The State of Space Weather Scientific Modeling—An Introduction

The discipline of “Space Weather” is built on the scientific foundation of solar-terrestrial physics but with a strong orientation toward applied research. Models describing the solar-terrestrial environment are therefore at the heart of this discipline, for both physical understanding of the processes involved and establishing the capability to predict the consequences of these processes. This issue of Space Science Reviews contains four topical reviews on primarily European scientific progress in understanding and modeling space weather phenomena. The four reviews deal with (i) monitoring, modeling and predicting solar weather, (ii) the radiation environment of the Earth, (iii) solar wind disturbances and their interaction with geospace, and (iv) the upper atmosphere’s response to space weather events.     

The influence of in situ pitch-angle cosine coverage on the derivation of solar energetic particle injection and interplanetary transport conditions

Modelization of solar energetic particle (SEP) events aims at revealing the general scenario of SEP injection and interplanetary propagation and relies on in situ measurements of SEP distributions. In this paper, we study to what extent the LEFS60 and LEMS30 electron telescopes of the Electron Proton Alpha Monitor (EPAM) on board the Advanced Composition Explorer are able to scan pitch-angle distributions during near-relativistic electron events. We estimate the percentage of the pitch-angle cosine range scanned by both telescopes for a given magnetic field configuration. We obtain that the pitch-angle coverage is always higher for LEFS60 than for LEMS30. Therefore, LEFS60 provides more information of the directional distribution of the observed particles. The aim of the paper is to study the relevance of the coverage when fitting LEFS60 particle measurements in order to infer the solar injection and the interplanetary transport conditions. By studying synthetic electron events, we obtain that at least 70% of the pitch-angle cosine range needs to be scanned by the telescope. Otherwise, multiple scenarios can explain the data.     

CME Theory and Models

This chapter provides an overview of current efforts in the theory and modeling of CMEs. Five key areas are discussed: (1) CME initiation; (2) CME evolution and propagation; (3) the structure of interplanetary CMEs derived from flux rope modeling; (4) CME shock formation in the inner corona; and (5) particle acceleration and transport at CME driven shocks. In the section on CME initiation three contemporary models are highlighted. Two of these focus on how energy stored in the coronal magnetic field can be released violently to drive CMEs. The third model assumes that CMEs can be directly driven by currents from below the photosphere. CMEs evolve considerably as they expand from the magnetically dominated lower corona into the advectively dominated solar wind. The section on evolution and propagation presents two approaches to the problem. One is primarily analytical and focuses on the key physical processes involved. The other is primarily numerical and illustrates the complexity of possible interactions between the CME and the ambient medium. The section on flux rope fitting reviews the accuracy and reliability of various methods. The section on shock formation considers the effect of the rapid decrease in the magnetic field and plasma density with height. Finally, in the section on particle acceleration and transport, some recent developments in the theory of diffusive particle acceleration at CME shocks are discussed. These include efforts to combine self-consistently the process of particle acceleration in the vicinity of the shock with the subsequent escape and transport of particles to distant regions.     

History of cosmic ray research in Finland

The history of cosmic ray research in Finland can be traced back to the end of 1950s, when first ground-based cosmic ray measurements started in Turku. The first cosmic ray station was founded in Oulu in 1964 performing measurements of cosmic rays by a muon telescope, which was later complemented by a neutron monitor. Since the 1990s, several research centers and universities, such as The Finnish Meteorological Institute, Helsinki University of Technology, University of Oulu, University of Turku and University of Helsinki have been involved in space science projects, such as SOHO, AMS, Cluster, Cassini, BepiColombo, etc. At the same time, ground-based cosmic ray measurements have reached a new level, including a fully automatic on-line database in Oulu and a new muon measuring underground site in Pyhäsalmi. Research groups in Helsinki, Oulu and Turku have also extensive experience in theoretical investigations of different aspects of cosmic ray physics. Cosmic ray research has a 50-year long history in Finland, covering a wide range from basic long-running ground-based observations to high-technology space-borne instrumentation and sophisticated theoretical studies. Several generations of researchers have been involved in the study ensuring transfer of experience and building the recognized Finnish research school of cosmic ray studies.     

Thermoviscoelastic Analysis of Stress in Composite Structures- Micro-to-Structural Approach

Manufacturing of composite materials is usually accompanied with residual stresses. These stresses should be evaluated and assessed. To this end, a micromechanical model for periodic material whose temperature dependent constituents behave as thermorheologically complex materials （TCM） has been developed. This model, referred as the high fidelity generalized method of cells （HFGMC）, takes into account the detailed interaction be- tween the fiber and resin, their volume ratios, the fibers distribution and their waviness. This model is linked, in conjunction with a special UMAT subroutine, to the ABAQUS finite element code for prediction of the response of thermoviscoelastic composite structures during cool down process. The present investigation shows the effect of the cool down rate on the residual stress developed in the composite cylindrical structures.     

