Severe space weather has the potential to cause significant socio‐economic impact and it is widely accepted that mitigating this risk requires more comprehensive observations of the Sun and heliosphere, enabling more accurate forecasting of significant events with longer lead‐times. In this context, it is now recognized that observations from the L5 Sun‐Earth Lagrange point (both remote and in situ) would offer considerable improvements in our ability to monitor and forecast space weather. Remote sensing from L5 allows for the observation of solar features earlier than at L1, providing early monitoring of active region development, as well as tracking of interplanetary coronal mass ejections through the inner heliosphere. In situ measurements at L5 characterize the solar wind's geoeffectiveness (particularly stream interaction regions), and can also be ingested into heliospheric models, improving their performance. The Vigil space weather mission is part of the ESA Space Safety Program and will provide a real‐time data stream for space weather services from L5 following its anticipated launch in the early 2030s. The interplanetary magnetic field is a key observational parameter, and here we describe the development of the Vigil magnetometer instrument for operational space weather monitoring at the L5 point. We summarize the baseline instrument capabilities, demonstrating how heritage from science missions has been leveraged to develop a low‐risk, high‐heritage instrument concept.

Abstract Coronal mass ejections (CMEs) can create significant disruption to human activities and systems on Earth, much of which can be mitigated with prior warning of the upstream solar wind conditions. However, it is currently extremely challenging to accurately predict the arrival time and internal structure of a CME from coronagraph images alone. In this study, we take advantage of a rare opportunity to use Solar Orbiter, at 0.5 au upstream of Earth, as an upstream solar wind monitor. In combination with low‐latency images from STEREO‐A, we successfully predicted the arrival time of two CME events before they reached Earth. Measurements at Solar Orbiter were used to constrain an ensemble of simulation runs from the ELEvoHI model, reducing the uncertainty in arrival time from 10.4 to 2.5 hr in the first case study. There was also an excellent agreement in the Bz profile between Solar Orbiter and Wind spacecraft for the second case study, despite being separated by 0.5 au and 10° longitude. The opportunity to use Solar Orbiter as an upstream solar wind monitor will repeat once a year, which should further help assess the efficacy upstream in‐situ measurements in real time space weather forecasting.

Accurately predicting the z-component of the interplanetary magnetic field, particularly during the passage of an interplanetary coronal mass ejection (ICME), is a crucial objective for space weather predictions. Currently, only a handful of techniques have been proposed and they remain limited in scope and accuracy. Recently, a robust machine learning technique was developed for predicting the minimum value of B-z within ICMEs based on a set of 42 "features," that is, variables calculated from measured quantities upstream of the ICME and within its sheath region. In this study, we investigate these so-called explanatory variables in more detail, focusing on those that were (a) statistically significant and (b) most important. We find that number density and magnetic field strength accounted for a large proportion of the variability. These features capture the degree to which the ICME compresses the ambient solar wind ahead. Intuitively, this makes sense: Energy made available to coronal mass ejections (CMEs) as they erupt is partitioned into magnetic and kinetic energy. Thus, more powerful CMEs are launched with larger flux-rope fields (larger B-z), at greater speeds, resulting in more sheath compression (increased number density and total field strength).

The forecasting of local GIC effects has largely relied on the forecasting of dB / dt as a proxy and, to date, little attention has been paid to directly forecasting the geoelectric field or GICs themselves. We approach this problem with machine learning tools, specifically recurrent neural networks or LSTMs by taking solar wind observations as input and training the models to predict two different kinds of output: first, the geoelectric field components E x and E y ; and second, the GICs in specific substations in Austria. The training is carried out on the geoelectric field and GICs modeled from 26 years of one‐minute geomagnetic field measurements, and results are compared to GIC measurements from recent years. The GICs are generally predicted better by an LSTM trained on values from a specific substation, but only a fraction of the largest GICs are correctly predicted. This model has a correlation with measurements of around 0.6, and a root‐mean‐square error of 0.7 A. The probability of detecting mild activity in GICs is around 50%, and 15% for larger GICs.

Abstract Geometric modeling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modeling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modeling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modeling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modeling errors are minimised for an observer in the L5 region. Furthermore, geometric modeling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2 ± 1.2 h, 8.3 ± 1.0 h, and 5.8 ± 0.9 h for the average, fast, and extreme CME scenarios.

