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This chapter offers results from an artificial simulation exercise that was designed to answer three fundamental questions that lie at the heart of anticipatory adaptation. First, how can confidence in projected vulnerabilities and impacts be greater than the confidence in attributing what has heretofore been observed? Second, are there characteristics of recent historical data series that do or do not portend our achieving high confidence in attribution to climate change in support of framing adaptation decisions in an uncertain future? And finally, what can analysis of confidence in attribution tell us about ranges of “not-implausible” extreme futures vis-à-vis projections based at least implicitly on an assumption that the climate system is static? An extension of the IPCC method of assessing our confidence in attribution to anthropogenic sources of detected warming presents an answer to the first question. It is also possible to identify characteristics that support an affirmative answer to the second. Finally, this chapter offer some insight into the significance of our attribution methodology in informing attempts to frame considerations of potential extremes and how to respond.

In this chapter, an effort has been made to give an overview of the aerodynamic loading on structures due to non-synoptic wind events, mainly tornadoes and downbursts. A brief description of the provisions in the building codes and standards for non-synoptic wind loads is presented. Current state of the art in simulating non-synoptic wind systems to obtain wind loads on structures is also discussed. The primary focus is buildings, bridges, and transmission lines in the discussion of the aerodynamic loading on structures. Finally, some insights are given on how future research in evaluating non-synoptic wind loads on structures might unfold.

Analytical and semi-empirical models are inexpensive to run and can complement experimental and numerical simulations for risk analysis-related applications. Some models are developed by employing simplifying assumptions in the Navier-Stokes equations and searching for exact, but many times inviscid solutions occasionally complemented by boundary layer equations to take surface effects into account. Other use simple superposition of generic, canonical flows for which the individual solutions are known. These solutions are then ensembled together by empirical or semi-empirical fitting procedures. Few models address turbulent or fluctuating flow fields, and all models have a series of constants that are fitted against experiments or numerical simulations. This chapter presents the main models used to provide primarily mean flow solutions for tornadoes and downbursts. The models are organized based on the adopted solution techniques, with an emphasis on their assumptions and validity.

Most building damage occurs at relatively low wind speeds, at or below 50 m s^–1 (112 mph), as certain components fail, such as doors, windows, chimneys, and roof coverings. Rainwater then enters these openings, leading to interior damage. Structural failures usually begin with the removal of gable end walls, roof decking, and poorly attached roof structures as wind speeds increase; the greatest damage occurs at roof level as wind speeds increase with height above the ground. Internal wind pressure effects can lead to additional, more catastrophic damage, such as the removal of walls and ceilings. It is difficult to measure wind speeds directly on buildings as they would have to be instrumented well in advance of the storm, and there is no guarantee the storm would strike them. Furthermore, flying debris can damage pressure sensors on instrumented buildings. Thus, damage evaluators must infer failure wind speeds indirectly by studying damage left behind in the wake of windstorms. Therefore, it is important that damage evaluators know how buildings are constructed to better understand how they fail. This chapter identifies similar failure modes in residential structures regardless of wind type according to information from more than four decades of storm damage surveys. The information presented herein highlights some of the lessons learned in evaluating storm damage to wood-framed residential structures.

There is a clear need to learn more about the exact characteristics of downslope wind storms in order to accurately address relevant topics in environmental aerodynamics and wind engineering. In particular, the characteristics of the atmospheric boundary layer are well known and provided in international standards and textbooks; however, further work is required to elucidate characteristics of downslope wind storms and make these characteristics available in a form suitable for engineering applications. While downslope wind storms have been successfully addressed in the meteorology, climatology, and geophysics communities, the focus of those groups is quite different from the focus in wind engineering; that is, the existing data on characteristics of downslope wind storms are of marginal relevance for engineering applications. It is therefore the scope of this chapter to provide a critical review of the state of the art on characteristics of those local and unique winds in comparison with the typical atmospheric boundary layer. It is expected that this work will encourage a more detailed codification of those winds. Another important goal is to enhance an interdisciplinary collaboration among the meteorology, geophysics, and engineering communities because it is shown in this chapter that the current wind engineering standards do not entirely keep up with the atmospheric physics of downslope wind storms.

Convective storms affect countries worldwide, with billions in losses and dozens of fatalities every year. They are now the key insured loss driver in the United States, even after considering the losses sustained by tropical cyclones in 2017. Since 2008, total insured losses from convective storms have exceeded $10 billion per year. Additionally, these losses continue to increase year over year. Key loss drivers include increased population, buildings, vehicles, and property values. However, other loss drivers relate to construction materials and practices, as well as building code adoption and enforcement. The increasing loss trends pose a number of challenges for the insurance industry and broader society. These challenges are discussed, and some recommendations are presented.

Decision making under questions of deep uncertainty can be vague or specific, open-ended or fixed, easy or hard. This chapter very briefly addresses issues and approaches to decision making on adaptation to climate change. Depending on the research question, a complicated set of multiple approaches and tools may be needed. To highlight the types of approaches, this chapter discusses a variety of decision making tools and relates them to a particular problem: a homeowner choosing whether to do nothing, buy insurance, or elevate their home. The chapter culminates in a table summarizing the pros and cons of a variety of approaches.

