Heliospheric MHD Models(for the LWS Community)

LWS Workshop, Boulder, CO, March 23-26, 2004

Dusan Odstrcil1,2 and Vic Pizzo2

1University of Colorado/CIRES, 2NOAA/Space Environment Center

Outline

• A. Heliospheric modeling

• B. Access to existing data sets

• C. Access to existing modeling system

• D. May 12, 1997 Interplanetary Event

• Conclusions

A. Heliospheric Modeling

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

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)

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

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)

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

B. Access to Available Data Sets

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

CDP SRB

NCAR, Unidata NSF, UCSD, General Atomic

NCAR systems Multi-platform

NetCDF Multi-format

Web-based Installation needed

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

Community Data Portal – Main Interface

[ http://dataportal.ucar.edu ]

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)

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

Example – Providing 3-D Density

Development of tools for utilizing multi-point remote observations Analysis of various remote observations for selected (computed) events

ICME

Earth

Stereo-A

Stereo-B

C. Access to Existing Modeling System

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

ENKI – Interface to ENLIL

ENKI – Interface to ENLIL

ENKI – Interface to ENLIL

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

D. May 12, 1997 Interplanetary Event

Global Solar and Coronal Observations

Remote solar observations of the photospheric magnetic field Remote coronal observations of

the white-light scattered on density structures

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

May 12, 1997 Halo CME

Running difference images fitted by the cone model

CME Cone Model

[ Zhao et al., 2001 ]

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

Boundary Conditions

Ambient Solar WindAmbient Solar Wind

+ Plasma Cloud

Latitudinal Distortion of ICME Shape

ICME propagates into bi-modal solar wind

Radial Compression of ICME Structure

Fast stream follows the ICME

Evolution of Density Structure

ICME propagates into the enhanced density of a streamer belt flow

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

Early time Later time

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

Global view Detailed view

Evolution of Parameters at Earth

May 12, 1997 – Interplanetary Shock

• Shock propagates in a fast stream and

merges with its leading edge

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

1.0 AU

Fast-Stream Position

Ambient state before the CME launch

Disturbed state during the CME launch

Ambient state after the CME launch

Case A1 Case A3

[ SAIC maps -- Pete Riley ]

Effect of Fast-Stream Position

Case A1 Case A3

Earth : Interaction region followed by shock and CME (not observed)

Earth : Shock and CME (observedbut 3-day shift is too large)

Fast-Stream Evolution

Ambient state before the CME launch

Disturbed state during the CME launch

Ambient state after the CME launch

Case A2 Case B2

[ SAIC maps -- Pete Riley ]

Effect of Fast-Stream Evolution

Case A2 Case B2

Earth : Interaction region followed by shock and CME (not observed)

Earth : Shock and CME (observedbut shock front is radial)

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

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