Comments on “Stochastic TEC Structure Characterization” by Charles Rino, Yu Morton, Brian Breitsch, and Charles Carrano, Journal of Geophysical Research: Space Physics , 124 , https://doi.org/10.1029/2019JA026958

Energetic ions reflected and accelerated by the Earth&#8217;s bow shock travel back into the solar wind, forming the ion foreshock, and generate ultralow frequency (ULF) waves. Such ULF waves have been extensively studied over the past few decades using satellite measurements. However, the spatial variations of the wave properties cannot be well resolved by satellite observations due to the limited number of available spacecraft simultaneously inside the ion foreshock. Therefore, we conduct a global survey of the ULF wave properties in the ion foreshock through analysis of a Vlasiator (a hybrid-Vlasov code) simulation. Previous studies validated that this simulation well reproduced Earth&#8217;s foreshock and the ULF waves in it [e.g., Palmroth et al., 2015; Turc et al., 2018]. Here we focus on the wave properties, including frequency, ellipticity, polarization, wave normal angle and growth rate, of the well-known 30-sec wave and its multiple harmonics. We report that the ULF waves near the edge of the foreshock are very different from the waves in the center of the foreshock. We also show the related ion distribution and discuss the connection between the observed ion beams and ULF waves, aiming at understanding the cause of the observed differences in wave properties.&#160;This study is supported by NASA grant 80NSSC20K0801. Vlasiator is developed by the European Research Council Starting grant 200141-QuESpace, and Consolidator grant GA682068-PRESTISSIMO received by the Vlasiator PI. Vlasiator has also received funding from the Academy of Finland. See www.helsinki.fi/vlasiator&#160;Palmroth, M., et al. (2015), ULF foreshock under radial IMF: THEMIS observations and global kinetic simulation Vlasiator results compared, J. Geophys. Res. Space Physics, 120, 8782&#8211;8798, doi:10.1002/2015JA021526.Turc, L., Ganse, U., Pfau-Kempf, Y., Hoilijoki, S., Battarbee, M., Juusola, L., et al. (2018). Foreshock properties at typical and enhanced interplanetary magnetic field strengths: results from hybrid-Vlasov simulations. Journal of Geophysical Research: Space Physics, 123, 5476&#8211;5493. doi:10.1029/2018JA025466.

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Atmospheric Escape Processes and Planetary Atmospheric Evolution: from misconceptions to challenges

10.5194/epsc2020-32 ◽

2020 ◽

Author(s):

Guillaume Gronoff ◽

Phil Arras ◽

Suleiman Baraka ◽

Jared M Bell ◽

Gael Cessateur ◽

...

Keyword(s):

A Priori ◽

Careful Analysis ◽

Space Physics ◽

Habitable Zone ◽

M Dwarfs ◽

Geophysical Research ◽

Atmospheric Evolution ◽

Atmospheric Escape ◽

Surface Location ◽

New Criteria

The recent discoveries of telluric exoplanets in the habitable zone of different stars have led to questioning the nature of their atmosphere, which is required to determine their habitability. Atmospheric escape is one of the challenging problems to be solved: simply adapting what is currently observed in the solar system is doomed to fail due to the large variations in the conditions encountered around other stars. A better strategy is to review the different processes that shaped planetary atmospheres and to evaluate their importance depending upon the stellar conditions. This approach allowed us to show that processes like ion-pickup were a more important way to lose atmosphere at Mars in the past.&#160; We reviewed the different escape mechanisms and their magnitude in function of the different conditions. This led us to discover discrepancies in the current literature concerning problems such as the Xenon paradox or the importance of a magnetic field in protecting an atmosphere. This shows that one should be very careful before claiming the presence of an atmosphere on planets in the habitable zone of their M-dwarfs: new criteria such as the Alfven surface location with respect to the planet should be taken into account a-priori. Overall, the habitability of a planet should not be claimed only on by its location in the habitable zone but also after careful analysis of the interaction between its atmosphere and its parent star [Gronoff et al. 2020].&#160; &#160; &#160;Gronoff, G., Arras, P., Baraka, S., Bell, J. M., Cessateur, G., Cohen, O., et al. ( 2020). Atmospheric Escape Processes and Planetary Atmospheric Evolution. Journal of Geophysical Research: Space Physics, 125, e2019JA027639. https://doi.org/10.1029/2019JA027639&#160;

