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Developments in the helioseismic imaging of the deep solar interior and sunspot structure Shravan M. Hanasoge Stanford University Max-Planck-Institut For Solar System Research
Developments in the helioseismicimaging of the deep solar interiorand sunspot structure
Shravan M. HanasogeStanford University
Max-Planck-Institut For Solar System Research
Talk outline Introduction
Modeling supergranulation
Modeling meridional flow
On the complex beast that is the travel time
Conclusions
Eruption above a sunspot
From the Hinode press release (2007), observations in the G-band and Ca II H
Solar prominences (Hinode)
Granules: sources of waves
From the Hinode press release, G-band observations
Acoustic wave propagation in the interior
Figure from SOI/MDI website, created by Sasha Kosovichev
Motivation
To develop interaction and propagationtheories of waves
(Re-)evaluate, (re-)interpret observations
Hopefully discover something new
Simulating the solar wavefield
Incredible breadth of scales and wide range ofphenomena
Cannot simulate the entire Sun yet!
Pick battles: simulate wave propagation inappropriate geometry
Differential studies
Mimic observed modal distribution
SOI/MDI website
Forget non-linear magneto-convection
Model purely linear wave interactions
Stochastically excite waves in the Sun
Place time-stationary perturbations inthe simulation box
Analyze the resultant wavefield
Simulated power spectra
Spectrum looks like the solar one - two thumbs way up!
Modeling Supergranulation
Large-scale coherent convection
Have wave-like properties?
Understanding their structure and dynamics via analyses of wavefield statistics
Supergranulation
Gizon, Duvall, & Schou (2001)
Feature method: MDI data analysis
Regions of divergence Travel-time map
Duvall (2006)
Modeling supergranulation
Birch, Duvall, & Hanasoge (2007)
Frequency filtering and unexplained obs.
Differential sampling
More constraints
Highly constrained situation
Observations: very precise
Conclusion: unable to matchdata with required precision
Meridional flow
Instrumental for solar cycle
Transports magnetic flux
Redistributes angular momentum
Solar cycle predictors depend on flow profiles
Analysis and models
Differential measurement of travel times
Many systematics such as light travel time
delays and projection effects
Previous analyses did not take into account?
Modeling medium-l observations
Distance Latitude Distance (Deg)
Systematics
Light travel-time delays (disk edge)
Line-of Sight (horizontal components etc.)
Fore shortening
MTF
Radiative heat transfer
Unknown!
The complex beast that is the travel time
Travel time is not raypath travel time
Signal contributions from disparate location
Non-homogeneity of sources leads tocomplex effects
Sunspots: Observational understanding
Sunspot (computational) model
Wave statistics: results
3 mHz 4 mHz 5mHz
Filtering related issues
Fast mode propagation: problems III
WKB approximation (Elena Khomenko)
Wave propagation physics is different
Leads to Large changes in travel times
Must interpret correctly!
Non-sequitur: convection as seen by waves
ASH simulations
Miesch et al. (2000)
No waves in the ASHsimulations.
Difference travel-timemap
Waves are scattered bythe convective cells.
Unpublished, private communication (Duvall, 2007)
Conclusions
Details that have been neglected in the pastare gaining importance
Must develop accurate wave interactiontheories
Systematics are serious and must beconsidered
Fin
