The need for and use of socio-economic scenarios for climate change analysis: A new approach based on shared socio-economic pathways

Socio-economic scenarios constitute an important tool for exploring the long-term consequences of anthropogenic climate change and available response options. A more consistent use of socio-economic scenarios that would allow an integrated perspective on mitigation, adaptation and residual climate impacts remains a major challenge. We assert that the identification of a set of global narratives and socio-economic pathways offering scalability to different regional contexts, a reasonable coverage of key socio-economic dimensions and relevant futures, and a sophisticated approach to separating climate policy from counter-factual “no policy” scenarios would be an important step toward meeting this challenge. To this end, we introduce the concept of “shared socio-economic (reference) pathways”. Sufficient coverage of the relevant socio-economic dimensions may be achieved by locating the pathways along the dimensions of challenges to mitigation and to adaptation. The pathways should be specified in an iterative manner and with close collaboration between integrated assessment modelers and impact, adaptation and vulnerability researchers to assure coverage of key dimensions, sufficient scalability and widespread adoption. They can be used not only as inputs to analyses, but also to collect the results of different climate change analyses in a matrix defined by two dimensions: climate exposure as characterized by a radiative forcing or temperature level and socio-economic development as classified by the pathways. For some applications, socio-economic pathways may have to be augmented by “shared climate policy assumptions” capturing global components of climate policies that some studies may require as inputs. We conclude that the development of shared socio-economic (reference) pathways, and integrated socio-economic scenarios more broadly, is a useful focal point for collaborative efforts between integrated assessment and impact, adaptation and vulnerability researchers.     

代表性浓度路径情景下的全球温室气体减排和对中国的挑战

介绍了政府间气候变化专门委员会（IPCC）为第五次评估报告开发的新情景——代表性浓度路径（RCPs）,分析了RCPs情景的内在优势,并描述了4类代表性RCPs（RCP8.5、RCP6、RCP4.5和RCP3-PD）的特征。利用IPCC最新发布的RCPs数据,分析了高端、中端稳定和低端浓度路径下,全球温室气体的排放空间、区域分担和减排成本,并着重探讨了低端路径与全球温度升幅限制在2℃以下目标之间的关系及其给中国带来的主要挑战和应对途径。     

The concepts and development of a participatory regional integrated assessment tool

This paper provides an overview of the development of the ‘Regional Impact Simulator’ – a user friendly software tool designed to allow stakeholders to perform integrated assessments of the effects of climate and/or socio-economic change on the important sectors and resources of two contrasting UK regions. This includes the assessment of agriculture, water resources, biodiversity and coastal and river flooding. The tool arose from the need to further develop the methods applied in the earlier RegIS project, which was the first local to regional integrated assessment in the UK. The limitations of RegIS included very long run times, a limited number of simulations, incomplete linkages between models and no allowance for scenario uncertainty. Based upon the stakeholder needs identified within RegIS, a series of guiding principles were developed with Steering Committee stakeholders, which informed the concept of the ‘Regional Impact Simulator’ including functionality, appearance and complexity. An Integrated Assessment Methodology based upon the Drivers-Pressure-State-Impact-Response (DPSIR) framework facilitated the integration of multiple models, scenarios and datasets within the software interface. The development of the ‘Regional Impact Simulator’ provides a test-bed for further studies of stakeholder-led, regional, integrated assessment, and provides an opportunity to learn the many lessons in undertaking such studies.     

The Shared Socioeconomic Pathways and their energy,land use,and greenhouse gas emissions implications: An overview

This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO₂ emissions of the baseline scenarios range from about 25 GtCO₂ to more than 120 GtCO₂ per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m² that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectoral extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6).     

Spatial variations of sea-level rise and impacts: An application of DIVA

Due to complexities of creating sea-level rise scenarios, impacts of climate-induced sea-level rise are often produced from a limited number of models assuming a global uniform rise in sea level. A greater number of models, including those with a pattern reflecting regional variations would help to assure reliability and a range of projections, indicating where models agree and disagree. This paper determines how nine new patterned-scaled sea-level rise scenarios (plus the uniform and patterned ensemble mean rises) influence global and regional coastal impacts (wetland loss, dry land loss due to erosion and the expected number of people flooded per year by extreme sea levels). The DIVA coastal impacts model was used under an A1B scenario, and assumed defences were not upgraded as conditions evolved. For seven out of nine climate models, impacts occurred at a proportional rate to global sea-level rise. For the remaining two models, higher than average rise in sea level was projected in northern latitudes or around populated coasts thus skewing global impact projections compared with the ensemble global mean. Regional variability in impacts were compared using the ensemble mean uniform and patterned scenarios: The largest relative difference in impacts occurred around the Mediterranean coast, and the largest absolute differences around low-lying populated coasts, such as south, south-east and east Asia. Uniform projections of sea-level rise impacts remain a useful method to determine global impacts, but improved regional scale models of sea-level rise, particularly around semi-enclosed seas and densely populated low-lying coasts will provide improved regional impact projections and a characterisation of their uncertainties.     

