Accurate forecasting of the properties of coronal mass ejections (CMEs) as they approach Earth is now recognized as an important strategic objective for both NOAA and NASA. The time of arrival of such events is a key parameter, one that had been anticipated to be relatively straightforward to constrain. In this study, we analyze forecasts submitted to the Community Coordinated Modeling Center at NASA's Goddard Space Flight Center over the last 6 years to answer the following questions: (1) How well do these models forecast the arrival time of CME‐driven shocks? (2) What are the uncertainties associated with these forecasts? (3) Which model(s) perform best? (4) Have the models become more accurate during the past 6 years? We analyze all forecasts made by 32 models from 2013 through mid‐2018, and additionally focus on 28 events, all of which were forecasted by six models. We find that the models are generally able to predict CME‐shock arrival times—in an average sense—to within ±10 hr, but with standard deviations often exceeding 20 hr. The best performers, on the other hand, maintained a mean error (bias) of −1 hr, a mean absolute error of 13 hr, and a precision (standard deviation) of 15 hr. Finally, there is no evidence that the forecasts have become more accurate during this interval. We discuss the intrinsic simplifications of the various models analyzed, the limitations of this investigation, and suggest possible paths to improve these forecasts in the future.

Aims.We introduce a new model for coronal mass ejections (CMEs) that has been implemented in the magnetohydrodynamics (MHD) inner heliosphere model EUHFORIA. Utilising a linear force-free spheromak (LFFS) solution, the model provides an intrinsic magnetic field structure for the CME. As a result, the new model has the potential to predict the magnetic components of CMEs at Earth. In this paper, we present the implementation of the new model and show the capability of the new model. Methods. We present initial validation runs for the new magnetised CME model by considering the same set of events as used in the initial validation run of EUHFORIA that employed the Cone model. In particular, we have focused on modelling the CME that was responsible for creating the largest geomagnetic disturbance (Dst index). Two scenarios are discussed: one where a single magnetised CME is launched and another in which we launch all five Earth-directed CMEs that were observed during the considered time period. Four out of the five CMEs were modelled using the Cone model. Results. In the first run, where the propagation of a single magnetized CME is considered, we find that the magnetic field components at Earth are well reproduced as compared to in-situ spacecraft data. Considering a virtual spacecraft that is separated approximately seven heliographic degrees from the position of Earth, we note that the centre of the magnetic cloud is missing Earth and a considerably larger magnetic field strength can be found when shifting to that location. For the second run, launching four Cone CMEs and one LFFS CME, we notice that the simulated magnetised CME is arriving at the same time as in the corresponding full Cone model run. We find that to achieve this, the speed of the CME needs to be reduced in order to compensate for the expansion of the CME due to the addition of the magnetic field inside the CME. The reduced initial speed of the CME and the added magnetic field structure give rise to a very similar propagation of the CME with approximately the same arrival time at 1 au. In contrast to the Cone model, however, the magnetised CME is able to predict the magnetic field components at Earth. However, due to the interaction between the Cone model CMEs and the magnetised CME, the magnetic field amplitude is significantly lower than for the run using a single magnetised CME. Conclusions. We have presented the LFFS model that is able to simulate and predict the magnetic field components and the propagation of magnetised CMEs in the inner heliosphere and at Earth. We note that shifting towards a virtual spacecraft in the neighbourhood of Earth can give rise to much stronger magnetic field components. This gives the option of adding a grid of virtual spacecrafts to give a range of values for the magnetic field components.

Accurate forecasting of the arrival time and subsequent geomagnetic impacts of coronal mass ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress toward defining community-agreed metrics and validation methods to assess the current state of CME modeling capabilities. This will allow the community to quantify our current capabilities and track progress in models over time. First, it is crucial that the community focuses on the collection of the necessary metadata for transparency and reproducibility of results. Concerning CME arrival and impact we have identified six different metadata types: 3-D CME measurement, model description, model input, CME (non)arrival observation, model output data, and metrics and validation methods. Second, the working team has also identified a validation time period, where all events within the following two periods will be considered: 1

