1. Non-LTE atmosphere calculations of the solar spectrum
Prof. Dr. Werner K. Schmutz
Director PMOD/WRC
Davos, Switzerland
ISSI PROBA2 workshop, Bern June 2006

2. Overview Project overview: Variability of the Sun and Global Climate
Observations of the Total (and Spectral) Solar Irradiance
Understanding the variabiltity of the Total Solar Irradiance (TSI)
UV model calculations
Understanding UV variability

3. Sun – Earth connection at PMOD/WRC
Theoretical research project “Variability of the Sun and Global Climate in
collaboration with ETH Zürich
Experimental PMOD/WRC space experiments:
VIRGO/SoHO ( ?)
PREMOS/PICARD (2008)
LYRA/PROBA2 (2007)

4. The Sun-Earth connection: what is the influence of the Sun on the climate?
Graphics: Dr. J. Beer EAWAG, Switzerland

5. Variability of the Sun and Global Climate Project organization phase II: (phase I )
Ph.D. student EAWAG 10Be reconstruction of TSI back in time
Project Manager
Dr. Eugene Rozanov
Ph.D. student PMOD/WRC
prediction of solar spectrum
Ph.D. student PMOD/WRC
CCM calculations
Ph.D. student IACETH
comparison
with observations

6. Variability of the Sun and Global Climate
Aim:
Combine solar physics with GCM calculations
Search for mechanisms how the solar variations influences the terrestrial climate
Investigate past climate changes from the point of view of a possible variation of the solar irradiation

7. Variability of the Sun and Global Climate
Solar physics:
Understand the observed variability of the solar irradiation
Investigate the variability of the solar UV radiation
Reconstruct the solar irradiance variations for the past 20 years, 100 years, 400 years, (104 years, 106 years … )

8. Variability of the Sun and Global Climate
Global climate model calculations with interactive photochemistry (GCM + CTM  CCM) :
expand existing troposphere-stratosphere-mesosphere version of GCM/PC to allow for a detailed spectral specification of the incident radiation
evaluate the effects of variations in spectral solar irradiance input on ozone and other trace gases

9. Observations of the Solar Constant

10. Total Solar Irradiance – „PMOD-Composite”

11. TSI (W/m2) Indices: Rz As MgII F10.7
Graph: curtesy of N. Krivova

12. TSI cycle 23

13. Sunspot area cycle 23

14. TSI and Sunspot area cycle 23 As
TSI

15. Understanding the variabiltity of the Total Solar Irradiance (TSI)
3-component model: quiet sun — faculae — sun spots
Thomas Wenzler, ETH-ZH
+ S. Solanki & N. Krivova (+ M. Schüssler), MPS
(newer models based on 4 components)

16. 3-component model: filling factors a observed Kurucz ATLAS9 models for the intensity I
q = quite sun
s = sun spot
f = faculae

17. Sun spots reduce the solar irradiance

18. Faculae increase the solar irradiance

19. facular and sunspot effective areas (1)
MDI magnetogramm continuum intensity image
August 30, 1996

20. facular and sunspot effective areas (1)
maps for faculae for sunspots
August 30, 1996: active region dominated by faculae

21. facular and sunspot effective areas (2)
MDI magnetogramm continuum intensity image
November 25, 1996

22. facular and sunspot effective areas (2)
maps for faculae for sunspots
November 25, 1996: faculae and sunspot extracted

23. Comparison with observations (1a)
Fligge, Solanki Unruh 2000, A&A 353, 380

24. Comparison with observations (1b)
Fligge, Solanki Unruh 2000, A&A 353, 380

25. Comparison with observations: cycle 21 – 23 Wenzler et al
Comparison with observations: cycle 21 – 23 Wenzler et al. 2005, A&A in press

26. Comparison with observations (2): spectral variation between maximum and minimum
Unruh, Solanki, Fligge 2000, A&A 345, 635
calculated
Lean 1997

27. Comparison with observations (3): spectral variation between maximum and minimum

28. Understanding the UV variabiltity
Modeling Variations of the Solar UV Spectrum with COSI
Margit Haberreiter, Micha Schöll, Werner Schmutz
+ input from the 3 (4) –component model
COSI: model atmosphere in spherical geometry and non-LTE level populations
in this application: solar structure is input

29. Synthetic solar spectrum
Present status:
ATLAS9: Kurucz LTE model fits the observations

30. Observed composite solar spectrum vs ATLAS9

31. SUSIM solar spectrum vs ATLAS9

32. Temperature Structure

33. A raising temperature structure beyond the minimum is needed
ATLAS9: Kurucz LTE model fits the optical observations, but:
non-LTE model is needed to calculate the UV spectrum
(l < 200 nm)

34. In LTE, a raising temperature structure yields a much to strong UV radiation and UV variability

35. The problem to calculate a solar atmosphere
non-LTE model is needed for the UV spectrum
(l < 200 nm)
Ok, no problem, but:
Introduction of non-LTE affects also the visual and IR part of the spectrum!

36. The problem to calculate a solar atmosphere
Introduction of non-LTE affects the visual and IR part of the spectrum!
But,
the spectrum is (obviously) also affected by:
Temperature structure
Abundances
which have been thought to be known ...

37. The problem to calculate a solar atmosphere (work in progress)
Introduction of non-LTE affects the visual and IR part of the spectrum!
This requires to re-determine:
Temperature structure
Abundances

38. Comparison of the synthetic non-LTE COSI spectrum with SOLSPEC observations

39. Non-LTE versus LTE calculations of the solar spectrum

40. Comparison of COSI results with observations: Lyman-a

41. Comparison of COSI results with observations: spectral variation between maximum and minimum

42. Correlation of spectral features
strongest 2 principle components ( 90%)
Axis1 = short time variability (27 days)
Axis2 = long term variability (year)
s = sun spot nr
f F10.7
m MgII index
Fig. from Dudok de Wit et al. Annales Geophysicae, 23, 3055–3069, 2005

43. Next step: Place the filling factors for faculae and sunspots
Aim:  Recon-struction of physical solar parameters
Dudok de Wit, personal communication: LYRA filters 1-4

44. Conclusions
fractions of solar irradiance variations due to solar surface magnetism (lower limit estimates):
Solar rotation time scale:  90%
Activity cycle time scale:  90%
Secular (centuries) time scale: ?
Status: magnetic evolution can be modeled (contribution of other sources is unknown)
UV modeling
fair progress – not yet solved
UV influence on climate
ozone reaction understood
tropospheric climate response only about 50% of the estimated solar influence