
Extreme event attribution (EEA) studies have become a critical tool for understanding how climate change influences the likelihood and severity of extreme weather events. However, most studies to date have focused predominantly on the physical science of hazards, with limited attention to the role of vulnerability in translating the hazard into impacts—the social, economic, political, and historical conditions that shape who is affected and how. The COMPASS project aims to develop a harmonised framework for climate and impact attribution, with a particular focus on compound and sequential extremes. In this context, the role of vulnerability factors in determining the nature and scale of impacts is even more critical as one hazard mayinfluence vulnerability and modify the impact of a second hazard. While COMPASS is developing approaches to quantitative vulnerability modeling, there remains a significant gap, and many questions, around the inclusion of qualitative vulnerability analysis. This guidance note, deliverable 3.2, aims to address that gap by providing practical directions to researchers on qualitatively assessing vulnerability and non-climatic compounding factors in attribution research. Developed through a review of literature and 16 expert interviews, the report synthesizes current practices, identifies key challenges, and outlines actionable approaches for integrating vulnerability more meaningfully into EEA. It contributes to the COMPASS objective of developing a scalable and flexible methodology for translating hazards to societal impacts in order to conduct impact attribution studies. While this documentdiscusses both quantitative and qualitative approaches, it is the integration of the two that may add the most value for researchers. Key findings and recommendations include: Vulnerability is central to understanding disaster impacts. Without it, attribution studies risk reinforcing hazard-centric narratives that obscure structural drivers of harm such as poverty, inequality, weak governance, and systemic marginalization. Qualitative and mixed-method approaches are essential to extend impact attribution to data-scarce regions. These methods allow researchers to capture lived experiences, root causes, and contextspecific drivers of vulnerability, particularly in places where social datasets have gaps, do not exist, or are inaccessible (e.g. conflict-affected areas). The use case for EEA studies needs to be clearly defined. Vulnerability integration must be designed from the outset, aligned with the intended use—whether for informing recovery, shaping adaptation strategies, or informing policy discussions. Compound events often have compounding impacts that require systems thinking. Multiple, interacting hazards demand tools that can track how vulnerabilities evolve over time and across sectors. Simple additive models are insufficient. Collaboration with local actors enhances relevance and legitimacy of attribution studies. Co-producing knowledge with communities, practitioners, and local researchers ensures assessments are grounded, inclusive, and policy relevant. The report outlines a range of methodological options—quantitative, qualitative, and integrative—highlighting when and how each option can be used. It emphasizes that no single method is universally applicable; instead, researchers must choose approaches that reflect the complexity of risk and the realities of those most affected. Within COMPASS, this guidance note will serve as a starting point for determining which vulnerability assessment methodology is more appropriate for each Use Case addressed in COMPASS work package. Deliverable 3.2 – Guidance note on qualitatively assessing vulnerability factors in attribution studies. Ultimately, by embedding vulnerability into attribution science, we move closer to the goal of making climate evidence more actionable, equitable, and meaningful for real-world decisions
climate change, vulnerability, impact, compound events, attribution, risk
climate change, vulnerability, impact, compound events, attribution, risk
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