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  • 1
    Keywords: Image processing. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (430 pages)
    Edition: 1st ed.
    ISBN: 9780323858144
    DDC: 538.766
    Language: English
    Note: Front Cover -- Magnetospheric Imaging -- Magnetospheric Imaging: Understanding the Space Environment through Global Measurements -- Copyright -- Contents -- List of contributors -- Introductory chapter: imaging-a new perspective for magnetospheric research -- Potential of global imaging -- Global context of the chapters -- Optical imaging -- Optical imaging -- ULF wave imaging -- ULF wave imaging -- Plasma sheet imaging from particle precipitation -- Plasma sheet imaging from particle precipitation -- Ultraviolet imaging -- Ultraviolet imaging -- Energetic Neutral Atom (ENA) imaging -- Energetic Neutral Atom (ENA) imaging -- X-ray imaging -- X-ray imaging -- Radio-frequency imaging -- Radio-frequency imaging -- Magnetic field imaging -- Magnetic field imaging -- Future missions -- References -- 1 - Ground-based all-sky imaging techniques for auroral observations and space weather research -- 1. Overview -- 2. Applications of ground-based all-sky imaging technique -- 2.1 Auroras, geomagnetic storms, and substorms -- 2.2 Wave-particle interactions -- 2.3 Space weather and ionospheric scintillation -- 3. Auroral processes -- 4. Auroral imaging of the magnetosphere -- 4.1 THEMIS all-sky imager array -- 5. Multispectral auroral imaging -- 5.1 Potential application in future missions -- 6. JHU/APL GoIono GBO and all-sky imagers -- 6.1 GoIono imaging array in Alaska -- 6.2 Implementation and operations -- 7. Summary -- References -- 2 - Energetic neutral atom imaging of the terrestrial global magnetosphere -- 1. Introduction -- 2. History -- 3. ENA production mechanisms -- 4. Measurement techniques -- 4.1 High-energy ENA cameras -- 4.2 Low-energy cameras -- 5. Ring current and plasma sheet -- 5.1 Storm ring current morphology and evolution -- 5.2 Plasmasheet -- 6. ENA imaging of ionospheric outflow -- 7. Inversion techniques. , 8. Summary and future directions -- References -- 3 - Making the invisible visible: X-ray imaging -- 1. Introduction -- 2. The governing equations and their inputs -- 2.1 The equations -- 2.2 Measured inputs-mostly ς -- 2.3 Model inputs-mostly Q -- 3. Considerations -- 3.1 Field of view -- 3.2 Angular resolution -- 3.3 Bandpass -- 4. Instruments -- 4.1 Optics -- 4.2 Detectors and their consequences -- 4.3 Shades -- 5. Simulations -- 5.1 Emissivity -- 5.2 Instrument -- 5.3 Backgrounds -- 5.4 Putting it all together -- 6. Extracting information -- 6.1 Location in the image -- 6.2 Propagating from image to standoff distance -- 6.3 Further considerations -- 7. Future missions -- 7.1 CuPID -- 7.2 LEXI -- 7.3 SMILE SXI -- 7.4 STORM XRI -- 8. Summary -- References -- 4 - Radio-frequency imaging techniques for ionospheric, magnetospheric, and planetary studies -- 1. Introduction -- 2. Radio remote-sensing techniques -- 2.1 Active techniques -- 2.1.1 Radio sounding with free-space wave modes -- 2.1.1.1 Vertical-incidence ionosondes -- 2.1.1.1 Vertical-incidence ionosondes -- 2.1.1.2 Oblique-incidence and ground scatter