Nowadays, space weather has become an international issue to the world's countries because of its catastrophic effect on space-borne and ground-based systems, and industries, impacting our lives. One of the main solar activities that is considered as a major driver of space weather is solar flares. Solar flares can be defined as an enormous eruption in the sun's atmosphere. This phenomenon happens when magnetic energy stored in twisted magnetic fields, usually near sunspots, is suddenly released. Yet, their occurrence is not fully understood. These flares can affect the Earth by the release of massive quantities of charged particles and electromagnetic radiation. Investigating the associations between solar flares and sunspot groups is helpful in comprehending the possible cause and effect relationships among solar flares and sunspot features. 01 This thesis proposes a new approach developed by integrating advances in image processing, machine learning, and deep learning with advances in solar physics to extract valuable knowledge from historical solar data related to sunspot regions and flares. This dissertation aims to achieve the following: 1) We developed a new prediction algorithm based on the Automated Solar Activity Prediction system (ASAP) system. The proposed algorithm updates the ASAP system by extending the training process and optimizing the learning rules to the optimize performance better. Two neural networks are used in the proposed approach. The first neural network is used to predict whether a specific sunspot class at a particular time is likely to produce a significant flare or not. The second neural network is used to predict the type of this flare, X or M-class. 2) We proposed a new system called the ASAP_Deep system built on top of the ASAP system introduced in [6] but improves the system with an updated deep learning-based prediction capability. In addition, we successfully apply Convolutional Neural Network (CNN) to the sunspot group image without any pr-eprocessing or feature extraction. Moreover, our system results are considerably better, especially for the false alarm ratio (FAR); this reduces the losses resulting from the protection measures applied by companies. In addition, the proposed system achieves a relatively high score of True Skill Statistic (TSS) and Heidke Skill Score (HSS). 3) We presented a novel system that used the Deep Belief Networks (DBNs) to predict the solar flares occurrence. The input data are SDO/HMI Intensitygram and Magnetogram images. The model outputs are "Flare or No-Flare" of significant flare occurrence (M and X-class flares). In addition, we created a dataset from the sunspots groups extracted from SDO HMI Intensitygram images. We compared the results obtained from the complete suggested system with those of three previous flare forecast models using several statistical metrics. In our view, these developed methods and results represent an excellent initial step toward enhancing the accuracy of flare forecasting, enhance our understanding of flare occurrence, and develop efficient flare prediction systems. The systems, implementation, results, and future work are explained in this dissertation.

No / The effect of a self-induced electric field is investigated analytically and numerically on differential and mean electron spectra produced by beam electrons during their precipitation into a flaring atmosphere as well as on the emitted hard X-ray (HXR) photon spectra. The induced electric field is found to be a constant in upper atmospheric layers and to fall sharply in the deeper atmosphere from some "turning point" occurring either in the corona (for intense and softer beams) or in the chromosphere (for weaker and harder beams). The stronger and softer the beam, the higher the electric field before the turning point and the steeper its decrease after it. Analytical solutions are presented for the electric fields, which are constant or decreasing with depth, and the characteristic "electric" stopping depths are compared with the "collisional" ones. A constant electric field is found to decelerate precipitating electrons and to significantly reduce their number in the upper atmospheric depth, resulting in their differential spectra flattening at lower energies (<100 keV). While a decreasing electric field slows down the electron deceleration, allowing them to precipitate into deeper atmospheric layers than for a constant electric field, the joint effect of electric and collisional energy losses increases the energy losses by lower energy electrons compared to pure collisions and results in maxima at energies of 40-80 keV in the differential electron spectra. This, in turn, leads to the maxima in the mean source electron spectra and to the "double power law" HXR photon spectra (with flattening at lower energies) similar to those reported from the RHESSI observations. The more intense and soft the beams are, the stronger is the lower energy flattening and the higher is the "break" energy where the flattening occurs.

