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Nudging high-latitude Weimer potentials toward AMIE by assimilating AMIE-driven TIEGCM density rates

Seebany
Datta-Barua
Illinois Institute of Technology
Abstract text

One of the challenges of ionospheric dynamics is in the specification of the high-latitude electric potential, which governs the large scale electrodynamic energy input. This potential in principle should be consistent with the particle precipitation and closure current systems at the high-latitudes. Separate specification of the potential and particle precipitation, in which they are decoupled and independent, can lead to nonphysical results when used to drive global models such as the thermosphere-ionosphere electrodynamic general circulation model (TIEGCM).
This work investigates how well we can use data assimilation to estimate corrections to the high-latitude potential based on observations of ionospheric density rates. We represent the “true” ionosphere as the TIEGCM model with high-latitude potential specified by assimilative mapping of ionospheric electrodynamics (AMIE). The resulting plasma densities are finite differenced and used in the EMPIRE algorithm (estimating model parameters with ionospheric reverse engineering). EMPIRE forms the ion continuity equation at each gridpoint in the global F region as a system linear in a state of corrections to electric potential and neutral winds. The state consists of coefficients to spherical harmonics for each, the electric potential and neutral winds. The observations are the difference between the density rate “data” and the background model values of production, loss, and convective terms. EMPIRE Kalman filters the difference to estimate adjustments to potential and winds. The background model of neutral densities and winds, and charged and neutral temperatures that contribute to the production, loss and convective terms are derived from a TIEGCM run that uses Weimer as the driving potential. We run the quiet day 26 May 2017 and the following storm day 27 May 2017. In this work, we use EMPIRE to estimate corrections to the Weimer potential and show how much closer to the AMIE potential they are.
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Approved for public release; distribution is unlimited. Public Affairs release approval #AFRL-2025-1670

Authors
Seebany Datta-Barua, Illinois Institute of Technology
Michael David, Utah State University
Russell Landry, Air Force Research Laboratory
Riley Troyer, Utah State University
Vince Eccles, Utah State University
Non-Student
Poster category
DATA - Data Assimilation, Data Analytics, Methods and Management