One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such asCoronal Mass Ejections (CMEs), in order to improve our ability to forecast them and reduce the risk to ourtechnologically driven society. To do this, it is crucial to assess the application of theoretical models or even tocreate models that are entirely data-driven. The quality and availability of suitable data are of paramountimportance. We have already merged public data about CMEs from both in-situ and remote instrumentation inorder to build a database (DB) of CME properties. To evaluate the accuracy of such a DB and confirm therelationship between in-situ and remote observations, we have employed the drag-based model (DBM). DBM is ananalytical model that assumes the aerodynamic drag caused by the surrounding solar wind to be the primary factorin the interplanetary propagation of CMEs. Here, we explore the parameter space for the drag parameter and solarwind speed using a Monte Carlo approach to analyse how well the DBM described the propagation of CMEs. Withthis method, we validate and/or correct the initial hypotheses about solar wind speed, and also yield additionalinformation about CMEs. Using a data-driven approach, this procedure allows us to present a homogeneous,reliable, and robust dataset for the investigation of CME propagation.

Mugatwala, R., Francisco, G., Chierichini, S., Napoletano, G., Foldes, R., DEL MORO, D., et al. (2023). A revised Database of CME characteristics from in-situ and remote observations. In EGU23, the 25th EGU General Assembly, held 23-28 April, 2023 in Vienna, Austria and Online. Online at https://egu23.eu/, id. EGU-15961 [10.5194/egusphere-egu23-15961].

A revised Database of CME characteristics from in-situ and remote observations

Ronish Mugatwala;Gregoire Francisco;Simone Chierichini;Gianluca Napoletano;Dario Del Moro;Luca Giovannelli;Giancarlo de Gasperis;
2023-01-01

Abstract

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such asCoronal Mass Ejections (CMEs), in order to improve our ability to forecast them and reduce the risk to ourtechnologically driven society. To do this, it is crucial to assess the application of theoretical models or even tocreate models that are entirely data-driven. The quality and availability of suitable data are of paramountimportance. We have already merged public data about CMEs from both in-situ and remote instrumentation inorder to build a database (DB) of CME properties. To evaluate the accuracy of such a DB and confirm therelationship between in-situ and remote observations, we have employed the drag-based model (DBM). DBM is ananalytical model that assumes the aerodynamic drag caused by the surrounding solar wind to be the primary factorin the interplanetary propagation of CMEs. Here, we explore the parameter space for the drag parameter and solarwind speed using a Monte Carlo approach to analyse how well the DBM described the propagation of CMEs. Withthis method, we validate and/or correct the initial hypotheses about solar wind speed, and also yield additionalinformation about CMEs. Using a data-driven approach, this procedure allows us to present a homogeneous,reliable, and robust dataset for the investigation of CME propagation.
EGU General Assembly 2023
2023
Rilevanza internazionale
2023
Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre
Settore PHYS-05/B - Fisica del sistema Terra, dei pianeti, dello spazio e del clima
English
https://doi.org/10.5194/egusphere-egu23-15961
Intervento a convegno
Mugatwala, R., Francisco, G., Chierichini, S., Napoletano, G., Foldes, R., DEL MORO, D., et al. (2023). A revised Database of CME characteristics from in-situ and remote observations. In EGU23, the 25th EGU General Assembly, held 23-28 April, 2023 in Vienna, Austria and Online. Online at https://egu23.eu/, id. EGU-15961 [10.5194/egusphere-egu23-15961].
Mugatwala, R; Francisco, G; Chierichini, S; Napoletano, G; Foldes, R; DEL MORO, D; Erdelyi, R; Giovannelli, L; DE GASPERIS, G; Camporeale, E
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/391030
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