arXiv subjects

Jürgen Hinterreiter

Publications and source records attributed to Jürgen Hinterreiter.

15 recordsLinked to original sources

arXiv2024

Coupling between magnetic reconnection, energy release, and particle acceleration in the X17.2 2003 October 28 solar flare

The 2003 October 28 (X17.2) eruptive flare was a unique event. The coronal electric field and the π-decay γ-ray emission flux had the highest values ever inferred in solar flares. This study reveals physical links between the magnetic reconnection process, the energy release, and the acceleration of electrons and ions to high energies in the chain of the magnetic energy transformations in the impulsive phase of the solar flare. The global reconnection rate and the local reconnection rate are calculated from flare ribbon separation in Hα filtergrams and photospheric magnetic field maps. Available results of INTEGRAL and CORONAS-F/SONG observations are combined with Konus-Wind data to quantify time behavior of electron and proton acceleration. Prompt γ-ray lines and delayed 2.2 MeV line temporal profiles observed with Konus-Wind and INTEGRAL/SPI used to detect and quantify the nuclei with energies of 10-70 MeV. The global and local reconnection rates reach their peaks at the end of the main rise phase of the flare. The spectral analysis of the high-energy γ-ray emission revealed a close association between the acceleration process efficiency and the reconnection rates. High-energy bremsstrahlung continuum and narrow γ-ray lines were observed in the main rise phase. In the main energy release phase, the upper energy of the bremsstrahlung spectrum was significantly reduced and the pion-decay γ-ray emission appeared abruptly. We discuss the reasons why the change of the acceleration regime occurred along with the large-scale magnetic field restructuration of this flare. We argue that the main energy release and proton acceleration up to subrelativistic energies began just when the reconnection rate was going through the maximum, i.e., after a major change of the flare topology.

astro-ph.SR↗

arXiv2023

Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

(Shortened version) Current efforts in space weather forecasting of CMEs have been focused on predicting their arrival time and magnetic structure. To make predictions, methods have been developed to derive the true CME speed, size and position, among others. Difficulties in determining input parameters for CME forecasting arise from the lack of direct measurements of the coronal magnetic fields and uncertainties in estimating the CME 3D geometric and kinematic parameters. White-light coronagraph images are usually employed by a variety of CME reconstruction techniques. We explore how subjectivity affects the 3D CME parameters that are obtained from the GCS reconstruction technique. We have designed two different synthetic scenarios where the ``true'' geometric parameters are known in order to quantify such uncertainties for the first time. We explore this as follows: 1) Using the ray-tracing option from the GCS model software, and 2) Using 3D MHD simulation data from the MAS code. Our experiment includes different viewing configurations using single and multiple viewpoints. CME reconstructions using a single viewpoint had the largest errors and error ranges for both synthetic GCS and simulated MHD white-light data. Increasing the number of viewpoints to two, the errors decreased by about 4$^\circ$ in latitude, 22$^\circ$ in longitude, 14$^\circ$ in tilt, and 10$^\circ$ in half-angle, pointing towards a need for at least two viewpoints. We found the following CME parameter error bars as a starting point for quantifying the minimum error in CME parameters from white-light reconstructions: $Δθ$ (latitude)=${6^\circ}$, $Δϕ$ (longitude)=${11^\circ}$, $Δγ$ (tilt)=${25^\circ}$, $Δα$ (half-angle)=${10^\circ}$, $Δh$ (height)=$0.6 R_{\odot}$, and $Δκ$ (ratio)=$0.1$.