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On the flow of geomagnetically induced currents in an electric power transmission network

Canadian Journal of Physics ◽

10.1139/p10-028 ◽

2010 ◽

Vol 88 (5) ◽

pp. 357-363 ◽

Cited By ~ 4

Author(s):

Risto J. Pirjola

Keyword(s):

Electric Power ◽

Power Transmission ◽

Power Grid ◽

Space Physics ◽

Practical Significance ◽

Test Model ◽

Geomagnetically Induced Currents ◽

Geophysical Research ◽

Model Calculations ◽

Induced Currents

Geomagnetically induced currents (GICs) in conductor networks are among the ground-level effects of space weather. GICs are a possible source of problems to the system. Today, electric power transmission grids are the most important concern regarding GICs, which may in the worst cases lead to blackouts in large areas and permanent damage to transformers. The evaluation of GIC risks and the design of possible countermeasures require estimation of expected GIC magnitudes in transformers. This can be achieved by model calculations supplemented by GIC recordings at some sites. Although in principle GICs can flow all over a large galvanically-connected power grid, which should thus be included as a whole in a GIC calculation, the network must usually be restricted somehow in practical computations of GICs. By using a power grid test model, this paper provides a systematic numerical investigation showing that GICs do not flow over very long distances in a power grid, which is a good result and justifies the neglect of the parts of the network that lie far away from the area of primary interest. Besides practical significance in electric power engineering, studies of GICs can be used for space physics and geophysical research as well. It is also important to understand the features of the flow pattern of GICs in a network.

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Polar Mesospheric Summer Echoes (PMSE) during artificial heating

10.5194/egusphere-egu21-7237 ◽

2021 ◽

Author(s):

Tinna Gunnarsdottir ◽

Arne Poggenpohl ◽

Ove Havnes ◽

Ingrid Mann

Keyword(s):

Electron Temperature ◽

Electron Density ◽

Initial Density ◽

Space Physics ◽

Dust Particles ◽

Typical Result ◽

Geophysical Research ◽

Ice Particles ◽

Radar Scattering ◽

Summer Echoes

Polar Mesospheric Summer Echoes (PMSE) are regions of enhanced radar backscatter at 80 to 90 km that are assumed to form in the presence of neutral air turbulence and charged ice particles as a result of spatial variations in the electron density. Changes in the electron temperature, as can be generated by the EISCAT heater, influence the electron diffusivity as well as the charging of the ice particles and both are parameters that influence the radar scattering. In many cases, an overshoot effect [1] can be observed when the backscattered power is reduced during heater-on and rises above the initial signal during heater-off. We present observations made on the 11-12 and 15-16 of August 2018 with the EISCAT VHF radar during PMSE conditions. The EISCAT heating facility, operated at 5.423 MHz, was run in identical cycles where the heater was on for 48 seconds and off for 168 seconds. The observations clearly show the overshoot effect, caused by the cyclic heating of PMSE. &#160;The surface charge of the ice particles increases during the heater-on intervals because of the higher electron temperature. As the heater is turned off the electrons are quickly cooled. The dust particles, however, still carry a higher charge, i.e. more electrons, so that the electrons cannot immediately obtain the initial density distribution. The typical result is that the electron density gradients are increased, which in turn lead to increased radar scattering, an overshoot. During the heater off phase, dust and plasma conditions are expected to relax back to undisturbed conditions. A theory was developed by Havnes [1] to explain the overshoot and we use a dusty plasma code [2] based on this theory to calculate the overshoot curves. They agree well with the average of the observational data. There is clear indication that during high precipitation the PMSE cloud is not affected by the heater and accordingly does not show an overshoot effect.&#160;&#160;1. &#160; &#160; Havnes, O. (2004). Polar Mesospheric Summer Echoes (PMSE) overshoot effect due to cycling of artificial electron heating. Journal of Geophysical Research: Space Physics, 109(A2).2. &#160; &#160; Biebricher, A., Havnes, O., Hartquist, T. W., & LaHoz, C. (2006). On the influence of plasma absorption by dust on the PMSE overshoot effect. Advances in Space Research, 38(11), 2541-2550.

