Climate Change Adaptation Planning: Risk Assessment for Airports (2015)

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P A R T I I A Primer on Climate Change and Uncertainty for the Airport Context

13 4.1 Existing Climate and Weather-Related Events The IPCC, a world authority tasked with evaluating climate science, notes that the effects of changing climate have been felt worldwide in recent decades. In the United States, identified changes include increasing temperature, an increasing number of heavy rain days, and a num- ber of other impacts summarized below. In this guidebook, the term “climate vector” is used to describe aspects of climate that are known to affect airport operations. Collectively, these vectors (defined in 4.2.2, below), such as snow, ice, strong winds, heavy rainfall, or lightning, can result in delays, diversions, or stoppages that affect travelers, airport personnel and tenants, and ulti- mately, the airport’s bottom line. This can quickly have a cascading effect on the wider aviation system, further impacting stakeholders. Each of these climate impacts has the potential to affect air traffic and airport infrastructure. The degree to which climate change affects an airport is dependent on the magnitude of the change, the location of the airport, the airport’s level of preparedness, and existing infrastructure’s ability to withstand extreme weather events that exceed design criteria for the infrastructure. The selected vectors were chosen to show projections related to asset and operational vulnerabilities and the catalogue of adaptation tools and resources that exist (Burkett and Davidson, 2012) to support airport managers and staff in choosing adaptation strategies in response to a variety of climate change impacts and their associated risks. Knowing the specific impacts on an airport’s region and the particular vulnerabilities of an individual airport system is critical for adaptation planning. The ACROS tool supports airport planning by reporting impacts and potential adapta- tion options for further assessment. 4.2 National Climate Change Projections 4.2.1 How Might Climate Change in the Future? Climate change has increasingly affected aircraft and airport operations over the past two to three decades (IPCC, 2014a). In the period from 1980 to 2012, the United States has experienced 144 weather/climate disasters costing at least $1 billion each (Lott and Ross 2006; Smith and Katz 2013). These losses are tied to events ranging from hurricanes and tornado outbreaks to winter storms, wildfires, and droughts; however, they also relate to population increases and redistribu- tion of the population. Extreme weather events, including heat waves, floods, and drought have become more frequent and intense over parts of the country during the past 50 years (Melillo et al., 2014). The National Climate Assessment indicates that the impact of weather on human activities is inescapable and growing, and climate change-related extreme weather events will increase disruptions of infrastructure service in the future. C H A P T E R 4 Understanding Climate Change’s Impact on Airports

14 Climate Change Adaptation Planning: Risk Assessment for Airports Extreme events that impact population centers can be particularly damaging. In October 2012, Superstorm Sandy inflicted serious impacts on East Coast airports and national airline operations through storm surge, winds, flooding rains, and wet snows that lasted 2 to 5 days. The hurricane transitioned into a powerful, extratropical storm, resulting in thousands of delayed or cancelled flights and the closure of several major airports on the East Coast. These closures affected millions of travelers across the globe. In addition to physical damages, the International Air Transport Association (IATA) estimates that Sandy resulted in half a billion dollars in lost revenue for airlines (IATA, 2012). Climate scientists expect further increases in the frequency of extreme weather events, and those increases, coupled with an expanding population, are likely to result in more costly impacts. Of particular importance are extreme (and by definition, rare) events that can overwhelm an airport’s response resources and cause major disruptions and economic losses to airport stake- holders. Extreme events will also have significant physical and economic consequences at the regional level, which may manifest as impacts to airports (e.g., transportation infrastructure disruptions, impaired flow of goods, and reduced resource availability such as potable water and power). Furthermore, the gradual nature of change for many climate-related impacts implies that inaction may not manifest as a specific problem for years, reiterating the importance of a longer-term planning horizon. 4.2.2 Choosing Climate Vectors and Future Projection Proper treatment of future climate change not only involves informing the user about how weather is expected to change, but also providing an overview of the reference or “baseline” period. The latter is defined in this project as the period 1979–2012, and is based largely on data availability considerations. This period is also long enough to be considered a climate period (at least 30 years) as defined by the National Climatic Data Center (NOAA, 2014). Future projec- tions in this study (the years 2030 and 2060) were developed using the output of the IPCC AR5, the most up-to-date, comprehensive, national-scale information available at the time of research. Table 4-1 summarizes the climate vectors chosen for the ACROS tool. The summary also includes a confidence level, which is defined here as a subjective measure of projection reliability, based on scientific literature and agreement among global climate models, also known as general circulation models or GCMs. High confidence indicates less uncertainty than medium or low confidence; low-confidence vectors have the most uncertainty. Note that even “low” confidence implies that the vector may still be of value, and contrasts sharply with no confidence, as is seen for vectors like wind and fog. In the latter case, it was either (i) unfeasible to construct the vector based on data constraints, or (ii) the vector was constructed for the historical period, but was impossible to project into the future because of biases in the GCMs. The vectors selected for this project correspond directly to common climate-related concerns for infrastructure, based on literature sources and airport subject matter expert (SME) knowl- edge. Airport SMEs identified climate stressors that would impact airport operations and then worked with atmospheric scientists to identify specific climate metrics that could be analyzed. For example, high temperatures were identified as a stressor to multiple assets and operations. Examples of vectors related to high air temperature are days per year when air temperature exceed 90°F and days per year when temperatures exceed 100°F. Additional climate vectors developed to assess this stressor are shown in Table 4-1. 4.2.3 What Is a GCM? GCMs, or general circulation models, are numerical simulations of physical processes in the atmosphere, ocean, and land surfaces, and are used to model global climate. Although GCMs