Yes / In this paper, we introduce two novel models for processing real-life satellite images to quantify and then visualise their magnetic structures in 3D. We believe this multidisciplinary work is a real convergence between image processing, 3D visualization and solar physics. The first model aims to calculate the value of the magnetic complexity in active regions and the solar disk. A series of experiments are carried out using this model and a relationship has been indentified between the calculated magnetic complexity values and solar flare events. The second model aims to visualise the calculated magnetic complexities in 3D colour maps in order to identify the locations of eruptive regions on the Sun. Both models demonstrate promising results and they can be potentially used in the fields of solar imaging, space weather and solar flare prediction and forecasting.

yes / The importance of real-time processing of solar data especially for space weather applications is increasing continuously. In this paper, we present an automated hybrid computer platform for the short-term prediction of significant solar flares using SOHO/Michelson Doppler Imager images. This platform is called the Automated Solar Activity Prediction tool (ASAP). This system integrates image processing and machine learning to deliver these predictions. A machine learning-based system is designed to analyze years of sunspot and flare data to create associations that can be represented using computer-based learning rules. An imaging-based real-time system that provides automated detection, grouping, and then classification of recent sunspots based on the McIntosh classification is also created and integrated within this system. The properties of the sunspot regions are extracted automatically by the imaging system and processed using the machine learning rules to generate the real-time predictions. Several performance measurement criteria are used and the results are provided in this paper. Also, quadratic score is used to compare the prediction results of ASAP with NOAA Space Weather Prediction Center (SWPC) between 1999 and 2002, and it is shown that ASAP generates more accurate predictions compared to SWPC. / EPSRC

Σε αυτήν την εργασία συζητάμε κυρίως τις ηλιακές παρατηρήσεις οι οποίες προτείνουν την ύπαρξη του σωματιδίου axion. Η αρχή λειτουργίας των ηλιακών τηλεσκοπίων που χρησιμοποιούνται για την ανίχνευση των ηλιακών axions μπορεί να βρίσκεται πίσω από την απροσδόκητη ηλιακή εκπομπή ακτίνων X, ακόμη και επάνω από 3.5 keV από τα μη ενεργά active regions. Επειδή αυτό συνδέεται με τα ηλιακά μαγνητικά πεδία και παρουσιάζει την αναμενόμενη B2 εξάρτηση, που είναι χαρακτηριστική για την αλληλεπίδραση τους με μαγνητικά πεδία. Τα μαγνητικά πεδία γίνονται σε αυτό το πλαίσιο ο καταλύτης και όχι η ειδάλλως πιθανή/απροσδιόριστη πηγή ενέργειας των ηλιακών ακτίνων X. Επιπλέον, ίσως μπορέσουμε (ίσως και όχι) να είμαστε σε θέση να αναδημιουργήσουμε πλήρως τον υποτιθέμενο ενσωματωμένο συντονισμό αλληλεπίδρασης των axions στον ήλιο και, να είμαστε σε θέση (ή και όχι) να τον αντιγράψουμε σε ένα επίγειο πείραμα. Τα σήματα των ηλιακών axions μπορεί να είναι παροδικές εκλάμψεις ακτίνων X ή συνεχής ακτινοβολία, όπως π.χ. από την κορώνα η οποία εκ πρώτης όψεος παραβιάζει το δεύτερο νόμο της θερμοδυναμικής καθώς και το νόμο Planck περί ακτινοβολίας μέλανος σώματος. Για την κατανόηση του προβλήματος της ηλιακής κορώνας και των άλλων ηλιακών μυστηρίων, όπως είναι οι ηλιακές καταιγίδες, οι ηλιακές κηλίδες, οι κατανομές χημικών στοιχείων, κ.λ.