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First Results from the 3D MHD Heliospheric Simulations Driven by the SMEI/IPS Observations

Learn how heliospheric simulations improve solar wind modeling accuracy for space weather research. Dive into the ENLIL 3-D Solar Wind Model description, method of solution, and model utilization with IPS and SMEI observations.

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First Results from the 3D MHD Heliospheric Simulations Driven by the SMEI/IPS Observations

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  1. First Results from the 3D MHD Heliospheric Simulations Driven by the SMEI/IPS Observations D. Odstrcil1,2, V.J. Pizzo2, C.N. Arge3, B.V.Jackson4, P.P. Hick4 1University of Colorado/CIRES 2NOAA/Space Environment Center 3Air Force Research Laboratory/VSBXS 4University of California at San Diego/CASS SPIE Meeting, San Diego, CA, July 31 – August 4, 2005

  2. Need for Heliospheric Simulations Numerical modeling plays a critical role in our effort to understand the connection between solar eruptive phenomena and their impacts in the near-Earth space environment and in interplanetary space: • 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 remote and in-situ observations. • Models will play a key role in space weather research and forecasting.

  3. 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 formulas, empirical or numerical coronal models, observed values - portable, self-documenting NetCDF file format • Outputs: - distribution at specified time levels - temporal evolution at specified positions - portable, self-documenting NetCDF file format

  4. Solar wind simulations can be driven by coronal models (either empirical potential or numerical MHD) using observed photospheric magnetic field. An example below uses the Wang-Sheeley-Arge model and shows: • Latitudinal distribution of the outflow velocity at 21.5 Rs (top panel). • Predicted evolution at Earth (solid line) together with actually observed values(dots) by Wind spacecraft (bottom panel). Ambient Solar Wind

  5. The heliospheric tomography model developed at UCSD provides reconstruction of the solar wind density and velocity structure out to 3 AU using data from ground-based interplanetary scintillation (IPS) observations provided by Stelab at Nagoya University, Japan (Jackson et al., 1998; Kojima et al., 1998). • This model can be linked with the heliospheric model in two ways: (1) Forward modeling – output from the tomography model is used to drive the heliospheric model. (2) Tomography modeling – the heliospheric model is used iteratively within the tomography model. Utilization of IPS and SMEI Observations Visualization of the solar wind density structure reconstructed by the heliospheric tomography model.

  6. Photospheric Observations IPS/SMEI Observations Forward Heliospheric Modeling Coronal Model Tomography Model Interplanetary Magnetic Field Solar Wind Density and Velocity Time-Dependent Boundary Conditions Heliospheric Model

  7. Boundary Conditions from Coronal Model Velocity distribution at the inner boundary and equatorial plane

  8. Boundary Conditions from Tomography Model • Distribution of solar wind density (left) and velocity (right) at 35 Rs as extracted from the heliospheric tomography model. • Black areas show missing values and white areas showvalues out of range. • Temperature is derived by assuming total pressure balance and is scaled to provide typical values observed at 1 AU.

  9. Evolution of Solar Wind Speed – 1 & 2

  10. Evolution of Solar Wind Speed – 3 & 4

  11. Evolution of Solar Wind Speed – 5 & 6

  12. Evolution of Solar Wind Speed – 7 & 8

  13. Distribution of Solar Wind Density – 6

  14. Distribution of Solar Wind Speed – 6

  15. We have used the reconstructed solar wind density and velocity at 35 Rs provided by the tomography model to drive the heliospheric MHD model. Fast stream flows (evolving and co-rotating) observed in May/June 2003 were used to initiate the MHD model. • Evolution of the global solar wind structure has been simulated in the inner heliosphere. The results are similar to those provided by the tomography reconstruction code utilizing a kinematic solar wind model. Differences are mostly at the co-rotating interaction region, which is more radially extended in the MHD simulations. • The tomography model will improve accuracy of the heliospheric MHD model by providing time-dependent conditions at the inner boundary and by data assimilation within the computational region. However, better interpolation techniques are needed to account for data that are missing or out of scale. Conclusions – 1

  16. The heliospheric MHD model will be incorporated into the tomography model to improve the accuracy of reconstructed solar wind parameters, in particular through better simulation of: (1) dynamic interaction of co-rotating streams; (2) formation of interplanetary shocks; and (3) interplanetary magnetic field evolution. • Using the kinematic model for iterative tomography reconstruction is much faster, but the heliospheric MHD model accounts for 3-D dynamic interactions and interplanetary magnetic field evolution. The kinematic model may provide initial conditions for the heliospheric MHD model to speed-up its convergence. • Both the tomography reconstruction and heliospheric MHD model will be delivered to the Community Coordinated Modeling Center (CCMC) at NASA/GSFC. Conclusions – 2

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