Published February 10, 2026 | Version 3.0

SuperDARN data in netCDF format (2018-Dec)

  • 1. JHU/APL

Description

2018-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

20181201.nc.zip

Files (6.8 GB)

Name Size
md5:e449e050e75b2c6059d1300da3ac836f
283.2 MB Preview Download
md5:9479b4261c67ae3d50912834793a4446
257.9 MB Preview Download
md5:58ed92d2893fce1b09c1e1500e52bf74
263.5 MB Preview Download
md5:f14885d82c0e8185dfd75fdf4ec3af88
269.3 MB Preview Download
md5:b7669a2ef4b6aae623776d0cd2c671a3
207.9 MB Preview Download
md5:fb6159524085c22e811f0a8e1dec772b
177.3 MB Preview Download
md5:99714e0f3252511644113fed6508089d
228.9 MB Preview Download
md5:6f8c34444b4f42de3fe0e6c8e3bf8a4e
188.5 MB Preview Download
md5:656a32bdd5b86d4edc72542b1ee248ca
178.9 MB Preview Download
md5:4e6ecbe923e90c4a9a7c7d3934d7153f
184.7 MB Preview Download
md5:46f6aca5d1a466bdadb6ea1ab93e482a
208.1 MB Preview Download
md5:16a2f2603db34d9ad9af3f32a3b4da8f
228.0 MB Preview Download
md5:f8d6b8032a6b03d74bdef99bb1588e65
226.3 MB Preview Download
md5:177094b9b01c4d4b38bcf98ba9f0cb39
240.0 MB Preview Download
md5:0313fafa5d066631b9f7ea46ca88a2df
217.3 MB Preview Download
md5:2d85db89829dd4766bfc1997b6f91074
246.5 MB Preview Download
md5:bb008e27ee5985e460122e4d40729a0d
253.0 MB Preview Download
md5:77fddd31083d6f0e5bf9757c143ad5ac
251.1 MB Preview Download
md5:37c01b3f81c3c08fed601273fa8a9ff4
229.8 MB Preview Download
md5:986817660ae336a529a97723d12f277f
210.3 MB Preview Download
md5:c3baa730b911008b43a090e9d69b5481
193.7 MB Preview Download
md5:c2ab8729c1c0d5593adfd9b976ad4db9
214.3 MB Preview Download
md5:8b615fcc0d3091764a87cbd373fdee8a
192.7 MB Preview Download
md5:c040ed73c13459a3b89ed9fadb007921
207.4 MB Preview Download
md5:119e749bdb1c2ccabf5c570a1db341bf
205.4 MB Preview Download
md5:b4af9adf0ff545db6f149fdcd7a1620a
195.0 MB Preview Download
md5:6d351b84d7c78a08a250f531419a57ef
211.6 MB Preview Download
md5:c828070ec2dec3f01a1be9895fdf2fc5
217.3 MB Preview Download
md5:7c6ddbfa581587cddf83c853706aed9c
199.6 MB Preview Download
md5:a1958c84d4df1295348d5af732700fe5
194.2 MB Preview Download
md5:6d4ff72ac25c43e37de0275a1da38c40
176.2 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/101.0290 (DOI)