UK Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK; Soil Geography and Landscape Group, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, the Netherlands.
UK Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.
Sci Total Environ. 2021 Feb 20;756:143172. doi: 10.1016/j.scitotenv.2020.143172. Epub 2020 Nov 16.
As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale.
随着应对全球变暖的压力变得日益紧迫,纳入多个社会、经济和环境驱动因素的情景分析对于支持政府和其他利益相关者规划气候变化减缓和适应行动变得越来越重要。这导致了最近在多个尺度上对未来情景分析的爆炸式增长,自政府间气候变化专门委员会 (IPCC) 研究界共同社会经济途径 (SSPs) 和代表性浓度途径 (RCPs) 发展以来,这一趋势进一步加速。虽然 RCPs 已被广泛应用于气候模型,以在多个尺度上生成气候情景,以研究气候变化的影响、适应和脆弱性 (CCIAV),但 SSPs 最近才被扩展用于不同的地理和部门应用。在英国,这一点可见一斑,该国进行了大量投资,以根据 RCP 生成英国气候预测 (UKCP18),但不存在 SSP 的英国版本。我们通过开发一组多驱动定性和定量的英国 SSPs 来满足这一需求,该方法采用了最先进的情景方法,将与本地相关的驱动因素和指标的国家利益相关者知识与来自欧洲和全球 SSPs 的更高层次信息相结合。这是通过一个密集的参与性过程实现的,该过程促进了自上而下和自下而上方法的结合,以开发一组具有本地全面性但与全球和欧洲 SSPs 一致的英国特定 SSPs。由此产生的情景平衡了一致性和合法性的重要性,表明分歧不一定是不一致的结果,也不是为了在适当的规模上对叙述进行情境化而做出的选择。