Context.Solar Orbiter, the new-generation mission dedicated to solar and heliospheric exploration, was successfully launched on February 10, 2020, 04:03 UTC from Cape Canaveral. During its first perihelion passage in June 2020, two successive interplanetary coronal mass ejections (ICMEs), propagating along the heliospheric current sheet (HCS), impacted the spacecraft.Aims.This paper addresses the investigation of the ICMEs encountered by Solar Orbiter on June 7−8, 2020, from both an observational and a modeling perspective. The aim is to provide a full description of those events, their mutual interaction, and their coupling with the ambient solar wind and the HCS.Methods.Data acquired by the MAG magnetometer, the Energetic Particle Detector suite, and the Radio and Plasma Waves instrument are used to provide information on the ICMEs’ magnetic topology configuration, their magnetic connectivity to the Sun, and insights into the heliospheric plasma environment where they travel, respectively. On the modeling side, the Heliospheric Upwind eXtrapolation model, the 3D COronal Rope Ejection technique, and the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) tool are used to complement Solar Orbiter observations of the ambient solar wind and ICMEs, and to simulate the evolution and interaction of the ejecta in the inner heliosphere, respectively.Results.Both data analysis and numerical simulations indicate that the passage of two distinct, dynamically and magnetically interacting (via magnetic reconnection processes) ICMEs at Solar Orbiter is a possible scenario, supported by the numerous similarities between EUHFORIA time series at Solar Orbiter and Solar Orbiter data.Conclusions.The combination of in situ measurements and numerical simulations (together with remote sensing observations of the corona and inner heliosphere) will significantly lead to a deeper understanding of the physical processes occurring during the CME-CME interaction.

Studying the ambient solar wind, a continuous pressure‐driven plasma flow emanating from our Sun, is an important component of space weather research. The ambient solar wind flows in interplanetary space determine how solar storms evolve through the heliosphere before reaching Earth, and especially during solar minimum are themselves a driver of activity in the Earth's magnetic field. Accurately forecasting the ambient solar wind flow is therefore imperative to space weather awareness. Here, we present a machine learning approach in which solutions from magnetic models of the solar corona are used to output the solar wind conditions near the Earth. The results are compared to observations and existing models in a comprehensive validation analysis, and the new model outperforms existing models in almost all measures. In addition, this approach offers a new perspective to discuss the role of different input data to ambient solar wind modeling, and what this tells us about the underlying physical processes. The final model discussed here represents an extremely fast, well‐validated and open‐source approach to the forecasting of ambient solar wind at Earth.

Predicting the Bz magnetic field embedded within ICMEs, also known as the Bz problem, is a key challenge in space weather forecasting. We study the hypothesis that upstream in situ measurements of the sheath region and the first few hours of the magnetic obstacle provide sufficient information for predicting the downstream Bz component. To do so, we develop a predictive tool based on machine learning that is trained and tested on 348 ICMEs from Wind, STEREO-A, and STEREO-B measurements. We train the machine learning models to predict the minimum value of the Bz component and the maximum value of the total magnetic field Bz in the magnetic obstacle. To validate the tool, we let the ICMEs sweep over the spacecraft and assess how continually feeding in situ measurements into the tool improves the Bz prediction. Because the application of the tool in operations needs an automated detection of ICMEs, we implement an existing automated ICME detection algorithm and test its robustness for the time intervals under scrutiny. We find that the predictive tool can predict the minimum value of the Bz component in the magnetic obstacle with a mean absolute error of 3.12 nT and a Pearson correlation coefficient of 0.71 when the sheath region and the first 4 hours of the magnetic obstacle are observed. While the underlying hypothesis is unlikely to solve the Bz problem, the tool shows promise for ICMEs that have a recognizable magnetic flux rope signature. Transitioning the tool to operations could lead to improved space weather forecasting.

