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Press Release
Press Release
New report shows how closer alignment between scientific estimates and economic modeling of physical risks is...
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Mark Campanale, Founder and CEO, Carbon Tracker Initiative: “The net result of flawed economic advice is widespread complacency amongst investors and policy makers, with many investors viewing climate scenario analysis as a tick-box disclosure exercise. Until the gap between scientists and economists’ expectations of future climate damages is closed and Government bodies act to ensure the integrity of advice upon which investment decisions are made, financial institutions will continue to chronically under-price climate risks - meaning that pension funds and taxpayers will remain dangerously exposed.”
Aligning modelling of economic damages with climate science
Recalibrating Climate Risk explains why economic models used by governments, central banks and investors are increasingly understating climate risks as the world moves towards 2°C. It shows how this can create a false sense of security – and why decision-makers should act now rather than wait for perfect models.
Led by the University of Exeter (Green Futures Solutions), in partnership with Carbon Tracker, the report draws on structured expert judgement from climate scientists across 12 countries to clarify where today’s ‘damage models’ fall short and what decision-makers should do to manage investment risks under rising uncertainty.
The report builds on earlier work challenging the under-pricing of climate damages in financial decision-making, including Carbon Tracker’s Loading the DICE Against Pensions (2023) and The Emperor’s New Climate Scenarios (IFoA/University of Exeter, 2023).
Key findings
- Physical climate damages are structural and compounding. At higher levels of warming, impacts are more likely to cascade across sectors and geographies, undermining the conditions economies rely on for stable growth.
- Real-world losses are shaped by local and regional extremes (heatwaves, floods, droughts) that can be poorly captured by models focused on global average temperature. Many approaches still link damages to global mean temperature, even though disruption is often driven by local and regional extremes.
- GDP-based metrics can undercount losses linked to mortality and morbidity, inequality, ecosystem degradation and social disruption, and can even appear to recover after disasters through reconstruction spending. GDP can mask welfare losses and distributional impacts, including when reconstruction spending raises GDP after disasters.
- Uncertainty increases sharply towards and beyond 2°C. Tail risks and tipping points become more relevant, yet models often present precise-looking point estimates that may not be decision-useful in deep uncertainty. As warming rises, point estimates can look precise while becoming less reliable for decision-making under deep uncertainty.
- The report argues against waiting for perfect modelling, and instead calls for governance, supervision and investment practice to be recalibrated towards precaution, robustness and transparency.
What the data shows
Expert judgement points to a widening gap between how climate scientists expect impacts to unfold and how many economic damage models represent them. As warming approaches 2°C, risk becomes less linear and more uncertain, while many economic models still assume impacts remain smooth and comparable to historical experience. That mismatch can produce climate damage estimates that look precise but are not reliable for decision-making – particularly when extremes, cascading disruption and welfare losses are not fully reflected in GDP-based outputs. In practice, this can encourage overconfidence in resilience and understate exposure to systemic disruption.
Recommendations
- Policymakers, regulators and central banks should focus on financial system resilience, updating supervisory approaches to reflect extremes, compounding impacts, tail risks and systemic vulnerability.
- Institutional investors, pension funds and investment advisers should treat physical climate risk as potentially correlated and economy-wide, stress testing strategies against cascading disruption that may not be visible in GDP-based outputs or conventional diversification assumptions. For long-horizon investors, this means testing strategy against correlated shocks and physical disruption that diversification may not protect against.
- Climate risk analysts and modelling providers should avoid single ‘best-estimate’ outputs, and instead support risk management under deep uncertainty, providing ranges and transparent assumptions – and being explicit about where models may break down at higher warming levels.
Call to action
To learn more about results, implications or next steps, please contact B.Dickenson-Bampton@exeter.ac.ukor or joel.benjamin@carbontracker.org
Download the full report (PDF), including technical details for direct damage function improvements.