Climate Risk Management最新文献

As the relationship between climate change and agricultural production increasingly gains attention, the FAO recommends the adoption of climate-smart agriculture practices (CSAPs) to ensure the stable development of agriculture amidst changing climatic conditions. However, the adoption rate of CSAPs remains low and the effects of livelihood capitals have received little attention. Based on the survey data for 916 farmers in the Jianghan Plain of China, this paper adopts a multivariate Probit model to examine the impact of farmers’ livelihood capitals which are measured by an entropy-TOPSIS approach on their adoption of CSAPs. Our results demonstrate that different livelihood capitals exert various influence on the adoption of CSAPs. Specifically, human, financial, physical, and social capital have positive relationships with pesticide-oriented CSAPs such as integrated pest management (IPM). Natural capital has a positive relationship with seed- and water- oriented CSAPs like tolerant rice varieties (TRV). Natural capital positively relates to soil-oriented CPSPs including rice straw mulching (RSM) while physical capital has a negative effect. Natural and physical capitals have positive relationships with fertilizer-oriented CSAPs like deep placement of fertilizer (DPF). Social and natural capitals have positive relationships with soil-oriented CSAPs such as no-tillage direct seeding (NTDS) while financial capital has a negative effect. Climate factors are also important in the adoption of CSAPs such as TRV and RSM. Finally, policy recommendations are suggested to enhance household livelihood capitals to promote the adoption of each type of CSAP.

Organisations, in the private, public and third sectors, are critical stakeholders and actors in the governance of climate change adaptation. Understanding organisational perceptions of preparedness, risk and response to climate change is important for effective climate adaptation-focused actions and policy design. Our study focuses on two research questions: what factors influence adaptation actions by organisations?, and what do organisations mean by the term ‘adaptation’? To address these, we developed and analysed a national survey of UK-based organisations’ perceptions of adapting to a changing climate, administered in spring 2021 (n = 2,429). Our findings confirm that awareness matters: respondents who reported that their organisation had high levels of concern about climate change risk or threat, and which had greater integration of adaptation within processes, are more likely to take adaptation action. In addition, we find a positive relationship between the occurrence and type of extreme event experienced and increased adaptation action by organisations. However, when asked about specific adaptation measures taken by organisations, examples of mitigation are more frequently mentioned compared to adaptation-type actions. Whether this may signal confusion or conflation of adaptation and mitigation by organisations requires further study. These findings offer critical insights into the perceptions of organisations as pivotal leaders of enacting responses to climate change. A renewed focus on organisational experiences, awareness, attitudes and capacity regarding adaptation can assist in better understanding how organisations can facilitate improved climate-resilient decision-making.

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.