ionosondes -- 2.1.1.2 Oblique-incidence and ground scatter ionosondes -- 2.1.1.3 Space-borne sounders -- 2.1.1.3 Space-borne sounders -- 2.1.2 Radio sounding with trapped wave modes (Z and whistler modes) -- 2.1.2.1 Z-mode sounding -- 2.1.2.1 Z-mode sounding -- 2.1.2.1.1 Nonducted earthward propagating Z-Mode echoes -- 2.1.2.1.1 Nonducted earthward propagating Z-Mode echoes -- 2.1.2.1.2 Diagnostic uses of nonducted Z-Mode echoes -- 2.1.2.1.2 Diagnostic uses of nonducted Z-Mode echoes -- 2.1.2.1.3 Ducted and nonducted Z-mode echoes trapped within the Z mode propagation cavity -- 2.1.2.1.3 Ducted and nonducted Z-mode echoes trapped within the Z mode propagation cavity. , 2.1.2.1.4 Remote sensing of plasma composition along the geomagnetic field lines -- 2.1.2.1.4 Remote sensing of plasma composition along the geomagnetic field lines -- 2.1.2.1.5 Scattered or diffuse Z-mode echoes -- 2.1.2.1.5 Scattered or diffuse Z-mode echoes -- 2.1.2.1.6 Diagnostic uses of scattered Z-Mode echoes -- 2.1.2.1.6 Diagnostic uses of scattered Z-Mode echoes -- 2.1.2.2 Whistler-mode sounding -- 2.1.2.2 Whistler-mode sounding -- 2.1.2.2 1Magnetospherically and specularly reflected whistler-mode echoes in a smooth magnetosphere -- 2.1.2.2 1Magnetospherically and specularly reflected whistler-mode echoes in a smooth magnetosphere -- 2.1.2.2.2 WM-echo propagation paths: effects of FAIs on echo propagation -- 2.1.2.2.2 WM-echo propagation paths: effects of FAIs on echo propagation -- 2.1.2.2.3 Examples of whistler mode echoes -- 2.1.2.2.3 Examples of whistler mode echoes -- 2.1.2.2.4 Whistler mode radio sounding of electrons and ions -- 2.1.2.2.4 Whistler mode radio sounding of electrons and ions -- 2.1.2.2.5 Whistler and Z-mode radio sounding of field-aligned electron-density irregularities -- 2.1.2.2.5 Whistler and Z-mode radio sounding of field-aligned electron-density irregularities -- 2.1.3 Bistatic sensing of plasma using traversing signals -- 2.1.3.1 Total electron content -- 2.1.3.1 Total electron content -- 2.1.3.2 Slant and vertical TEC -- 2.1.3.2 Slant and vertical TEC -- 2.1.3.3 Radio tomography using STEC -- 2.1.3.3 Radio tomography using STEC -- 2.1.3.4 Radio tomographic technique using Faraday rotation -- 2.1.3.4 Radio tomographic technique using Faraday rotation -- 2.1.3.5 Spacecraft-to-spacecraft tomography with radio occultation -- 2.1.3.5 Spacecraft-to-spacecraft tomography with radio occultation -- 2.1.4 Radio sounding via signal scatter -- 2.1.4.1 Incoherent scatter radar -- 2.1.4.1 Incoherent scatter radar. , 2.1.4.2 Coherent scatter radar -- 2.1.4.2 Coherent scatter radar -- 2.1.5 Surface-penetrating radar -- 2.2 Passive wave map technique -- 2.2.1 Wave map -- 2.2.2 Imaging with narrow-beam riometers -- 3. Applications of radio techniques to imaging -- 3.1 Radio Imaging of plasmas by means of sensor data fusion -- 3.2 Ionospheric imaging applications -- 3.2.1 Two-dimensional mapping of VTEC -- 3.2.2 Tomography application based on STEC -- 3.2.2.1 Spacecraft-to-ground 3D tomography -- 3.2.2.1 Spacecraft-to-ground 3D tomography -- 3.2.2.2 Spacecraft-to-spacecraft tomography with radio occultation -- 3.2.2.2 Spacecraft-to-spacecraft tomography with radio occultation -- 3.2.2.3 