Top 100 Countries by Climate Risk Index (Heat, Floods, Storms), 2025

What the 2025 ranking implies: unbalanced profiles, regional patterns and practical use

Composite rankings are most informative when they are read as profiles, not as a single league table. Two countries can sit close together in the overall Top 100 and still face very different climate pressures. This section highlights how “unbalanced profiles” appear in the data, what regional patterns are most visible in 2025, and why the index is often cited in policy, finance and planning discussions.

Countries with unbalanced profiles (a high driver with weaker secondary risks)

A common unbalanced pattern is heat-dominant risk. Countries in arid and semi-arid zones can score very high on heat, while storms remain structurally limited and flood risk is more localised to specific basins. In the table, examples include Niger and Chad (very high heat scores with low storm scores), as well as parts of the Middle East where extreme heat is the primary driver. In such profiles, health impacts, labour productivity, water stress and power demand peaks tend to carry a larger share of the risk signal than cyclone landfalls.

Another unbalanced pattern is storm-dominant risk, where tropical cyclone intensity and exposure dominate. Many small island states show this structure: their storm score is high, and floods can also be elevated due to coastal processes, while heat is meaningful but not always the single strongest driver. Examples in the Top 100 include Vanuatu, Solomon Islands and several Pacific islands. In these cases, a limited land area concentrates assets and critical infrastructure, making resilience and recovery capacity central to impact outcomes.

A third unbalanced pattern is flood-heavy profiles, where geography (river deltas, low-lying coastlines, basin dynamics) raises flood risk substantially. Delta countries and densely populated coastal plains frequently fall into this group, with Bangladesh being a prominent multi-hazard example where flood remains extremely strong. In Europe, flood-heavy profiles can appear even with moderate heat and storm scores, reflecting exposure and the economics of assets at risk rather than tropical cyclone hazard.

Regional picture in 2025 (why the Top 100 looks the way it does)

The 2025 Top 100 is shaped by two layers: (1) long-run climate and hazard structure, and (2) where people and assets are concentrated. South and Southeast Asia stand out because dense populations overlap with a combination of heat stress and high riverine/coastal flood exposure, and in some locations, cyclone hazard. Sub-Saharan Africa shows many heat-elevated profiles and flood exposure in key basins, where vulnerability and coping capacity can magnify impacts. Small Island Developing States cluster because storm exposure can dominate expected losses, and recovery constraints can matter as much as the physical hazard itself.

Importantly, the index does not imply that lower-ranked countries have “no risk.” It indicates that, on a harmonised global scale, the combination of heat, flood and storm drivers is comparatively smaller or that exposure/vulnerability proxies are lower. Within-country variation can be large: coastal provinces, major cities, or specific river basins can face far higher risk than the national average.

How the index is typically used (business, insurance, public planning)

In practical settings, a country-level climate risk index is rarely used alone. It is usually combined with sector exposure and subnational analysis. Still, it is valuable as an initial map of where deeper due diligence is most likely to pay off. Typical applications include: (a) prioritising adaptation planning and resilient infrastructure funding, (b) informing insurance and reinsurance portfolio screening (especially for flood and storm tail risks), (c) identifying where supply chains may face disruption from compound events, and (d) supporting development and humanitarian risk reduction strategies where vulnerability amplifies hazard impacts.

Technical note: the 0–100 scaling is designed for comparability. A difference of, say, 5 points does not translate into a fixed percentage change in losses. It indicates a higher composite risk level given the normalisation and weights used (Heat 40%, Flood 35%, Storm 25%).