Coronal mass ejections (CMEs) are the major space weather drivers, and an accurate modeling of their onset and propagation up to 1 AU represents a key issue for more reliable space weather forecasts. In this paper we use the newly developed EUropean Heliospheric FORecasting Information Asset (EUHFORIA) heliospheric model to test the effect of different CME shapes on simulation outputs. In particular, we investigate the notion of “spherical” CME shape, with the aim of bringing to the attention of the space weather community the great implications of the CME shape implementation details for simulation results and geoeffectiveness predictions. We take as case study an artificial Earth‐directed CME launched on 6 June 2008, corresponding to a period of quiet solar wind conditions near Earth. We discuss the implementation of the cone model used to inject the CME into the modeled ambient solar wind, running several simulations of the event and investigating the outputs in interplanetary space and at different spacecraft and planetary locations. We apply empirical relations to simulation outputs at L1 to estimate the expected CME geoeffectiveness in terms of the magnetopause stand‐off distance and the induced Kp index. Our analysis shows that talking about spherical CMEs is ambiguous unless one has detailed information on the implementation of the CME shape in the model. All the parameters specifying the CME shape in the model significantly affect simulation results at 1 AU as well as the predicted CME geoeffectiveness, confirming the pivotal role played by the shape implementation details in space weather forecasts.

In order to address the growing need for more accurate space weather predictions, a new model named EUHFORIA (EUropean Heliospheric FORecasting Information Asset) was recently developed . We present first results of the performance assessment for the solar wind modeling with EUHFORIA and identify possible limitations of its present setup. Using the basic EUHFORIA 1.0.4. model setup with the default input parameters, we modeled background solar wind (no coronal mass ejections) and compared the obtained results with ACE, in situ measurements. For the need of statistical study we developed a technique of combining daily EUHFORIA runs into continuous time series. The combined time series were derived for the years 2008 (low solar activity) and 2012 (high solar activity) from which in situ speed and density profiles were extracted. We find for the low activity phase a better match between model results and observations compared to the considered high activity time interval. The quality of the modeled solar wind parameters is found to be rather variable. Therefore, to better understand the obtained results we also qualitatively inspected characteristics of coronal holes, sources of the studied fast streams. We discuss how different characteristics of the coronal holes and input parameters to EUHFORIA influence the modeled fast solar wind, and suggest possibilities for the improvements of the model.

Coronal mass ejections (CMEs) typically cause the strongest geomagnetic storms, so a major focus of space weather research has been predicting the arrival time of CMEs. Most arrival time models fall into two categories: (1) drag-based models that integrate the drag force between a simplified CME structure and the background solar wind and (2) full magnetohydrodynamic models. Drag-based models typically are much more computationally efficient than magnetohydrodynamic models, allowing for ensemble modeling. While arrival time predictions have improved since the earliest attempts, both types of models currently have difficulty achieving mean absolute errors below 10 hr. Here we use a drag-based model ANTEATR (Another Type of Ensemble Arrival Time Results) to explore the sensitivity of arrival times to various input parameters. We consider CMEs of different strengths from average to extreme size, speed, and mass (kinetic energies between 9 × 10 29 and 6 × 10 32 erg). For each scale CME, we vary the input parameters to reflect the current observational uncertainty in each and determine how accurately each must be known to achieve predictions that are accurate within 5 hr. We find that different scale CMEs are the most sensitive to different parameters. The transit time of average strength CMEs depends most strongly on the CME speed, whereas an extreme strength CME is the most sensitive to the angular width. A precise CME direction is critical for impacts near the flanks but not near the CME nose. We also show that the Drag-Based Model has similar sensitivities, suggesting that these results are representative for all drag-based models.Plain Language Summary Large explosions of plasma and magnetic field known as coronal mass ejections (CMEs) frequently erupt from the solar atmosphere. When CMEs head toward Earth, they interact with the near-Earth plasma and magnetic field, affecting the "space weather." CMEs typically cause the strongest space weather effects, so a major focus has been predicting the time it takes for a CME to propagate from the Sun to the Earth. Many models have been developed over the past decades to predict the arrival time of CMEs, but all have difficulty achieving absolute errors less than 10 hr. Here we use a simple model that integrates the drag force between a CME and the background solar wind. Due to the model's simplicity, we can run a large number of simulations, allowing us to explore how the arrival time changes as the various model inputs are changed. We consider CMEs of different strengths and find that the behavior differs between average and extreme CMEs. We determine the precision needed for each input parameter to achieve predictions that are accurate within 5 hr. We compare our results with those from a similar model. Both models exhibit the same sensitivity to the input parameters, suggesting that these results are representative for most drag-based models.Coronal mass ejections (CMEs) are large explosions of plasma and structured magnetic field that routinely erupt from the solar ...

Aims This paper presents a H2020 project aimed at developing the world’s most advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and Coronal Mass Ejection (CME) evolution modelling with Solar Energetic Particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast Geomagnetically Induced Currents (GICs) and radiation on geospace. Methods We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely 1) data-driven flux-rope CME models, and 2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Uccle (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. Results The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.

No abstract