Understanding Climate Change’s Impact on Airports 15 have been refined significantly since their inception in the 1960s, important caveats still exist as to what the models can and cannot simulate. As shown in Table 4-1, all temperature- and humidity-related vectors are robust in the sense that even the lower end of future projections still implies a substantially warmer and more humid climate. However, the main limitation of a GCM is its coarse scale, with a model grid as large as 150 miles. As a result of this factor, models cannot easily incorporate locally confined precipitation such as thunderstorms, which can be quite common, especially in the summertime. Additionally, GCMs are unable to simu- late hurricanes with adequate intensity, implying that some of the precipitation-related find- ings in ACROS may be conservative, especially along the southeast coast of the United States where hurricane-related rainfall and wind pose risks. Nevertheless, the ACROS screening tool attempts to provide climate impact insights to airport managers and operators who, outside of those along the coast subject to SLR impacts, may have heard very little about the type of climate impacts they can expect. There will be ample room to refine the climate projections (as well as incorporate additional vectors such as wind and fog) as higher resolution modeling becomes available in the near future. IPCC AR5 relies on simulations from over 30 GCMs and four different scenarios. Atmo- spheric carbon dioxide concentrations drive these models. The ACROS tool shows the ranges of model outcomes solely for a single scenario, representative concentration pathway (RCP) 8.5. RCP 8.5 is one of the four climate scenarios prepared for the IPCC AR5. RCP 8.5 assumes little to no global mitigation of carbon dioxide emissions. For a full climate analysis, especially one that extends significantly past mid-century, it is customary to review multiple scenarios. However, for the screening tool, only RCP 8.5 was used because this scenario does CLIMATE VECTOR DESCRIPTION CONFIDENCE Hot Days High temperature ≥ 90°F HIGH Very Hot Days High temperature ≥ 100°F HIGH Freezing Days High temperature ≤ 32°F HIGH Frost Days Low temperature ≤ 32°F HIGH Heang Day Mean temperature ≤ 65°F HIGH Cooling Day Mean temperature ≥ 65°F HIGH Cooling Degree Days Departure of mean temperature ≥ 65°F HIGH Heang Degree Days Departure of mean temperature ≤ 65°F HIGH Hot Nights Low temperature ≥ 68°F HIGH Humid Days Mean dew point temperature ≥ 65°F HIGH Snow Days Snow accumulaon ≥ 2 in. MEDIUM Storm Days Thunderstorm rainfall ≥ 0.15 in. LOW Heavy Rain (1 day) Daily rainfall ≥ 0.8 in. LOW Heavy Rain (5 day) Total 5-day rainfall MEDIUM Dry Days Consecu‚ve days of rainfall ≤ 0.03 in. MEDIUM Sea Level Rise Daily runway flooding (Na‚onal Flight Data Center eleva‚on) HIGH Sea Level Rise – Base Flood Eleva‚on (BFE) Rela‚vely infrequent but substan‚al flooding HIGH Wind* Prevailing wind direc‚on and speed NONE Fog* Visibility ≤ 0.25 miles NONE *Vector was invesgated, but not included in the ACROS tool due to lack of confidence in exisng models. Table 4-1. Overview of selected climate vectors.

16 Climate Change Adaptation Planning: Risk Assessment for Airports not diverge markedly from the other scenarios until after the period of interest for this study (present day to 2060). For more on GCMs and sources of uncertainty for climate models, please see Chapter 5. 4.3 Atmospheric Climate Vectors Projections of the key climate vectors shown in Table 4-1 were prepared for 2030 and 2060 to assist airport managers over the short- and long-term planning horizons. The projections considered both the past 34 years of observation and the trends projected by GCMs for 2030 and 2060. Results for several selected climate vectors are presented in the figures below. These climate vectors are depicted to provide the reader with a broad overview of projected changes to United States climate. To view the full set of atmospheric vectors included in this study, includ- ing the model ranges (25th, median, and 75th percentile), please see Appendix F. To learn more about uncertainty related to climate modeling and the ramifications for engineering and plan- ning, please see Chapter 5 of this guidebook. Finally, please note that Hawaiian airports have been excluded from this study. The grid sizes of currently available GCMs are composed of approximately 99% ocean and only 1% landmass for the Hawaiian Islands. At these grid sizes, Hawaiian climate is not reliably repro- duced, and is therefore not included in ACROS. The availability of downscaled models (i.e., with smaller grid sizes) would significantly improve the characterization of Hawaii and other islands. 4.4 Hot Days: Number of Days >– 90ºF Figure 4-1 shows that nearly all airports across the continental United States are likely to experience more days where the temperature reaches 90°F in 2030 and 2060. In typically warmer locations such as the southern plains and Southeast, the changes were substantial. However, strong increases were noted across the intermountain west, the northern plains, and the North- east. All of these values suggest substantial increases over present conditions. There is agreement among all GCMs for this vector, hence the high confidence in this vector. AK AK AK Figure 4-1. Projected changes in Hot Days from baseline to 2030 and 2060. Unit: days/year. Hawaii was considered, but omitted from this analysis as GCM grid size is too large to produce reliable atmospheric projections for Hawaii at this time.

Understanding Climate Change’s Impact on Airports 17 4.5 Frost Days: Number of Days with Low Temperatures <– 32ºF Consistent with Hot Days, there are likely to be substantial decreases in the number of Frost Days nationwide, as shown in Figure 4-2. The largest changes are projected to occur south of the intermountain west and the northern tier of the country, corresponding to areas where values are initially highest. 4.6 Cooling Degree Days Cooling Degree Days (CDDs) are based on the day’s average temperature minus 65°F and relate the day’s temperature to the energy demands of air conditioning. ( )= ° − °CDD Daily Average Temperature if > 65 F 65 F For example, if the day’s high is 90°F and the day’s low is 70°F, the day’s average is 80°F. From 80°F, we subtract 65°F, resulting in 15 CDDs. Thus, as the number of CDDs increases, the use of energy to provide air conditioning at airports increases. As expected from the previously described temperature-related vectors, significant increases in CDDs are noted nationwide by 2030, with additional large increases by 2060. Figure 4-3 shows the extensive increase in CDDs across the United States. While relative humidity increases are not figured into the CDD calculation (although they are also substantial), changes of over 25 percent in the number of annual CDDs could indicate the need to change the American Society of Heating and Air-Conditioning Engineers (ASHRAE)-specified United States climate zone map used at a given airport. 4.7 Storm Days The Storm Day vector was developed by investigating thunderstorm-related precipitation modeled by GCMs. A Storm Day is noted when that precipitation exceeds a certain thresh- old, and is thus anticipated to produce impacts such as flash flooding, gusty winds, hail, and, AK AK AK Figure 4-2. Projected changes in Frost Days from baseline to 2030 and 2060. Unit: days/year. Hawaii was considered, but omitted from this analysis as GCM grid size is too large to produce reliable atmospheric projections for Hawaii at this time.

