From simulated data to AR: 3D visualization techniques for meaningful representation of atmospheric gravity wave data and AR applications

Abstract:

Atmospheric gravity waves (AGWs) are major drivers of the upper atmosphere circulation [e.g., Fritts and Alexander, RG, 41, 2003]. As these AGWs propagate upwards and interact with the background atmosphere their intrinsic parameters change; they can also be reflected or refracted at critical layers or generate new AGWs. Simulation studies coupled across different layers help us understand AGWs’ evolutions and accurately interpret the data and identify sources. We present a framework that utilizes modeled data and real all-sky imager data and represents it in 3D space using different visualization techniques to allow for the characterization of different types of AGWs (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. Additionally we have developed a workflow to represent this data in widely accessible augmented reality (AR) formats such as Apple’s Universal Scene Description mobile format (USDZ) that any Apple device is readily able to visualize. With better visualizations of the 3D morphology of AGWs it is possible to learn new or unexpected dynamics or interactions of the AGWs with the background atmosphere, including reflection, refraction, secondary wave generation, etc., as well as simultaneous visualization of the sources such as tsunamis, earthquakes and thunderstorms. It is our expectation that the AR platform will allow for significant improvements in the communication of science, specifically in our case on the topic of AGWs, their atmospheric impact and Aeronomy techniques in general. AR models can easily be placed in websites, poster presentations, kiosks and diverse print media and help attract, engage and better communicate our scientific results. 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 AGWs and spatial domains are mapped to geodetic longitude, latitude and altitude. Our all-sky imager data is primarily mountain waves, a type of AGWs, from the Andes Lidar Observatory (ALO).