assimilation of solar spectral irradiance data within the solid project margit haberreiter pmod/wrc,...
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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/WRCFebruary 12-14, 2013
Annual Meeting in Orleans, France
http://projects.pmodwrc.ch/solid/ESPM-14 Margit HaberreiterDublin, 8.-12.2014
Overview
Motivation
Goals
Approach
First Results
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
SOLID Motivation I – Scattered SSI Data
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
SOLID Motivation II – Overlapping data and models do not agree
Ermolli et al., 2013, ACP
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Instrumental accuracy (210 nm)
Courtesy Micha Schoell
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
Importance for other research fields
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 HaberreiterDublin, 8.-12.2014
SOLID in a nutshell• SOLID: First European Comprehensive SOLar Irradiance 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
8ESPM-14 Margit HaberreiterDublin, 8.-12.2014
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 HaberreiterDublin, 8.-12.2014
SOLID – Type of observations
• Reference Spectra– ATLAS1, ATLAS3, SOLAR/ISS/SOLSPEC,
(Thuillier et al., 2006, 2013, 2014)
• SSI time seriese.g. SORCE/SIM, SORCE/SOLSTICE,
PROBA2/LYRA, UARS/SOLSITCE, UARS/SUSIM,
• Proxy time series– E.g. Mg II index, F10.7
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
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 HaberreiterDublin, 8.-12.2014
EUV Reconstruction versus SOHO/SEM
SOLMOD ReconstructionError of the modelled SSI is of the order of the observationHaberreiter et al., 2014, accepted, J. Space Weather Space Climate
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
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 HaberreiterDublin, 8.-12.2014
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 HaberreiterDublin, 8.-12.2014
How to stitch it together?
• Mean – introduces discontinuities (not a good idea)
• Median
• Take your favorite data set (very subjective)
• Bayesian approach
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Our SOLID Approach
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Wit the Bayesian approach:
Derive the composite that is most compatible with the observations
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)
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
Example: Uncertainty in the UV
UV SpectrumUncertainty SOLSTICEUncertainty SUSIM
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Courtesy Kretzschmar
First Studies – Mg II index
Courtesy Thierry Dudok de Wit
First Studies – Mg II index
Courtesy Thierry Dudok de Wit
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 eachESPM-14 Margit HaberreiterDublin, 8.-12.2014
SOLID Webpage
http://projects.pmodwrc.ch/solid/• Database• Wiki• Deliverables
Poster on the SOLID Project
Haberreiter et al.
SOLID – Webpage and Database
http://projects.pmodwrc.ch/solid-visualization/makeover/
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
Small Scale Heating Events in the solar corona
Coronal heating events identified from 3D MHD simulations
Poster:
Guerreiro,
Haberreiter,
Hansteen,
Schmutz,
ESPM-14 Margit HaberreiterDublin, 8.-12.2014
Questions
SOLID – How do we address the problem
SSI and TSIWP2
WP3 WP4 WP5
prox
ies
EUV/UV spectra
data
modeling
groups
WP6Interaction with
communitiesWP8Dissemination
end-usersatmospheric research
photobiology
space weather
ionospherethermosphere
Interaction with user communities