Dr. Raza Sufian Understanding air-sea interactions during tropical cyclones using passive acoustic monitoring | New Mexico State University - BE BOLD. Shape the Future. Skip to main content

Thursday, March 12, 2026

4:00 pm-5:00 pm

Understanding air-sea interactions during tropical cyclones using passive acoustic monitoring

 Air-sea interaction processes define many prominent features of the acoustic ambient noise spectrum in the ocean (Wenz, 1962). Therefore, underwater acoustic field measurements have demonstrated a substantial potential in monitoring wind speed over the ocean. Shaw et al. (1978) pioneered the field by establishing a linear relationship between the underwater sound pressure levels and the logarithm of low to moderate local wind speeds. Later, Wilson and Makris (2006) further advanced the theory by proposing a parameterized acoustic notional surface source model specifically designed to estimate high wind speeds during tropical cyclones. However, even in the Gulf of Mexico region, that is heavily impacted by hurricanes, acoustic data input is not routinely used to track cyclones’ wind speeds. The talk will discuss several approaches to the analysis of the acoustic data collected by the bottom-anchored passive acoustic monitoring system during storm Barry (2019) in the Gulf of Mexico to estimate local wind speeds. The estimated wind speeds are compared to the high-resolution ones generated by the Weather Research and Forecast model. Recently, underwater gliders equipped with passive acoustic systems in addition to traditional set of environmental sensors have been emerging as a new tool for understanding the marine conditions that influence the onset and amplification of tropical cyclones. In this context acoustic data could aid in refining wind strength forecasting, thereby aiding in high spatial resolution wind mapping during hurricanes. Fully autonomous glider’s reconnaissance may also offer a new type of field data (acoustic) to integrate into the operational weather forecasting models used by NOAA and U.S. NAVY for more reliable cyclone strength prediction. [Research supported by the Office of the Under Secretary of Defense for Research and Engineering, award# FA9550-21-1-0215]