engleski

Statistical Model for Predicting Arrival and Geoeffectiveness of CMEs Based on near Real‐Time Remote Solar Observations

One of main issues of space weather is the timely prediction of strong geomagnetic storms, mainly caused by coronal mass ejections (CMEs) arriving at Earth. However, with current knowledge on CMEs, we are not yet able to predict the arrival time, velocity and magnetic field, or even if it will hit or entirely miss the Earth. Therefore, an empirical statistical model was established and implemented that can be used as an early geomagnetic storm warning. For every detected CME, the alert system provides a probability estimation of both arrival and geoeffectiveness using near‐real time remote observations of CMEs and associated flares. The probability estimation for CME arrival resulted from an analysis of front‐sided halo CMEs. For each of these CMEs the relationship with an Interplanetary CME (ICME) was identified based on in‐situ data. As such an empirical probabilistic relationship was established for the CME arrival based on the source position. The statistical geoeffectiveness model was set up using a dataset of front‐sided, solar flare‐associated CMEs and association was made with a specific Dst (disturbance storm time) index. This sample contains geoeffective and non‐geoeffective CMEs. The results of an extensive statistical analysis confirmed some previously known connections between remote solar properties and geomagnetic storms, namely the importance of CME speed, apparent width, source position and associated solar flare type. We quantify these relationships and use them to construct a statistical model for predicting the probability of geomagnetic storm level. Both probability models for CME arrival and geoeffectiveness are combined to provide a geomagnetic storm alert in case of CME detection. This work has received funding from the European Commission FP7 Project COMESEP (263252).

space weather ; coronal mass ejections ; geomagnetic storms

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