1. Using World Interplanetary Scintillation Systems
for Space Weather Predictions
B.V. Jackson
Center for Astrophysics and Space Sciences,
University of California at San Diego, LaJolla, CA, USA
H.-S. Yu, P.P. Hick, A. Buffington,
Center for Astrophysics and Space Sciences, University of California at San Diego, LaJolla, CA, USA
M. Tokumaru
Solar-Terrestrial Environment Laboratory, Nagoya University, Nagoya , Japan
D. Odstrcil
George Mason University, Fairfax, Virginia, and NASA-Goddard Spaceflight Center, USA
S. Hong, J. Kim
Korean Space Weather Center, National Radio Research Agency, 198-6, Jeju, South Korea
Where necessary I will add comments
B. Lee, J. Yi, J Yun
SELab, 8, Nonhyeon-ro 150-gil, Gangnam-gu, Seoul, South Korea
M.M Bisi
RAL Space, Science & Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Oxford, Didcot, Oxfordshire, OX11 0QX, England (UK)
A. Gonzalez-Espararza
George Mason University, Fairfax, Virginia, and NASA-Goddard Spaceflight Center, USA
Masayoshi

2. Introduction: IPS Space Weather Predictions IPS Tomographic Analyses:
STELab, Japan; The UCSD iterative kinematic prediction technique; Used primarily with STELab observations, Other data sets can fill in; Used in space weather prediction elsewhere including at the KSWC, Jeju; the CCMC; NICT, Japan
IPS tomographic analysis displays:
UCSD, elsewhere
Magnetic field component forward-modeling – Br, Bt:
Part of the package developed at UCSD
Interesting Developments:
Bn determination via a simple technique (under development)
My talk will proceed this way

3. Interplanetary Scintillation (IPS) Analysis
The Solar Wind Imaging Facility, Toyokawa (SWIFT) array is shown in the above photograph. B. Jackson is standing on the steps that take one to the antenna dipoles. The non-moving array is steerable in declination, providing views of radio sources as the transit the meridian above Japan.

4. IPS Heliospheric Analyses (STELab)
DATA
IPS Heliospheric Analyses (STELab)
The STELab interplanetary scintillation 327 MHz remote-sensing cylindrical parabola near Mt. Fuji is shown. The array moves in declination to provide views of sources at different locations in the sky as they pass overhead. The other array of this type is at Kiso, to the north of Toyokawa.
STELab IPS array near Mt. Fuji
STELab IPS array systems

5. IPS Heliospheric Analyses (STELab)
DATA
IPS Heliospheric Analyses (STELab)
Density inhomogenieties in the solar wind on the order of 150 km size from point radio sources produce an intensity pattern variation on the ground that travels away from the Sun with the solar wind speed. This pattern, measured and correlated between different radio sites in Japan allows a determination of the solar wind speed by translating this value to the line of sight perpendicular. The fuzz observed correlates from one radio site to another.
IPS line-of-sight response
STELab IPS array systems

6. Current STELab Toyokawa IPS System
The Solar Wind Imaging Facility, Toyokawa (SWIFT) array is shown in the above photograph. B. Jackson is standing on the steps that take one to the antenna dipoles. The non-moving array is steerable in declination, providing views of radio sources as the transit the meridian above Japan.
New STELab IPS array in Toyokawa (3,432 m2 array now operates well – year-round operation began in 2011)

7. World-Wide IPS observation network
Pushchino103MHz
70,000㎡
STEL Multi-Station 327MHz
2000 ㎡×3, 3500 ㎡
MEXART
140MHz、10,000㎡
IPS
UK/EISCAT
LOFAR)
Russia
Let’s move onto the next.
For studying of transient phenomena such as CMEs, high cadence observations are needed. A world-wide network is essential to improve cadence of IPS observations. As shown here, there are some IPS stations where IPS observations have been performed. By exchanging IPS data among these stations, we can make continuous monitoring of the solar wind and CMEs. Such a network observations is useful for studying radial evolution of CMEs.
Korea
Japan
India
Mexico
MWA
80-300MHz
Ooty 327MHz、16,000㎡
US-Australia 7

8. Current Dedicated IPS Radio Systems
Other current operating IPS radio arrays are shown. The Puschino, Russia array is the largest IPS array currently in existence.
The Ootacamund (Ooty), India off-axis parabolic cylinder 530 m long and 30 m wide (15,900 m2) operating at a nominal frequency of MHz.
The Pushchino Radio Observatory 70,000 m2 110 MHz array, Russia (summer 2006)
Now named the “Big Scanning Array of the Lebedev Physical Institute” (BSA LPI).

