Coronal Mass Ejections (CMEs) are large-scale eruptions of plasma and magnetic fields from the Sun. They are considered to be the main drivers of strong space weather events at Earth. Multiple models have been developed over the past decades to be able to predict the propagation of CMEs and their arrival time at Earth. Such models require input from observations, which can be used to fit the CME to an appropriate structure.

When determining input parameters for CME propagation models, it is common procedure to derive kinematic parameters from remote-sensing data. The resulting parameters can be used as inputs for the CME propagation models to obtain an arrival prediction time of the CME f.e. at Earth. However, when fitting the CME structure to obtain the needed parameters for simulations, different geometric structures and also different parts of the CME structure can be fitted. These aspects, together with the fact that 3D reconstructions strongly depend on the subjectivity and judgement of the scientist performing them, may lead to uncertainties in the fitted parameters. Up to now, no large study has tried to map these uncertainties and to evaluate how they affect the modelling of CMEs. Furthermore, when using these determined parameters as inputs into CME propagation models, they spread throughout the modelling domain and influence the final results of the simulation and the predicted arrival time of the modelled CME.

Fitting a large set of CMEs within a selected period of time, we aim to investigate the uncertainties in the CME fittings in detail. Each event is fitted multiple times by different scientists. We discuss statistics on uncertainties of the fittings. We also present some first results of the impact of these uncertainties on CME propagation modelling.

Acknowledgements: This work has been partly supported by the International Space Science Institute (ISSI) in the framework of International Team 480 entitled: Understanding Our Capabilities In Observing And Modeling Coronal Mass Ejections'.

How to cite: Verbeke, C., Mays, M. L., and Mierla, M. and the International Team 480 from the International Space Science Institute: Understanding Our Capabilities In Observing And Modeling Coronal Mass Ejections: Understanding our capabilities in observing and modelling Coronal Mass Ejections, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8877, https://doi.org/10.5194/egusphere-egu23-8877, 2023.

The Space Weather Empirical Ensemble Package (SWEEP) is a 3-year project that, very recently, delivered a suite of software tools to the UK Met Office to improve their space weather forecasting capabilities. Part of this package was Automated CME Characterisation (ACMEC) software to automatically detect, and characterise, CMEs in near real-time (NRT) coronagraph data. ACMEC ingests STEREO COR2 beacon data, and SOHO LASCO C2/C3 NRT data, and given the availability of clean data, provides estimates of the CME’s 3D trajectory, angular extent, and speed. It also provides estimates of uncertainties in these values, enabling an ensemble forecast at Earth. We present example case studies to show the efficiacy of ACMEC, and reflect on the challenges faced, and lessons learned during the development stages. Future perspectives are given, including new missions, and the realisation that the development of machine learning methods are required for such complicated tasks in the next 10 years. 

How to cite: Morgan, H., Bunting, K., Gandhi, H., and Williams, T.: Automated detection and characterision of CMEs in near real-time coronagraph data: lessons and challenges arising from the SWEEP project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1121, https://doi.org/10.5194/egusphere-egu23-1121, 2023.

How to cite: Bauer, M., Amerstorfer, T., Weiss, A. J., Davies, J. A., Möstl, C., Amerstorfer, U. V., Reiss, M. A., and Harrison, R. A.: Predicting CMEs Using ELEvoHI With STEREO-HI Beacon Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2226, https://doi.org/10.5194/egusphere-egu23-2226, 2023.

The COSPAR iSWAT (international Space Weather Action Teams) initiative is a global hub for collaborations addressing challenges across the field of space weather. We present the COSPAR Space Weather Roadmap update for the iSWAT clusters H1+H2 covering interplanetary space and its characteristics, with focus on large-scale corotating and transient structures impacting Earth. We review the physical background of different solar wind streams together with coronal mass ejections and the considerable efforts that have been made to model these phenomena. We outline the limitations coming from observations with rather large uncertainties, making reliable predictions of the structures impacting Earth difficult. Moreover, in the wake of the upcoming solar cycle 25, the increased complexity of interplanetary space with enhanced solar activity poses a challenge to models. The current paper presents the efforts and progress achieved in recent years, identifies open questions, and gives an outlook for the next 5-10 years.

How to cite: Temmer, M., Scolini, C., Richardson, I. G., Heinemann, S. G., Paouris, E., Vourlidas, A., and Bisi, M. M. and the iSWAT Cluster H1+H2 Writing teams: Space Weather Roadmap update for iSWAT Clusters H1+H2, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5512, https://doi.org/10.5194/egusphere-egu23-5512, 2023.

