Brian C. O’Neill

A new scenario framework for climate change research: the concept of shared socioeconomic pathways

The new scenario framework for climate change research envisions combining pathways of future radiative forcing and their associated climate changes with alternative pathways of socioeconomic development in order to carry out research on climate change impacts, adaptation, and mitigation. Here we propose a conceptual framework for how to define and develop a set of Shared Socioeconomic Pathways (SSPs) for use within the scenario framework. We define SSPs as reference pathways describing plausible alternative trends in the evolution of society and ecosystems over a century timescale, in the absence of climate change or climate policies. We introduce the concept of a space of challenges to adaptation and to mitigation that should be spanned by the SSPs, and discuss how particular trends in social, economic, and environmental development could be combined to produce such outcomes. A comparison to the narratives from the scenarios developed in the Special Report on Emissions Scenarios (SRES) illustrates how a starting point for developing SSPs can be defined. We suggest initial development of a set of basic SSPs that could then be extended to meet more specific purposes, and envision a process of application of basic and extended SSPs that would be iterative and potentially lead to modification of the original SSPs themselves.

A new scenario framework for Climate Change Research: scenario matrix architecture

This paper describes the scenario matrix architecture that underlies a framework for developing new scenarios for climate change research. The matrix architecture facilitates addressing key questions related to current climate research and policy-making: identifying the effectiveness of different adaptation and mitigation strategies (in terms of their costs, risks and other consequences) and the possible trade-offs and synergies. The two main axes of the matrix are: 1) the level of radiative forcing of the climate system (as characterised by the representative concentration pathways) and 2) a set of alternative plausible trajectories of future global development (described as shared socio-economic pathways). The matrix can be used to guide scenario development at different scales. It can also be used as a heuristic tool for classifying new and existing scenarios for assessment. Key elements of the architecture, in particular the shared socio-economic pathways and shared policy assumptions (devices for incorporating explicit mitigation and adaptation policies), are elaborated in other papers in this special issue.

Simulating the Biogeochemical and Biogeophysical Impacts of Transient Land Cover Change and Wood Harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

AbstractTo assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional type (PFT) and wood harvest parameters have been developed. The new parameters capture the dynamics of the Coupled Model Intercomparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005 and for the four representative concentration pathway (RCP) scenarios from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 reveals that the model produced a historical cumulative land use flux of 127.7 PgC from 1850 to 2005, which is in general agreement with other global estimates of 156 PgC for the same period. The biogeophysical impacts of the transient land cover change parameters were cooling of the near-surface atmosphere over land by −0.1°C, through increased surface albedo and reduced shortwa...

A new scenario framework for climate change research: background, process, and future directions

The scientific community is developing new global, regional, and sectoral scenarios to facilitate interdisciplinary research and assessment to explore the range of possible future climates and related physical changes that could pose risks to human and natural systems; how these changes could interact with social, economic, and environmental development pathways; the degree to which mitigation and adaptation policies can avoid and reduce risks; the costs and benefits of various policy mixes; and the relationship of future climate change adaptation and mitigation policy responses with sustainable development. This paper provides the background to and process of developing the conceptual framework for these scenarios, as described in the three subsequent papers in this Special Issue (Van Vuuren et al., 2013; O’Neill et al., 2013; Kriegler et al., Submitted for publication in this special issue). The paper also discusses research needs to further develop, apply, and revise this framework in an iterative and open-ended process. A key goal of the framework design and its future development is to facilitate the collaboration of climate change researchers from a broad range of perspectives and disciplines to develop policy- and decision-relevant scenarios and explore the challenges and opportunities human and natural systems could face with additional climate change.

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

The projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatially explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.

Systematic construction of global socioeconomic pathways using internally consistent element combinations

Shared Socioeconomic Pathways (SSPs) describe alternative outcomes for socioeconomic development. Papers describing the conceptual framework for SSPs refer to challenges to mitigation and to adaptation as fundamental concepts. Identifying which socioeconomic factors are the most important determinants of these challenges, and how to combine them in an internally consistent manner, is critical to scenario design. Here we demonstrate a systematic and traceable approach for identifying and prioritizing scenario elements. In this study, we identify 13 determinants of mitigation and adaptation challenges at a globally aggregated scale based on a survey of 25 experts. In addition, we use 19 expert elicitations and a cross-impact balance analysis to create approximately 1.5 million combinations of trends for these determinants and rank them in terms of internal consistency. Using the 1,000 most consistent combinations, we construct composite metrics for challenges to mitigation and adaptation to uncover distinguishable characteristics for five types of SSPs: those with Low, Medium, and High challenges to both mitigation and adaptation (consistent with SSPs 1–3), and those in which adaptation challenges or mitigation challenges dominate (consistent with SSPs 4–5). We find a distinguishing characteristic for mixed typology SSP4 (low mitigation challenges, high adaptation challenges): High trends for innovation capacity could lower challenges to mitigation but not necessarily challenges to adaptation. We also find that a low trend for quality of governance consistently corresponds to higher challenges to adaptation. These findings are suggestive for future research on the SSPs in particular, while our analytical approach is instructive for scenario development in general.

