Research project · 2026–2030

CLOSER: Closing the Loop — Attribution of Complex Climate Disasters to Climatic and to Policy Changes

Climate-related disasters rarely have a single cause: they emerge from the interplay of climatic and non-climatic drivers, such as land-use change, water management, exposure and social vulnerability, and often compound and cascade across systems. CLOSER aims to develop an integrated science of event attribution, forecast and impact, to support effective policymaking that prevents imminent harm and reduces risk in the coming decades.

Funding: Horizon Europe Research and Innovation Action (grant 101293581)
Duration: 48 months (September 2026 – August 2030)
Coordinator: Paolo Scussolini, Vrije Universiteit Amsterdam
PI at UC3M: Miguel-Ángel Fernández-Torres
Consortium: 15 beneficiaries and 1 associated partner from 11 countries on 3 continents
Case Applications: Six cases worldwide, from the Mediterranean and Northern Europe to the Caribbean, Senegal and India

Group photo of the CLOSER consortium members outdoors — The CLOSER consortium, September 2026.

Project structure

5 pillars · 3 key outputs

Pillar ACo-creating innovationsLiving Labs where stakeholders and researchers co-create scientific innovations and decision-making frameworks.
Pillar B · UC3MAdvancing disaster dataA harmonised global database linking climate hazards with exposure, impacts and vulnerability.
Pillar CModelling impactsProcess-based, complex-system and AI-based modelling of the systemic impacts of complex events.
Pillar DAttributing disastersA protocol to attribute the impacts of past, ongoing and future events to climatic and non-climatic drivers.
Pillar EUnderstanding policiesActionable understanding of how past and present policies shape disaster impacts and inequalities.

KOUT1Knowledge Base of Climate-related DisastersHarmonised global datasets of hazards, exposure, vulnerability, impacts and their attribution.
KOUT2Protocol for Expanded Attribution and ForecastMethods to attribute and forecast the impacts of extreme and slow-onset events, including compound and cascading ones.
KOUT3Decision-Making FrameworksTools that help decision-makers assess policy options for climate-related disasters, including the fairness of their outcomes.

Role of UC3M

UC3M contributes expertise in artificial intelligence, computer vision and data fusion to Pillar B, helping to build the Knowledge Base of Climate-related Disasters (KOUT1). The expected research focuses on:

AI-based detection of climate hazardsDeep learning and data-driven tools to map the spatial footprint and timing of single and compound extremes, such as heatwaves, droughts, floods and wildfires, at global scale.
Impacts from remote sensing and multimodal data fusionFusion of satellite observations with other heterogeneous sources to identify disaster impacts, especially in regions where impacts are under-reported.
Trustworthy and explainable AITransparent and interpretable AI methods, so that data-driven results can be traced and safely used to inform decisions.

Publications and activities

The project started in September 2026. Results will be listed here as they become available.

CLOSER is funded by the European Union under the Horizon Europe programme (grant agreement No. 101293581). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.