Mesoscale and large‐scale variability in high‐latitude ionospheric convection: Dominant modes and spatial/temporal coherence

Abstract

[1] Empirical orthogonal function (EOF) analysis, a variant of principle component analysis, is applied to 20 months of plasma drift data from the Super Dual Auroral Radar Network radars in the high-latitude region of the Northern Hemisphere. Dominant modes of ionospheric electric field variability are identified and the spatial and temporal coherence of this variability is quantified. The first three modes of variability, which, together with the mean, account for 50% of the observed squared electric field (E 2 ), are characterized by global spatial scales and long time scales ( 1 h). The first and second modes of variability represent the strengthening/weakening of the global convection pattern and the shaping of the convection pattern into asymmetrical round-and crescent-shaped cells. These two modes are correlated with the B z and B y components of the interplanetary magnetic field. The third mode represents the expansion/contraction of the convection pattern and is weakly correlated with the solar wind velocity. For EOFs beyond EOF 3, the power contained in the modes falls off rapidly, the characteristic spatial and temporal scales decrease, and weak correlations with external driving parameters are observed. These higher-order EOFs likely capture more random behavior of the electric field variability. The notable exception to this trend is EOF 11, which captures midlatitude variations on the duskside and is enhanced during subauroral polarization stream events. The EOF technique described in this paper is applied in a companion paper to characterize the covariance of ionospheric electric fields for use in an assimilative mapping procedure.

Modes of high‐latitude auroral conductance variability derived from DMSP energetic electron precipitation observations: Empirical orthogonal function analysis

“…EOFs of the Hall and Pedersen conductances, herein represented using the polar cap spherical harmonics basis, are obtained by a sequential nonlinear regression analysis of observations along DMSP satellite trajectories and ordered by their variance. These EOFs and their amplitudes can be used to describe the spatial and temporal coherence of the Pedersen and Hall conductances in a manner similar to that reported by Matsuo et al [, ] and Cousins et al [, ] for electric field variability and Cousins et al [, ] for field‐aligned current variability. Our results allow for improved modeling of the background error covariance needed for ionospheric assimilative procedures [ Richmond and Kamide , ; Matsuo et al , ].…”

“…Some aspects of the correlations are noteworthy: Since indices represent imperfect proxies for ionospheric phenomena, which themselves often respond in a nonlinear manner to many different drivers, we are encouraged by the fact that several of the correlation coefficients between the indices and higher‐order EOFs are greater than 0.5. The more localized the EOF features, the less likely they are to be correlated with the parameters. This is why correlations generally decrease for higher‐order EOFs [ Matsuo et al , ; Cousins et al , ]. Thus, low correlations do not necessarily mean a relationship does not exist.…”

Mapping high‐latitude ionospheric electrodynamics with SuperDARN and AMPERE

“…The assimilative approach taken in this study provides a framework for optimally combining the different observations, as well as background statistical models, taking into account the error properties of the various sources of information. In particular, the procedure developed in this study incorporates statistical error properties obtained through empirical orthogonal function (EOF) analysis of both SuperDARN data (described by Cousins et al []) and of AMPERE data (described in the companion paper Cousins et al [], referred to hereafter as Paper 1).…”

Temporal Characteristic of the Mesoscale Plasma Flow Perturbations in the High‐Latitude Ionosphere

“…However, more than 50% of the observations are in the dayside where we see only a weak dependency on AE and no dependency on IMF B z . The work by Cousins et al () also found a weak correlation with AE index and almost no correlation with IMF B z for smaller spatial (<1,000 km) and shorter temporal scale (a few tenth minutes) variability in the electric field.…”