Heliospheric MHD Models (for the LWS Community)

1. Heliospheric MHD Models(for the LWS Community) Dusan Odstrcil1,2 and Vic Pizzo2 1University of Colorado/CIRES, 2NOAA/Space Environment Center LWS Workshop, Boulder, CO, March 23-26, 2004

2. Outline • A.Heliospheric modeling • B. Access to existing data sets • C. Access to existing modeling system • D. May 12, 1997 Interplanetary Event • Conclusions

3. A. Heliospheric Modeling

4. Need for Heliospheric Simulations • Very little of the inner heliosphere can be directly sampled - many phenomena are of global scale; cannot be well understood by observations at a point or in a plane • Similar coronal ejecta may appear differently in the heliosphere due to their interactions with background solar wind or with other transient disturbances • Models are absolutely necessary for interpreting the available observations • Models will play a key role in space weather applications

5. Solar Wind Parameters Large variations in plasma parameters between the Sun and Earth Different regions involve different processes and phenomena We distinguish between the coronal and heliospheric regions with an interface located in the super-critical flow region (usually 18-30 Rs)

6. ENLIL – 3-D Solar Wind Model • Mathematical Description: - ideal magnetohydrodynamic (MHD) approximation - additional equations for injected mass and polarity tracking • Method of Solution: - explicit finite-difference scheme - modified Lax-Friedrichs Total-Variation-Diminishing algorithm - parallelization by domain-decomposition • Inputs: - Analytical, empirical, or numerical coronal models - NetCDF file format • Outputs: - Distribution at specified time levels - Temporal evolution at specified positions - NetCDF file format

7. Currently Supported Input Data • Analytic Models: - structured solar wind (bi-modal, tilted) - over-pressured plasma cloud (3-D) - magnetic flux-rope (3-D in progress) • Empirical Models: - WSA source surface - SAIC source surface - CME cone model (location, diameter, and speed) • Numerical Models: - SAIC coronal model (ambient + transient outflow)

8. Heliospheric Simulations • Using Available Data Sets: Visualize, analyze, and utilize a large collection of data sets obtained during representative periods and events • Using Available Modeling System: Prepare input data using existing initialization procedures and data sets, and configure the existing numerical model • Writing New Initialization Procedures: Develop new initialization procedures to produce input data for the code, incorporate them into the ENKI portal, and run the existing numerical model • Writing New Computational Procedures: Develop new computational procedures, incorporate them into the ENLIL model as well as the ENKI portal, and use the existing initialization system to run the modified code

9. B. Access to Available Data Sets

10. Community Data Portal (CDP) –Storage Resources Broker (SRB)

11. Community Data Portal • The Community Data Portal (CDP) is a collection of earth science datasets from NCAR, UCAR, UOP, and participating organizations A central gateway to the large and diversified datasets in the following research areas: • oceanic • atmospheric • space weather • turbulence Web-based portal with the following functionality: • data search • metadata browsing • data download • analysis and visualization NCAR/SCD project supported by NSF/Cyberinfrastructure Strategic Initiative

12. Community Data Portal – Main Interface [ http://dataportal.ucar.edu ]

13. Community Data Portal – Data Sets • Representative 3-D interactions in structured wind (hypothetic scenarios) • Ambient solar wind for selected Carrington rotations (empirical models) • Transient heliospheric disturbances for selected event (MURI, CISM, SHINE) driven by empirical models) • Interplanetary consequences of coronal magnetic eruptions (coupled coronal and heliospheric numerical models)

14. Example – Providing a Global Context • Development of tools for utilizing multi-point in-situ observations • Analysis of various in-situ observations for selected (computed) events

15. Example – Providing 3-D Density ICME Stereo-A Earth Stereo-B • Development of tools for utilizing multi-point remote observations • Analysis of various remote observations for selected (computed) events

