Physics‐based solar wind driver functions for the magnetosphere: Combining the reconnection‐coupled MHD generator with the viscous interaction

Borovsky, Joseph E.

doi:10.1002/jgra.50557

Cited by 32 publications

(59 citation statements)

References 174 publications

(266 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a well‐known periodicity in the solar wind and in geomagnetic activity at the solar rotation period of 27 days that produces these peaks in the autocorrelation functions [cf. Borovsky , , Figure 13; Borovsky and Denton , , Figure 10]. Looking at plots of the autocorrelation functions for longer times (not shown), about 10 peaks at 27 day multiples can be seen for the autocorrelation functions of the indices F e1.2 and F e130 and about 15 peaks at 27 day multiples can be identified for the autocorrelation function of v sw .…”

Section: Autocorrelations and Correlations Of The Substorm Indicesmentioning

confidence: 97%

Systems science of the magnetosphere: Creating indices of substorm activity, of the substorm‐injected electron population, and of the electron radiation belt

Borovsky

Yakymenko

2017

JGR Space Physics

Self Cite

View full text Add to dashboard Cite

To more fully monitor the elements of the magnetosphere‐ionosphere system and its activity, indices are created to quantify the rate of substorm onset occurrence, the rate of substorm activations, the intensity of the 130 keV substorm‐injected electrons and the intensity of the 1.2 MeV radiation‐belt electrons. The reactions of these various indices to the onset of isolated substorms are examined, and the behaviors of the indices are explored before and during high‐speed‐stream‐driven storms and during solar wind rarefactions after high‐speed streams. Autocorrelation functions of the indices are analyzed and compared with autocorrelation functions of solar wind parameters and geomagnetic indices. Lagged‐time correlations between the indices and solar wind variables and geomagnetic indices are surveyed. These 1 h resolution indices are available to the research community.

show abstract

Section: Autocorrelations and Correlations Of The Substorm Indicesmentioning

confidence: 97%

Systems science of the magnetosphere: Creating indices of substorm activity, of the substorm‐injected electron population, and of the electron radiation belt

Borovsky

Yakymenko

2017

JGR Space Physics

Self Cite

View full text Add to dashboard Cite

show abstract

“…A number of corrections to the control function were developed in Borovsky [] resulting in minor improvements of the correlation with activity indices. This work was extended in Borovsky [] to include the viscous interaction. Typical correlation coefficients with activity indices were about 0.8 corresponding to a prediction efficiency of ~60%.…”

Section: Coupling Functionsmentioning

confidence: 99%

An optimum solar wind coupling function for the AL index

2015

View full text Add to dashboard Cite

We define a coupling function as a product of solar wind factors that partially linearizes the relation between it and a magnetic index. We consider functions that are a product of factors of solar wind speed V, density N, transverse magnetic field B ⊥ , and interplanetary magnetic field (IMF) clock angle θ c each raised to a different power. The index is the auroral lower (AL index) which monitors the strength of the westward electrojet. Solar wind data 1995-2014 provide hour averages of the factors needed to calculate optimum exponents. Nonlinear inversion determines both the exponents and linear prediction filters of short data segments. The averages of all exponents are taken as optimum exponents and for V, N, B ⊥ , and sin(θ c /2) are [1.92, 0.10, 0.79, 3.67] with errors in the second decimal. Hourly values from 1966 to 2014 are used next to calculate the optimum function (opn) and the functions VBs (eys), epsilon (eps), and universal coupling function (ucf). A yearlong window is advanced by 27 days calculating linear prediction filters for the four functions. The functions eps, eys, ucf, and opn, respectively, predict 43.7, 61.2, 65.6, and 68.3% of AL variance. The opn function is 2.74% better than ucf with a confidence interval 2.60-2.86%. Coupling strength defined as the sum of filter weights (nT/mV/m) is virtually identical for all functions and varies systematically with the solar cycle being strongest (188 nT/mV/m) at solar minimum and weakest (104) at solar maximum. Saturation of the polar cap potential approaching solar maximum may explain the variation.

show abstract

“…Borovsky , , equation ; cf. Borovsky , , equation ]

{normalβ}_{normals} = {((), M_{A} true/ 6)}^{1.92} .

Finally, the mass density ρ s of the magnetosheath plasma near the nose of the magnetosphere can be written as [cf. Borovsky , , equation ]

{normalρ}_{normals} = C {normalρ}_{normalo},

where ρ o is the mass density of the solar wind and C is the compression ratio of the bow shock, which can be written as [cf.…”

Section: The Reconnection‐rate Reduction Factor For Magnetospheric Dementioning

confidence: 99%

“…Cassak and Shay , , equation ]

{normalv}_{out}^{2} {= (B}_{normalm} {normalB}_{normals} / 4 π) (({normalB}_{normalm} {+ B}_{normals}) / ({normalρ}_{normalm} {normalB}_{normals} + {normalρ}_{normals} {normalB}_{normalm})) .

