Text for Data Analysis- Introduction- Web service IUGONET Type-A- Analysis software SPEDAS/UDAS- Application
Published by IUGONET Project Team, Jan. 2019.
http://www.iugonet.org/
1Analysis Software SPEDAS• The IUGONET Data Analysis Software(UDAS) is the plug-in software for Space
Physics Environment Data Analysis
System(SPEDAS), formerly known as
THEMIS Data Analysis Software suite(TDAS)• The IUGONET data (e.g., geomagnetic
data, aurora data, radar data, and so forth)and many satellite mission data (THEMIS,
GOES, WIND, and ACE) can be handled.

SPEDAS/TDAS• It is possible to use many routines tovisualize and analyze time series data.
• It accesses the IUGONET data through theRelationship
Internet, and then the data are
between UDAS,
automatically downloaded onto the user's
SPEDAS, and IDL
computerHands-on workshop at Polar Research Institute of China on Jan. 31,
20192

Outline of Loading/Plotting Data Using SPEDAS
Data Servers
on the Internet

User
PC

Automatic
download

Data areloaded as
tplot variables

data

SSL, Berkeley,
THEMIS, GBO
CDAWeb, OMNI,ACE, Wind, etc.

Directories for the
downloaded data
are createdautomatically.

data
data

Data can be easily plotted, for example, by only three basis
commands with the SPEDAS-CUI tool.
1. Set a time period
2. Load *** data
3. Plot the loaded datatimespan, ‘yyyy-mm-dd’
iug_load_***tplot, +++If using the GUI tool, only a few simple clicks of your mouse are required to makethe same plot as that created by the above command with the CUI tool
Hands-on workshop at Polar Research Institute of China on Jan. 31,
20193

A variety of SPEDAS(1) Source code of SPEDASBoth CUI and GUI are available.
Commercial license of IDL is required.
All functions in SPEDAS are available.
The latest version of UDAS can be applied.
(2) Executable file of SPEDAS
Only GUI version is available.
Commercial license of IDL is not required.
It includes IDL Virtual Machine, so it can be used justby downloading the archived package.

4 4

Download source code of SPEDAS
Download source code of the latest version of SPEDAS
1. Access to Software page of the THEMIS mission
http://themis.ssl.berkeley.edu/software.shtml
2. Find “Downloads”

1. Click “Download TDAS xx.x + SPEDAS
x.xx source”

5Set IDL path to SPEDAS•Both Windows and Mac–

Copy the downloaded “spedas_x_xx.zip” tothe directory you like and unzip it there.
If you have no idea about the directory,
please copy to– [Windows] C:¥Program
Files¥Exelis¥IDL85¥external– [Mac] /Applications/exelis/idl85/external•Windows
–
–
–
–
–

•

Run IDL8.5.
WindowPreferencesIDLPath
Click “Insert”
Select “spedas_x_xx”
Mark the checkbox on the left and click “OK”.

Mac
–
–
–
–
–

Run IDL8.5.
IDLPreferencesIDLPath
Click “Insert”
Select “spedas_x_xx”
Mark the checkbox on the left and click “OK”.

6

Confirm the installation of SPEDASRun IDL.
IDL> thm_init [enter]
THEMIS countdown: xxxxxx xxxxxx xxxx since launch
THEMIS>  Prompt changes to “THEMIS”.

7

GUI version of SPEDAS
1. IDL> spd_gui•

You can analyze data with GUI tool
similarly to CUI tool.
8How to install SPEDAS-GUI (VM version)
Even if you have not yet installed IDL on your PC, you can install
GUI tool (VM version) soon and participate in the lecture.
http://spedas.org/wiki/index.php?title=Downloads_and_Installation(Search by “spedas install”.)
Download from here.

9How to run SPEDAS-GUI (VM version)[1] Double click ’spedas’ in theunzipped directory:‘spedas_v_x/spd_gui/’Double click this.

Ckick ‘spd_gui’button.

[2] Then, IDL Virtual Machine window
opens. Click ‘spd_gui’ button.

