Resolving the 180 Degree Ambiguity in Vector Magnetic Fields T. Metcalf.

Slides:



Advertisements
Similar presentations
Estimating the magnetic energy in solar magnetic configurations Stéphane Régnier Reconnection seminar on Thursday 15 December 2005.
Advertisements

High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR) The National Center for Atmospheric Research is operated by the University.
CME/Flare Mechanisms Solar “minimum” event this January For use to VSE must be able to predict CME/flare Spiro K. Antiochos Naval Research Laboratory.
High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR) The National Center for Atmospheric Research is operated by the University.
Abstract Individual AR example: 8910 The only selection criterion imposed in this study is that the AR must be within 30 degrees of disk center to minimize.
Can We Determine Electric Fields and Poynting Fluxes from Vector Magnetograms and Doppler Shifts? by George Fisher, Brian Welsch, and Bill Abbett Space.
Free Magnetic Energy and Flare Productivity of Active Regions Jing et al. ApJ, 2010, April 20 v713 issue, in press.
September 2006 CISM All Hand Meeting Properties of Solar Active Regions and Solar Eruptive Events Yang Liu -- Stanford University
Comparison of NLFFF Extrapolations for Chromospheric and Photospheric Magnetograms of AR J. McTiernan SSL/UCB SHINE 2005 Workhsop.
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.
Coronal Boundaries of Active Regions Derived From Soft X-ray Images.
HMI & Photospheric Flows 1.Review of methods to determine surface plasma flow; 2.Comparisons between methods; 3.Data requirements; 4.Necessary computational.
M3 Session AIA/HMI Science Meeting D-1 : M3-Magnetic Field Data Products Data Product Development Session Chairs: R. Larsen/Y. Liu Status: [draft]
HMI – Synoptic Data Sets HMI Team Meeting Jan. 26, 2005 Stanford, CA.
Free Magnetic Energy: Crude Estimates by Brian Welsch, Space Sciences Lab, UC-Berkeley.
1 SDO/HMI Products From Vector Magnetograms Yang Liu – Stanford University
NJIT-seminar Newark, NJITWiegelmann et al: Nonlinear force-free fields 1 Nonlinear force-free extrapolation of coronal magnetic.
September 2006 CISM All Hand Meeting Progress in the Past Year and Plan for Next Year Yang Liu and the Solar Group in Stanford University
Feb. 2006HMI/AIA Science Team Mtg.1 Determining the 3D Magnetic Field Geometry A. A. van Ballegooijen, E. E. DeLuca, M. Bobra Smithsonian Astrophysical.
Magnetic Field Extrapolations And Current Sheets B. T. Welsch, 1 I. De Moortel, 2 and J. M. McTiernan 1 1 Space Sciences Lab, UC Berkeley 2 School of Mathematics.
Free Energies via Velocity Estimates B.T. Welsch & G.H. Fisher, Space Sciences Lab, UC Berkeley.
Inductive Local Correlation Tracking or, Getting from One Magnetogram to the Next Goal (MURI grant): Realistically simulate coronal magnetic field in eruptive.
Predicting Coronal Emissions with Multiple Heating Rates Loraine Lundquist George Fisher Tom Metcalf K.D. Leka Jim McTiernan AGU 2005.
Preliminary Results from Nonlinear Field Extrapolations using Hinode Boundary Data Marc DeRosa (LMSAL), on behalf of the NLFFF Team* WG1 ~ SHINE 2007 *Karel.
POSTER TEMPLATE BY: Solar Flare and CME Prediction From Characteristics of 1075 Solar Cycle 23 Active Regions Determined Using.
Changes of Magnetic Structure in 3-D Associated with Major Flares X3.4 flare of 2006 December 13 (J. Jing, T. Wiegelmann, Y. Suematsu M.Kubo, and H. Wang,
Stokes Inversion 180  Azimuth Ambiguity Resolution Non-linear Force-free field (NLFFF) Extrapolation of Magnetic Field Progress in Setting up Data Processing.
Nonlinear Force-Free Field Modeling AIA/HMI Science Team Meeting Session C2 14 February 2006 Marc DeRosa on behalf of the “NLFFF Consortium” (Karel Schrijver,
Data-Driven Simulations of AR8210 W.P. Abbett Space Sciences Laboratory, UC Berkeley SHINE Workshop 2004.
Free Magnetic Energy in Solar Active Regions above the Minimum-Energy Relaxed State (Regnier, S., Priest, E.R ApJ) Use magnetic field extrapolations.
Jan. 27, 2005HMI team meeting The Minimum Energy Fit The Slowest Motion Required by Induction Dana Longcope Montana State University Work supported by.
Tests of NLFFF Models of AR J.McTiernan SSL/UCB.
