Three CMEs which erupted on 2017 Sep 4 and 6 underwent mutual interaction before reaching Earth on Sep 6-9, where it gave rise to a complex and unexpectedly geoeffective structure as detected by WIND at L1. The spacecraft first observed an interplanetary (IP) shock on Sep 6 followed by a turbulent sheath. The leg of the CME flux rope is detected on Sep 7, in which clear signatures of a shock-in-a-cloud can be distinguished, coming from the third CME which propagated into the preceding flux rope. We model the source of this complex ejecta with WSA-ENLIL+Cone and EUHFORIA to assess and compare the overall performance for interacting CMEs as opposed to single CME events. We find that following the conventional algorithm for determination of input parameters give large deviation in the event prediction at L1. The overestimated density of the IP shock 1 is due to the way of implementation of the magnetogram in WSA model. Excluding the slow CME from the input leads to even larger deviation. The prediction of IP shock 1 drastically improves by introducing of a customized density enhancement factor (dcld) based on coronagraph image observations. This novel approach, is simple and accessible, and could be applied to improve the forecast for fast, undisturbed CMEs. The deviation in the prediction of IP shock 2 comes from its interaction with the low proton temperature environment of the preceding magnetic cloud, giving rise to an expansion of the shock front. Additionally, the properties of the background solar wind plasma have been preconditioned by passage of the previous IP shock. This was confirmed from the kilometric type II radio burst emission following the eruption of the third CME. The propagation profile of this CME implies an almost non-existent deceleration in the interplanetary medium, in contrast to the expected CME deceleration due to interaction with the background plasma. In summary, this study presents clear indications that magnetic interaction must be taken into account to reliably forecast multiple CME events. Preconditioning of previous CMEs must also be considered in more depth, and ultimately requires a realistic, time-dependent model of the ambient solar wind which responds well to propagating shock waves. Models in space physics presents us with the perfect tools for understanding not only the physical processes that the simplified models can predict, but perhaps more importantly, help us begin to understand what the models fail to predict.

Coronal Mass Ejections (CMEs) are considered to be one of the most energetic events in the heliosphere. Capable of inducing geomagnetic storms on Earth that can cause damage to electronics, a pillar which the modern society we live in leans heavily upon. Being able to accurately predict the arrival of CMEs would present us with the ability to issue timely warnings to authorities and commercial actors, allowing for protective measures to be put in place minimizing the damage. In this study the predicted arrival times and speeds from the Drag Based Model (DBM) and Drag Based Ensemble Model (DBEM) were compared to observational data from a set of 12 events containing fast, Earth-directed Halo CMEs and their corresponding shocks. Although DBM was developed to model CME propagation, varying some parameters allow it to be used for estimating shock/sheath arrival. The results presented in this study indicate that on average DBM performs best when the drag-parameter γ is in the range 0.2 ≤ γ ≤ 0.3. However the variability in the results show that determining a universal value of γ for fast CMEs does not increase the consistency in the model's performance. For completeness, further investigation is needed to account for not only halo CMEs. This will allow to test broader range of variation in the DBEM input parameters.

Coronal Mass Ejections (CMEs) and solar flares are energetic events taking place at the Sun that can affect the space weather or the near-Earth environment by the release of vast quantities of electromagnetic radiation and charged particles. Solar active regions are the areas where most flares and CMEs originate. Studying the associations among sunspot groups, flares, filaments, and CMEs is helpful in understanding the possible cause and effect relationships between these events and features. Forecasting space weather in a timely manner is important for protecting technological systems and human life on earth and in space. The research presented in this thesis introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot groups, flares, filaments, and CMEs (2) applying machine learning algorithms to the associations¿ datasets and (3) studying the evolution patterns of sunspot groups using time-series methods. Machine learning algorithms are used to provide computerised learning rules and models that enable the system to provide automated prediction of CMEs, flares, and evolution patterns of sunspot groups. These numerical rules are extracted from the characteristics, associations, and time-series analysis of the available historical solar data. The training of machine learning algorithms is based on data sets created by investigating the associations among sunspots, filaments, flares, and CMEs. Evolution patterns of sunspot areas and McIntosh classifications are analysed using a statistical machine learning method, namely the Hidden Markov Model (HMM).