IDL license is not required.
10Help 1：SPEDAS HTML documentation (1)http://themis.ssl.berkeley.edu/software_docs.shtml

You can find the HTML
documentations at
SPEDAS website
HTML documentation11

Help 1： SPEDAS HTML documentation (2)http://themis.ssl.berkeley.edu/socware/spedas_x_xx/idl/_spd_doc.html

12Help 2： Example crib sheet (1)In the directory “spedas_x_xx/idl/projects”:

There are many example scripts named “cribsheet” in these directories.
13

Help 2： Example crib sheet (2)iug_crib_ask_nipr.pro
You can copy and pastethese commands to IDL
command line.
Or,
Run these scripts asfollows:
IDL> .r iug_crib_ask_nipr

14Help 3： Use IUGONET Type-A
http://search.iugonet.org

We explain how to use the IUGONET Type-A later.
Hands-on workshop at Polar Research Institute of China on Jan. 31, 201915

What event do we analyze today?
We analyze the effect of X-class flares on the solar surface on 5th and 7th
March 2012 and associated coronal mass ejection (CME) on the interplanetary space and the Earth’s upper atmosphere.
GOES X-ray Flux

X-class flare

From Space Weather News
Hands-on workshop at Polar Research Institute of China on http://swnews.jp/
Jan. 31, 201916

Let’s use IUGONET web service(IUGONET Type-A)

17

Search data
1. Access IUGONET Type-A (http://search.iugonet.org/)

2. Set “Timespan” to
2012/03/05 To 2012/03/11

3. Click “Search” button

Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Search results (List display)

Search results are listed in text.

Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Change search result display to QL-plot

1. Click Plot

Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Search results (QL-plot display)
QL-plots of found data are displayed.

For time-series data, you can choose
the time interval from 1, 3, and 7 days.
The default value is 7 days.
For this example, data during theinterval from 2012/03/05 to 2012/03/11
is plotted.

For image data, the QLimage on the last dayof the timespan isdisplayed.

1. ScrollHands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Find information of data (Metadata)
Geomagnetic Indices

1. Click ASY and SYM indices

Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Change date and time interval of QL-plot
Set date. (This date is thelast day of the timepsan)

QL-plot

To previous day

Time interval

To next day

SYM-H index is an indicator ofgeomagnetic storm, which is
associated with the ring
current in the magnetosphere.
ScrollHands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Detailed information of data (Metadata)

Description

Acknowledgement(Rules of the road)Contact
PersonAccessInformation

ScrollHands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Find how to analyze data using SPEDAS“How to Plot” shows
SPEDAS commands to plot data and how to plot data by using GUI tool.
CUI #Basic：
Minimally neededcommands to plot data
CUI #Advanced：
Commands used tomake QL-plot of dataGUI：
How to plot data by GUI tool.

Hands-on workshop
at Polar
Research Institute
China on Jan. 31, 2019
Returnto Search
Resultof Page.

2

Plot multiple data using UDAS web (1)Scroll

1. Select data and mark the check-boxes(maximum number of data is 3)
Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Plot multiple data using UDAS web (2)1. Click “Create” button
Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Plot multiple data using UDAS web (3)1. Mark checkboxes of the data
which you want to plot.
SYM-H index is similar to themagnetic data at Kagosima,
because SYM-H is created frommagnetic field at low-latitude
stations.

2. Click “Plot” button.

Hands-on workshop at Polar Research Institute of China on Jan. 31, 20192

Analyze data using SPEDAS

29

Use “How to Plot” in IUGONET Type-A
CUI #Basic：
Minimally neededcommands to plot data
CUI #Advanced：
Commands used tomake QL-plot of dataGUI：
How to plot data by GUI tool.

