Ionospheric control of the magnetosphere: conductance

Ridley, A. J.; Gombosi, T. I.; Zeeuw, Darren L. De

doi:10.5194/angeo-22-567-2004

Cited by 383 publications

(489 citation statements)

References 29 publications

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“…The electric field changes resulting from weaker conductances can affect the magnetospheric phenomena, altering the current patterns. Ridley et al (2004) conducted multiple MHD simulations with the same solar wind/IMF conditions but with different Pederson conductances, showing that field-aligned currents decrease as the Pederson conductances decrease. If we expect similar behaviors in our MHD model (although our case is more complicated than his ideal cases), the reduced conductances can decrease field-aligned currents, thus resulting in less electric field changes due to the decrease of the two primary parameters in the current continuity equation.…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, MHD models cannot simulate auroral particle dynamics due to their fluid approach. The MHD modelers take different approaches to parameterize auroral precipitation (Raeder 2003;Ridley et al 2004;Zhang et al 2015a). However, these approaches are empirically or analytically obtained with assumptions that simplify auroral process and most importantly the spatial distribution of precipitation patterns.…”

Section: Summary and Concluding Remarksmentioning

confidence: 99%

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Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

Connor

Zesta

Fedrizzi

et al. 2016

J. Space Weather Space Clim.

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The magnetosphere is a major source of energy for the Earth's ionosphere and thermosphere (IT) system. Current IT models drive the upper atmosphere using empirically calculated magnetospheric energy input. Thus, they do not sufficiently capture the stormtime dynamics, particularly at high latitudes. To improve the prediction capability of IT models, a physics-based magnetospheric input is necessary. Here, we use the Open Global General Circulation Model (OpenGGCM) coupled with the Coupled Thermosphere Ionosphere Model (CTIM). OpenGGCM calculates a three-dimensional global magnetosphere and a two-dimensional high-latitude ionosphere by solving resistive magnetohydrodynamic (MHD) equations with solar wind input. CTIM calculates a global thermosphere and a high-latitude ionosphere in three dimensions using realistic magnetospheric inputs from the OpenGGCM. We investigate whether the coupled model improves the storm-time IT responses by simulating a geomagnetic storm that is preceded by a strong solar wind pressure front on August 24, 2005. We compare the OpenGGCM-CTIM results with low-earth-orbit satellite observations and with the model results of Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe). CTIPe is an up-to-date version of CTIM that incorporates more IT dynamics such as a low-latitude ionosphere and a plasmasphere, but uses empirical magnetospheric input. OpenGGCM-CTIM reproduces localized neutral density peaks at~400 km altitude in the high-latitude dayside regions in agreement with in situ observations during the pressure shock and the early phase of the storm. Although CTIPe is in some sense a much superior model than CTIM, it misses these localized enhancements. Unlike the CTIPe empirical input models, OpenGGCM-CTIM more faithfully produces localized increases of both auroral precipitation and ionospheric electric fields near the high-latitude dayside region after the pressure shock and after the storm onset, which in turn effectively heats the thermosphere and causes the neutral density increase at 400 km altitude.

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Section: Resultsmentioning

confidence: 99%

Section: Summary and Concluding Remarksmentioning

confidence: 99%

Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

Connor

Zesta

Fedrizzi

et al. 2016

J. Space Weather Space Clim.

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“…Conductance distributions given by Ridley et al [2004] are representative, indicating a range of S P from 2 to 20 Siemens, representative of the entire dayside region and polar cap under a wide range of conditions, and compatible with 8 S as a typical value. For given Poynting flux, convection speeds will be correspondingly lower in the low-latitude dayside or nighttime auroral zone, but Poynting flux may also be larger, with compensating effect on the magnitude of ionospheric convection speed.…”

Section: Convective Pickupmentioning

confidence: 99%

Mechanisms of ionospheric mass escape

Moore

Khazanov

2010

J. Geophys. Res.

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[1] The dependence of ionospheric O + escape flux on electromagnetic energy flux and electron precipitation into the ionosphere is derived for a hypothetical ambipolar pickup process, powered the relative motion of plasmas and neutral upper atmosphere, and by electron precipitation, at heights where the ions are magnetized but influenced by photoionization, collisions with gas atoms, ambipolar and centrifugal acceleration. Ion pickup by the convection electric field produces "ring-beam" or toroidal velocity distributions, as inferred from direct plasma measurements, from observations of the associated waves, and from the spectra of incoherent radar echoes. Ring beams are unstable to plasma wave growth, resulting in rapid relaxation via transverse velocity diffusion, into transversely accelerated ion populations. Ion escape is substantially facilitated by the ambipolar potential, but is only weakly affected by centrifugal acceleration. If, as cited simulations suggest, ion ring beams relax into nonthermal velocity distributions with characteristic speed equal to the local ion-neutral flow speed, a generalized "Jeans escape" calculation shows that the escape flux of ionospheric O + increases with Poynting flux and with precipitating electron density in rough agreement with observations.

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“…We used the BATS-R-US model of the solar wind-magnetosphere-ionosphere interaction [Gombosi et al, 2000;Ridley et al, 2004], which is available at the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov/). The model is based on the equations of ideal single-fluid MHD.…”

Section: Instrumentation and Modelmentioning

confidence: 99%

Asymmetry of magnetosheath flows and magnetopause shape during low Alfvén Mach number solar wind

et al. 2013

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[1] Previous works have emphasized the significant influence of the solar wind Alfvén Mach number (M A ) on magnetospheric dynamics. Here we report statistical, observational results that pertain to changes in the magnetosheath flow distribution and magnetopause shape as a function of solar wind M A and interplanetary magnetic field (IMF) clock angle orientation. We use all Cluster 1 data in the magnetosheath during the period 2001-2010, using an appropriate spatial superposition procedure, to produce magnetosheath flow distributions as a function of location in the magnetosheath relative to the IMF and other parameters. The results demonstrate that enhanced flows in the magnetosheath are expected at locations quasi-perpendicular to the IMF direction in the plane perpendicular to the Sun-Earth line; in other words, for the special case of a northward IMF, enhanced flows are observed on the dawn and dusk flanks of the magnetosphere, while much lower flows are observed above the poles. The largest flows are adjacent to the magnetopause. Using appropriate magnetopause crossing lists (for both high and low M A ), we also investigate the changes in magnetopause shape as a function of solar wind M A and IMF orientation. Comparing observed magnetopause crossings with predicted positions from an axisymmetric semi-empirical model, we statistically show that the magnetopause is generally circular during high M A , while is it elongated (albeit with moderate statistical significance) along the direction of the IMF during low M A . These findings are consistent with enhanced magnetic forces that prevail in the magnetosheath during low M A . The component of the magnetic forces parallel to the magnetopause produces the enhanced flows along and adjacent to the magnetopause, while the component normal to the magnetopause exerts an asymmetric pressure on the magnetopause that deforms it into an elongated shape.

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Ionospheric control of the magnetosphere: conductance

Cited by 383 publications

References 29 publications

Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

Mechanisms of ionospheric mass escape

Asymmetry of magnetosheath flows and magnetopause shape during low Alfvén Mach number solar wind

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