Statistical characteristics of small‐scale spatial and temporal electric field variability in the high‐latitude ionosphere

Cousins, E. D. P.; Shepherd, Simon

doi:10.1029/2011ja017383

Cited by 27 publications

(55 citation statements)

References 42 publications

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“…Data from several studies suggest that turbulent regimes characterize also the electric and geomagnetic field fluctuations on smaller spatial and temporal scales. For example, Cousins and Shepherd () analyzed the statistical characteristics of the electric field fluctuations observed in high‐latitude regions of Earth's ionosphere at small spatial (between 45 km and 450 km) and temporal (between 2 min and 20 min) scales finding that both the probability density function distribution shapes and scale‐size dependencies of the analyzed fluctuations were consistent with the properties which were expected for a turbulent flow. At the same time, Golovchanskaya and Kozelov () demonstrated the scale‐free structure of electric fluctuations on scales in the range 0.5–256 km using data measured by the Dynamics Explorer 2 satellite orbiting at polar latitudes during periods characterized by southward interplanetary magnetic field.…”

Section: Introductionmentioning

confidence: 96%

Scaling Features of High‐Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

et al. 2017

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This paper attempts to explore the statistical scaling features of high‐latitude geomagnetic field fluctuations at Swarm altitude. Data for this study are low‐resolution (1 Hz) magnetic data recorded by the vector field magnetometer on board Swarm A satellite over 1 year (from 15 April 2014 to 15 April 2015). The first‐ and second‐order structure function scaling exponents and the degree of intermittency of the fluctuations of the intensity of the horizontal component of the magnetic field at high northern latitudes have been evaluated for different interplanetary magnetic field orientations in the GSM Y‐Z plane and seasons. In the case of the first‐order structure function scaling exponent, a comparison between the average spatial distributions of the obtained values and the statistical convection patterns obtained using a Super Dual Auroral Radar Network dynamic model (CS10 model) has been also considered. The obtained results support the idea that the knowledge of the scaling features of the geomagnetic field fluctuations can help in the characterization of the different ionospheric turbulence regimes of the medium crossed by Swarm A satellite. This study shows that different turbulent regimes of the geomagnetic field fluctuations exist in the regions characterized by a double‐cell convection pattern and in those regions near the border of the convective structures.

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Section: Introductionmentioning

confidence: 96%

Scaling Features of High‐Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

et al. 2017

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“…The estimator for x is based on Bayesian inference with the assumption of Gaussian processes, equivalent to the one used in optimal interpolation in atmospheric data assimilation [e.g., Lorenc , ] and kriging in spatial statistics [e.g., Cressie , ]. The assumption of Gaussian processes may be justified for our application, as the probability distribution of high‐latitude ionospheric electric fields is close to Gaussian for spatial scales larger than a few hundred kilometers [ Cousins and Shepherd , ]. The vectors x and y are now assumed to be distributed according to the multivariate normal distribution denoted by

scriptℳ scriptN

boldx \sim scriptℳ scriptN [{boldx}_{b}, {boldC}_{b}],

…”

Section: Analysis Methodsmentioning

confidence: 99%

Inverse procedure for high‐latitude ionospheric electrodynamics: Analysis of satellite‐borne magnetometer data

et al. 2015

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This paper presents an analysis of data from the magnetometers on board the Defense Meteorological Satellite Program (DMSP) F-15, F-16, F-17, and F-18 satellites and the Iridium satellite constellation, using an inverse procedure for high-latitude ionospheric electrodynamics, during the period of 29-30 May 2010. The Iridium magnetometer data are made available through the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) program. The method presented here is built upon the assimilative mapping of ionospheric electrodynamics procedure but with a more complete treatment of the prior model uncertainty to facilitate an optimal inference of complete polar maps of electrodynamic variables from irregularly distributed observational data. The procedure can provide an objective measure of uncertainty associated with the analysis. The cross-validation analysis, in which the DMSP data are used as independent validation data sets, suggests that the procedure yields the spatial prediction of DMSP perturbation magnetic fields from AMPERE data alone with a median discrepancy of 30-50 nT. Discrepancies larger than 100 nT are seen in about 20% of total samples, whose location and magnitude are generally consistent with the previously identified discrepancy between DMSP and AMPERE data sets. Resulting field-aligned current (FAC) patterns exhibit more distinct spatial patterns without spurious high-frequency oscillatory features in comparison to the FAC products provided by AMPERE. Maps of the toroidal magnetic potential and FAC estimated from both AMPERE and DMSP data under four distinctive interplanetary magnetic field (IMF) conditions during a magnetic cloud event demonstrate the IMF control of high-latitude electrodynamics and the opportunity for future scientific investigation.

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“…Richmond (2010) argued that energy dissipated through large-scale structures (>15 min and >1,000 km) do not make a large contribution as smaller-scale structures do over a localized region. The temporal and spatial distributions 10.1029/2019JA027562 of the electric field fluctuations at the ionosphere were studied extensively by Cousins and Shepherd (2012), using Super Dual Auroral Radar Network (SuperDARN) radars. The temporal and spatial distributions 10.1029/2019JA027562 of the electric field fluctuations at the ionosphere were studied extensively by Cousins and Shepherd (2012), using Super Dual Auroral Radar Network (SuperDARN) radars.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, they have discussed the effects of spatial variability on temporal fluctuations and estimated the range for temporal variability to be between 10 and 16 min for the nightside, high-latitude ionosphere. In this paper, we define mesoscale electric field variability as between 100 and 500 km spatially following the definition in Zhu et al (2019) and between 2 and 15 min temporally based on the Forsyth et al (2017) study for the lower limit and Cousins and Shepherd (2012) for the upper limit. In general, spatiotemporal properties of high-latitude drivers are categorized through field-aligned current (FAC) systems; however, there is no widely accepted categorization for electric field properties.…”

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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Statistical characteristics of small‐scale spatial and temporal electric field variability in the high‐latitude ionosphere

Cited by 27 publications

References 42 publications

Scaling Features of High‐Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

Scaling Features of High‐Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

Inverse procedure for high‐latitude ionospheric electrodynamics: Analysis of satellite‐borne magnetometer data

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

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