The role of magnetospheric plasma in solar wind-magnetosphere coupling: A review

Walsh, Brian M.; Zou, Ying

doi:10.1016/j.jastp.2021.105644

Cited by 8 publications

(8 citation statements)

References 81 publications

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“…These are numerous. They include: mass loading of the near‐Earth tail with ionospheric O + ions from the cleft ion fountain (Yu & Ridley, 2013); the formation of thin tail current sheets (Pulkkinen & Wiltberger, 2000); the development of a cold dense plasma sheet (Lavraud et al., 2006); and mass loading of the dayside magnetopause reconnection region (Walsh & Zou, 2021).…”

Section: Preconditioningmentioning

confidence: 99%

Solar Wind—Magnetosphere Coupling Functions: Pitfalls, Limitations, and Applications

Lockwood

2022

Space Weather

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Coupling functions are widely used constructs in space physics designed to quantify the effect of given set of solar wind conditions incident upon the near-Earth space environment, the magnetosphere. They do not try to allow for every physical mechanism involved explicitly, rather they attempt to capture and amalgamate the key drivers and explain a large fraction of the variance of a terrestrial space weather index or indicator. Correlations between interplanetary parameters and terrestrial disturbance indices became possible after the first spacecraft to visit interplanetary space had acquired sufficient data (e.g., Arnoldy, 1971) and the concept of combining parameters into a coupling function that allows for the different influences on terrestrial space-weather disturbance was first introduced in the PhD thesis of Perreault (1974). This led to the much-used "epsilon factor" coupling function, ε (Perreault & Akasofu, 1978). Unfortunately, there was an error in the theoretical basis for ε (Lockwood, 2019) which causes it to perform significantly less well, on all timescales, than other coupling functions (Finch & Lockwood, 2007). A large number of alternative formulations have been proposed since (see reviews by Newell et al. [2007], McPherron, et al. [2015], and Lockwood and McWilliams [2021b). Some of these coupling functions are based on theory, others are empirical fits to observations. In reality, most are a mixture of both approaches, with theory guiding the selection of parameters for empirical coupling functions (and the mathematical formulation used to combine them), whereas theoretically -derived coupling functions often use coefficients, branching ratios or exponents that are taken from observations. Coupling functions have also been derived and/or tested using global numerical MHD simulations of the magnetosphere (e.g., Wang et al., 2014). For all coupling functions, correlation with one or more terrestrial space weather disturbance index has traditionally been used as the metric by which their merit and performance is evaluated. In the past, not much attention was paid to the effects of this choice of performance metric, nor the effects of averaging timescale, nor the fact that different parts, features and indices of the coupled magnetosphere-ionosphere-thermosphere system respond differently to a given set of conditions. In addition, when building a space weather climatology, we will need to know the form of the occurrence probability distributions of indicators of space weather phenomena in order to predict probabilities of certain conditions, events and integrated effects (Lockwood et al., 2019b(Lockwood et al., , 2019c. However, little attention has been given to matching the distributions of a proposed coupling functions to those of the space weather indicator that they are designed to predict. Studies of coupling between the solar wind and the magnetosphere are now increasingly applying systems analysis and machine-learning techniques (e.g.

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Section: Preconditioningmentioning

confidence: 99%

Solar Wind—Magnetosphere Coupling Functions: Pitfalls, Limitations, and Applications

Lockwood

2022

Space Weather

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“…Finally, the preconditioning of the magnetosphere (Borovsky and Steinberg, 2006;Lavraud et al, 2006), which will alter the reaction of the magnetosphere to driving, and solar-wind/ magnetosphere feedback loops (Borovsky and Valdivia, 2018;Walsh and Zou, 2021), which will produce a time-dependent reaction to steady driving, have not been considered.…”

Section: Other Issuesmentioning

confidence: 99%

On the Saturation (or Not) of Geomagnetic Indices

Borovsky

2021

Front. Astron. Space Sci.