The rate at which we develop and update solar and heliospheric models has outpaced the rate at which we build our data and validation infrastructure. As a consequence, we end up with a bottleneck in advancing heliospheric modeling. The validation practices that rely only on selected events and time intervals, the usage of individually developed metrics, and a slow iterative process between developers and end-users all contribute to this bottleneck. These validation practices make a complete assessment of the "state-of-the-art" in space weather modeling difficult or even impossible. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. Our mission is to provide the science community with an assessment of the state-of-the-art in solar wind modeling at Earth and other planetary environments. To this end, we are developing an open online platform hosted at NASA's CCMC for validating large-scale solar wind models by comparing their solutions with measurements from space explorers. The new online platform will allow the space weather community to test the quality of state-of-the-art solar wind models with unified metrics providing an unbiased assessment of progress over time. In this contribution, we will give a status update on our team effort, showcase the first version of the online platform, and outline future perspectives.

How to cite: Reiss, M., Muglach, K., Perri, B., Mullinix, R., and Wiegand, C.: Bottlenecks in space weather model validation: Where do we stand and how do we move forward?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6142, https://doi.org/10.5194/egusphere-egu23-6142, 2023.

Forecasting the ambient solar wind several days in advance still proves extremely difficult. In fact, state-of-the-art models (either physics-based or based on machine learning) do not consistently outperform simple baseline predictions based on 1-day persistence or 27-day recurrence. In turn, our inability to precisely forecast the ambient solar wind impacts both the accuracy and the lead-time of every Geospace and Magnetosphere-Ionosphere-Thermosphere model used for space weather purposes.

Here, we present preliminary results about a physics-informed machine learning model that aims to predict the ambient solar wind up to 5 days ahead, by combining Global Oscillation Network Group (GONG) observations and a simplified solar wind propagation model, known as HUX (Heliospheric Upwind eXtrapolation). In essence the model learns a coronal model in a completely data-driven fashion, by using ACE observations as its target.

How to cite: Camporeale, E. and Hu, A.: Physics-informed Machine Learning prediction of ambient solar wind speed, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4005, https://doi.org/10.5194/egusphere-egu23-4005, 2023.

Predicting space weather effects of the solar wind requires knowing the location and properties of any embedded high speed streams (HSSs) or stream interactions regions that form as the fast solar wind catches up to slow preceding wind. Additionally, this information is critical for understanding how a coronal mass ejection (CME) interacts with the solar wind during its propagation. We present the Mostly Empirical Operation Wind with a High Speed Stream (MEOW-HiSS) model, which runs nearly instantaneously. This model is derived from MHD simulations of an idealized HSS emanating from a circular coronal hole (CH). We split the MHD HSS radial profiles into small regions well-described by simple functions (e.g. flat, linear, exponential, sinusoidal) that can be constrained using the MHD values. We then determine how the region boundaries and the constraining values change with CH area and the distance of the HSS front. MEOW-HiSS requires the CH area and front distance and produces the corresponding radial profile with an error less than 10\% for most parameters. MEOW-HiSS produces profiles at subsequent times with almost no loss in accuracy. We also compare MEOW-HiSS results to four HSS observed in situ at 1 au. We present a method for determining MEOW-HiSS inputs from EUV images and use these values to hindcast the observed cases. We find average accuracies of 2.8 cm^-3 in the number density, 56.7 km/s in the radial velocity, 2.2 nT in the absolute radial magnetic field, 1.6 nT in the absolute longitudinal magnetic field, and 7x10^4 K in the temperature.

How to cite: Kay, C., Nieves-Chinchilla, T., Hofmeiseter, S., and Palmerio, E.: An Efficient, Time-Dependent High Speed Stream Model and Application to Solar Wind Forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9811, https://doi.org/10.5194/egusphere-egu23-9811, 2023.

To address Objective II of the National Space Weather Strategy and Action Plan 'Develop and Disseminate Accurate and Timely Space Weather Characterization and Forecasts' and US Congress PROSWIFT Act 116–181, our team is developing a new set of open-source software that would ensure substantial improvements of Space Weather (SWx) predictions. On the one hand, the focus is on the development of data-driven models. On the other hand, each individual component of our software will have higher accuracy with a dramatically improved performance. This is done by the application of new computational technologies and enhanced data sources. The development of such software paves way for improved SWx predictions accompanied with an appropriate uncertainty quantification. This will make it possible to forecast hazardous SWx effects on the space-borne and ground-based technological systems, and on human health. Our models involve (1) a new, open-source solar magnetic flux model (OFT), which evolves information to the back side of the Sun and its poles, and updates the model flux with new observations using data assimilation methods; (2) a new potential field solver (POT3D) associated with the Wang-Sheeley-Arge coronal model, and (3) a new adaptive, 4-th order of accuracy solver (HelioCubed) for the Reynolds-averaged MHD equations implemented on mapped multiblock grids (cubed spheres). We describe the software and results obtained with it, including the appication of machine learning to modeling coronal mass ejections, which makes it possible to improve SWx predictions by decreasing the time-of-arrival mismatch.  The test show that our software is formally more accurate and performs much faster than its predecessors used for SWx predictions.

