Autonomous ! CME! Detection ! FOR ! Heliospheric! Imager 2: ! !

1! 2

Lauren Biddle1, Tim Howard2 !

Coronal Mass Ejections!

Leading Edge!Effect Earth’s magnetosphere!!Disrupts Radio Transmission!!Damage to satellites and power grids!!Airliner passengers at risk!!

SOHO/LASCO  C3  

SMEI!

Written by previous REU students!!analyzed data from !the Solar Mass Ejection Imager!(SMEI)!!Images provided an entire view of the !“sky”!!Has since been decommissioned. ! !

Image taken May, 2003!

The images used for the program used as the basis for the design of our newest leading edge detection

method!

CLED_S!Data were extremely noisy!!²  Hot pixels!²  Zodiacal light!²  Stars/planets!²  moon!²  Shutters!²  magnetosphere !

Resulted in !false positives!

Proof of concept:!!It can be done better!

STEREO!

Images  generated  from  stereo-­‐ssc.nascom.nasa.gov  

A!B!

SECCHI!S un !E arth !C onnection !C oronal and !H eliospheric ! I nvestigation!

Images  from  stereo.gsfc.nasa.gov  

SECCHI!

Images  from  stereo.gsfc.nasa.gov  

Heliospheric! Imager 2!

FOV!

HI!

Earth!A geometrical representation of the HI-2B FOV!

Defise  et  al.  (2001)  

earth!

Elon!

PA!

Heliospheric! Imager 2!

PA!

Elon!

CLED_HI !

Utilizes IDL SolarSoft routines! and CLEDS techniques to! isolate the coordinates of! the leading edge of a CME!

CME Leading Edge Detection for Heliospheric Imagers!

CLED_HI !

Elon

gaCo

n  

PosiCon  Angle  Tappin  et  al.  (2012)  

1! After rotating coordinates, !stack images into a cube !

CLED_HI !

El

on

ga

tio

n!

time!

“J-Map”!

!Note the log scale!

Liu  et  al.  (2010)  

CLED_HI !

CLED_HI !2! Parsing!

CLED_HI !CLED_HI !3! Hough

Transform!

Accumulator space θ-ρ !

Real space!ε- t!

a! b!

c!d!

θ-ρ !ε- t!

e!f!

[A] J-map!![B] ‘Hough transformed’!![C] after the threshold ! is applied!![D] transformed back! into real space!![E] resultant image ! from edge detection! routine!![F] final j-map with ! intensity mask!tappin et al. (2012)!

SMEI (Solar mass ejection imager)  

                               

CLED_HI !CLED_HI !

advantages!

reduces bias from subjectivity of human perception!

CLEDHI provides consistency in the identification of CMEs!

Can assist in the enhancement of space weather prediction tools!

3D models!One example:!

Tappin-Howard Model!

Earth!

TH Model!

Can use leading edge coordinates from HI!!Returns CME’s structural and kinetic information ! !² Location!² Trajectory!² Speed!² Structure!!!Fits model using geometric relations!!Estimate arrival time and speed!Tappin  &  Howard  (2009)  

Future Work!Earth will be out of FOV  

Projected position on January 1, 2013  

can be used with hi-1 images as well!

can be made for precise for the scientific understanding of CMEs!

Easily Adaptable:!

adaptable to the next generation of Heliospheric imagers !

Recap!² CLEDHI is a

for HI-2, based off of CLEDS, designed for SMEI images!

² CLEDHI’s methods utilize to

identify a cme !

when identifying and classifying cmes !

² Leading edge coordinates

for space weather prediction!

for scientific research and future generations of Heliospheric Imagers!

Thank You!

Special thanks to:!

² My advisor, Dr. Tim Howard!

² Marty, Erin and the entire! LASP REU program!

² NSF !

References!Defise,  J.-­‐M.,  Halain,  J.-­‐P.,  Mazy,  E.,  et  al.  2001,  ,  4498,  63 !Tappin,  S.J.,  &  Howard,  T.A.,  2009,  Space  Sci.  Rev.,  147,  55-­‐87  Tappin,  S.  J.,  Howard,  T.  A.,  Hampson,  M.  M.,  Thompson,  R.  N.,  &  Burns,  C.  E.  2012,  Journal  of  Geophysical  Research  (Space  Physics),  117,  5103