astro-ph.SR↗

arXiv2021

Predicting CMEs using ELEvoHI with STEREO-HI beacon data

Being able to accurately predict the arrival of coronal mass ejections (CMEs) at Earth has been a long-standing problem in space weather research and operations. In this study, we use the ELlipse Evolution model based on Heliospheric Images (ELEvoHI) to predict the arrival time and speed of 10 CME events that were observed by HI on the STEREO-A spacecraft between 2010 and 2020. Additionally, we introduce a Python tool for downloading and preparing STEREO-HI data, as well as tracking CMEs. In contrast to most previous studies, we use not only science data, which has a relatively high spatial and temporal resolution, but also low-quality beacon data, which is - in contrast to science data - provided in real-time by the STEREO-A spacecraft. We do not use data from the STEREO-B spacecraft. We get a mean absolute error of 8.81 $\pm$ 3.18 h / 59 $\pm$ 31 kms$^{-1}$ for arrival time/speed predictions using science data and 11.36 $\pm$ 8.69 h / 106 $\pm$ 61 kms$^{-1}$ for beacon data. We find that using science data generally leads to more accurate predictions, but using beacon data with the ELEvoHI model is certainly a viable choice in the absence of higher resolution real-time data. We propose that these differences could be minimized if not eliminated altogether if higher quality real-time data was available, either by enhancing the quality of the already available data or coming from a new mission carrying a HI instrument on-board.

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arXiv2021

Quantifying the uncertainty in CME kinematics derived from geometric modelling of Heliospheric Imager data

Geometric modelling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modelling, 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 modelling 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 modelling 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 modelling errors are minimised for an observer in the L5 region. Furthermore, geometric modelling 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 $8.2\pm1.2$~h, $8.3\pm1.0$~h, and $5.8\pm0.9$~h for the average, fast, and extreme CME scenarios.

astro-ph.SR↗

arXiv2021

Machine learning for predicting the Bz magnetic field component from upstream in situ observations of solar coronal mass ejections

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.

physics.space-ph↗

arXiv2021

Solar origins of a strong stealth CME detected by Solar Orbiter

Aims.We aim to locate the origin of a stealth coronal mass ejection (CME) detected in situ by the MAG instrument on board Solar Orbiter, and make connections between the CME observed at the Sun, and the interplanetary CME (ICME) measured in situ. Methods. Remote sensing data are analysed using advanced image processing techniques to identify the source region of the stealth CME, and the global magnetic field at the time of the eruption is examined using Potential Field Source Surface (PFSS) models. The observations of the stealth CME at the Sun are compared with the magnetic field measured by the Solar Orbiter spacecraft, and plasma properties measured by the Wind spacecraft. Results. The source of the CME is found to be a quiet Sun cavity in the northern hemisphere. We find that the stealth CME has a strong magnetic field in situ, despite originating from a quiet Sun region with an extremely weak magnetic field. Conclusions. The interaction of the ICME with its surrounding environment is the likely cause of a higher magnetic field strength measured in situ. Stealth CMEs require multi-wavelength and multi-viewpoint observations in order to confidently locate the source region, however their elusive signatures still pose many problems for space weather forecasting. The findings have implications for Solar Orbiter observing sequences with instruments such as EUI that are designed to capture stealth CMEs

astro-ph.SR↗

arXiv2021

Radial Evolution of the April 2020 Stealth Coronal Mass Ejection between 0.8 and 1 AU -- A Comparison of Forbush Decreases at Solar Orbiter and Earth

Aims. We present observations of the first coronal mass ejection (CME) observed at the Solar Orbiter spacecraft on April 19, 2020, and the associated Forbush decrease (FD) measured by its High Energy Telescope (HET). This CME is a multispacecraft event also seen near Earth the next day. Methods. We highlight the capabilities of HET for observing small short-term variations of the galactic cosmic ray count rate using its single detector counters. The analytical ForbMod model is applied to the FD measurements to reproduce the Forbush decrease at both locations. Input parameters for the model are derived from both in situ and remote-sensing observations of the CME. Results. The very slow (~350 km/s) stealth CME caused a FD with an amplitude of 3 % in the low-energy cosmic ray measurements at HET and 2 % in a comparable channel of the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) on the Lunar Reconnaissance Orbiter, as well as a 1 % decrease in neutron monitor measurements. Significant differences are observed in the expansion behavior of the CME at different locations, which may be related to influence of the following high speed solar wind stream. Under certain assumptions, ForbMod is able to reproduce the observed FDs in low-energy cosmic ray measurements from HET as well as CRaTER, but with the same input parameters, the results do not agree with the FD amplitudes at higher energies measured by neutron monitors on Earth. We study these discrepancies and provide possible explanations. Conclusions. This study highlights that the novel measurements of the Solar Orbiter can be coordinated with other spacecraft to improve our understanding of space weather in the inner heliosphere. Multi-spacecraft observations combined with data-based modeling are also essential to understand the propagation and evolution of CMEs as well as their space weather impacts.

