Data for Helioseismology Testing: Large-Scale Stein-Nordlund Simulations Dali Georgobiani Michigan State University Presenting the results of Bob Stein.

Slides:



Advertisements
Similar presentations
Turbulent Convection in Stars Kwing Lam Chan Hong Kong University of Science and Technology “A Birthday Celebration of the Contribution of Bernard Jones.
Advertisements

SDO/HMI multi-height velocity measurements Kaori Nagashima (MPS) Collaborators: L. Gizon, A. Birch, B. Löptien, S. Danilovic, R. Cameron (MPS), S. Couvidat.
Numerical Simulations of Supergranulation and Solar Oscillations Åke Nordlund Niels Bohr Institute, Univ. of Copenhagen with Bob Stein (MSU) David Benson,
Helioseismic data from Emerging Flux & proto Active Region Simulations Bob Stein – Michigan State U. A.Lagerfjärd – Copenhagen U. Å. Nordlund – Niels Bohr.
Emerging Flux Simulations Bob Stein A.Lagerfjard Å. Nordlund D. Benson D. Georgobiani 1.
Åke Nordlund & Anders Lagerfjärd Niels Bohr Institute, Copenhagen Bob Stein Dept. of Physics & Astronomy, MSU, East Lansing.
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,
SSPVE Discussion Group B Question 5 To what extent is it possible to predict the emergence of active regions before they reach the photosphere, or to predict.
Initial Analysis of the Large-Scale Stein-Nordlund Simulations Dali Georgobiani Formerly at: Center for Turbulence Research Stanford University/ NASA Presenting.
Solar Convection: What it is & How to Calculate it. Bob Stein.
The Sun Astronomy 311 Professor Lee Carkner Lecture 23.
Solar Convection Simulations Bob Stein David Benson.
Supergranulation-Scale Solar Convection Simulations David Benson, Michigan State University, USA Robert Stein, Michigan State University, USA Aake Nordlund,
TIME-DISTANCE ANALYSIS OF REALISTIC SIMULATIONS OF SOLAR CONVECTION Dali Georgobiani, Junwei Zhao 1, David Benson 2, Robert Stein 2, Alexander Kosovichev.
Solar Turbulence Friedrich Busse Dali Georgobiani Nagi Mansour Mark Miesch Aake Nordlund Mike Rogers Robert Stein Alan Wray.
Convection Simulations Robert Stein Ake Nordlund Dali Georgobiani David Benson Werner Schafenberger.
Supergranulation Scale Solar Surface Convection Simulations Dali Georgobiani Michigan State University Presenting the results of Bob Stein (MSU) & Åke.
Solar Magneto-Convection: Structure & Dynamics Robert Stein - Mich. State Univ. Aake Nordlund - NBIfAFG.
Excitation of Oscillations in the Sun and Stars Bob Stein - MSU Dali Georgobiani - MSU Regner Trampedach - MSU Martin Asplund - ANU Hans-Gunther Ludwig.
Summary. Two directions in modeling Adopting physical (realistic) models Creating artificial data sets with simplified physics.
From detailed magneto- convection simulations to modelling the convection zone-corona system Mats Carlsson Institute of Theoretical Astrophysics, University.
Super-granulation Scale Convection Simulations Robert Stein, David Benson - Mich. State Univ. Aake Nordlund - Niels Bohr Institute.
Generation of Artificial Data in Support of SDO-HMI Nagi N. Mansour, NASA ARC Alan Wray, NASA ARC Thomas Hartlep, Stanford CTR Alexander Kosovichev, Stanford.
Supergranulation-Scale Simulations of Solar Convection Robert Stein, Michigan State University, USA Aake Nordlund, Astronomical Observatory, NBIfAFG, Denmark.
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)
Data for Helioseismology Testing Dali Georgobiani Michigan State University Presenting the results of Bob Stein (MSU) & Åke Nordlund (NBI, Denmark) with.
Convection Simulation of an A-star By Regner Trampedach Mt. Stromlo Observatory, Australian National University 8/19/04.
Solar Surface Dynamics convection & waves Bob Stein - MSU Dali Georgobiani - MSU Dave Bercik - MSU Regner Trampedach - MSU Aake Nordlund - Copenhagen Mats.
ob/data.html 1. Emerging Flux Simulations & proto Active Regions Bob Stein – Michigan State U. A.Lagerfjärd – Copenhagen U.
Asymmetry Reversal in Solar Acoustic Modes Dali Georgobiani (1), Robert F. Stein (1), Aake Nordlund (2) 1. Physics & Astronomy Department, Michigan State.
Simulating Solar Convection Bob Stein - MSU David Benson - MSU Aake Nordlund - Copenhagen Univ. Mats Carlsson - Oslo Univ. Simulated Emergent Intensity.
Detection of Emerging Sunspot Regions in the Solar Interior Stathis Ilonidis, Junwei Zhao, and Alexander Kosovichev Stanford University LoHCo Workshop.