π., καταλήγουμε τουλάχιστον σε δύο νέα ‘εξωτικά σωματίδια’, όπως είναι: α) παγιδευμένα ‘βαριά’ axions τύπου Kaluza-Klein τα οποία διασπώνται ακτινοβολώντας και επιτρέπουν μια συνεχή αυτο-ακτινοβολία του ήλιου, μέσω της αυθόρμητης διάσπασής τους σε δύο φωτόνια. Αυτή η διεργασία εξηγεί την ξαφνική αναστροφή θερμοκρασίας στα ~2000 χλμ επάνω από την επιφάνεια του ήλιου. β) εξερχόμενα ‘ελαφριά’ axions, τα οποία αλληλεπιδρούν με τα τοπικά μαγνητικά πεδία μέσω της χαρακτηριστικής εξάρτησης (~B2). Η αλληλεπίδραση αυτή εξαρτάται από πολλές παραμέτρους, μία εκ των οποίων είναι η συχνότητα πλάσματος του περιβάλλοντος χώρου. Η συχνότητα αυτή θα πρέπει να ταιριάζει με τη μάζα ηρεμίας του axion, προκειμένου να έχουμε τον επιθυμητό συντονισμό. Η αναμενόμενη συμπεριφορά αυτών των δυο κατηγοριών αυτή εξηγεί τα κατά τα άλλα απρόβλεπτα παροδικά, αλλά ταυτόχρονα και συνεχή, ηλιακά φαινόμενα. Κατόπιν, η ενεργειακή κατανομή των φωτονίων ενός υποψήφιου φαινομένου άγνωστης προέλευσης μπορεί να ‘φωτογραφίσει’ το σημείο γέννησης των axions. Παραδείγματος χάριν, αυτό θα μπορούσε να προτείνει ότι ηλιακή κορώνα θερμοκρασίας ~2MK έχει τις ρίζες της στο πάνω μέρος της «ζώνης ακτινοβολίας» (radiation zone) ακόμα κι αν αυτό από μόνο του δεν μπορεί να εξηγήσει προφανώς την τόσο απότομη περιοχή μετάπτωσης μεταξύ της χρωμόσφαιρας και της κορώνας. Το προβλεφθέν μαγνητικό πεδίο Β ≈ 10 – 50 Τ στην αποκαλούμενη tachocline σε ακτίνα ~0.7R๏, κάνει αυτήν την περιοχή μια πιθανή νέα πηγή ηλιακών axions. Σε κάθε περίπτωση, η πολλαπλή σκέδαση φωτονίων μέσω του φαινομένου Compton ενισχύει τη μετατροπή φωτονίων από axions, δεδομένου ότι τα axions δεν μπορουν να αλληλεπιδράσουν πολλές φορές και έτσι δραπετεύουν. Καταλήγουμε λοιπόν στο συμπέρασμα ότι η ενεργειακή κατανομή κάτω από περίπου 100 eV είναι ένα νέο παράθυρο για τις αναζητήσεις axion. Εντυπωσιακά, αυτή η ενεργιακή κατανομή συμπίπτει με το γεγονός ότι: α) οι ενέργειες των φωτονίων που προκύπτουν από την αυθόρμητη διάσπαση των axions για μια εξωτερική αυτο-ακτινοβολία του ήλιου, πρέπει να διαπεράσουν μέχρι την ‘περιοχή μετάπτωσης’ στα ~2000 χλμ επάνω από την ηλιακή επιφάνεια, και β) με την κύρια συνιστώσα της ηλιακής φωτεινότητας ακτίνων X χαμηλής ενέργειας, η οποία είναι άγνωστης προέλευσης. Κατά συνέπεια, τα άμεσα/έμμεσα σήματα υποστηρίζουν τα axions ως μια εξήγηση της αινιγματικής συμπεριφοράς του ήλιου. Π.χ., η ανεξήγητη «solar oxygen crisis». Έτσι, λαμβάνοντας υπόψη σχετικές παρατηρήσεις στους ‘πόρους’, παρατηρείται μια επίσης εντυπωσιακή ~B2 εξάρτηση της κατανομής των χημικών στοιχείων πάνω απο έναν ‘πόρο’. Όλη αυτή η συμπεριφορά μπορεί να εξηγηθεί μέσω της πίεσης ακτινοβολίας απο την εκπομπή ακτίνων X που προέρχονται από τα axions του ηλιακού πυρήνα, ή, ακόμη και από κάποια άλλη εσωτερική ηλιακή πηγή axions. Έτσι, κεραίες αxions θα μπορούσαν να αξιοποιήσουν / ενσωματώσουν ένα τέτοιο μηχανισμό. Τέλος, η παρατηρηθείσα χαμηλο-ενεργειακή εκπομπή ακτίνων X από τον ‘ήρεμο’ ήλιο στα υψηλότερα πλάτη καθώς επίσης και η εκτεταμένη δραστηριότητα που συνδέεται με τις μαγνητικές δομές, που διασχίζουν το κέντρο του ηλιακού δίσκου, προτείνουν ότι τελικά έχουμε να κάνουμε με ένα σενάριο axions πολλών συνιστωσών. Ένα τέτοιο σενάριο ίσως είναι τελικά στην πράξη, αυτό που εξηγεί γιατί τα ηλιακά axions δεν έχουν προσδιοριστεί / παρατηρηθεί μέχρι τώρα στο καθ’ολα πλούσιο και χωρο-χρονικά μεταβαλλόμενο ηλιακό φάσμα ακτίνων X. Τέλος, υποστηρίζουμε, σε αυτήν την εργασία ότι, τα ηλιακά axions που μετατρέπονται σε (υψηλοενεργειακές) ακτίνες X κοντά στην ηλιακή επιφάνεια μπορούν να ιονίσουν τα ανωτέρω στρώματα. Αυτό έχει σαν αποτέλεσμα την ισοτροπική Compton σκέδαση και την ενεργειακή υποβάθμιση των φωτονίων. Τα φωτόνια διαδίδονται μέσα στο πλάσμα με πολλαπλές σκεδάσεις Compton (τυχαίος βηματισμός). Και τα δύο φαινόμενα επιτρέπουν για πρώτη φορά την σύνδεση της ηλιακής εκπομπής ακτίνων X με το τυποποιημένο