Abstract We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020,https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020,https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993,https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML‐AIM, the Weimer (2005,https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005,https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times. 
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                            Red Line Diffuse‐Like Aurora Driven by Time Domain Structures Associated With Braking Magnetotail Flow Bursts
                        
                    
    
            Abstract Magnetotail earthward‐propagating fast plasma flows provide important pathways for magnetosphere‐ionosphere coupling. This study reexamines a flow‐related red‐line diffuse‐like aurora event previously reported by Liang et al. (2011,https://doi.org/10.1029/2010ja015867), utilizing THEMIS and ground‐based auroral observations from Poker Flat. We find that time domain structures (TDSs) within the flow bursts efficiently drive electron precipitation below a few keV, aligning with predominantly red‐line auroral intensifications in this non‐substorm event. The diffuse‐like auroras sometimes coexisted with or potentially evolved from discrete forms. We forward model red‐line diffuse auroras due to TDS‐driven precipitation, employing the time‐dependent TREx‐ATM auroral transport code. The good correlation (∼0.77) between our modeled and observed red line emissions underscores that TDSs are a primary driver of the red‐line diffuse‐like auroras, though whistler‐mode wave contributions are needed to fully explain the most intense red‐line emissions. 
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                            - Award ID(s):
- 2247034
- PAR ID:
- 10508852
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 51
- Issue:
- 10
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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