Predicting wind extremes in a warming climate: from general circulation to storm-resolving models via improved turbulence representation

ABSTRACT
A wave of unprecedented extreme weather events, breaking records worldwide, has raised urgent questions about the ability of current weather and climate models to anticipate the emerging impacts of climate change on human life and infrastructure. Among these, extreme wind speeds and gusts, often associated with midlatitude cyclones and low-level jets, pose a growing threat to critical sectors of society. In this talk, I will first present projections of near-surface extreme winds over the midlatitudes of both hemispheres under an idealized warming scenario, based on CMIP-class models. I will then illustrate how global kilometer-scale simulations may provide new insight into how the structure and intensity of North Atlantic midlatitude cyclones respond to climate warming. Finally, I will discuss results from a set of experiments with the GFDL-AM4 model that  incorporate improved turbulence representation via the CLUBB scheme. These highlight the role of prognosed momentum fluxes in better  capturing low-level jet dynamics and improving the simulation of the diurnal precipitation cycle. Together, these studies demonstrate the importance of refined physics and high-resolution modelling for advancing our understanding and prediction of wind extremes in a warming climate.

BIO
Emanuele Silvio Gentile is an atmospheric physicist and climate modeler, with a background in theoretical physics. His research combines
kilometre-scale climate models, higher-order turbulence physics, and emerging AI and machine learning tools to investigate how moist convection and sub-grid turbulent processes shape near-surface extremes, and how mesoscale weather responds to climate change. He studies the Earth's climate as an interconnected system, linking atmospheric dynamics with land, ocean, and wave interactions.

He is currently a Research Scientist at NCAS and the University of Reading, working within the CANARI project to run very high-resolution
simulations that assess how climate change is altering heavy precipitation, inland flooding, and extreme winds across the UK and North Atlantic. Previously, Emanuele worked at NOAA's Geophysical Fluid Dynamics Laboratory and Princeton University, where he collaborated with Ming Zhao and Leo Donner to advance the representation of boundary-layer turbulence, convection, and clouds in GFDL's AM4 model. He holds a PhD in Atmosphere, Ocean, and Climate from the University of Reading and a First-Class Honours degree in Theoretical Physics from Imperial College London, where he received the Tessella Prize for innovative use of computational techniques in physics. He is original from Bologna where
he was born and raised.

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