CME propagation in the interplanetary medium - (A …jk/science/solaire09_KleimannJ.pdfCME...

CME propagation in the interplanetary medium(A review talk)

Jens Kleimann

Theoretische Physik IV,Ruhr-Universität Bochum, Germany

3rd SOLAIRE Network MeetingNovember 05, 2009 � Puerto de la Cruz, Tenerife

A CME’s life: It...gets born, [Initiation models: flux emergence, C. Jacobs]evolves, [Coronal development of CMEs, T. Török]and leaves home to see places. [ ↓ This talk ↓]

1 Motivation2 Observation / Statistics

TrajectoryArrival timesGeo-effectiveness

3 (MHD) Modellinganalyticalnumerical

4 Conclusions

A CME’s life: It...gets born, [Initiation models: flux emergence, C. Jacobs]evolves, [Coronal development of CMEs, T. Török]and leaves home to see places. [ ↓ This talk ↓]

1 Motivation2 Observation / Statistics


3 (MHD) Modellinganalyticalnumerical

4 Conclusions

MotivationObservation / Statistics

(MHD) ModellingConclusions

Why care about CMEs?Major manifestation of solar activity

M ≈ 1012...13 kg, W ≈ 1023...25 Jrate (1...6)/day, ∼10 % of which hit Earth!

CMEs relate to many other fields of Solar physicsflares↔ CMEsparticle acceleration at shocksglobal flux removal...

Commercial application: “space weather”safety concerns for astronautics,satellite communication failures, etc.

J. Kleimann CME propagation in the interplanetary medium


















S/C observations from:LASCO on SOHO (white-lightcoronagraph, 32R� FoV, since 1995)ACE, Wind (in-situ @ L1, since 1997)Helios 1/2 (in-situ @ 0.3 AU, 1974 – ’81)SMEI on Coriolis (white-light, all-sky,since 2003, r > 70R�)STEREO A/B (since 2007)anecdotal: ICME detection via H+

enhancement by Voyager 2 (@ 58 AU)& Ulysses [Paularena et al. 2001]

...





Main goals: Predict a CME’s...

1. trajectory, 2. arrival time (at Earth), 3. geo-effectiveness

1st order assumption: CMEs expand radially.⇒ Only "halo" CMEs will hit Earth. [Schwenn 2005]:

∼10% of events involved non-halo CMEs (missing alarms)∼10% of halo CMEs miss Earth (false alarms)

Eastward deflection due to Parker spiral?

slow fastCMEs go

East↙ ↘West(noticeably) (slightly)

[Wang et al. 2004]










slow fastCMEs go


[Wang et al. 2004]










slow fastCMEs go


[Wang et al. 2004]










slow fastCMEs go


[Wang et al. 2004]










slow fastCMEs go


[Wang et al. 2004]










slow fastCMEs go


[Wang et al. 2004]





CME tracking

STEREO’s dual view can be used to re-construct the 3-D trajectory via stereoscopy.(Well-posed problem for points and curves[Inhester 2006]).

Problems:CMEs are extended, partiallytranslucend objects⇒ tricky toidentify common features in images.S/C launched into "deep" solar min.⇒ only few events to study.

[Maloney et al., submitted]

Preliminary results indicate"quasi-radial" paths.





CME tracking









CME tracking









CME tracking



[Maloney et al., submitted]Preliminary results indicate"quasi-radial" paths.





Arrival times (@ 1AU)

Required data:1 initial speed (from coronagraphs, modulo projection)2 pos.(+) / neg.(−) acceleration a en route due to

thermal pressure (+), magnetic forces (±), gravity (−),aerodynamic drag (−), "snow plough-effect" (−)

For r < 32R� : linear height-time-fit ok. [St.Cyr et al. 2000](gradual CMEs: a > 0 out to ∼6 R� [Schwenn et al. 2006])

For r → 1 AU : empirical models for single CMEsProblem: direct CME data only available near Sun(coronagraphs) and Earth (in-situ spacecrafts)



















⇒ Need to bridge [∼ 0.2,1.0] AU interval.





Solution #1: Trace type II radio emissions from the CME’s upstreamshock, occurring at harmonic f = 9

√n/m−3 MHz

→ n at source region→ positionbut: stand-off distance not known (≤ 0.25 AU at Earth)

Solution #2: Identify CME–ICME pairs, use quadrature observations(1 coronagraph + 1 in-situ S/C over limb) to minimizeprojection effects.

