Motivated by the need to better understand and predict exchange processes between the land surface and the atmosphere and their impact on weather and climate, the past decades have seen substantial efforts devoted to studying atmospheric turbulence within and above natural and built environments.
The current understanding of such a flow phenomenon is largely rooted in studies of equilibrium boundary layers over and within idealized rough surfaces. Yet, the real world is characterized by flow unsteadiness, three-dimensionality in mean flow, and intricate surface morphologies that defy precise measurement. Under these conditions, the airflow may experience departures from equilibrium with the underlying surface stress, misalignment of shear and strain rates, persistent large-scale secondary circulations, and model predictions may feature a high degree of uncertainty.
Marco Giometto,
Columbia University
Fundamental questions remain unanswered regarding structural changes of atmospheric turbulence under such realistic scenarios, challenging our ability to comprehend and predict land- atmosphere interaction across a spectrum of practical situations.
In this talk, I will highlight recent efforts in my group devoted to addressing these knowledge gaps and discuss some promising avenues for related research.
Dr. Giometto is an assistant professor in the civil engineering and engineering mechanics department at Columbia University and an Amazon Visiting Academic. He studies both fundamental and applied problems related to fluid dynamics and turbulence, with an emphasis on atmospheric boundary layer processes.
He received his Ph.D. in Mechanical Engineering from École Polytechnique Fédérale de Lausanne and held postdoctoral positions at the University of British Columbia and at the Center for Turbulence Research at Stanford University. He is the recipient of several awards, including a CAREER award from the NSF, an Early Career Program Award from the Army Research Office, and a Young Investigator Award from the Office of Naval Research.