16. C. Access to Existing Modeling System

17. ENKI – Interface to ENLIL • Client-Based Approach: - runs locally - remote access via ssh and scp • Input Data: - initial and/or boundary values - run and batch parameters • Numerical Model: - parameters for CPP preprocessor - array dimensions • Visualization: - interactive preview - standardized views • Data Management: - update source files - transfer input/output files • Project Management: - project review, report, and archiving

18. ENKI – Interface to ENLIL

19. ENKI – Interface to ENLIL

20. ENKI – Interface to ENLIL

21. Remote Visualization: ENKI-IDL • Preview of data before downloading processing and visualization, archiving, etc. • Plot 1-D profiles and 2-D contours or surfaces of 1-D, 2-D, or 3-D data

22. D. May 12, 1997 Interplanetary Event

23. Global Solar and Coronal Observations Remote solar observations of the photospheric magnetic field Remote coronal observations of the white-light scattered on density structures

24. Ambient Solar Wind Models SAIC 3-D MHD steady state coronal model based on photospheric field maps CU/CIRES-NOAA/SEC 3-D solar wind model based on potential and current-sheet source surface empirical models

25. May 12, 1997 Halo CME Running difference images fitted by the cone model

26. CME Cone Model Best fitting for May 12, 1997 halo CME • latitude: N3.0 • longitude: W1.0 • angular width: 50 deg • velocity:650 km/s at 24 Rs (14:15 UT) • acceleration: 18.5 m/s2 [ Zhao et al., 2001 ]

27. Boundary Conditions Ambient Solar Wind + Plasma Cloud Ambient Solar Wind

28. Latitudinal Distortion of ICME Shape ICME propagates into bi-modal solar wind

29. Radial Compression of ICME Structure Fast stream follows the ICME

30. Evolution of Density Structure ICME propagates into the enhanced density of a streamer belt flow

31. Early time Later time Propagation of Energetic Particles IMF line connected to Earth by-passes the shock structure => Interplanetary CME-driven shock cannot generate energetic particles observed at Earth IMF line connected to Earth passes through the shock structure => Quasi-perpendicular shock can generate energetic particles under certain circumstances

32. Global view Detailed view Energetic Particles & Radio Emission Important effect occurs away from the Sun-Earth line Enhanced shock interaction together with quasi-perpendicular propagation relative to IMF lines favors particle acceleration and generation of radio emission

33. Evolution of Parameters at Earth

34. May 12, 1997 – Interplanetary Shock Distribution of parameters in equatorial plane Evolution of velocity on Sun-Earth line 0.2 AU 0.4 AU 0.6 AU 0.8 AU • Shock propagates in a fast stream and • merges with its leading edge 1.0 AU

35. Case A1 Case A3 [ SAIC maps -- Pete Riley ] Fast-Stream Position Ambient state before the CME launch Disturbed state during the CME launch Ambient state after the CME launch

36. Effect of Fast-Stream Position Case A1 Case A3 Earth : Interaction region followed by shock and CME (not observed) Earth : Shock and CME (observed but 3-day shift is too large)

37. Case A2 Case B2 [ SAIC maps -- Pete Riley ] Fast-Stream Evolution Ambient state before the CME launch Disturbed state during the CME launch Ambient state after the CME launch

38. Effect of Fast-Stream Evolution Case A2 Case B2 Earth : Interaction region followed by shock and CME (not observed) Earth : Shock and CME (observed but shock front is radial)

39. Conclusions – 1 of 2 • It becomes possible to: - simulate ambient solar wind parameters - estimate arrival of shock and ejecta - provide a global context • It is not possible to: - reproduce detail locations of stream boundaries - reproduce an internal magnetic structure of ICMEs

40. Conclusions – 2 of 2 • Key areas needing development: - consensus on what mechanisms lead to and launch CME - how to characterize the inputs given the sparse nature of the observations - improved treatment of reconnection - self-consistent (or at least much improved) inclusion of energetic particles on global scale - framework for modeling, visualization, and analysis