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Toward Forecasting Space Weather Tamas Gombosi The University of Michigan Isradynamics 2010 Conference Ein Bokek (Dead Sea), Israel April 11-16, 2010

Toward Forecasting Space Weather

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Toward Forecasting Space Weather. Tamas Gombosi The University of Michigan Isradynamics 2010 Conference Ein Bokek (Dead Sea), Israel April 11-16, 2010. Space Weather. - PowerPoint PPT Presentation

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Page 1: Toward Forecasting Space Weather

Toward Forecasting Space Weather

Tamas GombosiThe University of Michigan

Isradynamics 2010 ConferenceEin Bokek (Dead Sea), Israel

April 11-16, 2010

Page 2: Toward Forecasting Space Weather

Space Weather

Space weather: conditions in geospace that can have adverse effects on space-borne and ground-based technological systems and can endanger human life or health.

(courtesy of Doug Biesecker, NOAA SWPC)

Page 3: Toward Forecasting Space Weather

Modeling the Space Weather System

Disparate time scalesDisparate spatial scales

Disparate physics……

☞ Model coupling is needed

Page 4: Toward Forecasting Space Weather

Coupled Space Weather Models

Space Weather Modeling Framework (SWMF)Centered at the University of MichiganEnables flexible Sun-to-Earth model chainSingle executable

Center for Integrated Space Weather Modeling (CISM) coupled model

Centered at Boston UniversityEnables Sun-to-Earth model chainMultiple executables

Integrated Magnetosphere-Ionosphere ModelCentered at the University of New HampshireCouples a global magnetosphere, an ionosphere-thermosphere, a radiation belt and a ring current modelSingle executable

Page 5: Toward Forecasting Space Weather

Freely available at http://csem.engin.umich.edu

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SWMF Capabilities: Physics

Fluid EquationsCompressible HDIdeal MHDSemi-relativistic MHDResistive MHDSingle-fluid Hall MHDTwo-fluid Hall MHDMulti-species (Hall) MHDMulti-fluid (Hall) MHDAnisotropic pressureHeat conduction

Additional PhysicsMultiple materialsNon-ideal EOSRadiation

Gray diffusionMultigroup diffusion

Source termsGravity, mass loading, chemistry, photo-ionization, recombination, etc…

Various resistivity modelsSemi-empirical coronal heatingAlfven wave energy transport and dissipationSelf-consistent turbulence

Page 7: Toward Forecasting Space Weather

SWMF Capabilities: Numerics

Time integration SchemesLocal time-stepping for steady stateExplicit (with Boris correction)Explicit/implicitSemi-implicitPoint-implicit

GridsBlock-adaptive treeCartesianGeneralized grids including spherical, cylindrical, toroidal

TVD SolversRoeHLLDHLLEArtificial-windRusanov

LimitersKoren (3rd order)MCBeta

Div(B) control8-waveHyperbolic/parabolic schemeProjectionStaggered grid (CT)

Ray tracingFast & parallel

Synthetic imagesWhite light coronagraphEUV LOS

171Å, 195Å, 284Å

X-ray radiographsTomography

Page 8: Toward Forecasting Space Weather

SWMF Capabilities: Framework

Source code:250,000 lines of Fortran in the currently used models34,000 lines of Fortran 90 in the core of the SWMF13,000 lines of Fortran 90 in the wrappers and couplers

User manual with example runs and full documentation of input parametersFully automated nightly testing on 9 different machine/compiler combinationsSWMF runs on any Unix/Linux based system with a Fortran 90 compiler, MPI library, and Perl interpreter

Page 9: Toward Forecasting Space Weather

Simulation and Tomography

2005 05 14 21:03 2005 05 15 21:05 2005 05 16 21:00 2005 05 17 21:05

2005 05 18 21:00 2005 05 19 21:05 2005 05 20 21:00 2005 05 21 0306

2005 05 21 21:05 2005 05 22 21:05 2005 05 23 21:00 2005 05 24 21:05

2005 05 25 21:00 2005 05 26 21:05 2005 05 27 21:00 2005 05 27 23:44

ne=106

ne=5x105

Frazin et al., 2008

Page 10: Toward Forecasting Space Weather

Thermodynamic Solar Wind Model(van der Holst, Oran and Sokolov)

