How high should we build a dyke today, knowing that it will serve for more than 50 years? This depends on the probability distribution of future temperatures. We review the literature on estimates of future emissions for current/stated policy scenarios and current pledge scenarios. Reviewing expert elicitations, abatement costs of scenarios, learning rates of technologies, fossil fuel supply side dynamics and geoengineering, we argue that scenarios with emissions largely beyond current/stated policy scenarios and largely below current pledge scenarios are relatively unlikely. Based on this, we develop a literature-informed evaluation of the likelihoods of future temperature for use in Value at Risk stress tests in 2030, 2050 and 2100.
Urban Heat Island (UHI) and Heat Waves (HWs) are very important research topics as they have a strong impact on society and their synergies are not enough understood. Urbanisation and global warming are dynamic processes that amplify the UHI intensity and the HWs, as well as their synergies. In this context, it is not a surprise to see that the number of publications tackling the linkages between UHI and HWs has constantly increased in the last decades. The development of new instruments and technologies allowed for consistent improvements in the temporal and spatial resolution of the data that boosted both the monitoring and analysis of the UHI-HW. The use of satellite remote sensing was very limited at the beginning of the analysed period and has become common practice in the last decade. Last, but not least, the interdisciplinary approaches, including physical, social, and economic aspects are more frequent and support the integrated development of the urban areas. Such changes are captured in this review including more than 400 titles, covering the period 1991–2022, aiming to foster further research on emergent climate change risks at urban scales and contextualise the future urban planning. This review provides a comprehensive, accessible and structured overview of the UHI-HW topic as a support for a better understanding of the gaps to be addressed by future research.
Climate adaptation decision making can be informed by a quantification of current and future climate risk. This is important for understanding which populations and/or infrastructures are most at risk in order to prioritise adaptation action. When assessing the risk of overheating in buildings, many studies use advanced building models to comprehensively represent the vulnerability of the building to overheating, but often use a limited representation of the meteorological (hazard) information which does not vary realistically in space. An alternative approach for quantifying risk is to use a spatial risk assessment framework which combines information about hazard, exposure and vulnerability to estimate risk in a spatially consistent way, allowing for risk to be compared across different locations. Here we present a novel application of an open-source CLIMADA-based spatial risk assessment framework to an ensemble of climate projections to assess overheating risk in ∼20,000 schools in England. In doing so, we demonstrate an approach for bringing together the advantages of open-source spatial risk assessment frameworks, data science techniques, and physics-based building models to assess climate risk in a spatially consistent way, allowing for the prioritisation of adaptation action in this vulnerable young population. Specifically, we assess the expected number of days each school overheats (internal operative temperature exceeds a high threshold) in a school-year based on three global warming levels (recent past, 2 °C and 4 °C warmer than pre-industrial). Our results indicate an increase in this risk in future warmer climates, with the relative frequency of overheating at internal temperatures in excess of 35 °C increasing more than at 26 °C. Indeed, this novel demonstration of the approach indicates that the most at-risk schools could experience up to 15 school days of internal temperature in excess of 35 °C in an average year if the climate warms to 2 °C above pre-industrial. Finally, we demonstrate how the spatial consistency in the output risk could enable the prioritisation of high risk schools for adaptation action.
Global climate change has resulted in unusual climatic events of increasing intensity and frequency with severe impacts. An individual disaster is often coupled with another at the same time or in the form of a cascade. Major issues discussed in disaster management range from risks, environmental vulnerability, and resiliency, to the identification of human disaster-inducing land uses and their locations across a region, particularly in watersheds. The accurate identification of these disaster-inducing areas – that is, those locations of land use that may cause or contribute to making downstream impacts worse than they would be in the absence of such land uses – would be of assistance for disaster management agencies in order to mitigate disasters in advance. This study applies spatial autocorrelation statistics to explore the spatial and temporal dynamics associated with compound disasters. The study then utilizes the Soil and Water Assessment Tool (SWAT) to calculate runoff volume and sediment discharge to identify the locations of human disaster-inducing land uses. Our modeling outcomes show that there are various kinds of spatial and temporal clusters among compound disasters, and that certain areas are affected by similar disasters regularly while other locations might be the cause of these regular disasters.
Mountain permafrost warming resulting from climate change increases gravitational hazards. This interdisciplinary study compares the networks of actors involved in managing such hazards in three regions of the European Alps. Interviews were conducted with 40 people (members of local authorities, mountain professionals, and private citizens) at the foot of Mont Blanc (Chamonix, France), in the Vanoise massif (France), and in the canton of Valais (Switzerland). Data were analysed qualitatively and quantitatively using interaction matrices and network diagrams. Communal authorities played a central role but partnered with many other public and private actors. In Valais, collaboration to protect infrastructure and inhabited areas was centred around communal and cantonal authorities. In Chamonix, the network of actors gave a significant role to mountain professionals. In Vanoise, the network was less dense and less well-defined, although actors had high expectations regarding awareness-raising and prevention. Sources of tension existed in all three networks, particularly between authorities and mountain professionals. To strengthen community resilience, authorities should develop more mechanisms for citizen participation in risk management.