Published January 16, 2026 | Version 3.0

SuperDARN data in netCDF format (1995-Mar)

  • 1. JHU/APL

Description

1995-Mar 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

19950301.nc.zip

Files (575.0 MB)

Name Size
md5:27abf8567894afab2b708b7a0d939c3f
15.3 MB Preview Download
md5:1d959653f21c419df87c4b981cf75b25
12.8 MB Preview Download
md5:82b2e18a5d1240812f17bc408cfca9c1
13.7 MB Preview Download
md5:b8d549b8694458afdf57fbc8c35e2733
15.4 MB Preview Download
md5:006d62407b0d7f1ea4bbc1a46275d4c0
16.8 MB Preview Download
md5:14f6621f09919bbd215435d699feff5a
21.1 MB Preview Download
md5:2a036b50b91f9504fda5071630d846b8
19.8 MB Preview Download
md5:d4d3eef93fd189961b036aaf4a35fd8b
27.1 MB Preview Download
md5:1310450dde07d8c97420d2bbf4c61ac5
30.6 MB Preview Download
md5:f07edd3624742d6396eb0feb04b97122
23.2 MB Preview Download
md5:7a832135dbd2e4ff951b22c6a2d5c300
19.3 MB Preview Download
md5:1b14b27063a7dacbad44222064f2263f
13.2 MB Preview Download
md5:319f3f9103bde295b201db62fafd7272
8.3 MB Preview Download
md5:8322e1d8443dab4de9e8cb76cc7a9815
9.8 MB Preview Download
md5:b74961e9202c06924b975b5f596eb586
11.8 MB Preview Download
md5:b228d5e20c3e12f60b4d09b6a5bc5d67
11.2 MB Preview Download
md5:a3c7b7261367597dcb171f68d5b9c927
19.2 MB Preview Download
md5:0249cf80bae4913459e647ccc29a56f5
17.5 MB Preview Download
md5:3a8ae0cba7062facedba84067cf985f5
21.1 MB Preview Download
md5:658838c5e14c74bcec68dbd1abeee6b9
20.6 MB Preview Download
md5:bdee3a2a60cfb9dc933bc111d8bf6ee4
20.1 MB Preview Download
md5:1b13c8a84d0620a1faeda00c5a671f37
25.2 MB Preview Download
md5:de1247c51d6cc82b5187656d49d3bcea
27.7 MB Preview Download
md5:d0e657e2da13326bd7864549ed52b061
27.2 MB Preview Download
md5:8d4155d4b6fec5a7a5db51a95a091d1c
21.8 MB Preview Download
md5:53a8ed5d4a5432d562623dea9a359250
14.7 MB Preview Download
md5:ab7082e58d8630c2026fbcac214adf25
15.7 MB Preview Download
md5:b3834d344989f6aa40aa6510969f84f5
18.2 MB Preview Download
md5:ea54d774d607040cdab2163979fc0f32
16.3 MB Preview Download
md5:6c2b6996b0cbd15f810a83881c97023b
18.8 MB Preview Download
md5:f43d90db6456ce42071c06a16795f8ff
21.4 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/102.0469 (DOI)