ST4.3

Beyond certain distance the ICME propagation becomes mostly governed by the interaction of the ICME and the ambient solar wind. Configuration of the interplanetary magnetic field and features of the related ambient solar wind in the ecliptic and meridional plane are different. Therefore, one can expect that the inclination of the CME flux rope axis i.e. tilt, influences the propagation of the ICME itself. In order to study the relation between the tilt parameter and the ICME propagation we investigated isolated Earth-impacting CME-ICME evets in the time period from 2006. to 2014. We determined the CME tilt in the “near-Sun” environment from the 3D reconstruction of the CME, obtained by the Graduated Cylindrical Shell model using coronagraphic images provided by the STEREO and SOHO missions. We determined the tilt of the ICME in the “near-Earth” environment using in-situ data. We constrained our study to CME-ICME events that show no evidence of rotation while propagating, i.e. have a similar tilt in the “near-Sun” and “near-Earth” environment. We present preliminary results of our study and discuss their implications for space-weather forecasting using the drag-based(ensemble) [DB(E)M] model of heliospheric propagation.

How to cite: Martinić, K., Dumbović, M., and Vršnak, B.: Influence of the CME orientation on the ICME propagation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2526, https://doi.org/10.5194/egusphere-egu21-2526, 2021.

We present a statistical study on the early evolution of coronal mass ejections (CMEs), to better understand the effect of CME (over)- expansion and how it relates to the production of Solar Energetic Particle (SEP) events. We study the kinematic CME characteristics in terms of their radial and lateral expansion, from their early evolution in the Sun’s atmosphere as observed in EUV imagers and coronagraphs. The data covers 72 CMEs that occurred in the time range of July 2010 to September 2012, where the twin STEREO spacecraft where in quasiquadrature to the Sun-Earth line. From the STEREO point-of-view, the CMEs under study were observed close to the limb. We calculated the radial and lateral height (width) versus time profiles and derived the corresponding peak and mean velocities, accelerations, and angular expansion rates, with particular emphasis on the role of potential lateral overexpansion in the early CME evolution. We find high correlations between the radial and lateral CME velocities and accelerations. CMEs that are associated tend to be located at the high-value end of the distributions of velocities, widths, and expansion rates compared to nonSEP associated events.

How to cite: Adamis, A., Veronig, A., Podladchikova, T., Dissauer, K., Miteva, R., Guo, J., Haberle, V., Dumbovic, M., Temmer, M., Kozarev, K., Magdalenic, J., and Kay, C.: Statistical study of CMEs, lateral overexpansion and SEP events, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3216, https://doi.org/10.5194/egusphere-egu21-3216, 2021.

Coronal mass ejections (CMEs) are arguably one of the most violent explosions in our solar system. CMEs are also one of the most important drivers for space weather. CMEs can have direct adverse effects on several human activities. Reliable and fast prediction of the CMEs arrival time is crucial to minimize such damage from a CME. We present a new pipeline combining machine learning (ML) with a physical drag-based model of CME propagation to predict the arrival time of the CME. We evaluate both standard ML approaches and a combination of ML + probabilistic drag based model (PDBM, Napoletano et al. 2018). More than 200 previously observed geo-effective partial-/full-halo CMEs make up the database for this study (with information extracted from the Richardson & Cane 2010 catalogue, the CDAW data centre CME list, the LASCO coronagraphic images, and the HEK database - Hurlburt et al. 2010). The P-DBM provides us with a reduced computation time, which is promising for space weather forecasts. We analyzed and compared various machine learning algorithms to identify the best performing algorithm for this database of the CMEs. We also examine the relative importance of various features such as mass, CME propagation speed, and height above the solar limb of the observed CMEs in the prediction of the arrival time. The model is able to accurately predict the arrival times of the CMEs with a mean square error of about 9 hours.  We also explore the differences in prediction from ML models and emblem prediction method namely P-DBM model.

How to cite: Tiwari, A., Camporeale, E., Teunissen, J., Foldes, R., Napoletano, G., and Del Moro, D.: Predicting arrival time for CMEs: Machine learning and ensemble methods, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7661, https://doi.org/10.5194/egusphere-egu21-7661, 2021.

