Bernat Jiménez Esteve

I am an atmospheric scientist working at the intersection of atmospheric dynamics, climate variability, numerical modelling, and artificial intelligence for weather and climate research. Since July 2026, I have been a “César Nombela” Research Fellow at the Instituto de Geociencias (IGEO), a joint center of the Universidad Complutense de Madrid (UCM) and the Consejo Superior de Investigaciones Científicas (CSIC), where I lead, as Principal Investigator, the ADAPT-X project (AI-Driven AnticiPated aTtribution of eXtreme events), funded by the Comunidad de Madrid. I joined IGEO in 2024, after positions at ETH Zürich, Meteomatics and the Barcelona Supercomputing Center.

My research focuses on the physical drivers of climate variability and extreme weather, with particular interest in heatwaves, teleconnections, atmospheric circulation, and sub-seasonal-to-seasonal predictability. I combine observations, reanalysis products, numerical models, large climate-model ensembles, and emerging AI-based weather prediction systems to better understand and attribute high-impact weather events.

A central part of my current work is the use of AI-based weather prediction models for rapid climate-change attribution. I study how anthropogenic warming modifies the likelihood, intensity, and dynamical drivers of extreme events. I also contribute to international initiatives within APARC (Atmospheric Processes And their Role in Climate), a core project of the World Climate Research Programme (WCRP). Within APARC, I co-lead the extreme events topic of the Atmospheric Reanalysis Intercomparison Project (A-RIP), which aims to improve the representation of key atmospheric processes in reanalysis datasets for better understanding of past climate variability. I also contribute to LEADER (Large Ensembles for Attribution of Dynamically-driven ExtRemes), which investigates the role of internal variability in the polar vortex and its influence on surface climate extremes.