Coronal Mass Ejections that impact Earth drive the most severe space weather. To better enable effective space weather mitigation plans, there is much interest in improving the quality of CME arrival time predictions, particularly by quantifying and reducing the prediction uncertainty. A limited set of observatories, challenges in interpreting observation data, and limiting assumptions in CME parameterisations all play important roles in the uncertainty of the predicted CME evolution.

Data assimilation techniques provide a path for improving the predictive skill, by integrating observations into a modelling framework in a way that returns model states that better reflect the true state of a system. Furthermore, such techniques can self-consistently account for uncertainty in the observations, and uncertainty in the models structure and parameterisations.

We present some early results from our work to build a particle filter data assimilation scheme around the HUXt solar wind model. Assimilating the time-elongation profiles of CME flanks observed by the Heliospheric Imagers on NASAs STEREO mission, we demonstrate that such methods have good potential to improve modelled CME arrival time predictions. Using a simulation study, we present an estimate of the potential CME arrival time prediction improvements gained by using this particle-filter approach with an L5 Heliospheric Imager.

How to cite: Barnard, L., Owens, M., Scott, C., and Lang, M.: Improving CME modelling with data assimilation of Heliospheric Imager observations into the HUXt solar wind numerical model., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-192, https://doi.org/10.5194/egusphere-egu21-192, 2020.

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.

We present the first results of our newly developed CME arrival prediction model, which allows the CME front to deform and adapt to the changing solar wind conditions. Our model is based on ELEvoHI and makes use of the WSA/HUX (Wang-Sheeley-Arge/Heliospheric Upwind eXtrapolation) model combination, which computes large-scale ambient solar wind conditions in the interplanetary space. With an estimate of the solar wind speed and density, we are able to account for the drag exerted on different parts of the CME front. Initially, our model relies on heliospheric imager observations to confine an elliptical CME front and to obtain an initial speed and drag parameter for the CME. After a certain distance, each point of the CME front is propagating based on the conditions in the heliosphere. In this case study, we compare our results to previous arrival time predictions using ELEvoHI with a rigid CME front. We find that the actual arrival time at Earth and the arrival time predicted by the new model are in very good agreement.

How to cite: Hinterreiter, J., Amerstorfer, T., Reiss, M. A., Weiss, A. J., Möstl, C., Temmer, M., Bauer, M., Bailey, R. L., and Amerstorfer, U. V.: CME arrival time predictions with a deformable front, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5830, https://doi.org/10.5194/egusphere-egu21-5830, 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.

Interaction of solar events propagating throughout the interplanetary space with the magnetic field of the Earth may result in disruption of the magnetosphere. Disruption of the magnetic field is followed by the formation of the time-varying electric field and thus electric current is induced in Earth-bound structures such as transmission networks, pipelines or railways. In that case, it is necessary to be able to predict a future state of the magnetosphere and magnetic field of the Earth. The most straightforward way would use geomagnetic indices. Several studies are investigating the relationship of the response of the magnetosphere to changes in the solar wind with motivation to give a more accurate prediction of geomagnetic indices during geomagnetic storms. To forecast these indices, different approaches have been attempted--from simple correlation studies to neural networks.

We study the effects of interplanetary shocks observed at L1 on the Earth's magnetosphere with a database of tens of shocks between 2009 and 2019. Driving the magnetosphere is described as integral of reconnection electric field for each shock. The response of the geomagnetic field is described with the SYM-H index. We created an algorithm in Python for prediction of the magnetosphere state based on the correlation of solar wind driving and magnetospheric response and found that typical time-lags range between tens of minutes to maximum 2 hours. The results are documented by a large statistical study.

How to cite: Výbošťoková, T., Němeček, Z., and Šafránková, J.: Magnetospheric response to solar wind driving, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8951, https://doi.org/10.5194/egusphere-egu21-8951, 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.

Coronal mass ejections (CMEs), the most violent eruptive phenomena occurring in the heliosphere, erupt in the form of gigantic clouds of magnetized plasma from the Sun and can reach Earth within several hours to days. If the magnetic field inside an Earth-directed CME or its associated sheath region has a southward directed component (Bz), then it interacts stronger with the Earth’s magnetosphere, leading to severe geomagnetic storms. Therefore, it is crucial to predict the magnitude and orientation of Bz inside an Earth impacting interplanetary CME (ICME) in order to forecast the intensity of the resulting geomagnetic storms. However, due to lack of realistic inputs and the complexity of the Sun-Earth system in a time-dependent heliospheric context, it is very difficult to perform a reliable forecast of Bz at 1 AU.  

In this work, we use recently developed observational techniques to constrain the kinematic and magnetic properties of CME flux ropes. Using those observational properties as realistic inputs, we construct an analytical force free flux rope model to mimic the magnetic structure of a CME and simulate its evolution from Sun to Earth using the “European heliospheric forecasting information asset” (EUHFORIA). In order to validate our tool, we simulate an Earth-directed CME event on 2013 April 11 and compare the simulation results with the in-situ observations at 1 AU. Further, we assess the performance of EUHFORIA in forecasting of Bz, using different flux rope models like spheromak and torus.  The results obtained from this study help to improve our understanding to build the steppingstones towards the forecasting of Bz in near real time.

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: Sarkar, R., Pomoell, J., Asvestari, E., Kilpua, E., Mierla, M., Rodriguez, L., and Poedts, S.: On the prediction of magnetic field vectors of ICME using data constrained simulation with EUHFORIA, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10325, https://doi.org/10.5194/egusphere-egu21-10325, 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.

Halo coronal mass ejections (CMEs) are one of the most effective drivers of intense geomagnetic storms. Despite the recent advances in space weather forecasting, the accurate arrival prediction of halo CMEs remains a challenge.  This is because in general CMEs interact with the background solar wind during their propagation in the interplanetary space. In addition, in the case of halo CMEs, the accurate estimation of their kinematics is difficult due to projection effects in the plane-of-sky.

In this study, we are revisiting the arrival of twelve geoeffective Earth-directed fast halo CMEs using an empirical and a numerical approaches. For this purpose we refine the input to the Drag-based Model (DBM) and to the EUropean Heliospheric Forecasting Information Asset (EUHFORIA), which are recently available for users from the ESA Space Situational Awareness Portal (http://swe.ssa.esa.int).

The DBM model has been tested using different values for the input drag parameter.  On average, the predicted arrival times are confined in the range of ± 10 h. The closest arrival to the observed one has been achieved with a drag value higher than the recommended for fast CMEs. Setting a higher drag also helped to obtain a closer to the observed CME arrival speed prediction. These results suggest that the exerted solar wind drag was higher than expected. Further, we are searching for clues about the CME propagation by performing EUHFORIA runs using the same CME kinematics. Preliminary results show that both models perform poorly for CMEs that have possibly undergone CME-CME interaction, underlying again the importance of taking into account the state of the interplanetary space in the CME forecast.

How to cite: Yordanova, E., Dumbovic, M., Temmer, M., Scolini, C., Magdalenic, J., J. Thompson, W., Sorriso-Valvo, L., P. Dimmock, A., and Rosenqvist, L.: Comparative study of halo CME arrival predictions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14187, https://doi.org/10.5194/egusphere-egu21-14187, 2021.