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ASCII Downloader was added, 19 Dec. 2019.

We added new function "ASCII Downloader" to convert CDF/netCDF to ASCII files, on UDAS web.

Capture Image:

This function converts CDF/netCDF to ASCII files, and enables you to download it to your local PC. It is useful for easy reading on your analysis software and confirmation of actual numerical values immediately. In addition, it is also very effecive for comparing several research field data on universal platform for data fusion.

Quick Look Images about Geomagnetic Data (WDS Kyoto), 26 Nov. 2018.

 The Data Analysis Center for Geomagnetism and Space Magnetism (DACGSM), Kyoto University collects long-term geomagnetic field data measured by magnetometers installed all over the world and provides them for researchers and data users as a World Data Center for Geomagnetism (WDC Kyoto). DACGSM is also one of the IUGONET members, and manages these geomagnetic field data, metadata, and analysis routines. We created its Quick Look images (PNGs) with UDAS (IUGONET Data Analysis Software) on SPEDAS. The number of geomagnetic stations is 437, and the oldest station was built in 1883.
 Recently, several interdisciplinary researches combining several data which originate from different fields make significant progress, for example: Classic Books, Social Data, Scientific Data and so on. These historical data become very valuable and useful and may create new discoveries and theories. We hope for researches to use our database for such activities.
Examples (WDC Data only):
Examples (Comparison with Dst/AE/SYM):
Detailed information of WDS Kyoto:
For older data, please contact WDC Kyoto.

Quick Look Images and How to Analysis about MAGDAS Data (ICSWSE, Kyushu University, Japan) was added, 22 Feb. 2018.

 The MAGDAS (MAGnetic Data Acquisition System) is worldwide magnetometer array operated by International Center for Space Weather Science and Education (ICSWSE), Kyushu University, and now being deployed in order to carry out space weather studies and educations.
 We need to clarify the dynamics of geospace plasma changes during magnetic storms and auroral substorms, the electro-magnetic response of iono-magnetosphere to various solar wind changes, and the penetration and propagation mechanisms of DP2-ULF range disturbances from the solar wind region into the equatorial ionosphere. By using this new MAGDAS data, we can conduct real-time monitoring and modeling of (1) the global 3-dimensional current system (2) the ambient plasma density for understanding the electromagnetic and plasma environment changes in the geospace, and so on.
Examples (MAGDAS):
Examples (MAGDAS and Dst/AE):

Detailed information:

How to create plot (SPEDAS CUI#Basic Command and CUI Operating Procedure) was added, 28 Aug. 2017.

 We renewed the "How to plot" section in the metadata display page.
 The "How to plot" section shows the IDL/SPEDAS commands to plot the found data and helps users to analyze the data with IDL/SPEDAS. The section is divided into three parts as follows.
"CUI #Basic" : IDL/SPEDAS commands minimally required to plot the data.
"CUI #Advanced" : IDL/SPEDAS commands used to create quick-look (QL) plot
 in the metadata display page.
"GUI" : How to plot the data with SPEDAS-GUI.
 Detailed information of SPEDAS:

The first campaign of the ERG (Arase) - ground coordinated observations in March - April, 2017.

 The Arase (ERG) satellite was launched at 20:00 (JST) on December 20, 2016 from Uchinoura Space Center, JAXA with an ellipse orbit (perigee: 320 km, apogee: 33,200 km, and period: 580 min). All the instruments of the Arase satellite has been recently operated and measure DC electric and magnetic field variations, plasma waves and energetic particles in the inner magnetosphere.
 In the first campaign observation, we operate various kinds of ground-based instruments such as the EISCAT radar, all-sky camera, EMCCD camera, induction magnetometer, riometer and related instruments near the footprint of the orbit of the Arase satellite in order to clarify the generation and loss mechanisms of high-energetic particles in Geospace and magnetosphere-ionosphere-termosphere coupling process during geomagnetic storms and substorms.
 Detailed information of this campaign:
 Schedule and main ground-based collaborators:
  1, 2017/03/23 04:09-07:02UT, Husafell (Iceland), PWING and PSA.
  2, 2017/03/23 09:49-11:38UT, Athabasca (Canada), PWING and PSA.
  3, 2017/03/25 00:50-01:45UT, Tromso (Norway), EISCAT.
  4, 2017/03/26 23:17-26:35UT, Tromso (Norway), PWING and PSA.
  5, 2017/03/28 13:38-14:10UT, Gakona (Alaska), PWING and PSA.
  6, 2017/03/28 22:34-27:15UT, Tromso (Norway), EISCAT.
  7, 2017/03/30 12:28-14:56UT, Gakona (Alaska), PWING and PSA.
  8, 2017/03/31 00:00-03:30UT, Tromso (Norway), EISCAT.
 Our IUGONET team has collected the Quick-Look images of the campaign observations taken by various kinds of ground-based instruments, and registered the metadata to IUGONET Type-A. Now, you can easily and immediately see these Quick-Look images from this site. Please check it!

PWING Data Come, 10 Feb. 2017.

 PWING (Study of dynamical variation of particles and waves in the inner magnetosphere using ground-based network observations) is the project to aiming at future secure/safe space use by understanding the particle acceleration and loss in the inner magnetosphere.
 This project has been conducted by Prof. Kazuo Shiokawa, Institute for Space-Earth Environmental Research (ISEE), Nagoya University, and promotes a study of temporal and spatial distributions of energetic particles and ELF-VLF plasma waves in the inner magnetosphere by installing the five ground-based instruments in the sub-auroral to auroral regions with the same longitudinal intervals.
 Details of the PWING project are described on the PWING web site ( If you want to know information of the PWING instruments and data, please see the metadata of each dataset and read carefully them.
 Our IUGONET system team collaborate with PWING project, and we produce the function to compare the plots of all observatories and instruments of PWING by 1-click. This page also has a 'page-a-day viewing' function. It is easy to check PWING data.

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