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Energetic proton depletion near Io: atmospheric charge exchange and inhomogeneous magnetic and electric fields

10.5194/epsc2020-588 ◽

2020 ◽

Author(s):

Christiaan van Buchem ◽

Hans Huybrighs ◽

Aljona Blöcker ◽

Vincent Dols ◽

Olivier Witasse ◽

...

Keyword(s):

Electric Fields ◽

Charge Exchange ◽

Large Scale ◽

Space Physics ◽

Scale Height ◽

Neutral Atmosphere ◽

Geophysical Research ◽

Particle Tracing ◽

Energetic Proton ◽

Galilean Moon

The flux of energetic protons (80 keV-1.04 Mev) near the Galilean moons was measured by the Energetic Particle Detector (EPD) on the Galileo mission (1995 - 2003). Near Galilean moon, such as Io and Europa, depletions of the energetic proton flux, of several orders of magnitude, were observed. Such energetic proton depletions can be caused by the precipitation of these particles onto the moon's surface or charge exchange with the neutral atmosphere. In order to interpret the depletion features in the EPD data, a Monte Carlo particle tracing code has been developed by (H. L. F. Huybrighs et al., 2020; Hans L. F. Huybrighs et al., 2017; Hans Leo Frans Huybrighs, 2018). The expected flux of the energetic ions is simulated under different scenarios, for three Galileo flybys of Io (I24, I27, and I31), including with and without an atmosphere and inhomogeneous magnetic and electric fields. By comparing the simulated distribution to the EPD data, the cause of the depletion features can be investigated. The following causes of energetic proton depletion near Io are identified: <ul> <li>Some depletions are consistent with atmospheric charge exchange for flybys I24, I27, and I31.</li> <li>Some of depletions coincide with the inhomogeneous fields produced in the MHD model by (Dols et al., 2012) for flybys I24, I27, and I31.</li> <li>For I24 the depletions are consistent with a two component atmosphere: a dense low scale height atmosphere and an extended corona described by a low surface density but a large scale height as presented by (Bl&#246;cker et al., 2018).</li> </ul> Furthermore, latitudinal and longitudinal dependencies in the atmospheric models for Io are investigated for all three aforementioned flybys. Bibliography <ul> <li>Bl&#246;cker, A., Saur, J., Roth, L., & Strobel, D. F. (2018). MHD Modeling of the Plasma Interaction With Io&#8217;s Asymmetric Atmosphere. Journal of Geophysical Research: Space Physics, 123(11), 9286&#8211;9311. https://doi.org/10.1029/2018JA025747</li> <li>Dols, V., Delamere, P. A., Bagenal, F., Kurth, W. S., & Paterson, W. R. (2012). Asymmetry of Io&#8217;s outer atmosphere: Constraints from five Galileo flybys. Journal of Geophysical Research: Planets, 117(E10). https://doi.org/10.1029/2012JE004076</li> <li>Huybrighs, H. L. F., Roussos, E., Bl&#246;cker, A., Krupp, N., Futaana, Y., Barabash, S., et al. (2020). An Active Plume Eruption on Europa During Galileo Flyby E26 as Indicated by Energetic Proton Depletions. Geophysical Research Letters, 47(10). https://doi.org/10.1029/2020gl087806</li> <li>Huybrighs, Hans L. F., Futaana, Y., Barabash, S., Wieser, M., Wurz, P., Krupp, N., et al. (2017). On the in-situ detectability of Europa&#8217;s water vapour plumes from a flyby mission. https://doi.org/10.1016/j.icarus.2016.10.026</li> <li>Huybrighs, Hans Leo Frans. (2018). A search for signatures of Europa&#8217;s atmosphere and plumes in Galileo charged particle data. Retrieved from http://arxiv.org/abs/1812.11215</li> </ul>

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Timescales of Ionospheric Field-Aligned Currents during a Geomagnetic Storm: Global Magnetospheric Simulations

10.5194/egusphere-egu2020-16461 ◽

2020 ◽

Author(s):

Joseph Eggington ◽

John Coxon ◽

Robert Shore ◽

Ravindra Desai ◽

Lars Mejnertsen ◽

...

