D. Odstrcil1,2, V.J. Pizzo2, C.N. Arge3, B.V.Jackson4, P.P. Hick4

Slides:

Advertisements

Similar presentations

K. Fujiki, H. Ito, M. Tokumaru Solar-Terrestrial Environment Laboratory (STELab), Nagoya University. SOLAR WIND FORECAST BY USING INTERPLANETARY SCINTILLATION.

Advertisements

The Solar Wind and Heliosphere (with a space weather emphasis!) V J Pizzo (NOAA/SEC)

Heliospheric Computations Dusan Odstrcil University of Colorado/CIRES and NOAA/Space Environment Center Solar MURI Team Meeting, Berkeley CA, December.

Global Properties of Heliospheric Disturbances Observed by Interplanetary Scintillation M. Tokumaru, M. Kojima, K. Fujiki, and M. Yamashita (Solar-Terrestrial.

Reviewing the Summer School Solar Labs Nicholas Gross.

Spatial distribution of the auroral precipitation zones during storms connected with magnetic clouds O.I. Yagodkina 1, I.V. Despirak 1, V. Guineva 2 1.

1 Diagnostics of Solar Wind Processes Using the Total Perpendicular Pressure Lan Jian, C. T. Russell, and J. T. Gosling How does the magnetic structure.

Heliospheric MHD Models (for the LWS Community) LWS Workshop, Boulder, CO, March 23-26, 2004 Dusan Odstrcil 1,2 and Vic Pizzo 2 1 University of Colorado/CIRES,

Heliospheric MHD Modeling of the May 12, 1997 Event MURI Meeting, UCB/SSL, Berkeley, CA, March 1-3, 2004 Dusan Odstrcil University of Colorado/CIRES &

Understanding Magnetic Eruptions on the Sun and their Interplanetary Consequences A Solar and Heliospheric Research grant funded by the DoD MURI program.

Tucson MURI SEP Workshop March 2003 Janet Luhmann and the Solar CISM Modeling Team Solar and Interplanetary Modeling.

Understanding Magnetic Eruptions on the Sun and their Interplanetary Consequences A Solar and Heliospheric Research grant funded by the DoD MURI program.

C. May 12, 1997 Interplanetary Event. Ambient Solar Wind Models SAIC 3-D MHD steady state coronal model based on photospheric field maps CU/CIRES-NOAA/SEC.

CISM solar wind metrics M.J. Owens and the CISM Validation and Metrics Team Boston University, Boston MA Abstract. The Center for Space-Weather Modeling.

When will disruptive CMEs impact Earth? Coronagraph observations alone aren’t enough to make the forecast for the most geoeffective halo CMEs. In 2002,

Merging of coronal and heliospheric numerical two-dimensional MHD models D. Odstrcil, et al., J. Geophys. Res., 107, 年 10 月 14 日太陽雑誌会 ( 速報.

Identifying Interplanetary Shock Parameters in Heliospheric MHD Simulation Results S. A. Ledvina 1, D. Odstrcil 2 and J. G. Luhmann 1 1.Space Sciences.

Ambient Solar Wind Simulation of ambient solar wind driven by modified daily-updated WSA model:  Latitudinal distribution of the outflow velocity at 21.5.

C. May 12, 1997 Interplanetary Event. May 12, 1997 Interplanetary Coronal Mass Ejection Event CU/CIRES, NOAA/SEC, SAIC, Stanford Tatranska Lomnica, Slovakia,

Coronal and Heliospheric Modeling of the May 12, 1997 MURI Event MURI Project Review, NASA/GSFC, MD, August 5-6, 2003 Dusan Odstrcil University of Colorado/CIRES.

The “cone model” was originally developed by Zhao et al. ~10 (?) years ago in order to interpret the times of arrival of ICME ejecta following SOHO LASCO.

UCB MURI Team Introduction An overview of ongoing work to understand a well observed, eruptive active region, along with closely related studies…..

MHD Modeling of the Large Scale Solar Corona & Progress Toward Coupling with the Heliospheric Model.

Predictions of Solar Wind Speed and IMF Polarity Using Near-Real-Time Solar Magnetic Field Updates C. “Nick” Arge University of Colorado/CIRES & NOAA/SEC.

RT Modelling of CMEs Using WSA- ENLIL Cone Model

What coronal parameters determine solar wind speed? M. Kojima, M. Tokumaru, K. Fujiki, H. Itoh and T. Murakami Solar-Terrestrial Environment Laboratory,

Numerical simulations are used to explore the interaction between solar coronal mass ejections (CMEs) and the structured, ambient global solar wind flow.

Evolution of the 2012 July 12 CME from the Sun to the Earth: Data- Constrained Three-Dimensional MHD Simulations F. Shen 1, C. Shen 2, J. Zhang 3, P. Hess.

Comparison of the 3D MHD Solar Wind Model Results with ACE Data 2007 SHINE Student Day Whistler, B. C., Canada C. O. Lee*, J. G. Luhmann, D. Odstrcil,

The Solar Wind.

AFRL/CISM Collaborations

Conclusions Using the Diffusive Equilibrium Mapping Technique we have connected a starting point of a field line on the photosphere with its final location.

