What climate risk means for infrastructure investments

Infrastructure assets are illiquid, fixed in place, and exposed to physical climate risks including flooding, extreme winds, heat, and wildfires. Unlike other asset classes, they cannot be repositioned when conditions change. Localised failures can cascade across entire systems, creating outsized financial impacts. Despite this, most infrastructure underwriting still relies on incomplete or overly simplified physical risk assessments, creating a material blind spot in how infrastructure risk is priced.

Scaling investment while managing physical risk

Infrastructure has established itself as a core institutional asset class, with private AUM exceeding $1.3 trillion, having quadrupled over the past decade (p.4). Global infrastructure investment requirements are projected to reach approximately $106 trillion by 2040 (p.5). Structural tailwinds include AI-related energy consumption, data centre expansion, the energy transition, grid modernisation, and onshoring of industrial capacity.

The durability of infrastructure cash flows is inseparable from physical climate risk. For long-duration investors, rigorous assessment of climate exposure is critical to underwriting asset resilience and protecting long-term returns.

A new standard for analysing complex infrastructure risk

Traditional climate risk tools were designed for single-point assets and fail to capture spatial variation across networks. First Street’s Complex Assets Module addresses this by decomposing linear geometries and large polygons into segments, linking exposure to asset-specific damage functions and downtime modelling. This replaces bespoke, consultant-led analyses with a scalable, standardised framework applicable across portfolios.

Airports: Flooding can force full operational shutdown

In April and May 2024, floodwaters submerged large portions of Porto Alegre’s Salgado Filho International Airport, reaching 2.5 meters in some areas and resulting in roughly $180 million in damage (p.7). The airport remained closed to commercial flights for nearly five months. First Street’s model identified 376 sub-assets, with 83% exposed to flooding in a 1% annual event, modelling losses of up to $181.8 million and a maximum downtime of 152 days, equating to a revenue loss of $40–44 million (~40–45% of annual revenue) (p.9).

Residential development: Climate risk can emerge rapidly within a single hold period

A 206-home residential development in suburban central Florida was modelled for wildfire burn probability: 12% today, rising to 17% over 10 years and 26% over 30 years (p.11). Wildfire is a total-loss event, driving full reconstruction timelines of up to 907 days and a revenue loss of $12.8 million (~248% of annual NOI) (p.12). Investors face a multi-hazard trade-off as inland growth shifts exposure from hurricane risk to wildfire risk.

Rail networks: Local damage can disrupt entire corridors

Storm Bernd in July 2021 damaged approximately 600 kilometres of Deutsche Bahn rail lines, with floodwaters reaching 10.2 meters and estimated damage of €1.3 billion (p.13). Modelling the Dortmund–Frankfurt ICE corridor across 2,891 segments found 23% exposed to flooding, with a maximum downtime of 60 days and revenue loss of approximately €72 million (~20% of annual revenue) (p.15).

Transmission lines: Modest failures cause network-wide losses

Typhoon Odette struck the Philippines in December 2021 with gusts reaching 168 mph, damaging at least 95 facilities including 12 transmission towers and more than 600 transmission poles (p.16). Modelling a Surigao–Davao corridor across 3,650 segments found 100% exposed to winds of at least 74 mph. Maximum downtime was 3 days, with a revenue loss of $1.6–2.1 million (~1% of annual revenue) (p.18), though repeated failures drive cumulative capital expenditure and reliability risk.

Toll roads: Local flooding can disrupt corridor-wide revenue

In May 2019, more than 10 inches of rainfall caused flash flooding along a four-mile stretch of the Kansas Turnpike, closing the highway for approximately two days (p.19). Modelling across 3,803 segments found 9% exposed, with maximum flood depths of 13.6 feet in a 1% event and a cumulative probability of 26% over 30 years. Maximum downtime was 40 days, with a revenue loss of $40–45 million (~10–12% of annual revenue) (p.21).

Conclusion: Infrastructure risk is investment risk

Across all five case studies, infrastructure risk is shaped by the interaction of exposure, asset design, spatial configuration, and system dependencies. Localised vulnerabilities propagate through interconnected systems in nonlinear patterns, often outside the scope of traditional point-based frameworks. First Street’s Complex Assets Module connects hazard exposure with modelled damage and downtime, enabling more rigorous underwriting, pricing, and capital allocation across infrastructure portfolios.