Keyword(s):

Magnetic Field ◽

Solar Wind ◽

Geomagnetic Storm ◽

Geomagnetic Storms ◽

Onset Time ◽

Space Physics ◽

System Response ◽

Time Lags ◽

Geophysical Research ◽

Novel Approach

Geomagnetic storms generate a complex and highly time-dependent response in the magnetosphere-ionosphere system. Enhancement in field-aligned currents (FACs) can be very localised, and so accurately predicting the stormtime response of the ionosphere is crucial in forecasting the potential impacts of a severe space weather event at a given location on the Earth. Global MHD simulations provide a means to model ionospheric conditions in real-time for a given geomagnetic storm, allowing direct comparison to space- and ground-based observations from which the observations can be placed in global context to better understand the physical drivers behind the system's response.&#160;&#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160;&#160;Using the Gorgon MHD code and driving with upstream data from the ACE spacecraft, we simulate the state of the magnetosphere-ionosphere system during a geomagnetic storm commencing on 3rd May 2014. To elucidate the characteristic timescales of the system response during this event, we adopt a novel approach originally applied by Shore et al. (2019) to ground magnetic field data from SuperMAG, and by Coxon et al. (2019) to FAC data from AMPERE. In this method the simulated FAC at each point on the ionospheric grid is cross-correlated with solar wind time-series for time lags of up to several hours, and the lag with the strongest correlation is identified.From this we construct maps of the characteristic response timescale and strength of correlation in the ionosphere to IMF By and Bz, and interpret these results in terms of the varying stormtime FAC morphology by comparing the simulation results to observations by AMPERE and SuperMAG during this same event. Finally, we identify sources of asymmetry in the ionospheric response, such as that between day/night and north/south, relating these to asymmetries in magnetospheric dynamics such as magnetopause and magnetotail reconnection, and changes in global convection as the system reconfigures. This will reveal the importance of different aspects of magnetosphere-ionosphere system in influencing the coupling timescales, as well as the role of onset time in determining the potential impacts of a severe event. References:Shore, R. M., Freeman, M. P., Coxon, J. C., Thomas, E. G., Gjerloev, J. W., & Olsen, N. (2019). Spatial variation in the responses of the surface external and induced magnetic field to the solar wind. Journal of Geophysical Research: Space Physics, 124. https://doi.org/10.1029/2019JA026543Coxon, J. C., Shore, R. M., Freeman, M. P., Fear, R. C., Browett, S. D., Smith, A. W., et al. (2019). Timescales of Birkeland currents driven by the IMF. Geophysical Research Letters, 46, 7893&#8211; 7901. https://doi.org/10.1029/2018GL081658

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Characterization of the Pc5 frequency range power spectrum at low latitude in 22 years of geomagnetic field observations.

10.5194/egusphere-egu2020-4516 ◽

2020 ◽

Author(s):

Alessandro Colonico ◽

Simone Di Matteo ◽

Umberto Villante

Keyword(s):