Ideal magnetohydrodynamics (MHD) simulations are known to have problems in satisfying the solenoidal constraint (i.e. the divergence of magnetic field should be equal to zero, $ ablacdotvec{B} = 0$). The simulations become unstable unless specific measures have been taken. In this thesis, a solenoidal constraint satisfying technique that allows discrete satisfaction of the solenoidal constraint up to the machine accuracy is presented and validated with a variety of test cases. Due to its inspiration from Chorin's artificial compressibility method developed for incompressible CFD applications, the technique was named as extit{artificial compressibility analogy (ACA)} approach. It is demonstrated that ACA is a purely hyperbolic, stable and consistent technique, which is moreover easy to implement. Unlike some other techniques, it does not pose any problems of the sort that $ ablacdotvec{B}$ errors accumulate in the vicinity of the stagnant regions of flow. With these crucial properties, ACA is thought to be a remedy to the drawbacks of the most commonly used solenoidal constraint satisfying techniques in the literature namely: Incorrect shock capturing and poor performance of the convective stabilization mechanism in regions of stagnant flow for Powell's source term method; exceedingly complex implementation for constrained transport technique due to the staggered grid representation; computationally expensive nature due to the necessity of a Poisson solver combined with hyperbolic/elliptic numerical methods for classical projection schemes. In the first chapter of the thesis, general background knowledge is given about plasmas, MHD and its history, a certain class of upwind finite volume methods, namely Riemann solvers, and their applications in MHD, the definition, constituents, formation mechanisms and effects of space weather and some of the space missions that are and will be performed in its prediction. Secondly, detailed analysis of the compressible ideal MHD equations is given in the form of the derivation of the equations, their dimensionless numbers which will be of use to specify the flows in the following chapters, and finally, the presentation of the MHD waves and discontinuities, which indicates the complexity of the system of ideal MHD equations and therefore their further numerical analysis. The next discussion is about the main subject of the thesis, namely the solenoidal constraint satisfying techniques. First of all, the definition and significance of the solenoidal constraint is given. Afterwards, the most common solenoidal constraint satisfying techniques in the literature are reviewed along with their abovementioned drawbacks. Moreover, particular emphasis is given to the Powell's source term approach which was also implemented in the upwind finite volume MHD solver developed. In addition, the hyperbolic divergence cleaning technique is presented in detail together with the resemblance and differences between it and ACA. Some other solenoidal constraint satisfying techniques are briefly mentioned at this stage. After these, ACA is presented in the following way: The point of inspiration, which is the analogy made with Chorin's artificial compressibility method developed for incompressible CFD, the introduction of the modified system of ideal MHD equations due to ACA, the derivation of the wave equation governing the propagation of $ ablacdotvec{B}$ errors and the analytical consistency proof. Having finished the core discussion of the thesis, the solver developed and its constituents are given in the fourth chapter. Furthermore, a brief overview of the platform into which this solver was implemented, namely COOLFluiD, is also given at this point. Afterwards, a thorough numerical verification of the ACA approach has been made on an increasingly complex suite of test cases. The results obtained with ACA and Powell's source term implementations are given in order to numerically analyse and verify ACA and compare the two methods and validate them with the results from literature. The sixth chapter is devoted to further validation of ACA performed with a variety of more advanced space weather-related simulations. In this chapter, also the $vec{B}_{ extrm{0}} + vec{B}_{ extrm{1}}$ splitting technique used to treat planetary magnetosphere is presented along with its application to ACA and Powell's source term approaches. This technique is utilized in obtaining the solar wind/Earth's magnetosphere interaction results and is based on suppressing the direct inclusion of the Earth's magnetic field, which is a dipole field, in the solution variables. In this way, problems are avoided with the energy equation that could arise from the drastic change of the ratio of the dipole field and the variable field computed by the solver (i.e. $frac{lvertvec{B}_{ extrm{0}}lvert}{lvertvec{B}_{ extrm{1}}lvert}$) in the computational domain. Finally, conclusions and future perspectives related to the material presented in the thesis are put forward.

The work described in this thesis is part of the Open Space project, a collaboration between Linköping University, NASA and the American Museum of Natural History. The long-term goal of Open Space is a multi-purpose, open-source scientific visualization software. The thesis covers the research and implementation of a pipeline for preparing and rendering volumetric data. The developed pipeline consists of three stages: A data formatting stage which takes data from various sources and prepares it for the rest of the pipeline, a pre-processing stage which builds a tree structure of of the raw data, and finally an interactive rendering stage which draws a volume using ray-casting. The pipeline is a fully working proof-of-concept for future development of Open Space, and can be used as-is to render space weather data using a combination of suitable data structures and an efficient data transfer pipeline. Many concepts and ideas from this work can be utilized in the larger-scale software project.

Space weather is the field within the space sciences that studies how the Earths magnetosphere is influenced by the Sun. The Sun is constantly emitting dangerous radiation and plasma which in some cases can affect or damage the systems on Earth. Scientists have an interest in studying this interaction and therefore visualizations of space weather data are useful. OpenSpace is an interactive software that visualizes the entire known universe with real-time data. OpenSpace supports a range of different visualization methods and techniques, for this work, the relevant visualization tools are field lines and cut planes. GAMERA is a simulation model that simulates a wide range of situations where plasma is subjected to the influence of magnetic fields, the simulations are based on curvilinear grids. This project focuses on implementing data from GAMERA into OpenSpace. OpenSpace already supports a variety of different simulation models, although none that uses curvilinear grids for the data. The curvilinear grid can adapt to the specific shape and geometry of the data, allowing for more accurate data representation. The project aims to create a pipeline for reading data files from simulation runs and visualize it as field lines and cut planes. The files used in this project contain data suitable for volumes and field lines. The method was to first develop a reader to extract and manage desired data from HDF5 files in which the simulation data is stored. The data used to visualize field lines is rendered with an already existing component in OpenSpace. Secondly, a slice operation was developed to extract cut planes from the files containing data for volume visualization, these are then visualized with the help of a component for rendering cut planes which was developed during this work. The work led to a pipeline that reads and manages simulation data from GAMERA and the data is successfully visualized. However, there is room for improvement in color rendering, robustness and level of user interaction during runtime. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

