A Probabilistic Approach to the Drag-Based Model

Abstract

-The forecast of the time of arrival (ToA) 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 ToA 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.

Exploring Thermospheric Variations Triggered by Severe Geomagnetic Storm on 26 August 2018 Using GRACE Follow‐On Data

“…The cause can be a southward oriented magnetic field of the ICME itself that reconnects with the Earth's northward magnetic field or strong compression due to the shock‐sheath structure that is produced by the interaction with a slower surrounding solar wind flow Gosling et al (). The interaction process with the collisionless plasma in the interplanetary space and subsequent ICME propagation behavior can be described by the magnetohydrodynamic equivalent of the aerodynamic drag force (Cargill, ; Napoletano et al, ; Vršnak et al, ).…”

The Tor Vergata Synoptic Solar Telescope (TSST): A robotic, compact facility for solar full disk imaging

“…TSST Magnetograms can be used to estimate the flare probability of active regions using the R value, i.e. the total unsigned magnetic flux introduced by Schrijver (2007) (Napoletano et al, 2018;Berrilli et al, 2019b).…”

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

“…The P−DBM makes use of probability distributions, rather than exact values, as input parameters, to model the CME propagation in the interplanetary space, allow− ing us to forecast ICME arrival times and velocities and to evaluate also the uncertainty on the forecast. Details on the implementation and an extended description are in Napoletano et al (2018). In the following, we briefly introduce some concept and present an example of the validation outputs.…”

“…: Daglis, 2001;Schrijver and Siscoe, 2010], and the space−weather centers employ different methods to model and predict the propagation of ICMEs. Among those, the Space Weather Prediction Center of the National Oceanic and Atmospheric Administration 1 , SWPC/NOAA, in USA, and the Met Office Space Weather Operations Centre 2 in UK, employ the WSA−ENLIL+Cone model [Odstrcil et al, 2004], while the Galileo Ionosphere Prediction Serv− ice [Albanese et al, 2018] and the SWERTO 3 regional service [Berrilli et al, 2018] in Italy employs the Prob− abilistic−Drag Based Model [P−DBM − Napoletano et al, 2018].…”