andrzej fludra algorithm for automatic detection of coronal dimming as a tool for predicting cme’s...

Andrzej Fludra

Algorithm for automatic detection of coronal dimming as a tool for predicting CME’s

Danielle Bewsher & Richard Harrison

Presented by Andrzej Fludra


Introduction• CME related coronal (x-ray) dimming first seen with Skylab

– Rust & Hildner, 1976; Rust, 1983• Also observed with

– Yohkoh • e.g Watanabe et al., 1992; Sterling & Hudson, 1997;

Gopalswamy & Hanaoka, 1998– EIT

• e.g Zarro et al., 1999– CDS

• Only detailed spectral analysis• e.g Harrison & Lyons, 2000; Harrison et al., 2003

• If dimming identifies low coronal source– Analyse source plasma before onset– Possibility of CME prediction?


CME Prediction• Can we predict a CME onset

– No of pixels with decrease in intensity – Using different emission lines

• If successful at limb, then extend to disk.

• Basic scheme – Scan Mg IX and Fe XVI EJECT mosaics – 1996 to 2005: 178 datasets suitable for use – Automated procedure.

• If contiguous set of pixels (predefined minimum number)• Show decrease in intensity beyond specified limit • Define a CME alarm.

• Compare alarms CME lists– CACTUS


CDS Observations• EJECT studies started mid-1996

– JOP67• Mosaic of three 4 arcmin fields• Exposure: 10 s• 4 x 240 arcsec slit (60 locations)• Cadence: 50 min• Six emission lines:

– He I 584 Å (20,000 K)– O V 629 Å (250,000 K)– Mg IX 368 Å (1 million K)– Fe XVI 360 Å (2 million K)– Si X 347/356 Å (1.3 million K)

• Trade off – Cadence– Plasma diagnostic tools

• Plasma diagnostics of CME source– Only CDS can do


Classic Dimming Example


CME Prediction Algorithm• Prep/calibrate data• Remove background

– Assume constant background in space– Variable in time and wavelength

• Make mosaics from individual rasters• Make fixed difference dataset

– Reference for fixed difference• Find pixels where fixed difference is significant

– If abs(difference) > statistical error• Block out pixels on disk• Group pixels with dimming together space and time

– Any of 8 surrounding pixels in space – Same pixels at t - 1 and t + 1

• Group neglected if – Number of pixels in group < 1% of pixels in space-time volume


Checking CME Prediction

• IF significant dimming observed in CDS– in enough pixels in space-time volume– in either Mg IX OR Fe XVI – THEN raise alarm

• Check against CME list– CACTUS (ROB, automated)

• IF CME identified in list– same time range (±1 hour) – same position range (±10°)

• AND CDS alarm has been raised• THEN

– Successful alarm


Mg IX data


Mg IX fixed difference


Mg IX Significant Dimming


Comparison


Results

• Dimming identified in Mg IX– 4% of pixels

• No dimming identified in Fe XVI• CDS alarm raised• CACTUS identified CME in same location and time• Successful alarm


Results

• Analysing 20 CDS datasets in 2000– Alarms: 15– Successful: 10– False: 5

• Better than 50:50!• Of the 15 alarms dimming observed in

– Only Mg IX: 5 datasets– Only Fe XVI: 3 datasets– Both Mg IX and Fe XVI: 7 datasets

• Majority of datasets have active region on limb


Future Work

• Extend comparison to CDAW list• Do CME lists have every CME?

– If CDS raises alarm, but no CME in list, check LASCO data?• Analyse more CDS datasets• More development

– Reference frame for fixed difference– Criteria for maintaining group– Significance of group dimming– Include disk pixels in analysis– Search CME lists in time range of dimming only, not in time

range of whole of CDS observations• Watch this space!


Fe XVI Data


Fe XVI Fixed Difference


Fe XVI Significant Dimming

• No significant dimming!

andrzej fludra algorithm for automatic detection of coronal dimming as a tool for predicting cme’s...

Documents

cme alarm

significant dimming

data slide

fixed difference slide

cme onset

time successful alarm

cds alarm

number of pixels