Prediction of solar flaresPrediction of solar flareson the basis of correlationon the basis of correlationwith long-term irradiancewith long-term irradiance

and sunspot levelsand sunspot levels

Ingolf E. Dammasch, Marie Dominique (ROB)Ingolf E. Dammasch, Marie Dominique (ROB)

SIDC Seminar, Brussels, 07 Mar 2014

LYRAthe Large-Yield Radiometer onboard PROBA2

Contents

LYRA, spectral response, data Poster for ESWW10 Development, future questions

LYRA: the Large-Yield RAdiometer

3 instrument units (redundancy) 4 spectral channels per head 3 types of detectors,

Silicon + 2 types of

diamond detectors (MSM, PIN):

- radiation resistant

- insensitive to visible light

compared to Si detectors High cadence up to 100 Hz

• Royal Observatory of Belgium (Brussels, B)Principal Investigator, overall design, onboard software specification, science operations

• PMOD/WRC (Davos, CH)Lead Co-Investigator, overall design and manufacturing

• Centre Spatial de Liège (B)Lead institute, project management, filters

• IMOMEC (Hasselt, B)Diamond detectors

• Max-Planck-Institut für Sonnensystemforschung (Lindau, D)calibration

• science Co-Is: BISA (Brussels, B), LPC2E (Orléans, F)…

LYRA highlights

LYRA highlights

4 spectral channels covering a wide emission temperature range

Redundancy (3 units) gathering three types of detectors Rad-hard, solar-blind diamond UV sensors (PIN and MSM) AXUV Si photodiodes

2 calibration LEDs per detector (λ = 465 nm and 390 nm) High cadence (up to 100Hz) Quasi-continuous acquisition during mission lifetime

Ly Hz Al Zr

Unit1 MSM PIN MSM Si

Unit2 MSM PIN MSM MSM

Unit3 Si PIN Si Si

SWAP and LYRA spectral intervalsfor solar flares, space weather, and aeronomy

LYRA channel 1: the H I 121.6 nm Lyman-alpha line (120-123 nm)LYRA channel 2: the 200-220 nm Herzberg continuum range (now 190-222 nm)LYRA channel 3: the 17-80 nm Aluminium filter range incl the He II 30.4 nm line (+ <5nm X-ray)LYRA channel 4: the 6-20 nm Zirconium filter range with highest solar variablility (+ <2nm X-ray)SWAP: the range around 17.4 nm including coronal lines like Fe IX and Fe X

LYRA spectral response

Spectral degradation after 200 days in space

Experience from SOVA (1992/93) and LYRA (2010/11) combined(“molecular contamination on the first optical surface … caused by UV-induced polymerization”)

Reminder: LYRA spectral response

channel 2-3: Aluminium filter, nominally 17-80nm channel 2-4: Zirconium filter, nominally 6-20nm additional SXR components <5 nm, <2 nm for comparison: GOES 0.1-0.8 nm => Flares !

LYRA data product: 3day quicklook

LYRA data product: flare list

LYRA data product: GOES vs. LYRA proxies

LYRA data product: long-term solar levels

Contents

LYRA, spectral response, data Poster for ESWW10 Development, future questions

“Level”

Significant daily minimum,without flaresor instrumentalartefacts

“Variance”

Dailyminor-flaringactivity,standard deviationin small corridor

“Level”

100 values (*)closest aroundLYRA ch2-4selected from 1300 observations=>estimateddistribution offlare strengths

Same forLYRA ch2-3,GOES,DSSN=>forecast based on400 values

“Variance”

100 values (*)closest aroundLYRA ch2-4selected from 1300 observations=>estimateddistribution offlare strengths

Same forLYRA ch2-3,GOES,DSSN=>forecast based on400 values

“Level” – daily forecast

“Variance” – daily forecast

Warnings

This is a statistical flare forecast (“Bayesian approach”). M- and X-flares are so exceptional that the estimated median

will always stay below. Probabilities may rise from 0% to 30-40% (M) or 5-10% (X). It is not assumed that statistics like these can substitute a space

weather forecaster's experience. Magnetic structures are not taken into consideration. But statements like the following become possible: “When the GOES level rises to B7, one has an almost 50%

chance of observing an M-flare.” “No X-flare ever occurred while LYRA ch2-3 was below

0.0023 W/m², or LYRA ch2-4 was below 0.00095 W/m².”

“Level”

Test Aug-Oct 2013

Method changesslower

Median leads tounderestimationduring high activity

Probabilities reflectsituation better

“Variance”

Test Aug-Oct 2013

Method followscloser

Median leads tounderestimationduring high activity

Probabilities reflectsituation better

Contents

LYRA, spectral response, data Poster for ESWW10 Development, future questions

Three months later…

“Does it make sense?” – “Yes”, said Mike Wheatland (Univ. Sidney, invited lecture at ESWW10)

Second activity peak of cycle 24 – does it change the statistics? How to evaluate a forecast which consists of more than one

value? Are my methods better than the “Yesterday’s Weather”

hypothesis? How can they be improved? Which forecasting parameter is the most reliable? Are our space weather forecasters interested?

Still problems with under-estimationsin periods ofhigh activity

Skill scores

Create bins of probabilities of certain events (M-flare prediction between 0-5%, 5-10%, etc) and check the real percentage of events in these days (“reliability plot”)

Per month or per week, check the prediction of events like M-days (=sum of M-flare probabilities) against the realized number of events (“prediction of event days”)

Six months of prediction data exist, calculations TBD

Results to be presented

An abstract was submitted to COSPAR Session D2.2-E3.2 “Space Climate” Title “Long-term irradiance observation and short-term flare

prediction with LYRA on PROBA2”

Please visit

http://solwww.oma.be/users/dammasch/flares/FlareProbability.html http://solwww.oma.be/users/dammasch/flares/FlareProbabilityVar.html