Context. The recent launch of Solar Orbiter and the flyby of BepiColombo opened a brief window during which these two spacecraft, along with the existing spacecraft at L1, were positioned in a constellation that allowed for the detailed sampling of any Earth-directed coronal mass ejection (CME). Fortunately, two such events occurred during this time period with in situ detections of an interplanetary coronal mass ejection (ICME) by Solar Orbiter on the 2020 April 19 and 2020 May 28. These two events were subsequently observed in situ by BepiColombo and Wind as well around a day later. Aims. We attempt to reconstruct the observed in situ magnetic field measurements for all three spacecraft simultaneously using an empirical magnetic flux rope model. This allows us to test the validity of our flux rope model on a larger and more global scale. It additionally allows for cross-validation of the analysis with different spacecraft combinations. Finally, we can also compare the results from the in situ modeling to remote observations obtained from the STEREO-A heliospheric imagers, which were able to capture the interplanetary evolution of the coronal mass ejections. Methods. We made use of the 3D coronal rope ejection model (3DCORE) in order to simulate the ICME evolution and reconstruct the measured flux rope signatures at the spacecraft positions. For this purpose, we adapted a previously developed approximate Bayesian Computation sequential Monte-Carlo (ABC-SMC) fitting algorithm for the application to multi-point scenarios. This approach not only allows us to find global solutions, within the limits of our model, but to also naturally generate error estimates on the model parameters and detect potential ambiguities. Results. We show that we are able to generally reconstruct the flux rope signatures at three different spacecraft positions simultaneously by using our model in combination with the flux rope fitting algorithm. For the well-behaved April 19 ICME, our approach works very well and displays only minor deficiencies. The May 28 ICME, on the other hand, shows the limitations of our approach for less clear ICME measurements or strongly deformed shapes. Unfortunately, the usage of multi-point observations for these events does not appear to solve inherent issues, such as the estimation of the magnetic field twist or flux rope aspect-ratios due to the specific constellation of the spacecraft positions, which all lie near the ecliptic plane. As our general approach can be used for any fast-forward simulation based model, we give a blueprint for future studies using more advanced ICME models.

Geomagnetic storms resulting from high-speed streams can have significant negative impacts on modern infrastructure due to complex interactions between the solar wind and geomagnetic field. One measure of the extent of this effect is the Kyoto $Dst$ index. We present a method to predict $Dst$ from data measured at the Lagrange 5 (L5) point, which allows for forecasts of solar wind development 4.5 days in advance of the stream reaching the Earth. Using the STEREO-B satellite as a proxy, we map data measured near L5 to the near-Earth environment and make a prediction of the $Dst$ from this point using the Temerin-Li $Dst$ model enhanced from the original using a machine learning approach. We evaluate the method accuracy with both traditional point-to-point error measures and an event-based validation approach. The results show that predictions using L5 data outperform a 27-day solar wind persistence model in all validation measures but do not achieve a level similar to an L1 monitor. Offsets in timing and the rapidly-changing development of $B_z$ in comparison to $B_x$ and $B_y$ reduce the accuracy. Predictions of $Dst$ from L5 have an RMSE of $9$ nT, which is double the error of $4$ nT using measurements conducted near the Earth. The most useful application of L5 measurements is shown to be in predicting the minimum $Dst$ for the next four days. This method is being implemented in a real-time forecast setting using STEREO-A as an L5 proxy, and has implications for the usefulness of future L5 missions.

Interplanetary coronal mass ejections (ICMEs) are a significant feature of the heliospheric environment and the primary cause of adverse space weather at the Earth. ICME propagation, and the evolution of ICME magnetic field structure during propagation, are still not fully understood. We analyze the magnetic field structures of 18 ICME magnetic flux ropes observed by radially aligned spacecraft in the inner heliosphere. Similarity in the underlying flux rope structures is determined through the application of a simple technique that maps the magnetic field profile from one spacecraft to the other. In many cases, the flux ropes show very strong underlying similarities at the different spacecraft. The mapping technique reveals similarities that are not readily apparent in the unmapped data and is a useful tool when determining whether magnetic field time series observed at different spacecraft are associated with the same ICME. Lundquist fitting has been applied to the flux ropes and the rope orientations have been determined; macroscale differences in the profiles at the aligned spacecraft may be ascribed to differences in flux rope orientation. Assuming that the same region of the ICME was observed by the aligned spacecraft in each case, the fitting indicates some weak tendency for the rope axes to reduce in inclination relative to the solar equatorial plane and to align with the solar east-west direction with heliocentric distance.

The interplanetary evolution of 11 magnetic clouds (MCs) recorded by at least two radially aligned spacecraft is studied. The in situ magnetic field measurements are fitted to a cylindrically symmetric Gold–Hoyle force-free uniform-twist flux-rope configuration. The analysis reveals that in a statistical sense, the expansion of the studied MCs is compatible with self-similar behavior. However, individual events expose a large scatter of expansion rates, ranging from very weak to very strong expansion. Individually, only four events show an expansion rate compatible with isotropic self-similar expansion. The results indicate that the expansion has to be much stronger when the MCs are still close to the Sun than in the studied 0.47–4.8 au distance range. The evolution of the magnetic field strength shows a large deviation from the behavior expected for the case of isotropic self-similar expansion. In the statistical sense, as well as in most of the individual events, the inferred magnetic field decreases much slower than expected. Only three events show behavior compatible with self-similar expansion. There is also a discrepancy between the magnetic field decrease and the increase of the MC size, indicating that magnetic reconnection and geometrical deformations play a significant role in the MC evolution. About half of the events show a decay of the electric current as expected for self-similar expansion. Statistically, the inferred axial magnetic flux is broadly consistent with remaining constant. However, events characterized by a large magnetic flux show a clear tendency toward decreasing flux.