1. Copy these SPEDAS commands by mouse.
30Basic commands of SPEDAS
1. IDL> thm_init(Initialize)

2. THEMIS> timespan, 'YYYY-MM-DD/hh:mm:ss', N, /<option>(Set timespan)e.g.,timespan, 'YYYY-MM-DD', N (N days from YYYY-MM-DD)
timespan, 'YYYY-MM-DD/hh:mm:ss', N, /hour(N hours from YYYY-MM-DD/hh:mm:ss)

3. THEMIS> ???_load_???, site='site_name' (Load data)“???_load_???” is the load procedure.
e.g., “iug_load_eiscat” loads EISCAT radar data.
4. THEMIS> tplot, 'tplot_variable'(Plot loaded data.)
tplot, ['tplot_variable1', 'tplot_variable2', 'tplot_variable3', ….]
tplot, [1, 2, 3, …]

31

Copy&Paste SPEDAS commands to IDL
0. Run IDL.
1. IDL>  Paste the copied SPEDAS commands here and executethe commands.
IDL> thm_init
THEMIS> timespan, ['2012-03-05 00:00:00', '2012-03-12 00:00:00']
THEMIS> iug_load_gmag_wdc, site='sym asy‘
(Load SYM and ASM indices)
THEMIS> split_vec, 'wdc_mag_sym'
THEMIS> split_vec, 'wdc_mag_asy'(Divide SYM and ASY indices into each component (H and D).)
THEMIS> tplot, ['wdc_mag_sym_0', 'wdc_mag_sym_1', 'wdc_mag_asy_0', 'wdc_mag_asy_1']

You can create the sameplot as QL-plot of Type-A.

32

Show loaded tplot variables
Show loaded tplot variables.
tplot_names (, 'tplot_variables', /verbose)
1. THEMIS> tplot_names
1 wdc_mag_sym
2 wdc_mag_asy
3 wdc_mag_sym_0
4 wdc_mag_sym_1
5 wdc_mag_asy_0
6 wdc_mag_asy_1

2. THEMIS> tplot, [3, 4, 5, 6](Numbers for tplot variables
are also available for plotting
data.)

You can create the sameplot as QL-plot of Type-A.
33

Show details of tplot variables
Show details of tplot variables.
tplot_names, 'tplot_variable', /verbose
1. THEMIS> tplot_names, 'wdc_mag_sym', /verbose“Tplot variable” is different from normal IDL variable and includes
metadata as well as numerical data.
 allows to create good-looking plots easily with a few commands.

34

Add AE index to stack plot (1)Geomagnetic Indices

1. Click AE index at IUGONET
Type-A to find how to load it.
35Add AE index to stack plot (2)1. THEMIS> iug_load_gmag_wdc, site=‘ae’(Load AE index from Kyoto WDC.)**************************************************The rules for the data use and exchange are defined by the Guide on the World
Data Center System (ICSU Panel on World Data Centers, 1996). Note that
information on the appropriate institution(s) is also supplied with the WDC
data sets. If the data are used in publications and presentations, the data
suppliers and the WDC for Geomagnetism, Kyoto must properly be acknowledged.
Commercial use and re-distribution of WDC data are, in general, not allowed.
Please ask for the information of each observatory to the WDC.The distributionof the data has been partly supported by the IUGONET (Inter-university Upper
atmosphere Global Observation NETwork) project (http://www.iugonet.org/) fundedby the Ministry of Education, Culture, Sports, Science and Technology (MEXT),
Japan.
**************************************************The data use policy is displayedon the CUI window. Please confirm
the data use policy.

2. THEMIS> tplot_names(Confirm the loaded data)“wdc_mag_ae_prov_1min” is additionally displayed.

3. THEMIS> tplot, ['wdc_mag_sym_1', 'wdc_mag_ae_prov_1min']SYM-H index:(Indicator ofgeomagnetic storm)
AU, AL, AE, AO index：(Indicator of auroral
activity.)36

Add AE index to stack plot (3)Divide tplot variables into each component.
split_vec, 'tplot_variable'
Create a vector from some time-series data.
join_vec, ['tplot_variable1', 'tplot_variable2', ….], 'tplot_variable'
1. THEMIS> split_vec, 'wdc_mag_ae_prov_1min'
2. THEMIS> tplot, ['wdc_mag_sym_1', 'wdc_mag_ae_prov_1min_0']

Plot Dst and AE indices only.
AU and AL shows eastward andwestward auroral current,
respectively. AE is a value of
AU-AL (i.e., total auroral activity)and AO is the average of AU
and AL.
37

Add other magnetic data to stack plot (1)Geomagnetic field data

1. Next, click Kagoshima station of
210 MM network.
38

Add other magnetic data to stack plot (2)1. THEMIS> iug_load_gmag_mm210, site='kag'(Load magnetometer data at KAG from 210 MM network.)
2. THEMIS> tplot_names(Check loaded tplot variables.)
mm210_mag_kag_1sec_hdz
mm210_mag_kag_1min_hdz
mm210_mag_kag_1h_hdz

 (Added magnetometer data at KAG.)

