How Researchers Simulate Io’s Volcanic and Atmospheric Conditions

Table of Links Abstract Introduction 1.1. Io as the main source of mass for the magnetosphere 1.2. Stability and variability of the Io torus system 1.3. Hypothesized volcanic mass supply events 1.4. Objective of this review Review of the relevant components of the Io-Jupiter system 2.1. Volcanic activity: hot spots and plumes 2.2 Io’s bound atmosphere 2.3 Exosphere and atmospheric escape 2.4 Electrodynamic interaction, plasma-neutral collisions, and the related atmospheric loss processes 2.5. Neutrals from Io in Jupiter’s magnetosphere 2.6. Plasma torus and sheet, energetic particles 2.7 Jupiter’s aurora and connections to the Io torus 2.8 Dust from Io Summary: What we know and what we do not know and 3.1 Current understanding for normal (stable) conditions 3.2 Canonical number for mass supply 3.3 Transient events in the plasma torus, neutral clouds and nebula, and aurora 3.4 Gaps in understanding, contradictions, and inconsistencies Future observations and methods and 4.1 Spacecraft measurements 4.2 Remote Earth-based observations 4.3 Modeling efforts Appendix, Acknowledgements, and References 4.3 Modeling efforts Successful modeling, whether numerical or analytical, depends on the applicability and correct implementation of the relevant included physics and choices about boundary and initial conditions. Regarding the torus and transient events, atmospheric escape is critical as it is the precursor of the plasma supply to the torus and then to the whole magnetosphere. But regarding the atmosphere structure and dynamics, Io escape is in a sense a secondary physical process; it is not the major contributor to mass, momentum or energy input to/from the plumes or atmosphere and thus does not play a major role in the modeling of the atmosphere. 4.3.1 Spatial scales, time scales and undetermined feedbacks The mass-loading of the Jovian magnetosphere presumably results from a long chain of processes where the timescales and length-scales of the physical processes at play vary considerably, starting from (i) the volcanic plumes and sublimation atmosphere (10-400 km) to the formation of the bound atmosphere and exosphere (several RIo), (ii) the supply to the neutral clouds by plasma-atmosphere interaction and (iii) the formation of Io’s plasma torus (~2 RJ), and finally (iv) the radial plasma transport from the Io plasma torus through the whole Jovian magnetosphere (several 10s RJ). These physical processes are linked probably in non-linear ways (via feedback mechanisms) and some relevant processes may not yet be recognized. Clearly, these processes cannot all be accommodated in a single model or simulation. A number of the low-hanging models (called hereafter sub-models) have already been harvested; the easiest next step is to iterate between and/or patch together multiple sub-models. 4.3.2 Current sub-models and their limitations Currently, separate sub-models focus on describing a few selected aspects of this long chain of processes and parameterize (assume constant) the features not addressed in each specific model. The parameterization is then constrained by observations. Below are examples of such sub-models, their outputs and the parameterizations of processes that cannot be described physically in the sub-models themselves but could potentially be addressed in other sub-models. Atmosphere and plume models. Sophisticated atmospheric models have been developed, which include the contribution of major plumes and sublimation of the SO2 surface frost. Various escape processes should be considered for a combined sublimation and plume atmosphere. DSMC atmospheric models have used imposed streams of incoming plasma and static E/B fields (e.g., Moore et al., 2012), which themselves should depend non-linearly on the atmospheric distribution and density and can be addressed in other sub-models described below. Global-scale winds driven by sublimation/condensation, plumes and plasma impact may provide an additional velocity at the top of the atmosphere which, combined with thermal processes, could yield significant escape. Simple thermal escape rates are exponentially sensitive to the exobase temperature so it may be reasonable to expect possibly locally enhanced escape due to winds or plumes, chemical recombination or plasma interactions boosting LTE escape. Models of planetary escape which establish whether two or more driving processes contribute to high-speed winds and thereby enhanced thermal escape remain to be developed. Plasma-interaction models. Models of the plasma-atmosphere interaction (fluid or kinetic modelling) focus on the electromagnetic interaction and properties of the plasma. They include some physical chemistry (e.g., ionization, charge exchange, collisions) but the simulations to date generally rely on a prescribed static atmospheric distribution and composition. Some models also prescribe a static description of plumes (Blöcker et al., 2018). The