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        Ionospheric Multi-Spacecraft Analysis Tools

        Approaches for Deriving Ionospheric Parameters

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        Contributor(s)
        Dunlop, Malcolm Wray (editor)
        Lühr, Hermann (editor)
        Language
        English
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        Abstract
        This open access book provides a comprehensive toolbox of analysis techniques for ionospheric multi-satellite missions. The immediate need for this volume was motivated by the ongoing ESA Swarm satellite mission, but the tools that are described are general and can be used for any future ionospheric multi-satellite mission with comparable instrumentation. In addition to researching the immediate plasma environment and its coupling to other regions, such a mission aims to study the Earth’s main magnetic field and its anomalies caused by core, mantle, or crustal sources. The parameters for carrying out this kind of work are examined in these chapters. Besides currents, electric fields, and plasma convection, these parameters include ionospheric conductance, Joule heating, neutral gas densities, and neutral winds. ;
        URI
        http://library.oapen.org/handle/20.500.12657/23065
        Keywords
        Physics; Space sciences; Atmospheric sciences; Observations, Astronomical; Astronomy—Observations; Planetary science
        DOI
        10.1007/978-3-030-26732-2
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Cham, 2020
        Series
        ISSI Scientific Report Series,
        Classification
        Astronomy, space and time
        Solar system: the Sun and planets
        Earth sciences
        Astronautics
        Pages
        288
        Rights
        https://creativecommons.org/licenses/by/4.0
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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