9. Other and Potential Future Dedicated IPS Systems
KSWC (South Korea)
MEXART (Mexico)
Dedicated IPS 700 m2 327 MHz IPS radio 32 tile array, Jeju Island
Additional radio arrays that are used or can potentially be used for IPS are (from upper left clockwise), the MEXican ARray Telescope (MEXART); the Korean Space Weather Center (KSWC) radio array, Jeju; the LOw Frequency ARray (LOFAR), The Netherlands and Western Europe; and the Murchison Widefield Array (MWA), Western Australia.
Dedicated IPS IPS 9,600 m2 140 MHz IPS radio array near Michoacan, Mexico

10. View from MEXART, Mexico Ecliptic Plane Projection
“Image” of the Sky
View from MEXART, Mexico
View from STELab, Japan
Ecliptic Plane Projection

11. Recent Morelia Remote Sensing Workshop
(20-24 October 2015)
1) A standardized IPS format was settled upon.
2) All participants agreed to share their data and host
websites to present their data in real time as soon as it becomes available.
3) At this time a new member joined the group of
organizations that provide access to their IPS
data set in real time from the world’s largest (70,000 m2) radio array currently operating; the 110 Mhz system at Pushchino, Russia.

12. UCSD IPS Predictions

13. IPS line-of-sight response Sample outward motion over time
Jackson, B.V., et al., 2008, Adv. in Geosciences, 21,
Heliospheric C.A.T. analyses: example line-of-sight distribution for each sky location to form the source surface of the 3D reconstruction.
STELab IPS
This shows how the UCSD IPS time-dependent Computer Assisted Tomography (C.A.T.) analysis works. The 327 MHz IPS line of sight weighting provides a weight for each source observation on a spherical source surface below each line. As material moves outward from the Sun, it follows a very specific modeled path and expansion that is weighted differently at different times. The full mathematical treatment can be found in Jackson, B.V., et al., 2008, Adv. in Geosciences, 21,
Sample outward motion over time

14. IPS line-of-sight response
Jackson, B.V., et al., 2008, Adv. in Geosciences, 21,
Heliospheric C.A.T. analyses: example line-of-sight distribution for each sky location to form the source surface of the 3D reconstruction.
STELab IPS
This shows the line of sight traces on a Carrington map at the source surface (lower right). The line of sight weighting provides a weight for each source observation on the source surface. The full mathematical treatment can be found in Jackson, B.V., et al., 2008, Adv. in Geosciences, 21,
14 July 2000
13 July 2000

15. Time-Dependent Analysis Using Other IPS Systems
Fisheye velocity skymaps with additional radio sources
Jackson, B.V., et al., 2013, AGU 2013 Presentation , May, Cancoon, Mexico.
Analysis including MEXART source
Analysis without MEXART source
I have added the MEXART velocity (with its appropriate different weighting (for this different frequency and source size) into the UCSD tomographic analysis for one such speed measurement. In this instance there is little difference between the addition of the MEXART radio source into the tomographic analysis.

16. Current Prediction Analyses
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
Current Prediction Analyses
UCSD IPS analysis
UCSD Web pages
The UCSD forecast website.
Web Analysis Runs Automatically Using Linux on a P.C.

17. UCSD IPS prediction analysis
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Web analysis runs automatically using Linux on a P.C.

18. UCSD IPS prediction analysis
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis
Fit to ACE and CELIAS data
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Web analysis runs automatically using Linux on a P.C.