comparison of the model results with the plasma properties and fields observed along a probe trajectory or the remotely observed auroral emissions constrain this static atmospheric distribution and composition and overall electromagnetic interaction model. But such models do not include the atmospheric response to the plasma bombardment. Neutral cloud models. Neutral Cloud Models (NCM) simulate the distribution of neutrals (e.g., Na, O, S, SO2) along the orbit of Io under the gravitational fields of Jupiter and Io. These models include some physical chemistry (ionization, charge exchange, etc.) that shape the neutral clouds. These loss processes have been calculated with a prescribed static plasma torus density, composition, and temperatures. More importantly, in such models, the source of these neutral clouds is based on a very simplified description of the neutral fluxes from Io’s exobase. These models prescribe a velocity distribution for the escaping neutrals that is typical of atmospheric sputtering and prescribe the Io-graphic distribution of these neutral fluxes assuming a purely radial ejection velocity. Comparison of the simulated neutral cloud with the observations of neutrals along Io’s orbit constrains the velocities, Io-graphic location and composition of the neutral ejection from Io’s exobase. But sub-models (earlier in the modeling chain) that simulate the plasma-atmosphere interaction conclude that the neutral loss comes from not only sputtering but also from other processes (e.g., charge exchange, molecular dissociation, and photo-processes), which provide neutrals with velocities sometimes much larger than a sputtering velocity distribution and ejection directions that are not radial. Moreover, the sub/anti-Jovian asymmetries might be a consequence of the Hall-effect on the electromagnetic interaction which deflects ions into the anti-Jovian hemisphere and the electrons into the sub-Jovian hemisphere (Saur et al., 1999). This yields a radially outward current through the ionosphere connecting flux tube current from Jupiter inside Io's orbit with return current towards Jupiter along flux tubes outside Io's orbit. Plasma torus models. Models of the plasma torus include a detailed description of the physical chemistry that calculates the ion composition and energy to simulate the time-averaged plasma properties of the torus. The simplifications involved in this modeling include the parameterization of the neutral supply rate, of the neutral S/O ratio and of the radial plasma transport. Comparison of the simulated plasma properties with in situ measurements constrains the neutral supply rate, the O/S ratio and the transport rate. All of the parameters are generally assumed constant with time for each model. 4.3.3. Future progress in modeling Considering the open questions and not yet understood aspects (Section 3.4.4) it is clear that we have not yet identified some dominant processes or quantitatively estimated some significant feedback mechanisms. Future modeling might include interactions between two or more physically distinct sub-models or sub-domains of the overall Io environment. A first simple approach is to proceed to multiple iterations between two sub-models. Such iterations are already in progress (atmosphere/torus or atmosphere/neutral cloud) and will help determine the nature, and the quantitative significance of the feedback between two joined sub-models. A more complex approach is to physically couple two subsequent sub-models in a single simulation. DSMC simulations are already moving in this direction and substantial progress is in sight (Klaiber 2024) but require large computing resources. With current computing power it should be possible to simulate a full 3D coupled model of Io’s torus, plumes and atmosphere with radiative transport and solid body heat transfer through an entire Io orbit, including eclipse. On ~104 processors it would only take a few days. The resulting highly resolved global circulation model could serve as a community baseline dataset upon which to examine different escape mechanisms. But the parameter space to be explored (e.g., plume, torus, and local interaction variations) is still extremely large. Both PDE solvers and stochastic solvers have their place: Navier-Stokes/DSMC, DSMC/PIC or PIC/MHD hybrid methods applied in the appropriate physical regime, could help reduce the simulation computing time and allow a more efficient exploration of the large parameter space. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) L. Roth, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and a Corresponding author; (2) A. Blöcker, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and Department of Earth and Environmental Sciences, Ludwig Maximilian University of Munich, Munich, Germany; (3) K. de Kleer, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (4) D. Goldstein, Dept. Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX USA; (5) E. Lellouch, Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), Observatoire de Paris, Meudon, France; (6) J. Saur, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (7) C. Schmidt, Center for Space Physics, Boston University, Boston, MA, USA; (8) D.F. Strobel, Departments of Earth & Planetary Science and Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA; (9) C. Tao, National Institute of Information and Communications Technology, Koganei, Japan; (10) F. Tsuchiya, Graduate School of Science, Tohoku University, Sendai, Japan; (11) V. Dols, Institute for Space Astrophysics and Planetology, National Institute for Astrophysics, Italy; (12) H. Huybrighs, School of Cosmic Physics, DIAS Dunsink Observatory, Dublin Institute for Advanced Studies, Dublin 15, Ireland, Space and Planetary Science Center, Khalifa University, Abu Dhabi, UAE and Department of Mathematics, Khalifa University, Abu Dhabi, UAE; (13) A. Mura, XX; (14) J. R. Szalay, Department of Astrophysical Sciences, Princeton University, Princeton, NJ, USA; (15) S. V. Badman, Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK; (16) I. de Pater, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (17) A.-C. Dott, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (18) M. Kagitani, Graduate School of Science, Tohoku University, Sendai, Japan; (19) L. Klaiber, Physics Institute, University of Bern, 3012 Bern, Switzerland; (20) R. Koga, Department of Earth and Planetary Sciences, Nagoya University, Nagoya, Aichi 464-8601, Japan; (21) A. McEwen, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (22) Z. Milby, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (23) K.D. Retherford, Southwest Research Institute, San Antonio, TX, USA and University of Texas at San Antonio, San Antonio, Texas, USA; (24) S. Schlegel, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (25) N. Thomas, Physics Institute, University of Bern, 3012 Bern, Switzerland; (26) W.L. Tseng, Department of Earth Sciences, National Taiwan Normal University, Taiwan; (27) A. Vorburger, Physics Institute, University of Bern, 3012 Bern, Switzerland. Table of Links Abstract Abstract Introduction 1.1. Io as the main source of mass for the magnetosphere 1.2. Stability and variability of the Io torus system 1.3. Hypothesized volcanic mass supply events 1.4. Objective of this review Review of the relevant components of the Io-Jupiter system 2.1. Volcanic activity: hot spots and plumes 2.2 Io’s bound atmosphere 2.3 Exosphere and atmospheric escape 2.4 Electrodynamic interaction, plasma-neutral collisions, and the related atmospheric loss processes 2.5. Neutrals from Io in Jupiter’s magnetosphere 2.6. Plasma torus and sheet, energetic particles 2.7 Jupiter’s aurora and connections to the Io torus 2.8 Dust from Io Summary: What we know and what we do not know and 3.1 Current understanding for normal (stable) conditions 3.2 Canonical number for mass supply 3.3 Transient events in the plasma torus, neutral clouds and nebula, and aurora 3.4 Gaps in understanding, contradictions, and inconsistencies Future observations and methods and 4.1 Spacecraft measurements 4.2 Remote Earth-based observations 4.3 Modeling efforts Introduction 1.1. Io as the main source of mass for the magnetosphere 1.2. Stability and variability of the Io torus system 1.3. Hypothesized volcanic mass supply events 1.4. Objective of this review Introduction 1.1. Io as the main source of mass for the magnetosphere 1.1. Io as the main source of mass for the magnetosphere 1.2. Stability and variability of the Io torus system 1.2. Stability and variability of the Io torus system 1.3. Hypothesized volcanic mass supply events 1.3. Hypothesized volcanic mass supply events 1.4. Objective of this review 1.4. Objective of this review Review of the relevant components of the Io-Jupiter system 2.1. Volcanic activity: hot spots and plumes 2.2 Io’s bound atmosphere 2.3 Exosphere and atmospheric escape 2.4 Electrodynamic interaction, plasma-neutral collisions, and the related atmospheric loss processes 2.5. Neutrals from Io in Jupiter’s magnetosphere 2.6. Plasma torus and sheet, energetic particles 2.7 Jupiter’s aurora and connections to the Io torus 2.8 Dust from Io Review of the relevant components of the Io-Jupiter system 2.1. Volcanic activity: hot spots and plumes 2.1. Volcanic activity: hot spots and plumes 2.2 Io’s bound atmosphere 2.2 Io’s bound atmosphere 2.3 Exosphere and atmospheric escape 2.3 Exosphere and atmospheric escape 2.4 Electrodynamic interaction, plasma-neutral collisions, and the related atmospheric loss processes 2.4 Electrodynamic interaction, plasma-neutral collisions, and the related atmospheric loss processes 2.5. Neutrals from Io in Jupiter’s magnetosphere 2.5. Neutrals from Io in Jupiter’s magnetosphere 2.6. Plasma torus and sheet, energetic particles 2.6. Plasma torus and sheet, energetic particles 2.7 Jupiter’s aurora and connections to the Io torus 2.7 Jupiter’s aurora and connections to the Io torus 2.8 Dust from Io 2.8 Dust from Io Summary: What we know