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In this study, a new high-latitude empirical model is introduced, named for Auroral energy Spectrum and High-Latitude Electric field variabilitY (ASHLEY). This model improves specifications of soft electron precipitations and electric field variability that are not well represented in existing high-latitude empirical models. ASHLEY consists of three components, ASHLEY-A, ASHLEY-E, and ASHLEY- Evar, which are developed based on the electron precipitation and bulk ion drift measurements from the Defense Meteorological Satellite Program (DMSP) satellites during the most recent solar cycle. On the one hand, unlike most existing high-latitude electron precipitation models, which have assumptions about the energy spectrum of incident electrons, the electron precipitation component of ASHLEY, ASHLEY-A, provides the differential energy fluxes in the 19 DMSP energy channels under different geophysical conditions without making any assumptions about the energy spectrum. It has been found that the relaxation of spectral assumptions significantly improves soft electron precipitation specifications with respect to a Maxwellian spectrum (up to several orders of magnitude). On the other hand, ASHLEY provides consistent mean electric field and electric field variability under different geophysical conditions by ASHLEY-E and ASHLEY-Evar components, respectively. This is different from most existing electric field models which only focus on the large-scale mean electric field and ignore the electric field variability. Furthermore, the consistency between the electric field and electron precipitation is better taken into account in ASHLEY [ABSTRACT FROM AUTHOR]

A 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. [ABSTRACT FROM AUTHOR]

We have developed a method for reprocessing the multi-decadal, multi-spacecraft Defense Meteorological Satellite Program Magnetometer (DMSP SSM) dataset and have applied it to fifteen spacecraft-years of data (DMSP Flight 16-18, 2010-2014). This Level-2 dataset improves on other available SSM datasets with recalculated spacecraft locations and magnetic perturbations, artifact signal removal, representations of the observations in geomagnetic coordinates, and in-situ auroral boundaries. Spacecraft locations have been recalculated using ground-tracking information. Magnetic perturbations (measured field minus modeled main-field) are recomputed. The updated locations ensure the appropriate model field is used. We characterize and remove a slow-varying signal in the magnetic field measurements. This signal is a combination of ring current and measurement artifacts. A final artifact remains after processing: step-discontinuities in the baseline caused by activation/deactivation of spacecraft electronics. Using coincident data from the DMSP precipitating electrons and ions instrument (SSJ4/5), we detect the in-situ auroral boundaries with an improvement to the Redmon et al. [2010] algorithm. We embed the location of the aurora and an accompanying figure of merit in the Level-2 SSM data product. Finally, we demonstrate the potential of this new dataset by estimating field-aligned current (FAC) density using the Minimum Variance Analysis (MVA) technique. The FAC estimates are then expressed in dynamic auroral boundary coordinates using the SSJ-derived boundaries, demonstrating a dawn-dusk asymmetry in average FAC location relative to the equatorward edge of the aurora. The new SSM dataset is now available in several public repositories.