The Solar TErrestrial RElations Observatory (STEREO) and its heliospheric imagers (HIs) have provided us the possibility to enhance our understanding of the interplanetary propagation of coronal mass ejections (CMEs). HI‐based methods are able to forecast arrival times and speeds at any target and use the advantage of tracing a CME's path of propagation up to 1 AU and beyond. In our study, we use the ELEvoHI model for CME arrival prediction together with an ensemble approach to derive uncertainties in the modeled arrival time and impact speed. The CME from 3 November 2010 is analyzed by performing 339 model runs that are compared to in situ measurements from lined‐up spacecraft MErcury Surface, Space ENvironment, GEochemistry, and Ranging and STEREO‐B. Remote data from STEREO‐B showed the CME as halo event, which is comparable to an HI observer situated at L1 and observing an Earth‐directed CME. A promising and easy approach is found by using the frequency distributions of four ELEvoHI output parameters, drag parameter, background solar wind speed, initial distance, and speed. In this case study, the most frequent values of these outputs lead to the predictions with the smallest errors. Restricting the ensemble to those runs, we are able to reduce the mean absolute arrival time error from 3.5 ± 2.6 to 1.6 ± 1.1 hr at 1 AU. Our study suggests that L1 may provide a sufficient vantage point for an Earth‐directed CME, when observed by HI, and that ensemble modeling could be a feasible approach to use ELEvoHI operationally.

Because of their activity, late-type stars are known to host powerful flares producing intense high-energy radiation on short timescales that may significantly affect the atmosphere of nearby planets. We employ a one-dimensional aeronomic model to study the reaction of the upper atmosphere of the hot Jupiter HD 209458b to the additional high-energy irradiation caused by a stellar flare. Atmospheric absorption of the additional energy produced during a flare leads to local atmospheric heating, accompanied by the formation of two propagating shock waves. We present estimates of the additional atmospheric loss occurring in response to the flare. We find the mass-loss rate at the exobase level to significantly increase (3.8 × 1010, 8 × 1010, and 3.5 × 1011 g s−1 for 10, 100, and 1000 times the high-energy flux of the quiet star, respectively) in comparison to that found considering the inactive star (2 × 1010 g s−1).

The Rosetta spacecraft of the European Space Agency made ground-breaking observations of comet 67P/Churyumov-Gerasimenko and of its cometary environment. We search for magnetic holes in that environment, i.e., significant depressions in the magnetic field strength, measured by the Rosetta fluxgate Magnetometer (MAG) in April and May 2015. In that time frame of two months, we identified 23 magnetic holes. The cometary activity was intermediate and increasing because Rosetta was on the inbound leg toward the Sun. While in April solar wind protons were still observed by Rosetta near the comet, in May these protons were already mostly replaced by heavy cometary ions. Magnetic holes have frequently been observed in the solar wind. We find, for the first time, that magnetic holes exist in the cometary environment even when solar wind protons are almost absent. Some of the properties of the magnetic holes are comparable to those of solar wind holes; they are associated with density enhancements, sometimes associated with co-located current sheets and fast solar wind streams, and are of similar scales. However, particularly in May, the magnetic holes near the comet appear to be more processed, featuring shifted density enhancements and, sometimes, bipolar signatures in magnetic field strength rather than simple depressions. The magnetic holes are of global size with respect to the coma. However, at the comet, they are compressed owing to magnetic field pile-up and draping so that they change in shape. There, the magnetic holes become of comparable size to heavy cometary ion gyroradii, potentially enabling kinetic interactions.

