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Thanks to the SOLID Team

Assimilation of solar spectral irradiance data within the SOLID project Margit Haberreiter PMOD/WRC, Davos, Switzerland. Thanks to the SOLID Team. Kick-off Meeting at PMOD/WRC February 12-14, 2013 Annual Meeting in Orleans, France http:// projects.pmodwrc.ch /solid/.

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Thanks to the SOLID Team

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  1. Assimilation of solar spectral irradiance data within the SOLID projectMargit HaberreiterPMOD/WRC, Davos, Switzerland

  2. Thanks to the SOLID Team Kick-off Meeting at PMOD/WRC February 12-14, 2013 Annual Meeting in Orleans, France http://projects.pmodwrc.ch/solid/ ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  3. ESPM-14 Margit Haberreiter Dublin, 8.-12.2014 Overview • Motivation • Goals • Approach • First Results

  4. SOLID Motivation I – Scattered SSI Data ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  5. SOLID Motivation II – Overlapping data and models do not agree Ermolli et al., 2013, ACP ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  6. Instrumental accuracy (210 nm) Courtesy MichaSchoell ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  7. Importanceforotherresearchfields • Stellar Physics • to be able to link the Sun to other solar like stars the variation in SSI is important • Sun-Earth connection • Investigate solar long-term changes in spectral irradiance and their influence on the Earth’s climate • Influence on other planets • Effect on other planetary atmospheres (link to exoplanets) ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  8. ESPM-14 Margit Haberreiter Dublin, 8.-12.2014 SOLID in a nutshell • SOLID: First European Comprehensive SOLarIrradiance Data exploitation • Goal: provide a consistent SSI time series from the EUV to IR with error bars • Approach: use all existing SSI and proxy data complemented with models to fill temporal and spectral gaps • Coordinator: PMOD/WRC (W. Schmutz, Projekt Manager M. Haberreiter) • Partners: 9 institutes from 7 Countries (CH, FR, BE, UK, DE, EL, IT) • + 1 US collaborator (LASP) • Start: December 2012; Duration: 3 years

  9. SOLID – What exactly do we do • Solar spectral irradiance data • Reconstruction models of SSI • “Stitch it all together” i.e. find an objective method to obtain the most correct SSI time series ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  10. SOLID – Type of observations • Reference Spectra • ATLAS1, ATLAS3, SOLAR/ISS/SOLSPEC, (Thuillier et al., 2006, 2013, 2014) • SSI time series e.g. SORCE/SIM, SORCE/SOLSTICE, PROBA2/LYRA, UARS/SOLSITCE, UARS/SUSIM, • Proxy time series • E.g. Mg II index, F10.7 ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  11. SOLID – Modelling to fill the gaps • Empirical modelling • Principal Component Analysis, Single Value Decomposition • Semi-Empirical Modelling • Combine synthetic spectra based on solar image analysis • SATIRE, COSI, SOLMOD, OAR • Including an update of atomic lines ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  12. EUV Reconstruction versus SOHO/SEM SOLMOD Reconstruction Error of the modelled SSI is of the order of the observation Haberreiter et al., 2014, accepted, J. Space Weather Space Climate ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  13. Accuracy, Precision, Stability • Accuracy (confidence in absolute level) • Previous issues, e.g. TIM-VIRGO off-set) • Precision (confidence in short-term uncertainty) • Repeatability of the measurement (influenced e.g. by readout noise of the instrument) • Stability (confidence in long-term uncertainty) • Instrument degradation (covered by instrument teams) ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  14. Sanity Check of each SSI Data set • Noise estimate for each data set • One homogeneous data format • Missing data interpolated via single value decomposition (Error introduced is estimated) • Outliers are removed and flagged • Solar outliers are kept in the data set! • Data processing tracable ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  15. How to stitch it together? • Mean – introduces discontinuities (not a good idea) • Median • Take your favorite data set (very subjective) • Bayesian approach ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  16. ESPM-14 Margit Haberreiter Dublin, 8.-12.2014 Our SOLID Approach Wit the Bayesian approach: Derive the composite that is most compatible with the observations

  17. ESPM-14 Margit Haberreiter Dublin, 8.-12.2014 Our SOLID Appraoch • Bayesian: Provides the most compatible value (based on objective prior information) • Perform the data fusion scale-wise E.g. daily, 28 day, 81-day, annual, solar cycle • Requirement: • time-dependent uncertainties (confidence intervals) • ε(t, scale) • Independent data sets (no inbreeding) • Proof of concept: new TSI composite (Dudok de Wit et al., in prepration; Kopp et al., in preparation)

  18. Example: Uncertainty in the UV UV Spectrum Uncertainty SOLSTICE Uncertainty SUSIM Courtesy Kretzschmar ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  19. First Studies – Mg II index Courtesy Thierry Dudok de Wit

  20. First Studies – Mg II index Courtesy Thierry Dudok de Wit

  21. Goal: Unprecedented SSI time series • Approach will be applied to all SSI data sets (incl models) • homogeneous dataset • i.e. uniform time and wavelength grid • from EUV to IR • Realistic error bars (important for the composite) • time and wavelength dependent confidence intervals for each ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  22. SOLID Webpage • http://projects.pmodwrc.ch/solid/ • Database • Wiki • Deliverables Poster on the SOLID Project Haberreiter et al.

  23. SOLID – Webpage and Database http://projects.pmodwrc.ch/solid-visualization/makeover/ ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  24. Small Scale Heating Events in the solar corona Poster: Guerreiro, Haberreiter, Hansteen, Schmutz, Coronal heating events identified from 3D MHD simulations ESPM-14 Margit Haberreiter Dublin, 8.-12.2014

  25. Questions

  26. SOLID – How do we address the problem

  27. Newsletter http://projects.pmodwrc.ch/solid/ Email: Margit.habereiter@pmodwrc.ch Tourpali@auth.gr

  28. Interaction with user communities SSI and TSI WP2 WP5 proxies WP4 EUV/UV spectra WP3 data WP6 Interaction with communities WP8 Dissemination end-users photobiology modeling groups ionosphere thermosphere atmospheric research space weather

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