πρότυπο ηλιακών axions. Δηλαδή, έχουμε να κάνουμε όχι μόνο με μια ακτινική εκπομπή ακτίνων X που προέρχονται από το κέντρο του ηλιακού δίσκου αλλά και με ένα ενεργειακό φάσμα που μετατοπίζεται προς όλο και χαμηλότερες ενέργειες. Αυτό είναι κάτι νέο που προέκυψε από αυτήν την εργασία. Επιπλέον, τονίζουμε ότι, από την λογική αυτής της εργασίας προκύπτει το σημείο γέννησης / μετατροπής axions, και μάλιστα ‘φωτογραφίζοντας’ την ηλιακή επιφάνεια. Αυτό το συμπέρασμα είναι πολύ σημαντικό. Διότι, εάν υιοθετήσουμε το ευρέως διαδεδομένο, αντίστροφο φαινόμενο Primakoff, που πιστεύεται ότι προκαλεί αυτήν την αλληλεπίδραση, όπως γίνεται παραδείγματος χάριν στην 2η φάση του πειράματος CAST με το ‘buffer gas’ στους μαγνητικούς σωλήνες, καταλήγουμε για πρώτη φορά σε μια μάζα ηρεμίας ενός σωματιδίου όπως είναι το axion: maxion ≥ 0.01 eV/c2. Αυτό το γεγονός μαζί με την γωνιακή και ενεργειακή κατανομή των ακτίνων Χ, που προέρχονται από axions στην επιφάνεια του ήλιου, προέκυψαν από αυτήν την εργασία. Επίσης, και η ανάλυση των δισδιάστατων κατανομών ηλιακών ακτίνων Χ χαμηλής ενέργειας απο δημοσιευθέντα αρχεία δεδομένων οδήγησε σε νέα αποτελέσματα. / We discuss mainly solar signatures suggesting axion or axion(-like) particles. The working principle of axion helioscopes can be behind unexpected solar X-ray emission, even above 3.5 keV from non-flaring active regions. Because this is associated with solar magnetic fields shows the expected B2- dependence. The magnetic fields become in this framework the catalyst and not the otherwise suspected / unspecified energy source of solar X-rays. In addition, the built–in fine tuning we may (not) be able to fully reconstruct, and, we may (not?) be able to copy in an earth bound experiment. Solar axion signals are transient X-ray brightenings, or, continuous radiation from the corona violating at first sight the second law of thermodynamics and Planck’s law of black body radiation. To understand the corona problem and other mysteries like flares, sunspots, elemental abundances, etc., we arrive at least at two exotica: a) trapped, radiatively decaying, massive axions of the Kaluza Klein type allow a continuous self-irradiation of the Sun, via their spontaneous decay, explaining the sudden temperature inversion ~2000 km above the Sun’s surface and b) outstreaming light axions interact with local fields (~B2), depending crucially, among other parameters on the plasma frequency which must match the axion rest mass, explaining the otherwise unpredictable transient, but also continuous, solar phenomena. Then, the photon energy distribution of a related phenomenon of unknown origin might point at the birth place of involved axions. For example, this could suggest that the ~2 MK solar corona has its axion roots at the top of the radiative zone even though this alone can not explain the steep transition region (TR) between the chromosphere and the corona. The predicted B ≈ 10–50 T at the so called tachocline at ~0.7R, make this place a potential coherent axion source, while the multiple photon scattering enhances the photon-to-axion conversion unilaterally, since axions escape. We conclude that the energy range below some 100 eV is a new window of opportunity for axion searches. Remarkably, it coincides with a) the 10 derived photon energies for an external self-irradiation of the Sun, which has to penetrate until the transition region at ~2000 km above the solar surface, and b) with the bulk of the soft solar X-ray luminosity, which is of unknown origin. Thus, (in)direct signatures support axions or the like as an explanation of enigmatic behavior in the Sun and beyond; e.g., the otherwise unexplained “solar oxygen crisis” taking