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Analysis of Signal-to-Noise Ratio (SNR) in Coronagraph Observations of Coronal Mass Ejections (CMEs)- Georg-August-Universitaet Goettingen, Germany; Jackie A. Davies - RAL Space, United Kingdom; Matthew J. West - Royal Observatory of Belgium, Belgium; Volker Bothmer - Georg-August-Universität Göttingen, Germany; Bram Bourgoignie - Royal Observatory of Belgium, Belgium; Chris J. Eyles - RAL Space, United Kingdom; Philipp Huke - Georg-August-Universität Göttingen, Germany; Piers Jiggens - European Space Agency, Netherlands; Bogdan Nicula - Royal Observatory of Belgium, Belgium; James Tappin - RAL Space, United Kingdom Session: Space Weather Instrumentation AbstractWe analyse the SNR requirements for the ESA-funded Solar Coronagraph for OPErations (SCOPE) with respect to manual and automatic detection of CMEs in its FOV of 2.5 to 30 Rs. Firstly, SNR values are estimated from SOHO/C3 coronagraph images for a number of CMEs. Additionally, we generate sequences of artificial coronagraph images, each comprising a modelled coronal background and a CME, the latter simulated using the Graduated Cylindrical Shell (GCS) model. Images are created with CME SNR levels between 0.5 and 10 at the outer edge of the FOV and velocities between 700 and 2800 km/s, and then analysed for the detectability of the CME above the noise with the automatic detection tool CACTus. We find that CMEs near the edge of the C3 FOV are typically 2% of the total brightness, with SNR between 1 and 4 at their leading edge. The automated detection of CMEs in our simulated images succeeded well down to SNR = 1 and for CME velocities up to 1400 km/s. At lower SNR/higher velocity, detection started to break down. The results from both approaches confirm that the initial SCOPE design goal of SNR=4 would, if achieved, deliver comparable performance with a compact design. |
Registration opens:
16 July 2020
Abstract submission opens:
16 July 2020
European Space Weather Medals:
6 September 2020
Registration deadline:
25 September 2020
Registration deadline: [extended]
10 October 2020
Abstract submission deadline:
4 September 2020