The challenge to detect and attribute effects of climate change on human and natural systems

Future scenarios of the energy system under greenhouse gas emission constraints depict dramatic growth in a range of energy technologies. Technological growth dynamics observed historically provide a useful comparator for these future trajectories. We find that historical time series data reveal a consistent relationship between how much a technology’s cumulative installed capacity grows, and how long this growth takes. This relationship between extent (how much) and duration (for how long) is consistent across both energy supply and end-use technologies, and both established and emerging technologies. We then develop and test an approach for using this historical relationship to assess technological trajectories in future scenarios. Our approach for “learning from the past” contributes to the assessment and verification of integrated assessment and energy-economic models used to generate quantitative scenarios. Using data on power generation technologies from two such models, we also find a consistent extent - duration relationship across both technologies and scenarios. This relationship describes future low carbon technological growth in the power sector which appears to be conservative relative to what has been evidenced historically. Specifically, future extents of capacity growth are comparatively low given the lengthy time duration of that growth. We treat this finding with caution due to the low number of data points. Yet it remains counter-intuitive given the extremely rapid growth rates of certain low carbon technologies under stringent emission constraints. We explore possible reasons for the apparent scenario conservatism, and find parametric or structural conservatism in the underlying models to be one possible explanation.     

Assessment of climate information needs in the Argentinean Agro-business sector

The present investigation aims at identifying the needs of the Argentinean agro-business sector for climate research and information. Our approach is focused on any type of climate information from past observations to seasonal prediction and climate change projections. We tried, in particular, to evaluate the possible existence of specific research themes that would be of major interest for these agriculture end-users. We interviewed representatives of seventeen companies from three major agrobusiness sectors: (1) regional/national entities such as agricultural associations, cooperatives and commercial trade boards; (2) insurance companies in the Argentinean agro-insurance market; and (3) large national and international companies representing cereal producers, agro-chemistry and agro-seeds. While all the interviewees recognized the strong influence of climate on their activities, they all pointed out that, at the time of making decision, they considered the political and economic risks rather than the climate one. In many aspects, climate is often considered as a fatality against which it is difficult to be protected. An interesting result is the confidence of the private sectors in the climate information provided by public sources (INTA, SMN, Universities) although they contract private consultants for frequent reports and tendencies. Finally, we explain how such sectors could make a better use of climate information (seasonal prediction, climate change scenarios) that could be integrated in their business projections. In particular, the development of new financial contracts (climate derivatives) open in countries with a relatively poor insurance history new ways to protect the different agricultural sectors, from the producer to large companies.     

Climate and Water: From Climate Models to Water Resources Management and Vice Versa

This article reviews the recent developments in the functional chain from climate models to climate scenarios, through hydrology all the way to water resources management, design and policy making. Although climate models, such as Global Circulation Models (GCMs) continue to evolve, their outputs remain crude and often even inappropriate to watershed-scale hydrological analyses. The bridging techniques are evolving, though. Many families of regionalization technologies are under progress in parallel. Perhaps the most important advances are in the field of regional weather patterns, such as ENSO (El Niño-Southern Oscillation), NAO (North Atlantic Oscillation) and many more. The gap from hydrology to water resources development is by far not that wide. The traditional and contemporary practices are well in place. In climate change studies, the bottleneck is not in this link itself but in the climatic input. The tendency seems to be towards integrated water resources assessments, where climate is only one among many changes that are expected to occur, such as demography, land cover and land use, economy, technologies, and so forth. In such a pragmatic setting a risk–analytic interpretation of those scenarios is often called for. The above-outlined continuum from climate to water is a topic where the physically based modelers, the empiricists and the pragmatists should not get restricted to their own way of thinking. The issues should develop hand in hand. Perhaps the greatest challenge is to incorporate and respect the pragmatic policy-related component to the two other branches. For this purpose, it is helpful to reverse the direction of thinking from time to time to start—instead of climate models—from practical needs and think how the climate scenarios and models help really in the difficult task of designing better water structures, outline better policies and formulate better operational rules in the water field.     

