The Solar MURI Effort: Recent Results, Directions for the Future

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The Solar MURI Effort Recent Results,
Directions for the Future

• George Fisher
• SSL, UC Berkeley

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Overall vision of our MURI effort

• Develop a time dependent, physics-based forward
  model of the Sun and heliosphere that takes as
  input time sequences of real vector magnetic
  field observations from the solar atmosphere.
• Required components
• Understanding CME eruption mechanisms
• State-of-the-art solar magnetic data and analysis
  techniques
• A formalism that can incorporate magnetic data
  into MHD models
• MHD techniques that can cope with greatly varying
  temporal and spatial scales

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The Solar MURI project involves team members from
9 Universities

• UC Berkeley
• University of Colorado
• Stanford University
• Drexel University
• University of New Hampshire
• Montana State University
• UC San Diego
• Big Bear Solar Observatory (NJIT)
• University of Hawaii

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Our MURI effort supported the development of new
instrumentation for measuring magnetic fields in
CME-producing regions of the Sun
An FeXIII IR Zeeman coronal magnetogram from the
UH Solar-C telescope on Haleakala, of NOAA 10581
superimposed on an EIT FeXV image. Magnetic field
contours (thick to thin) correspond to 4, 2, 0,
and -2 Gauss fields. Tick-marks show the
spatial scale in arc-seconds.
The Infrared Imaging Magnetograph (IRIM)
developed by the Big Bear Solar Observatory
(BBSO) has been put into preliminary operation.
It is one of the first imaging spectro-polarimeter
s working at the Fe I 1.5649 ?m line, and is used
for the observation of the deepest photospheric
layers. IRIM combines the advantages of the
infrared Zeeman sensitivity with the capability
of spatial mapping. It provides a promising tool
to probe the small-scale magnetic features.
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CME initiation physics
Breakout model eruptions carried out by Gimin
Gao and Peter MacNeice (Drexel University) of
asymmetric configurations high resolution study
of shock structures with potential for particle
acceleration.
Research by team member Terry Forbes (UNH)
studying the physics of line-tied twisted flux
ropes, was able to show that such initial
configurations can explain (1) eruption without
escape, (2) out-of-plane twisting motion, and (3)
formation of aneurism-like structures
Alfven Mach No.
Density
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Numerical Simulation of Interplanetary CME
Propagation
contours density in equatorial plane
color velocity at boundary and ejecta
Remote observations of the photospheric magnetic
field
Remote observations of the coronal mass ejection
(CME)

• APPROACH
• Use available remote observations of solar
  activity for WSA (Arge et al.) and cone (Zhao et
  al.) models (Stanford)
• Use outputs from the above models for 3-D
  magneto-hydrodynamic model (U. Colorado -
  Odstrcil et al.)

Plasma cloud is ejected into interplanetary space

• FOLLOW-ON USE OF BASIC RESEARCH RESULTS FROM MURI
• NSF/Center for Integrated Space Weather Modeling
  (CISM) has incorporated the system for
  development of their solar-energetic-particle
  models
• NOAA/Space Environment Center is incorporating
  the system for prediction of solar wind
  parameters at Earth

Interplanetary shock and ejecta are approaching
Earth
PI Dusan Odstrcil, University of Colorado
NOAA/SEC
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Observe how CMEs propagate to through the
interplanetary medium to 1AU
SMEI observations of the January 20, 2005 CME,
shown in a remote-view presentation for the same
time. The view is from 30 above the ecliptic
plane and about 30 west of the Sun-Earth line.
There is little or no evidence that the bulk of
the CME mass reached Earth (shown as a blue dot)
even though the solar energetic particles
associated with the event arrived within 20
minutes of the event onset, and the shock
associated with the CME event reached the Earth
on about 18 UT January 21.
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Conclusions about the most critical research that
will follow from this project

• We must resolve the basic physics of the CME
  Initiation problem before comprehensive
  Sun-heliosphere system models will have any real
  predictive capability. This will be accomplished
  with the analysis of better data of the pre-CME
  coronal and chromospheric evolution to be taken
  with upcoming NASA missions (Solar-B, Stereo, and
  SDO), new high-resolution ground-based data, and
  by careful comparisons of this data with existing
  and future theoretical models. This focus-topic
  was one of those recommended by the steering
  committee for LWS-TRT, because of its importance
  for the future of space weather models.
• We must continue the development of techniques
  that allow the incorporation of vector magnetic
  field data into time dependent models of flare
  and CME producing regions of the Sun. This
  capability is required by any realistic
  Sun-heliosphere model with predictive capability.
  
• The remainder of this talk is an outline for
  carrying out this research by members of our
  group at UC Berkeley and collaborators.

