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Geospace coupling involves mass, momentum and energy transport across regions and scales, and thus it inherently poses cross‐regional and multiscale nature. Global processes have been relatively well understood thanks to a large amount of data accumulated over decades, a growing observation network, global simulations, and data science approaches. During geomagnetic storms, solar wind energy reaching the magnetosphere is some tens of TW, and ~1% of solar wind energy is supplied to the magnetosphere‐ionosphere (M‐I) system (Feldstein et al., 2003). Of the energy reaching the M‐I system, ~50% is supplied to the ionosphere as Poynting flux or field‐aligned currents (FACs) and dissipates as Joule heating. Precipitation into the atmosphere carries ~25% of energy. The rest (~25%) goes into the ring current, primarily in a form of bursty injections from the magnetotail rather than slow convection. Similar energy partition is seen during substorms even with weaker solar‐wind energy input (Ostgaard et al., 2002a, 2002b). These numbers emphasize the importance of ionosphere processes for energy dissipation processes.

Owing to accumulation of large database and data science, such large‐scale energetics in the high‐latitude ionosphere can be specified nearly routinely. For example, data assimilation incorporating SuperDARN, AMPERE, and a statistical precipitation model specifies global convection, FAC, Poynting flux, and conductance distributions (e.g., Cousins et al., 2015). However, as Figure 3.1a shows, statistical averaging of precipitation only provides a smooth large‐scale (> ~1,000 km horizontal) oval structure, which is vastly different from actual structured and dynamically varying aurora. The energy flux distribution reconstructed from the THEMIS all‐sky imager (ASI) network (Fig. 3.1b) depicts a number of mesoscale (tens to hundreds km horizontal) precipitation structures during a substorm (see section 3.4). Narrow field‐of‐view (FOV) imaging has even resolved small‐scale (< ~10 km horizontal) intense precipitation structures and conductance gradients (Fig. 3.1c). While it is difficult to measure kinetic scale structures (< ~1 m), recent PIC simulations have predicted the existence of meter‐scale turbulent density structures created by Farley‐Buneman instability (Oppenheim & Dimant, 2013). The process is nonlinear and there are net changes in conductance due to the density structures. The instability also increases temperature over the scale size of flows (Schlegel & St. Maurice, 1981). The mesoscale, small‐scale, and kinetic‐scale structures can have comparable or larger magnitudes than those at larger scales, and thus those potentially affect larger‐scale dynamics. While studies on how global processes are affected by small‐scale processes are limited, Wiltberger et al. (2017) incorporated the kinetic turbulence conductance formulated by Oppenheim and Dimant (2013) into the coupled MHD simulation and evaluated effects of kinetic turbulence. They showed that the inclusion of kinetic turbulence processes led to a conductance increase by 20% and a better agreement with measured D_st. The cross‐polar‐cap potential decreased by 13%, and this may substantially improve estimation of cross‐polar‐cap potential, which tends to be overestimated in MHD simulations. Thus, the multiscale processes may play a substantial role in understanding ionosphere processes.

Figure 3.1 Illustration of multiscale processes: (a) Large‐scale statistical precipitating electron energy flux distribution from OVATION‐SM ; (b) instantaneous precipitating electron energy flux distribution in the nightside using THEMIS ASIs (this study); (c) instantaneous small‐scale Pedersen conductance distribution derived from narrow FOV imaging; (d) kinetic simulation of ionosphere density; (e,f) global Pedersen conductance in coupled MHD simulations without and with kinetic turbulence conductance

(a: Mitchell et al., 2013; c: Grubbs et al., 2018; d: Oppenheim & Dimant, 2013; e,f: Wiltberger et al., 2017; Mitchell et al. (2013). Reproduced with permission of John Wiley & Sons).

Also important in the geospace system are coupling processes to adjacent regions. In addition to large‐scale transport processes, mesoscale/small‐scale processes can also propagate over long distances and substantially contribute to processes in surrounding regions. Representative features are schematically illustrated in Figure 3.2 and described in later sections. For example, plasma redistribution occurs due to plasma transport from dayside to nightside as polar cap patches and tongues of ionization (TOIs) leading to changes in plasma density structures in surrounding regions. Mesoscale structures such as flow channels play a substantial role in plasma transport, and can also affect energetics in downstream regions.

Figure 3.2 Schematic illustration of various types of high‐latitude mesoscale ionospheric processes. (a) Weak‐moderate and (b) active geomagnetic conditions. The electron auroral oval is marked by the two black circles. The colors indicate the dominant wavelength of optical emission. The colored lines and filled circles indicate arcs and patches of optical emission. The dashed lines and arrows into/out of the plane indicate plasma flows and FACs.

In the following sections, we review properties of mesoscale and small‐scale features and processes in key regions of the high‐latitude ionosphere.