The Drag-based Model (DBM) is an analytical model for heliospheric propagation of Coronal Mass Ejections (CMEs) that predicts the CME arrival time and speed at Earth or any other given target in the solar system. It is based on the equation of motion and depends on initial CME parameters, background solar wind speed, w and the drag parameter γ. A very short computational time of DBM (< 0.01s) allowed us to develop the Drag-Based Ensemble Model (DBEM) that considers the variability of model input parameters by making an ensemble of n different input parameters to calculate the distribution and significance of the DBM results. Using such an approach, we apply DBEM to determine the most likely CME arrival times and speeds, quantify the prediction uncertainties and calculate the confidence intervals. Recently, a new DBEMv3 version was developed including the various improvements and Graduated Cylindrical Shell (GCS) option for the CME geometry input as well as the CME propagation visualizations. Thus, we compare the DBEMv3 with previous DBEM versions (e.g. DBEMv2), evaluate it and determine the DBEMv3 performance and errors by using various CME-ICME lists. Compared to the previous versions, the DBEMv3 provides very similar results for all calculated output parameters with slight improvement in the performance. Based on the evaluation performed for 146 CME-ICME pairs, the DBEMv3 performance with mean error (ME) of -11.3 h, mean absolute error (MAE) of 17.3 h was obtained, similar to previous DBM and DBEM evaluations. Fully operational DBEMv3 web application was integrated as one of the ESA Space Situational Awareness portal services (https://swe.ssa.esa.int/current-space-weather) providing an important tool for space weather forecasters.

How to cite: Calogovic, J., Dumbović, M., Sudar, D., Vršnak, B., Martinić, K., Temmer, M., and Veronig, A.: Drag-Based Ensemble Model (DBEM) to predict the heliospheric propagation of CMEs, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7753, https://doi.org/10.5194/egusphere-egu21-7753, 2021.

In the last years, many kinds of CME models, based on a drag-based evolution through interplanetary space, have been developed and are now widely used by the community. The unbeatable advantage of those methods is that they are computationally cheap and are therefore suitable to be used as ensemble models. Additionally, their prediction accuracy is absolutely comparable to more sophisticated models.

The ELlipse Evolution model based on heliospheric imager (HI) observations (ELEvoHI) assumes an elliptic frontal shape within the ecliptic plane and allows the CME to adjust to the ambient solar wind speed, i.e. it is drag-based. ELEvoHI is used as an ensemble simulation by varying the CME frontal shape within given boundary values. The results include a frequency distribution of predicted arrival time and arrival speed and an estimation of the arrival probability.

In this study, we investigate the possibility of not only varying the parameters related to the CME's ecliptic extent but also the ambient solar wind speed for each CME ensemle member. Although we have used a range of +/-100 km/s for possible values of the solar wind speed in the past, only the best candidate was in the end used to contribute to the prediction. We present the results of this approach by applying it to a CME propagating in a highly structured solar wind and compare the frequency distribution of the arrival time and speed predictions to those of the usual ELEvoHI approach.

How to cite: Amerstorfer, T., Hinterreiter, J., Reiss, M. A., Davies, J. A., Möstl, C., Weiss, A. J., Bauer, M., Amerstorfer, U. V., Bailey, R. L., and Harrison, R. A.: Effect of the ambient solar wind speed on drag-based CME prediction accuracy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8932, https://doi.org/10.5194/egusphere-egu21-8932, 2021.

How to cite: Maharana, A., Scolini, C., Raeder, J., and Poedts, S.: Predicting geo-effectiveness of CMEs with EUHFORIA coupled to OpenGGCM, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9854, https://doi.org/10.5194/egusphere-egu21-9854, 2021.