Spacecraft-to-spacecraft tomography with Faraday rotation -- 3.2.2.3 Spacecraft-to-spacecraft tomography with Faraday rotation -- 3.2.3 Ionosonde networks -- 3.2.3.1 Imaging by averaging with interpolation -- 3.2.3.1 Imaging by averaging with interpolation -- 3.2.3.2 Ionosonde networks for real-time ionospheric imaging -- 3.2.3.2 Ionosonde networks for real-time ionospheric imaging -- 3.2.3.3 HF radio skymap and ionospheric disturbances -- 3.2.3.3 HF radio skymap and ionospheric disturbances -- 3.2.3.4 Frequency-angular sounding -- 3.2.3.4 Frequency-angular sounding -- 3.2.4 SuperDARN -- 3.3 Magnetospheric imaging -- 3.3.1 Active Radio Imaging -- 3.3.1.1 Imaging the plasmasphere -- 3.3.1.1 Imaging the plasmasphere -- 3.3.1.2 Imaging the high-latitude dayside magnetosphere -- 3.3.1.2 Imaging the high-latitude dayside magnetosphere -- 3.3.1.3 Z mode radio imaging of the magnetospheric electron density -- 3.3.1.3 Z mode radio imaging of the magnetospheric electron density -- 3.3.1.4 Whistler-mode radio imaging of magnetospheric electron and ion densities -- 3.3.1.4 Whistler-mode radio imaging of magnetospheric electron and ion densities -- 3.3.2 Passive radio imaging. , 3.3.2.1 Imaging of trapped nonthermal continuum radiation -- 3.3.2.1 Imaging of trapped nonthermal continuum radiation -- 3.4 Imaging planetary environments -- 4. Future capabilities -- 4.1 New technologies -- 4.2 Future ionospheric radars -- 4.3 Application of tomographic techniques (satellite-to-satellite) -- 4.4 Applications of surface-penetrating radar -- 5. Conclusions -- References -- Further reading -- 5 - Magnetospheric imaging via ground-based optical instruments -- 1. Introduction -- 2. Instrumentation -- 3. Technique -- 3.1 Application: December 18, 2017 -- 4. Conclusion -- References -- 6 - The future of plasmaspheric extreme ultraviolet (EUV) imaging -- 1. Introduction -- 1.1 Space plasma imaging -- 1.2 Wide-field extreme ultraviolet imaging 30.4 nm (EUV) imaging at Earth -- 1.2.1 Concept and impact of plasmaspheric 30.4nm imaging -- 1.2.2 The IMAGE EUV optical design -- 1.2.3 Example of IMAGE EUV science images -- 1.2.4 What is the future of plasmaspheric EUV imaging? -- 2. Imaging of terrestrial He+ (30.4 nm) -- 2.1 The D13 EUV imager -- 2.1.1 D13 filter transmission -- 2.1.2 D13 mirror reflectivity -- 2.1.3 Wider field of view -- 2.2 High resolution plasmasphere observatory -- 2.2.1 Global observation of plasmaspheric fine-scale structure -- 2.2.2 HRPO optical design -- 2.2.3 HRPO angular resolution -- 2.2.4 HRPO sensitivity and effective area -- 2.2.5 Simulated HRPO images -- 2.3 Continuous stereo imaging of refilling and erosion -- 2.3.1 System-level refilling -- 2.3.2 System-level convection -- 2.3.3 Interchange instability -- 2.4 Side-view imaging -- 2.4.1 Geosynchronous EUV -- 2.4.2 EUV imaging from the Moon -- 3. Imaging of terrestrial O+ and O++ (83.4 nm) -- 3.1 The dense oxygen torus -- 3.2 EUV imaging of the dense torus -- 3.3 Simulated oxygen torus images -- 3.3.1 Torus formation -- 3.3.2 Torus distribution. , 3.4 The promise of dense oxygen torus imaging.
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  • 2
    Electronic Resource
    Electronic Resource
    [s.l.] : Macmillan Magazines Ltd.