Some of the most profound impacts of climate variability and change are expected in the water sector. These include more frequent, severe, and persistent droughts; more frequent, widespread, and extreme floods; more episodic and harmful water pollution episodes. Coping with more variable water supplies alongside rising demand will involve institutional reform, new infrastructure, adjustments to operations, and water demand management. A smarter, decision-led approach to deploying climate information in water management will also be required. This chapter begins with an overview of analytical frameworks for assessing and adapting water resource systems to uncertain climate threats and opportunities. It then gives examples of the diverse sources of information that are being accessed by some water managers to establish plausible ranges of climate change as a basis for decision-making. Examples from Denver, Colorado, and Dublin, Republic of Ireland show how narratives of future system changes and historical data can help test the efficacy of decisions under uncertainty. These two case studies demonstrate how early dialogue and information exchange among practitioners and scientists are fundamental to adaptation planning. In both places, unconventional sources of climate risk information were used to more rigorously stress test water management and planning assumptions. The preferred adaptation decision frameworks were dynamic, iterative, and open-ended. The chapter closes by acknowledging that further development of the decision-making approaches described herein may be needed to evaluate mixtures of adaptation options across multiple sectors.

With the transition from a descriptive construct to a normative concept, resilience has engendered debate as to its appropriateness and effectiveness as a community planning strategy in addressing existing and future threats. In some measure the questions raised are because the role of cultural values in resilience construction has not been fully explored. As communities, cities, and regions strive to enhance resilience, a greater understanding of the importance of cultural values is required. The authors adopt two metaphors are useful in describing how resilience is construction. They use the metaphors to construct a heuristic that incorporates cultural values in resilience construction in a very transparent manner. The heuristic draws upon the theoretical work in cultural values by Mary Douglas, the enhancement of that work by Kahan and others, and by integrating the two into recent work in resilience on assemblage theory.

This chapter summarizes recent research first on the policy prescription of building codes designed with wind engineering principles, then on research concerning how markets for wind-enhanced construction offers other channels for increased resilience. Florida’s statewide building code was enacted after Hurricane Andrew; it was the first statewide building code designed for wind. But non-synoptic systems, such as tornadoes, also cause high levels of damage, so the city of Moore, Oklahoma, adopted a code to address that threat. The first purpose of this chapter is to conduct an analysis of the cost-effectiveness of these codes. An examination of other states that may also justify stronger codes follows. Finally, the chapter reviews research on how real estate markets value voluntary mitigation. Using markets for above-code construction provides opportunities to increase resilience in states where stronger building codes are not adopted.

This chapter is an introduction to tornado storms from an engineering perspective. The material included here relates to warnings and subsequent response by people, the chance of tornado hazard at a location, tornado–structure interaction, and building design for tornadoes for life safety. Other chapters in this handbook, referenced here, give details on interrelated subjects, in this chapter, reader will gain an overview of the available knowledge on tornadoes from an engineering perspective. Other chapters of this handbook and the references at the end of this chapter can provide in-depth understanding of engineering other aspects of tornado.

To quantitatively investigate a gusty wind from the viewpoint of aerodynamic forces, a wind tunnel that can control the rise time of a step-function-like gust was devised and utilized. When the non-dimensional rise time, which is calculated using the rise time of the gusty wind, the wind speed, and the size of an object, is less than a certain value, the wind force is greater than under the corresponding steady wind. Therefore, this wind force is called the “overshoot wind force” for objects the size of orbital vehicles in an actual wind observation. The finding of the overshoot wind force requires a condition of the wind speed recording specification and depends on the object size and the gusty wind speed.

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

Severe winds produced by thunderstorm outflows cause damage to structures and properties worldwide. Due to their high frequency of occurrence, these winds can be considered one of the most high-risk phenomena in the plethora of the dangerous manifestations of the weather in the troposphere. Through the analysis of experimental data that initiated with visual observations and followed with quantitative measurements, the downburst phenomenon was first discovered and measured in the second half of the last century. Since then, the physical processes responsible for downburst formation have been identified thanks to the advances in observing systems, numerical modeling techniques, as well as smaller scale physical experiments carried out under well-controlled and confined conditions. The purpose of this chapter is to summarize what has been learned about kinematics, dynamics, and thermodynamics of downbursts and unveil the physics behind this phenomenon, running through the most relevant discoveries over the last half century in this research field.

Increasing the amount of resilient infrastructure investments in developing countries is key to achieving development goals. Two issues need to be addressed to better support investment decisions. First, analysts need to better integrate the social, economic, and environmental dimensions of investment decisions in their quantitative analyses, given the intertwined objectives of climate change adaptation and poverty reduction. Second, analysts and practitioners need to recognize that the future state of those three dimensions is deeply uncertain and that new techniques need to be used that look for robust investments—performing well under multiple future conditions—rather than an optimal solution under a single prediction of the future. Doing so can be achieved by beginning important decision processes with an integrated model representing technical and socioeconomic factors, and exploring various interventions under many possible futures.

This article reviews the techniques and approaches historically employed to measure non-synoptic wind storms. While most of these efforts have originated from the atmospheric science community, the focus of this article relates to meeting the requirements of the engineering community. While the recognition of the importance of these non-synoptic wind system events is increasing, their engineering-relevant characteristics are still largely unknown. While gaps in knowledge concerning the engineering-relevant aspects of non-synoptic wind systems are plentiful, focused application of high-resolution research instrumentation offers hope to remove many of these unknowns. Future engineering-oriented measurement campaigns will likely make use of both traditional anemometry and remote sensing technologies to document the characteristics of non-synoptic wind systems.

Numerical models have been instrumental in analyzing the wind field of non-synoptic wind storms as it is very difficult to obtain a complete data set from observations alone. Depending on the application, one must decide between mesoscale modeling, microscale modeling, or a combination of the two. Mesoscale modeling considers the full extent of the physics involved in the atmosphere but is limited in the spatiotemporal resolution that can be achieved. On the other hand, microscale modeling can produce a high-fidelity simulation of the wind field, but often lacks in the extent of the physics and physical mechanisms that are simulated. Applications and limitations of these modeling techniques are discussed, as well as the future direction of mesoscale and microscale modeling of non-synoptic wind storms.