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Speaker: Jingxuan Wei, Postdoctoral Fellow, University of Texas Institute for Geophysics

Host: Sean Gulick

Title: Acoustically Mapping the Ocean: The Progress and Prospects of Seismic Oceanography

Abstract: Exploring and characterizing the ocean are crucial for understanding its conditions and addressing on-going challenges like climate change. Yet, our understanding of the ocean is limited by existing data sampling capabilities. There remains a considerable observational gap, specifically in the submesoscale (1-10 km) to mesoscale (10-100 km) range where energy transfer occurs through vertical mixing that drives the exchange of heat, nutrients, and organic matters. These limitations in observations leave uncertainties in how best to represent ocean circulation in computer simulations, contributing to the large spread in climate model projections.

Seismic Oceanography (SO) is an emerging acoustic technique adapted from reflection seismology that offers a solution to several observational limitations. The unique combination of extensive coverage and high spatial resolution making SO an ideal tool to characterize a wide range of oceanic processes from basin-scale currents to turbulent flows. The greatest strength of SO is the synergy of mapping thermohaline structures and calculating distributions of oceanographic properties, such as temperature, salinity, current speed, and diapycnal diffusivity (turbulent mixing).

However, since its first application in 2003, SO has not yet becoming a widely accepted tool. In this talk, I will introduce its potential, challenges, ongoing development and discuss future possibilities. First, I will demonstrate the capabilities of SO by presenting a case study in the South Atlantic where seismic data reveals enhanced turbulent mixing caused by storm and topography. In the second part, I will focus on my recent work on standardizing SO to accurately derive turbulent mixing rates. Finally, through my recent proposal, I will discuss future efforts to be taken to promote SO for wider application and unlock the immense potential of existing seismic dataset for better ocean characterization.