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Developing the techniques for determining the
dynamics of magnetic fields at the photosphere,
needed for dynamic models of the corona
Data Driving --- The Strategy
Model Corona
Active Boundary Layer
Observational Data / MEF, ILCT
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The objective

• To directly incorporate observations of the
  vector magnetic field at the photosphere (or
  chromosphere) into physics-based dynamic models
  of the solar atmosphere

• The requirements
• Sequences of reduced, ambiguity-resolved vector
  magnetograms
• of sufficient quality to incorporate into an MHD
  code
• (2) A robust method of determining the electric
  field consistent with both
• the observed evolution of the photospheric field
  and Faradays Law
• (3) An MHD code (or set of coupled codes)
  capable of modeling a region
• encompassing the photosphere (where relatively
  reliable measurements
• of the magnetic field are available),
  chromosphere, transition region and
• corona
• (4) A physically self-consistent means of
  incorporating (1) and (2) into (3)

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• Understand sequences of reduced, high-quality,
  ambiguity-resolved vector magnetograms well
  enough to incorporate them into a numerical
  simulation
• What magnetic field data provide the most
  important information about
• the state of the solar atmosphere, and how
  do we prepare the data and
• make best use of it?
• What is the best way to generate the initial
  atmosphere of a
• time-dependent calculation one that is both
  physically meaningful,
• and consistent with the relevant
  observations of the corona?
• (current method the optimization
  technique, e.g., Wheatland et al. 2000)
• How do we best describe the evolution of a model
  photosphere
• given the evolution of, and noise in, the
  observed data and our best
• understanding of the most important physics?

We currently rely on our colleagues from our
SHINE-funded collaboration with CoRA and MSU to
obtain quality measurements of active region
vector magnetic fields, and to address each of
these questions prior to attempting to
incorporate a given dataset into a numerical
calculation. (e.g., IVM data AR8210, May
1998 AR9046, June 2000 AR10030, July 2002
AR10725, Feb 2005)
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• (2) A method of determining the electric field
  consistent with both the observed evolution of
  the photospheric field and the MHD induction
  equation e.g., ILCT (Welsch et al. 2004) or MEF
  (Longcope 2004). The following is a description
  of how ILCT works.
• Apply Fourier Local Correlation Tracking (FLCT,
  Welsch et al. 2004) to
• to obtain an approximation to the 2D flux
  transport velocity uf
• Note that uf does not represent the 3D flow field
  of the magnetized
• plasma, v. However, the two are
  geometrically related (Demoulin
• Berger 2003)

Note that FLCT and ILCT are being transitioned to
CISM as Deliverables. The current codes are
publicly available on our MURI website.
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To demonstrate how ILCT relates the MHD induction
equation to the flux transport velocity, consider
the vertical component of the ideal MHD
induction equation (here, for clarity, we
neglect the resistive term --- in general, it
can be included)
Substituting the geometric relation of the
previous slide, we have
(1)
Now, simply define Bnuf in the following way
(2)
Substituting this expression into (1) yields
Since the LHS is known, we have a Poisson
equation for f that can be easily solved.
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Taking the curl of (2), we have
If we assume that u(FLCT) (our LCT approximation
of uf) represents a true flux transport velocity,
we again have a solvable Poisson equation.
With both scalar potentials known, we can
determine a flux transport velocity that is both
consistent with the observed evolution of the
photospheric field and the MHD induction
equation
Up to this point, the analysis only requires the
normal component of the magnetic field! The
vector field is necessary only when
extracting the 3D flow field from
Note that to obtain v, we must appeal to the fact
that field-aligned flows are unconstrained by the
induction equation (one way of closing the
system is to simply assume ).
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• Brian Welsch has recently implemented a
  preliminary, automated
• Magnetic Evolution Pipeline (MEP)
• New MDI magnetograms are automatically downloaded
  (cron
• checks for new magnetograms using wget),
  de-projected, and
• tracked using FLCT
• The output stream includes de-projected
  magnetograms, FLCT
• flows (.png graphics files and ASCII data
  files), and tracking parameters
• Full documentation and all codes (including
  possible bugs!) are
• currently online

http//solarmuri.ssl.berkeley.edu/welsch/public/d
ata/Pipeline/
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Validation of ILCT, MEF and other similar
methods Use artificial magnetograms from MHD
simulations where the solutions are known
(Note that the MHD code used for this purpose,
ANMHD, is publicly available from our MURI
website, and is slated to be assimilated by CCMC)
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Validation of velocity inversion techniques
MEF
FLCT
ILCT
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Validation of velocity inversion techniques vx,
vy, vz
MEF
FLCT
ILCT
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1. An MHD code (or set of coupled codes) capable of
   modeling a region encompassing the
   photosphere, chromosphere, transition region and
   corona

