Investigating Stormtime Variability of Exospheric Hydrogen with WACCM-X & Lyao_rt

A major geomagnetic storm occurred on 6-7 April 2000, reaching a minimum Dst value of -288 nT, the second lowest recorded value of that year. The main phase of the storm took place between 18 UT on 6 April and 01 UT on 7 April. Previous studies revealed evidence for stormtime exospheric hydrogen density variability (e.g. Zoennchen et al., 2017; Cucho-Padin & Waldrop, 2019) and, more recently, a modeling study aimed to decipher the same stormtime behavior by comparing results from the Model for Analyzing Terrestrial Exosphere with TWINS spacecraft Lyman-α observations (Connor et al., 2024). In this study, we use WACCM-X simulations of the April 2000 stormtime conditions to characterize the distribution of exospheric hydrogen density and temperature. We then apply the radiative transfer code lyao_rt (Bishop, 1999) to forward model the expected Balmer-α (Hα) emission, allowing us to investigate how exospheric hydrogen abundance varies before, during, and after the storm. This storm in particular was chosen because there exists near-simultaneous ground-based Fabry-Perot interferometer (FPI) observations of geocoronal Hα from Pine Bluff Observatory (PBO) in Wisconsin. These observations were obtained on 5-6 April 2000 with a maximum F10.7 and Ap index of 195 and 82, respectively, at the PBO geographic location. Although the observational coverage is limited, we compare the forward modeled Hα column emission intensities with the near-simultaneous PBO FPI observations of geocoronal Hα. WACCM-X hydrogen density and temperature maps are also presented. Furthermore, we include a sensitivity study that explores the effects of time-dependent asymmetry of hydrogen density using the same conditions for the April 2000 geomagnetic storm. This is conducted through a sequence of lyao_rt simulations that each assume spherical symmetry but evolve hydrogen density through time, where the resulting Hα intensities are then interpreted in an averaged sense. With this, we hope to uncover aspects of the net variability in global hydrogen abundance while avoiding the computational complexity of fully asymmetric radiative transfer.