Preparing U.S. Airport Infrastructure for Weather Events (2026)
Chapter: Speaker Sessions
Speaker Sessions
Speaker 1
Building Airport Resilience from Lessons to Action
Sandy Hertz, formerly of the Maryland DOT
Sandy Hertz discussed the systemic challenge of airports and agencies lacking standardized methods to assess threats and prioritize investments. Hertz presented ideas for airports to study lessons learned on resiliency from other modes of transportation and apply existing tools to improve the airport’s ability to respond to weather events.
Hertz emphasized that the focus of the Insight Event’s discussions had been on building structured and actionable resilience into airports. She referred to NCHRP Project 23-32, “Transportation Asset Risk and Resilience,” of which she is the chair, which is in progress and intends to fill a gap by offering a repeatable, science-based approach for assessing climate-related threats to critical transportation assets.33 Hertz noted that it is difficult to standardize guidance on vulnerability and how it will affect each airport region by region; even using the data that exist to assess the level of risk is circumstantial. She explained that this NCHRP project considers how to identify threat–asset pairs within a system. On an airport campus, there may not be a full asset inventory, but the critical airport infrastructure is easily identified. The project team is actively seeking case studies on extreme heat impacts to airport runways to include in the report.
Hertz explained the United States Department of Transportation (U.S. DOT) Resilience Coalition—a U.S. DOT and AASHTO initiative—is gathering bottom-up feedback from practitioners to identify capacity, data, and tool gaps. The U.S. DOT Resilience Coalition developed a white paper to inform federal strategies.34 She shared that a national resilience strategy needs to be built on common definitions, shared metrics, and actionable methods.
Hertz discussed airport resiliency and how airports are campus-based but interconnected with other airports, and disruptions often are felt across the system. She pointed to the Bureau of Transportation statistics as a resource for obtaining data on disruptions, delays, and other metrics. She noted that 60 percent of airport delays stem
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33 Transportation Research Board. NCHRP Project 23-32, “Transportation Asset Risk and Resilience.” http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=5361.
34 AASHTO. 2024. U.S. DOT Resilience Coalition: Summary of Findings. U.S. DOT. https://shareit.transportation.org/drive/s/JtvdpdJeY6468nL2l0lDxxtPnWEmRM.
from weather, which poses a challenge for airport resilience. Hertz explained that data can be used to help classify risks and justify improvements that are needed. She referenced ACRP Research Report 263: Creating Self-Directed Resiliency Plans for General Aviation Airports as a resource to prepare for stressors.35 The report identifies methods for self-directed planning for local airport resilience.
Hertz provided an example of Charlotte Douglas International Airport and impacts resulting from Hurricane Helene. She noted that airport fact sheets can be used to justify recovery efforts and investments. They help identify the number of people served, regional connections, and interdependencies and can be used as a tool when communicating with stakeholders after a weather event has concluded and aid in future planning.
Hertz cited the disaster-response example of the Key Bridge collapse in Maryland. She described that, within 30 seconds of the disaster, the Maryland DOT police closed the bridge to traffic. The bridge collapsed within 2.5 minutes after being struck by the container ship, showing how quickly emergency response is needed to save lives. Hertz suggested that airports should develop partnerships across multiple modes of transportation within their region to ensure redundancy and resilience. She shared that coordination with emergency planning is critical as well as developing after-action reports. She suggested coordinating emergency training exercises with FEMA to practice responses. She identified the need for airports to build capacity for resilience planning, including identifying primary stakeholders, developing contingency plans, and standardizing risk assessments and communications.
Hertz introduced practical methods featured in NCHRP 23-32 and the Resilience Coalition report, along with aviation-specific efforts that can help airports advocate for funding and prepare for future weather challenges. Her presentation included the following equations:
- Resilience benefit equation: B = T × P (total benefit × probability of hazard).
- Annual risk equation: R = C × V × T (cost × vulnerability × threat probability).
Hertz suggested using tools such as the Risk Analysis and Management for Critical Asset Protection (RAMCAP)36 and cost–benefit analysis to help quantify investment value. She explained that tools exist, but staff need to be trained to build core competence in resilience planning. She suggested that airports should consider the
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35 Witt, A., A. Lollar, L. Desai, B. Smith, M. Stephens, K. Fabend, and M. Held. 2024. ACRP Research Report 263: Creating Self-Directed Resiliency Plans for General Aviation Airports. Transportation Research Board, Washington, DC. https://doi.org/10.17226/27879.
36 American Cyber Defense Agency. 2006. Risk Analysis and Management for Critical Asset Protection (RAMCAP). American Society of Military Engineers. https://www.cisa.gov/mts-resilience-resources/risk-analysis-and-management-critical-asset-protection-ramcap.
frequency of exceeding design standards to determine how to improve resilience based on data from prior weather events.
Hertz suggested ACRP Research Report 268: Integrating Crisis Management and Business Continuity at Airports: A Practical Guide as a resource.37 She concluded by sharing that her vision for a resilient, future-ready airport system is one in which planning is proactive, inclusive, and data driven.
Speaker 2
AI and Airport Infrastructure: Deep Dive
Brian Bothwell, United States Government Accountability Office (GAO)
Brian Bothwell introduced the U.S. GAO and the work of the Science, Technology Assessment, and Analytics (STAA) team. He provided examples of GAO reports that are relevant to airports.
