Modeling Kelvin Helmholtz Instability Tube and Knot Dynamics and Their Impact on Mixing in the Lower Thermosphere

We present modeling results of tube and knot (T&K) dynamics accompanying thermospheric Kelvin Helmholtz Instabilities (KHI) in an event captured by the 2018 Super Soaker campaign (R. L. Mesquita et al., 2020, https://doi.org/10.1029/2020JA027972 ). Chemical tracers released by a rocketsonde on 26 January 2018 showed coherent KHI in the lower thermosphere that rapidly deteriorated within 45–90 s. Using wind and temperature data from the event, we conducted high resolution direct numerical simulations (DNS) employing both wide and narrow spanwise domains to facilitate (wide domain case) and prohibit (narrow domain case) the axial deformation of KH billows that allows tubes and knots to form. KHI T&K dynamics are shown to produce accelerated instability evolution consistent with the observations, achieving peak dissipation rates nearly two times larger and 1.8 buoyancy periods faster than axially uniform KHI generated by the same initial conditions. Rapidly evolving twist waves are revealed to drive the transition to turbulence; their evolution precludes the formation of secondary convective instabilities and secondary KHI seen to dominate the turbulence evolution in artificially constrained laboratory and simulation environments. T&K dynamics extract more kinetic energy from the background environment and yield greater irreversible energy exchange and entropy production, yet they do so with weaker mixing efficiency due to greater energy dissipation. The results suggest that enhanced mixing from thermospheric KHI T&K events could account for the discrepancy between modeled and observed mixing in the lower thermosphere (Garcia et al., 2014, https://doi.org/10.1002/2013JD021208 ; Liu, 2021, https://doi.org/10.1029/2020GL091474 ) and merits further study. Atmospheric turbulence is challenging to observe and model, but its understanding is pivotal to developing better long‐term climate prediction capabilities into general circulation models (GCMs). Turbulence occurs when coherent structures break down into smaller structures that mix with the surrounding air. This mixing behavior determines how energy and momentum are distributed when the large structure breaks down. Because mixing occurs at small scales, GCMs use parameterizations to estimate unresolved mixing without using more resources. This study simulates a representative turbulence event in the thermosphere to learn how to improve mixing parameterizations in GCMs. Regions of strong wind shear generate char