Creating quantitative scenario projections for the UK shared socioeconomic pathways

The Shared Socioeconomic Pathways (SSPs) were developed as a framework for exploring alternative futures with challenges for climate change mitigation and adaptation. Whilst originally developed at the global scale, the SSPs have been increasingly interpreted at the national scale in order to inform national level climate change policy and impact assessments, including mitigation and adaptation actions. Here, we present a set of quantitative SSP scenario projections, based on narratives and semi-quantitative trends, for the UK (the UK-SSPs) for a wide range of sectors that are relevant to the UK climate research, policy and business communities. We show that a mixed-methods approach that combines computational modelling with an interpretation of stakeholder storylines and empirical data is an effective way of generating a comprehensive range of quantitative indicators across sectors and geographic areas in a specific national context. The global SSP assumptions of low challenges to climate adaptation lead to similar socioeconomic outcomes in UK-SSP1 and UK-SSP5, although based on very different dynamics and underlying drivers. Convergence was also identified in indicators related to more efficient natural resource use in the scenarios with low challenges to climate change mitigation (UK-SSP1 and UK-SSP4). Alternatively, societal inequality played a strong role in scenarios with high challenges to adaptation leading to convergence in indicator trends (UK-SSP3 and UK-SSP4)

Climate change scenario services: From science to facilitating action

The goal of limiting global warming to well below 2°C as set out in the Paris Agreement calls for a strategic assessment of societal pathways and policy strategies. Besides policy makers, new powerful actors from private sector, including finance, have stepped up to engage in forward-looking assessments of a Paris-compliant and climate-resilient future. Climate change scenarios have addressed this demand by providing scientific insights on the possible pathways ahead to limit warming in line with the Paris climate goal. Despite the increased interest, the potential of climate change scenarios has not been fully unleashed, mostly due to a lack of an intermediary service that provides guidance and access to climate change scenarios. This perspective presents the concept of a climate change scenario service, its components, and a prototypical implementation to overcome this shortcoming aiming to make scenarios accessible to a broader audience of societal actors and decision makers

Downscaling population and urban land use for socio-economic scenarios in the UK

Projecting the distribution of population is critical in supporting analysis of the impacts and risks associated with climate change. In this paper, we apply a computational algorithm parameterised for the UK Shared Socioeconomic Pathway (UK-SSP) narratives to create 1-km gridded urban land use and population projections for the UK to the end of the twenty-first century. Using a unimodal neighbourhood function, we model heterogeneity in urban sprawl patterns. The urban land use maps are used as weights to create downscaled population projections. We undertake a model uncertainty analysis using 500 simulations with varying parameter settings per UK-SSP. Results illustrate how sprawl can emerge from scenario conditions even when population numbers decline, and irrespective of socio-economic wellbeing. To avoid negative environmental externalities associated with uncontrolled sprawl, such as in UK-SSP5 and UK-SSP3, planning policies will be vital. Uncertainties about future population development in the UK are higher in rural areas than in urban areas. This has an effect on the competition for land and influences confidence in projections of broader land system change

Safe and just Earth system boundaries.

This is the final version. Available from Nature Research via the DOI in this record. Data availability The data supporting Figs. 2 and 3 are available at https://doi.org/10.6084/m9.figshare.22047263.v2 and https://doi.org/10.6084/m9.figshare.20079200.v2, respectively. We rely on other published datasets for the climate boundary16, N boundary72 (model files are at https://doi.org/10.5281/zenodo.6395016), phosphorus73,74 (scenario breakdowns are at https://ora.ox.ac.uk/objects/uuid:d9676f6b-abba-48fd-8d94-cc8c0dc546a2, and a summary of agricultural sustainability indicators is at https://doi.org/10.5281/zenodo.5234594), current N surpluses129,130 (the repository at https://dataportaal.pbl.nl/downloads/IMAGE/GNM) with the critical N surplus limit72 subtracted, and estimated subglobal P concentration in runoff based on estimated P load to freshwater131 and local runoff data132,133. Current functional integrity is calculated from the European Space Agency WorldCover 10-metre-resolution land cover map (https://esa-worldcover.org/en). The safe boundary and current state for groundwater are derived from the Gravity Recovery And Climate Experiment (http://www2.csr.utexas.edu/grace/RL06_mascons.html) and the Global Land Data Assimilation System (https://disc.gsfc.nasa.gov/datacollection/GLDAS_NOAH025_3H_2.1.html). More information is available in ‘Code availability’ and Supplementary Methods. Source data for Fig. 2 are provided with this paper.Code availability: The code used to produce Figs. 2 and 3 are available at https://doi.org/10.6084/m9.figshare.22047263.v2 and https://doi.org/10.6084/m9.figshare.20079200.v2, respectively. The code used to make the nutrient Earth system boundary layers in Fig. 3 is available at https://doi.org/10.5281/zenodo.7636716. The code used to make the surface water layer in Fig. 3 and derive the subglobal Earth system boundaries for surface water is available at https://doi.org/10.5281/zenodo.7674802. The code to estimate current functional integrity is available at https://figshare.com/articles/software/integrity_analysis/22232749/2. The code to derive the groundwater layer in Fig. 3 and derive the total annual groundwater recharge is available at https://doi.org/10.5281/zenodo.7710540.The stability and resilience of the Earth system and human well-being are inseparably linked1-3, yet their interdependencies are generally under-recognized; consequently, they are often treated independently4,5. Here, we use modelling and literature assessment to quantify safe and just Earth system boundaries (ESBs) for climate, the biosphere, water and nutrient cycles, and aerosols at global and subglobal scales. We propose ESBs for maintaining the resilience and stability of the Earth system (safe ESBs) and minimizing exposure to significant harm to humans from Earth system change (a necessary but not sufficient condition for justice)4. The stricter of the safe or just boundaries sets the integrated safe and just ESB. Our findings show that justice considerations constrain the integrated ESBs more than safety considerations for climate and atmospheric aerosol loading. Seven of eight globally quantified safe and just ESBs and at least two regional safe and just ESBs in over half of global land area are already exceeded. We propose that our assessment provides a quantitative foundation for safeguarding the global commons for all people now and into the future.Stockholm Universit

Creating quantitative scenario projections for the UK shared socioeconomic pathways

The Shared Socioeconomic Pathways (SSPs) were developed as a framework for exploring alternative futures with challenges for climate change mitigation and adaptation. Whilst originally developed at the global scale, the SSPs have been increasingly interpreted at the national scale in order to inform national level climate change policy and impact assessments, including mitigation and adaptation actions. Here, we present a set of quantitative SSP scenario projections, based on narratives and semi-quantitative trends, for the UK (the UK-SSPs) for a wide range of sectors that are relevant to the UK climate research, policy and business communities. We show that a mixed-methods approach that combines computational modelling with an interpretation of stakeholder storylines and empirical data is an effective way of generating a comprehensive range of quantitative indicators across sectors and geographic areas in a specific national context. The global SSP assumptions of low challenges to climate adaptation lead to similar socioeconomic outcomes in UK-SSP1 and UK-SSP5, although based on very different dynamics and underlying drivers. Convergence was also identified in indicators related to more efficient natural resource use in the scenarios with low challenges to climate change mitigation (UK-SSP1 and UK-SSP4). Alternatively, societal inequality played a strong role in scenarios with high challenges to adaptation leading to convergence in indicator trends (UK-SSP3 and UK-SSP4)