and what we do not know and 3.1 Current understanding for normal (stable) conditions 3.2 Canonical number for mass supply 3.3 Transient events in the plasma torus, neutral clouds and nebula, and aurora 3.4 Gaps in understanding, contradictions, and inconsistencies Summary: What we know and what we do not know and 3.1 Current understanding for normal (stable) conditions Summary: What we know and what we do not know and 3.1 Current understanding for normal (stable) conditions 3.2 Canonical number for mass supply 3.2 Canonical number for mass supply 3.3 Transient events in the plasma torus, neutral clouds and nebula, and aurora 3.3 Transient events in the plasma torus, neutral clouds and nebula, and aurora 3.4 Gaps in understanding, contradictions, and inconsistencies 3.4 Gaps in understanding, contradictions, and inconsistencies Future observations and methods and 4.1 Spacecraft measurements 4.2 Remote Earth-based observations 4.3 Modeling efforts Future observations and methods and 4.1 Spacecraft measurements Future observations and methods and 4.1 Spacecraft measurements 4.2 Remote Earth-based observations 4.2 Remote Earth-based observations 4.3 Modeling efforts 4.3 Modeling efforts Appendix, Acknowledgements, and References Appendix, Acknowledgements, and References 4.3 Modeling efforts Successful modeling, whether numerical or analytical, depends on the applicability and correct implementation of the relevant included physics and choices about boundary and initial conditions. Regarding the torus and transient events, atmospheric escape is critical as it is the precursor of the plasma supply to the torus and then to the whole magnetosphere. But regarding the atmosphere structure and dynamics, Io escape is in a sense a secondary physical process; it is not the major contributor to mass, momentum or energy input to/from the plumes or atmosphere and thus does not play a major role in the modeling of the atmosphere. 4.3.1 Spatial scales, time scales and undetermined feedbacks The mass-loading of the Jovian magnetosphere presumably results from a long chain of processes where the timescales and length-scales of the physical processes at play vary considerably, starting from (i) the volcanic plumes and sublimation atmosphere (10-400 km) to the formation of the bound atmosphere and exosphere (several RIo), (ii) the supply to the neutral clouds by plasma-atmosphere interaction and (iii) the formation of Io’s plasma torus (~2 RJ), and finally (iv) the radial plasma transport from the Io plasma torus through the whole Jovian magnetosphere (several 10s RJ). These physical processes are linked probably in non-linear ways (via feedback mechanisms) and some relevant processes may not yet be recognized. Clearly, these processes cannot all be accommodated in a single model or simulation. A number of the low-hanging models (called hereafter sub-models) have already been harvested; the easiest next step is to iterate between and/or patch together multiple sub-models. 4.3.2 Current sub-models and their limitations Currently, separate sub-models focus on describing a few selected aspects of this long chain of processes and parameterize (assume constant) the features not addressed in each specific model. The parameterization is then constrained by observations. Below are examples of such sub-models, their outputs and the parameterizations of processes that cannot be described physically in the sub-models themselves but could potentially be addressed in other sub-models. Atmosphere and plume models. Sophisticated atmospheric models have been developed, which include the contribution of major plumes and sublimation of the SO2 surface frost. Various escape processes should be considered for a combined sublimation and plume atmosphere. DSMC atmospheric models have used imposed streams of incoming plasma and static E/B fields (e.g., Moore et al., 2012), which themselves should depend non-linearly on the atmospheric distribution and density and can be addressed in other sub-models described below. Global-scale winds driven by sublimation/condensation, plumes and plasma impact may provide an additional velocity at the top of the atmosphere which, combined with thermal processes, could yield significant escape. Simple thermal escape rates are exponentially sensitive to the exobase temperature so it may be reasonable to expect possibly locally enhanced escape due to winds or plumes, chemical recombination or plasma interactions boosting LTE escape. Models of planetary escape which establish whether two or more driving processes contribute to high-speed winds and thereby enhanced thermal escape remain to be developed. Atmosphere and plume models. Atmosphere and plume models. Plasma-interaction models. Models of the plasma-atmosphere interaction (fluid or kinetic modelling) focus on the electromagnetic interaction and properties of the plasma. They include some physical chemistry (e.g., ionization, charge exchange, collisions) but the simulations to