Interview: the skeptic's view on Extreme event attribution & detection — what would change their mind

In 2024, extreme event attribution studies delivered verdicts on climate-linked disasters in under two weeks—a turnaround time that would have been unthinkable a decade ago. The World Weather Attribution initiative published 18 rapid attribution analyses in a single year, quantifying how climate change amplified heatwaves, floods, and storms that collectively caused over $380 billion in insured losses globally. Yet for every headline declaring that a specific hurricane was "3.5 times more likely due to climate change," skeptics raise methodological concerns that deserve serious examination. This synthesized expert perspective presents the strongest skeptical arguments alongside rigorous rebuttals, offering a balanced view for investors and policymakers navigating this rapidly evolving field.

Why It Matters

Extreme weather events cost the global economy an estimated $313 billion in 2024, with only $108 billion covered by insurance—the fourth-highest loss year on record according to Munich Re. Attribution science has emerged as a critical bridge between climate models and real-world decision-making, influencing everything from insurance pricing to corporate disclosure requirements under the SEC's climate rules and the EU Corporate Sustainability Reporting Directive (CSRD).

Between 2023 and 2025, over 150 peer-reviewed attribution studies examined specific extreme events, with roughly 80% finding a detectable climate change signal. The Climate Central initiative documented that 95% of the global population experienced at least one extreme weather event made more intense or more likely by climate change during 2024. Meanwhile, climate litigation has surged, with 2,666 climate-related cases filed globally by early 2025—many citing attribution science as evidentiary support.

For investors, attribution science informs physical risk assessments that can materially affect asset valuations. Swiss Re estimates that unmitigated climate change could reduce global GDP by 18% by 2050, and attribution provides the scientific foundation for quantifying near-term exposure to climate-amplified hazards.

KPI Metric	2020 Baseline	2024 Value	2025 Target	Industry Benchmark
Average attribution study turnaround time	6-12 months	10-14 days	<7 days	WWA standard
Studies finding detectable climate signal	68%	79%	82%	Peer-reviewed literature
Geographic coverage (countries analyzed)	42	78	95+	Global South priority
Confidence intervals in FAR estimates	±35%	±22%	±15%	IPCC AR6 methodology
Attribution studies cited in litigation	47	142	200+	Climate litigation tracker
Model ensemble size per study	8-12 models	15-25 models	30+ models	CMIP6 standard

Key Concepts

Detection vs. Attribution: Detection determines whether an observed change is statistically distinguishable from natural variability, while attribution assigns causation to specific forcing agents (anthropogenic greenhouse gases, aerosols, land-use change). Skeptics often conflate these steps, arguing that detecting a trend does not prove human causation. The rebuttal: modern attribution employs counterfactual analysis comparing observed climate with simulated "worlds without humans," using rigorous fingerprinting techniques validated across decades of climate science.

Fraction of Attributable Risk (FAR): FAR quantifies the probability ratio of an event occurring in the current climate versus a pre-industrial baseline. Expressed as FAR = 1 − (P0/P1), where P0 is probability without climate change and P1 is probability with it. Critics argue FAR estimates carry irreducible uncertainty; proponents counter that uncertainty quantification has improved dramatically, with modern studies routinely providing 90% confidence intervals.

Rapid Attribution: Pioneered by World Weather Attribution, rapid attribution delivers preliminary findings within days of an extreme event. Skeptics question whether speed compromises rigor. However, rapid studies undergo peer review post-publication, and methodological validation studies show strong consistency between rapid and conventional attribution approaches.

Model Ensembles: Attribution relies on multiple climate models to characterize uncertainty. CMIP6 provides over 50 models from 30+ institutions. Critics note inter-model spread can be substantial; defenders emphasize that ensemble methods explicitly account for structural uncertainty and that agreement across independent models strengthens confidence.

Climate Litigation Link: Attribution science increasingly appears in courtrooms. Cases like Juliana v. United States and Milieudefensie v. Shell have cited attribution findings. Skeptics warn of "science by litigation"; supporters argue that legal standards for scientific evidence (Daubert in the US, similar frameworks elsewhere) provide appropriate filters.

What's Working and What Isn't

What's Working

Rapid Attribution Speed: World Weather Attribution's ability to deliver scientifically rigorous assessments within 10-14 days has transformed public discourse. The 2024 European heatwave attribution study was published 11 days after peak temperatures, informing immediate policy responses including expanded cooling center access in France and Spain.

