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Simulations of Solar Convection Zone

Simulations of Solar Convection Zone. Nagi N. Mansour. Goals. Provide numerical simulation models for interpretation of SDO data Develop understanding of physical mechanisms in the convection zone and links to the atmosphere

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Simulations of Solar Convection Zone

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  1. Simulations of Solar Convection Zone Nagi N. Mansour

  2. Goals • Provide numerical simulation models for interpretation of SDO data • Develop understanding of physical mechanisms in the convection zone and links to the atmosphere • Provide simulation data for testing and developing data analyses tools

  3. Targets • Solar turbulent convection • Tachocline • Upper convective boundary layer • Supergranulation • Granulation and wave excitation • Wave propagation • Magnetoconvection

  4. Doppler Velocity Line-of-sight Magnetograms Vector Magnetograms Continuum Brightness HMI Science Analysis Plan HMI Data Processing Data Product Science Objective Tachocline Global Helioseismology Processing Internal rotation Ω(r,Θ) (0<r<R) Meridional Circulation Filtergrams Internal sound speed, cs(r,Θ) (0<r<R) Differential Rotation Near-Surface Shear Layer Full-disk velocity, v(r,Θ,Φ), And sound speed, cs(r,Θ,Φ), Maps (0-30Mm) Local Helioseismology Processing Activity Complexes Active Regions Carrington synoptic v and cs maps (0-30Mm) Sunspots Irradiance Variations High-resolution v and cs maps (0-30Mm) Observables Magnetic Shear Deep-focus v and cs maps (0-200Mm) Flare Magnetic Configuration Flux Emergence Far-side activity index Magnetic Carpet Line-of-Sight Magnetic Field Maps Coronal energetics Large-scale Coronal Fields Vector Magnetic Field Maps Solar Wind Coronal magnetic Field Extrapolations Far-side Activity Evolution Predicting A-R Emergence Coronal and Solar wind models IMF Bs Events Version 1.0w Brightness Images

  5. Approach • Large-scale 3D simulations: • Fully compressible MHD equations • Inelastic approximation • Realistic thermodynamics • Radiative energy transport • Data assimilation and Inverse Modeling

  6. Tools • Fully compressible MHD equations • Three-Dimensional code (TVD scheme) with realistic equation of state (S. Ustyugov) • High order finite difference LES code with MHD, real gas, radiation and subgrid scale models (A. Wray) • Initiated contact with R. Stein (MSU)

  7. Tools • Inelastic approximation • Slab geometry with SGS model (M. Kirkpatrick) • Initiated collaboration with Colorado Research Ass./UC Boulder/Stanford U./ARC Spherical Code+LES

  8. Resources • NASA Supercomputing facility: • SGI 1,024-processor Origin 3000 • SGI 512-processor Origin 3000 • SGI 256-processor Origin • 32-processor Cray SV1e • SGI and Sun workstations • 600 terabytes online/nearline data storage • Stanford SDO/HMI group

  9. SIMULATION Development plan • Compressible MHD: • Implement SGS and radiation models into the Stein/Nordland code • Data Assimilation • Name the Code and make it available as a Community code under CCMC (Community Coordinated Modeling Center)

  10. SIMULATION Development plan • Inelastic Code: • (ASH & HYPE) + SGS • Data Assimilation • Make codes available under CCMC

  11. Development plan • Using data to develop understanding/models • Inverse Modeling ? UiUj

  12. Collaborations • Sasha Kosovichev (SDO/HMI) [GURU] • Center for Turbulence Research • Alan Wray • Michael Rogers • Sergey Ustyugov • Robert Stein (MSU) • Colorado Research Ass.: • M. Miesch • J. Werne • T. Lund • K. Julien ( U. Colorado Boulder)

  13. Requirements • Support for the scientific teams: • CS under full cost accounting • University/Industry science • Support of High-End Computing by NASA: • Compute cycles • Formulate IT requirements: • Grid • Viz. tools • Analyses tools

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