3. THEMIS> tplot, ['wdc_mag_sym_1', 'wdc_mag_ae_prov_1min_0', $'mm210_mag_kag_1sec_hdz']• SYM-H index:
An indicator ofmagnetic storm• AE index:
An indicator ofauroral activity• Magnetic field at KAG
Ch1: North-south
Ch2: East-west
Ch3: Vertical39

Add other magnetic data to stack plot (3)Change limits of time interval.
tlimit, 'YYYY1-MM1-DD1/hh1:mm1:ss1', 'YYYY2-MM2-DD2/hh2:mm2:ss2'
tlimit + clicks by mouse (Set max and min limits by clicking.)
tlimit, /last (Return previous limits)tlimit, /full (Change to full limits)
1. THEMIS> tlimit, '2012-03-07', '2012-03-08'(Change the time range.)40Add other magnetic data to stack plot (4)Change limits of y axis.
ylim, 'tplot_variables', min, max (, LOG=log)
ylim, 'tplot_variables', min, max, 1ylim, 'tplot_variables', min, max, 0(Set y-axis to log scale.)(Set y-axis to linear scale.)

1. THEMIS> ylim, 'wdc_mag_sym_1', -100, 100 (Set y-axis range.)
2. THEMIS> tplot

41

Add other magnetic data to stack plot (5)Set options for visualization of data.
tplot_options, 'tplot_variable', ‘value'e.g., tplot_options, 'region', [x0, y0, x1, y1] (Set the region of axis position)
tplot_options, 'title', 'strings' (Set the title of plot.)
tplot_options, 'var_label', 'tplot_variable' (Add the label to the bottom.)
1. THEMIS> tplot_options, 'region', [0.05, 0, 1, 1] (Set the region of axis position.)
2. THEMIS> tplot

The Y-axis title wasdisplayed correctly.

42Add other magnetic data to stack plot (6)Set options for visualization of data.
options, 'tplot_variable', ‘option_name', 'value'e.g., options, 'tplot_variable', 'labels', 'label_strings' (Set labels for lines)
options, 'tplot_variable', 'ytitle', 'ytitle_strings' (Set y-axis title.)
options, 'tplot_variable', 'colors', value (Set colors of lines. The values
are 0: black, 1: magenta, 2: blue, 3: cyan, 4: green, 5: yellow, 6: red.)
1. THEMIS> options, 'mm210_mag_kag_1sec_hdz', 'labels', ['H', 'D', 'Z']
(Change the labels of 'mm210_mag_kag_1sec_hdz'.)
2. THEMIS> tplot

43

Data analysis of tplot_variable (FFT) (1)“How to Plot” display of magnetometer data at KAG

CUI #Advanced:
You can find how to analyze
data here.

44

Data analysis of tplot_variable (FFT) (2)Apply the FFT method to the magnetometer data at KAG
tdpwrspc, 'tplot_variable', nboxpoints=nfft, nshiftpoints=nshift(nboxpoints: number of FFT points. nshiftpoints: number of shift points.)
1. THEMIS> tdpwrspc, 'mm210_mag_kag_1sec_hdz', nboxpoints=512,
nshiftpoints=256 (Apply FFT to the magnetometer data at KAG)
2. THEMIS> tplot_names
3. THEMIS> tplot, ['wdc_mag_sym_1', 'wdc_mag_ae_prov_1min_0','mm210_mag_kag_1sec_hdz_x', 'mm210_mag_kag_1sec_hdz_x_dpwrspc']