18 Climate Change Adaptation Planning: Risk Assessment for Airports potentially, tornadoes. It is crucial to note that this vector is assigned low confidence because GCMs lack the horizontal resolution to explicitly resolve these severe weather features. In other words, thunderstorm precipitation was selected to describe days with stormy weather because hail and other thunderstorm-related impacts are not directly modeled. Figure 4-4 shows the baseline value of Storm Days, as well as anticipated changes by 2030 and 2060. Unlike the previous temperature-related vectors, there are regions with both increases and decreases in Storm Day frequency. Notable increases occur mainly in the eastern part of the United States, as well as parts of the Northwest. Meanwhile, slight decreases are seen in the southern plains. It is likely that the confidence in, and approaches to, defining the Storm Day vector will rapidly increase in the coming years as higher resolution modeling enhances the capability of modeling small-scale, severe weather phenomena that is of great interest to airport managers and staff. AK AK AK Figure 4-3. Projected changes in CDDs from baseline to 2030 and 2060. Unit: days/year. Hawaii was considered, but omitted from this analysis as GCM grid size is too large to produce reliable atmospheric projections for Hawaii at this time. AK AK AK Figure 4-4. Projected changes in Storm Days from baseline to 2030 and 2060. Unit: days/year. Hawaii was considered, but omitted from this analysis as GCM grid size is too large to produce reliable atmospheric projections for Hawaii at this time.

Understanding Climate Change’s Impact on Airports 19 4.8 Maximum 5-Day Rainfall While the Storm Day vector shows a relatively minimal impact nationwide, likely due to the physical constraints of the GCMs, other measures of rainfall show much more robust changes. One particular measure of rainfall is the maximum accumulated rainfall over any consecutive 5-day period during a calendar year—Heavy Rain 5-Day for short. Figure 4-5 shows the pro- jected changes nationwide. In summary, as the atmosphere warms, it holds more water vapor that can eventually condense and turn to rainfall. This is especially true for heavy rainfall events that rely on moisture convergence. Nearly the entire contiguous United States is expected to see a rise in Heavy Rain 5-Day by 2060, with some increases also evident in 2030. The areas most strongly affected are those that typically receive more rainfall. The Ohio River valley, the Northeast, southern Texas, and the West Coast are all projected to see increases of up to 0.5 inches, or 30 percent, of their baseline value. It is particu- larly important to recognize that this is likely a conservative estimate because of the previously mentioned limitations that GCMs face as a result of their coarse resolution. Numerous scientific studies have suggested that localized extreme events, such as those affecting a specific airport on a specific day, will likely increase at a faster rate than area-wide averages would suggest. 4.9 Other Climate Vectors Projected changes were assessed for the other vectors shown in Table 4-1. In addition to the vectors shown above, all remaining temperature-related vectors listed below showed marked changes, indicating a warming climate: • Very Hot Days, • Freezing Days, • Heating Degree Days, • Hot Nights, and • Humid Days. AK AK AK Figure 4-5. Projected changes in Heavy Rain 5-Day from baseline to 2030 and 2060. Units: inches. Hawaii was considered, but omitted from this analysis as GCM grid size is too large to produce reliable atmospheric projections for Hawaii at this time.

20 Climate Change Adaptation Planning: Risk Assessment for Airports For precipitation vectors, Snow Days displayed decreases nationwide, although there is marked regional variability, with the largest decreases occurring over the intermountain west. Dry Days showed inconclusive changes east of the Mississippi River, but general decreases occurred over the western United States, especially in the arid Southwest. Furthermore, as noted, several vec- tors of interest to airport systems were omitted from this study (wind, fog) because models for these vectors are not yet considered reliable. Despite the limited modeling currently available, it is still possible to provide information about potential adaptation and planning activities for wind and fog, so information about these vectors is included in Appendix A. Please see Appen- dix F for nationwide maps of projected changes to all climate vectors, including the upper and lower boundaries. 4.10 Sea Level Rise Increases in sea level will impact airports through increasing frequency and magnitude of coastal flooding events. This includes increased flood depths during events, increased frequency of nuisance flooding, or in some cases, permanent inundation of airport grounds. Changes in sea level are a result of global and local factors. Global factors include atmospheric temperature, heat transfer to the oceans and subsequent expansion of those water bodies, as well as glacial and ice sheet melting. The primary local factor is vertical land movement, followed by water circula- tion. Trends in sea level are measured by the National Oceanic and Atmospheric Administration (NOAA) at water level monitoring stations (Figure 4-6). Climate change is expected to result in a positive acceleration of historically observed trends in sea level. Projections of future sea levels were developed over short- and long-term planning horizons extending to 2030 (Figure 4-7) and 2060 (Figure 4-8) to assist airport decision makers in recognizing potential exposure to SLR impacts based on an acceleration factor derived from downstream effects of global temperature increases. Global projections in sea level change were estimated and then related to local conditions by incorporating an adjustment based mainly on vertical land movement. The potential exposure to future increases in SLR was categorized Figure 4-6. Historically observed amounts and direction of sea level change for the last half century at NOAA water level monitoring stations.

Understanding Climate Change’s Impact on Airports 21 according to increasing impacts on airport operations and facilities. Exposure to each of these metrics was determined by assessing local changes in coastal flooding metrics against runway elevations from the National Flight Data Center (NFDC) database. The assessment included an analysis of recurrent flooding/permanent inundation and periodic flooding. Recurrent flooding and permanent inundation: SLR will increase nuisance flooding, especially for low-lying sites, resulting in daily or permanent inundation of airport grounds. Events driv- ing this type of flooding would include higher than normal tides and relatively small coastal storms. Such flooding will consist of standing water and/or low-velocity flooding resulting in the Figure 4-7. Increases in sea level at NOAA water level monitoring stations reflecting RCP 8.5 projections for 2030. Figure 4-8. Increases in sea level at NOAA water level monitoring stations reflecting RCP 8.5 projections for 2060.

22 Climate Change Adaptation Planning: Risk Assessment for Airports interruption of operations and damage to infrastructure as a result of water saturation. Inunda- tion was evaluated by comparing future sea level to airport runway elevations. The frequency of recurrent flooding expected in 2030 and 2060 at each airport was calculated by comparing sea level conditions, past water level observations, and representative airport elevations. These attributes are specific to each facility and are summarized in the ACROS tool. Periodic Flooding: Relatively infrequent but substantial flooding from tropical storms, hurri- canes and typhoons, and nor’easters can result in significant impacts to airport facilities. Such flood hazards are captured on the Flood Insurance Rate Maps (FIRMs) developed by the Federal Emergency Management Agency (FEMA). BFEs provided on these maps represent the 1-percent- annual-chance flood condition (also known as the 100-year flood event), which is the regulatory requirement for structure elevation or floodproofing. The relationship between the BFE and a structure’s elevation determines the flood insurance premium. Future changes to BFEs are specific to each facility and are presented in the ACROS tool. For more information about ACROS climate and sea level rise output, please see Chapter 7, The ACROS Tool User Guide.

