Modelling Solar Activity for Space Weather

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Modelling Solar Activity for Space Weather Thierry Dudok de Wit (LPCE, CNRS and University of Orléans) special thanks to T. Amari, V. Carbone, R. Lallement, H. Lundstedt, T.

1 Modelling Solar Activity for Space Weather Thierry Dudok de Wit (LPCE, CNRS and University of Orléans) special thanks to T. Amari, V. Carbone, R. Lallement, H. Lundstedt, T. Woods Space Weather Week - ESTEC 1/12/04 - TDdW 1 Outline What types of models? Some examples coronal mass ejections flares Solar energetic particles EUV flux Future needs Focus will be on space weather applications (up to the corona) Two recent reviews : H. Koskinen and T. Pulkkinen, SPEE report, ESA (1998) C. Lathuillère et al., Ann. Geo. 20 (2002) Space Weather Week - ESTEC 1/12/04 - TDdW 2

Present status Our present understanding of solar physics (Parker, 1997) «Several islands of established theory, bridged with plausible conjectures and separated by more than one abyss of total

2 Present status Our present understanding of solar physics (Parker, 1997) «Several islands of established theory, bridged with plausible conjectures and separated by more than one abyss of total ignorance» but But wo do not need to understand everything in order to serve space weather objectives (analogy with terrestrial weather) Space Weather Week - ESTEC 1/12/04 - TDdW 3 Modelling the Sun The ultimate model of the Sun should start from the solar dynamo The solar interior is remarkably well known But this is (presently) of little interest for space weather applications Space Weather Week - ESTEC 1/12/04 - TDdW 4

3 Where can solar models contribute? Solar models mainly serve three objectives Space weather 1) forecast/nowcast geoeffective events 2) interpolate sparsely spaced observations 3) provide a better physical understanding of the Sun Solar Physics Priorities for solar physics and for space weather are not the same Space Weather Week - ESTEC 1/12/04 - TDdW 5 Solar vs other models Models that are of interest for space weather applications Space Weather Week - ESTEC 1/12/04 - TDdW 6

Key issues where models can contribute Flares & Active regions understand the solar dynamo and the dynamics of magnetic energy buildup in the corona find precursors to solar activity : active region

4 Key issues where models can contribute Flares & Active regions understand the solar dynamo and the dynamics of magnetic energy buildup in the corona find precursors to solar activity : active region development and long-term evolution Coronal Mass Ejections when and how are they initiated determine their geoeffectiveness : determine coronal magnetic field as boundary conditions to the solar wind Solar Energetic Particle Events when and how are they initiated Solar electromagnetic radiation (radio, UV, EUV, X-ray) predict variability Space Weather Week - ESTEC 1/12/04 - TDdW 7 Three types of models Physics-based models (MHD + others) often computationally expensive (no real-time) close to the physics, good for understanding Empirical models tailored to specific needs can be fast and simple Statistical models require large databases (= many observations) to be meaningful useful for risk assessment Space Weather Week - ESTEC 1/12/04 - TDdW 8

Physics-based models of the solar magnetic field (equilibrium, MHD) Space Weather Week - ESTEC 1/12/04 - TDdW 9 Physics-based models Objective : Extrapolate the coronal magnetic field (presently not

5 Physics-based models of the solar magnetic field (equilibrium, MHD) Space Weather Week - ESTEC 1/12/04 - TDdW 9 Physics-based models Objective : Extrapolate the coronal magnetic field (presently not measured) from photospheric observations (Kitt Peak, SoHO/MDI, Themis,...) describe the onset of flares / CMEs Outputs coronal magnetic field (reconnection, energetics,...) various physical parameters : X-ray/UV emission, particle acceleration,... Space Weather Week - ESTEC 1/12/04 - TDdW 10

Types of models Two types of models : static : reconstruct equilibrium at a given time

expensive (hours) Space Weather Week - ESTEC 1/12/04 - TDdW 11 Different approximations

variable scalar minutes hours potential model force-free model nonlin.

