assimilation of solar spectral irradiance data within the solid project margit haberreiter pmod/wrc,...

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


SOLID Motivation II – Overlapping data and models do not agree

Ermolli et al., 2013, ACP


Instrumental accuracy (210 nm)

Courtesy Micha Schoell


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)


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


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


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


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


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


How to stitch it together?

• Mean – introduces discontinuities (not a good idea)

• Median

• Take your favorite data set (very subjective)

• Bayesian approach


Our SOLID Approach


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)


Example: Uncertainty in the UV

UV SpectrumUncertainty SOLSTICEUncertainty SUSIM


Courtesy Kretzschmar

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/


Small Scale Heating Events in the solar corona

Coronal heating events identified from 3D MHD simulations

Poster:

Guerreiro,

Haberreiter,

Hansteen,

Schmutz,


Questions

SOLID – How do we address the problem

Newsletter

http://projects.pmodwrc.ch/solid/

Email:[email protected]

[email protected]

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

assimilation of solar spectral irradiance data within the solid project margit haberreiter pmod/wrc,...

Documents

margit haberreiterdublin

solid motivation

solid modelling

solid teamkick

modelled ssi

existing ssi

ssi dataespm

spectral gapscoordinator