19. UCSD IPS prediction analysis
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis
Fit to ACE and CELIAS data
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Web analysis runs automatically using Linux on a P.C.

20. More Details
Magnetic Field

21. CSSS model Source surface Br field component sample
(Zhao, X. P. and Hoeksema, J. T., 1995, J. Geophys. Res., 100 (A1), 19.)
CSSS model
Dunn et al., 2005, Solar Physics 227: 339–353.
Source surface Br field component sample
Inner region: the CSSS model calculates the magnetic field using photospheric measurements and a horizontal current model.
2. Middle region: the CSSS model opens the field lines. In the outer region.
3. Outer region: the UCSD tomography convects the magnetic field along velocity flow lines.

22. Radial and Tangential Magnetic Field Magnetic Field Extrapolation
(Jackson, B.V., et al., 2011, Adv. in Geosciences, 30, )
Earth
Radial and Tangential Magnetic Field
Magnetic Field Extrapolation
Here is a UCSD forecast of magnetic field from the Website.
Web Analysis Runs Automatically Using Linux on a P.C.

23. Correlations (from UCSD forecast)
(Jackson, B.V., et al., 2011, Adv. in Geosciences, 30, )
Correlations (from UCSD forecast)
Pearson’s “r” correlation five-day behind comparison
Here is a UCSD forecast of magnetic field from the Website.
Web Analysis Runs Automatically Using Linux on a P.C.

24. Correlations (from UCSD predictions)
(Jackson, B.V., et al., 2011, Adv. in Geosciences, 30, )
Correlations (from UCSD predictions)
Pearson’s “r” correlation one-day ahead comparison
Here is a UCSD forecast of magnetic field from the Website.
Web Analysis Runs Automatically Using Linux on a P.C.

25. Radial and Tangential Magnetic Field
(Jackson, B.V., et al., 2011, Adv. in Geosciences, 30, )
Earth
Radial and Tangential Magnetic Field
Here is a UCSD forecast of magnetic field from the Website.
Web Analysis Runs Automatically Using Linux on a P.C.

26. UCSD Kinematic IPS Model
IPS Prediction (KSWC)
UCSD Kinematic IPS Model

27. IPS Prediction (KSWC) IPS-Driven ENLIL
IPS-Driven ENLIL

28. But what is really wanted is Bz

29. UCSD Archival IPS Analysis of V and D at WIND over Carrington rotation (April 27 – May 25, 2007)
velocity
density

30. I have often wondered where the Bz in-situ field comes from
I have often wondered where the Bz in-situ field comes from. The Parker spiral analysis does not indicate how a normal field (north-south) can occur, and yet the field exists and is ever-present in the heliosphere.

31. Extrapolated Bn closed field component for CR 2056
(Jackson, B.V., et al., 2015, ApJL, 803:L , doi: / /803/1/L1.)
CSSS model
Closed field
Extrapolated Bn closed field component for CR 2056
Extrapolated Bt field component for CR 2056
Extrapolated Br field component for CR 2056
About 1/50th of the static flux r-1.34 fall-off

32. Br ten-year correlation summary plot - GONG data
Extrapolated Closed field component
Work in progress

33. Bt ten-year slope summary plot - GONG data
Br ten-year slope summary plot - GONG data
Bn ten-year slope summary plot - GONG data
Closed field
Work in progress

34. I suggest that at least part of the Bn component comes from closed fields that escape from near the solar surface – perhaps through some non-static process.

35. Summary: IPS Space Weather Predictions IPS Tomography Analyses:
Making good predictions of in-situ measurements ahead of time keeps you “honest”
New Systems:
Incorporation of other systems into the analysis is possible, and possibly helps other IPS sites standardize and edit their own data sets
Interesting Developments:
Potential practical determination of three-component magnetic fields is under development, so far at fairly low resolution
M Potentaily talk will proceed this way

36. UCSD IPS prediction analysis using STELab data today
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis
using STELab data today
Fit to ACE and CELIAS data
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Web analysis runs automatically using Linux on a P.C.