23 5.1 A Brief Note on Uncertainty The concept of uncertainty inherent to evaluation of future climate outcomes can lead to the belief that climate modeling is not mature enough for decision-making purposes. Largely, this is a function of the difference between the technical usage of the word “uncertainty” and how it is used in common language. A scientist is a professional skeptic, trained to assess possibilities and likelihoods, and in this context, measuring and reporting uncertainty is a necessary, ethical requirement. Rather than signifying unreliability or doubt, the term “uncertainty,” as used by scientists, represents a measure of how well climate scientists know their models. Through their own work as well as the work of the scientific community, they gain a clearer understanding of each model’s strengths and weaknesses, which they are then able to quantify. Relationships between cause and effect may be very clear to a scientist; however, no model can ever be perfect. Therefore, scientists must try to: • Understand where model imperfections lie, • Investigate sources of uncertainty thoroughly, and • State what is known about uncertainty in very stark terms so that the scientific community can make further enhancements or generate guidelines on how to deal with unknowns. In practical terms, the presence of model uncertainty does not indicate that decision makers should ignore model results until model uncertainty has been completely removed. Instead, uncertainty means: • Numerous data inputs and variable interaction options directly affect the resulting accuracy of the output scenarios, and scientists have developed a detailed understanding of modeling strengths. • Scientists are confident that it is time to begin using model information as an important plan- ning tool for improving infrastructure resilience (Melillo et al., 2014). Climate models provide decision makers an additional piece of information for allocating resources when used in com- bination with existing planning tools. • Readers and airport decision makers should be aware that uncertainties exist in any model when interpreting outputs and their applicability to future organizational design, planning, and investments. • Some models are stronger than others (e.g., scientists have more confidence in air tempera- ture models than precipitation models) and from a practical standpoint, projections with higher uncertainty indicate the need to plan for a wider variety of possible futures than do those with lower uncertainty (i.e., higher confidence). C H A P T E R 5 Managing Uncertainty When Planning Based on Projections

24 Climate Change Adaptation Planning: Risk Assessment for Airports • The output of today’s best GCMs match actual historical and current values closely. How- ever, the longer the outlook is for future projections, the wider the range of plausible inputs such as carbon dioxide emissions. Therefore, for even the most scientifically accurate models, uncertainty increases the further into the future modelers investigate. • Models will improve and circumstances (e.g., economy, emissions, population) will change, requiring updates over time. Scientists, planning experts, and other key decision makers worldwide are planning and acting on the projected outcomes of today’s climate models, and the aim of this guidebook and tool is to provide climate information for use in airport planning and operation. 5.2 Airport Sources of Uncertainty (ACRP Report 76) ACRP Report 76: Addressing Uncertainty about Future Airport Activity Levels in Airport Deci- sion Making (Kincaid et al., 2012) discusses sources of uncertainty for air traffic forecasts. Much of the section concerning the uncertainty that airports face is broadly applicable here. While there is no need to reproduce the text in its entirety, the list below touches on the topic areas covered. For additional information on uncertainty in the airport context, please see ACRP Report 76 (http://onlinepubs.trb.org/onlinepubs/acrp/acrp_rpt_076.pdf). • Global, regional, or local economic conditions; • Airline strategy (e.g., changes to services); • Airline restructuring or failure; • Low-cost-carrier growth; • Competition from other airports; • Technology change; • Regulatory and government policy; • Social and cultural factors; • Shock events (e.g., health pandemics); and • Statistical or model error. The last point, “statistical or model error,” is an issue that holds true not only for the demand forecast models that were the focus of ACRP Report 76, but also for the climate models used in this project to develop the screening tool. However, there are a number of procedures and prac- tices to reduce that uncertainty as well as guidelines for dealing with uncertainty. The following sections describe some of these procedures. 5.3 Climate Model Sources of Uncertainty 5.3.1 Uncertainty from the Earth System GCMs are good at predicting climate (long-term averages in weather) and are progressing in their ability to predict shorter-term processes such as El Niño. The occurrence of the events below, which also affect climate, cannot be predicted: • Volcanic eruptions, • Behavior of the sun, and • Future emissions of greenhouse gases. Depending on magnitude, the events above can significantly affect climate for months or years after the fact. While it is possible to accurately model resulting climate scenarios based on these events, the actual occurrence of eruptions, sun behavior, and carbon emissions is difficult to predict.

Managing Uncertainty When Planning Based on Projections 25 5.3.2 Uncertainty from Models The major climate drivers are well understood, and models have been used to successfully replicate past climate and make near-term predictions that have been confirmed by observation. Models capture large-scale processes in the global climate system, but downscaling methods are available to convert model results to the local scale. Modelers typically use a number of different models (“ensembles”) with a number of different inputs to develop a range of future possibilities; adaptation options should ideally reflect that range. Uncertainty comes from a number of different sources in climate models, such as: 1. Modeling approaches/type of model, 2. Assumptions, 3. Inputs, 4. Structures and processes (how the model handles inputs), 5. Sensitivity, 6. Treatment of feedbacks, and 7. Downscaling methods. While not used in this project, downscaling is the set of procedures used to translate GCM outputs into detailed, local predictions of surface conditions. To learn more about the sources of uncertainty in climate models, please see the detailed reference in Appendix G. 5.3.3 How This Project Considers Climate Uncertainty Model confidence for individual vectors is described further in Chapter 4. Sources of uncertainty in model selection and scenario selection, as well as the implications for vulnerability and risk assessment, are noted below. 5.3.3.1 Model Selection For this project, a range of four to seven GCMs informed the database that was used to construct each climate vector. Having more than one GCM simulation provided the research team with an indication of the uncertainty that is always inherent with climate change projec- tions, especially at the decadal time scales that are considered here. For example, if all seven GCMs showed that Ronald Reagan National Airport in Washington, D.C., will see 20 more Hot Days (days above 90°F) in 2060 compared to the present, it is possible to be more confident in this number than if the seven GCMs showed changes of -10, 0, 10, 20, 30, 40, and 50 days. Note that this latter range still averages to 20, but provides much less certainty since one model cannot be chosen as more accurate than another. For practical suggestions on the implica- tions of climate vector uncertainty for planning, design, and engineering, please see Chapter 7, Section 7.6. 5.3.3.2 Scenario Selection Typically, models examine a range of scenarios to develop projections. The IPCC’s AR5 develops four greenhouse gas and aerosol emission scenarios, also called forcing scenarios. These scenarios are abbreviated as RCP 2.6, 4.5, 6.0, and 8.5. These scenarios were selected to describe a reasonable range of possible future scenarios. The lowest, RCP 2.6, describes a low- emissions scenario where emissions peak in 2035, and RCP 8.5 describes increasing emissions. Scenarios examined for this project do not appreciably diverge until after mid-century and the maximum forecast length needed for this project is for the year 2060, so only RCP 8.5 was used. It is recommended that studies considering longer time frames examine multiple forcing scenarios.

