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BEGIN:VEVENT
DTSTAMP:20260428T033000Z
DTSTART;VALUE=DATE-TIME:20240116T150000
DTEND;VALUE=DATE-TIME:20240116T160000
SUMMARY:Siegfried Gonzi (MET Office): The Met Office’s Operational Corona
 l Mass Ejection (CME) Prediction System
TZID:Europe/London
UID:20240116-8a17841a8ce92c70018cf32f645306eb@warwick.ac.uk
CREATED:20240111T141613Z
DESCRIPTION:Abstract: MOSWOC (Met Office Space Weather Operations Centre)
  started providing CME arrival time forecasts in 2014. CMEs consist of p
 lasma that travel from the Sun to Earth at hundreds of kilometers per se
 conds. Earth directed CMEs can lead to significant disruptions to electr
 icity power generation\, Global Navigation Satellite System positioning 
 and satellite orbit tracking. Typical travel times of CMEs from the Sun 
 to Earth are 2 to 4 days. It is important to model the evolution of the 
 CMEs as soon as they have been observed in coronagraph images. There are
  many processes involved before a forecast can be issued. Each of these 
 processes generates its own problems due to lack of the perfect observat
 ions and models. MOSWOC’s Sun to Earth model is initialized by boundary 
 conditions which are imperfect and the CME parameters that go into the m
 odel have to be derived\, from a CME Analysis Tool (CAT)\, by human fore
 casters. Given all these uncertainties one single model forecast is hard
 ly a good representation of the true state\, and a space weather forecas
 ter would never trust it. I describe in this talk our CME ensemble predi
 ction system which is used to deal with the uncertainties in the data an
 d models that otherwise would lead to inadequate forecasts. But even wit
 h an ensemble prediction system the CME arrival time error can exceed +-
 24 hours. I will also discuss our future plans for improving the CME for
 ecasting system at the Met Office.
LOCATION:L3
CATEGORIES:CFSA Seminar
LAST-MODIFIED:20240111T141613Z
ORGANIZER;CN=Anne-Marie Broomhall:
END:VEVENT
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