The automated prediction of solar flares from SDO images using deep learning

In the last few years, there has been growing interest in near-real-time solar data processing, especially for space weather applications. This is due to space weather impacts on both space-borne and ground-based systems, and industries, which subsequently impacts our lives. In the current study, the deep learning approach is used to establish an automated hybrid computer system for a short-term forecast; it is achieved by using the complexity level of the sunspot group on SDO/HMI Intensitygram images. Furthermore, this suggested system can generate the forecast for solar flare occurrences within the following 24 h. The input data for the proposed system are SDO/HMI full-disk Intensitygram images and SDO/HMI full-disk magnetogram images. System outputs are the “Flare or Non-Flare” of daily flare occurrences (C, M, and X classes). This system integrates an image processing system to automatically detect sunspot groups on SDO/HMI Intensitygram images using active-region data extracted from SDO/HMI magnetogram images (presented by Colak and Qahwaji, 2008) and deep learning to generate these forecasts. Our deep learning-based system is designed to analyze sunspot groups on the solar disk to predict whether this sunspot group is capable of releasing a significant flare or not. Our system introduced in this work is called ASAP_Deep. The deep learning model used in our system is based on the integration of the Convolutional Neural Network (CNN) and Softmax classifier to extract special features from the sunspot group images detected from SDO/HMI (Intensitygram and magnetogram) images. Furthermore, a CNN training scheme based on the integration of a back-propagation algorithm and a mini-batch AdaGrad optimization method is suggested for weight updates and to modify learning rates, respectively. The images of the sunspot regions are cropped automatically by the imaging system and processed using deep learning rules to provide near real-time predictions. The major results of this study are as follows. Firstly, the ASAP_Deep system builds on the ASAP system introduced in Colak and Qahwaji (2009) but improves the system with an updated deep learning-based prediction capability. Secondly, we successfully apply CNN to the sunspot group image without any pre-processing or feature extraction. Thirdly, 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. Also, the proposed system achieves a relatively high scores for True Skill Statistics (TSS) and Heidke Skill Score (HSS).     

Multi-Wavelength Observations of CMEs and Associated Phenomena

This chapter reviews how our knowledge of CMEs and CME-associated phenomena has been improved, since the launch of the SOHO mission, thanks to multi-wavelength analysis. The combination of data obtained from space-based experiments and ground based instruments allows us to follow the space-time development of an event from the bottom of the corona to large distances in the interplanetary medium. Since CMEs originate in the low solar corona, understanding the physical processes that generate them is strongly dependant on coordinated multi-wavelength observations. CMEs display a large diversity in morphology and kinematic properties, but there is presently no statistical evidence that those properties may serve to group them into different classes. When a CME takes place, the coronal magnetic field undergoes restructuring. Much of the current research is focused on understanding how the corona sustains the stresses that allow the magnetic energy to build up and how, later on, this magnetic energy is released during eruptive flares and CMEs. Multi-wavelength observations have confirmed that reconnection plays a key role during the development of CMEs. Frequently, CMEs display a rather simple shape, exhibiting a well known three-part structure (bright leading edge, dark cavity and bright knot). These types of events have led to the proposal of the ‘`standard model’' of the development of a CME, a model which predicts the formation of current sheets. A few recent coronal observations provide some evidence for such sheets. Other more complex events correspond to multiple eruptions taking place on a time scale much shorter than the cadence of coronagraph instruments. They are often associated with large-scale dimming and coronal waves. The exact nature of these waves and the physical link between these different manifestations are not yet elucidated. We also discuss what kind of shocks are produced during a flare or a CME. Several questions remain unanswered. What is the nature of the shocks in the corona (blast-wave or piston-driven?) How they are related to Moreton waves seen in Hα? How they are related to interplanetary shocks? The last section discusses the origin of energetic electrons detected in the corona and in the interplanetary medium. “Complex type III-like events,”which are detected at hectometric wavelengths, high in the corona, and are associated with CMEs, appear to originate from electrons that have been accelerated lower in the corona and not at the bow shock of CMEs. Similarly, impulsive energetic electrons observed in the interplanetary medium are not the exclusive result of electron acceleration at the bow shocks of CMEs; rather they have a coronal origin.     

Shock acceleration of energetic particles in wave heated corona

The solar wind wave heating models require substantial amount of wave power in order to efficiently heat and accelerate solar wind. The level of fluctuations is however limited by energetic particle observations. The simplest cyclotron sweep models result in convection-dominated transport, contradicting observations. However, models incorporating wave-wave -interactions, which cause wave energy to cascade in wavenumber, allow more reasonable energetic particle transport in the interplanetary space. The mean free path of the energetic particles remains still relatively short in the corona, providing favorable conditions for coronal mass ejection (CME) related shock acceleration. We study the consequences of this scenario on the energetic particle production related to CMEs. The role of self-generated waves is also discussed.     

New method of enhancement using wavelet transforms applied to SODISM telescope

PICARD is a space-based observatory hosting the Solar Diameter Imager and Surface Mapper (SODISM) telescope, which has continuously observed the Sun from July 2010 and up to March 2014. In order to study the fine structure of the solar surface, it is helpful to apply techniques that enhance the images so as to improve the visibility of solar features such as sunspots or faculae. The objective of this work is to develop an innovative technique to enhance the quality of the SODISM images in the five wavelengths monitored by the telescope at 215.0?nm, 393.37?nm, 535.7?nm, 607.1?nm and 782.2?nm. An enhancement technique using interpolation of the high-frequency sub-bands obtained by Discrete Wavelet Transforms (DWT) and the input image is applied to the SODISM images. The input images are decomposed by the DWT as well as Stationary Wavelet Transform (SWT) into four separate sub-bands in horizontal and vertical directions namely, low-low (LL), low–high (LH), high-low (HL) and high–high (HH) frequencies. The DWT high frequency sub-bands are interpolated by a factor 2. The estimated high frequency sub-bands (edges) are enhanced by introducing an intermediate stage using a Stationary Wavelet Transform (SWT), and then all these sub-bands and input image are combined and interpolated with half of the interpolation factor α/2, used to interpolate the high-frequency sub-bands, in order to reach the required size for IDWT processing. Quantitative and visual results show the superiority of the proposed technique over a bicubic image resolution enhancement technique. In addition, filling factors for sunspots are calculated from SODISM images and results are presented in this work.