Toward More Realistic 3D MHD Simulations of Magnetic Flux Emergence (and Decay) in Active Regions W. P. Abbett Space Sciences Laboratory University of.

Slides:



Advertisements
Similar presentations
Particle acceleration in a turbulent electric field produced by 3D reconnection Marco Onofri University of Thessaloniki.
Advertisements

Chip Manchester, Fang Fang, Bill Abbett, Bart van der Holst Patterns of Large- Scale Flux Emegence Patterns of Large- Scale Flux Emegence.
Can We Determine Electric Fields and Poynting Fluxes from Vector Magnetograms and Doppler Shifts? by George Fisher, Brian Welsch, and Bill Abbett Space.
Emerging Flux Simulations Bob Stein A.Lagerfjard Å. Nordlund D. Benson D. Georgobiani 1.
Simulation of Flux Emergence from the Convection Zone Fang Fang 1, Ward Manchester IV 1, William Abbett 2 and Bart van der Holst 1 1 Department of Atmospheric,
Chip Manchester 1, Fang Fang 1, Bart van der Holst 1, Bill Abbett 2 (1)University of Michigan (2)University of California Berkeley Study of Flux Emergence:
“Assimilating” Solar Data into MHD Models of the Solar Atmosphere W.P. Abbett SSL UC Berkeley HMI Team Meeting, Jan 2005.
Using Photospheric Flows Estimated from Vector Magnetogram Sequences to Drive MHD Simulations B.T. Welsch, G.H. Fisher, W.P. Abbett, D.J. Bercik, Space.
Simulations of the Quiet Sun Magnetic Field: From the Upper Convection Zone into the Corona William P. Abbett Space Sciences Laboratory, Univ. of California,
1 A New Technique for Deriving Electric Fields from Sequences of Vector Magnetograms George H. Fisher Brian T. Welsch William P. Abbett David J. Bercik.
Reducing the Divergence of Optimization-Generated Magnetic Fields J.M. McTiernan, B.T. Welsch, G.H. Fisher, D.J. Bercik, W.P. Abbett Space Sciences Lab.
Simulations of Emerging Magnetic Flux in Active Regions W. P. Abbett Space Sciences Laboratory University of California, Berkeley.
Update: Incorporating Vector Magnetograms into Dynamic Models of the Solar Atmosphere CISM-AG Meeting: March 2006 Bill Abbett, Brian Welsch, George Fisher.
Estimating Electric Fields from Sequences of Vector Magnetograms George H. Fisher, Brian T. Welsch, William P. Abbett, and David J. Bercik University of.
UCB-SSL Plans for Next Year Joint CCHM/CWMM Workshop, July 2007 W.P. Abbett, G.H. Fisher, and B.T. Welsch.
Solar Turbulence Friedrich Busse Dali Georgobiani Nagi Mansour Mark Miesch Aake Nordlund Mike Rogers Robert Stein Alan Wray.
Connecting the Quiet Sun Convection Zone and Corona W.P. Abbett Space Sciences Laboratory Univ. of California, Berkeley.
Coupled Models for the Emergence of Magnetic Flux into the Solar Corona W. P. Abbett UC Berkeley SSL G. H. Fisher, Y. Fan, S. A. Ledvina, Y. Li, and D.
Diffusion Model Error Assessment Jim E. Morel Texas A&M University CRASH Annual Review October 29, 2010.
Modeling Active Region Magnetic Fields on the Sun W.P. Abbett Space Sciences Laboratory University of California, Berkeley.
New Opportunities: Flux Emergence Modeling George H. Fisher Space Sciences Laboratory UC Berkeley.
Incorporating Vector Magnetic Field Measurements into MHD models of the Solar Atmosphere W.P. Abbett Space Sciences Laboratory, UC Berkeley and B.T. Welsch,
Inductive Local Correlation Tracking or, Getting from One Magnetogram to the Next Goal (MURI grant): Realistically simulate coronal magnetic field in eruptive.
UCB-SSL Progress Report for the Joint CCHM/CWMM Workshop W.P. Abbett, G.H. Fisher, and B.T. Welsch.
Understanding the Connection Between Magnetic Fields in the Solar Interior and the Solar Corona George H. Fisher Space Sciences Laboratory UC Berkeley.
The Dynamic Evolution of Quiet Sun Magnetic Fields in the Solar Atmosphere W.P. Abbett, Space Sciences Laboratory, Univ. of California, Berkeley
Subsurface Evolution of Emerging Magnetic Fields Yuhong Fan (HAO/NCAR) High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR)
SSL (UC Berkeley): Prospective Codes to Transfer to the CCMC Developers: W.P. Abbett, D.J. Bercik, G.H. Fisher, B.T. Welsch, and Y. Fan (HAO/NCAR)
Ward Manchester University of Michigan Coupling of the Coronal and Subphotospheric Magnetic Field in Active Regions by Shear Flows Driven by The Lorentz.
High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR) The National Center for Atmospheric Research is operated by the University.
