Projects

Current Projects

ADAPT-X: AI-Driven AnticiPated aTtribution of eXtreme events

Funder: Comunidad de Madrid – “César Nombela” Talent Attraction Programme  ·  Ref: 2025-T1/ECO-36122
Duration: July 2026 – June 2031  ·  Role: Principal Investigator

Extreme events such as heatwaves and heavy precipitation pose growing risks to society. ADAPT-X develops the first operational climate service capable of attributing extreme events to anthropogenic climate change before they occur. Using AI-based weather prediction models, we combine forecasts under current and counterfactual (pre-industrial) climate conditions to quantify the human fingerprint on extreme events in near-real time — delivering anticipated attribution as an early warning tool for stakeholders and decision-makers.

Past Projects

Desarrollo de Servicios Climáticos Operativos

Funder: Recovery and Resilience Facility, NextGeneration EU  ·  Ref: CSC2300000
PIs: J.M. Gutiérrez, S.M. Vicente, D. Barriopedro, S. Beguería, C. Azorín  ·  Budget: 6,250,000 €
Duration: January 2023 – June 2026  ·  Role: Team member

Development of operational climate services for Spain in collaboration with AEMET and the Oficina Española del Cambio Climático, including services for the attribution of extreme events to climate change.

CLINT: CLImate INTelligence — Extreme events detection, attribution and adaptation design using machine learning

Funder: European Commission, Horizon 2020  ·  Ref: 101003876
Coordinator: Politecnico di Milano (Italy)  ·  Budget: 6,067,720 €
Duration: July 2021 – October 2025  ·  Role: Team member

Development of an artificial-intelligence framework for climate science and services, improving the understanding and predictability of extreme events and quantifying their impacts on climate-related sectors under historical and projected climate conditions, from the European to the local scale.

HEATforecast: Dynamical Constraints for the Predictability of Heat Waves

Funder: European Research Council (ERC), EXCELLENT SCIENCE  ·  Ref: 847456
PI: D. Domeisen (ETH Zürich / University of Lausanne)  ·  Budget: 1,499,849 €
Duration: March 2020 – May 2025  ·  Role: Team member

ERC Starting Grant investigating the physical drivers and predictability limits of heatwaves using a hierarchy of idealized general circulation models.

Improving the Prediction of Sub-seasonal to Seasonal Weather and Climate — From Theory to Application

Funder: Swiss National Science Foundation (SNF)  ·  Ref: PP00P2_170523
PI: D. Domeisen (ETH Zürich / University of Lausanne)  ·  Budget: 1,500,000 CHF
Duration: August 2017 – July 2021  ·  Role: Team member

Research on understanding and improving sub-seasonal to seasonal (S2S) forecasts, with focus on ENSO teleconnections and their influence on North Atlantic–European climate predictability.