Demonstration of method to evaluate in the operational environment space weather models that predict shock arrivals and geomagnetic disturbances using solar and interplanetary data for input

Details Demonstration of method to evaluate in the operational environment space weather models that predict shock arrivals and geomagnetic disturbances using solar and interplanetary data for input Demonstration of method to evaluate in the operational environment space weather models that predict shock arrivals and geomagnetic disturbances using solar and interplanetary data for input

Dec 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002esasp.506..205s&link_type=abstract

In: Solar variability: from core to outer frontiers. The 10th European Solar Physics Meeting, 9 - 14 September 2002, Prague, Cze

Physics

Interplanetary Disturbances, Space Weather, Predictions

Scientific paper

The ability to predict the arrival of interplanetary disturbances (shocks, ejecta and magnetic clouds) at or near Earth is of great interest in space weather because of their relationship to geomagnetic storms. A number of models have been developed for this purpose. It is important to provide, for each model, verification using standard statistical techniques to enable the intercomparison of different models, and to test the models in an operational environment. This paper compares the prediction capabilities of five models based on solar observations and one based on measurements at L1. Three of the models initiated at the Sun are based on metric type II radio burst observations of coronal shocks and two use white light observations of halo/partial-halo coronal mass ejections. The prediction technique at L1 uses low-energy energetic ion measurements of shock-accelerated energetic ion enhancements (EIEs). The time period of the study is January-May, 2002. The predictions are compared to shocks observed by the ACE spacecraft and to geomagnetic activity as measured by Kp. Although the data sample is small, the statistical inter-comparison of the results of these models is presented to demonstrate the method and illustrate some of the difficulties in making quantitative assessment of model effectiveness.

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