The estimation of the Coronal Mass Ejection (CME) arrival is an open issue in the field of Space Weather. Many models have been developed to predict Time-of-Arrival (ToA). In this work, we utilize an updated version of the Effective Acceleration Model (EAM) to calculate the ToA. The EAM predicts the ToA of the CME-driven shock and the sheath's average speed at 1 AU. The model assumes that the interaction between the ambient solar wind and the interplanetary CME (ICME) results in constant acceleration or deceleration. We recently compared EAM against ENLIL and drag based models (DBEM) with a sample of 16 CMEs. We confirmed the well-known fact that the deceleration of fast ICMEs in the interplanetary medium is not captured by most models. We study further the deceleration of fast ICMEs by introducing, for the first time, wide-angle observations by the STEREO heliospheric imagers into the EAM model. The speed profiles for some test cases show deceleration in the interplanetary medium at greater distances compared with the field-of-view of the coronagraphs.

How to cite: Paouris, E., Vourlidas, A., Papaioannou, A., and Anastasiadis, A.: The CME arrival prediction with the Effective Acceleration Model: Further testing with heliospheric imaging observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10254, https://doi.org/10.5194/egusphere-egu21-10254, 2021.

Previous studies of Coronal Mass Ejections (CMEs) have shown the importance of understanding their geometrical structure and internal magnetic field configuration for improving forecasting at Earth. The precise prediction of the CME shock and the magnetic cloud arrival time, their magnetic field strength and the orientation upon impact at Earth is still challenging and relies on solar wind and CME evolution models and precise input parameters. In order to understand the propagation of CMEs in the interplanetary medium, we need to understand their interaction with the complex features in the magnetized background solar wind which deforms, deflects and erodes the CMEs and determines their geo-effectiveness. Hence, it is important to model the internal magnetic flux-rope structure in the CMEs as they interact with CIRs/SIRs, other CMEs and solar transients in the heliosphere. The spheromak model (Verbeke et al. 2019) in the heliospheric wind and CME evolution simulation EUHFORIA (Pomoell and Poedts, 2018), fits well with the data near the CME nose close to its axis but fails to predict the magnetic field in CME legs when these impact Earth (Scolini et al. 2019). Therefore, we implemented the FRi3D stretched flux-rope CME model (Isavnin, 2016) in EUHFORIA to model a more realistic CME geometry. Fri3D captures the three-dimensional magnetic field structure with parameters like skewing, pancaking and flattening that quantify deformations experienced by an interplanetary CME. We perform test runs of real CME events and validate the ability of FRi3D coupled with EUHFORIA in predicting the CME geo-effectiveness. We have modeled two real events with FRi3D. First, a CME event on 12 July 2012 which was a head-on encounter at Earth. Second, the flank CME encounter of 14 June 2012 which did not leave any magnetic field signature at Earth when modeled with Spheromak. We compare our results with the results from non-magnetized cone simulations and magnetized simulations employing the spheromak flux-rope model. We further discuss how constraining observational parameters using the stretched flux rope CME geometry in FRi3D affects the prediction of the magnetic field strength in our simulations, highlighting improvements and discussing future perspective.

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0)

How to cite: Poedts, S., Maharana, A., Scolini, C., and Isavnin, A.: Predicting geo-effectiveness of CMEs using a novel 3D CME model FRi3D integrated into EUHFORIA, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11605, https://doi.org/10.5194/egusphere-egu21-11605, 2021.

Due to their simplicity and relatively short computational time, empirical models for Solar Wind Transients, based on a restricted number of assumptions and on the values of a small set of parameters, play an important role in Space Weather forecasting. For this reason, an optimal choice of values for the model parameters is of critical importance in this approach. In this work, we compiled a list of CME events by merging and cross-referencing several databases and made use of such experimental data to evaluate statistical distributions for the model parameters of a chosen forecasting model for ICME arrivals, namely the Drag-Based model. Our results lead to several considerations and refinements to be implemented in the future in this and other forecasting models.

How to cite: Napoletano, G., Foldes, R., Berrilli, F., Calchetti, D., de Gasperis, G., Del Moro, D., Kumar Tiwari, A., Teunissen, J., and Camporeale, E.: Investigating the drag-based model parameters through statistical methods, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13434, https://doi.org/10.5194/egusphere-egu21-13434, 2021.