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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Neal, J.S. Nichols, T.F. Townsend, L.W. |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Nucl. Eng., Tennessee Univ., Knoxville, TN, USA (Neal, J.S.; Nichols, T.F.; Townsend, L.W.) |
| Abstract | Predicting large solar energetic particle (SEP) events before onset at the Sun is beyond our current forecasting capability. There is, however, a high correlation between large SEP events and fast, coronal mass ejections (CMEs). Event-triggered forecasting methodologies can utilize (1) solar observables such as CME speed, width, or longitude prior to particle arrival at a monitoring spacecraft and/or (2) arriving particle properties such as intensity or energy spectra. It has been proposed that proton intensities on the stream-limited plateau present a minimal radiation hazard to astronauts, and hazardous intensities can occur upon CME-driven shock arrival at the spacecraft. It then follows, that forecasts need only predict the arrival time and severity of the shock prior to its arrival at the spacecraft. Ongoing efforts seek to predict the time of arrival and particle flux magnitude of shocks in order to provide a one hour warning of shock impact at Earth. In order to evaluate the correctness of this proposal, we evaluate five large events for imparted dose prior to and after shock arrival. We also discuss the implications of our results for event-triggered methodologies. |
| Starting Page | 704 |
| Ending Page | 711 |
| File Size | 450512 |
| Page Count | 8 |
| File Format | |
| ISBN | 0780388704 |
| DOI | 10.1109/AERO.2005.1559361 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-03-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Load forecasting Electric shock Space vehicles Weather forecasting Protons Earth Sun Hazards Storms Monitoring |
| Content Type | Text |
| Resource Type | Article |
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