• Some realities
• Extreme spatial and temporal disparities
• small-scale, active region, and global features
  are fundamentally inter-connected
• magnetic features at the photosphere are
  long-lived (relative to the convective turnover
  time) while features in the magnetized corona can
  evolve rapidly (e.g., topological changes
  following reconnection events)
• Vastly different physical regimes
• photosphere and below relatively dense,
  turbulent (high-ß) plasma with strong magnetic
  fields organized in isolated structures
• corona field-filled, low-density, magnetically
  dominated plasma (at least around strong
  concentrations of magnetic flux!)
• flow speeds in CZ below the surface are typically
  below the characteristic sound and Alfven speeds,
  while the chromosphere, transition region and
  corona are often shock-dominated

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• different physical regimes (contd)
• corona energetics dominated by optically thin
  radiative cooling, anisotropic thermal
  conduction, and some form of coronal heating
  consistent with the empirical relationship of
  Pevtsov et al. 2003 (energy dissipation as
  measured by soft X-rays proportional to the
  measured unsigned magnetic flux at the
  photosphere)
• photosphere/chromosphere energetics dominated by
  optically thick radiative transitions
• Additional computational challenges
• A dynamic model atmosphere extending from at or
  below the photosphere
• to the corona must
• span a 10 order of magnitude change in gas
  density and a thermodynamic transition from the
  1MK corona to the optically thick, cooler layers
  of the low atmosphere, visible surface, and below
• resolve a 100km photospheric pressure scale
  height (energy scale height in the transition
  region can be as small as 1km!) while following
  large-scale evolution

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Toward more realistic AR models

• We must solve the following system

• Energy source terms (Q) include
• Optically thin radiative cooling
• Anisotropic thermal conduction
• An option for an empirically-based coronal
  heating mechanism --- must maintain a corona
  consistent with the empirical constraint of
  Pevtsov (2003)
• LTE optically thick cooling (options solve the
  grey transfer equation in the 3D Eddington
  approximation, or use a simple parameterization
  that maintains the super-adiabatic gradient
  necessary to initiate and maintain convective
  turbulence)

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Surmounting practical computational challenges

• The MHD system is solved semi-implicitly on a
  block adaptive mesh.
• The non-linear portion of the system is treated
  explicitly using the semi-discrete central method
  of Kurganov-Levy (2000) using a 3rd-order CWENO
  polynomial reconstruction
• Provides an efficient shock capture scheme, AMR
  is not required to resolve shocks
• The implicit portion of the system, the
  contributions of the energy source terms, and the
  resistive and viscous contributions to the
  induction and momentum equations respectively, is
  solved via a Jacobian-free Newton-Krylov
  technique
• Makes it possible to treat the system implicitly
  (thereby providing a means to deal with temporal
  disparities) without prohibitive memory
  constraints

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Toward AR scale MPI-AMR relaxation run (test)

• The near-term plan
• Dynamically and energetically relax a 30Mm
  square Cartesian domain extending to 2.5Mm below
  the surface.
• Introduce a highly-twisted AR-scale magnetic
  flux rope (from the top of a sub-surface
  calculation) through the bottom boundary of the
  domain
• Reproduce (hopefully!) a highly sheared,
  d-spot type AR at the surface, and follow the
  evolution of the model corona as AR flux emerges
  into, reconnects and reconfigures coronal fields
• The long term plan
• global scales / spherical geometry

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• Towards a physically self-consistent means of
  incorporating
• (1) and (2) into (3) The Active
  Boundary Layer

• Use AMPS as essentially two, fully coupled codes
  a thin, dynamic photospheric layer actively
  coupled (internally i.e., not via a framework)
  to the AMPS domain
• Within the thin, photospheric boundary layer,
  the continuity, induction,
• and energy equations are solved given an ILCT
  flow field (assumed to
• permeate the entirety of the thin layer).
• This active boundary is dynamically coupled to
  AMPS, which solves
• the full MHD system in a domain that extends
  from the top of the
• model photosphere into the transition region
  and low corona
• Inherent physical assumption Coronal forces do
  not affect the photosphere
• This internally-coupled system could instead
  extend to the low
• transition region, and then be externally coupled
  to existing Coronal models whose lower boundaries
  necessarily reside in the transition region.

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Summary Picture of the Overall System
Model Corona
Active Boundary Layer
Observational Data / ILCT
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• Summary (where were at)
• Sequences of reduced, ambiguity-resolved vector
  magnetograms of sufficient quality to incorporate
  into an MHD code
• ? --- we look forward to the increasing
  availability of sequences of quality vector
  magnetograms
• (2) A robust method of determining the electric
  field consistent with both
• the observed evolution of the photospheric
  magnetic field and
• Faradays Law
• ? --- complete
• (3) An MHD code (or set of coupled codes)
  capable of modeling a region
• encompassing the photosphere (where
  relatively reliable measurements
• of the magnetic field are available),
  chromosphere, transition region and
• low corona
• ? --- almost there.
• (4) A physically self-consistent means of
  incorporating (1) and (2) into (3)
• ? --- still working on it! Hope to have
  something to present at SHINE