26 Climate Change Adaptation Planning: Risk Assessment for Airports 5.3.3.3 Vulnerability, Risk, and Practical Considerations In addition to climate model uncertainty and the airport system uncertainty discussed above, other sources of uncertainty that influence vulnerability and risk include: • The response of airport assets and operations to climate-related impact stressors; • Imperfect knowledge about vulnerabilities to impacts and stressors; and • Multiple possible outcomes from a single projected change (e.g., warmer temperatures may result in either less or more ice, depending on the effect on precipitation). While it is important to understand sources of uncertainty, those sources should not be a bar- rier to planning. Instead, a resilience-focused approach recommends that more uncertainty calls for prioritizing high-risk, high-confidence projections and, for lower-confidence projections, planning to suit a broad range of futures. Please see Chapter 6 for guidance on prioritization and Chapter 7 for guidance on practical considerations for dealing with climate vulnerability uncertainty in engineering, planning, and design.

27 This guidebook suggests strategies for organizing asset vulnerability and risk information using the ACROS tool (see Chapter 7 for the User Guide), but the sections below also outline a methodology for performing an assessment and adaptation planning independent of the tool. The assessment process is illustrated in Step 2 as shown in Figure 2-1. These steps are shown in Figure 6-1. 6.1 Assess Baseline Climate and Projected Climate Changes Several resources are provided within this guidebook and the ACROS tool to support this step of the climate adaptation planning process. Chapter 4 provided an overview of U.S. climate change, and more detailed figures showing model ranges can be found in Appendix F. The ACROS tool provides a site-specific walkthrough of projected changes with outlooks to 2030 and 2060. Baseline conditions and projected changes are summarized in the report generated by the tool. Advisory committees may also obtain their own projections independently. Appendix E: Resources includes a number of sources for projections, and community stakeholders such as local universities and municipal or regional planning groups may also have high-quality local projections. When assessing baseline and projected changes, it is critical to consider both catastrophic and long-term stressors. Managers of exposed facilities are encouraged to consider the projected changes and resultant impacts in both their short- and long-term planning activities. Immediate, catastrophic events may be the most visible face of climate change, but many impacts, like those caused by SLR, are part of a relatively slow process. Informing planning decisions with exposure and risk information in the near term can help spur proactive infrastructure decisions that both reduce existing exposures and avoid future losses. Another key point is that a single climate stressor can result in a range of impacts. It is also important to note than the same type of change (e.g., warming air temperatures) can cause seemingly opposite effects depending on local topography, the season, urbanization, and other factors. Consider the case of winter precipitation in a region that typically experiences snowy winters. On the positive side, warmer winters throughout the United States may translate into less need for snow and ice removal for many airports. Conversely, in some locations, warmer temperatures may result in an increase in ice events (as snow events are replaced by rain, freez- ing rain, and sleet), presenting more severe adverse impacts in some locations. It is important to understand the range of impacts that changing climate may cause. Understanding an airport’s exposure to these impacts will help apprise airport management of areas that may need addi- tional attention and investment, and allow for timely integration into existing planning, design, and construction processes to avoid costly retrofitting expenditures down the line. C H A P T E R 6 Develop Adaptation Options Based on Potential Vulnerabilities

28 Climate Change Adaptation Planning: Risk Assessment for Airports 6.2 Identify Critical Assets and Operations 6.2.1 Inventory Airport Assets and Operations With multiple potential impacts from each climate vector on each airport asset or operation, the next step in the climate change adaptation planning process is to inventory airport assets. This asset list may be partial or it may cover the entire airport system. The ACROS tool has a relatively comprehensive asset list pre-populated with assets and operations common to most airports (discussed in greater detail in Chapter 7). Advisory committees may also wish to exam- ine assets independently of the ACROS tool, in which case asset management systems may be particularly helpful in the inventory phase. Finally, while not addressed directly in this guidebook, advisory committees may also want to communicate with municipalities, departments of transportation, and other entities and agencies who own assets that affect airport operations. Changes in climate are likely to affect operations and infrastructure region-wide. Potential impacts to infrastructure, operations, or ancillary suppliers (e.g., electricity) may represent ongoing challenges, but may also present opportunities. 6.2.2 Critical Assets and Operations Once an airport has defined a list of assets and/or operations with potential impacts from climate change, the next step is to assess two characteristics of each asset and operation, namely criticality and vulnerability. Criticality is defined as the importance of the asset or operation to overall functioning of the airport, and high criticality can reflect a single asset or operation that is a significant component of the airport system, as well as an asset that has a high degree of con- nectivity between other assets and operations within the airport system. Criticality can be defined from a variety of perspectives: • Service/operational. • Public health and safety. • Reputation. • Restoration cost. • Regulatory impacts. Understanding criticality can help airport advisory committees better understand the potential for isolated failures of individual systems to escalate into a domino effect, otherwise known as “cascading failures.” An example of a cascading failure in the airport system could include the fail- ure of a pump station during a heavy precipitation event. The pump failure then results in localized ponding of stormwater. A transformer is inundated by the water, and subsequently fails. Attempts to balance the load across several transformers causes multiple failures, resulting in power loss, electric heat loss, and telecom disruptions over all or part of the airport. In this example, disruption to one, seemingly minor part of the airport system had extensive impact on operations. Discussion of “what-if ” scenarios such as the above can be used to help ascertain asset criticality to airport operations. The following sample definition of criticality is provided in the ACROS tool, although advi- sory committee teams are welcome to define the three tiers to accommodate other dimensions of criticality. An excellent reference on this topic is ACRP Report 69: Asset and Infrastructure Man- agement for Airports—Primer and Guidebook (GHD, Inc., 2012), especially Table E-2 (http:// onlinepubs.trb.org/onlinepubs/acrp/acrp_rpt_069.pdf). 1—Loss of the asset/operation would have a negligible impact on the airport. 2—Loss of the asset/operation would hamper airport function. 3— Loss of the asset/operation would significantly impair or shut down the airport until repair, replacements, etc., were secured. Develop an Adaptation Plan (Independent or Supported by the ACROS Tool) Assess Baseline Climate and Projected Climate Changes Identify Critical Assets and Operations Inventory Asset and Operational Vulnerabilities Prioritize Risks and Incorporate into Stand-Alone or Mainstreamed Documents Figure 6-1. Climate adaptation planning process. Excerpted from Figure 2-1.