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arXiv2021

Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations

In this study, we evaluate a coronal mass ejection (CME) arrival prediction tool that utilizes the wide-angle observations made by STEREO's heliospheric imagers (HI). The unsurpassable advantage of these imagers is the possibility to observe the evolution and propagation of a CME from close to the Sun out to 1 AU and beyond. We believe that by exploiting this capability, instead of relying on coronagraph observations only, it is possible to improve today's CME arrival time predictions. The ELlipse Evolution model based on HI observations (ELEvoHI) assumes that the CME frontal shape within the ecliptic plane is an ellipse, and allows the CME to adjust to the ambient solar wind speed, i.e. it is drag-based. ELEvoHI is used to perform ensemble simulations by varying the CME frontal shape within given boundary conditions that are consistent with the observations made by HI. In this work, we evaluate different set-ups of the model by performing hindcasts for 15 well-defined isolated CMEs that occurred when STEREO was near L4/5, between the end of 2008 and the beginning of 2011. In this way, we find a mean absolute error of between $6.2\pm7.9$ h and $9.9\pm13$ h depending on the model set-up used. ELEvoHI is specified for using data from future space weather missions carrying HIs located at L5 or L1. It can also be used with near real-time STEREO-A HI beacon data to provide CME arrival predictions during the next $\sim7$ years when STEREO-A is observing the Sun-Earth space.

physics.space-ph↗

arXiv2021

Why are ELEvoHI CME arrival predictions different if based on STEREO-A or STEREO-B heliospheric imager observations?

Accurate forecasting of the arrival time and arrival speed of coronal mass ejections (CMEs) is a unsolved problem in space weather research. In this study, a comparison of the predicted arrival times and speeds for each CME based, independently, on the inputs from the two STEREO vantage points is carried out. We perform hindcasts using ELlipse Evolution model based on Heliospheric Imager observations (ELEvoHI) ensemble modelling. An estimate of the ambient solar wind conditions is obtained by the Wang-Sheeley-Arge/Heliospheric Upwind eXtrapolation (WSA/HUX) model combination that serves as input to ELEvoHI. We carefully select 12 CMEs between February 2010 and July 2012 that show clear signatures in both STEREO-A and STEREO-B HI time-elongation maps, that propagate close to the ecliptic plane, and that have corresponding in situ signatures at Earth. We find a mean arrival time difference of 6.5 hrs between predictions from the two different viewpoints, which can reach up to 9.5 hrs for individual CMEs, while the mean arrival speed difference is 63 km s$^{-1}$. An ambient solar wind with a large speed variance leads to larger differences in the STEREO-A and STEREO-B CME arrival time predictions ($cc~=~0.92$). Additionally, we compare the predicted arrivals, from both spacecraft, to the actual in situ arrivals at Earth and find a mean absolute error of 7.5 $\pm$ 9.5 hrs for the arrival time and 87 $\pm$ 111 km s$^{-1}$ for the arrival speed. There is no tendency for one spacecraft to provide more accurate arrival predictions than the other.

astro-ph.SR↗

arXiv2020

Analysis of coronal mass ejection flux rope signatures using 3DCORE and approximate Bayesian Computation

