A new solar prominence catalogue with SOPRA

Nicolas Labrosse1, Silvia Dalla2,

Jinchang Ren3, and Steve Marshall3

1- University of Glasgow, Scotland

2- University of Central Lancashire, England

3- University of Strathclyde, Scotland

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13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• Fact: some attempts to make large statistical studies of

global prominence properties

– Manual detection

E.g. Gilbert et al (2000): identify distinguishing characteristics of APs and

EPs and study the relationship between prominence activity and CMEs

– Automatic detection

Foullon & Verwichte (2005); Wang et al. (2010)

• Can be improved by producing large catalogues for

statistical studies

• Link with filament / flare / CME catalogues

• Automatic feature recognition from SDO/AIA data

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Aims

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• What does SOPRA mean?

• sopra prep

• a (gen) over

• b (più in su di) above

Solar Off-limb Prominence Reconstruction Algorithm

• Approach

– Process only He II 304 images

Prominences are best viewed in this channel

Limits dependence on other channels' availability

Faster to process than when using additional channels

• Now developed for SOHO/EIT data

• Being tested on SDO/AIA

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SOPRA

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• Pre-processing of image

• Take radial intensity profiles, calculate moments and label them

• Train Support Vector Machine

• Algorithm recognises off-limb structures based on the moments of the radial intensity profiles

• At the position on the limb where a prominence is detected, morphological image reconstruction is applied

• Prominence characteristics are extracted

– Results feed the catalogue

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Method

Training of classifier

Classification

Reconstruction

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• Pre-processing of image

• Take radial intensity profiles, calculate moments and label them

• Train Support Vector Machine

• Algorithm recognises off-limb structures based on the moments of the radial intensity profiles

• At the position on the limb where a prominence is detected, morphological image reconstruction is applied

• Prominence characteristics are extracted

– Results feed the catalogue

4

Method

Classification

Reconstruction

prominence

active region quiet corona

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• Pre-processing of image

• Take radial intensity profiles, calculate moments and label them

• Train Support Vector Machine

• Algorithm recognises off-limb structures based on the moments of the radial intensity profiles

• At the position on the limb where a prominence is detected, morphological image reconstruction is applied

• Prominence characteristics are extracted

– Results feed the catalogue

5

Method

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• Pre-processing of image

• Take radial intensity profiles, calculate moments and label them

• Train Support Vector Machine

• Algorithm recognises off-limb structures based on the moments of the radial intensity profiles

• At the position on the limb where a prominence is detected, morphological image reconstruction is applied

• Prominence characteristics are extracted

– Results feed the catalogue

6

Method

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• We processed 29367 FITS files covering ~ all EIT full-disk

images at 304 Å between 01/1996 and 06/2011

– Took > 2 weeks on 4x Quad Core AMD with 64 GB of RAM

• 315307 unique prominences detected

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Applying SOPRA on the EIT database

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011 8

Results: histograms

Prominence area

Latitude

Time

Altitude

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011 9

Results: correlations

Area vs time

Altitude vs time

Latitude vs time

Altitude vs latitude

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011

• SOPRA: Solar Off-limb Prominence Reconstruction Algorithm

– Labrosse et al., Solar Physics, 262, 449 (2010)

• The algorithm as a whole is working well

– Production of catalogue from EIT observations since 1996

– Generates HEK-compliant output

– Large samples for statistical studies (> 300000 detections so far)

– Track prominence eruptions

– Link with filament / flare / CME catalogues

– Monitor impact of prominence eruptions on space weather

Thank you for listening to this last talk!

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Conclusions

13th European Solar Physics Meeting, Rhodes, Greece, 12-16 September 2011 – Nicolas Labrosse – 16/9/2011 11

AIA