Modeling Substorm Effects on the Upper Atmosphere Using High-cadence Forcing from Ground-based Observations
Abstract
General circulation models (GCMs) usually use empirical models to specify the high-latitude ion convection and particle precipitation when simulating magnetic storm events. The same approach is applied for substorm simulations (e.g., Liu et al., 2015; Sheng et al., 2017). However, most empirical models are constructed to describe the large-scale variability of high-latitude geomagnetic forcing during storms, and it can be questionable to directly use them in substorm simulations. Although efforts have been made to include a substorm component to existing empirical models (e.g., Weimer, 2001) or develop empirical models specifically for substorms (e.g., Wing et al., 2013), it is not sure how well they represent the multi-scale and transient substorm-time electrodynamic forcing and the response of the IT system during substorms still needs to be examined systematically. Recent advancements in observational and analysis techniques make it possible to generate high-resolution and high-cadence convection maps based on SuperDARN line-of-sight velocity observations (Bristow et al., 2016, 2022) and highresolution nighttime electron precipitation maps based on all-sky imager (ASI) measurements (Nishimura et al., 2021). Both techniques could extend the coverage of the multi-scale forcing to most North American longitudes if weather and technical conditions allow. With the availability of these multi-scale electrodynamic forcing derived from high-resolution observations, it is now timely to investigate the upper atmospheric response to the highly dynamic substorm-time geomagnetic forcing. We propose to implement the high-resolution observations of electrodynamic forcing in the global ionosphere-thermosphere model (GITM) and simulate selected substorm events. Specifically, we will address the following science questions (SQs).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2024
- Source ID
- FA95502310634
Entities
People
- Sheng Cheng
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Texas at Arlington