Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book is a unique and important resource for space physicists, space weather professionals and computer scientists in related fields. - Collects many representative non-traditional approaches to space weather into a single volume - Covers, in an accessible way, the mathematical background that is not often explained in detail for space scientists - Includes free software in the form of simple MATLAB® scripts that allow for replication of results in the book, also familiarizing readers with algorithms

This book describes the basic concepts of spacecraft operations for both manned and unmanned missions. The first part of the book provides a brief overview of the space segment. The next four parts deal with the classic areas of space flight operations: mission operations, communications and infrastructure, the flight dynamics system, and the mission planning system. This is followed by a part describing the operational tasks of the various subsystems of a classical satellite in Earth orbit. The last part describes the special requirements of other mission types due to the presence of astronauts, the approach of a satellite to another target satellite, or leaving Earth orbit in interplanetary missions and landing on other planets and moons. The 2nd edition is published seven years after the first edition. It contains four new chapters on flight procedures, the human factors, ground station operation, and software and systems. In addition, several chapters have been extensively expanded. The entire book has been brought up to date and the language has been revised. This book is based on the “Spacecraft Operations Course” held at the German Space Operations Center. However, the target audience of this book is not only the participants of the course, but also students of technical and scientific courses, as well as technically interested people who want to gain a deeper understanding of spacecraft operations.

Examines how solar and terrestrial space phenomena affect sophisticated technological systems Contemporary society relies on sophisticated technologies to manage electricity distribution, communication networks, transportation safety, and myriad other systems. The successful design and operation of both ground-based and space-based systems must consider solar and terrestrial space phenomena and processes. Space Weather Effects and Applications describes the effects of space weather on various present-day technologies and explores how improved instrumentation to measure Earth's space environment can be used to more accurately forecast changes and disruptions. Volume highlights include: Damage and disruption to orbiting satellite equipment by solar particles and cosmic rays Effects of space radiation on aircraft at high altitudes and latitudes Response of radio and radar-based systems to solar bursts Disturbances to the propagation of radio waves caused by space weather How geomagnetic field changes impact ground-based systems such as pipelines Impacts of human exposure to the space radiation environment The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more about the Space Physics and Aeronomy collection in this Q&A with the Editors in Chief

Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. - Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials - Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets - Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems - Utilizes case studies to illustrate how machine learning methods can be employed in practice

This volume is dedicated to the Solar Dynamics Observatory (SDO), which was launched 11 February 2010. The articles focus on the spacecraft and its instruments: the Atmospheric Imaging Assembly (AIA), the Extreme Ultraviolet Variability Experiment (EVE), and the Helioseismic and Magnetic Imager (HMI). Articles within also describe calibration results and data processing pipelines that are critical to understanding the data and products, concluding with a description of the successful Education and Public Outreach activities. This book is geared towards anyone interested in using the unprecedented data from SDO, whether for fundamental heliophysics research, space weather modeling and forecasting, or educational purposes. Previously published in Solar Physics journal, Vol. 275/1-2, 2012. Selected articles in this book are published open access under a CC BY-NC 2.5 license at link.springer.com. For further details, please see the license information in the chapters.

The book covers intimately all the topics necessary for the development of a robust magnetohydrodynamic (MHD) code within the framework of the cell-centered finite volume method (FVM) and its applications in space weather study. First, it presents a brief review of existing MHD models in studying solar corona and the heliosphere. Then it introduces the cell-centered FVM in three-dimensional computational domain. Finally, the book presents some applications of FVM to the MHD codes on spherical coordinates in various research fields of space weather, focusing on the development of the 3D Solar-InterPlanetary space-time Conservation Element and Solution Element (SIP-CESE) MHD model and its applications to space weather studies in various aspects. The book is written for senior undergraduates, graduate students, lecturers, engineers and researchers in solar-terrestrial physics, space weather theory, modeling, and prediction, computational fluid dynamics, and MHD simulations. It helps readers to fully understand and implement a robust and versatile MHD code based on the cell-centered FVM.