Published February 9, 2026 | Version 3.0
Dataset Open

SuperDARN data in netCDF format (2021-Oct)

  • 1. JHU/APL

Description

2021-Oct 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

20211001.nc.zip

Files (9.8 GB)

Name Size Download all
md5:4b3dd72d093dc9b819769bd2bf556dba
327.3 MB Preview Download
md5:f36dd669786bb63d8e0cb5129b7aeedd
293.1 MB Preview Download
md5:9176398e3adcbdeba95c092899c25613
304.4 MB Preview Download
md5:0e7dea7bd1fac30c34fe91fe7671e7e1
325.1 MB Preview Download
md5:3c39b60d5ebf19a26f69317160d52504
333.1 MB Preview Download
md5:4bf075d4fc960806ecbc91d1e0471e2b
329.6 MB Preview Download
md5:942e6d933a085791eafe420732ae8fff
318.0 MB Preview Download
md5:6edf734192e3906800851a85eaf0703e
365.1 MB Preview Download
md5:fa392be8dbaf6896efe54f41cfda98c0
386.5 MB Preview Download
md5:629023faf5949816a84928c68988494b
375.7 MB Preview Download
md5:c758a74ed3ac50824f7abcf943d856f0
335.2 MB Preview Download
md5:f445a2e0363875a2361060ab5ac75ca5
245.2 MB Preview Download
md5:4e1df6f4253f48fb67f5ae4e32d24cf2
289.7 MB Preview Download
md5:a38e8c0be389eb23ceedc2fcede6d1f0
332.3 MB Preview Download
md5:79697d4db242649669d336511470f21a
341.3 MB Preview Download
md5:78a9b64275e1b47051bfce31c8202477
339.1 MB Preview Download
md5:52e7df962b907599d27a7350cd8c1b54
262.1 MB Preview Download
md5:134494d5861a55f11574375231a2dc21
333.0 MB Preview Download
md5:bbbe31b1e9c80b8909be582a5f20a0af
278.2 MB Preview Download
md5:998481cb1858bfc1d90e32fed4ef8711
330.0 MB Preview Download
md5:67a1f1296ea5245946dac2e767be59dc
331.3 MB Preview Download
md5:4222357c3d37146407ad071927d9e1f9
320.0 MB Preview Download
md5:497b8ccd8ed85a60d14f72ae7be8cacb
341.1 MB Preview Download
md5:f2e0e8fa37c83d0d3ca66e511c1e000e
332.0 MB Preview Download
md5:45d960527f1270a242ff58db5e8009ad
236.8 MB Preview Download
md5:35322d83724eeb4ac4c8fde32ac8a388
246.8 MB Preview Download
md5:f1eb86530c21cb4c6d84641245222a6d
388.5 MB Preview Download
md5:adccc483e360432763d62f30aae6ffa6
321.8 MB Preview Download
md5:a8fc79e8ac4e581ee11a719d2cb34b0b
284.9 MB Preview Download
md5:743f4c2ca22f0960a54bff6139f53d36
298.8 MB Preview Download
md5:97bce53eb3b1663b11f9a56e84ff7402
285.9 MB Preview Download

Additional details

Related works

Is derived from
Dataset: 10.20383/102.0677 (DOI)