Papers from SWICo members
Dario Del Moro, Gianluca Napoletano, Roberta Forte, Luca Giovannelli, Ermanno Pietropaolo, Francesco Berrilli
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. The P−DBM belongs to a family of models that apply a somewhat simplified description of the main interaction the ICME is subject to during its interplanetary journey. The drag−based models (DBMs) assume that beyond a certain heliospheric distance, a simple aerodynamic drag equation can describe the interaction between the ICME and the solar
Ensemble modeling incorporate the intrinsic limitation of information due to measure errors or due to the lack of measure at all, in form of probability distributions. In practice, instead of a single run to forecast an ICME propagation, a set of runs, driven with input parameters extracted from suitable distributions are used to retrieve a distribution of output parameters. 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