Develop Adaptation Options Based on Potential Vulnerabilities 29 6.3 Inventory Asset and Operational Vulnerabilities Based on an airport system inventory developed, the committee can create a matrix of poten- tially affected assets and operations (either independently or with the support of the ACROS tool), noting known or perceived vulnerabilities. Vulnerability is defined as the sensitivity of an asset or operation to a climate stressor. Vulnerability will be highly dependent on the robustness of existing infrastructure and operations to accommodate a specific climate change vector (e.g., higher tem- peratures) as well as the degree of change expected. In addition to infrastructure, various opera- tional departments and their staff could be affected. Both are described in greater detail below. 6.3.1 Asset Condition Major factors that should be considered in assessing asset vulnerability include: • Capacity/current ability to handle relevant conditions, • Age, • State of repair—physical as well as electrical components, and • Deferred maintenance. Similar factors should be considered in assessing operational procedures: • Ability to handle relevant conditions, • Time since last update, • Outstanding updates, and • Training and staffing deficits. 6.3.2 Asset Vulnerabilities to Current Conditions In Chapters 4 and 5, readers were provided with an overview of U.S. climate change using vec- tors that are significant for airport infrastructure and operations. Vulnerabilities from changing climate may not always be readily apparent. In order to understand and rank vulnerability, it is critical to understand current vulnerabilities. Known weaknesses are especially relevant, and staff with first-hand knowledge of the assets or operations under consideration are invaluable resources for this part of the risk assessment. For example, extreme heat events are already damaging transportation infrastructure, including airport runways (Rakich, et al., 2011). As air temperatures increase, heating, ventilation, and air conditioning (HVAC) systems may be taxed beyond capacity, causing failures or significant passenger discomfort. Receiving water ambient temperatures may increase, causing changes in aquatic life, which could, in turn, affect an airport’s regulatory requirements for stormwater dis- charge. Information of this type helps the advisory committee understand the likelihood that an asset or operation will be affected by a number of identified consequences or climate stressors. This scheme assumes that asset and operations at higher risk to negative impacts from identified stress- ors today will continue to be at high risk if the climate drivers that cause these stressors intensify. The following sample definition of vulnerability is provided in the ACROS tool. Advisory committees may use this definition or modify as they see fit. The term “impact” refers to climate stressors, such as floods, higher temperatures, and heavy rainfall events: 1—Asset/operation is unlikely to be affected by this impact. 2—Asset/operation is likely to be impaired by this impact. 3—Asset/operation is likely to be significantly impaired or disabled by impact. In the examples above as well as in the tool, a three-point scale was developed for both vulner- ability and criticality. In the tool, default criticality estimations (on a 1 to 3 scale) are provided.

30 Climate Change Adaptation Planning: Risk Assessment for Airports The defaults were developed by SMEs to reflect common conditions at U.S. airports. The three- point scale is in keeping with the screening-level risk estimate produced by the tool. At this level, finer gradations were not considered appropriate, though the case study process revealed some interest in using finer gradations at some airports. Airports with more time and budget to conduct criticality and vulnerability assessments might consider employing a five- or even a seven-point scale. Table B-1 in Appendix B is available to support the recording of vulnerabilities. Vulnerabili- ties may include infrastructure lifecycle considerations such as age, deferred maintenance, or operational condition (e.g., ramp worker safety due to excessive heat stress). As the airport con- siders vulnerabilities, the following items should also be noted, because they will affect timing and appropriateness of the adaptation activities: • Upcoming asset replacement or retrofits, • Changes in business conditions, • Potential regulatory issues, and • Alterations to airport development plans. Appendix B contains a checklist of typical airport assets and operations included in the ACROS tool. The ACROS tool provides climate change impacts for individual asset categories, as do the appendices to this guidebook. Not all airports will have all assets, and some airports may have different assets, but this list is reasonably comprehensive. Appendix B also contains a list of assets and operations that were not included in the project, but were suggested during the case study and comment period of this project. Although researching, compiling adaptation options, and tying vulnerabilities to climate vectors for these suggested assets and operations was not feasible at the time this guidebook was written, airport advisory committee teams may wish to investigate adaptation options for these items alongside the ACROS-supported planning process or other adaptation activities they may be engaged in. 6.4 Prioritize Risks and Incorporate into Stand-Alone or Mainstreamed Documents Risk prioritization can be broken up into several steps. First, it is often useful to develop an estimate-level ranking scheme to group airport risks. Following the estimate-level grouping, the advisory committee may desire to focus on a sub-set of assets and operations that are a) high- risk, b) high-priority for other reasons (e.g., due to funding availability), or c) both. This guide- book principally focuses on the estimate-level risk ranking, with a brief discussion of deeper investigation for high-priority assets and operations. The ACROS tool streamlines the preliminary assessment by walking users through a process to identify assets and operations unique to the individual airport. It then allows the user to evalu- ate collectively the criticality and vulnerability of airport infrastructure or operations indepen- dently of potential climate changes. The tool provides risk ranking as well as potential adaptation options and planning processes for airport officials to consider as they embark on their own planning, design/construction, and operations assessment programs. The intended outcome of preliminary assessment is either a stand-alone adaptation plan, or one that is integrated into existing airport planning processes or documents (see Chapters 8 and 9). 6.4.1 Estimate-Level Risk Ranking In order to quickly begin grouping higher versus lower risk assets for adaptation prioritiza- tion, a simple three-tier grouping is recommended at this stage of the assessment, as employed

