1. B.V. Jackson, H.-S. Yu, P.P. Hick, and A. Buffington,
Center for Astrophysics and Space Sciences,
University of California at San Diego, LaJolla, CA, USA
Where necessary I will add comments
Masayoshi

2. 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

3. 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)

4. Ecliptic Plane Projection
“Image” of the Sky
Ecliptic Plane Projection

5. 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

6. 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

7. 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.

8. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
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.

9. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Time-Dependent Model: Real-time forecast of the solar wind at Earth Shown are time series of solar wind parameters near Earth derived from the time-dependent tomography model (solid curve) in comparison with Advanced Composition Explorer (ACE) spacecraft velocity and SOHO (CELIAS) density data (dashed curves). The 'root-mean-square' residual difference between the two time series is indicated. Velocity is to the left; density derived from interplanetary scintillation (IPS) g-level is to the right. The display is updated hourly, most recently at 2015/07/09 02 UT as indicated by the vertical dashed line. ACE and CELIAS data are usually available up to this time; the time-dependent model forecasts several days past this time into the future. The model is updated every time new data are received from STELab,_Japan, most recently at 2015/07/08 18 UT. The animations run in 6.0-hour steps from 6.0 days before, to 1.0 days after the last time data were received.
Web analysis runs automatically using Linux on a P.C.

10. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Go to In-situ 5-Day Aftcast
Go to In-situ 5-Day Aftcast
Time-Dependent Model: 1-day forecasts and 5-day aftcasts of the solar wind at Earth
Shown are 1-day forecasts and 5-day aftcasts of the solar wind density and velocity in comparison with actual solar wind conditions observed by ACE. For each of the most recent 30 tomographic reconstructions one point is extracted from the time series at Earth. For the 1-day forecast a point 1-day later than the forecast time is extracted, i.e., one day to the right of the vertical dashed line in the timeseries. For the 5-day aftcast a point 5 days earlier than the forecast time is extracted, i.e. 5 days to the left of the dashed line in the timeseries. The forecast data are compared with actual ACE observations 1 day later (5 days earlier for aftcasts). Velocity is to the left, density derived from interplanetary scintillation (IPS) g-level is to the right. The display is updated every time new data are received from STELab, Japan, most recently at 2015/07/08 18 UT.
Web analysis runs automatically using Linux on a P.C.

11. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Go to In-situ 1-Day Forecast
Go to In-situ 1-Day Forecast
Time-Dependent Model: 1-day forecasts and 5-day aftcasts of the solar wind at Earth
Shown are 1-day forecasts and 5-day aftcasts of the solar wind density and velocity in comparison with actual solar wind conditions observed by ACE. For each of the most recent 30 tomographic reconstructions one point is extracted from the time series at Earth. For the 1-day forecast a point 1-day later than the forecast time is extracted, i.e., one day to the right of the vertical dashed line in the timeseries. For the 5-day aftcast a point 5 days earlier than the forecast time is extracted, i.e. 5 days to the left of the dashed line in the timeseries. The forecast data are compared with actual ACE observations 1 day later (5 days earlier for aftcasts). Velocity is to the left, density derived from interplanetary scintillation (IPS) g-level is to the right. The display is updated every time new data are received from STELab, Japan, most recently at 2015/07/08 18 UT.
Web analysis runs automatically using Linux on a P.C.

12. Magnetic Field Extrapolation
(Zhao, X. P. and Hoeksema, J. T., 1995, J. Geophys. Res., 100 (A1), 19.)
Magnetic Field Extrapolation
Dunn et al., 2005, Solar Physics 227: 339–353.
In a technique worked out by Zhao, X. P. and Hoeksema, J. T., 1995, J. Geophys. Res., 100 (A1), 19, we are able to project outward magnetic field from the solar surface. This works globally using archival data or in forecast. The potential field model provides a measurement of radial field at the source surface. This is projected outward using the UCSD solar wind model to provide a radial and tangential field anywhere within the 3D volume.
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.
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,

13. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Time-Dependent Model: Real-time forecast of the solar wind at Earth Shown are time series of solar wind parameters near Earth derived from the time-dependent tomography model (solid curve) in comparison with The 'root-mean-square' residual difference between the two time series is indicated. Advanced Composition Explorer (ACE) spacecraft data (dashed curve). Radial magnetic field is to the left; tangential magnetic field is to the right. The display is updated hourly, most recently at 2015/07/09 03 UT as indicated by the vertical dashed line. ACE data are usually available up to this time; the time-dependent model forecasts several days past this time into the future. The model is updated every time new data are received from STELab, Japan, most recently at 2015/07/08 18 UT. The animations run in 6.0-hour steps from 6.0 days before, to 1.0 days after the last time data were received.
Web analysis runs automatically using Linux on a P.C.

14. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Go to In-situ 5-Day Aftcast
Go to In-situ 5-Day Aftcast
Time-Dependent Model: 1-day forecasts and 5-day aftcasts of the solar wind at Earth
Shown are 1-day forecasts and 5-day aftcasts of the solar wind density and velocity in comparison with actual solar wind conditions observed by ACE. For each of the most recent 30 tomographic reconstructions one point is extracted from the time series at Earth. For the 1-day forecast a point 1-day later than the forecast time is extracted, i.e., one day to the right of the vertical dashed line in the timeseries. For the 5-day aftcast a point 5 days earlier than the forecast time is extracted, i.e. 5 days to the left of the dashed line in the timeseries. The forecast data are compared with actual ACE observations 1 day later (5 days earlier for aftcasts). Velocity is to the left, density derived from interplanetary scintillation (IPS) g-level is to the right. The display is updated every time new data are received from STELab, Japan, most recently at 2015/07/08 18 UT. .
Web analysis runs automatically using Linux on a P.C.

15. UCSD IPS prediction analysis validation
Skysweep view
Jackson, B.V., et al., 2011, Adv. in Geosciences, 30,
UCSD IPS prediction analysis validation
A Hammer-Aitoff display showing the STELab source locations. The source value is indicated relative to the model background value.
Go to In-situ 1-Day Forecast
Go to In-situ 1-Day Forecast
Time-Dependent Model: 1-day forecasts and 5-day aftcasts of the solar wind at Earth
Shown are 1-day forecasts and 5-day aftcasts of the solar wind density and velocity in comparison with actual solar wind conditions observed by ACE. For each of the most recent 30 tomographic reconstructions one point is extracted from the time series at Earth. For the 1-day forecast a point 1-day later than the forecast time is extracted, i.e., one day to the right of the vertical dashed line in the timeseries. For the 5-day aftcast a point 5 days earlier than the forecast time is extracted, i.e. 5 days to the left of the dashed line in the timeseries. The forecast data are compared with actual ACE observations 1 day later (5 days earlier for aftcasts). Velocity is to the left, density derived from interplanetary scintillation (IPS) g-level is to the right. The display is updated every time new data are received from STELab, Japan, most recently at 2015/07/08 18 UT.
Web analysis runs automatically using Linux on a P.C.

16. Summary: There are many ways to validate these analyses
1. How many values are there to fit?
2. How well do the iterations converge?
3. How well does the model agree with the observations?
4. How well does the modeling agree with in-situ observations?
a. Root mean squared residual differences.
b. Person’s “R” correlations
i. Forecast values
ii. Forecast differences
iii. “Aftcast” values
M Potentially talk will proceed this way