Forecasting the 2018 February 12th CME propagation with the P-DBM model: a fast warning procedure

Abstract

The forecast of the time of arrival of a Coronal Mass Ejection (CME) to Earth is of critical importance for our high−technology society and for the Earth’s upper atmosphere status and LEO satellites. We realized a procedure based on the Drag−Based Model which uses probability distributions, rather than exact values, as input parameters, and allows the evaluation of the uncertainty on the forecast. We tested this approach using a set of CMEs whose transit times are known, obtaining extremely promising results.

We realized a real−time implementation of this algorithm which ingests the outputs of automated CME tracking algorithms as inputs to provide early warning for those CME approaching Earth. We present the results of this real−time fast warning procedure for the case of the 2018 February 12th CME.