into account related observations in pores, which also show striking ~B2 – dependence of elemental abundance in a pore. They can be associated with the radiation pressure of the X-ray emission from converted axions from the solar core, or, other as yet unpredicted inner solar axion source. Axion antennas could take advantage of such a feed back. Finally, the observed soft X-ray emission from the quiet Sun at highest latitudes as well as the extended activity associated with magnetic structures crossing the solar disk centre suggest that a multi-component axion(-like) scenario is finally at work, which explains why the solar axions have not been identified / noticed before in the rich and spatiotemporarily changing solar X-ray spectrum. Finally, it is arguing in this work that solar axions converted to (hard) X-rays near the solar surface can ionize the layers above. This gives rise to the isotropic Compton scattering and to the photon energy degradation while the photons propagate inside the plasma. Both effects allow for the first time to reconcile solar X-ray emission with the standard solar axion model, i.e. not only radial X-ray emission distinguishing thus the solar disk center, and, an energy spectrum shifted towards lower and lower energies. Moreover, the concluded place of birth of the axion conversion points at the solar surface. If we assume the widely mentioned coherent inverse Primakoff-effect being behind this interaction, as it is done for example in CAST phase II with buffer gas in the magnetic pipes, then the axion or axion-like rest mass is maxion ≥ 0.01 eV/c^2.

Machine-learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CME catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flare and CME data, which are later arranged in numerical-training vectors and fed to machine-learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Properties representing the intensity, flare duration, and duration of decline and duration of growth are extracted from all the associated (A) and not-associated (NA) flares and converted to a numerical format that is suitable for machine-learning use. The machine-learning algorithms Cascade Correlation Neural Networks (CCNN) and Support Vector Machines (SVM) are used and compared in our work. The machine-learning systems predict, from the input of a flare¿s properties, if the flare is likely to initiate a CME. Intensive experiments using Jack-knife techniques are carried out and the relationships between flare properties and CMEs are investigated using the results. The predictive performance of SVM and CCNN is analysed and recommendations for enhancing the performance are provided. / EPSRC

Made available in DSpace on 2016-03-15T19:35:58Z (GMT). No. of bitstreams: 1 Douglas Felix da Silva.pdf: 5938737 bytes, checksum: aa521c46d45966ffa8b9f1f8067be11c (MD5) Previous issue date: 2016-01-28 / Fundação de Amparo a Pesquisa do Estado de São Paulo / Solar flares are characterized by a sudden release of energy, of magnetic origin, that accelerates particles producing emission throughout the entire electromagnetic spectrum and plasma heating. It is believed that a fraction of these accelerated particles are injected into bipolar magnetic fields. Radiation from these events at radio wavelengths is due to the acceleration of the energetic particles that spiral around magnetic loops. Thus masurements of right and left circularly polarized brightness temperature of three flares at the frequencies of 45 and 90 GHz yield degrees of circular polarization that reached 5 to 40 % and were opposites at 45 and 90 GHz, always being reversed for the events. The interpretation of these results may be associated with