CIRCAD’s research and engagement activities are driven by close collaboration among academic researchers, industry partners, and public-sector stakeholders working at the intersection of climate risk, resilience, and decision-making.
Through CIRCAD’s Industry Advisory Board (IAB), our members, including Aon, American Family Insurance, IBHS, Liberty Mutual, NASA, USAA, and WTW, help identify emerging challenges and priority research areas related to climate risk assessment, disaster resilience, and adaptation. This collaborative model ensures that CIRCAD’s research is grounded in real-world needs and designed to generate actionable insights for decision-makers.
In addition to advancing research, CIRCAD fosters engagement through monthly and quarterly meetings, workshops, and ongoing collaboration between researchers and member organizations. CIRCAD also creates opportunities for on-campus engagement at Duke University and the University of Georgia, including visits from Industry Advisory Board members for talks, workshops, meetings with faculty, and discussions around shared goals, research priorities, and emerging challenges.
CIRCAD currently supports four funded research projects led by faculty at Duke University and the University of Georgia. These projects address critical challenges in climate risk and resilience and reflect the priorities identified through collaboration with our member organizations.
- 1. Incentive Dynamics in Climate Resilience Systems: Insurance, Public Infrastructure, and Private Adaptation
Led by Yichun Fan (Duke University), Martin Smith (Duke University), and Craig Landry (University of Georgia)
The economic damages from climate disasters depend on both physical hazards, such as storms, flooding, extreme heat, and wildfires, and human behavior, including where people choose to live, private investments in climate proofing homes and public investments such as in flood control and wildfire suppression. Scientists have a working understanding of physical climate risks but know far less about how people respond to these risks. Improving our understanding of private responses to climate risk can inform better insurance products and enhance climate resilience.
A new research project is using AI to analyze hundreds of millions of building permits, tracking where people build and how they fortify their homes against climate hazards, from reinforcing roofs to fireproofing and elevating foundations. CIRCAD researchers will leverage these new data to examine how insurance pricing and public infrastructure affect household decisions and ultimately inform climate resilient planning at the system level.
- 2. Climate-Driven Aging, Dynamic Vulnerability, and Economic Network Cost Evaluation
Led by Beshoy Morkos (University of Georgia), Andrew Johnson (Duke University), Sara Oliver (Duke University)
This project develops novel, AI-driven approaches to understand how roofs degrade over time and how that degradation, combined with changing climate conditions, drives damage, costs, and long-term risk. Current models used by insurers and planners treat buildings as static, meaning they assume a roof today behaves the same way years from now. This project challenges that assumption by generating new data and models that reveal how roofing materials weaken over time due to heat, sunlight, moisture, and repeated exposure to weather. These models translate physical aging into measurable changes in damage risk, providing a more accurate picture of how and when failures occur.
The project integrates this new knowledge into a simulation platform that tracks roofs over decades. It combines climate projections, material aging, and economic factors to model how individual homes, and entire communities, change over time. This enables analysis of when roof replacement or upgrades become cost-effective, how stronger materials alter long-term outcomes, and how risk accumulates if no action is taken. The impact extends beyond individual decisions, as the platform will allow insurers, governments, and industry to test policies such as rebates, insurance pricing changes, and resilience programs before implementing them. It will predict how these strategies may influence homeowner behavior, reduce losses, and improve the long-term insurability of communities.
By linking climate exposure, material degradation, and economic decision-making, this project produces new data, models, and tools that shift the focus from reacting to disasters toward actively reducing risk.
- 3. Framing Environmental Risk: Modeling the Process of Climate-Contingent Investment
Led by Scott Huettel (Duke University), Gavan Fitzsimons (Duke University), and Marcus Cunha (University of Georgia)
Environmental risks present challenges for investment, insurance, and resilience decisions. For home-owners, assessing these risks involves consideration of outcomes that are low-probability, catastrophic, and distant in the future – exactly the circumstances shown by research to be most likely to generate biases or errors in the decision process. Moreover, the complexity of risk assessments can lead consumers to delay choices, under-insure property, or forgo insurance entirely.Our project brings decisions about environmental risks into a decision science laboratory, so that we can identify factors that shape consumer decisions about resilience and insurance. Our research team will ask consumers to evaluate environmental risk information about homes for sale in North Carolina and Georgia. After viewing each home, each consumer will choose between possible investments in the home that involve tradeoffs between building resilience or improving luxury. We will measure their attentional engagement using high-resolution eye-tracking, which in turn feeds into computational models of the decision process. Through this work, we seek to better understand consumers’ assessments of environmental risks so that we can develop messaging that overcomes cognitive biases in decision making.
- 4. High-Resolution Weather Risk Assessment for Seasonal to Decadal Planning
Led by Weiming Hu (University of Georgia), Liyin He (Duke University), David Fastovich (University of Georgia), Andrew Grundstein (University of Georgia), Marshall Shepherd (University of Georgia), Yi Deng (Georgia Tech)
Severe storms that produce hail, wind gusts, and tornadoes can potentially be more costly than anticipated: in recent years over $45 billion annually in actual claims versus $10-20 billion predicted by current models. This gap exists partly because storm forecasts operate at limited resolution (up to 60 miles), which makes them challenging for accurate risk assessment at smaller scales like individual car dealerships. Additionally, while models may aggregate perils, they may not fully capture how storm hazards compound across regions or amplify each other over time.
Our two-year project addresses these problems through three parallel efforts: building a comprehensive map of how storm hazards compound across the United States, developing an index to identify where infrastructure is most vulnerable to multiple simultaneous hazards, and training advanced AI models to produce storm predictions at a higher spatial resolution (~ 2.5 miles). We will combine these tools to reveal how different storm hazards are connected over time and whether they amplify each other in ways that could dramatically increase losses. The final deliverables will provide stakeholders with more spatially detailed risk maps and a deeper understanding and robust assessment of compound storm risks.