Develop Adaptation Options Based on Potential Vulnerabilities 31 within the ACROS tool. The initial ranking includes the traditional dimensions of risk described in Appendix E (likelihood × consequence = vulnerability), as well as a few additional dimensions: • Timing: a ranking of the climate risk is provided for both the years 2030 and 2060; • Criticality and connectivity: the importance of each asset for overall airport functioning is assessed; and • Magnitude of change to climate vector: a larger change to a more hazardous state is considered of greater importance than smaller changes. This assumption is a simplification, but it is use- ful to help initially distinguish higher and lower risk assets and operations. In keeping with an asset management approach, it is recommended that a risk estimate be provided for each asset and operation. Risks in the tool are provided for 2030 and 2060, provid- ing information about the timing of shifts toward more hazardous conditions. As in the ACROS tool, advisory committee members may also wish to assign relative risks to all climate stressors affecting each asset. Note that in the risk estimate formula below, the projected change in climate vector does not contain a term for likelihood. To include a likelihood term, a site-level, high- resolution analysis would be required that is beyond what this screening estimate can provide. Later in the adaptation process, but prior to engineering and design activities, such an analysis is recommended. The climate change risk estimate used by the tool is simple multiplication: Risk Criticality Vulnerability Climate Vector( ) ( ) ( )= × × ∆ Where: Criticality: an integer from 1–3 (user input). Estimates degree of importance to the airport. Vulnerability: an integer from 1–3 (user input). Estimates the consequence of an individual stressor × likelihood of negative impact to an individual asset (the traditional dimensions of risk). Climate Vector D: the change, in number of days, for each vector (contained in the tool). Estimates magnitude of shift toward more hazardous conditions. This formula is used to rank risks as a first step in developing insight into the airport’s high- est priority risks. The tool uses this formula to break assets and operations into three categories using natural breaks (a statistics-based data clustering method): red, yellow, and blue for higher to lower overall risk. Although the tool and process are not structured to translate risk exposure directly into cost, this qualitative approach provides an initial, reasoned judgment as to the exposures toward which airports could direct their attention and resources. The following example illustrates how the risk estimate works. An airport’s only parking garage with serious drainage issues and projected increases in rainfall intensity might rank as highly critical to the airport from a financial perspective, and it is highly vulnerable to flooding; therefore it has a high estimated risk. Together, the risk ranking above gives a qualitative indica- tion of which risks require action (i.e., high, imminent risks), preparation (high or medium, but longer-term risks), or continued observation (medium or low risks manifesting over the longer term). Airport personnel using the tool may alter the computed priority ranking based on judg- ment, past impacts, and organizational goals. 6.4.2 Develop Resilience-Promoting Adaptation Strategies As discussed above, the definition of a resilient adaptation strategy in the context of climate change adaptation is an action that addresses current and future airport needs at the asset and operational levels, without jeopardizing the flexibility of the airport system as a whole (for

32 Climate Change Adaptation Planning: Risk Assessment for Airports example, by locking an airport into a costly investment or pathway). Therefore, selected adap- tations will need to be cost-effective, in accordance with airport operational and development goals, and suitable for a range of possible futures. This approach is referred to as “no regrets” climate change adaptation, where a risk assessment prompts selection of activities that yield benefits (e.g., cost savings) even in the absence of climate change. In addition to being well- suited for today’s funding constrained environment, this approach also helps absorb some of the uncertainty from factors ranging from future economic conditions to climate projections (see Chapter 5 for more information on uncertainty). The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) (IPCC, 2012) notes that adaptation approaches can include actions that: • Reduce exposure to risks; • Reduce vulnerability; • Improve resilience to changing risks; • Transform an organization or relevant aspects thereof; • Prepare, respond, and recover from impacts; and • Transfer and share risks. Functionally, adaptation projects may be classified as physical, operational, or relational [i.e., involving communication; Transportation Research Circular E-C152 (Transportation Research Board, 2011)]. Another way to categorize adaptations is as follows: 1. Prevention: In addition to providing ways to avoid hazards in the first place, preventative activ- ities are intended to keep hazard problems from getting worse, and are administered through actions that influence the way land is developed and buildings are constructed. They are par- ticularly effective in reducing future vulnerability, especially in areas of an airport property where development has not occurred or capital improvements have not been substantial. 2. Structural Protection: Structural protection measures involve the modification of existing air- port buildings and structures to help them better withstand the forces of a hazard, or removal of the structures from hazardous locations. 3. Natural Resource Protection: Natural resource protection activities reduce the impact of climate change by preserving or restoring an airport’s natural areas and their protective functions. Such areas include floodplains, wetlands, steep slopes, and sand dunes. Park, recreation, or conserva- tion agencies and organizations often implement these protective measures. 4. Infrastructure Projects: Structural adaptation projects are intended to lessen the impact of climate change by modifying the environmental natural progression of the climate change vector through construction. These projects are usually designed by engineers and managed or maintained by public works staff. 5. Emergency Services: Although not typically considered an “adaptation” technique, emer- gency service measures do minimize the impact of extreme weather events on people and property. These commonly are actions taken immediately prior to, during, or in response to an event. They are a key element of managing the residual risk after reducing risk through other adaptation actions. 6. Education, Awareness, and Collaboration: Education, awareness, and collaboration activities engage and educate airport staff, tenants, and other stakeholders about climate change and adaptation. The ACROS tool comes pre-loaded with a number of prevention- and mitigation-oriented adaptation strategies based on adaptation literature and the expert experience and judgment of airport professionals. Adaptation activities may include: • The use of applicable building construction standards; • Hazard avoidance through appropriate land-use practices;