45

Convenient function for tplot_variables (1)Calculate the sum of two tplot variables.
add_data, 'tplot_variable1', 'tplot_variable2'
Calculate the difference of two tplot variables.
dif_data, 'tplot_variable1', 'tplot_variable2'
Calculate the product of two tplot variables.
mult_data, 'tplot_variable1', 'tplot_variable2'
Calculate the division of two tplot variables (“tplot_variable1”/”tplot_variable2”)
div_data, 'tplot_variable1', 'tplot_variable2'
Calculate the average of a tplot variable over time of res(s).
avg_data, 'tplot_variable', res
Calculate the derivation of a tplot variable.
deriv_data, 'tplot_variable'46

Convenient function for tplot_variables (2)• Interpolate “tplot_variable1” using time of “tplot_variable2”.
tinterpol, ‘tplot_variable1’, ‘tplot_variable2’• Smooth “tplot_variable” by running average with a time window of dt(s).
tsmooth_in_time, 'tplot_variable', dt• Apply the high-pass filter of dt(s) to “tplot_variable”.
thigh_pass_filter, 'tplot_variable', dt• Subtract average value from “tplot_variable”.
tsub_average, 'tplot_variable' (, /median)• Calculate dynamic spectrum of “tplot_variable”
tdpwrspc, 'tplot_variable', nboxpoints=nbx, nshiftpoints=nsp
47

Convenient function for tplot_variables (3)Replace values of “tplot_variable” outside of limits with NaN.
tclip, 'tplot_variable', amin, amax
Interpolate data for NaN and Inf in “tplot_variable”.
tdeflag, 'tplot_variable' , 'linear'
Replace data gap (margin+dt ~ maxgap*dt) in “tplot_variable” with NaN.
tdegap, 'tplot_variable', maxgap=maxgap, margin=margin
Remove spike noise from “tplot_variable”.
clean_spikes, 'tplot_variable'
Calculate dynamic spectrum of “tplot_variable” by wavelet transform.
wav_data, 'tplot_variable'48

Convert between “tplot variables” and IDL variables (1)Retrieve data or limit structure from “tplot_variable”.
get_data, 'tplot_variable', data=d, dlimits=dlim, lim=lim
data structuredefault limits structure

limits structure

1. THEMIS> get_data, 'mm210_mag_kag_1sec_hdz', data=d, dlimits=dl, lim=lim
2. THEMIS> help, d, /struct (Check data structure.)** Structure <17ac3700>, 2 tags, length=12096000, data length=12096000, refs=1:
X
DOUBLE Array[604800](Time : 1 dimension)Y
FLOAT Array[604800, 3](Magnetic field vector : 2 dimension)

3. THEMIS> help, dl, /struct(Check default limits structure.)** Structure <1ab92dd0>, 4 tags, length=1256, data length=1250, refs=2:
CDF
STRUCT -> <Anonymous> Array[1]
SPEC
BYTE
0
LOG
BYTE
0
YSUBTITLESTRING '[nT]'

4. THEMIS> help, lim, /struct(Check limits structure.)** Structure <e3fa9f0>, 3 tags, length=64, data length=56, refs=2:
COLORS
INT
Array[3]LABELSSTRING Array[3]LABFLAG
INT
1
49

Convert between “tplot variables” and IDL variables (2)Create “tplot variable” from data structure and limits structures.
store_data, ‘tplot_variable’, data={x:time, y:val}, dlimits=dlim, lim=lim
time: unix time (number of seconds since 1970-01-01UT)
val: data array
1. THEMIS> time = d.x(Substitute time to IDL variable, “time”.)

2. THEMIS> val = sqrt( d.y[*, 0]^2 + d.y[*, 1]^2 + d.y[*, 2]^2 )(Calculate the absolute value of the magnetic field,
sqrt(Bx^2 + By^2 +Bz^2) and substitute it to “val”)
3. THEMIS> store_data, 'kag_abs', data = { x:time, y:val }4. THEMIS> tplot_names
5. THEMIS> tplot, ['mm210_mag_kag_1sec_hdz', 'kag_abs']

