Visualization and characterization of 3D structures of GWs produced by different sources using simulated data

Abstract:

GWs can have sufficiently large vertical wavelengths and horizontal phase speeds to significantly affect multiple layers of the atmosphere [e.g., Taylor and Hapgood, PSS, 36(10), 1988; Yue et al., JGR, 114, 2009; Nishioka et al., GRL, 40, 2013]. Simulation studies coupled across different layers help us understand these GWs’ evolutions and accurately interpret the data and identify sources. We present a framework that utilizes modeled data and represents it in 3D space using different visualization techniques to allow for the characterization of different types of GWs (generated by different sources) with respect to their morphology and their temporal evolution. Specifically we make use of 3D isosurfaces, volumetric representations (point clouds) and surface displacement maps. This clear understanding of the 3D structure is additional knowledge to the use of traditional 2D slices which are required for spectral analyses. This is a preliminary study with the expectation that through the visualization of different GW phenomena it is possible to learn new or unexpected dynamics or interactions of the GWs with the different layers of the atmosphere, including reflection, refraction, secondary wave generation, dissipation, etc, as well as simultaneous visualization of the sources such as tsunamis, earthquakes and thunderstorms. For our simulated data we employ the 3D outputs of the compressible atmospheric dynamics model “MAGIC” and the self-consistent multi-fluid ionosphere model “GEMINI” [e.g., Zettergren and Snively, JGR, 120, 2015]. The simulations are constructed with physically-constrained convective sources of GWs and spatial domains are mapped to geodetic longitude, latitude and altitude. Model outputs include emission rates for airglow that also allows us to simulate observable data as measured by different imaging instruments: stratospheric CO₂ radiance (~43 km peak), as measured by the AIRS IR spectrometer onboard the Aqua satellite [Aumann et al., IEEE, 41, 2003]; mesospheric OH(3,1) band emissions (~87 km peak) and O(¹S) (~95 km peak), observed from ground or space airglow imagers as well as the O(¹D) 630 nm (~250 km peak) emission, observed by ground-based all-sky imagers such as MANGO [Bhatt and Kendall, AGU FM, 2017]; and temperature and wind data throughout the entire vertical domain.