Critical Role ◽

Field Measurements ◽

Space Physics ◽

Spectral Indices ◽

Frequency Range ◽

Geophysical Research ◽

Low Latitude ◽

Background Spectrum ◽

Robust Identification ◽

Magnetospheric Field

An important aspect of the interaction between the solar wind (SW) and the Earth&#8217;s magnetosphere concerns the possible relationship between SW and magnetospheric fluctuations under different SW conditions. In recent investigations (Di Matteo and Villante, 2017,2018) we revealed the critical role of the analytical methods and the spectral analysis techniques in the identification of fluctuations between &#8776;1-5 mHz in the SW parameters as well as in the magnetospheric field measurements at the geostationary orbit and developed a new approach, based on the joint use of the Welch and the Multitaper methods, for a more robust identification of these oscillations in both regions. Here, we extend the analysis to ground measurements, analyzing 22 years of magnetic field measurements along the H and D components at low latitude (L&#8217;Aquila, Italy, &#955;&#8776;36.3&#176;, L&#8776;1.6). We found that, in general, the much steeper spectrum of the geomagnetic fluctuations with respect to the ones estimated in the SW parameters and magnetospheric field, might deeply influence the identification of real events. We then examined, for the entire period, consecutive two hours intervals through the day during low geomagnetic activity conditions (Dst>-50), and, for each interval, we carefully evaluated the characteristics of the background spectrum. As a matter of fact, in the &#8776;1-5 mHz frequency range the spectral indices of both components typically range between -3.5 and -2 with a steeper spectrum in the night sector when the fluctuations power is lower. Simulations of red noise representations, with spectral indices similar to the observed ones, combined with the Sq variation show a systematic reduction of the rate of identification of real events up to &#8776;2 mHz.Ref.Di Matteo, S., and U. Villante, J. Geophys.Res. Space Physics, 122, 4905&#8211;4920, doi:10.1002/2017JA023936.Di Matteo, S., and U. Villante, Journal of Geophysical Research: Space Physics, 123, doi.org/10.1002/2017JA024922.

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Comparison of semi-implicit and explicit particle in cell methods for the study of turbulence in space plasmas

10.5194/egusphere-egu2020-9805 ◽

2020 ◽

Author(s):

Francesco Pucci ◽

Tulasi N. Parashar ◽

William H. Matthaeus ◽

Giovanni Lapenta

Keyword(s):

Large Scale ◽

Plasma Heating ◽

Debye Length ◽

Space Physics ◽

Computational Time ◽

Maxwell System ◽

Temperature Anisotropy ◽

Geophysical Research ◽

Particle In Cell ◽

Non Linear

The plasma that permeates the solar wind, the solar corona, the Earth's magnetosheath and several other space environments is in a turbulent state. The effect of turbulence on the dynamics of such systems&#160; is very relevant, considering that it is invoked to explain plasma heating, and particle acceleration and transport in those environments. From a mathematical point of view, turbulence is a non linear phenomenon whose study, in the kinetic&#160; description of plasmas, requires the solution of the non linear Vlasov-Maxwell system of equations.&#160; Due to the complexity of the problem, the solutions are nowadays found mainly by means of numerical simulations.&#160; The most widely used method for the solution of the Vlasov-Maxwell system is the Particle In Cell (PIC) method. &#160;&#160; PIC methods can be divided into two major classes: explicit and implicit, depending on the algorithm used for advancing the solution in time. In this work, we compare two different PIC methods that use an explicit and a semi-implicit algorithm, respectively.&#160; The explicit method is implemented in the code P3D[1], while the semi-implicit method in code iPic3D[2]. Both methods are fully kinetic, namely they retain the kinetic effects for both ions and electrons.&#160; The two codes are tested against a classical set up of plasma turbulence in a 2D cartesian&#160; geometry[3]. The system is initialized with a restricted number of modes at large scale and evolves in time without forcing. The box size is of several tens of ion inertial length. The&#160; grid size is of the order of the Debye length for the explicit scheme, to ensure numerical stability, and is varied across the electron skin depth for the semi-implicit, by performing different simulations. Several analyses are presented: global energy conversion, magnetic and electric spectra, scale dependent kurtosis,&#160; temperature anisotropy for both species, proxies of dissipation such as J.E and PiD[4]. The weaknesses and strengths of the two methods in terms of description of the physical dynamics and of&#160; computational time are presented, along with a convergence study of the semi-implicit to the explicit method as the resolution of the former is varied.&#160;[1] Zeiler, A., Biskamp, D., Drake, J. F., Rogers, B. N., Shay, M. A., & Scholer, M. (2002). Journal of Geophysical Research: Space Physics, 107(A9), SMP-6. [2] Markidis, S., Lapenta, G., & Rizwan-uddin (2010). Mathematics and Computers in Simulation, 80(7), 1509-1519. [3] Parashar, T. N., Matthaeus, W. H., & Shay, M. A. (2018). The Astrophysical Journal Letters, 864(1), L21. [4] Yang, Y., Matthaeus, W. H., Parashar, T. N., Wu, P., Wan, M., Shi, Y., et al. (2017). Physical Review E, 95(6), 061201.

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