1 University of California, San Diego, U.S.A., 2 NASA - Goddard Space Flight Center, U.S.A., 3 George Mason University, U.S.A., 4 Naval Research Laboratory,

Synoptic Network Workshop (HAO/NCAR, April 2013) Space Weather and Synoptic Observations V J Pizzo – NOAA/SWPC.

Measurements of White-Light Images of Cometary Plasma as a Proxy for Solar Wind Speed J.M. Clover, M.M. Bisi, A. Buffington, B.V. Jackson, P.P. Hick Center.

Modeling 3-D Solar Wind Structure Lecture 13. Why is a Heliospheric Model Needed? Space weather forecasts require us to know the solar wind that is interacting.

1 Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

1 Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

1 Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

1 Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

Heliospheric Simulations of the SHINE Campaign Events SHINE Workshop, Big Sky, MT, June 27 – July 2, 2004 Dusan Odstrcil 1,2 1 University of Colorado/CIRES,

1 Center for Astrophysics and Space Sciences, University of California, San Diego 9500 Gilman Drive #0424, La Jolla, CA , U.S.A

State of NOAA-SEC/CIRES STEREO Heliospheric Models STEREO SWG Meeting, NOAA/SEC, Boulder, CO, March 22, 2004 Dusan Odstrcil University of Colorado/CIRES.

1 Test Particle Simulations of Solar Energetic Particle Propagation for Space Weather Mike Marsh, S. Dalla, J. Kelly & T. Laitinen University of Central.

1 Pruning of Ensemble CME modeling using Interplanetary Scintillation and Heliospheric Imager Observations A. Taktakishvili, M. L. Mays, L. Rastaetter,

1 CASS, University of California, San Diego, U.S.A. ; 2 STFC Rutherford Appleton Laboratory, UK; 3 George Mason University, U.S.A.; 4 NASA/GSFC,

IPS tomography IPS-MHD tomography. Since Hewish et al. reported the discovery of the interplanetary scintillation (IPS) phenomena in 1964, the IPS method.

A 3D-MHD Model Interface Using Interplanetary Scintillation (IPS) Observations B.V. Jackson 1, H.-S. Yu 1, P.P. Hick 1, A. Buffington 1, D. Odstrcil 2,

Manuela Temmer Institute of Physics, University of Graz, Austria Tutorial: Coronal holes and space weather consequences.

Solar System Physics Group Heliospheric physics with LOFAR Andy Breen, Richard Fallows Solar System Physics Group Aberystwyth University Mario Bisi Center.

H.-S. Yu 1, B.V. Jackson 1, P.P. Hick 1, A. Buffington 1, M. M. Bisi 2, D. Odstrcil 3,4, M. Tokumaru 5 1 CASS, UCSD, USA ; 2 STFC RALab, Harwell Oxford,

B.V. Jackson H.-S. Yu, P.P. Hick, A. Buffington,

B.V. Jackson, H.-S. Yu, P.P. Hick, and A. Buffington,

Driving 3D-MHD codes Using the UCSD Tomography

H.-S. Yu1, B.V. Jackson1, P.P. Hick1,

Determination of the North-South Heliospheric Magnetic Field from Inner-Corona Closed-Loop Propagation B.V. Jackson Center for Astrophysics and Space Sciences,

Y. C.-M. Liu, M. Opher, O. Cohen P.C.Liewer and T.I.Gombosi

Comparison of the 3D MHD Solar Wind Model Results with ACE Data 2007 SHINE Student Day Whistler, B. C., Canada C. O. Lee*, J. G. Luhmann, D. Odstrcil,

2014SWW - S9 3D Reconstruction of IPS Remote-sensing Data: Global Solar Wind Boundaries for Driving 3D-MHD Models Hsiu-Shan Yu1, B.V. Jackson1, P.P. Hick1,

ST23-D2-PM2-P-013 The UCSD Kinematic Global Solar Wind Boundary for use in ENLIL 3D-MHD Forecasting Bernard JACKSON1#+, Hsiu-Shan YU1, Paul HICK1, Andrew.

Introduction to Space Weather Interplanetary Transients

IPS Heliospheric Analyses (STELab)

Exploration of Solar Magnetic Fields from Propagating GONG Magnetograms Using the CSSS Model and UCSD Time-Dependent Tomography H.-S. Yu1, B. V. Jackson1,

B.V. Jackson H.-S. Yu, P.P. Hick, A. Buffington, M. Tokumaru

Solar Wind Transients and SEPs

Lecture 5 The Formation and Evolution of CIRS

Abstract We simulate the twisting of an initially potential coronal flux tube by photospheric vortex motions. The flux tube starts to evolve slowly(quasi-statically)

ESS 261 Topics in magnetospheric physics Space weather forecast models ____ the prediction of solar wind speed April 23, 2008.

Introduction to Space Weather

Presentation transcript:

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

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.

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

Ambient Solar Wind 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).

Utilization of IPS and SMEI Observations 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. Visualization of the solar wind density structure reconstructed by the heliospheric tomography model.

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

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

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 show values out of range. Temperature is derived by assuming total pressure balance and is scaled to provide typical values observed at 1 AU.

Evolution of Solar Wind Speed – 1 & 2

Evolution of Solar Wind Speed – 3 & 4

Evolution of Solar Wind Speed – 5 & 6

Evolution of Solar Wind Speed – 7 & 8

Distribution of Solar Wind Density – 6

Distribution of Solar Wind Speed – 6

Conclusions – 1 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 – 2 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.