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Most geomagnetic indices are associated with processes internal to the magnetosphere-ionosphere system: convection, magnetosphere-ionosphere current systems, particle pressure, ULF wave activity, etc. The saturation (or not) of various geomagnetic indices under various solar-wind driver functions (a.k.a. coupling functions) is explored by examining plots of the various indices as functions of the various driver functions. In comparing an index with a driver function, “saturation” of the index means that the trend of stronger geomagnetic activity with stronger driving weakens in going from mid-range driving to very strong driving. Issues explored are 1) whether the nature of the index matters (i.e., what the index measures and how the index measures it), 2) the relation of index saturation to cross-polar-cap potential saturation, and 3) the role of the choice of the solar-wind driver function. It is found that different geomagnetic indices exhibit different amounts of saturation. For example the SuperMAG auroral-electrojet indices SME, SML, and SMU saturate much less than do the auroral-electrojet indices AE, AL, and AU. Additionally it is found that different driver functions cause an index to show different degrees of saturation. Dividing a solar-wind driver function by the theoretical cross-polar-cap-potential correction (1+Q) often compensates for the saturation of an index, even though that index is associated with internal magnetospheric processes whereas Q is derived for solar-wind processes. There are composite geomagnetic indices E(1) that show no saturation when matched to their composite solar-wind driver functions S(1). When applied to other geomagnetic indices, the composite S(1) driver functions tend to compensate for index saturation at strong driving, but they also tend to introduce a nonlinearity at weak driving.

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“…Similarly to the MP behavior under northward IMF, this boundary layer is characterized by the magnetic field pile-up and density decrease. Nevertheless, questions as how is the magnetosheath flow influenced by geomagnetic storms or what is the role of plasmaspheric plume at the magnetopause remain open (Walsh & Zou, 2021).…”

Section: Discussionmentioning

confidence: 99%

Storm‐Time Magnetopause: Pressure Balance

et al. 2022

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The magnetopause (MP) is a thin current sheet which separates shocked solar wind (SW) flow carrying frozen-in interplanetary magnetic field (IMF) from the area controlled by the terrestrial magnetic field forming the Earth's magnetosphere. The MP shape and position are determined by the upstream conditions characterized by the dynamic pressure (P DYN ) and by IMF orientation, mostly represented by its B Z component. When approaching the Earth magnetosphere, the supersonic SW is converted into a subsonic plasma flow through a formation of the bow shock. The region between the bow shock and MP, so called the magnetosheath, is occupied by the SW plasma that is slowed down, heated, and compressed and its dynamic pressure is converted into the thermal (ion plus electron) and magnetic pressures. The sum of the pressures is expected to be nearly equal to the SW dynamic pressure (note that farther from the subsolar point, the magnetosheath velocity is non-zero). However, Samsonov et al. (2012) andSamsonov et al. (2016) reported that the total pressure exerted onto the subsolar MP is lower than the SW dynamic pressure and their ratio depends on the IMF orientation. Thus, the MP location is given by a balance of the magnetosheath total pressure and magnetospheric magnetic pressure because the pressure of hot and tenuous magnetospheric plasma is supposed to be negligible. This approach is used in many MP empirical models because it leads to scaling of the MP standoff distance as 𝐴𝐴 𝐴𝐴 −1∕6 DYN . Based on this simple consideration, the magnitude of the magnetospheric magnetic field (B MSP ) would be larger than that in the magnetosheath (B MSH ). However, Farrugia et al. (2017) presented the observations of two dayside MP crossings when B MSH is by a factor of 2.2 larger than B MSP during a passage of the magnetic cloud when IMF was high, the upstream dynamic pressure dropped notably under 1 nPa and the SW flow became sub-Alfvénic. Although these circumstances in the SW are exceptional, the interaction of a low Mach number (M A

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The role of magnetospheric plasma in solar wind-magnetosphere coupling: A review

Cited by 8 publications

References 81 publications

Solar Wind—Magnetosphere Coupling Functions: Pitfalls, Limitations, and Applications

Solar Wind—Magnetosphere Coupling Functions: Pitfalls, Limitations, and Applications

On the Saturation (or Not) of Geomagnetic Indices

Storm‐Time Magnetopause: Pressure Balance

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