We present a major update to the 3D coronal rope ejection (3DCORE) technique for modeling coronal mass ejection flux ropes in conjunction with an Approximate Bayesian Computation (ABC) algorithm that is used for fitting the model to in situ magnetic field measurements. The model assumes an empirically motivated torus-like flux rope structure that expands self-similarly within the heliosphere, is influenced by a simplified interaction with the solar wind environment, and carries along an embedded analytical magnetic field. The improved 3DCORE implementation allows us to generate extremely large ensemble simulations which we then use to find global best-fit model parameters using an ABC sequential Monte Carlo (SMC) algorithm. The usage of this algorithm, under some basic assumptions on the uncertainty of the magnetic field measurements, allows us to furthermore generate estimates on the uncertainty of model parameters using only a single in situ observation. We apply our model to synthetically generated measurements to prove the validity of our implementation for the fitting procedure. We also present a brief analysis, within the scope of our model, of an event captured by Parker Solar Probe (PSP) shortly after its first fly-by of the Sun on 2018 November 12 at 0.25 AU. The presented toolset is also easily extendable to the analysis of events captured by multiple spacecraft and will therefore facilitate future multi-point studies.

astro-ph.SR↗

arXiv2020

Prediction of the in situ coronal mass ejection rate for solar cycle 25: Implications for Parker Solar Probe in situ observations

The Parker Solar Probe (PSP) and Solar Orbiter missions are designed to make groundbreaking observations of the Sun and interplanetary space within this decade. We show that a particularly interesting in situ observation of an interplanetary coronal mass ejection (ICME) by PSP may arise during close solar flybys ($< 0.1$~AU). During these times, the same magnetic flux rope inside an ICME could be observed in situ by PSP twice, by impacting its frontal part as well as its leg. Investigating the odds of this situation, we forecast the ICME rate in solar cycle 25 based on 2 models for the sunspot number (SSN): (1) the forecast of an expert panel in 2019 (maximum SSN = 115), and (2) a prediction by McIntosh et al. (2020, maximum SSN = 232). We link the SSN to the observed ICME rates in solar cycles 23 and 24 with the Richardson and Cane list and our own ICME catalog, and calculate that between 1 and 7 ICMEs will be observed by PSP at heliocentric distances $< 0.1$ AU until 2025, including 1$σ$ uncertainties. We then model the potential flux rope signatures of such a double-crossing event with the semi-empirical 3DCORE flux rope model, showing a telltale elevation of the radial magnetic field component $B_R$, and a sign reversal in the component $B_N$ normal to the solar equator compared to field rotation in the first encounter. This holds considerable promise to determine the structure of CMEs close to their origin in the solar corona.

astro-ph.SR↗

arXiv2020

Forecasting the Ambient Solar Wind with Numerical Models. II. An Adaptive Prediction System for Specifying Solar Wind Speed Near the Sun

The ambient solar wind flows and fields influence the complex propagation dynamics of coronal mass ejections in the interplanetary medium and play an essential role in shaping Earth's space weather environment. A critical scientific goal in the space weather research and prediction community is to develop, implement and optimize numerical models for specifying the large-scale properties of solar wind conditions at the inner boundary of the heliospheric model domain. Here we present an adaptive prediction system that fuses information from in situ measurements of the solar wind into numerical models to better match the global solar wind model solutions near the Sun with prevailing physical conditions in the vicinity of Earth. In this way, we attempt to advance the predictive capabilities of well-established solar wind models for specifying solar wind speed, including the Wang-Sheeley-Arge (WSA) model. In particular, we use the Heliospheric Upwind eXtrapolation (HUX) model for mapping the solar wind solutions from the near-Sun environment to the vicinity of Earth. In addition, we present the newly developed Tunable HUX (THUX) model which solves the viscous form of the underlying Burgers equation. We perform a statistical analysis of the resulting solar wind predictions for the time 2006-2015. The proposed prediction scheme improves all the investigated coronal/heliospheric model combinations and produces better estimates of the solar wind state at Earth than our reference baseline model. We discuss why this is the case, and conclude that our findings have important implications for future practice in applied space weather research and prediction.

physics.space-ph↗

arXiv2019

Unusual plasma and particle signatures at Mars and STEREO-A related to CME-CME interaction

