Speaker: Dr. Aditi Sheshadri from Stanford University

Title: Towards an improved understanding and representation of atmospheric gravity waves

Abstract: Atmospheric gravity waves (GWs) are ubiquitously excited on the Earth and are critical drivers of the atmospheric circulation, however, they present a challenge to climate prediction: waves on scales of 10²-10⁵m can neither be systematically measured with conventional observational systems, nor properly resolved in atmospheric models. I will describe recent work in my group aimed at understanding the effects of gravity waves on climate variability and improving their representation in GCMs. a) We have leveraged high-resolution data from balloon flights launched by Loon LLC, originally deployed for internet access. The opportunistic Loon dataset, though not from a scientific campaign, gives us access to thousands of balloon flights with measurements of position, pressure, and temperature from which we have inferred statistics of gravity wave motions in the lower stratosphere. b) We have developed a machine learning GW parameterization, coupled it to a global climate model, showed that it is stable and accurate when run online, and that it reproduces features of the climate that depend critically on GWs. c) I will describe recent results with regard to systematic calibration and uncertainty quantification of a popular gravity wave parameterization.