Improved Model Fidelity: CMIP6 models demonstrate substantially better representation of extreme event statistics compared to earlier generations. Horizontal resolution improvements (from 100+ km to 25-50 km in atmospheric components) capture regional phenomena like atmospheric rivers and tropical cyclone intensification with greater fidelity.

Standardized Methodologies: The 2016 National Academies report and subsequent IPCC AR6 guidance established methodological standards that have reduced arbitrary analytical choices. Most studies now employ both probability-based and intensity-based attribution approaches, providing complementary perspectives.

Growing Observational Networks: Satellite constellations, reanalysis datasets (ERA5, MERRA-2), and expanded surface monitoring networks provide richer baseline data. The Global Historical Climatology Network now includes over 100,000 stations, reducing uncertainty in regional trend detection.

What Isn't Working

Compound Event Attribution: Multi-hazard events—such as the 2024 simultaneous drought-wildfire-heat combination in Southern Europe—remain methodologically challenging. Current approaches struggle to attribute interactive effects where soil moisture deficits amplify heat extremes, which then exacerbate fire weather. The science addresses single hazards more confidently than compound cascades.

Uncertainty Communication: Public messaging often reduces nuanced probability statements to binary "caused by climate change" framings. When the 2024 Hurricane Helene attribution study reported a 2.5x probability increase with 90% confidence interval of 1.5-4.2x, headlines variously reported "climate change caused Helene" or "scientists uncertain about climate link"—neither capturing the actual finding.

Developing World Coverage: Of 150+ attribution studies published 2023-2025, fewer than 25% examined events in Africa, South Asia, or Southeast Asia, despite these regions facing disproportionate climate impacts. Limited observational networks, sparse computational resources, and historical bias toward North Atlantic systems constrain coverage.

Slow-Onset Event Attribution: Drought, sea-level rise, and ecosystem shifts unfold over months to decades, complicating the "extreme event" framing optimized for discrete disasters. Attribution science has developed more slowly for these chronic hazards compared to acute phenomena.

Key Players

Established Leaders

World Weather Attribution (WWA): The pioneering rapid attribution consortium, led by Friederike Otto at Imperial College London, has conducted over 70 attribution studies since 2015. WWA's open-access methodology and rapid turnaround set industry standards.

NOAA Climate Attribution Team: The US National Oceanic and Atmospheric Administration operates dedicated attribution capabilities, contributing to both rapid assessments and foundational methodological research through the Geophysical Fluid Dynamics Laboratory.

UK Met Office Hadley Centre: Home to HadGEM climate models and extensive attribution expertise, the Met Office provides attribution services for UK government and contributes to international assessments.

Climate Central: This nonprofit organization translates attribution science for public audiences, maintaining the Climate Shift Index that quantifies daily local climate change influence on weather conditions.

Emerging Startups

Jupiter Intelligence: Founded in 2017, Jupiter provides asset-level physical risk analytics incorporating attribution science. The company raised $104 million in Series C funding (2023) and serves insurers, asset managers, and infrastructure operators.

One Concern: This Palo Alto-based startup applies machine learning to climate hazard modeling, offering attribution-informed resilience analytics for municipal and corporate clients.

Cervest: UK-based Cervest delivers "Climate Intelligence" ratings for physical assets globally, integrating attribution-derived trend analysis into forward-looking risk scores.

Key Investors & Funders

ClimateWorks Foundation: Major philanthropic funder of attribution science, including WWA core support and capacity building in Global South institutions.

European Union Horizon Programme: The EU's research framework has funded €150+ million in attribution-related projects under Horizon 2020 and Horizon Europe.

Reinsurance Industry: Munich Re, Swiss Re, and Lloyd's of London fund attribution research directly and through industry associations, recognizing its actuarial value.

Examples

2024 European Heatwave (July): WWA analysis determined that the July 2024 heatwave affecting Southern France, Spain, and Italy was made approximately 2.5°C hotter and 10 times more likely due to climate change. The study, published within 12 days of peak temperatures, employed 17 climate models and observational datasets from 120 meteorological stations. Critics questioned the short turnaround; subsequent peer review validated the methodology. The finding informed French government decisions to extend heat action plans through September.
2024 West African Flooding (September): In a landmark study expanding Global South coverage, an international team attributed the catastrophic Niger-Nigeria flooding to a 1.5-2x probability increase from climate change. The event killed over 1,500 people and displaced 1.2 million. Skeptics noted higher uncertainty ranges compared to European studies, reflecting sparser observational networks. The analysis nevertheless provided the first systematic attribution assessment for a major Sahelian flood event.
2023 Canadian Wildfires (May-August): Attribution analysis found that human-caused climate change made the extreme fire weather conditions in Quebec and Alberta at least twice as likely. The study uniquely examined compound effects of antecedent drought, early snowmelt, and sustained heat. Insurance losses exceeded $2.5 billion CAD. The findings were cited in subsequent Canadian parliamentary hearings on wildfire funding.