date generally rely on a prescribed static atmospheric distribution and composition. Some models also prescribe a static description of plumes (Blöcker et al., 2018). The comparison of the model results with the plasma properties and fields observed along a probe trajectory or the remotely observed auroral emissions constrain this static atmospheric distribution and composition and overall electromagnetic interaction model. But such models do not include the atmospheric response to the plasma bombardment. Plasma-interaction models. Plasma-interaction models. Neutral cloud models. Neutral Cloud Models (NCM) simulate the distribution of neutrals (e.g., Na, O, S, SO2) along the orbit of Io under the gravitational fields of Jupiter and Io. These models include some physical chemistry (ionization, charge exchange, etc.) that shape the neutral clouds. These loss processes have been calculated with a prescribed static plasma torus density, composition, and temperatures. More importantly, in such models, the source of these neutral clouds is based on a very simplified description of the neutral fluxes from Io’s exobase. These models prescribe a velocity distribution for the escaping neutrals that is typical of atmospheric sputtering and prescribe the Io-graphic distribution of these neutral fluxes assuming a purely radial ejection velocity. Comparison of the simulated neutral cloud with the observations of neutrals along Io’s orbit constrains the velocities, Io-graphic location and composition of the neutral ejection from Io’s exobase. But sub-models (earlier in the modeling chain) that simulate the plasma-atmosphere interaction conclude that the neutral loss comes from not only sputtering but also from other processes (e.g., charge exchange, molecular dissociation, and photo-processes), which provide neutrals with velocities sometimes much larger than a sputtering velocity distribution and ejection directions that are not radial. Moreover, the sub/anti-Jovian asymmetries might be a consequence of the Hall-effect on the electromagnetic interaction which deflects ions into the anti-Jovian hemisphere and the electrons into the sub-Jovian hemisphere (Saur et al., 1999). This yields a radially outward current through the ionosphere connecting flux tube current from Jupiter inside Io's orbit with return current towards Jupiter along flux tubes outside Io's orbit. Neutral cloud models. Neutral cloud models. Plasma torus models. Models of the plasma torus include a detailed description of the physical chemistry that calculates the ion composition and energy to simulate the time-averaged plasma properties of the torus. The simplifications involved in this modeling include the parameterization of the neutral supply rate, of the neutral S/O ratio and of the radial plasma transport. Comparison of the simulated plasma properties with in situ measurements constrains the neutral supply rate, the O/S ratio and the transport rate. All of the parameters are generally assumed constant with time for each model. Plasma torus models. Plasma torus models. 4.3.3. Future progress in modeling Considering the open questions and not yet understood aspects (Section 3.4.4) it is clear that we have not yet identified some dominant processes or quantitatively estimated some significant feedback mechanisms. Future modeling might include interactions between two or more physically distinct sub-models or sub-domains of the overall Io environment. A first simple approach is to proceed to multiple iterations between two sub-models. Such iterations are already in progress (atmosphere/torus or atmosphere/neutral cloud) and will help determine the nature, and the quantitative significance of the feedback between two joined sub-models. A more complex approach is to physically couple two subsequent sub-models in a single simulation. DSMC simulations are already moving in this direction and substantial progress is in sight (Klaiber 2024) but require large computing resources. With current computing power it should be possible to simulate a full 3D coupled model of Io’s torus, plumes and atmosphere with radiative transport and solid body heat transfer through an entire Io orbit, including eclipse. On ~104 processors it would only take a few days. The resulting highly resolved global circulation model could serve as a community baseline dataset upon which to examine different escape mechanisms. But the parameter space to be explored (e.g., plume, torus, and local interaction variations) is still extremely large. Both PDE solvers and stochastic solvers have their place: Navier-Stokes/DSMC, DSMC/PIC or PIC/MHD hybrid methods applied in the appropriate physical regime, could help reduce the simulation computing time and allow a more efficient exploration of the large parameter space. