Estimating the vector electric field using monostatic, multibeam incoherent scatter radar measurements

Nicolls, M. J.; Cosgrove, R. B.; Bahcivan, H.

doi:10.1002/2014rs005519

Cited by 32 publications

(56 citation statements)

References 15 publications

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“…It is clear that the assumption on relatively strong electric fields to ensure strong drift across the field in the midlatitudes also requires an extra theoretical and practical studies. In this paper, we did not evaluate electric fields themselves, as the incoherent scatter radar cannot determine the full vector of the electric field even at one point [ Nicolls et al , ]. The radar measures velocity only along the line of sight which provides the information on the component of the electric field; the information on other components may be provided by other beams, but a monostatic radar gets it from another area of space.…”

Section: Resultsmentioning

confidence: 99%

“…Such an idea of regularizing was used by several authors in papers on the calculation of the electric field full vector by a monostatic multibeam radar [ Nicolls et al , ]. Let us solve the system in respect of V ll and V p :

V_{l l} = A_{l l} - B_{l l} V_{p e}

V_{p} = A_{p} - B_{p} V_{p e},

where

A_{l l} = \frac{V_{155} normalcos ((), β_{159}) - V_{159} Cos ((), β_{155})}{normalcos ((), α_{155}) normalcos ((), β_{159}) - normalcos ((), α_{159}) normalcos ((), β_{155})}

B_{l l} = \frac{normalcos ((), β_{159}) normalcos ((), γ_{155}) - normalcos ((), β_{155}) normalcos ((), γ_{159})}{normalcos ((), α_{155}) normalcos ((), β_{159}) - normalcos ((), α_{159}) normalcos ((), β_{155})}

A_{p} = \frac{V_{159} - A_{l l} normalcos ((), α_{159})}{normalcos ((), β_{159})}

B_{p} = \frac{normalcos ((), γ_{159}) - B_{l l} normalcos ((), α_{159})}{normalcos ((), β_{159})}

…”

Section: Ionospheric Motionsmentioning

confidence: 99%

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Calculation of meridional neutral winds in the middle latitudes from the Irkutsk incoherent scatter radar

et al. 2015

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This paper presents a consistent technique for velocity determination of meridional neutral winds from the Irkutsk incoherent scatter radar (IISR.) We calculated plasma drift velocity based on phase analysis of an autocorrelation function of an incoherent scatter signal. We also preliminary tested the described technique by determining several low‐orbit satellite velocities. Midlatitude meridional neutral winds were calculated using a “three‐beam” technique from the IISR velocity with taking into account motions due to electric fields across magnetic field lines in both meridional and zonal directions. It has been shown that an underestimated impact of the motions generated by electric fields can seriously interfere in determining wind velocities. The results obtained were compared with the modeled wind values.

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Section: Resultsmentioning

confidence: 99%

V_{l l} = A_{l l} - B_{l l} V_{p e}

V_{p} = A_{p} - B_{p} V_{p e},

where

A_{l l} = \frac{V_{155} normalcos ((), β_{159}) - V_{159} Cos ((), β_{155})}{normalcos ((), α_{155}) normalcos ((), β_{159}) - normalcos ((), α_{159}) normalcos ((), β_{155})}

B_{l l} = \frac{normalcos ((), β_{159}) normalcos ((), γ_{155}) - normalcos ((), β_{155}) normalcos ((), γ_{159})}{normalcos ((), α_{155}) normalcos ((), β_{159}) - normalcos ((), α_{159}) normalcos ((), β_{155})}

A_{p} = \frac{V_{159} - A_{l l} normalcos ((), α_{159})}{normalcos ((), β_{159})}

B_{p} = \frac{normalcos ((), γ_{159}) - B_{l l} normalcos ((), α_{159})}{normalcos ((), β_{159})}

…”

Section: Ionospheric Motionsmentioning

confidence: 99%

Calculation of meridional neutral winds in the middle latitudes from the Irkutsk incoherent scatter radar

et al. 2015

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“…A computationally expedient way to define the roughness penalty,

r (ū)

, is in the following form:

r (ū) = ∥ Cū ∥_{2}^{2}

where C is some matrix that measures the roughness at every pixel. One popular choice for C is a discrete approximation to a curvature operator, which has previously been used in aeronomical inverse problems [ Hysell et al , ; Cosgrove et al , ; Nicolls et al , ]. We construct C as a block matrix which measures all second derivatives of u , v , and w :