Modeling and Data Analysis Associated With Supergranulation Walter Allen.
1 Status of Ring-diagram Analysis of MOTH Data Kiran Jain Collaborators: F. Hill, C. Toner.
Solar Physics Course Lecture Art Poland Modeling MHD equations And Spectroscopy.
P MODE TRAVEL TIME IN ACTIVE REGIONS USING TIME-DISTANCE METHOD CRAAG, Observatory of Algiers, BP 63 Bouzareah 16340, Algiers, Algeria. (1)
Supergranulation Waves in the Subsurface Shear Layer Cristina Green Alexander Kosovichev Stanford University.
Comparison of convective boundary layer velocity spectra calculated from large eddy simulation and WRF model data Jeremy A. Gibbs and Evgeni Fedorovich.
Decay of a simulated bipolar field in the solar surface layers Alexander Vögler Robert H. Cameron Christoph U. Keller Manfred Schüssler Max-Planck-Institute.
Imaging Solar Tachocline Using Numerical Simulations and SOHO/MDI Data Junwei Zhao 1, Thomas Hartlep 2, Alexander G. Kosovichev 1, Nagi N. Mansour 2 1.W.W.Hansen.
Using Realistic MHD Simulations for Modeling and Interpretation of Quiet Sun Observations with HMI/SDO I. Kitiashvili 1,2, S. Couvidat 2 1 NASA Ames Research.
Magneto-Hydrodynamic Equations Mass conservation /t = − ∇ · (u) Momentum conservation (u)/t =− ∇ ·(uu)− ∇ −g+J×B−2Ω×u− ∇ · visc Energy conservation /t.
Local Helioseismology LPL/NSO Summer School June 11-15, 2007.
Photospheric MHD simulation of solar pores Robert Cameron Alexander Vögler Vasily Zakharov Manfred Schüssler Max-Planck-Institut für Sonnensystemforschung.
Valentina Abramenko 1, Vasyl Yurchyshyn 1, Philip R. Goode 1, Vincenzo Carbone 2, Robert Stein Big Bear Solar Observatory of NJIT, USA; 2 – Univ.
Tests of the Ring-Diagram Inversions A. Kosovichev.
Acoustic wave propagation in the solar subphotosphere S. Shelyag, R. Erdélyi, M.J. Thompson Solar Physics and upper Atmosphere Research Group, Department.
Gas-kineitc MHD Numerical Scheme and Its Applications to Solar Magneto-convection Tian Chunlin Beijing 2010.Dec.3.
Emerging Flux Simulations & proto Active Regions Bob Stein – Michigan State U. A.Lagerfjärd – Copenhagen U. Å. Nordlund – Niels Bohr Inst. D. Georgobiani.
Emerging Flux Simulations & semi-Sunspots Bob Stein A.Lagerfjärd Å. Nordlund D. Georgobiani 1.
The Current Status of Sunspot Seismology H. Moradi, H. Schunker, L. Gizon (Max Planck Institute for Solar System Research, Katlenburg-Lindau, Germany)
CHANGSHENG CHEN, HEDONG LIU, And ROBERT C. BEARDSLEY
Horizontal Flows in Active Regions from Multi-Spectral Observations of SDO Sushant Tripathy 1 Collaborators K. Jain 1, B. Ravindra 2, & F. Hill 1 1 National.
日震学的未来与展望 赵俊伟 斯坦福大学汉森试验物理实验室. Outline Some outstanding problems HMI time-distance pipeline Validation of local helioseismology results.
A105 Stars and Galaxies  Homework 6 due today  Next Week: Rooftop Session on Oct. 11 at 9 PM  Reading: 54.4, 55, 56.1, 57.3, 58, 59 Today’s APODAPOD.
Simulations of Solar Convection Zone Nagi N. Mansour.
Solar Convection Simulations Robert Stein, David Benson - Mich. State Univ. Aake Nordlund - Niels Bohr Institute.
Simulated Solar Plages Robert Stein, David Benson - Mich. State Univ. USA Mats Carlsson - University of Oslo, NO Bart De Pontieu - Lockheed Martin Solar.
GOAL: To understand the physics of active region decay, and the Quiet Sun network APPROACH: Use physics-based numerical models to simulate the dynamic.
Planning for Helioseismology with SO/PHI Birch, Gizon, & Hirzberger Max Planck Institute for Solar System Physics.
Radiative Transfer in 3D Numerical Simulations Robert Stein Department of Physics and Astronomy Michigan State University Åke Nordlund Niels Bohr Institute.
Estimation of acoustic travel-time systematic variations due to observational height difference across the solar disk. Shukur Kholikov 1 and Aleksander.
Simulations and radiative diagnostics of turbulence and wave phenomena in the magnetised solar photosphere S. Shelyag Astrophysics Research Centre Queen’s.
Numerical Simulations of Solar Magneto-Convection
Solar Surface Magneto-Convection and Dynamo Action
GOAL: To understand the physics of active region decay, and the Quiet Sun network APPROACH: Use physics-based numerical models to simulate the dynamic.
Helioseismic data from Emerging Flux & proto Active Region Simulations
Forward Modeling for Time-Distance Helioseismology
Supergranule Scale Convection Simulations
holographic measurements of simulated flows
Presentation transcript:

Data for Helioseismology Testing: Large-Scale Stein-Nordlund Simulations Dali Georgobiani Michigan State University Presenting the results of Bob Stein (MSU) & Åke Nordlund (Denmark) with David Benson (MSU) Stanford, August 6, 2007

Stein–Nordlund RHD Simulations Conservative compressible 3D (M)HD equations LTR non-gray radiation transfer Realistic EOS and opacities  No free parameters (except for diffusion model).  Wave excitation and damping occur naturally.  There is an excellent correspondence between the code results and observations. 48 Mm 20 Mm

Simulations Supergranulation scale: 48 Mm x 48 Mm x 20 Mm Resolution: 100 km horizontal, 12–75 km vertical Numerical method: staggered variables Spatial differencing: 6 th order centered finite difference Time advancement: 3 rd order Runge-Kutta

Boundary Conditions Density: logarithmic extrapolation on top and bottom Velocity at the top is taken to be constant at its value at the last physical point Energy (per unit mass): top – slowly evolving average, bottom – fixed energy in inflows Initialization Start from existing 12x12x9 Mm simulation Extend adiabatically to 20 Mm and relax for a solar day to develop structures Double horizontally + small fraction of stretched fluctuations to remove symmetry Relax to develop large-scale structures

Radiation Treatment LTR Non-grey, 4 bin multigroup Equation of State Tabular EOS Includes ionization, excitation H, He, H 2, other abundant elements

Vertical velocity

Horizontal velocity divergence

Vertical velocity, horizontal slices at various heights

Vertical velocity, vertical slice

Image of the vertical momentum showing a granule 30 Mm across. This is a snapshot at a depth of 16.8 Mm.

96 Mm by 96 Mm wide simulations

Vertical Velocity at 2.5 & 8 Mm depth Boxes show domain of earlier simulations at 6, 12, 24 & 48 Mm widths.

Available Datasets Website (some info) Contact Bob Stein (more 2 datasets: 8.5 hr (511 min) solar time, no rotation 58.5 hr, with rotation Simulated data are being ingested into the new SDO JSOC database Thanks to Rick Bogart for his extensive help with archiving!

Archived Data Description Data are in FITS format Temporal cadence is 1 minute 3D spatial grid is 500x500x500 A snapshot of a variable occupies approximately 500 MB of disk space First and third directions are horizontal Second direction is vertical Vertical grid is provided separately

Data Set 1 Duration: 511 minutes, or hours No rotation 5 variables: horizontal velocities V x, V z, vertical velocity V y, temperature, density. Each variable is stored in a different directory, each snapshot in a separate file. Every 20 minutes of data are in one sub- directory.

Data Set 2 Duration: 58 hours 29 minutes Uniform background rotation 9 variables: horizontal velocities V x, V z, vertical velocity V y, temperature, density, pressure, internal energy, electron density and   Each snapshot of a variable is stored in a separate file; 9 variables at each time step are combined to be retrieved together (The data will be available for retrieval soon – maybe, in September)

Units of Variables Length is in 10 8 cm = 1 Mm Time is in 10 2 s Velocities V x, V z, and V y are in 10 km/s Temperature is in K Density is in g/cm 3 Pressure is in 10 5 dynes/cm 2 Internal energy is in 10 5 dynes/cm 2 Electron density is log cm -3

These simulations provide an excellent opportunity to validate various techniques, widely used in solar physics and helio- seismology for directly obtaining otherwise inaccessible properties (subsurface flows, structures etc.) On the other hand, these analysis techniques also help to examine how realistic the simulations are

Data Analysis Power spectrum Tests of time-distance methods Compare the results for the simulations and the SOHO/MDI high-res observations (211.5 Mm by Mm patch, 512 min)

Power Spectra SimulationsMDI high-res data

Time-Distance Diagram

TD Diagrams at Various Depths

Exploring Simulated Surface Structures Spatial filtering Spectral analysis f-mode time-distance analysis Local correlation tracking

Large Structures

Time-Distance Analysis

Local Correlation Tracking Correlation coefficient Is 0.99 But velocity amplitudes are under- estimated (~1.8 times lower than in simulations)

These and other results of the simulated data analysis were published in Georgobiani, D.; Zhao, J.; Kosovichev, A.; Benson, D.; Stein, R.; Nordlund, A. "Local Helioseismology and Correlation Tracking Analysis of Surface Structures in Realistic Simulations of Solar Convection" Astrophysical Journal 2007, Vol. 657, p.1157 Zhao, J.; Georgobiani, D.; Kosovichev, A.; Benson, D.; Stein, R.; Nordlund, A. "Validation of Time-Distance Helioseismology by Use of Realistic Simulations of Solar Convection" Astrophysical Journal 2007, Vol. 659, p.848

Summary - Advantages  More Time – Distance calculations?  Acoustic holography?  MHD: sunspot simulations (Nordlund)  Spectra? Mode asymmetries? Future Plans  Large domain – supergranulation scale  Deep - includes lower turning points  Fast code (parallelizes well)

Mean Atmosphere Temperature, Density and Pressure