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Modelling the Solar UV variability

Modelling the Solar UV variability. M. Haberreiter ISSI Study Team on Solar Magnetism and Irradiance 11.-15.October 2004. Overview. Synthetic spectra Reconstruction Conclusions What’s next. Identification of active regions from magnetograms. 1. Magnetic flux  filling factor 

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Modelling the Solar UV variability

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  1. Modelling the Solar UV variability M. Haberreiter ISSI Study Team on Solar Magnetism and Irradiance 11.-15.October 2004 Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  2. Overview • Synthetic spectra • Reconstruction • Conclusions • What’s next Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  3. Identification of active regions from magnetograms 1. Magnetic flux  filling factor  2. Intensity contrast < 1 sunspot (umbra, penumbra) else  faculae th: threshold magnetic flux 3: magnetic fluxsaturation Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  4. Modeling spectral variability Intensity spectra calculated with COSI: • quiet sun, Model C • faculae, Model P • sunspots, Model S Magnetogram analysis: • time-dependent filling factorsfor faculae (+network) ,sunspots Variation of solar activity: Krivova & Solanki (2003) Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  5. COSI - COde for Solar Irradiance • Updated version of the spherical radiative transfer code based on Schmutz W., 1997, A&A, 321, 268 • Spectrum synthesis program SYNSPEC, based on Hubeny 1988, Hubeny & Lanz 2000 • Physics-based model • atmosphere structure (p, T) by Fontenla et al., ApJ, 1999 for quiet Sun, sunspots, faculae • spherical geometry Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  6. COSI – COde for Solar Irradiance • non-local thermodynamic equilibrium (non-LTE), important below 200 nm • non-LTE line blanketing with opacity distribution functions • Latest photoionization cross sections • C I, Mg I, Al I, Si I, Fe I (Haberreiter et al. 2002) • Opacity project (Seaton et al. 1994) • IRON project (Bautista & Pradhan 1997) Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  7. Temperature profiles Fontenla et al. 1999, ApJ Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  8. Emission due to LTE and rising temperature H I  4863 - LTE Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  9. H I  4863 - NLTE Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  10. Hydrogen lines Haberreiter & Schmutz, 2003 Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  11. Model P - plage Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  12. Model C – quiet Sun Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  13. Model S - sunspot Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  14. Problems in the calculations of the spectra • Missing opacity in the UV • improvement with the new line list  • Problems of the continuums opacity • Inconsistency in the • Validation of Hminus bound free and free free opacity • Validation of the line formation of some lines Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  15. COSI versus measurement Data: Burlov-Vasiljev et al. 1995 Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  16. Synthetic spectrum versus Thuillier Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  17. Comparison of linelists • 200 to 325 nm more lines in new line list • additional opacity Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  18. Continuum-test Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  19. Magnetogram Data Begin End • NSO/Kitt Peak Vacuum Telescope, Tucson • NSO/KP, 512nm 08 / 24 / 1974 04 / 07 / 1992 • NASA/NSO, 868nm 11 / 21 / 1992 12 / 22 / 2001 (05 / 18 / 1996) • MDI/SOHO 05 / 19 / 1996 04 / 17 / 2002 MDI: Michelson Doppler Imager Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  20. Reconstruction quiet Sun Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  21. Daily Variability of Lyman  Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  22. Spectral variability – annual mean Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  23. Spectral variability – annual mean Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  24. Why is the variability too low? • free parameter sat is fitted to give the best correlations to the TSI composite • Considerable effect on TSI • Effect of sat on the UV? • Different sat for different model atmospheres? Thomas Wenzler et al. 2004 Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  25. Lyman – KP SPM Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  26. =320 nm– KP SPM Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  27. Conclusions • The Lyman reconstruction is lower than SOLSTICE data and Wood's composite but not so bad for the SUSIM data • Reconstructed UV variability is considerably lower than the SUSIM data or the Lean reconstruction • Is the free parameter of the magnetogram analysis different for different model atmospheres? • If yes, the freeparameter has to be determined for the model atmospheres by Fontenla Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  28. What’s next • Basis for the reconstruction • OLD: Faculae, quiet Sun and sunspots • NEW: umbra and penumbra instead of a single sunspot model (Alexandra Tritschler, 2002) • Latest version of the magnetogram-analysis (Wenzler 2004a,b) • Comparison with other synthetic models and reconstructions • P. Fox, Ilaria Ermolli on the basis of PSPT images • Implement the depth dependent turbulence broadening Margit Haberreiter, PMOD/WRC, Davos, Switzerland

  29. Thank you! Margit Haberreiter, PMOD/WRC, Davos, Switzerland

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