The Role of Short-Term Precursors in a Hybrid CME Forecast

Details The Role of Short-Term Precursors in a Hybrid CME Forecast The Role of Short-Term Precursors in a Hybrid CME Forecast

Dec 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010agufmsh54d..01j&link_type=abstract

American Geophysical Union, Fall Meeting 2010, abstract #SH54D-01

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[7924] Space Weather / Forecasting

Scientific paper

The AFRL Space Weather Forecasting Laboratory (SWFL) was established as a testbed for data, models and techniques used to forecast significant space weather events. Most space weather originates at the Sun with coronal mass ejections (CMEs) being a significant source. When CMEs strike the Earth, they can cause auroras, geomagnetic storms and other hazardous conditions that can adversely affect space and grounds systems and personnel. The longer the advance warning of these phenomena, the more effective and efficient can be the mitigating steps taken by the military and civilian communities. Warning periods between 72 and 120 hours are needed, based on the required lead times necessary for satellite and air tasking orders. However, the magnetic properties and other characteristics of CMEs vary greatly and CMEs travel at variable speeds, taking from one to four days to reach Earth. Often the most geoeffective CMEs travel the fastest and a strictly deterministic approach will not meet the advance warning requirements in these cases. To remedy this, forecasters and system designers must incorporate climatology, persistence, recurrence, and precursory indicators to break the 72 hour barrier. With the long operational record of SOHO and other Solar/Heliospheric instruments we have data to work with for climatology, and with the advent of the Solar Mass Ejection Imager and the STEREO spacecraft, tracking of CMEs has been demonstrated as practical. However, indicators and precursors, minutes to hours before a CME launches, are currently elusive. This talk examines what such precursors might be and how they would fit into a Hybrid CME forecast.

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