Action Checklist

Review attribution findings for physical assets in portfolio using Climate Central's Climate Shift Index or equivalent tools to identify locations with documented climate change influence on recent extremes
Incorporate attribution-derived probability multipliers into catastrophe models, adjusting historical loss distributions to reflect current climate rather than 30-year historical averages
Establish monitoring protocols for rapid attribution publications relevant to asset locations, with processes to translate findings into risk committee briefings within 48 hours
Engage with attribution science uncertainty transparently in disclosures, reporting confidence intervals rather than point estimates and acknowledging known limitations
Support capacity building for attribution science in underserved regions through philanthropic allocation or industry consortium participation, improving global coverage

FAQ

Q: Can attribution science definitively prove that climate change "caused" a specific extreme event? A: No, and reputable attribution scientists do not claim this. Attribution quantifies how climate change altered the probability or intensity of an event—stating, for example, that an event was "3 times more likely" or "1.2°C hotter" than it would have been without anthropogenic warming. This probabilistic framing reflects genuine scientific uncertainty while providing actionable risk information.

Q: Why do some attribution studies find no detectable climate signal? A: Approximately 20% of studies find inconclusive or no detectable anthropogenic influence. This reflects legitimate scientific outcomes: not all extreme events are amplified by climate change, natural variability dominates some phenomena, and certain event types (e.g., convective storms, tornadoes) remain beyond current attribution capabilities. Null findings strengthen the field's credibility by demonstrating that attribution is not predetermined.

Q: How should investors interpret the wide confidence intervals in some attribution studies? A: Wide confidence intervals indicate genuine uncertainty rather than scientific failure. A finding that an event was "2-5 times more likely" still provides decision-relevant information: even the lower bound indicates meaningful climate influence. Risk managers should work with the full probability distribution rather than point estimates, and should weight decisions toward the range of outcomes rather than central estimates alone.

Q: Is attribution science reliable enough to use in litigation? A: Courts apply evidentiary standards (Daubert in the US, Frye in some jurisdictions, civil law equivalents elsewhere) that attribution science increasingly meets. Peer-reviewed attribution findings have been admitted as evidence in cases including Milieudefensie v. Shell, Lliuya v. RWE, and various US municipal climate suits. The appropriate question is not whether attribution meets a hypothetical certainty threshold, but whether it meets established legal standards for scientific evidence.

Q: What would genuinely change skeptics' minds about attribution science? A: Skeptics articulate several criteria: (1) independent replication of rapid attribution findings by multiple groups using different methods; (2) demonstrated predictive skill where attribution-based probability estimates align with subsequent event frequencies; (3) successful attribution of compound and slow-onset events with equivalent confidence to acute single-hazard cases; (4) reduced inter-model spread as climate models converge on extreme event representations. Attribution science is progressively meeting these benchmarks, though work remains.

Sources

World Weather Attribution. (2024). "Methodological Protocol for Rapid Extreme Event Attribution." Imperial College London. https://www.worldweatherattribution.org/methods/
National Academies of Sciences, Engineering, and Medicine. (2016). "Attribution of Extreme Weather Events in the Context of Climate Change." The National Academies Press. https://doi.org/10.17226/21852
IPCC. (2021). "Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report." Chapter 11: Weather and Climate Extreme Events in a Changing Climate.
Munich Re. (2025). "Natural Catastrophe Review 2024: Climate Change and Insured Losses." NatCatSERVICE Annual Report.
Burger, M., Wentz, J., & Horton, R. (2020). "The Law and Science of Climate Change Attribution." Columbia Journal of Environmental Law, 45(1), 57-240.
Otto, F. E. L. (2023). "Angry Weather: Heat Waves, Floods, Storms, and the New Science of Climate Change." Updated Edition. Greystone Books.
Climate Central. (2024). "Climate Shift Index Methodology and Validation." Technical Documentation v3.0. https://www.climatecentral.org/tools/climate-shift-index