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New Models and Observational Strategies for reconstructing the Solar Spectral

Irradiance for Space Weather Applications

G. Cessateur, T. Dudok de Wit, M. Kretzschmar, L. VieiraG. Cessateur, T. Dudok de Wit, M. Kretzschmar, L. Vieira

LPC2E, University of Orléans, FranceLPC2E, University of Orléans, France

J. Lilensten J. LilenstenLPG, University of Grenoble, FranceLPG, University of Grenoble, France

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Outline

• Why is solar UV radiation important for Space Weather ?

• Observations and Modelling of the Solar Spectral Irradiance

• News strategies of observation

• Solar radio telescopes

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Solar UV Radiation

• 1-300 nm range ≈ 1% of the Total Solar Irradiance (TSI)

• Main source of energy for aeronomic processes

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Solar UV Radiation

Various time scale

• 11-years cycle

• 27-days solar rotation

• min to hours: impulsive events

SEM/SoHO

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Solar UV Radiation

SORCE & TIMED data (2003-2010)

EUV Flux ≈ 10-100%

FUV Flux < 10%

MUV Flux < 1%

Variability is wavelength-dependant

Rel

ativ

e V

aria

bilit

y [%

]

Wavelength (nm)

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Why is solar UV radiation important for space Weather ?

• Heating of the upper atmosphere (EUV) satellite drag

• Formation of the ionosphere (XUV-EUV)

• Photolysis (EUV-MUV) climate

satellite communications

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UARSUARS

SORCESORCE

SORCESORCE

TIMEDTIMED

AEAE--EEAEAE--CC

AE

RO

SA

ER

OS

-- AA

AE

RO

SA

ER

OS

-- BB

OSOOSO--55

SMSM--55

SMESME

EUV HOLE I EUV HOLE II

NOAANOAA--9/119/11

OS

OO

SO

-- 33

OS

OO

SO

-- 11

UARSUARS

SORCESORCE

SORCESORCE

TIMEDTIMED

AEAE--EEAEAE--CC

AE

RO

SA

ER

OS

-- AA

AE

RO

SA

ER

OS

-- BB

OSOOSO--55

SMSM--55

SMESME

EUV HOLE I EUV HOLE II

NOAANOAA--9/119/11

OS

OO

SO

-- 33

OS

OO

SO

-- 11

Which Observations are Available ?

Spectral Irradiance Observations (Δλ ≤ 1nm): Instrument satellite-based UV Models

Instrumental Challenge

• Lack of measurements

• Instrument degradation (e.g. Floyd et al, 1999)

• Intercalibration issues (e.g. Deland & Cebula, 2008)

SDOSDO

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Models based on solar proxies

1. Reference Spectra + Variability measured by indices: F10.7, < F10.7> 81d

2. Linear Combination of solar proxies and indices

EUV: Lyman α, Mg II, F10.7, < F10.7> 81d, He I(1058nm), E10.7, …

FUV/MUV: Mg II index (Facules) and Sunspots index

SERF / HFG (Hinteregger et al, 1981)EUVAC / HEUVAC (Richards et al, 1994, 2006)Radio Background Nusisov (1984)Woods and Rottman (2002)+

SERF2, EUV91/97, SOLAR 2000Tobiska et al, 1988,1991,1998,2000,2006NRLEUV: Warren et al, 2003, 2006; Lean et al 2003

Lean et al, 1997, 2000

Method Convenient but not reliable for Space weather purposes

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Models based on EUV-UV images

Solar variability in the EUV, FUV/MUV is driven by different features (Quiet Sun, sunspot, active network, enhanced network, ...).

Filling factor for different regions

Recent progress in automated image processing allows for tracking solar features in real-time (e.g. Barra et al, 2009)

1. Contrast defined empirically

2. Contrast defined semi-empirically, using the differential emission measure.

Cook et al, 1980Lean et al, 1982,1983,1984Worden et al, 1996,1998

Warren et al, 1998a, 1998b, 2005

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Models based on solar magnetograms

• Is solar spectral variability entirely driven by solar magnetism ?• The quiet Sun contribution plays a crucial role• The XUV and EUV ranges cannot be properly described but solar atmosphere NLTE models are steadily improving (Shapiro et al, 2010)

Solar variability in the UV, visible and IR is mainly driven by magnetic features (Quiet Sun, umbra, penumbra, faculae, ...).

Assign spectrum or coefficient to each

region

Solar spectrum is a combination of these

spectra

1. Empirical Approach (Oral Presentation L. Vieira Friday 10h15)

2. Semi-Empirical Approach: SATIRE model (Krivova et al, 2003, 2006)

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Observations VS Models: short time scales

Similar results for the FUV/MUV range (120-300 nm) (Lean et al, 2005)

EUV (10-120 nm)

Woods et al, 2005

Short time scales are well reconstructed, within 40% of the data

Model (NRLEUV)

Observations (TIMED SEE)

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Observations vs Models: long time scales

Important discrenpancies between models and observations(Haigh et al, 2010)

1) Calibration or instrument degradation?

2) Anomalous declining phase of the solar cycle 23

Different characteristics of the solar spectrum ?

Models are not well constrained

Observations

Model

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• No missions planned after SORCE to continuously monitor spectral irradiance above 120 nm

• Instrumental challenge: instrument degradation

Technology more robust: diamond detectors developed for radiometers

• Present and Futures Missions: is high spectral resolution really needed or can we just focus on a few spectral bands ?

New Strategies ?

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Observations with some Passbands

LYRA/PROBA2LYRA/PROBA2

PREMOS/PICARDPREMOS/PICARD

EUVS/GOES-13,14EUVS/GOES-13,14

EUVS/GOES-REUVS/GOES-R

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Observations with some Passbands

Different spectral lines evolve remarkably coherently they can be reconstructed from a combination of a few others (Dudok de Wit et al, 2005; Kretszchmar et al, 2006)

30.5 nm (He I)

121.5 nm (H I)

250.5 nm (Mg I)

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Statistical approach: Multidimensional scaling

Observations with some Passbands

4 passbands should suffice to reconstruct the solar UV spectral variability

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Empirical Approach

• Each spectral line can be reconstructed from a linear combination of four passbands

• Reconstruction error is comparable to instrumental error.

(Cessateur et al, submitted)

Observations with some Passbands

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• Continuous monitoring of the solar spectral irradiance is crucial for space weather and for space climate

• But data are highly fragmented and no observation of the full UV spectrum will exist after SORCE ends (2013)

• Lack of continuous observations:

Conclusions

1. Use solar proxies as substitutes (simple, but not accurate enough for upper atmosphere specification models)

2. Use segmented solar images (very promising, but calibration issues)

3. Use a simple dedicated monitors to observe a few passbands and reconstruct the spectrum from these.