2018/01/11 by Gianluca Napoletano, Roberta Forte, Napoletano, Gianluca +12
Earth and Planetary Sciences · Economics, Econometrics and Finance · Physics and Astronomy · #Earth and Planetary Astrophysics (astro-ph.EP) #FOS: Physical sciences #Geophysics (physics.geo-ph) #Geophysics and Gravity Measurements #Monetary Policy and Economic Impact #Solar and Space Plasma Dynamics #Solar and Stellar Astrophysics (astro-ph.SR) #Space Physics (physics.space-ph) #astro-ph.EP #astro-ph.SR #physics.geo-ph #physics.space-ph
paper · pdf · doi:10.48550/arxiv.1801.04201
18 pages, 4 figures
arxiv created 2018/01/11 · openalex publication_date 2018/01/11 · arxiv updated 2018/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 any future manned exploration of the Solar System. As critical as the forecast accuracy is the knowledge of its precision, i.e. the error associated to the estimate. We propose a statistical approach for the computation of the time of arrival using the drag-based model by introducing the probability distributions, rather than exact values, as input parameters, thus allowing the evaluation of the uncertainty on the forecast. We test this approach using a set of CMEs whose transit times are known, and obtain extremely promising results: the average value of the absolute differences between measure and forecast is 9.1h, and half of these residuals are within the estimated errors. These results suggest that this approach deserves further investigation. We are working to realize a real-time implementation which ingests the outputs of automated CME tracking algorithms as inputs to create a database of events useful for a further validation of the approach.