Conductance Model for Extreme Events: Impact of Auroral Conductance on Space Weather Forecasts. Issue 11 (12th November 2020)

• Record Type: Journal Article
• Authors: Mukhopadhyay, Agnit; Welling, Daniel T.; Liemohn, Michael W.; Ridley, Aaron J.; Chakraborty, Shibaji; Anderson, Brian J.
• Is Part Of: Space weather. Volume 18:Issue 11(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-12
• Subjects: ionospheric conductance; Space environment -- Periodicals; 551.509992
• DOI: 10.1029/2020SW002551
• Languages: English
• ISSNs: 1542-7390

Abstract

Abstract: Ionospheric conductance is a crucial factor in regulating the closure of magnetospheric field‐aligned currents through the ionosphere as Hall and Pedersen currents. Despite its importance in predictive investigations of the magnetosphere‐ionosphere coupling, the estimation of ionospheric conductance in the auroral region is precarious in most global first‐principles‐based models. This impreciseness in estimating the auroral conductance impedes both our understanding and predictive capabilities of the magnetosphere‐ionosphere system during extreme space weather events. In this article, we address this concern, with the development of an advanced Conductance Model for Extreme Events (CMEE) that estimates the auroral conductance from field‐aligned current values. CMEE has been developed using nonlinear regression over a year's worth of 1‐min resolution output from assimilative maps, specifically including times of extreme driving of the solar wind‐magnetosphere‐ionosphere system. The model also includes provisions to enhance the conductance in the aurora using additional adjustments to refine the auroral oval. CMEE has been incorporated within the Ridley Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF) for usage in space weather simulations. This paper compares performance of CMEE against the existing conductance model in RIM, through a validation process for six space weather events. The performance analysis indicates overall improvement in the ionospheric feedback to ground‐based space weather forecasts. Specifically, the model is able to improve the prediction of ionospheric currents, which impact the simulated d B / d t and Δ B, resulting in substantial improvements in d B / d t predictive skill. Plain Language Summary: Electric currents generated in the Earth's space environment due to its magnetic interaction with the Sun leads to charged particle deposition and closure of these currents in the terrestrial upper atmosphere, especially in the high‐latitude auroral region. The enhancement in the electrical charge‐carrying capacity as a result of this process in the Earth's upper atmosphere, also known as the ionosphere, is challenging to estimate in most numerical simulations attempting to study the interactive dynamic and chemical processes in the near‐Earth region. The inability to accurately estimate this quantity leads to underprediction of severe space weather events that can have adverse impacts on man‐made technology like electrical power grids, railway, and oil pipelines. In this study, we present a novel modeling approach to address this problem and provide global simulations with a more accurate estimate on the electrical conductivity of the ionosphere. Through this investigation, we show that the accurate measurement of the charge carriers in the ionosphere using the new model causes substantial improvements in the prediction of space weather on the ground, and significantly advances our understanding of global dynamics causing ground‐based space weather. Key Points: An updated auroral conductance module is built for global models using nonlinear regression and empirical adjustments spanning extreme events Expanded data set raises the ceiling of conductance values, impacting the polar cap potential, d B / d t, and dB predictions during extreme events Application of expanded model with empirical oval adjustments refines the conductance pattern and drastically improves d B / d t predictions