the asymmetry of the field strength of magnetic loop legs. The objective of this work is to study the magnetic field configuration and energy distribution of accelerated particles in solar flares. For the study of these solar flares, we use the observations of the telescopes POEMAS (POlarization Emission of Millimeter Solar Activity), that monitor the Sun at 45 and 90 GHz with circular polarization. Observations in radio were complemented with microwaves, using data from the Radio Solar Telescope Network (RSTN) at 1-15 GHz, and high frequency emission, at 212 and 405 GHz, observed by the Solar Submillimeter Telescope (SST). X-ray data were obtained from FERMI and RHESSI telescopes; and the Solar Dynamics Observatory (SDO) provided images at 171 Å and magnetograms of the active regions. To study the interaction between the particles and magnetic field we applied the model developed by Simões (2009). Numerical simulations were performed and produced sources at 45 and 90 GHz in a three dimensional magnetic loop with maximum intensity in opposite polarities of a dipole loop. The simulations also reproduced the degree of polarization and radio spectra observed in each event. Thus, by means of the simulations, we obtained the location of 45 and 90 GHz sources with predominant intensities in opposite magnetic polarities and with reversed degree of polarization. / A explosão solar é caracterizada por uma súbita liberação de energia, de origem magnética, a qual acelera as partículas produzindo emissão em todo o espectro eletromagnético e promovendo o aquecimento do plasma. Acredita-se que uma fração destas partículas não térmicas aceleradas são injetadas em campos magnéticos bipolares. A emissão de radiação proveniente dos eventos na faixa rádio é devida à aceleração das partículas energéticas associada ao movimento em espiral que fazem em torno dos arcos magnéticos. Medidas de temperatura de brilho circularmente polarizada à direita e à esquerda em três explosões solares nas frequências de 45 e 90 GHz apresentaram graus de polarização circular que alcançaram de 5 a 40 % e opostos em 45 e 90 GHz, sempre sendo invertidos para os eventos estudados. Uma interpretação desses resultados pode estar associada com a assimetria de intensidade do campo nos pés do arco magnético. O objetivo do trabalho é estudar a configuração do campo magnético e a distribuição de energia das partículas aceleradas em explosões solares na faixa rádio. Para o estudo das explosões, utilizamos as observações do sistema de telescópios POEMAS (POlarização da Emissão Milimétrica da Atividade Solar), que monitora o Sol em 45 e 90 GHz com medidas de polarização. As observações em rádio foram complementadas em micro-ondas, utilizando os dados da Rede de Radio Telescópios Solares (RSTN), de 1 a 15 GHz, e em altas frequências (212 e 405 GHz) pelo Telescópio Solar Submilimetrico (SST). Na faixa de raio X foram utilizados dados dos telescópios FERMI e RHESSI; enquanto do Solar Dynamics Observatory (SDO) foram obtidas imagens em 171 Å e magnetogramas das região ativas. Para estudar a interação entre as partículas e campo magnético foi aplicado o modelo desenvolvido por Simões (2009). Foram realizadas simulações numéricas que produziram fontes em 45 e 90 GHz num arco magnético em três dimensões, cujas fontes apresentaram máximos de intensidade em polaridades opostas de um arco dipolar. As simulações também reproduziram qualitativamente o grau de polarização observado em cada um dos eventos e também o espectro rádio. Assim, por meio da simulação, obtivemos as possíveis localizações das fontes em 45 e 90 GHz com intensidades predominantes em polaridades opostas e grau de polarização invertido.

