Abstract
The University of California, San Diego (UCSD) three-dimensional (3D) time-dependent tomography program, used for over a decade to reconstruct and forecast coronal mass ejections (CMEs), does so from observations of interplanetary scintillation (IPS) taken using the Solar-Terrestrial Environment Laboratory (STELab) radio arrays in Japan. An earlier article (Jackson et al. in Solar Phys. 265, 245, 2010) demonstrated how in-situ velocity measurements from the Advanced Composition Explorer (ACE) space-borne instrumentation can be used in addition to remote-sensing data to constrain a time-dependent tomographic velocity solution. Here we extend this in-situ inclusion to density measurements, and show how this constrains the tomographic density solution. Supplementing remote-sensing observations with in-situ measurements provides additional information to construct an iterated solar-wind parameter that is propagated outward from near the solar surface past the measurement location, and throughout the volume. As in the case of velocity when this is done, the largest changes within the volume are close to the radial directions around Earth that incorporate the in-situ measurements; the inclusion significantly reduces the uncertainty in extending these measurements to global 3D reconstructions that are distant in time and space from the spacecraft. At Earth, this analysis provides a finely tuned real-time result up to the latest time for which in-situ measurements are available, and enables more-accurate extension of these results near Earth to those remotely sensed. We show examples of this new algorithm using real-time STELab IPS data that were used in our forecasts throughout Carrington rotations 2010 through 2016, and we provide one metric prescription that we have used to determine the forecasting accuracy one, two, and three days in advance of the time data become available to analyze from STELab. We show that the accuracy is considerably better than assuming persistence of the same signal over one to two days in advance of when the data are available.
Highlights
Observations of interplanetary scintillation (IPS) of meter-wavelength intensity variations from point radio sources have long been a source of heliospheric remote-sensing information
We show examples of this new algorithm using real-time Solar-Terrestrial Environment Laboratory (STELab) IPS data that were used in our forecasts throughout Carrington rotations 2010 through 2016, and we provide one metric prescription that we have used to determine the forecasting accuracy one, two, and three days in advance of the time data become available to analyze from STELab
In Jackson et al (2010a) we describe some of the background analyses that have been used at the University of California, San Diego (UCSD) to provide threedimensional (3D) depictions of heliospheric structures using IPS techniques
Summary
Observations of interplanetary scintillation (IPS) of meter-wavelength intensity variations from point radio sources have long been a source of heliospheric remote-sensing information. For use in the analysis, we note that for conversion of in-situ density near Earth to g-level only the latter term of Equation (3) that utilizes the power βn = 0.40 is employed These two parameter fits have been used throughout 2011 to match the IPS tomography to ACE data fairly well, both of these parameters, but especially βn, can vary with ongoing radio array calibration, or for that matter different in-situ instrument data reduction techniques or plasma instruments. Since there are on average approximately 600 LOS g-level observations used during the 27-day CR periods in 2011 ( approximately 20 lines of sight per day), the in-situ weighting dominates that of the remote-sensing value total by slightly over a factor of 10 This weighting for the in-situ data measurement ensures that in-situ densities are accommodated in the analysis as well as the reconstruction resolutions can provide. This somewhat arbitrary remedy may not prove appropriate for all time intervals, but it seems to suffice for the 2011 time interval presented here
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