Modelling sporadic E (Es) layers in WACCM-X: Presenting a new methodology for the identification of Es layers, and the resulting climatology

Sporadic E (Es) layers are transient ionospheric phenomena that represent an important aspect of atmospheric dynamics, exerting influences on space weather and communication systems. They occur in the E region (~90-150 km) and are characterised by thin, localised layers of enhanced electron density. Their formation is linked to interactions involving atmospheric waves and tides, wind shear and/or electric field and plasma instabilities. Metal ions are tightly coupled with electrons through ionization and neutralisation processes and play a central role in the formation of Es layers1. Recently, Wu et al. [2021]2 examined the full transport of three metal ions (Fe+, Mg+ and Na+) in the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) - a self-consistent global model including their full neutral and ion-molecule chemistry and the injection of metals from meteoric ablation3,4. The work of Wu et al. [2021] significantly improved the modelled global distribution and seasonal dependence of the metal ions in WACCM-X; since it captures the complex interactions between numerous atmospheric components, this extended WACCM-X provides a useful framework for the study of Es layers on a global scale. Although modelling of parameters relevant to Es layers (winds, temperatures, chemical constituents) has been carried out using whole atmosphere models2,5, modelling of Es layer occurrence has not been carried out self-consistently using a global climate model with metal ion transport. In this study we present a novel method to identify Es layers in WACCM-X with full transport of metal ions. We present a detailed account of the methodology employed for the identification of Es layers within WACCM-X and the resulting climatology of Es occurrence. The derived climatology is compared to observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellite6, which provides global high-resolution ionospheric observations. This comparison enables us to evaluate the performance of the model and identifies potential areas for future development. By better understanding the complex interplay between atmospheric variability and Es layer behaviour, we aim to improve our understanding of Es layers and their role in atmospheric dynamics. The insights gained from this research advance modelling capabilities, and could support space weather forecasting and communication systems, as well as contributing to the broader understanding of Es layers and their significance in atmospheric science.   1. Yu, B., et al. (2021) Atmospheric Chemistry and Physics, 21(5), 4219-4230 2. Wu, J., W. Feng, H. L. i. Liu, X. Xue, D. R. Marsh, and J. M. C. Plane (2021), Atmospheric Chemistry and Physics, 21(20), 15619-15630 3. Liu, H.-L., et al. (2018), Journal of Advances in Modelling Earth Systems, 10(2), 381-402 4. Carrillo-Sánchez, J. D., J. C. Gómez-Martín, D. L. Bones, D. Nesvorný, P. Pokorný, M. Benna, G. J. Flynn, and J. M. C. Plane (2020), Icarus, 335, 113395 5. Chu, Y. H., C. Y. Wang, K. H. Wu, K. T. Chen, K. J. Tzeng, C. L. Su, W. Feng, and J. M. C. Plane (2014), Journal of Geophysical Research: Space Physics, 119(3), 2117-2136 6. https://www.cosmic.ucar.edu/global-navigation-satellite-system-gnss-background/cosmic-