Bothwell explained how the GAO STAA team conducts technology assessments and science and technology performance audits and provides recommendations in response to congressional requests on a broad array of topics. The team provides Congress with on-demand consulting and technical assistance to inform legislative work and audits agencies as needed.
Bothwell explained that STAA considered artificial intelligence (AI) applications in airport infrastructure. The team found that improved algorithms in machine learning and computing power lend themselves well to various applications in the airport environment, including indicating predictive maintenance based on sensor data, analyzing energy consumption data to optimize power usage, tracking passenger and aircraft movements for air traffic management, providing security enhancements, and forecasting weather.
Bothwell shared that GAO also reviewed AI applications in natural hazard modeling for severe storms, including hurricanes, floods, and wildfires, in a report titled Artificial Intelligence in Natural Hazard Modeling: Severe Storms, Hurricanes, Floods, and Wildfires.38 He explained that 15,000 severe storm warnings are issued each year by the weather service. The warnings are based on short-term predictions and long-term
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37 Van Horne, P., A. Saulcy, G. Lee, P. Villegas, A. Armstrong, B. Giles-Jones, K. Scott, D. DiMaria, W. MacMillan, S. Warner-Bean, R. Agnew, and C. Coverdell. 2024. ACRP Research Report 268: Integrating Crisis Management and Business Continuity at Airports: A Practical Guide. Transportation Research Board, Washington, DC. https://doi.org/10.17226/27915.
38 U.S. GAO. 2023. Artificial Intelligence in Natural Hazard Modeling: Severe Storms, Hurricanes, Floods, and Wildfires. https://www.gao.gov/products/gao-24-106213.
global predictions. He shared that “Machine learning is being applied to forecasting models for natural hazards such as severe storms, hurricanes, floods, and wildfires.” Model forecasts are poorly represented when compared with results, since information is delayed. Thunderstorm and tornado warnings have been promising in allowing more lead time for predictions. Hurricane predictions identify two key elements: the path and storm intensity. Bothwell explained that predicting intensity has limitations; machine-learning models have addressed these limitations and outperformed traditional models. There is not as much data available on Category 5 hurricanes, so the models are not as effective. He included that “A few machine-learning models are used operationally—in routine forecasting—such as one that may improve warning times.”
Bothwell explained that some uses of machine learning are considered close to operational, while others require years of development and testing. GAO identified three potential benefits to applying machine learning in natural hazard modeling for severe storms: (1) replace slow components of traditional models, thereby reducing the time required to make forecasts; (2) increase model accuracy; and (3) reduce uncertainty of model output. GAO identified the following challenges: (1) data limitations or lack of data sharing, which limit machine-learning models; (2) lack of trust and understanding of the algorithms; (3) limited coordination and collaboration; and (4) workforce and resource gaps. GAO suggests policy options within the report based on their findings.
Bothwell provided an overview of additional airport-related studies conducted by GAO. A report titled Airport Infrastructure: Selected Airports’ Efforts to Enhance Electrical Resilience was published in 2023. It provides a review of airport electrical power outages and their impacts on airport operations based on survey responses from 24 commercial-service airports.39 Bothwell also referenced a GAO report titled Aviation Operational Preparedness that has not yet been published. Additionally, future GAO work mandated through the FAA Reauthorization Act includes reports on weather reporting systems, weather camera programs for flight interruptions, airspace congestion, and ATC staffing.
The session then transitioned to a Q&A period with the audience.
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39 GAO. 2023. Airport Infrastructure: Selected Airports’ Efforts to Enhance Electrical Resilience. https://www.gao.gov/products/gao-23-105203.
Question 1: One participant observed that the country appears to be at an inflection point in how weather information is being delivered. The same participant noted their prediction is that information related to weather will become faster and more focused.
Question 2: Another participant inquired whether airports can analyze the weather that is most often responsible for delays. Is there an opportunity to use big data to predict lightning strikes and hail?
Bothwell noted that the GAO airport infrastructure report was published in 2023, so additional progress has likely been made since then.
Question 3: Has GAO considered any potential alarm fatigue from the public since the volume of alerts is so high as severe weather becomes more common?
Bothwell replied that it would be an interesting topic to look into, specifically what regions are impacted at varying times throughout the year. He noted that he is not aware of any ongoing studies.
Question 4: Did airlines review the information on severe weather? The participant noted that airport infrastructure is fixed, but airlines could use weather data to reroute or develop program changes. The participant also mentioned that prediction models could improve flight rerouting and drive airline decision-making to reduce delays.
Bothwell added that aircraft rerouting is a complex problem that was not reviewed as part of the GAO study.
Question 5: Has GAO looked at standardization of performance metrics that came out of the report to aid in trust building related to AI?
Bothwell commented that building trust and eliminating bias could support transparency in decision-making.
Question 6: A participant provided a comment that they were aware of an example in which AI had been used in airport forecasting and designing and optimizing the airport.
Question 7: Are there any GAO studies on virtual reality and its application at airports?
Bothwell replied that he was not aware of an airport-specific study, but GAO has published recent reports on virtual reality applications.40,41
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40 GAO. 2024. Immersive Technologies: Most Civilian Agencies Are Using or Plan to Use Augmented Reality, Virtual Reality, and More. https://www.gao.gov/products/gao-24-106665.
41 GAO. 2022. Science & Tech Spotlight: Extended Reality Technologies. https://www.gao.gov/products/gao-22-105541.