On July 25 2017 a multi-step Forbush decrease (FD) with the remarkable total amplitude of more than 15\% was observed by MSL/RAD at Mars. We find that these particle signatures are related to very pronounced plasma and magnetic field signatures detected in situ by STEREO-A on July 24 2017, with a higher than average total magnetic field strength reaching more than 60 nT. In the observed time period STEREO-A was at a relatively small longitudinal separation (46 degrees) to Mars and both were located at the back side of the Sun as viewed from Earth. We analyse a number of multi-spacecraft and multi-instrument (both in situ and remote-sensing) observations, and employ modelling to understand these signatures. We find that the solar sources are two CMEs which erupted on July 23 2017 from the same source region on the back side of the Sun as viewed from Earth. Moreover, we find that the two CMEs interact non-uniformly, inhibiting the expansion of one of the CMEs in STEREO-A direction, whereas allowing it to expand more freely in the Mars direction. The interaction of the two CMEs with the ambient solar wind adds up to the complexity of the event, resulting in a long, sub-structured interplanetary disturbance at Mars, where different sub-structures correspond to different steps of the FD, adding-up to a globally large-amplitude FD.

astro-ph.SR↗

arXiv2018

Statistical Properties of Ribbon Evolution and Reconnection Electric Fields in Eruptive and Confined Flares

A statistical study of the chromospheric ribbon evolution in H$α$ two-ribbon flares is performed. The data set consists of 50 confined ($62\,\%$) and eruptive ($38\,\%$) flares that occurred from June 2000 to June 2015. The flares are selected homogeneously over the H$α$ and $\textit{GOES}$ (Geostationary Operational Environmental Satellite) classes, with an emphasis on including powerful confined flares and weak eruptive flares. H$α$ filtergrams from Kanzelhöhe Observatory in combination with $\textit{MDI}$ (Michelson Doppler Imager) and $\textit{HMI}$ (Helioseismic and Magnetic Imager) magnetograms are used to derive the ribbon separation, the ribbon-separation velocity, the magnetic-field strength, and the reconnection electric field. We find that eruptive flares reveal statistically larger ribbon separation and higher ribbon-separation velocities than confined flares. In addition, the ribbon separation of eruptive flares correlates with the GOES SXR flux, whereas no clear dependence was found for confined flares. The maximum ribbon-separation velocity is not correlated with the GOES flux, but eruptive flares reveal on average a higher ribbon-separation velocity (by $\approx 10~$km$~$s$^{-1}$). The local reconnection electric field of confined ($cc=0.50~\pm~0.02$) and eruptive ($cc=0.77~\pm~0.03$) flares correlates with the GOES flux, indicating that more powerful flares involve stronger reconnection electric fields. In addition, eruptive flares with higher electric-field strengths tend to be accompanied by faster coronal mass ejections.

astro-ph.SR↗

arXiv2017

Reconnection fluxes in eruptive and confined flares and implications for superflares on the Sun

We study the energy release process of a set of 51 flares (32 confined, 19 eruptive) ranging from GOES class B3 to X17. We use H$α$ filtergrams from Kanzelhöhe Observatory together with SDO HMI and SOHO MDI magnetograms to derive magnetic reconnection fluxes and rates. The flare reconnection flux is strongly correlated with the peak of the GOES 1-8 Å soft X-ray flux (c=0.92, in log-log space), both for confined and eruptive flares. Confined flares of a certain GOES class exhibit smaller ribbon areas but larger magnetic flux densities in the flare ribbons (by a factor of 2). In the largest events, up to $\approx$50\%\ of the magnetic flux of the active region (AR) causing the flare is involved in the flare magnetic reconnection. These findings allow us to extrapolate toward the largest solar flares possible. A complex solar AR hosting a magnetic flux of $2\cdot 10^{23}\, \mathrm{Mx}$, which is in line with the largest AR fluxes directly measured, is capable of producing an X80 flare, which corresponds to a bolometric energy of about $7 \cdot 10^{32}$ ergs. Using a magnetic flux estimate of $6\cdot 10^{23}\, \mathrm{Mx}$ for the largest solar AR observed, we find that flares of GOES class $\approx$X500 could be produced ($E_{\rm bol} \approx 3 \cdot 10^{33}$ ergs). These estimates suggest that the present day's Sun is capable of producing flares and related space weather events that may be more than an order of magnitude stronger than have been observed to date.

astro-ph.SR↗