6 Types of models Two types of models : static : reconstruct equilibrium at a given time relatively fast (minutes) dynamic : reconstruction of the time evolution computationally expensive (hours) Space Weather Week - ESTEC 1/12/04 - TDdW 11 Different approximations Three levels of approximations potential force-free MHD linear non-linear! constant scalar! variable scalar minutes hours potential model force-free model nonlin. force-free model reconstruction of active region 8151 (Amari et al.,1999) Space Weather Week - ESTEC 1/12/04 - TDdW 12

Field extrapolation Extrapolation of the photospheric magnetic field towards the

(2003) : use computed coronal magnetic field to predict polarisation brightness of

4th, 2002 Space Weather Week - ESTEC 1/12/04 - TDdW 13 Field extrapolation Example :

7 Field extrapolation Extrapolation of the photospheric magnetic field towards the corona is routinely done using static potential field models Mikic et al. (2003) : use computed coronal magnetic field to predict polarisation brightness of solar eclipse on Dec. 4th, 2002 Space Weather Week - ESTEC 1/12/04 - TDdW 13 Field extrapolation Example : nowcast of the coronal magnetic field Permanently updated coronal magnetic field - PFSS model C.J. Schrijver Space Weather Week - ESTEC 1/12/04 - TDdW 14

What MHD models can teach us Mature models can provide better insight by

Pre-eruption sigmoid and posteruption arcade (Yohkoh) Space Weather Week -

sigmoids Example nonlinear force-free model computation of ohmic heating (proxy

8 What MHD models can teach us Mature models can provide better insight by filling observational gaps Example : origin and formation of sigmoids Pre-eruption sigmoid and posteruption arcade (Yohkoh) Space Weather Week - ESTEC 1/12/04 - TDdW 15 Sigmoids Several models have been used to investigate sigmoids Example nonlinear force-free model computation of ohmic heating (proxy for observed Soft X-ray emission) (Aulanier et al., 2002) Space Weather Week - ESTEC 1/12/04 - TDdW 16

9 t = 0 s Sigmoid appears with a shear opposite to that of the braided flux tube t = 630 s t = 840 s t = 1020 s Conclusion : models can help where observations are ambiguous Space Weather Week - ESTEC 1/12/04 - TDdW 17 Flares Coronal Mass Ejections Space Weather Week - ESTEC 1/12/04 - TDdW 18

10 CMEs : can they be predicted? Is there a robust precursor for the onset of a CME? Ejection with twisting or shearing of bipolar field on magnetic arcade! the complexity of the field topology makes prediction very difficult. Three possible approaches : detailed physical modelling of the region :! presently beyond reach statistical approach : use information about the field structure + a database of past CMEs to determine probability of occurrence empirical approach based on various criteria for the onset! a few attempts with limited success so far Space Weather Week - ESTEC 1/12/04 - TDdW 19 A criterion for the onset of CMEs Wavelet analysis of SoHO/MDI mean field data reveals a low frequency component one hour before the occurrence of a CME Wavelet scalogram with CME (averaged over 53 events) onset of CME Wavelet scalogram without CME (averaged over 23 events) Boberg et al., JGR 107, 2002 Space Weather Week - ESTEC 1/12/04 - TDdW 20

11 Flares : can they be predicted? The situation is very much the same as for CMEs Space Weather Week - ESTEC 1/12/04 - TDdW 21 An empirical flare prediction criterion Example : the topology (helicity) of the photospheric magnetic field changes shortly before the flare erupts. fractal dimension D increases shortly before flare erupts fractal dimension D X-ray flux Sorriso-Valvo et al., PSS 52, 2004 Space Weather Week - ESTEC 1/12/04 - TDdW 22

12 Solar Energetic Particle Events (SEPE) Space Weather Week - ESTEC 1/12/04 - TDdW 23 Solar Energetic Particle Events SEPE are an important hazard for manned space flights! short-term prediction (minutes) satellite components! long-term prediction (years) from a physical point of view, SEPEs are closely related to CMEs and shocks! physical modelling is extremely difficult Space Weather Week - ESTEC 1/12/04 - TDdW 24