Writing the mass‐density factor in the denominator of expression as

({normalρ}_{normalm} {normalB}_{normals} + {normalρ}_{normals} {normalB}_{normalm}) = {normalρ}_{normals} {normalB}_{normalm} (1 + p),

where p ≡ ρ m B s /ρ s B m (cf. expression ), expression can be written as

{normalv}_{out} {= v}_{As} {((), ((), B_{m} true/ B_{s}) + 1)}^{1 / 2} {((), 1 + normalp)}^{- 1 / 2} .

Using expression to replace B m /B s and expression to replace (1 + p) −1/2 , expression becomes

{normalv}_{out} {= v}_{As} {([], true(1 + β_{s})^{1 true/ 2} + 1)}^{1 / 2} M .

Section: The Length Of the Dayside Reconnection X‐linementioning

confidence: 99%

“…expression ), expression can be written as

{normalv}_{out} {= v}_{As} {((), ((), B_{m} true/ B_{s}) + 1)}^{1 / 2} {((), 1 + normalp)}^{- 1 / 2} .

Using expression to replace B m /B s and expression to replace (1 + p) −1/2 , expression becomes

{normalv}_{out} {= v}_{As} {([], true(1 + β_{s})^{1 true/ 2} + 1)}^{1 / 2} M .

In the Borovsky [] derivation for the estimate of the length of the reconnection X‐line, the condition p = 0, which is M = 1, was taken. For p ≠ 0, which gives M < 1, the reconnection‐outflow speed v out is slower than assumed by Borovsky []; hence, when ρ m ≠ 0, the shutdown of reconnection by shear associated with the magnetosheath flow is more severe and the reconnection X‐line will be shorter than that derived by Borovsky []. For the magnetosheath plasma flowing around the magnetosphere, flow shear increases in intensity with increasing distance from the nose of the magnetosphere.…”

Section: The Length Of the Dayside Reconnection X‐linementioning

confidence: 99%

See 1 more Smart Citation

Estimating the effects of ionospheric plasma on solar wind/magnetosphere coupling via mass loading of dayside reconnection: Ion‐plasma‐sheet oxygen, plasmaspheric drainage plumes, and the plasma cloak

et al. 2013

Self Cite

View full text Add to dashboard Cite

[1] Estimates are calculated for the storm time reduction of solar wind/magnetosphere coupling by the mass density ρ m of the magnetospheric plasma. Based on the application of the Cassak-Shay reconnection-rate formula at the dayside magnetopause, a numerical factor M is developed to quantify the effect of ρ m on the dayside reconnection rate. It is argued that the mass loading of dayside reconnection by ρ m also makes reconnection more susceptible to shutoff by magnetosheath velocity shear: a formula is developed to estimate the shortening of the dayside reconnection X-line by ρ m . Surveys of plasmaspheric drainage plumes at geosynchronous orbit during high-speed-stream-driven storms and coronal mass ejection (CME)-driven storms are presented: in the surveys the CME-driven storms are separated into sheath-driven portions and magnetic-cloud-driven portions. The storm time mass density of the warm plasma cloak (ionospheric outflows into the electron plasma sheet) is obtained from Alfven-wave analysis at geosynchronous orbit. A methodology is developed to extrapolate geosynchronous-orbit plasma measurements to the dayside magnetopause. For each of the three plasmas, estimates of the fractional reduction of the total dayside reconnection rate vary, with typical values of tens of percent; i.e., solar wind/ magnetosphere coupling is reduced by tens of percent during storms by oxygen in the ion plasma sheet, by the plasmaspheric drainage plume, and by the plasma cloak. Dependence of the reduction on the F 10.7 solar radio flux is anticipated. Via these ionospheric-origin plasmas, the magnetosphere can exert some control over solar wind/magnetosphere coupling. Pathways to gain a fuller understanding of the physics of the solar wind-driven magnetosphere-ionosphere system are discussed.Citation: Borovsky, J. E., M. H. Denton, R. E. Denton, V. K. Jordanova, and J. , Estimating the effects of ionospheric plasma on solar wind/magnetosphere coupling via mass loading of dayside reconnection: Ion-plasma-sheet oxygen, plasmaspheric drainage plumes, and the plasma cloak,

show abstract

Physics‐based solar wind driver functions for the magnetosphere: Combining the reconnection‐coupled MHD generator with the viscous interaction

Cited by 32 publications

References 174 publications

Systems science of the magnetosphere: Creating indices of substorm activity, of the substorm‐injected electron population, and of the electron radiation belt

Systems science of the magnetosphere: Creating indices of substorm activity, of the substorm‐injected electron population, and of the electron radiation belt

An optimum solar wind coupling function for the AL index

Estimating the effects of ionospheric plasma on solar wind/magnetosphere coupling via mass loading of dayside reconnection: Ion‐plasma‐sheet oxygen, plasmaspheric drainage plumes, and the plasma cloak

Contact Info

Product

Resources

About