Published January 16, 2026 | Version 3.0

SuperDARN data in netCDF format (1995-Jul)

  • 1. JHU/APL

Description

1995-Jul 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

19950701.nc.zip

Files (726.8 MB)

Name Size
md5:14c932e2a8160c129fb16a0cbba73f8a
16.2 MB Preview Download
md5:7dbef730963e5ed4b6ada4a5569b9f16
20.3 MB Preview Download
md5:5d30679e2173b77fd97d64ac939e3524
23.9 MB Preview Download
md5:eb5c39ecac55c652c0b967dd23e6c3c0
25.8 MB Preview Download
md5:6c994b641eb787c1f74ee7f89810c19a
25.1 MB Preview Download
md5:a4b7ea59befe66d3ded0f6ed7802526e
28.1 MB Preview Download
md5:981bde1de1b82819a9e1bbf9e11d4083
32.4 MB Preview Download
md5:d73f1c4a5c082e3afc32e676c0ab8e7b
30.6 MB Preview Download
md5:00625920497f77d58c201dec6383550d
27.2 MB Preview Download
md5:661e2a913f5a3e4c0851fc10f634da26
27.9 MB Preview Download
md5:5df4435d14b319fd031ea64bdc24a7a5
24.1 MB Preview Download
md5:3054e5f826b2f1b14dfff60293f61fa0
26.0 MB Preview Download
md5:e852bbba0aa6f5cd1331ba3bddb1faec
28.7 MB Preview Download
md5:c85d148652fb6f44a217ad55ff86d338
30.8 MB Preview Download
md5:e558f30b48df4ecc1f1290080f079e8b
28.9 MB Preview Download
md5:250bfad760af259fb6c9e87de046687d
28.9 MB Preview Download
md5:c4769efe4cd2b50c494502f4e0d63b1f
19.6 MB Preview Download
md5:7d24c5a582bef4ccf0e9b92162de9709
17.8 MB Preview Download
md5:b4c8296ac465e74f5b4c7c44488f877f
17.3 MB Preview Download
md5:414bb74ebb3d72beb21223bac3587351
15.8 MB Preview Download
md5:0aa391e5238882343702ab55a9005dcd
18.9 MB Preview Download
md5:8a0b579c3990bd77aa4a6a4afeb666fa
15.7 MB Preview Download
md5:93b582d434dc78bc92675bf2592772bd
18.1 MB Preview Download
md5:cb8ef58217e18be46ffd024dd1e067e1
21.9 MB Preview Download
md5:37fbbe1dc7fc3b1bdb7453683c41337d
19.6 MB Preview Download
md5:ecd035acb32c77d85daca6ab1480bb89
17.4 MB Preview Download
md5:dde6b26c53e2df74d19db2253e931599
24.3 MB Preview Download
md5:5626474332c921f55ba3257895e146c1
24.2 MB Preview Download
md5:f240b4dba34170a703ac100eb880603f
26.7 MB Preview Download
md5:1812efab5640d2073614ce25513e2b27
25.6 MB Preview Download
md5:8f11d643100dd34586e1623de94387d0
19.4 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/102.0469 (DOI)