13 Solar Energetic Particle Events There are two classes of models statistical models that provide confidence intervals! long-term prediction of fluence Examples (all available through SPENVIS) King [1974] model, made available through NSSDC JPL-91 Model (Feynman et al, 1993) used for mission planning ESP model (Xapsos et al., 2000) artificial intelligence is being tested to predict SEPE during long-duration flares! short-term prediction of fluence (>60% success for a 24hr prediction) Space Weather Week - ESTEC 1/12/04 - TDdW 25 Solar Energetic Particle Events Typical outputs of statistical models are the proton fluence spectrum compound probability of exceeding a specified fluence f of protons with energy greater than E during a mission lasting t years proton fluence spectrum for satellite in GPS orbit, 2003 (SPENVIS - ESP model) Space Weather Week - ESTEC 1/12/04 - TDdW 26

14 radio / UV / EUV / X-ray spectrum Space Weather Week - ESTEC 1/12/04 - TDdW 27 Solar EUV flux The solar EUV flux is a key parameter for space weather formation of the diurnal ionosphere! communications (minutes) heating of the ionosphere! satellite drag (hours) energy input! global climate change (years) Space Weather Week - ESTEC 1/12/04 - TDdW 28

15 Solar EUV flux Observational constraint : fluxes cannot be measured from ground! many attempts to use proxies instead (MgII, f10.7, e10.7, sunspot number,...) User needs nowcast/forecast the spectrum (wavelength resolution) nowcast/forecast the total irradiance (time resolution) Quiet Sun conditions are easier to model! very little has been done on extreme events Space Weather Week - ESTEC 1/12/04 - TDdW 29 Solar EUV flux : what models? Nowcast / forecast the spectrum use various proxies + atomic transition models to define reference spectra SC#REFN (Torr et al., 1976) Solar2000 (Tobiska, 2001) Warren (1998), Kretzschmar et al. (2002),... Nowcast / forecast the variability the attention has focused on the prediction of proxies (sunspot nr, f10.7 index,...) Space Weather Week - ESTEC 1/12/04 - TDdW 30

Sunspot number The prediction of the sunspot number still remains a paradigm Space Weather Week - ESTEC 1/12/04 - TDdW 31 Sunpots User needs short-term predictions (days) long term predictions

16 Sunspot number The prediction of the sunspot number still remains a paradigm Space Weather Week - ESTEC 1/12/04 - TDdW 31 Sunpots User needs short-term predictions (days) long term predictions (months/years) : cycle length, maximum amplitude, etc. Observational facts Prediction horizon is about 1 year (Mundt, 1991) sunspot minimum gives clues to amplitude of next maximum (Hathaway, 1999) the aa index can help improve predictions (Feynman, 1982) etc. Space Weather Week - ESTEC 1/12/04 - TDdW 32

Sunpots : prediction Long-term prediction of sunspots (months/years) use various empirical models (neural nets, nonlinear time series analysis techniques) Short-term prediction of sunspots (days) use

17 Sunpots : prediction Long-term prediction of sunspots (months/years) use various empirical models (neural nets, nonlinear time series analysis techniques) Short-term prediction of sunspots (days) use various empirical models improve estimates using information from the far side of the Sun from Lyman-! radiation from heliosismology Space Weather Week - ESTEC 1/12/04 - TDdW 33 Hidden side of the Sun The far side of the Sun can be investigated by Lyman-! images of the sky (SoHO-SWAN) Helioseismology (SoHO-MDI) : oscillation measurements from MDI + inversion of heliosismic models allows to locate active regions on the far side of the Sun Space Weather Week - ESTEC 1/12/04 - TDdW 34

imaging of far side Monitoring of Lyman-!