C = ([], \begin{matrix} C_{xx}^{u} \\ C_{xy}^{u} \\ C_{yx}^{u} \\ C_{yy}^{u} \\ C_{xx}^{v} \\ C_{xy}^{v} \\ C_{yx}^{v} \\ C_{yy}^{v} \\ C_{xx}^{w} \\ C_{xy}^{w} \\ C_{yx}^{w} \\ C_{yy}^{w} \end{matrix})

where, for example,

C_{xx}^{u}

approximates

\frac{\partial^{2} u}{\partial x^{2}}

at every pixel:

C_{xx}^{u} = \frac{1}{{(normalΔx)}^{2}} ([], \begin{matrix} - 1 & 2 & - 1 & 0 & 0 & . . . & 0 & 0 & 0 & . . . & 0 & 0 & 0 \\ 0 & - 1 & 2 & - 1 & 0 & . . . & 0 & 0 \end{matrix})

…”

Section: Inversionmentioning

confidence: 99%

Estimation of mesoscale thermospheric wind structure using a network of interferometers

2015

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We introduce a technique for estimating the regional thermospheric wind field from measurements made by a network of interferometers. Unlike previous work, this technique does not make assumptions about the functional form of the wind field and instead uses inverse theory to find the smoothest wind field that agrees with the measurements. This technique is general and applies to any network making radial velocity measurements. We show reconstructions of the thermospheric wind field over the eastern United States and over eastern Brazil, using data from two distinct networks of Fabry‐Perot interferometers measuring the Doppler shift of the 630.0 nm airglow emission. In Brazil, we find direct evidence of a convergent wind field during the period of rapid thermospheric temperature increase associated with the equatorial midnight temperature maximum.

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“…The electric fields and auroral precipitation are known to have an inverse relationship at auroral region (Evans et al, 1977), and their self-consistent treatment is crucial to further understand the mesoscale variability in the I-T system. The electric fields and auroral precipitation are known to have an inverse relationship at auroral region (Evans et al, 1977), and their self-consistent treatment is crucial to further understand the mesoscale variability in the I-T system.…”

Section: Sources Of Discrepanciesmentioning

confidence: 99%

“…Line-of-sight measurements from PFISR multibeam experiments are routinely used to construct two-dimensional plasma flow and electric fields (Clayton et al, 2019;Heinselman & Nicolls, 2008;Nicolls et al, 2014). Line-of-sight measurements from PFISR multibeam experiments are routinely used to construct two-dimensional plasma flow and electric fields (Clayton et al, 2019;Heinselman & Nicolls, 2008;Nicolls et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A New Framework to Incorporate High‐Latitude Input for Mesoscale Electrodynamics

et al. 2020

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Global circulation models (GCMs) for the ionosphere-thermosphere system traditionally use empirical models to specify upper boundary conditions to represent solar wind and magnetospheric drivers. However, the magnetosphere, ionosphere, and thermosphere systems are coupled on different spatial and temporal scales. During increased levels of geomagnetic activity, these empirical models can't resolve dynamic electric field variability (<500 km, <15 min) because of their statistical nature and/or low spatial and temporal resolutions. This results in an underestimation of energy input to the ionosphere, causing disagreements between model results and observations. This paper introduces a new framework to incorporate dynamic electric fields into GCMs: High-latitude Input for Mesoscale Electrodynamics (HIME). As a demonstration HIME uses the Poker Flat Incoherent Scatter Radar (PFISR) electric field estimates during an experiment on 2 March 2017. The electric potentials were calculated using the PFISR estimates and merged with a global empirical model of electric potential. A set of high-latitude electric potential drivers were used to drive the University of Michigan Global Ionosphere Thermosphere Model (GITM) to understand the effects of driving at different scales. Data versus model comparisons for ion temperature, electron temperature, and electron density are provided along the PFISR beams. The ion convection velocities and neutral winds at the PFISR location are compared with the PFISR and Scanning Doppler Imager data. The effects of different multiscale drivers are investigated. The results showed that energy deposited by HIME-driven simulations was locally larger by approximately an order of magnitude compared to the empirical model-driven results.

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Estimating the vector electric field using monostatic, multibeam incoherent scatter radar measurements

Cited by 32 publications

References 15 publications

Calculation of meridional neutral winds in the middle latitudes from the Irkutsk incoherent scatter radar

Calculation of meridional neutral winds in the middle latitudes from the Irkutsk incoherent scatter radar

Estimation of mesoscale thermospheric wind structure using a network of interferometers

A New Framework to Incorporate High‐Latitude Input for Mesoscale Electrodynamics

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