Emanuele Silvio Gentile, Dr

I am an atmospheric physicist and climate modeler with a foundation in theoretical physics, working at the interface of storm-resolving climate modelling, turbulence physics, and climate-risk science. My research combines km-scale climate models, large-ensemble simulations, and higher-order boundary-layer turbulence representations to quantify how moist convection and sub-grid processes control near-surface extremes and scale up to influence large-scale circulation, including midlatitude storm tracks, under climate change. I also apply targeted AI and ML approaches, including AI-based precipitation analysis and validation of AI weather models (e.g. GraphCast) and have expertise in running **large-eddy simulations (LES) on GPU architectures to study turbulent processes and support scalable uncertainty analysis, including regional very high-resolution ML models. Overall, my research treats Earth’s climate as an interconnected dynamical system, investigating how atmospheric circulation, land–atmosphere coupling, and ocean–wave interactions shape hazards, exposure-relevant extremes, and systemic climate risk,

Recently, my research focus has also expanded to incorporate risk and uncertainty quantification bridging weather and climate expertise to the insurance and financial sector. I use large climate ensembles, probabilistic and tail-based diagnostics, and distribution-focused metrics to characterise event likelihood, extreme-value behaviour, and uncertainty in hazard projections, with a view toward loss-relevant modelling for wind, precipitation, and compound events. This work aims to translate physically interpretable climate signals into decision-relevant risk information for the insurance, reinsurance, and financial sectors.

I am an atmospheric physicist and climate modeler with a background in theoretical physics. I combine km-scale climate models, higher-order turbulence physics, and emerging AI and ML to inves tools to investigate how moist convection and sub-grid turbulent processes shape near-surface extremes and how mesoscale weather responds to climate change. I am also an active member of the Climate and Finance cluster, contributing to efforts that bridge physical climate science, uncertainty quantification, and climate-risk assessment.

I am currently working as a Research Scientist at NCAS and University of Reading within the CANARI project, running very high resolution simulations to assess how climate change is altering heavy precipitation, inland flooding, and extreme winds across the UK and North Atlantic region.

Previously, I worked for nearly three years at GFDL/NOAA and Princeton University as a Postdoctoral Research Associate, with Dr Ming Zhao and Dr Leo Donner, to unify the treatment of boundary-layer turbulence, moist convection, and clouds implementing the higher-order turbulence scheme Cloud Layers Unified By Binormals within the world-class GFDL atmospheric climate model AM4, in close collaboration with Prof Vince Larson, Dr Julio Bacmeister, Prof Gunilla Svensson, and Prof Colin Zarzycki.

I began my academic career with a First-Class Honours in Theoretical Physics from Imperial College London, where I was awarded the Tessella Prize for the innovative application of computational methods in physics. My PhD in Atmosphere, Ocean, and Climate at the University of Reading, under Prof. Suzanne Gray and Dr. Huw Lewis, examined turbulent air-sea fluxes and their influence on midlatitude cyclones’ extreme winds.

In my leisure time, I enjoy playing volleyball and tennis, indulging in music ensembles while playing the piano, reading books, preparing delicious meals for my friends, and venturing into nature through hikes. Additionally, I love exploring new countries and their cultures.