18 Helioseismology The same active region, as seen with intervals of 1/2 solar rotation active region as seen on far side Lindsey & Braun, 2000 Space Weather Week - ESTEC 1/12/04 - TDdW 35 Lyman-! imaging of far side Monitoring of Lyman-! emission on the far side of the Sun is made possible by SWAN (SoHO) FAR SIDE NEAR SIDE Active region as seen on the far side of the Sun J.-L. Bertaux & E. Quémerais (2003) Space Weather Week - ESTEC 1/12/04 - TDdW 36

19 Who is using far-side observations? SWAN far-side data are exploited on a daily basis by JPL (Jet Propulsion Laboratory) : solar irradiance estimation several days ahead with the SOLAR 2000 code (Tobiska et al.) CLS (Collecte Localisation Satellites) : orbitography predictions several days ahead (A. Blusson) Space Weather Week - ESTEC 1/12/04 - TDdW 37 Long-term prediction : a dynamical systems approach Problem : the sunspot number is a proxy for!b and not for!b! some information is missing Dynamical systems theory provides analytical tools for understanding/predicting the dynamics of!b when!b only is known Result : low prediction horizon during solar minimum - analogous to weakly dissipative Rössler system Letellier et al., 2004 Space Weather Week - ESTEC 1/12/04 - TDdW 38

20 To conclude Space Weather Week - ESTEC 1/12/04 - TDdW 39 Availability of models Public domain, but upon request most models belong to that category Public domain, freely accessible there is presently a large effort toward making mature models easily accessible on the web and well documented Examples : SPENVIS Community Coordinated Modeling Center (CCMC / ILWS) French Online Magnetic Field Extrapolation (FROMAGE) Classified some models have been developed exclusively for specific users (DoD) Commercial none so far Space Weather Week - ESTEC 1/12/04 - TDdW 40

21 Future issues (I) improve skill : models must be improved optimize numerics : models must be faster stability and reliability are important couple different models example : equilibrium reconstruction + neural net a solution to handle the large range of scales Space Weather Week - ESTEC 1/12/04 - TDdW 41 Future issues (II) data assimilation models must be robust against sparse data need fast access to certified data centres high quality data (10 sec time resolution, 0.1 spatial resolution, low noise) make codes available to non-specialists documentation move from scientific to operational models : must this be carried out by physicists or not? Space Weather Week - ESTEC 1/12/04 - TDdW 42

22 The ultimate model architecture Photospheric magnetic field Remote sensing the solar corona (EUV, X-ray, visible, radio,...) In situ solar wind In situ magnetosphere observations Equilibrium models & MHD models models for eruptive phenomena solar wind models magnetospheric models models Space Weather Week - ESTEC 1/12/04 - TDdW 43 Present predictive capacity (models only) process forecast (months) forecast (days) forecast (hours) nowcast post-event analysis CMEs statistics MHD models flares and active regions statistics SEPEs empirical models EUV, X-ray & radio flux (flares) statistics EUV, X-ray & radio flux (ave) empirical models empirical models empirical models Space Weather Week - ESTEC 1/12/04 - TDdW 44

23 Analogy with meteorology Space weather has many similarities with atmospheric weather! we can partly rely on existing experience Solar activity is a truly global phenomenon global models can only be developed on an international basis, with a strong collaboration between teams data assimilation requires an international network of observatories (virtual observatories, ILWS) with well-established standards on a smaller scale, smaller models can be developed to serve specific purposes Space Weather Week - ESTEC 1/12/04 - TDdW 45 Analogy with meteorology But there are also some fundamental differences between space weather and atmospheric weather observations : our monitoring capacity is much smaller, and no in situ measurements are available! data assimilation is a real problem range of spatial scales : many meteorological processes are amenable to a local description. Solar processes cover a wide range of scales : from 100 km (nanoflares) to 10 7 km (coronal holes) range of time scales : solar processes occur on a wide range of scales : from seconds (flare) to years (solar cycle)! there won t be any equivalent to the European Centre for Medium Range Weather Forecast Space Weather Week - ESTEC 1/12/04 - TDdW 46

Rationale for a European Space Weather Programme

Rationale for a European Space Weather Programme Hannu Koskinen Finnish Meteorological Institute ESWS Final Presentation ESTEC, 6 December, 2001 Scope WP 300 of ESWS: Establishment of detailed rationale