50

Convert between “tplot variables” and IDL variables (3)51Calculation of “tplot variables” by calc (1)Calculate using “tplot_variables“ by “calc”.
calc, 'equation'• Whole of the equation is enclosed by single quotations ( ' ).
• “tplot_variables” are enclosed by double quotations ( ” ).
• Many functions, such as sin(), cos(), tan(), exp(), log(), abs(), min(), max(), total(),mean(), median() are available.
1. THEMIS> calc, ' "kag_abs_calc" = $sqrt( "mm210_mag_kag_1sec_hdz_x"^2 + $"mm210_mag_kag_1sec_hdz_y"^2 + $"mm210_mag_kag_1sec_hdz_z"^2) '2. THEMIS> tplot, ['mm210_mag_kag_1sec_hdz ', 'kag_abs', 'kag_abs_calc']

52

Calculation of “tplot variables” by calc (2)53Create an image file
Create an image file from the currently displayed image.
makepng, 'filename' (Create PNG file)
makejpg, 'filename' (Create JPEG file)makegif, 'filename' (Create GIF file)popen, 'filename'(Open postscript file.)
pclose (Close postscript file opened with popen.)
1. THEMIS> makepng, 'Figure_test' (Create PNG file, “Figure_test.png”)
2. THEMIS> makejpg, 'Figure_test' (Create JPEG file, “Figure_test.jpeg”)
3. THEMIS> makegif, 'Figure_test' (Create GIF file, “Figure_test.gif”)
4. THEMIS> popen, 'Figure_test'(Change plot device to postscript and open a file, “Figure_test.ps”.)
5. THEMIS> tplot(Plot data)
6. THEMIS> pclose (Close the postscript file and change device back to default.)

54

Create an ascii file
Create an ascii file for selected “tplot variable”.
tplot_ascii, 'tplot_variable' (, fname=‘filename‘)
Save “tplot variable” in a binary file.
tplot_save, 'tplot_variables', filename='filename'Restore “tplot variable” saved with “tplot_save”.
tplot_restore, filename='filename'
1. THEMIS> tplot_ascii, 'mm210_mag_kag_1h_hdz'(Save an ascii file named “mm210_mag_kag_1h_hdz.txt” in a current directry.)
Data in the “mm210_mag_kag_1h_hdz.txt”:
2012-03-05/00:00:00.000
2012-03-05/01:00:00.000…..

-2.2200001e+001-2.8200001e+001

3.5100002e+001
2.8100000e+001-1.2900001e+001-2.5600000e+001

2. THEMIS> tplot_save, 'mm210_mag_kag_1h_hdz'(Save a binary file named “saved.tplot” in a current directry.)
3. THEMIS> store_data, 'mm210_mag_kag_1h_hdz', /delete(Delete 'mm210_mag_kag_1h_hdz' from memory.)
4. THEMIS> tplot_names (Confirm that 'mm210_mag_kag_1h_hdz‘ was deleted.)
5. THEMIS> tplot_restore,filename='saved.tplot' (Restore the saved tplot variable.)55

Examples of Application

56

Plot solar wind parameters and geomagnetic indices (1)Tsurutani et al. (2014), J. Space Weather
Space Clim., 4, A02, DOI:
10.1051/swsc/2013056.
Characteristics of solar wind andgeomagnetic activity on 3 March 2012:

5. THEMIS> tplot,['OMNI_HRO_5min_flow_speed','OMNI_HRO_5min_proton_density','OMNI_HRO_5min_Bxyz_GSE','wdc_mag_sym_1','wdc_mag_ae_prov_1min_0']

 Geomagnetic storm (max. Dst = -148nT) is caused by negative IMF-Bz
associated with the magnetic cloud(MC).
 Extremely high temperature region (T~20*10^5K) passed through the
upstream and downstream ofinterplanetary shock the period from11:30UT on 8 March to 01:50UT on 9
March (Coronal loop or coronalsheath?).
 SI+ observed at 11:30UT on 8 Marchis very strong (~60nT).
57

Plot solar wind parameters and geomagnetic indices (2)1. THEMIS> timespan, '2012-03-08', 3 (Set timespan to 3 days from 2012-03-08.)
2. THEMIS> omni_load_data, /res5min (Load OMNI data.)
3. THEMIS> tplot_names(Check the loaded data.)
4. THEMIS> tplot,['OMNI_HRO_5min_flow_speed','OMNI_HRO_5min_proton_density','OMNI_HRO_5min_T','OMNI_HRO_5min_F','OMNI_HRO_5min_BX_GSE','OMNI_HRO_5min_BY_GSE','OMNI_HRO_5min_BZ_GSE','wdc_mag_ae_prov_1min_0','wdc_mag_sym_1']
5. THEMIS> ylim, 'wdc_mag_sym_1',-150, 50
6. THEMIS> tplot
58

