Context
As climate change impacts intensify globally, comprehensive Climate Risk Assessment (CRA) is crucial for effective disaster risk management and adaptation strategies. This systematic literature review examines recent developments in CRA, focusing on how climate risks are framed and assessed, highlighting challenges and opportunities for future research.
Key findings
- CRA must evolve to address complexity and uncertainty: climate risks are dynamic and there is increasing evidence that human responses modulate interactions between hazards, exposure, vulnerability—also influenced by socio-economic and environmental changes. Future CRA must address cascading, compounding, and interacting risks; integrate responses (adaptation/mitigation) as potential sources of risk; and approach exposure and vulnerability as dynamic concepts.
- Emerging concepts and approaches offer new analytical lenses: recent developments, such as Climatic Impact-Drivers (CID), risk tolerance, and event-based storylines approaches can produce more context-sensitive assessments, incorporating stakeholder needs and perceptions. Also, growing interest in multi-hazard approaches aims to prevent a fragmented view of local risk conditions by analyzing natural hazards of different kinds and their interrelationships in time and space, coinciding climatic and non-climatic factors driving risks, and considering the adaptive capacity of different receptors.
- Managing complexity and uncertainty remains the main challenge: deep uncertainty and complicated risk interactions, coupled with the lack of standardized, interoperable, and high-resolution datasets, often lead to operational difficulties in CRAs.
Implications
To advance climate risk assessment research and implementation the study suggests:
- Address knowledge gaps such as risk-related behaviour and normative choices, changes in exposure and vulnerability under diverse future socioeconomic scenarios and development pathways, responses modulating risk profiles over time, and risks under transient scenarios.
- Adopting a systemic approach to account for cascading and compounding risks, hazard thresholds, adaptation limits, feedback loops, and various risk pathways under different scenarios.
- Using storyline approaches along with visualisations and 3D simulations to improve CRA communication and mainstreaming in policy and decision-making.
- Leveraging emerging technologies such as AI, machine learning, earth observation, and big data analytics to enhance real-time risk prediction and modeling.
- Combining top-down (modeling) and bottom-up (stakeholder-informed) assessments to better understand risk dynamics, connections across systems, and “hidden” impacts in models.
References
Higuera Roa O., Bachmann M., Mechler R. et al. Challenges and opportunities in climate risk assessment: future directions for assessing complex climate risks. In Environmental Research Letters, 20, 053003.
