Importance of Regional‐Scale Auroral Precipitation and Electrical Field Variability to the Storm‐Time Thermospheric Temperature Enhancement and Inversion Layer (TTEIL) in the Antarctic E Region

Abstract

AbstractA dramatic thermospheric temperature enhancement and inversion layer (TTEIL) was observed by the Fe Boltzmann lidar at McMurdo, Antarctica during a geomagnetic storm (Chu et al. 2011, https://doi.org/10.1029/2011GL050016). The Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM) driven by empirical auroral precipitation and background electric fields cannot adequately reproduce the TTEIL. We incorporate the Defense Meteorological Satellite Program (DMSP)/Special Sensor Ultraviolet Spectrographic Imager (SSUSI) auroral precipitation maps, which capture the regional‐scale features into TIEGCM and add subgrid electric field variability in the regions with strong auroral activity. These modifications enable the simulation of neutral temperatures closer to lidar observations and neutral densities closer to GRACE satellite observations (~475 km). The regional scale auroral precipitation and electric field variabilities are both needed to generate strong Joule heating that peaks around 120 km. The resulting temperature increase leads to the change of pressure gradients, thus inducing a horizontal divergence of air flow and large upward winds that increase with altitude. Associated with the upwelling wind is the adiabatic cooling gradually increasing with altitude and peaking at ~200 km. The intense Joule heating around 120 km and strong cooling above result in differential heating that produces a sharp TTEIL. However, vertical heat advection broadens the TTEIL and raises the temperature peak from ~120 to ~150 km, causing simulations deviating from observations. Strong local Joule heating also excites traveling atmospheric disturbances that carry the TTEIL signatures to other regions. Our study suggests the importance of including fine‐structure auroral precipitation and subgrid electric field variability in the modeling of storm‐time ionosphere‐thermosphere responses.