Scenarios for vulnerability: opportunities and constraints in the context of climate change and disaster risk

Most scientific assessments for climate change adaptation and risk reduction are based on scenarios for climatic change. Scenarios for socio-economic development, particularly in terms of vulnerability and adaptive capacity, are largely lacking. This paper focuses on the utility of socio-economic scenarios for vulnerability, risk and adaptation research. The paper introduces the goals and functions of scenarios in general and reflects on the current global debate around shared socio-economic pathways (SSPs). It examines the options and constraints of scenario methods for risk and vulnerability assessments in the context of climate change and natural hazards. Two case studies are used to contrast the opportunities and current constraints in scenario methods at different scales: the global WorldRiskIndex, based on quantitative data and indicators; and a local participatory scenario development process in Jakarta, showing a qualitative approach. The juxtaposition of a quantitative approach with global data and a qualitative-participatory local approach provides new insights on how different methods and scenario techniques can be applied in vulnerability and risk research.

A new ensemble of GCM simulations to assess avoided impacts in a climate mitigation scenario

There is growing evidence that the role internal variability plays in our confidence in future climate projections has been under-appreciated in past assessments of model projections for the coming decades. In light of this, a 15 member ensemble has been produced to complement the existing 30 member “Large Ensemble” conducted with the Community Earth System Model (CESM). In contrast to the Large Ensemble, which explored the variability in RCP8.5, our new ensemble uses the moderate mitigation scenario represented by RCP4.5. By comparing outputs from these two ensembles, we assess at what point in the future the climates conditioned on the two scenarios will begin to significantly diverge. We find in general that while internal variability is a significant component of uncertainty for periods before 2050, there is evidence of a significantly increased risk of extreme warm events in some regions as early as 2030 in RCP8.5 relative to RCP4.5. Furthermore, the period 2061-2080 sees largely separate joint distributions of annual mean temperature and precipitation in most regions for the two ensembles. Hence, in the CESM’s representation of the Earth System for the latter portion of the 21st century, the range of climatic states which might be expected in the RCP8.5 scenario is significantly and detectably further removed from today’s climate state than the RCP4.5 scenario even in the presence of internal variability.

Historically grounded spatial population projections for the continental United States

Large-scale spatial population projections are of growing importance to the global change community. Spatial settlement patterns are a key determinant of vulnerability to climate-related hazards as well as to land-use and its consequences for habitat, energy use, and emissions of greenhouse gases and air pollutants. Few projections exist of spatial distribution at national or larger scales, and while recent efforts improve on earlier approaches that simply scaled or extrapolated existing spatial patterns, important methodological shortcomings remain and models have not been calibrated to nor validated against historical trends. Here we present spatially explicit 100-year projections for the continental United States consistent with two different scenarios of possible socio-economic development. The projections are based on a new model that is calibrated to observed changes in regional population distribution since 1950, corrects for distorting effects at borders, and employs a spatial mask for designating protected or uninhabitable land. Using new metrics for comparing spatial outcomes, we find that our projections anticipate more moderate trends in urban expansion and coastal settlement than widely used existing projections. We also find that differences in outcomes across models are much larger than differences across alternative socio-economic scenarios for a given model, emphasizing the importance of better understanding of methods of spatial population projection for improved integrated assessments of social and environmental change.

Enhancing engagement between the population, environment, and climate research communities: the shared socio-economic pathway process

Demographers have much to contribute to climate change science. This paper describes a new framework being developed by the climate research community that holds potential as an organizing tool for population–climate scholarship, as well as being useful for identifying demographic research gaps within the climate change field. The shared socio-economic pathways (SSPs) represent plausible alternative trends in the evolution of social and natural systems over the twenty-first century at the scale of the world and large regions. The SSPs can help identify population–environment research gaps by illuminating areas of intersection that will shape climate futures but require deeper scientific understanding—the association between urbanization and energy consumption is an example. Also, to vastly enhance the policy relevance of local case studies, the parameters outlined within the SSPs can offer a basic level of harmonization to facilitate generalization. In this way, the SSP framework can increase the relevance and accessibility of population research and, therefore, offer a mechanism through which demographic science can truly offer policy impact.