Sub-photosphere modelMultigroup radiation transportMHDMagnetic flux emergence

Low corona (1R☉r<2.5 R☉)γ=5/3, single temperatureHeat conductionTransport and dissipation of total energy of Alfvénic turbulence (E±)

Wave dissipation represents sources for the plasma momentum and internal energyAdditional coronal heating is obtained from the “unsigned flux” model (Abbett 2007) and observed X-ray luminosity (Pevtsov 2003)

Corona (2.5R☉<r<20R☉)γ=5/3, separate ion and electron temperaturesTransport and dissipation of frequency resolved Alfvén wave intensity, I±(ω)

Kolmogorov spectrum is assumed at the inner boundary

Observational inputs:Magnetogram driven potential field extrapolation (synoptic maps from GONG or MDI)Density and temperatures near the sun are predicted by the DEMT (Differential Emission Measure Tomography) results of Vasquez and Frazin (2009).Solar X-ray luminosity (EIT, STEREO)

Page 11: Toward Forecasting Space Weather

Boundary Conditions for CR2077with no Free ParametersGONG magnetogram WSA relation

STEREO/EUVI Differential Emission Measure Tomography (Vasques & Frazin)

Page 12: Toward Forecasting Space Weather

CR2077: Two State Solar Wind

In the fast windElectrons are cold (due to adiabatic cooling)Ions are hot (due to Alfvén wave heating)

In the slow windElectrons are hot (due to heat conduction)Ions are cold (no Alfvén wave heating)

Radial velocity

Ion temperature Electron temperature

Page 13: Toward Forecasting Space Weather

New Low Corona Model EIT 171Å EIT 195Å EIT 284Å SXT AlMg

Old SC modelsynthesis

New LC modelsynthesis

Observation:Aug 27, 1997

CR1913

Downs et al., ApJ, 712, 1219, 2010

Page 14: Toward Forecasting Space Weather
Page 15: Toward Forecasting Space Weather

Halloween Storm Simulation: Early Phase

Page 16: Toward Forecasting Space Weather

Alfvénic Turbulence and SEP Acceleration

Recent Hinode observations imply that MHD turbulence might be the source that powers, accelerates and heats the solar windToday it is possible to use many dimensional models (>3D)We developed a coupled solar wind-turbulence-SEP model

Separate transport equation is solved for turbulenceWave stress tensor and energy appear in the solar wind momentum and energy equationsEnergetic particles are accelerated by interaction with turbulence

t=7m t=80m t=137m

Sokolov et al., 2009

Page 17: Toward Forecasting Space Weather

FTE Simulation (Kuznetsova)

Resolution at the dayside magnetoapuse is 1/16 RE (400 km)Total number of cells in the simulation is 20 millionSolar wind parameters:

n = 2 cm–3

T = 20,000 K Vx = 300 km/sB = 5 nTIMF Turning From Northward (θ = 0∘) to IMF clock angle θ < 120∘

Page 18: Toward Forecasting Space Weather

Theta = 120o

Pressure

Subsolar FTE Structure

Cluster

Page 19: Toward Forecasting Space Weather

View from South

Page 20: Toward Forecasting Space Weather

Component Reconnection Near Sub-Solar Region (Y ~ 0 – 2 RE)And Anti-Parallel Reconnection at Flanks (Y ~ 12 - 15 RE)

View from the Sun

Page 21: Toward Forecasting Space Weather

Z-slice

Y-slice

X-slice

FTE at flanks (Y = 12 Re) is connected to FTE at the subsolar region ( Y = 0 ).

Page 22: Toward Forecasting Space Weather