Data-Driven Simulations of AR8210 W.P. Abbett Space Sciences Laboratory, UC Berkeley SHINE Workshop 2004.
Turbulent Dynamos and Small-Scale Activity in the Sun and Stars George H. Fisher Dave Bercik Chris Johns-Krull Lauren Alsberg Bill Abbett.
Modeling the Dynamic Evolution of the Solar Atmosphere: C4: HMI-AIA Team Meeting: Bill Abbett SSL, UC Berkeley.
Using Photospheric Flows Estimated from Vector Magnetogram Sequences to Drive MHD Simulations B.T. Welsch, G.H. Fisher, W.P. Abbett, D.J. Bercik, Space.
The Effect of Sub-surface Fields on the Dynamic Evolution of a Model Corona Goals :  To predict the onset of a CME based upon reliable measurements of.
1 A New Technique for Deriving Electric Fields from Sequences of Vector Magnetograms George H. Fisher Brian T. Welsch William P. Abbett David J. Bercik.
Using Simulations to Test Methods for Measuring Photospheric Velocity Fields W. P. Abbett, B. T. Welsch, & G. H. Fisher W. P. Abbett, B. T. Welsch, & G.
Modeling Emerging Magnetic Flux W.P. Abbett, G.H. Fisher & Y. Fan.
MHD Modeling of the Large Scale Solar Corona & Progress Toward Coupling with the Heliospheric Model.
A Simplified Treatment of Optically Thick Radiative Transfer in Large-scale Convection Zone to Corona Models W.P. Abbett and G.H. Fisher Space Sciences.
Summary of UCB MURI workshop on vector magnetograms Have picked 2 observed events for targeted study and modeling: AR8210 (May 1, 1998), and AR8038 (May.
New Coupled Models of Emerging Magnetic Flux in Active Regions W. P. Abbett, S. A. Ledvina, and G.H. Fisher.
Coronal Heating of an Active Region Observed by XRT on May 5, 2010 A Look at Quasi-static vs Alfven Wave Heating of Coronal Loops Amanda Persichetti Aad.
Solar Physics Course Lecture Art Poland Modeling MHD equations And Spectroscopy.
Stratified Magnetohydrodynamics Accelerated Using GPUs:SMAUG.
The Dynamic Evolution of Twisted Omega-loops in a 3D Convective Flow W.P. Abbett 1, Y. Fan 2, & G. H. Fisher 1 W.P. Abbett 1, Y. Fan 2, & G. H. Fisher.
PAT328, Section 3, March 2001MAR120, Lecture 4, March 2001S16-1MAR120, Section 16, December 2001 SECTION 16 HEAT TRANSFER ANALYSIS.
A particle-gridless hybrid methods for incompressible flows
Decay of a simulated bipolar field in the solar surface layers Alexander Vögler Robert H. Cameron Christoph U. Keller Manfred Schüssler Max-Planck-Institute.
Mass loss and Alfvén waves in cool supergiant stars Aline A. Vidotto & Vera Jatenco-Pereira Universidade de São Paulo Instituto de Astronomia, Geofísica.
3D simulations of solar emerging flux ISOBE Hiroaki Plasma seminar 2004/04/28.
© Fluent Inc. 11/24/2015J1 Fluids Review TRN Overview of CFD Solution Methodologies.
3D Spherical Shell Simulations of Rising Flux Tubes in the Solar Convective Envelope Yuhong Fan (HAO/NCAR) High Altitude Observatory (HAO) – National Center.
HEAT TRANSFER FINITE ELEMENT FORMULATION
Gas-kineitc MHD Numerical Scheme and Its Applications to Solar Magneto-convection Tian Chunlin Beijing 2010.Dec.3.
Emerging Flux Simulations & semi-Sunspots Bob Stein A.Lagerfjärd Å. Nordlund D. Georgobiani 1.
A Non-iterative Hyperbolic, First-order Conservation Law Approach to Divergence-free Solutions to Maxwell’s Equations Richard J. Thompson 1 and Trevor.
SHINE Formation and Eruption of Filament Flux Ropes A. A. van Ballegooijen 1 & D. H. Mackay 2 1 Smithsonian Astrophysical Observatory, Cambridge,
1 Zonal Boundary Conditions. 2 Some Basics The flow domain is divided into zones and grids are generated within each zone. The flow equations are solved.
Introduction to Space Weather Jie Zhang CSI 662 / PHYS 660 Spring, 2012 Copyright © The Sun: Magnetic Structure Feb. 16, 2012.
GOAL: To understand the physics of active region decay, and the Quiet Sun network APPROACH: Use physics-based numerical models to simulate the dynamic.
THE DYNAMIC EVOLUTION OF TWISTED MAGNETIC FLUX TUBES IN A THREE-DIMENSIONALCONVECTING FLOW. II. TURBULENT PUMPING AND THE COHESION OF Ω-LOOPS.
Numerical Simulations of Solar Magneto-Convection
Ward Manchester University of Michigan
WG1 – Sub-surface magnetic connections
GOAL: To understand the physics of active region decay, and the Quiet Sun network APPROACH: Use physics-based numerical models to simulate the dynamic.
Wave heating of the partially-ionised solar atmosphere
Convergence in Computational Science
Finite Volume Method for Unsteady Flows
Coronal Loop Oscillations observed by TRACE
Presentation transcript:

Toward More Realistic 3D MHD Simulations of Magnetic Flux Emergence (and Decay) in Active Regions W. P. Abbett Space Sciences Laboratory University of California, Berkeley

Challenges: Computational domain encompasses magnetized plasma of differing physical characteristics: –The convecting high-beta super-adiabatically stratified plasma of the sub-surface layers –The beta~1 surface layers: includes the energetic transition from the optically thick, cool chromosphere to the magnetically-heated, optically thin sparse corona –The low-beta magnetically dominated corona: energetics of the magnetically-confined coronal plasma dominated by thermal conduction and oprically thin radiative losses

Extreme disparity in both spatial and temporal scales: –Active regions on the photosphere evolve over time scales of days, weeks, and months, yet simulations that encompass both photospheric and coronal plasma are often Courant limited by e.g. fast moving magneto-acoustic waves in coronal loops. Resolving these waves can introduce unnecessary numerical diffusion at and below the surface. –Conductive and radiative timescales further restrict explicit calculations –Small scale structures can affect the evolution of large scale fields (e.g. the effect of convective turbulence on the emergence and decay of active region fields)

This has motivated a new numerical approach (or more precisely, a combination of existing techniques combined together to form a new code designed specifically for this set of challenges): First, the obligatory list of the system of equations that must be solved:

The energy source terms are of critical importance in order to couple a turbulent model convection zone with a low-density, magnetized model corona Source terms in the corona: Source term in the lower layers of the convection zone: (anisotropic thermal conduction and optically-thin radiative cooling) (radiative heating in the diffusion approximation with the radiative conductivity approximated using Kramer’s opacity law)

Artificial source terms acting to mimic optically-thick chromospheric cooling, and an average coronal heating mechanism consistent with the empirical relationship of Pevtsov et al. 2005: However, in practice, each term is multiplied by an envelope function (either depth, temperature or density dependent, depending on the individual term) to ensure that the heating or cooling term is smoothly shut off as the atmosphere transitions to a regime where a particular treatment is inapplicable. Of course, energy terms due to viscous and resistive heating are included as well. Each individual source term is included in the MHD energy equation

The Components of the Method: 1.A “Jacobian-free” Newton-Krylov fully implicit solver The basic idea: a multi-dimensional Taylor expansion of the system F(q) about the current state vector q Then for successive second-order corrections to an initial guess for q, solve and u pda te q via

A problem with multi-dimensional Newton-Raphson alone is that the matrix J = (dF/dq)| k takes up an excessive amount of memory: –J is an N X N matrix where N = neq∙nx∙ny∙nz The Newton-Krylov approach gets around this by forming a linear residual and solving for the correction vector using a standard Krylov-based technique called “GMRES”: where β is determined via the minimization of in a least-squares sense. The main point of all this, is that all one needs in the above sum to solve for the Newton correction is a matrix-vector product (of dimension N), which can be approximated by the “Frechet” derivative for any vector v, thereby eliminating the need for the explicit formation and storage of the matrix J.