How to cite: Pogorelov, N. V., Arge, C. N., Linker, J., Upton, L., Van Straalen, B., Caplan, R., Colella, P., Downs, C., Gebhard, C., Hegde, D. V., Henney, C., Jones-Mecholsky, S., Kim, T., Stulajter, M., Singh, T., Turtle, J., and Yalim, M.: Space Weather with Uncertainty Quantification: A New Sequence of Data-driven Models of the Solar Atmosphere and Inner Heliosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8215, https://doi.org/10.5194/egusphere-egu23-8215, 2023.

Our new magnetohydrodynamics (MHD) simulation model of the solar corona and solar wind and its new capabilities are presented. This model covers the range of heliocentric distance from 2.5 solar radii (Rs) up to 1 AU and beyond. Starting the simulation from 2.5 Rs, our Sun-to-Earth MHD model can utilize straightforwardly the information on the coronal mass ejection (CME) and its associated magnetic flux rope at their earliest phase.

This model is constructed by introducing the characteristic-based boundary treatment to our existing H3DMHD model [e.g. Wu+ (2015) JGR 121:1839]. The characteristic-based boundary treatment [e.g. Nakagawa+ (1987) A&Ap 197:354; Wu & Wang (1987) CMAME 64:267] can treat the temporal variations of MHD variables on the sub-sonic/Alfvenic boundary surface in a mathematically and physically consistent manner and enhances the computational robustness. In tailoring a set of characteristic equations for this new model, we assume that the coronal magnetic field is open to the interplanetary space and the solar coronal plasma is flowing outward everywhere at 2.5 Rs. Without the characteristic-based boundary treatment, we often fail to obtain the quasi-steady state of the solar corona and solar wind.

This new model can introduce various types of the numerical perturbation mimicking the CME initiation to the quasi-steady state of the trans-sonic/Alfvenic solar wind. For example, an outward-moving and expanding CME structure can be introduced as the time-dependent boundary values by calculating the MHD variables of the CME structures on the 2.5-Rs intersection. In the present model, the characteristic-based boundary treatment is not used for the boundary grids the CME is passing through, for simplicity; although, it is possible to construct a new set of characteristic equations incorporating with the CME model.

In this presentation, the details of the characteristic-based boundary treatment for the middle of the corona (hence, named CharM) are provided. The results of test simulations with various choices of parameters for the background steady trans-sonic/Alfvenic solar wind and the CME perturbations are compared to assess the dynamics of the CME evolution in the earliest period of the Sun-to-Earth disturbance propagation.

How to cite: Hayashi, K., Wu, C.-C., Liou, K., and Chen, J.: A new time-dependent three-dimensional magnetohydrodynamics (MHD) simulation model for the trans-sonic/Alfvenic solar wind from 2.5Rs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9206, https://doi.org/10.5194/egusphere-egu23-9206, 2023.

The HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) is a new mission concept conceived to address the widely recognized need to make a leap forward in the Space Weather (SWE) forecasting and science. The HENON baseline foresees one 12U CubeSat orbiting along a Distant Retrograde Orbit (DRO) of the Sun-Earth system, so that the HENON CubeSat will stay for a long period of time very far upstream of the Earth (well beyond L1 at least ~ 0.1 AU). HENON will embark a state of the art radiation monitor, which will provide high-resolution measurements of energetic particle spectra, making HENON the first mission ever providing a real time monitoring of the particle radiation environment in the deep space. This will enable the insight into the near-Earth spatial variations of SEP events giving rise to better boundary conditions for forecasting and nowcasting tools. The HENON mission also aims to embark payloads tailored for SWE observations, in order to pave the way for a significant improvement (several hours) of the forecasting horizons of geo-effective interplanetary structures (ICMEs, HSSs). HENON has important technological objectives including demonstration of the capability of the CubeSat technologies in deep space to reach both scientific and operational goals through the first ever operation in unexplored DRO orbits, thus paving the way for a future fleet of such CubeSats equally spaced along the DRO, which could provide continuous near real-time measurements for space weather forecasting. HENON is in the A/B study phase that is being developed in the framework of the ESA General Support Technology Program (GSTP). HENON is funded by the Italian Space Agency as part of the ALCOR programme.

How to cite: Laurenza, M., Marcucci, M. F., Zimbardo, G., Landi, S., Paglialunga, D., Di Tana, V., Provinciali, L., Cicalò, S., Vainio, R., Lehti, J., Němeček, Z., Prech, L., Safrankova, J., Eastwood, J., Brown, P., Walker, R., Jiggens, P., and Natalucci, S. and the HENON Team: The HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) mission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14274, https://doi.org/10.5194/egusphere-egu23-14274, 2023.