Modeling Variations of the Solar UV Spectrum with COSI

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Sun, Solar Activity, Uv, Radiative Transfer

Scientific paper

The aim of the present thesis is the reconstruction of the solar UV variability on the basis of solar spectrum synthesis, carried out with the radiative transfer code COSI (COde for Solar Irradiance) and an available analysis of magnetograms of the solar disk going back to 1974, describing the time-dependent contributions of the active regions - sunspot umbra, penumbra and faculae on the solar disk.
COSI is a spherical radiative transfer code that simultaneously solves the radiative transport equation and the equations for statistical equilibrium. This is essential for the spectrum synthesis of the ultra-violet (UV), as it is partly formed in the chromosphere, where the assumption of local thermodynamic equilibrium (LTE) does not hold. In its present form COSI is for the first time applied for solar studies. Thus a number of modifications, essential for the calculation of solar spectra, have been carried out within the scope of this thesis.
First there is the implementation of solar atmosphere structures to account for the temperature and density stratification for different active regions, in particular for the rising temperature profile of the chromosphere. Then the implantation of atomic levels and the corresponding photoionization cross sections was required to calculate the ionization, recombination and the line transitions of a number of lines in non-LTE. Furthermore, the radiative and collisional processes of negative hydrogen - being the dominant opacity source in the visible and IR wavelength range - are fully accounted for. In particular we implemented the collisional cross sections of the negative hydrogen with electrons and protons.
Most important is the inclusion of the opacity of all spectral lines in the solution of the non-LTE radiative transport. We employ the new concept of iterated opacity distribution functions (ODFs) - non-LTE ODFs - being ODFs that are iterated until the population numbers converge. We show that only with the inclusion of the line opacities can we reproduce observations.
The implementations are validated against other synthetic spectra, observations and a reference spectrum. To investigate the uncertainties of the observations we first compared the time series of the UV measurements of two instruments. This is essential, as these measurements are used to validate our reconstructions. We find that the observations reveal absolute (up to a factor of 2) and also different relative (up to a factor of 10) uncertainties. The comparisons of the synthetic spectra with reveal that from 1300 to 1700 A and in the IR the COSI calculations reproduce the observations very well. However, at other wavelengths the calculations generally overestimate the observed flux.
Representing the basis for the reconstructions, we calculate solar intensity spectra for the quiet Sun, sunspots and plage for different positions on the solar disk. They are then weighted according to their time-dependent fractional area on the solar disk, derived from an available analysis of space-based and ground-based magnetograms - the Solar Oscillations Investigation/Michelson Doppler Interferometer (SOI/MDI) onboard the ESA/NASA satellite Solar and Heliospheric Observatory (SoHO), and the National Solar Observatory/Kitt Peak Vacuum Telescope (NSO/KPVT). This leads to a time series of the specific irradiance.
A sensitivity study reveals that a reconstruction employing the umbra atmosphere structure (Model S) for calculating the penumbra intensities leads to a lower correlation with the observations than using Model C.
The reconstructions are compared with the Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) and Solar/Stellar Irradiance Comparison Experiment (SOLSTICE) observations. We find that the solar surface magnetic field is a suitable proxy for UV reconstructions. In particular, we find that between 1300 to 1700 A the observed variability is well reproduced. However, at other wavelength ranges the reconstructions underestimate the observed variability substantially.

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