Parameter Distributions for the Drag‐Based Modeling of CME Propagation

Abstract In recent years, ensemble modeling has been widely employed in space weather to estimate uncertainties in forecasts. We here focus on the ensemble modeling of Coronal Mass Ejections (CME) arrival times and arrival velocities using a drag-based model, which is well-suited for this purpose due to its simplicity and low computational cost. Although ensemble techniques have previously been applied to the drag-based model, it is still not clear how to best determine distributions for its input parameters, namely the drag parameter and the solar wind speed. The aim of this work is to evaluate statistical distributions for these model parameters starting from a list of past CME-ICME events. We employ LASCO coronagraph observations to measure initial CME position and speed, and in situ data to associate them with an arrival date and arrival speed. For each event we ran a statistical procedure to invert the model equations, producing parameters distributions as output. Our results indicate that the distributions employed in previous works were appropriately selected, even though they were based on restricted samples and heuristic considerations. On the other hand, possible refinements to the current method are also identified, such as the dependence of the drag parameter distribution on the CME being accelerated or decelerated by the solar wind, which deserve further investigation. Plain Language Summary Coronal Mass Ejections (CME), consisting of huge expulsions of plasma and magnetic field from the solar corona, are important for space weather. Among several forecasting techniques, the drag-based model, which describes CME propagation in interplanetary space, is widely used to compute CME transit time and impact speed, by describing the CME propagation as that of a solid body moving in an external fluid. In recent years, this model has been improved via a new approach in which statistical distributions of the input quantities are introduced to evaluate uncertainties of the resulting forecasts. Unfortunately, such distributions for the model parameters are still not very well known from experimental observations and it is hard to obtain them from theoretical models. In this work, we built an empirical method to evaluate such statistical distributions using a list of past CME-ICME events. New findings emerged from this analysis, such as a dependence of the drag parameter on the interplanetary coronal mass ejections being accelerated or decelerated, deserve further investigation.