Plot solar wind parameters and geomagnetic indices (3)1. THEMIS> options, 'OMNI_HRO_5min_BX_GSE', labels='Bx', colors=2
2. THEMIS> options, 'OMNI_HRO_5min_BY_GSE', labels='By', colors=4
3. THEMIS> options, 'OMNI_HRO_5min_BZ_GSE', labels='Bz', colors=6(Set colors and labels for IMF-Bx, By, Bz (2:blue, 4:green, 6:red).)4. THEMIS> store_data, 'OMNI_HRO_5min_Bxyz_GSE',
data=['OMNI_HRO_5min_BX_GSE', 'OMNI_HRO_5min_BY_GSE','OMNI_HRO_5min_BZ_GSE'](Store the IMF-Bx, By, Bz vector into
“OMNI_HRO_5min_Bxyz_GSE”)
5. THEMIS> tplot,['OMNI_HRO_5min_flow_speed','OMNI_HRO_5min_proton_density','OMNI_HRO_5min_T','OMNI_HRO_5min_F','OMNI_HRO_5min_Bxyz_GSE','wdc_mag_ae_prov_1min_0','wdc_mag_sym_1']

59

Compare GOES X-ray flux with geomagnetic field (1)1. THEMIS> timespan, ['2012-03-05 00:00:00', '2012-03-12 00:00:00'](Set timespan.)
2. THEMIS> goes_load_data, probes='15', datatype='xrs', /avg_1m(Load 1min-averaged X-ray flux data from the GOES-15.)
3. THEMIS> tplot, ['g15_xrs_avg', 'mm210_mag_kag_1sec_hdz'](Plot the GOES X-ray flux and magnetometer data at KAG.)

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Compare GOES X-ray flux with geomagnetic field (2)1. THEMIS> tlimit, '2012-03-06/20', '2012-03-07/04'(Change the time range to find a good correlation between X-ray flux
and geomagnetic field.)

Solar Flare Event (SFE)The east-west componentof the magnetic fieldshows large variation
when the X-class flareoccurred.
It is interpreted that theionospheric conductivity
was enhanced by theincrease in the X-ray flux.

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Plot SuperDARN radar data (1)You can find how to load and plot datafrom SuperDARN Hokkaido East radarby using IUGONET Type-A62

Plot SuperDARN radar data (2)1. THEMIS> timespan, '2012-03-09' (Set timespan.)
2. THEMIS> iug_load_sdfit, site='hok'(Load SuperDARN radar data at HOK.)
3. THEMIS> tplot_names (Check loaded data.)
4. THEMIS> tplot, ['sd_hok_pwr_1', 'sd_hok_vlos_bothscat_1','sd_hok_spec_width_1'](Plot the echo power, line-of-sight(LOS) Doppler velocity, spectral width.)63

Plot SuperDARN radar data (3)1. THEMIS> splitbeam, 'sd_hok_vlos_bothscat_1'(Split LOS plasma velocity into each beam.)
2. THEMIS> loadct_sd, 44(Change color table for the LOS Doppler velocity of SD radar.)
3. THEMIS> tplot, ['sd_hok_vlos_bothscat_1_azim04','sd_hok_vlos_bothscat_1_azim07', 'sd_hok_vlos_bothscat_1_azim10']
4. THEMIS> tlimit, '2012-03-09/06', '2012-03-09/12'
5. THEMIS> zlim, 'sd_hok_vlos_bothscat_1_*', -1500, 1500
6. THEMIS> tplot

Strong westward flow(>1000m/s) associated withSAPS (Sub-Auroral
Polarization Stream) can befound just after the minimum
peak of Dst.