Space Weather Forecast With HMI Magnetograms: Proposed data products Yang Liu, J. T. Hoeksema, and HMI Team.
NLFFF Energy Measurement of AR8210 J.McTiernan SSL/UCB.
Active Region Flux Transport Observational Techniques, Results, & Implications B. T. Welsch G. H. Fisher
A particularly obvious example of daily changing background noise level Constructing the BEST High-Resolution Synoptic Maps from MDI J.T. Hoeksema, Y.
2002 May 1MURI VMG mini-workshop1` Solar MURI Vector Magnetogram Mini-Workshop Using Vector Magnetograms in Theoretical Models: Plan of Action.
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.
SDO/AIA science plan: prioritization and implementation: Five Objectives in 10 steps C4/C6/M8HMI/AIA science teams meeting; Monterey; Feb I: C4/C6/M8:
1 What is the best way to use the chromospheric field information in coronal field extrapolation? Current state of art are nonlinear force-free extrapolations.
Instrumental & Technical Requirements. Science objectives for helioseismology Understanding the interaction of the p-mode oscillations and the solar magnetic.
Estimating Free Magnetic Energy from an HMI Magnetogram by Brian T. Welsch Space Sciences Lab, UC-Berkeley Several methods have been proposed to estimate.
Science Data Products – HMI Magnetic Field Images Pipeline 45-second Magnetic line-of-sight velocity on full disk Continuum intensity on full disk Vlos.
Why a Sun-Earth line Coronagraph is Best Doug Biesecker NOAA/SWPC.
Seething Horizontal Magnetic Fields in the Quiet Solar Photosphere J. Harvey, D. Branston, C. Henney, C. Keller, SOLIS and GONG Teams.
Extrapolation of magnetic fields
Coronal Mass Ejection As a Result of Magnetic Helicity Accumulation
Newark, Wiegelmann et al.: Coronal magnetic fields1 Solar coronal magnetic fields: Source of Space weather Thomas Wiegelmann, Julia Thalmann,
Optimization_fff as a Data Product J.McTiernan HMI/AIA Meeting 16-Feb-2006.
Nonlinear force-free coronal magnetic field extrapolation scheme for solar active regions Han He, Huaning Wang, Yihua Yan National Astronomical Observatories,
Azimuth disambiguation of solar vector magnetograms M. K. Georgoulis JHU/APL Johns Hopkins Rd., Laurel, MD 20723, USA Ambiguity Workshop Boulder,
Coronal magnetic fields Thomas Wiegelmann, MPI for Solar-System Research, (Former: MPI für Aeronomie) Katlenburg-Lindau Why are coronal magnetic fields.
SUB-GROUP 1: Surface Solar Magnetic Fields  The central question: Can we infer the orientation of Bz of an ICME at 1 AU by focusing on the study of the.
Source: Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on Author: Paucher, R.; Turk, M.; Adviser: Chia-Nian.
SDO-meeting Napa, Wiegelmann et al: Nonlinear force-free fields 1 Nonlinear force-free field modeling for SDO T. Wiegelmann, J.K. Thalmann,
Session 10 SHINE Workshop, June 23-27, 2008 Vector Magnetic Data Input into Global Models (Session 10) Chairs: Marc DeRosa and Ilia Roussev Working Group.
Spectro-polarimetry of NLTE lines with THEMIS/MSDP Chromospheric Magnetic Structures Results and prospects P. Mein, N. Mein, A. Berlicki,B. Schmieder 1)
A Non-iterative Hyperbolic, First-order Conservation Law Approach to Divergence-free Solutions to Maxwell’s Equations Richard J. Thompson 1 and Trevor.
Magnetic Helicity and Solar Eruptions Alexander Nindos Section of Astrogeophysics Physics Department University of Ioannina Ioannina GR Greece.
Scientific Interests in OVSA Expanded Array Haimin Wang.
Calibration of Solar Magnetograms and 180 degree ambiguity resolution Moon, Yong-Jae ( 文 鎔 梓 ) (Korea Astronomy and Space Science Institute)
Considerations on using Solar-B observations to model the coronal field over active regions Karel Schrijver, Marc DeRosa, Ted Tarbell SOT-17 Science Meeting;
A Method for Solving 180 Degree Ambiguity in Observed Solar Transverse Magnetic Field Huaning Wang National Astronomical Observatories Chinese Academy.
Extrapolating Coronal Magnetic Fields T. Metcalf.
SDO-meeting Napa, Wiegelmann et al: Nonlinear force-free fields 1 A brief summary about nonlinear force-free coronal magnetic field modelling.
Methods for automatic processing
How to forecast solar flares?
NLFFF Energy Measurement of AR8210
New Iterative Method of the Azimuth Ambiguity Resolution
Scientific Collaboration of NAOC Facilities & Solar-B
Presentation transcript:

Resolving the 180 Degree Ambiguity in Vector Magnetic Fields T. Metcalf

2005 JanuaryHMI Science Meeting2 of 10 The Transverse field is Ambiguous by 180 Deg This ambiguity must be resolved before analysis.

2005 JanuaryHMI Science Meeting3 of 10 Ambiguity Resolution is Required to Compute Correct Neutral Lines LOS/Transverse fieldVertical/Horizontal field From K.D. Leka 2000 Jun 05 N22 E20

2005 JanuaryHMI Science Meeting4 of 10 An Example of What Can Go Wrong A “fake” active region from model flux tubes. From Graham Barnes

2005 JanuaryHMI Science Meeting5 of 10 “Regions of Conflict” Region of Conflict “Line Current” Region of Conflict

2005 JanuaryHMI Science Meeting6 of 10 Classification of Various Techniques There are a number of ways to resolve the ambiguity but, as a practical matter, this is most difficult for the most “interesting” datasets while easy for “uninteresting” datasets. I will classify algorithms into two categories: “Requires only HMI data” and “Also requires some other dataset” All the “HMI only” methods make some a priori assumptions about what the field should look like. Problems to bear in mind: –Noise in the vector field measurement. –Projection effects near the limb. –Speed of algorithms.

2005 JanuaryHMI Science Meeting7 of 10 HMI Only Techniques Only HMI data required …. –Acute angle solution (compare transverse field direction to potential or force-free extrapolation) Fast, will fail in complex active regions. –Minimum energy solution (minimize Jz and div B), Metcalf (1994) Slow, but generally robust. –Structure minimization (applies smoothness constraint), Georgoulis et al. (2004) Potentially very fast, but makes some possibly big assumptions (like dB/dz < 0) and applies arbitrary smoothing.

2005 JanuaryHMI Science Meeting8 of 10 HMI+ Techniques HMI + Other data sets required –Correspondence with H-alpha fibrils Generally accurate, but difficult to automate. Would require full disk, high spatial resolution H- alpha images –div B = 0 Promising technique but requires dBz/dz. Would require observations of the chromospheric vector magnetic field from Solar-B or GBOs.

2005 JanuaryHMI Science Meeting9 of 10 What to do? The ‘minimum energy’ solution is usually robust, but too slow for routine work with HMI. Can it be optimized? Georgoulis’ minimum structure algorithm uses derivatives of |B| (an ambiguity free quantity) which makes it faster, but it is not yet clear how robust the technique is. Needs more testing. Perhaps the “right” way to resolve the ambiguity is to use  B=0 since this equation makes no assumptions. –Chromospheric fields from Solar-B/GBOs will help HMI. –How sensitive is this to noise? The currently available codes all use planar geometry. For HMI the codes will need to be upgraded to use spherical geometry, unless we only plan to look at ARs individually. This should be straightforward. K.D. Leka and I are currently attempting to use the vertical structure of the magnetic field observed from the photosphere and chromosphere to quantify the limitations of the algorithms. Stay tuned!

2005 JanuaryHMI Science Meeting10 of 10 Conclusion I forsee (at least) two methods routinely used for the 180° ambiguity resolution: –All vector magnetograms will have a first cut at the ambiguity resolution from the acute angle method. This method is fast and will get the orientation right over most of the field-of-view. Users will have to be made aware of the limitations. –For quantitative analysis, some other, more robust method (TBD) will be used. This algorithm will be slow and will be applied selectively, both in time and space. Questions: –What is the best method for quantitative analysis? –How quickly does the field evolve so that a new ambiguity resolution must be carried out? –How bad is the speed problem?