Develop Adaptation Options Based on Potential Vulnerabilities 33 • Relocation, retrofitting, or removal of structures at risk; • Reduction or limitation of the amount or size of the hazard; • Segregation of the hazard from that which is to be protected; • Modification of the basic characteristics of the hazard; • Purchase of additional insurance coverage; • Establishment of a climate change contingency fund; • Provision of protective systems or equipment for both cyber or physical risks; • Establishment of hazard warning and communication procedures; and • Redundancy or duplication of essential personnel, critical systems, equipment, and informa- tion materials. Over 700 impacts, paired with at least one and often several potential adaptations, were included in the tool. Those adaptation options relevant to the airport of interest are shown in the final printout produced by the ACROS tool. While this list represents the best information available in the literature and from SMEs at the time of production, users may find that as tech- nology changes and circumstances demand, the list requires modification. It is ultimately the advisory committee’s role to determine the appropriateness of potential adaptations for their airport. Guidelines and recommendations are provided as follows. 6.5 Refine and Monitor In most cases, the ACROS tool will serve as a starting point for the climate adaptation process, resulting in additional investigation into high-risk, high-priority assets and opera- tions. As discussed previously, high-priority risks include those where the asset or operation is critical to the entire airport system, the climate impact is present and already puts an asset or operation at risk, and the shift toward more hazardous conditions is large and immi- nent. The ACROS risk estimate can serve as a useful method to guide prioritization. It is suggested that airport managers initially focus on assets and operations with moderate to high levels of exposure (“red” and “yellow” risk levels; please see Chapter 7 for more infor- mation). While discussed only briefly here, monitoring changing climate and the success of adaptation activities will alert the advisory committee to needed refinements, as outlined in Figure 6-2. 6.5.1 Climate Information: Update as New Data, Models, and Higher Resolution Information Become Available For moderate- to high-risk assets and operations that are identified as high priority by the advisory committee, airport staff may wish to expand upon what the ACROS tool can offer by conducting independent, detailed assessments of potential risk. In this way, the ACROS tool output serves as a resource for developing a more detailed evaluation of system exposure and potential adaptation efforts to incorporate in ongoing planning efforts. Follow-up assessment activities may include: • A multi-scenario climate analysis examining vectors of interest (as noted above, the ACROS tool uses a single scenario). Differing timelines than those shown in the tool may be examined. • If applicable, investigation of the implications of the climate analysis for engineering and design specifications. • A benefit-cost analysis of the proposed adaptation measures for particular assets to identify optimal solutions. A number of useful resources for supporting these efforts can be found in Appendix E: Resources. Refine and Monitor Climate Information: Update as New Data, Models, and Higher Resolution Information Become Available Criticality: Refine Over Time Vulnerabilities: Update to Reflect Changes in Condition and Design Specifications Activities: Monitor and Revise on 3-5 Year Time Scale or As Needed Figure 6-2. Updates to the climate adaptation planning process. Excerpted from Figure 2-1.

34 Climate Change Adaptation Planning: Risk Assessment for Airports 6.5.2 Criticality and Vulnerability: Update and Refine Over the course of airport operations, previously unidentified system weaknesses may become apparent. Particularly in the wake of an incident or disaster response, adaptation priorities may need to be realigned to address the weakness to the airport system. This perspective also aligns with the concept of adaptive management, which encourages iterative problem solving as an approach to handling uncertainty. Merging adaptive management with risk assessments pro- vides a commonsense, hybrid framework that: • Updates as new information presents itself, • Iterates and adjusts adaptation approaches as necessary, and • Focuses on high-priority adaptations first. This commonsense approach is reflected in the experience of other U.S. airports. The Port Authority of New York and New Jersey underlined the particular importance of developing feasible adaptation strategies for the highest threats (McLaughlin et al., 2011). However, both the scope of the potential adaptation options as well as additional considerations, such as the need to respond to a disaster event, may affect the timing and availability of resources to mitigate identified risks, and should therefore be considered during development of the airport’s adapta- tion plan. Table B-2a in Appendix B provides an example checklist to facilitate comparison of adaptation options. Aspects to consider include the following. • Determine which adaptation option(s) are appropriate to the airport size and other con- straints (e.g., site layout, land availability, regulatory considerations). • Be aware of the schedule of important document updates (master plan, etc.—see Chapter 8) and incorporate adaptation strategies as appropriate. • Identify which adaptations are most time sensitive with respect to projected changes. • Take advantage of any project(s) affecting the operation or asset that are already planned/ underway and facilitate the adaptation. • Use retrofits and repairs as an opportunity to replace sub-optimal components with products or technology that save operating costs over time (Landrum & Brown, Inc., 2012). • Consider adaptation options early in the project design process to ensure efficient, cost- effective adaptation. • Understand the costs of action as well as the costs of inaction. • Consider the adaptations planned over the short term vs. the long term, and leave room in current projects to accommodate planned future adaptation elements. • Look for resilience-promoting adaptation options that are “low-hanging fruit,” i.e., compa- rable to or lower in cost than traditional methods and/or with a rapid return on investment. • Consider lifecycle and resilience elements in the design and construction process. • Be aware of funding availability to support implementation of the adaptation option(s). • Identify the opportunity for partnerships and communicate with airlines, tenants, and state and community contacts as needed. • Educate contractors about projected changes and intended adaptations so they can collabo- rate on achieving specific adaptation goals. In order to adequately assess the points above, consultation with appropriate airport staff, air- lines, and tenants is strongly recommended. It is also important to consider whether options are proven and under direct control of the airport (CDM, 2011), or whether cooperation with exter- nal groups (e.g., a regional transportation authority) will be necessary. Timely implementation of high-priority adaptations owned by those external to the airport will require pro active com- munication and cooperation. Appendix C: Adaptation Implementation Worksheets is available to assist airport users in considering the above criteria when selecting adaptation options. These worksheets can help the airport keep track of which assets and operations will be impacted by

Develop Adaptation Options Based on Potential Vulnerabilities 35 various risks, the selected adaptation option, the priority with which the option will be imple- mented, and the “owner” of the risk. It is also strongly recommended that the advisory committees open a line of communication with airports facing similar impacts. The recorded experience of other airports may provide additional understanding of potential weather or climate impacts as well as information con- cerning the outcome of various adaptation strategies. One example is the Chicago Department of Aviation Sustainable Airport Manual (2010), which is an excellent reference for indepen- dently developing or supplementing the list of adaptation options provided by the tool (see Appendix E). Although the manual does not deal specifically with climate change adaptation, it does identify opportunities to make climate-appropriate selections for particular airport assets, including choice of landscape plants, ASHRAE building guidelines, airfield lighting specifica- tions, and more. The manual also provides links to applicable case studies at airports around the nation. 6.5.3 Activities: Monitor and Revise on a 3–5 Year Time Scale or As Needed Risk assessment using an adaptive management approach is an ongoing process and ideally should be re-evaluated as part of the master planning process or sooner. Other triggers for re-evaluation may include extreme events (e.g., Superstorm Sandy, major dust storms), new information, significant disruptions to climate, and unsatisfactory adaptation performance. Any changes should be incorporated into the adaptation plan. Finally, in acknowledgement of the uncertainty that is part of developing climate projections, it is advisable to study applicable climate metrics (e.g., changes in precipitation duration, frequency, and intensity) in greater detail during the project planning stage for a given airport project. During the design stage, specifications that may improve resilience to climate change can be considered.