preview Download
md5:a719c25a7c67e255bea06e12ba195461
327.9 MB Preview Download
md5:eb785fb696ed111d06b1ac3b6441b6c6
335.3 MB Preview Download
md5:dcc9d8c354e4db72082a48696983fe13
304.7 MB Preview Download
md5:3db7a01dd3b52fc7b817beb81ae12393
361.1 MB Preview Download
md5:bc40ee3fd65bfbd64b401e66293ec23e
366.6 MB Preview Download
md5:578d2db8ad8d9c6a61eaacc81bbbf5be
351.7 MB Preview Download
md5:a8ebcbec3bcf3cc03c8286aabc62ae06
349.0 MB Preview Download
md5:31fa886cf85ae4f427fb5354424f9359
356.9 MB Preview Download
md5:6313526bc8e3a00bdeedd94d02ba0b5b
332.4 MB Preview Download
md5:cb4cf692206d35a9203d0e3ba4bbfd43
275.7 MB Preview Download
md5:4d3c50cc99741d4463d15cc065ba5487
284.9 MB Preview Download
md5:77a733193834c7c19020105756053603
311.0 MB Preview Download
md5:20441d634c8f896c6482847d1af35f3d
381.9 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/101.0289 (DOI)