Allison Hoadley Anderson
In architecture, mitigation reduces the magnitude of climate change by reducing demand for resources; anticipatory adaptation improves performance against hazards; and planned adaptation creates policies and codes to support adaptation.
Adaptation prepares for a future with intensifying climate conditions. The built environment must prepare for challenges that may be encountered during the service life of the building, and reduce human exposure to hazards. Structures are responsible for about 39% of the primary energy consumption worldwide and 24% of the greenhouse gas emissions, significantly contributing to the causes of climate change. Measures to reduce demand in the initial construction and over the life cycle of the building operation directly impact the climate.
Improving performance against hazards requires a suite of modifications to counter specific threats. Adaptation measures may address higher temperatures, extreme precipitation, stormwater flooding, sea-level rise, hurricanes, drought, soil subsidence, wildfires, extended pest ranges, and multiple hazards. Because resources to meet every threat are inadequate, actions with low costs now which offer high benefits under a range of predicted future climates become high-priority solutions.
Disaster risk is also reduced by aligning policies for planning and construction with anticipated hazards. Climate adaptation policies based on the local effects of climate change are a new tool to communicate risk and share resources. Building codes establish minimum standards for construction, so incorporating adaptation strategies into codes ensures that the resulting structures will survive a range of uncertain futures.
Brenden Jongman, Hessel C. Winsemius, Stuart A. Fraser, Sanne Muis, and Philip J. Ward
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Natural Hazard Science. Please check back later for the full article.
Flooding of rivers and coastlines is the most frequent and damaging of all natural hazards. Between 1980 and 2013, total direct damages exceeded $1 trillion, and at least 220,000 people lost their lives. Events with major economic losses include the 2011 flooding in Thailand ($40 billion) and the 2013 Central Europe floods ($16 billion). Flooding also triggers great humanitarian challenges. The 2015 Malawi floods were the worst in the country’s history and were followed by food shortages across large parts of the country.
Flood losses are increasing rapidly in some world regions, driven by economic development in floodplains and increases in extreme precipitation events and global sea level due to climate change. The biggest increase in flood losses is seen in low-income countries, where population growth is rapid and many cities are expanding quickly. At the same time, evidence shows that adaptation to flood risk is already happening, and that a large proportion of losses can be successfully contained by effective risk management strategies. Such risk management strategies may include floodplain zoning, construction and maintenance of flood defenses, reforestation of land draining into rivers, and use of early warning systems.
To reduce risk effectively, it is important to know the location and impact of potential floods, under current and future social and environmental conditions. In a risk assessment, models can be used to map the flow of water over land after an intense rainfall event or storm surge (the “hazard”). Modeled for many different potential events, this provides estimates of potential inundation depth in flood prone areas. Such maps can be constructed for different scenarios of climate change, based on changes in rainfall, temperature, and sea levels specified in climate change scenarios.
To assess the impact of the modeled hazard, that is, the cost of damage or lives lost, exposure (including buildings, population, and infrastructure) must be mapped using land-use and population density data, as well as construction information. Population growth and urban expansion can be simulated by increasing the density or extent of the urban area in the model. The effects of flood on people and on types of buildings and infrastructure are determined using a vulnerability function. This indicates the damage expected to occur to a structure (or group of people) as a function of flood intensity (i.e., inundation depth and flow velocity).
Potential adaptation measures such as land-use change or new flood defenses can be included in the model, to understand how effective they may be in reducing flood risk. This way, risk assessments can demonstrate the possible approaches available to policy makers to build a less risky future.
Tropical cyclones (TCs) in their most intense expression (hurricanes or typhoons) are the main natural hazards known to humankind. The impressive socioeconomic consequences for countries dealing with TCs make our ability to model these organized convective structures a key issue to better understanding their nature and their interaction with the climate system. The destructive effects of TCs are mainly caused by three factors: strong wind, storm surge, and extreme precipitation. These TC-induced effects contribute to the annual worldwide damage of the order of billions of dollars and a death toll of thousands of people. Together with the development of tools able to simulate TCs, an accurate estimate of the impact of global warming on TC activity is thus not only of academic interest but also has important implications from a societal and economic point of view. The aim of this article is to provide a description of the TC modeling implementations available to investigate present and future climate scenarios.
The two main approaches to dynamically model TCs under a climate perspective are through hurricane models and climate models. Both classes of models evaluate the numerical equations governing the climate system. A hurricane model is an objective tool, designed to simulate the behavior of a tropical cyclone representing the detailed time evolution of the vortex. Considering the global scale, a climate model can be an atmosphere (or ocean)-only general circulation model (GCM) or a fully coupled general circulation model (CGCM). To improve the ability of a climate model in representing small-scale features, instead of a general circulation model, a regional model (RM) can be used: this approach makes it possible to increase the spatial resolution, reducing the extension of the domain considered. In order to be able to represent the tropical cyclone structure, a climate model needs a sufficiently high horizontal resolution (of the order of tens of kilometers) leading to the usage of a great deal of computational power.
Both tools can be used to evaluate TC behavior under different climate conditions. The added value of a climate model is its ability to represent the interplay of TCs with the climate system, namely two-way relationships with both atmosphere and ocean dynamics and thermodynamics. In particular, CGCMs are able to take into account the well-known feedback between atmosphere and ocean components induced by TC activity and also the TC–related remote impacts on large-scale atmospheric circulation.
The science surrounding TCs has developed in parallel with the increasing complexity of the mentioned tools, both in terms of progress in explaining the physical processes involved and the increased availability of computational power. Many climate research groups around the world, dealing with such numerical models, continuously provide data sets to the scientific community, feeding this branch of climate change science.