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv Authors: (1) L. Roth, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and a Corresponding author; (2) A. Blöcker, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and Department of Earth and Environmental Sciences, Ludwig Maximilian University of Munich, Munich, Germany; (3) K. de Kleer, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (4) D. Goldstein, Dept. Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX USA; (5) E. Lellouch, Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), Observatoire de Paris, Meudon, France; (6) J. Saur, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (7) C. Schmidt, Center for Space Physics, Boston University, Boston, MA, USA; (8) D.F. Strobel, Departments of Earth & Planetary Science and Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA; (9) C. Tao, National Institute of Information and Communications Technology, Koganei, Japan; (10) F. Tsuchiya, Graduate School of Science, Tohoku University, Sendai, Japan; (11) V. Dols, Institute for Space Astrophysics and Planetology, National Institute for Astrophysics, Italy; (12) H. Huybrighs, School of Cosmic Physics, DIAS Dunsink Observatory, Dublin Institute for Advanced Studies, Dublin 15, Ireland, Space and Planetary Science Center, Khalifa University, Abu Dhabi, UAE and Department of Mathematics, Khalifa University, Abu Dhabi, UAE; (13) A. Mura, XX; (14) J. R. Szalay, Department of Astrophysical Sciences, Princeton University, Princeton, NJ, USA; (15) S. V. Badman, Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK; (16) I. de Pater, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (17) A.-C. Dott, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (18) M. Kagitani, Graduate School of Science, Tohoku University, Sendai, Japan; (19) L. Klaiber, Physics Institute, University of Bern, 3012 Bern, Switzerland; (20) R. Koga, Department of Earth and Planetary Sciences, Nagoya University, Nagoya, Aichi 464-8601, Japan; (21) A. McEwen, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (22) Z. Milby, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (23) K.D. Retherford, Southwest Research Institute, San Antonio, TX, USA and University of Texas at San Antonio, San Antonio, Texas, USA; (24) S. Schlegel, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (25) N. Thomas, Physics Institute, University of Bern, 3012 Bern, Switzerland; (26) W.L. Tseng, Department of Earth Sciences, National Taiwan Normal University, Taiwan; (27) A. Vorburger, Physics Institute, University of Bern, 3012 Bern, Switzerland. Authors: Authors: (1) L. Roth, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and a Corresponding author; (2) A. Blöcker, KTH Royal Institute of Technology, Space and Plasma Physics, Stockholm, Sweden and Department of Earth and Environmental Sciences, Ludwig Maximilian University of Munich, Munich, Germany; (3) K. de Kleer, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (4) D. Goldstein, Dept. Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX USA; (5) E. Lellouch, Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), Observatoire de Paris, Meudon, France; (6) J. Saur, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (7) C. Schmidt, Center for Space Physics, Boston University, Boston, MA, USA; (8) D.F. Strobel, Departments of Earth & Planetary Science and Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA; (9) C. Tao, National Institute of Information and Communications Technology, Koganei, Japan; (10) F. Tsuchiya, Graduate School of Science, Tohoku University, Sendai, Japan; (11) V. Dols, Institute for Space Astrophysics and Planetology, National Institute for Astrophysics, Italy; (12) H. Huybrighs, School of Cosmic Physics, DIAS Dunsink Observatory, Dublin Institute for Advanced Studies, Dublin 15, Ireland, Space and Planetary Science Center, Khalifa University, Abu Dhabi, UAE and Department of Mathematics, Khalifa University, Abu Dhabi, UAE; (13) A. Mura, XX; (14) J. R. Szalay, Department of Astrophysical Sciences, Princeton University, Princeton, NJ, USA; (15) S. V. Badman, Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK; (16) I. de Pater, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (17) A.-C. Dott, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (18) M. Kagitani, Graduate School of Science, Tohoku University, Sendai, Japan; (19) L. Klaiber, Physics Institute, University of Bern, 3012 Bern, Switzerland; (20) R. Koga, Department of Earth and Planetary Sciences, Nagoya University, Nagoya, Aichi 464-8601, Japan; (21) A. McEwen, Department of Astronomy and Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; (22) Z. Milby, Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA; (23) K.D. Retherford, Southwest Research Institute, San Antonio, TX, USA and University of Texas at San Antonio, San Antonio, Texas, USA; (24) S. Schlegel, Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany; (25) N. Thomas, Physics Institute, University of Bern, 3012 Bern, Switzerland; (26) W.L. Tseng, Department of Earth Sciences, National Taiwan Normal University, Taiwan; (27) A. Vorburger, Physics Institute, University of Bern, 3012 Bern, Switzerland.