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UCB-SSL Plans for Next Year

Joint CCHM/CWMM Workshop, July 2007





W.P. Abbett, G.H. Fisher, and B.T. Welsch

RADMHD: Modeling the combined convection

zone-to-corona system:



The code solves the resistive, fully-compressible MHD system of equations:





    u   0

t

 u   B 2  BB 

     uu   p 

  4  Π    g

I 

t   8  

B

   uB  Bu        B 

t

e 

   eu    p  u    B   Q

2



t 4



Closure relation: a non-ideal equation of state obtained through an inversion

of the OPAL tables (Rogers 2000),



p  p (  , e)

Modeling the combined convection zone-to-corona

system in a physically self-consistent way:



The source term Q in the energy equation,



e 

   eu    p  u    B   Q

2



t 4



must include the important physics believed to govern the evolution of the

combined system. In the corona, this includes



• radiative cooling (in the optically thin limit),

• the divergence of the electron heat flux,

• a coronal heating mechanism (if necessary).



In the lower atmosphere at and above the visible surface,

• radiative cooling (optically thick)



Below the surface in the deeper layers of the convective interior

• radiative cooling (in the optically thick diffusion limit)

Modeling the combined convection zone-to-corona system:

We represent the source term Q as follows:



Q  Qr  Qc  QB



In order to extend the spatial domain to active region scales, we choose not

to solve the optically-thick LTE transfer equation to obtain an expression for

surface cooling, Qr . Instead, we choose to approximate this cooling in

a way that successfully reproduces the average stratification and

solar-like convective turbulence of the more realistic simulations of

Bercik (2002) and Stein et al. (2003):

Q1   ne nh  (T )

Qr  1Q1   2Q2   3Q3 where Q2   1 e  e(  , T0 )

Q3     R (  , T )T 



and 1 ,  2 , and  3 represent dimension-less envelope functions that restrict

each term to the appropriate range of densities or depths in such a way as to

avoid sharp cutoffs.  (T ) is obtained from the CHIANTI atomic database.

Modeling the combined convection zone-to-corona system:

The structure of the transition region and corona depend strongly on the remaining

non-radiative terms in Q  Qr  Qc  QB: the divergence of the electron heat flux,



 T 

Qc   B     || (T ) B  2 

 B 

and an additional coronal heating rate QB (if necessary). We employ an

empirically-based description of coronal heating consistent with the observed

relationship between unsigned magnetic flux and the power dissipated in the



atmosphere by a coronal heating mechanism, QB dV  c .



The RHS of this equation represents the Pevtsov et al. (2003) power law

relationship between X-ray luminosity and unsigned magnetic flux at the



photosphere Lx  c . If we choose a simple heating function of the form

QB  B / B (consistent with Lundquist et al. 2007), we arrive at an

empirically-based form of coronal heating consistent with Pevtsov’s Law:

c B

QB 

 BdV

Modeling the combined convection zone-to-corona system:



The calibrated radiative source term Qr in Q  Qr  Qc  QB , coupled with a

constant radiative flux lower boundary condition (on average) maintains the

super-adiabatic stratification necessary to initiate and sustain convection.



The thermodynamic structure of the model is controlled by the energy

source terms, the gravitational acceleration and the applied thermodynamic

boundary conditions. No stratification is imposed a priori.

Numerical techniques and challenges:



A dynamic numerical model extending from below the photosphere out into

the corona must:



• span a ~ 10 - 15 order of magnitude change in gas density and a

thermodynamic transition from the 1 MK corona to the optically thick, cooler

layers of the low atmosphere, visible surface, and below;



• resolve a ~ 100 km photospheric pressure scale height while

simultaneously following large-scale evolution (we use the Mikic et al. 2005

technique to mitigate the need to resolve the 1 km transition region scale

height characteristic of a Spitzer-type conductivity);



• remain highly accurate in the turbulent sub-surface layers, while still

employing an effective shock capture scheme to follow and resolve shock

fronts in the upper atmosphere



• address the extreme temporal disparity of the combined system

RADMHD: Numerical techniques and challenges

• For the Quiet Sun: we use a semi-implicit, operator-split method.





    u   0

t

 u   B 2  BB 

     uu   p I   Π   g

t   8  4

 

B

   uB  Bu        B 

t

e 

   eu    p  u    B   Q

2



t 4



• Explicit sub-step: We use a 3D extension of the semi-discrete method of

Kurganov & Levy (2000) with the third order-accurate central weighted essentially

non-oscillatory (CWENO) polynomial reconstruction of Levy et al. (2000).

• CWENO interpolation provides an efficient, accurate, simple shock capture

scheme that allows us to resolve shocks in the transition region and corona

without refining the mesh. The solenoidal constraint on B is enforced implicitly.

RADMHD: Numerical techniques and challenges

• For the Quiet Sun: we use a semi-implicit, operator-split method





    u   0

t

 u   B 2  BB 

     uu   p I   Π   g

t   8  4

 

B

   uB  Bu        B 

t

e 

   eu    p  u    B   Q

2



t 4



• Implicit sub-step: We use a “Jacobian-free” Newton-Krylov (JFNK)

solver (see Knoll & Keyes 2003). The Krylov sub-step employs the generalized

minimum residual (GMRES) technique.