��

��

Obs.1

Obs.2

Idea: Relate travel timeT to initial (v0) vs. final(ve) speed.





Solution #1: Trace type II radio emissions from the CME’s upstreamshock, occurring at harmonic f = 9

√n/m−3 MHz

→ n at source region→ positionbut: stand-off distance not known (≤ 0.25 AU at Earth)

Solution #2: Identify CME–ICME pairs, use quadrature observations(1 coronagraph + 1 in-situ S/C over limb) to minimizeprojection effects.

��

��

Obs.1

Obs.2

Idea: Relate travel timeT to initial (v0) vs. final(ve) speed.





Arrival time statistics (I)

Bruecker et al. [1998]: Tavg ∼ 80 h(not too bad, esp. at solar min)Lindsay et al. [1999]: linear fit ofve = ve(v0)⇒ v approaches vsw

Gopalswamy et al. [2001]:linear a = a(v0) fit to (v0,T ) datakinematic eq. v0T + aT 2/2 = Rs/c ,→ T = T (v0), ∆T ≈ 10 hbest match if a = 0 beyond 0.75 AU



















Arrival time statistics (II)

Schwenn et al. [2005]: Correlationvrad ↔ speed of lateral expansion(defineable w/o projection effects!)⇒ vrad ≈ 0.88 vexp

viscous drag for decel. to vsw = 0

⇒ Th

=

[203− 20.77 ln

(vexp

km/s

)]Cargill [2004]: "aerodynamic" draga(v) ∝ (v − vsw)2 → little difference.








⇒ Th

=

[203− 20.77 ln

(vexp

km/s









⇒ Th

=

[203− 20.77 ln

(vexp

km/s






In summary:

1 On average T ≈ 80 h2 v0 highly variable, vcme → vsw for r � R�3 empirical formulas T = T (v0) or T (vexp), but:4 large scatter due to oversimplifaction, CMEs and IP

medium both too variable/structured for simple fitting laws

"[We propose] that a number of CMEs be droppedfrom La Torre di Pisa and their drag force be directlymeasured."

Reiner et al. [2003]





In summary:

1 On average T ≈ 80 h2 v0 highly variable, vcme → vsw for r � R�3 empirical formulas T = T (v0) or T (vexp), but:4 large scatter due to oversimplifaction, CMEs and IP

medium both too variable/structured for simple fitting laws

"[We propose] that a number of CMEs be droppedfrom La Torre di Pisa and their drag force be directlymeasured."

Reiner et al. [2003]





Geo-effectiveness := ability to cause severe magnetic storms/energetic particle flux at Earth.

Bz < 0 favors interaction with Earth’s magnetosphere:

Bz,cme

{> 0 ⇒ mainly FL repulsion⇒ shielding effect< 0 ⇒ dayside reconnection⇒ particle influx

(plus magnetosphere compression by −∇pcme)Bcme may stem from

1 original flux rope field and/or2 draped/compressed IMF ahead of CME

Fast CMEs have stronger ‖B‖ (but not Bz).[Lindsay et al. 1999]







Bz,cme











Bz,cme











Bz,cme








analyticalnumerical

MagnetoHydroDynamics

preferred tool to model underlyingphysics, esp. with respect to non-linearv↔ B interaction.

Analytical works (few in number):

1 The Gibson & Low [1998] flux rope.time-dependent 3-D MHD config;assumes self-similar evolutionstructure of ρ(r) used to create syntheticwhite-light imagesalso used as init for simulations




analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical

Analytical models (cont’d)

2 Flux tube model to probe a CME’sinternal properties [Wang et al. ’09]

requires: self-similarity, J ‖ B, ∂ϕ = 0fixing coefficients c1...6 by[R,L](t) fit to obs. data gives Γcme(t)critical values:Γ ≥ 4/3 : (fem/fth) decreases with rΓ ≥ 2/3 : no more net acceleration




analyticalnumerical







analyticalnumerical







analyticalnumerical







analyticalnumerical

Space weather prediction relies on large-scale numerical MHD.

