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The most dynamic electromagnetic coupling between the magnetosphere and ionosphere occurs in the polar upper atmosphere. It is critical to quantify the electromagnetic energy and momentum input associated with this coupling as its impacts on the ionosphere and thermosphere system are global and major, often leading to considerable disturbances in near‐Earth space environments. The current general circulation models of the upper atmosphere exhibit systematic biases that can be attributed to an inadequate representation of the Joule heating rate resulting from unaccounted stochastic fluctuations of electric fields associated with the magnetosphere‐ionosphere coupling. These biases exist regardless of geomagnetic activity levels. To overcome this limitation, a new multiresolution random field modeling approach is developed, and the efficacy of the approach is demonstrated using Super Dual Auroral Radar Network (SuperDARN) data carefully curated for the study during a largely quiet 4‐hour period on February 29, 2012. Regional small‐scale electrostatic fields sampled at different resolutions from a probabilistic distribution of electric field variability conditioned on actual SuperDARN LOS observations exhibit considerably more localized fine‐scale features in comparison to global large‐scale fields modeled using the SuperDARN Assimilative Mapping procedure. The overall hemispherically integrated Joule heating rate is increased by a factor of about 1.5 due to the effect of random regional small‐scale electric fields, which is close to the lower end of arbitrarily adjusted Joule heating multiplicative factor of 1.5 and 2.5 typically used in upper atmosphere general circulation models. The study represents an important step toward a data‐driven ensemble modeling of magnetosphere‐ionosphere‐atmosphere coupling processes.

 

Polar ionospheric electrodynamics plays an important role in the Sun–Earth connection chain, acting as one of the major driving forces of the upper atmosphere and providing us with a means to probe physical processes in the distant magnetosphere. Accurate specification of the constantly changing conditions of high-latitude ionospheric electrodynamics has long been of paramount interest to the geospace science community. The Assimilative Mapping of Ionospheric Electrodynamics procedure, developed with an emphasis on inverting ground-based magnetometer observations for historical reasons, has long been used in the geospace science community as a way to obtain complete maps of high-latitude ionospheric electrodynamics by overcoming the limitations of a given geospace monitoring system. This Chapter presents recent technical progress on inverse and data assimilation procedures motivated primarily by availability of regular monitoring of high-latitude electrodynamics by space-borne instruments. The method overview describes how electrodynamic state variables are represented with polar-cap spherical harmonics and how coefficients are estimated from the point of view of the Bayesian inferential framework. Some examples of the recent applications to analysis of SuperDARN plasma drift, Iridium, and DMSP magnetic fields, as well as DMSP auroral particle precipitation data are included to demonstrate the method.