• JFNK provides a memory-efficient means of implicitly solving a non-linear

system, and frees us from the restrictive CFL stability conditions imposed by

e.g., the electron thermal conductivity and radiative cooling.

RADMHD: Numerical techniques and challenges

• The MHD system is solved on an adaptive, domain-decomposed mesh.

Note: With our numerical techniques, AMR is not needed to

simulate the Quiet Sun. However, RADMHD has the capability

of interfacing with the PARAMESH libraries (MacNeice et al. 2000)

to provide an adaptive framework.



• Spatial disparities of the combined convection zone-to-corona system

are addressed via the CWENO explicit scheme, the domain decomposition

strategy, and AMR capability if necessary.



• Temporal disparities of the combined convection zone-to-corona system

are addressed via the JFNK implicit scheme. Pre-conditioning is an

essential requirement if one wishes to rapidly relax atmospheres by

significantly exceeding the CFL limit.



• Boundary conditions of the Quiet Sun simulations: Periodic in the

transverse directions, constant radiative flux in through a closed lower

boundary, open coronal boundary

The Quiet Sun magnetic field in the model chromosphere

Magnetic field generated

through the action of a

convective surface

dynamo.



Fieldlines drawn (in both

directions) from points

located 700 km above the

visible surface.



Grayscale image

represents the vertical

component of the velocity

field at the model

photosphere.



The low-chromosphere

acts as a dynamic, high-β

plasma except along thin

rope-like structures

threading the atmosphere,

connecting strong

photospheric structures to

the transition region-

corona interface.



Plasma-β ~ 1 at the

photosphere only in

localized regions of

concentrated field (near

strong high-vorticity

downdrafts



From Abbett (2007)

Flux submergence in the Quiet Sun and the connectivity between an initially

vertical coronal field and the turbulent convection zone









From Abbett (2007)

Reverse Granulation









• A brightness reversal with height in the atmosphere is a common feature of Ca II H and K

observations of the Quiet Sun chromosphere.

• In the simulations, a temperature (or convective) reversal in the model chromosphere occurs

as a result of the p div u work of converging and diverging flows in the lower-density layers

above the photosphere where radiative cooling is less dominant.

Gas temperature and Bz at ~ 700 km above and below the model photosphere









From Abbett (2007)

Flux cancellation and the effects of resolution:



The Quiet Sun magnetic flux

threading the model

photosphere over a 15

minute interval. Grid

resolution ~ 117 X 117 km

Average unsigned flux per

pixel: 34.5 G



Simulated noise-free

magnetograms reduced to MDI

resolution (high-resolution

mode) by convolving the dataset

with a 2D Gaussian with a

FWHM of 0.62” or 459 km.

Average unsigned flux per pixel

is now: 19.9 G



Simulated noise-free

magnetograms reduced to Kitt

Peak resolution. FWHM of the

Gaussian Kernel is 1.0” or 740

km. Average unsigned flux per

pixel: 15.0 G

Observed unsigned flux per pixel at

Kitt Peak: 5.5 G

log B









log β Bz log B









log J

Characteristics of the Quiet Sun model atmosphere:









Note: Above movie is not a timeseries!

PLANS: A Focus on the Physics of Active Region

Flux Emergence….



Extend the RADMHD quiet Sun simulations to active region spatial scales using

our new allocation on NASA’s Discover cluster at Goddard Space Flight Center



Once the large-scale quiet Sun model has energetically relaxed, introduce active

region strength magnetic fields from below by



(1) introducing a magnetic flux tube directly into the portion of the domain

representing the convection zone (similar to the more idealized simulations of,

e.g., Magara 2004, Manchester 2004, Archontis 2007);



(2) introduce magnetic flux into the domain from below using previous ANMHD

calculations of buoyant Ω-loops in the deep interior (Abbett 2000, 2004);



(3) introduce an interacting pair of twisted flux ropes into the RADMHD domain

below the visible surface, and study the magnetic topology of the corona as one

system emerges into another;

The Physics of Flux Emergence….





(4) study the effects of magnetic flux emergence at small scales (e.g., quiet-

Sun fields generated by surface convection or ephemeral active regions), and

the effect of small scale flux emergence on the large scale magnetic topology

of the model corona;



(5) follow the evolution of the model active region after emergence, study the

decay process and magnetic connectivity as convective turbulence interacts

with loop footpoints;



(6) test and validate our inversion techniques and boundary driving schemes by

driving RADMHD model corona with synthetic magnetograms and comparing

the resultant model coronae against the self-consistent calculations.

RADMHD Flux Emergence: Computational Requirements



The most computationally intensive portion of the project is to relax

the convectively unstable portion of the large-scale domain.



We reduce the computational cost by

(1) relaxing periodic sub-domains on our local cluster,

(2) filling the blocks of the larger grid with these solutions, and

(3) introducing an entropy perturbation throughout the large-scale domain to

break the symmetry.



We find that this process takes fewer processor hours than if we simply perturb

large-scale horizontally-invariant, super-adiabatically stratified background

atmospheres and allow the magnetoconvection to develop from scratch.

This is still an expensive process.



By comparison, the AR emergence timescale is quite rapid, and the emergence

runs are relatively inexpensive (though we choose to remain constrained by the

magnetosonic wavespeed in the corona)!



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