    Nature 393 (1998), S. 342-344 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The oldest documented, relationship between the number of sunspots (the solar cycle) and terrestrial effects is the increased frequency of aurorae in the period immediately after the solar maximum (the peak of the number of sunspots). This correlation is, however, based only on observations of ...
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2023-09-06
    Description: Learning from successful applications of methods originating in statistical mechanics, com- plex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between nor- mal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards. This review provides a systematic overview on existing nonlinear dynamical systems- based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems ap- proaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlin- ear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales.
    Description: Published
    Description: 38
    Description: 1A. Geomagnetismo e Paleomagnetismo
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 4
    Publication Date: 2024-04-30
    Description: In the domain of space science, numerous ground-based and space-borne data of various phenomena have been accumulating rapidly, making analysis and scientific interpretation challenging. However, recent trends in the application of artificial intelligence (AI) have been shown to be promising in the extraction of information or knowledge discovery from these extensive data sets. Coincidentally, preparing these data for use as inputs to the AI algorithms, referred to as AI-readiness, is one of the outstanding challenges in leveraging AI in space science. Preparation of AI-ready data includes, among other aspects: 1) collection (accessing and downloading) of appropriate data representing the various physical parameters associated with the phenomena under study from different repositories; 2) addressing data formats such as conversion from one format to another, data gaps, quality flags and labeling; 3) standardizing metadata and keywords in accordance with NASA archive requirements or other defined standards; 4) processing of raw data such as data normalization, detrending, and data modeling; and 5) documentation of technical aspects such as processing steps, operational assumptions, uncertainties, and instrument profiles. Making all existing data AI-ready within a decade is impractical and data from future missions and investigations exacerbates this. This reveals the urgency to set the standards and start implementing them now. This article presents our perspective on the AI-readiness of space science data and mitigation strategies including definition of AI-readiness for AI applications; prioritization of data sets, storage, and accessibility; and identifying the responsible entity (agencies, private sector, or funded individuals) to undertake the task.
    Description: Published
    Description: 1203598
    Description: OSA3: Climatologia e meteorologia spaziale
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 5
    Publication Date: 2013-02-01
    Description: Nature Geoscience 6, 125 (2013). doi:10.1038/ngeo1679 Authors: Clint Scott, Noah J. Planavsky, Chris L. Dupont, Brian Kendall, Benjamin C. Gill, Leslie J. Robbins, Kathryn F. Husband, Gail L. Arnold, Boswell A. Wing, Simon W. Poulton, Andrey Bekker, Ariel D. Anbar, Kurt O. Konhauser & Timothy W. Lyons The redox state of the oceans strongly influences the concentration of dissolved trace metals in sea water. Changes in the redox state of the oceans are thought to have limited the availability of some trace metals in the past, particularly during the Proterozoic eon, 2,500 to 542 million years ago. Of these trace metals, zinc (Zn) is of particular importance to eukaryotic organisms, because it is essential for a wide range of basic cellular functions. It has been suggested that during the Proterozoic, marine environments were broadly euxinic—that is, anoxic and sulphidic—which would have resulted in low Zn availability. Low Zn bioavailability could therefore be responsible for an observed delay in eukaryote diversification. Here we present a compilation of Zn abundance data from black shales deposited under euxinic conditions from the Precambrian time to the present. We show that these values track first-order trends in seawater Zn availability. Contrary to previous estimates, we find that Zn concentrations during the Proterozoic were similar to modern concentrations, supporting recent studies that call for limited euxinia at this time. Instead, we propose that predominantly anoxic and iron-rich deep oceans, combined with large hydrothermal fluxes of Zn, maintained high levels of dissolved Zn throughout the oceans. We thus suggest that the protracted diversification of eukaryotic Zn-binding proteins was not a result of Znbiolimitation.
    Print ISSN: 1752-0894
    Electronic ISSN: 1752-0908
    Topics: Geosciences
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