Earth is under constant influence of the Sun and phenomena driven by the solar wind that may affect man-made technology. These events are summarized under the concept of space weather. This creates variations in Earth’s magnetic field and nearby space. Space weather can affect power grids, gas pipelines and also have effects on human health. Due to these effects, as well as the scientific interest in space and the growing space industry, the need to monitor space weather, the space environment and how Earth is affected by them increases. Accurate magnetic mesurements rely on expensive magnetometers and careful calibration. Swedish Institute of Space Physics IRF, operates two magnetometers in Sweden, one observatory and one variometer to measure local geomagnetic variations. For the purpose of space weather, measurements of local variations have high demands on temporal resolution and precision but not the same need for long-term accuracy. The purpose of this thesis is to define and evaluate an autonomous system for local geomagnetic variations, with future hopes of creating a network of systems for space weather monitoring. The future goal is to be able to place systems in remote locations where they will be able to conduct measurements autonomously. The work was done by analysis and testing of a fluxgate magnetometer that was placed close to one of the IRFs existing magnetometers. Using data from the existing station as a reference, an analysis of the magnetometer could be performed. The results showed that the tested magnetometer had less precision than the existing station but could within a certain frequency range provide good results that make it possible to measure the local geomagnetic variations that may be of use for space weather. Conclusions from this study show that it is possible to create a simpler autonomous system for measurements of the local geomagnetic variations, but that this system requires further development, where future work can be based on this degree project as a basis. / Jorden är under konstant påverkan av solen och fenomen drivna av solvinden som kan påverka mänsklig teknologi. Dessa event sammanfattas under begreppet rymdväder. Genom detta skapas variationer i Jordens magnetfält och närliggande rymd. Rymdväder kan påverka kraftnät, gasledningar och även ha effekter på mänsklig hälsa. På grund av dessa effekter samt det vetenskapliga intresset för rymden och den växande rymdbranschen ökar behovet av att övervaka rymdväder, rymdmiljön samt hur Jorden påverkas av de. Exakta magnetiska mätningar är beroende av dyra magnetometrar och nogrann kalibrering. Institutet för Rymdfysik IRF driver två magnetometrar i Sverige, ett observatorium och en variometer för att mäta lokala geomagnetiska variationer. Då mätningar av lokala variationer har höga krav på temporal upplösning och precision men inte samma behov av kontroll på långsiktig noggrannhet. Syftet med det här examensarbetet är att definiera och utvärdera ett autonomt system för lokala geomagnetiska variationer, med framtida förhoppningar om att skapa ett nätverk av system för övervakning av rymdväder. Framtidsmålet är att kunna placera ut system på avlägsna platser där det autonomt ska kunna bedrivas mätningar. Arbetet gjordes genom analys och tester med en fluxgate-magnetometer som placerades i närheten av en av IRF befintliga magnetometrar. Med data från den existerande stationen som referens kunde en analys av magnetometern utföras. Resultatet visade att den testade magnetometern hade mindre precision än den befintliga stationen men kunde inom ett viss frekvensspann förse goda resultat som gjorde det möjligt att mäta de lokala geomagnetiska variationerna som kan vara till nytta för rymdväder. Slutsatser från denna studie visar att det är möjligt att skapa ett enklare autonomt system för mätningar av de lokala geomagnetiska variationerna men att detta system kräver vidare utveckling, där framtida arbete kan utgå från resultaten som erhölls i detta examensarbete.

Yes / This paper aims at providing an overview of latest advances in space weather modeling in an operational environment in Europe, including both the introduction of new models and improvements to existing codes and algorithms that address the broad range of space weather's prediction requirements from the Sun to the Earth. For each case, we consider the model's input data, the output parameters, products or services, its operational status, and whether it is supported by validation results, in order to build a solid basis for future developments. This work is the output of the Sub Group 1.3 "Improvement of operational models'' of the European Cooperation in Science and Technology (COST) Action ES0803 "Developing Space Weather Products and services in Europe'' and therefore this review focuses on the progress achieved by European research teams involved in the action.

Ideal magnetohydrodynamics (MHD) simulations are known to have problems in satisfying the solenoidal constraint (i.e. the divergence of magnetic field should be equal to zero, $<p>ablacdotvec{B} = 0$). The simulations become unstable unless specific measures have been taken.<p><p>In this thesis, a solenoidal constraint satisfying technique that allows discrete satisfaction of the solenoidal constraint up to the machine accuracy is presented and validated with a variety of test cases. Due to its inspiration from Chorin's artificial compressibility method developed for incompressible CFD applications, the technique was named as \ / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished