can we use nonlinear and selfconsistent models for data analysis? we learned from prof. schindler...

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Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent models. Karl Schindler also introduced me to observational data (Helmetstreamer and coronal mass ejections observed with SOHO/LASCO) and encouraged me to develop a corresponding 2D MHD model under his supervision. New aspects: - Feed models directly with measured data. - Computations in 3D. Thomas Wiegelmann

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Page 1: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Can we use nonlinear and selfconsistent models for data analysis?

• We learned from Prof. Schindler about the importanceof nonlinear and selfconsistent models.

• Karl Schindler also introduced me to observational data(Helmetstreamer and coronal mass ejections observedwith SOHO/LASCO) and encouraged me to develop a corresponding 2D MHD model under his supervision.

• New aspects:

- Feed models directly with measured data.

- Computations in 3D.

Thomas Wiegelmann

Page 2: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

• We cannot measure coronal magnetic fields directly.• Extrapolate the coronal magnetic fields from photospheric

(vector) magnetograms.• Needed: Model assumptions regarding the coronal plasma.• Use the reconstructed magnetic field model to support

data analysis, e.g., - Coronal images (SOHO, Solar-B)

- Doppler maps (SOHO/Sumer) - Stereoscopy (STEREO-mission) - Tomography (STEREO-mission)

Example: Coronal magnetic fields

Page 3: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Model Mathematics Observationsneeded

Validity

Potential

Fields

Line of sightmagnetogram

(Global) currentfree regions,quiet sun

Linear Force-

Free Fields

LOS magnetogram

+ observations ofplasma structures

Local in activeregions, low-betaplasma

Non Linear Force-Free

Vectormagnetogram

(3 times more data,ambiguities, noise)

Active regions,low beta plasmain low corona

MHS

Equilibrium

Vectormagnetogram

+ Tomographic Inversion of density

Helmet streamer,finite beta plasma,full solar corona

Coronal magnetic field models

0

)()( 0

B

pBB

0

)(

B

BrB

0

B

BB 0

0

B

B

Page 4: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Active regions contain mainly closed magnetic loops. Coronal plasma is trapped in closed loops and causes bright emission.The large scale magnetic field structure in coronal holes is open. The coronal plasma escapes along open field lines (solar wind). and the emissivity in coronal lines is strongly reduced here.

Page 5: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

EIT 195 Fe XIIFormation temperature1.5 million K

EIT 304 He IIFormation temperature60,000-80,000 K

Coronal Holes (Wiegelmann & Solanki, Sol. Phys. 2004)

Page 6: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent
Page 7: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

The emitting volume filled by gas at that temperaturecorresponds to the emitted radiation. In CH ~70% at low and ~10% at high temperaturescompared with the quiet Sun.

Use RTV scaling laws to approximate temperatures T ~ (pL)1/3

Page 8: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

EIT-image and projections of magnetic

field lines for a potential field (α=0) .(bad agreement)

Linear force-free field with α=+0.01 [Mm-1](bad agreement)

Active Regions (Marsch, Wiegelmann & Xia, A&A 2004)We use a linear force-free model with MDI-data and have the freedomto choose an appropriate value for the force-free parameter α.

Page 9: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Linear force-free field with α=-0.01 [Mm-1](better agreement)

3D-magnetic field lines, linear force-free α=-0.01 [Mm-1]

Page 10: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

SUMER Dopplergram in NeVIII ( 77 nm) and a 2-D-projection of some field lines. Mass flux density inferred from Doppler-

shift and intensity from SUMER observations.

up

down

Page 11: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Nonlinear force-free fields

• Why do we need nonlinear force-free fields?- Non magnetic forces are small in the corona.

- Potential and linear force-free fields are to simple to estimate free energy and magnetic topology.

• The computation is much more difficult:- Mathematical difficulties due to non-linearity.- Vector magnetograms are not force-free.- Transversal B-field is very noisy.- Limited field of view for current instruments (SFT/Tokyo, VTT/Tenerife, IVM/Hawaii)

BrJ )(

Page 12: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent
Page 13: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Preprocessing of non-force-free and noisy magnetograms.(Wiegelmann, Inhester, Sakurai 2006, using force-free consistency criteria developed by Aly 1989)

Page 14: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent
Page 15: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Test the nonlinear force-free extrapolations with Low&Lou 1990 equilibrium.

a: Reference, b: Potential field, c: Reconstruction from noisy data. d: Reconstruction from preprocessed noisy data

Page 16: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Preprocessing of vector magnetograms helps to diminish inconsistencies and noise.

(Wiegelmann, Inhester, Sakurai, Sol. Phys. 2006)

Page 17: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Measured loops in a newly developed AR (Solanki, Lagg, Woch,Krupp, Collados, Nature 2003)

Potential field reconstruction

Linear force-free reconstruction Non-linear force-free reconstruction

Comparison of observed magnetic loops and extrapolationsfrom the photosphere with different models.

Page 18: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

We compared measurements of magnetic loops in a newly developed active region with extrapolations from the photosphere. We got the best agreement ofmeasured and extrapolated loops for a non-linear force-free magnetic field model.

(Wiegelmann, Lagg, Solanki, Inhester, Woch, A&A 2005)

Page 19: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent
Page 20: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Magnetic fields and coronal tomography

a) Use only line of sight density integrals.

(Wiegelmann and Inhester, Sol. Phys., 2003)

b) Use only magneticfield data.

c) Use both line of sightdensity integrals andmagnetic field as regularization operator.

Page 21: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

• Launched 25.October 2006.

Near Future: STEREO-mission

Two almost identical spacecrafts will observe the Sun and solar wind

• Spacecrafts have different orbits due to Swing-by at moon.

• The two STEREO spacecrafts separate about 44o every year.

• More than 2GB data every day.

PhD students at the MPS in Lindau: - Li Feng: Stereoscopy of Active Regions.- Peng Ruan: Global model of the corona.

Markus Aschwanden:Since the STEREO mission is our first extensive multi-spacecraft 3D exploration of our heliosphere, its importance might be compared with the first determination of the true 3D geometry of our Earth globe, thaught by Thales of Milet and Pythagoras around 600 BC.

Page 22: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

2000-3-1 14:22 3-2 17:44

Li Feng: Stereoscopy of Active Regions

TRACE EUV images

Classical Stereoscopy

Magnetic Stereoscopy Optimal linear force-free model (black) andcoronal loops (red) from two viewpoints.

Page 23: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Peng Ruan:Global coronal modeling

Temperature distribution in the solar corona cut through longitude Ø=40o and 220o

Compute global magneticfield with different models:- Potential and LFF fields-MHS (Neukirch 95 model)

Compute the coronal plasmawith the help of Scaling Laws (Schrijver et al 2004)or selfconsistently from MHS model.

Compare artificial coronal images with real imagesfrom 2 Stereo viewpoints.

Aim: Find optimal model parameter set.

Page 24: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Conclusions• Potential magnetic fields and linear force-free

fields are popular due to their mathematic simplicity and available data. (e.g. from MDI on SOHO, Kitt Peak)

• Non-linear force-free fields are necessary todescribe active regions exactly. More challenging both observational (vector magnetographs) and mathematical.

• Vector magnetograms with high spatial and temporal resolution become available soon (SOLIS, Solar-B, SDO, Solar Orbiter).

Page 25: Can we use nonlinear and selfconsistent models for data analysis? We learned from Prof. Schindler about the importance of nonlinear and selfconsistent

Thank you very much to

Prof. Karl Schindler