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International assessments of evidence on climate change (e.g. Intergovernmental Panel on Climate Change, IPCC) or national climate change risk assessments (e.g. UK Climate Change Risk Assessment, CCRA) do not offer a sufficiently granular perspective on climate impacts to adequately inform governance of resilience to climate risks at the local level. Using an analysis of UK decision-makers managing and responding to heatwaves and flood risks, this paper argues how more robust local evidence is needed to inform decision-making regarding adaptation options for enhancing local resilience. We identify evidence gaps and issues relating to local climate change impacts, including sources and quality of evidence used, adequacy and accessibility of evidence available, ill-communicated evidence and conflicting or misused evidence. A lack of appreciation regarding how scientific evidence and personal judgement can mutually enhance the quality of decision-making underpins all of these gaps. Additionally, we find that the majority of evidence currently used is reductively based upon socio-economic and physical characteristics of climate risks. We argue that a step change is needed in local climate resilience that moves beyond current physical and socio-economic risk characterisation to a more inclusive co-constitution of social and politically defined climate risks at the local scale that are better aligned with the local impacts felt and needs of stakeholders. [ABSTRACT FROM AUTHOR]

• Analyse the impact of climate change on road transport systems. • Develop a risk prediction tool to reduce climate impact on roads. • Conduct economic analysis of various measures to reduce climate impact on roads. • Conduct an empirical study to provide useful insights for rational risk based climate adaptation. This paper aims to analyse the impacts of climate change to the current and predicted future situations of road transportation in the UK and evaluate the corresponding adaptation plans to cope with them. A conceptual framework of long-term adaptation planning for climate change in road systems is proposed to ensure the resilience and sustainability of road transport systems under various climate risks such as flooding and increased temperature. To do so, an advanced Fuzzy Bayesian Reasoning (FBR) model is first employed to evaluate the climate risks in the UK road transport networks. This modelling approach can tackle the high uncertainty in risk data and thus facilitate the development of the climate adaptation framework and its application in the UK road sector. To examine the feasibility of this model, a nationwide survey is conducted among the stakeholders to analyse the climate risks, in terms of the timeframe of climate threats, the likelihood of occurrence, the severity of consequences, and infrastructure resilience. From the modelling perspective, this work brings novelty by expanding the risk attribute "the severity of consequence" into three sub-attributes including economic loss, damage to the environment, and injuries and/or loss of life. It advances the-state-of-the-art technique in the current relevant literature from a single to multiple tier climate risk modelling structure. Secondly, an Evidential Reasoning (ER) approach is used to prioritise the best adaptation measure(s) by considering both the risk analysis results from the FBR and the implementation costs simultaneously. The main new contributions of this part lie in the rich raw data collected from the real world to provide useful practical insights for achieving road resilience when facing increasing climate risk challenges. During this process, a qualitative analysis of several national reports regarding the impacts posed by climate change, risk assessment and adaptation measures in the UK road sector is conducted for the relevant decision data (i.e. risk and cost). It is also supplemented by an in-depth interview with a senior planner from Highways England. The findings provide road planners and decision makers with useful insights on identification and prioritisation of climate threats as well as selection of cost-effective climate adaptation measures to rationalise adaptation planning. [ABSTRACT FROM AUTHOR]