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

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as
Coronal Mass Ejections (CMEs), in order to improve our ability to forecast them and reduce the risk to our
technologically driven society. To do this, it is crucial to assess the application of theoretical models or even to
create models that are entirely data-driven. The quality and availability of suitable data are of paramount
importance. We have already merged public data about CMEs from both in-situ and remote instrumentation in
order to build a database (DB) of CME properties. To evaluate the accuracy of such a DB and confirm the
relationship between in-situ and remote observations, we have employed the drag-based model (DBM). DBM is an
analytical model that assumes the aerodynamic drag caused by the surrounding solar wind to be the primary factor
in the interplanetary propagation of CMEs. Here, we explore the parameter space for the drag parameter and solar
wind speed using a Monte Carlo approach to analyse how well the DBM described the propagation of CMEs. With
this method, we validate and/or correct the initial hypotheses about solar wind speed, and also yield additional
information 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.