2. We need a numerical representation of the flux divergence terms in the MHD system --- there are a number of techniques available, but for simplicity in incorporating the scheme into the adaptive mesh domain-decomposition framework we employ the semi-discrete central scheme of Kurganov and Levy Ignoring the source terms, we have the system: Which can be represented numerically via: with flux functions F given by: where and Here, P i,j,k represents a third order CWENO (central weighted essentially non-oscillatory) polynomial interpolation of the state vector u to the cell faces, and λ l are the eigenvalues of the system.

3. The MPI and structured AMR (Adaptive Mesh Refinement) framework is that provided by PARAMESH v3.0 (MacNeice et al. 2000). Parallelization is achieved through domain decomposition –the current numerical scheme inherently minimizes inter-processor communication (e.g., block boundary data is exchanged relatively infrequently). Of course, the disadvantage of any central non-staggered scheme is the need to ensure that the magnetic field is divergence-free. Currently, we incorporate the “8-wave” formulation of Powell et al (since our particular domain of interest generally does not exhibit regions of stagnation); though we intend to incorporate a Constrained Transport scheme in the near future.

Putting it all together A simple semi-implicit temporal differencing scheme: Where here, e indicates the Newton-Raphson error vector (iterated to convergence), F represents the high-order, non-operator split numerical representation of the flux divergence vector (the quantities in parenthesis in the MHD system of conservation equations), and g denotes the source terms of the system that we wish to treat implicitly (here, we choose that the system be Courant-limited by the terms in f ). Alternatively, we can define the error vector as where here, the source terms are included in f. In the context of this particular differencing scheme, F n (obtained from the Kurganov-Levy explicit solution) can be viewed as a “physics-based pre-conditioner” for the Newton-Krylov system --- this greatly reduces the number of implicit iterations necessary for convergence.

Initial Results: First, the initial state must be generated --- the most challenging aspect of a calculation of this type. The state must include a super- adiabatically stratified model convection zone (at least extending ~ 4 Mm below the visible surface), a beta~1 cool model photosphere- chromosphere, along with the low-beta, low density, hot corona. Left: Photospheric surface layer (background shading denotes temperature perturbations above the mean state; density perturbations are shown by the overlaid contours). A constant radiative flux is imposed at the closed lower boundary, horizontal boundaries of this sub-domain are periodic, and the vertical boundary is assumed stress-free and closed. This state is not yet fully relaxed.

The transition layers should be reasonably resolved, and the total domain must be able to realistically encompass a small active region Left: Temperature perturbations along a vertical slice of this initial (un-relaxed) sub-domain (background shading denotes vertical velocity perturbations above the mean state; unsigned horizontal velocities are indicated by the overlaid contours). Once a dynamically relaxed state is achieved in this initial sub-domain, the periodic slices will be inserted in the MPI, domain-decomposed version of the code, allowing for a much larger, active region-scale domain in which to introduce strong, twisted flux ropes.

Sub-domain solutions at different depths (temperature perturbations at each height shown) from ~4 Mm below the visible surface to a K transition layer (above the photosphere, but below the corona at the top of the model “overshoot layer”).

Progress on the MPI-AMR version of the code: Above: Orszag-Tang vortex MHD test. Shown is the x- component of the magnetic field along horizontal slices through the 3D domain. Left: A horizontal slice through a 3D MHD blast test calculation --- shown are contours of the magnetic field strength. The calculation was performed on a Beowulf cluster. Block boundaries are shown; there are 32 cells per block and four levels of refinement. :

Once a dynamically relaxed state is achieved, an active region-scale buoyant flux rope can be inserted below the surface (or introduced into the lower boundary of the model convection zone), and magnetic structures can self-consistently emerge, evolve, and decay throughout the model atmosphere (similar to what was done in Abbett et al shown below for flux tubes in the deep convection zone)

References and Contact Information: Abbett, W.P., Fisher, G.H., Fan, Y., and Bercik, D.J., 2004, ApJ, 612, 557. Kurganov, A., and Levy, D., 2000, SIAM J. Sci. Comput., 22, MacNeice, P., Olson, K.M., Mobarry, C., deFainchtein, R., and Packer, C., 2000, Computer Physics Communications, 126, 330. Pevtsov, A.A., Fisher, G.H., Acton, L.W., Longcope, D.W., Johns-Krull, C.M., Kankelborg, C.C., and Metcalf, T.R., 2003, 598, Powell, K.G., Roe, P.L., Linde, T.J., Gombosi, T.I., De Zeeuw, D.L, JCP, , 284. Author