Predicting the magnetic field within an Earth‐directed coronal mass ejection (CME) well before its arrival at Earth is one of the most important issues in space weather research. In this article, we compare the intrinsic flux rope type, that is, the CME orientation and handedness during eruption, with the in situ flux rope type for 20 CME events that have been uniquely linked from Sun to Earth through heliospheric imaging. Our study shows that the intrinsic flux rope type can be estimated for CMEs originating from different source regions using a combination of indirect proxies. We find that only 20% of the events studied match strictly between the intrinsic and in situ flux rope types. The percentage rises to 55% when intermediate cases (where the orientation at the Sun and/or in situ is close to 45°) are considered as a match. We also determine the change in the flux rope tilt angle between the Sun and Earth. For the majority of the cases, the rotation is several tens of degrees, while 35% of the events change by more than 90°. While occasionally the intrinsic flux rope type is a good proxy for the magnetic structure impacting Earth, our study highlights the importance of capturing the CME evolution for space weather forecasting purposes. Moreover, we emphasize that determination of the intrinsic flux rope type is a crucial input for CME forecasting models.

Hot-Jupiters are subject to extreme radiation and plasma flows coming from their host stars. Past ultraviolet Hubble Space Telescope observations, supported by hydrodynamic models, confirmed that these factors lead to the formation of an extended envelope, part of which lies beyond the Roche lobe. We use gas-dynamic simulations to study the impact of time variations in the parameters of the stellar wind, namely that of coronal mass ejections (CMEs), on the envelope of the typical hot-Jupiter HD 209458b. We consider three CMEs characterized by different velocities and densities, taking their parameters from typical CMEs observed for the Sun. The perturbations in the ram-pressure of the stellar wind during the passage of each CME tear off most of the envelope that is located beyond the Roche lobe. This leads to a substantial increase of the mass-loss rates during the interaction with the CME. We find that the mass lost by the planet during the whole crossing of a CME is of ≈10^15 g, regardless of the CME taken into consideration. We also find that over the course of 1 Gyr, the mass lost by the planet because of CME impacts is comparable to that lost because of high-energy stellar irradiation.

We present an advance toward accurately predicting the arrivals of coronal mass ejections (CMEs) at the terrestrial planets, including Earth. For the first time, we are able to assess a CME prediction model using data over two thirds of a solar cycle of observations with the Heliophysics System Observatory. We validate modeling results of 1337 CMEs observed with the Solar Terrestrial Relations Observatory (STEREO) heliospheric imagers (HI) (science data) from 8 years of observations by five in situ observing spacecraft. We use the self-similar expansion model for CME fronts assuming 60° longitudinal width, constant speed, and constant propagation direction. With these assumptions we find that 23%-35% of all CMEs that were predicted to hit a certain spacecraft lead to clear in situ signatures, so that for one correct prediction, two to three false alarms would have been issued. In addition, we find that the prediction accuracy does not degrade with the HI longitudinal separation from Earth. Predicted arrival times are on average within 2.6 ± 16.6 h difference of the in situ arrival time, similar to analytical and numerical modeling, and a true skill statistic of 0.21. We also discuss various factors that may improve the accuracy of space weather forecasting using wide-angle heliospheric imager observations. These results form a first-order approximated baseline of the prediction accuracy that is possible with HI and other methods used for data by an operational space weather mission at the Sun-Earth L5 point.

In this study, we present a new method for forecasting arrival times and speeds of coronal mass ejections (CMEs) at any location in the inner heliosphere. This new approach enables the adoption of a highly flexible geometrical shape for the CME front with an adjustable CME angular width and an adjustable radius of curvature of its leading edge, i.e., the assumed geometry is elliptical. Using, as input, Solar TErrestrial RElations Observatory (STEREO) heliospheric imager (HI) observations, a new elliptic conversion (ElCon) method is introduced and combined with the use of drag-based model (DBM) fitting to quantify the deceleration or acceleration experienced by CMEs during propagation. The result is then used as input for the Ellipse Evolution Model (ElEvo). Together, ElCon, DBM fitting, and ElEvo form the novel ElEvoHI forecasting utility. To demonstrate the applicability of ElEvoHI, we forecast the arrival times and speeds of 21 CMEs remotely observed from STEREO/HI and compare them to in situ arrival times and speeds at 1 AU. Compared to the commonly used STEREO/HI fitting techniques (Fixed-phi, Harmonic Mean, and Self-similar Expansion fitting), ElEvoHI improves the arrival time forecast by about 2 to +/- 6.5 hr and the arrival speed forecast by approximate to 250 to +/- 53 km s(-1), depending on the ellipse aspect ratio assumed. In particular, the remarkable improvement of the arrival speed prediction is potentially beneficial for predicting geomagnetic storm strength at Earth.