Solar transient eruptions are the main cause of interplanetary-magnetospheric disturbances leading to the phenomena known as geomagnetic storms. Eruptive solar events such as coronal mass ejections (CMEs) are currently considered the main cause of geomagnetic storms (GMS). GMS are strong perturbations of the Earth’s magnetic field that can affect space-borne and ground-based technological systems. The solar-terrestrial impact on modern technological systems is commonly known as Space Weather. Part of the research study described in this thesis was to investigate and establish a relationship between GMS (periods with Dst ≤ −50 nT) and their associated solar and interplanetary (IP) properties during solar cycle (SC) 23. Solar and IP geoeffective properties associated with or without CMEs were investigated and used to qualitatively characterise both intense and moderate storms. The results of this analysis specifically provide an estimate of the main sources of GMS during an average 11-year solar activity period. This study indicates that during SC 23, the majority of intense GMS (83%) were associated with CMEs, while the non-associated CME storms were dominant among moderate storms. GMS phenomena are the result of a complex and non-linear chaotic system involving the Sun, the IP medium, the magnetosphere and ionosphere, which make the prediction of these phenomena challenging. This thesis also explored the predictability of both the occurrence and strength of GMS. Due to their nonlinear driving mechanisms, the prediction of GMS was attempted by the use of neural network (NN) techniques, known for their non-linear modelling capabilities. To predict the occurrence of storms, a combination of solar and IP parameters were used as inputs in the NN model that proved to predict the occurrence of GMS with a probability of 87%. Using the solar wind (SW) and IP magnetic field (IMF) parameters, a separate NN-based model was developed to predict the storm-time strength as measured by the global Dst and ap geomagnetic indices, as well as by the locally measured K-index. The performance of the models was tested on data sets which were not part of the NN training process. The results obtained indicate that NN models provide a reliable alternative method for empirically predicting the occurrence and strength of GMS on the basis of solar and IP parameters. The demonstrated ability to predict the geoeffectiveness of solar and IP transient events is a key step in the goal towards improving space weather modelling and prediction.

Solar flares and eruptions are manifestations of violent releases of magnetic energy from the solar atmosphere. They are powered by magnetic reconnection, a mechanism in which magnetic field lines change their connectivities to reach a lower-energetic state. Theoretical predictions regarding the generalised three-dimensional magnetic reconnection are imposed by the standard flare model in 3D. In this work we present the results of five peer-reviewed publications in which we focused on different predicted aspects of magnetic reconnection in 3D. We analyse evolution and morphology of seven eruptive flares, primarily using observations of the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory. In the first publication, (Lörinčík et al., 2019a), we interpreted variations of velocities of slipping flare kernels using the mapping norm of field line connectivity simulated via the model. In Lörinčík et al. (2019b) we showed that the observed conversion of filament strands to flare loops is a signature of the 'ar-rf' reconnection geometry between erupting flux rope and overlying coronal arcades. In another observation (Dudík, Lörinčík et al. (2019)), all constituents of this geometry were successfully identified together with the constituents of the 'rr-rf' geometry between two...

Space weather has become an international issue due to the catastrophic impact it can have on modern societies. Solar flares are one of the major solar activities that drive space weather and yet their occurrence is not fully understood. Research is required to yield a better understanding of flare occurrence and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, inspired by the physical Ising model, to estimate the magnetic complexity in active regions using solar images and an investigation of this measurement in relation to flare occurrence. The proposed name of the measurement is the Ising Magnetic Complexity (IMC). ii) Determination of the flare prediction capability of active region properties generated by the new active region detection system SMART (Solar Monitor Active Region Tracking) to enable the design of a new flare prediction system. iii) Determination of the active region properties that are most related to flare occurrence in order to enhance understanding of the underlying physics behind flare occurrence. The achieved results can be summarised as follows: i) The new active region measurement (IMC) appears to be related to flare occurrence and it has a potential use in predicting flare occurrence and location. ii) Combining machine learning with SMART¿s active region properties has the potential to provide more accurate flare predictions than the current flare prediction systems i.e. ASAP (Automated Solar Activity Prediction). iii) Reduced set of 6 active region properties seems to be the most significant properties related to flare occurrence and they can achieve similar degree of flare prediction accuracy as the full 21 SMART active region properties. The developed technologies and the findings achieved in this thesis will work as a corner stone to enhance the accuracy of flare prediction; develop efficient flare prediction systems; and enhance our understanding of flare occurrence. The algorithms, implementation, results, and future work are explained in this thesis.