Details

Autor(en) / Beteiligte

• Smith, Z. K.
• Dryer, M.
• McKenna‐Lawlor, S. M. P.
• Fry, C. D.
• Deehr, C. S.
• Sun, W.

Titel

Operational validation of HAFv2's predictions of interplanetary shock arrivals at Earth: Declining phase of Solar Cycle 23

Ist Teil von

• Journal of Geophysical Research - Space Physics, 2009-05, Vol.114 (A5), p.A05106-n/a

Ort / Verlag

Washington, DC: American Geophysical Union

Erscheinungsjahr

2009

Quelle

Wiley-Blackwell Journals

Beschreibungen/Notizen

• This is the third in a series of papers showing the performance of the Hakamada‐Akasofu‐Fry version 2 (HAFv2) model in predicting, in the operational environment, the arrival of interplanetary shocks at Earth. The first and second studies covered the time of the rise and maximum of Solar Cycle 23. This study covers the declining phase, through December 2006. The prediction of shock arrivals is important in space weather applications because these events are often followed by geomagnetic disturbances that disrupt human technologies. The HAFv2 uses, for input, a continuously updating background solar wind onto which transient events (interplanetary shocks) are superimposed whenever near‐real‐time observations are reported of a metric type II radio burst and/or a halo or partial halo coronal mass ejection (CME). Supporting inputs are obtained from GOES 1–8 Å X‐ray data and solar images. We present the performance of the model in standard meteorological forecast metrics and compare the accuracy of the three phases of Solar Cycle 23. We find that the accuracy of the model is consistent between the three periods. For this third phase, we show the added confidence in model predictions provided by the presence of halo/partial halo observations. Halo/partial halo CMEs were found to accompany approximately one half of the events. The predictions of this subset of events have a higher level of confidence and success. Thus the observation of a large CME should not be a requirement for a forecast but rather an indication that when one is observed, the confidence in the prediction is greatly increased.