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Plot SuperDARN radar data (4)1. THEMIS> window, 1, xsize=600, ysize=600 & erase
2. THEMIS> sd_init (Initialize for SD tool.)
3. THEMIS> sd_time, 1000 (Set time for 2D plot to 10:00UT.)
4. THEMIS> sd_map_set, /erase, /clip, /mltlabel, center_glat=60, center_glon=160(Set map for 2D plot.)
5. THEMIS> overlay_map_sdfit, 'sd_hok_vlos_1'(Plot the LOS velocity on the map.)

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Set color table
Set color table.
loadct2, value
options, ‘tplot_variable', ‘color_table’, value(Set color table separately for each “tplot_variable”)
1. THEMIS> loadct2, 0 (Black-White)
2. THEMIS> loadct2, 43 (First-Special. Default for SPEDAS.)
3. THEMIS> options, 'sd_hok_pwr_1', 'color_table', 0 (Black-White)
4. THEMIS> options, 'sd_hok_vlos_bothscat_1', 'color_table', 43 (Fast-Special)
5. THEMIS> options, 'sd_hok_spec_width_1', 'color_table', 43 (Fast-Special)
6. THEMIS> tplot, ['sd_hok_pwr_1', 'sd_hok_vlos_bothscat_1','sd_hok_spec_width_1']

66Plot EISCAT radar data (1)You can find how to load and plot
data from EISCAT (ESR-42m) radarby using IUGONET Type-A.

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Plot EISCAT radar data (2)1. THEMIS> timespan, '2012-03-09' (Set timespan.)
2. THEMIS> iug_load_eiscat, site='esr_42m'(Load ESR 42m-antenna data.)
3. THEMIS> tplot, ['eiscat_esr42m_ne', 'eiscat_esr42m_te','eiscat_esr42m_ti', 'eiscat_esr42m_vi'](Plot basic ionospheric parameters, i.e., electron density, electron temperature, ion
temperature and ion velocity.)68Plot EISCAT radar data (3)1. THEMIS> thm_load_gmag, site='lyr tro', /subtract_average(Load the magnetic field at Longyearbyen and Tromso. )2. THEMIS> tplot, ['eiscat_esr42m_ne', 'eiscat_esr42m_te','eiscat_esr42m_ti', 'eiscat_esr42m_vi','thg_mag_lyr', 'thg_mag_tro'](Plot both EISCAT radar and magnetometer data.)
3. THEMIS> tlimit, '2012-03-09/2', '2012-03-09/8'

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Plot meteor radar data (1)You can find how to loadand plot data from meteor
radar at Biak by using
IUGONET Type-A.

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Plot meteor radar data (2)1. THEMIS> timespan, ['2012-03-05/00:00:00', '2012-03-12/00:00:00']
2. THEMIS> iug_load_meteor_rish, site='bik', parameter=['h2t60min00','h2t60min30', 'h4t60min00', 'h4t60min30'], length='1_day'(Load meteor radar data at Biak. )3. THEMIS> tplot, ['iug_meteor_bik_uwnd_h2t60min00','iug_meteor_bik_uwndsig_h2t60min00', 'iug_meteor_bik_vwnd_h2t60min00','iug_meteor_bik_vwndsig_h2t60min00', 'iug_meteor_bik_mwnum_h2t60min00'](Plot zonal wind (uwnd), meridional wind (vwnd), and their variance and number of
meteor. )71

Plot meteor radar data (3)1. THEMIS> iug_load_gmag_wdc, site='sym'(Load SYM index. )2. THEMIS> split_vec, 'wdc_mag_sym'(Split SYM index into each component. )3. THEMIS> tplot, ['wdc_mag_sym_1', 'iug_meteor_bik_uwnd_h2t60min00','iug_meteor_bik_uwndsig_h2t60min00', 'iug_meteor_bik_vwnd_h2t60min00','iug_meteor_bik_vwndsig_h2t60min00', 'iug_meteor_bik_mwnum_h2t60min00'](Plot both SYM index and meteor radar data)
Does themeridional windchange during thegeomagnetic
storm?

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Note• Even if you can not find some kinds of data at the IUGONET
Type-A, it may be possible for you to analyze the data with
SPEDAS. Please notice that all IUGONET data have not beenregistered to IUGONET Type-A.
• QL plots of recent data have not been created yet at IUGONET
Type-A, however, it may be possible for you to plot the datawith SPEDAS.

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