A spatially explicit scenario-driven model of adaptive capacity to global change in Europe

Traditional impact models combine exposure in the form of scenarios and sensitivity in the form of parameters, providing potential impacts of global change as model outputs. However, adaptive capacity is rarely addressed in these models. This paper presents the first spatially explicit scenario-driven model of adaptive capacity, which can be combined with impact models to support quantitative vulnerability assessment. The adaptive capacity model is based on twelve socio-economic indicators, each of which is projected into the future using four global environmental change scenarios, and then aggregated into an adaptive capacity index in a stepwise approach using fuzzy set theory. The adaptive capacity model provides insight into broad patterns of adaptive capacity across Europe, the relative importance of the various determinants of adaptive capacity, and how adaptive capacity changes over time under different social and economic assumptions. As such it provides a context for the implementation of specific adaptation measures. This could improve integrated assessment models and could be extended to other regions. However, there is a clear need for a better theoretical understanding of the adaptive capacity concept, and its relationship to the actual implementation of adaptation measures. This requires more empirical research and coordinated meta-analyses across regions and economic sectors, and the development of bottom-up modelling techniques that can incorporate human decision making.     

Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century

This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment Summary

This special issue of Climatic Change describes an effort to improve methodology for integrated assessment of impacts and consequences of climatic change. Highlights of the seven foregoing Parts (papers) that constitute this special issue are summarized here. The methodology developed involves construction of scenarios of climate change that are used to drive individual sectoral models for simulating impacts on crop production, irrigation demand, water supply and change in productivity and geography of unmanaged ecosystems. Economic impacts of the changes predicted by integrating the results of the several sectoral simulation models are calculated through an agricultural land-use model. While these analyses were conducted for the conterminous United States alone, their global implications are also considered in this summary as is the need for further improvements in integrated assessment methodology.     

Challenges to scenario-guided adaptive action on food security under climate change

This paper examines the development and use of scenarios as an approach to guide action in multi-level, multi-actor adaptation contexts such as food security under climate change. Three challenges are highlighted: (1) ensuring the appropriate scope for action; (2) moving beyond intervention-based decision guidance; and (3) developing long-term shared capacity for strategic planning. To overcome these challenges we have applied explorative scenarios and normative back-casting with stakeholders from different sectors at the regional level in East Africa. We then applied lessons about appropriate scope, enabling adaptation pathways, and developing strategic planning capacity to scenarios processes in multiple global regions. Scenarios were created to have a broad enough scope to be relevant to diverse actors, and then adapted by different actor groups to ensure their salience in specific decision contexts. The initial strategy for using the scenarios by bringing a range of actors together to explore new collaborative proposals had limitations as well as strengths versus the application of scenarios for specific actor groups and existing decision pathways. Scenarios development and use transitioned from an intervention-based process to an embedded process characterized by continuous engagement. Feasibility and long-term sustainability could be ensured by having decision makers own the process and focusing on developing strategic planning capacity within their home organizations.     

Application of stochastic simulation to climatic-change studies

Stochastic modelling provides a tool for exploring the full implications of the statistical behavior of historical records and can be used to predict the changing probabilities that events of various magnitudes will occur for different climatic change scenarios. Two simulation models are presented, one for daily air temperature, and the other for daily precipitation. The simulation procedures are: (1) extract salient parameter values from historical records; (2) simulate long sequences of data using the stochastic models, with or without a climatic change scenario as provided by a general circulation model; and (3) using the simulated data as inputs, derive the probability distributions of other variables based on known deterministic or probabilistic relationships between the input and the predicted variables.Given a doubling of carbon dioxide concentration in the atmosphere, the climatic models produce varying degrees of temperature and precipitation changes. Examples of application, including the derivation of snowfall and riverice data using simulated temperature and precipitation, illustrate that stochastic modelling offers a suitable approach to quantify the possible hydrologic impacts of climatic change.     

The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development,with an example from Brazil

The main drawback of the Story-and-Simulation approach is the weak link between qualitative and quantitative scenarios. A semi-quantitative tool, Fuzzy Cognitive Mapping, is introduced as a possible improvement. An example from the Brazilian Amazon shows that by including an integrated set of factors and feedbacks, Fuzzy Cognitive Maps can capture (future) dynamics of deforestation. The example substantiates the tool's capacity to improve the consistency of narrative storylines and the diversity of quantitative models. The tool is designed, however, to be simple and therefore has important drawbacks. Future improvements should be made in the light of applications within a larger toolbox of scenario methods.     