CSEM [Toth 2005] CISM [Odstrcil 2008]

Major (technical) challenge: High resolution requirements due to1 need to track features� R� across > 200 R�2 Lack of symmetrysolar min: B� is 2-D, but CME expansion ∦ dipolar axis

solar max: B� is 3-D itself




analyticalnumerical








analyticalnumerical








analyticalnumerical

Solution #1: Ignore ϕ dependence anyway.expansion along polar axis:interesting but somewhat unrealisticexpansion near ecliptic(implies torus-shaped "CME")2-D/3-D comparison [Jacobs et al. 2007]

Solution #2: Performance tuningspecially tailored grids, esp. sphericalwith radially varying ∆r = ∆r(r)

multi-scale models [e.g. Riley et al. ’06]

mesh refinement techniques[BATS-R-US, AMRVAC, ...]




analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical








analyticalnumerical

Two types of MHD models

"principal": "realistic":idealized settings, few controlparameters

init near real situation, usesas much physics as possible

Goal: assess importance ofinitial config/ physical effectsfor resulting development

Goal: reproduce (remote/ in-situ) data from actual events

1 Different initialisation methods (→ previous review talks)2 Different realisations of the background solar wind:

uniform [Vandas et al. 1998, 2002]

structured [Odstrcil & Pizzo 1999; Manchester et al. 2004]

realistic [Hayashi et al. 2006; Shen et al. 2007]




analyticalnumerical













analyticalnumerical













analyticalnumerical

3 Different physics, e.g. treatment of the energy budget:isothermaladiabatic, γ = γ0 ≤ 5/3

γ = γ(r) [e.g. Fahr et al. ’76, Lugaz et al. ’07]

complete energy equation with

a) ad-hoc heating [e.g. Hartle & Barnes ’70, Manchester ’04]

e.g. Q(r) = q(r) [T0 − γp/ρ] ⇒ T → T0 "target temp."b) consistent Alfvenic wave heating (and pressure) pw:

∂tε± +∇ · [(v± vA)ε±] = −ε±2∇ · v and pw =

ε+ + ε−2

or

∂tP +∇ · [. . .] = ... and pw = 12

∫ fhf0

P(f , r) df




analyticalnumerical






∂tε± +∇ · [(v± vA)ε±] = −ε±2∇ · v and pw =

ε+ + ε−2

or

∂tP +∇ · [. . .] = ... and pw = 12

∫ fhf0

P(f , r) df




analyticalnumerical






∂tε± +∇ · [(v± vA)ε±] = −ε±2∇ · v and pw =

ε+ + ε−2

or

∂tP +∇ · [. . .] = ... and pw = 12

∫ fhf0

P(f , r) df




analyticalnumerical






∂tε± +∇ · [(v± vA)ε±] = −ε±2∇ · v and pw =

ε+ + ε−2

or

∂tP +∇ · [. . .] = ... and pw = 12

∫ fhf0

P(f , r) df




analyticalnumerical

Findings from principal models (I)

Some indication of nearlyself-similar evolution[e.g. Kleimann et al. ’09]

→ cf. constancy of cone angle[Schwenn et al. 2005]

(relevant for analytical models, etc.)




analyticalnumerical








analyticalnumerical








analyticalnumerical

Findings from principal models (II)

CME evolution depends strongly on1 background SW (e.g. higher speeds in fast, dilute winds,

depends on physics included) [Jacobs et al. 2005] and2 initial topology:{

"Inverse""Normal"

}prom.s give

{fasterslower

}CMEs which deflect

{equatorward.

poleward.

}

[Chané et al. 2006], as predicted by Zhang & Low [2004]




analyticalnumerical

Findings from principal models (II)

CME evolution depends strongly on1 background SW (e.g. higher speeds in fast, dilute winds,

depends on physics included) [Jacobs et al. 2005] and2 initial topology:{

"Inverse""Normal"

}prom.s give

{fasterslower

}CMEs which deflect

{equatorward.

poleward.

}

[Chané et al. 2006], as predicted by Zhang & Low [2004]




analyticalnumerical

Further challenges:CMEs exhibit diverse structure:Sometimes three parts ("light bulb"[Hundhausen 1988]), but often not.10(!) different morphological classesacc. to Howard et al. [1985]Interaction/merging: About 2 of 3 CMEsare "complex ejecta" [Burlaga 2002]

Incomplete knowledge of IMF structure(accessible only via extrapolation ofnear-surface fields + in-situ data at singlepoints)




analyticalnumerical






analyticalnumerical






Conclusions

CMEs show a very diverse phenomenology, thereforepurely kinematic models have limited predictive power.Modelling results crucially depend on physical effectsincluded (e.g. wave heating).As numerical models become more sophisticated, theybenefit from input due to high-quality S/C observations.Nearly self-similar evolution of single(!) CMEs⇒ realistic modelling at small radii is essential!


(Thank you!)

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