Linking model design and application for transdisciplinary approaches in social-ecological systems

As global environmental change continues to accelerate and intensify, science and society are turning to transdisciplinary approaches to facilitate transitions to sustainability. Modeling is increasingly used as a technological tool to improve our understanding of social-ecological systems (SES), encourage collaboration and learning, and facilitate decision-making. This study improves our understanding of how SES models are designed and applied to address the rising challenges of global environmental change, using mountains as a representative system. We analyzed 74 peer-reviewed papers describing dynamic models of mountain SES, evaluating them according to characteristics such as the model purpose, data and model type, level of stakeholder involvement, and spatial extent/resolution. Slightly more than half the models in our analysis were participatory, yet only 21.6% of papers demonstrated any direct outreach to decision makers. We found that SES models tend to under-represent social datasets, with ethnographic data rarely incorporated. Modeling efforts in conditions of higher stakeholder diversity tend to have higher rates of decision support compared to situations where stakeholder diversity is absent or not addressed. We discuss our results through the lens of appropriate technology, drawing on the concepts of boundary objects and scalar devices from Science and Technology Studies. We propose four guiding principles to facilitate the development of SES models as appropriate technology for transdisciplinary applications: (1) increase diversity of stakeholders in SES model design and application for improved collaboration; (2) balance power dynamics among stakeholders by incorporating diverse knowledge and data types; (3) promote flexibility in model design; and (4) bridge gaps in decision support, learning, and communication. Creating SES models that are appropriate technology for transdisciplinary applications will require advanced planning, increased funding for and attention to the role of diverse data and knowledge, and stronger partnerships across disciplinary divides. Highly contextualized participatory modeling that embraces diversity in both data and actors appears poised to make strong contributions to the world’s most pressing environmental challenges.     

Time-Series Modeling and Prediction of Global Monthly Absolute Temperature for Environmental Decision Making

A generalized,structural,time series modeling framework was developed to analyze the monthly records of absolute surface temperature,one of the most important environmental parameters,using a deterministicstochastic combined(DSC) approach.Although the development of the framework was based on the characterization of the variation patterns of a global dataset,the methodology could be applied to any monthly absolute temperature record.Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal,involving polynomial functions and the Fourier method,respectively,while stochastic processes were employed to account for any remaining patterns in the temperature signal,involving seasonal autoregressive integrated moving average(SARIMA) models.A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years.The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors,suggesting that DSC models,when coupled with other ecoenvironmental models,can be used as a supplemental tool for short-term(～10-year) environmental planning and decision making.     

Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation

The scientific community is now developing a new set of scenarios, referred to as Shared Socio-economic Pathways (SSPs) that will be contrasted along two axes: challenges to mitigation, and challenges to adaptation. This paper proposes a methodology to develop SSPs with a “backwards” approach based on (i) an a priori identification of potential drivers of mitigation and adaptation challenges; (ii) a modelling exercise to transform these drivers into a large set of scenarios; (iii) an a posteriori selection of a few SSPs among these scenarios using statistical cluster-finding algorithms. This backwards approach could help inform the development of SSPs to ensure the storylines focus on the driving forces most relevant to distinguishing between the SSPs. In this illustrative analysis, we find that energy sobriety, equity and convergence prove most important towards explaining future difference in challenges to adaptation and mitigation. The results also demonstrate the difficulty in finding explanatory drivers for a middle scenario (SSP2). We argue that methodologies such as that used here are useful for broad questions such as the definition of SSPs, and could also be applied to any specific decisions faced by decision-makers in the field of climate change.     

Using moisture conservation to evaluate oceanic surface freshwater fluxes in climate models

We apply a diagnostic based on moisture conservation in the atmosphere, integrated over planetary-scale ocean basins and drainage areas to evaluate freshwater fluxes over the ocean surface to three generations of the Hadley Centre climate model (HadCM3, HadGEM1 and HadGEM2-AO). The coherent inclusion of runoff by the diagnostic enables model surface freshwater fluxes to be compared directly with observational estimates of precipitation, evaporation and river discharge. We also introduce a normalised metric, based on model-observation RMS differences, to assess the representation of the fluxes by the model. This methodology could be a powerful tool for evaluating model performance during future model development and model intercomparison exercises. Using this diagnostic, and defining the drainage areas from the global river routing model TRIP, we obtain large-scale surface oceanic fluxes from ERA40 and NCAR-NCEP reanalysis data, which we compare with analogous budgets computed from a set of individual observational estimates of evaporation, precipitation and river discharge. The sum of errors in the Hadley Centre climate model in all ocean basins suggests a steady improvement over the three generations of the model. However, an analysis of sources and sinks of water vapour shows common errors in the models, like an excess of evaporation in the tropical-subtropical Atlantic, and a surplus of water vapour export from tropical-subtropical areas to the mid-latitude regions, making the oceanic surface fluxes too fresh at mid latitudes. Errors in the models are consistent with an excessively strong hydrological cycle.