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Credits for the cover image (left to right, top to bottom):
1. Sebastian Schmitt, heavy summer rainfall in Volgograd, Russia (2009)
2. Francis W. Zwiers, Amphitrite Point Lighthouse, Uclulelet, BC, Canada
3. Sebastian Schmitt, soil cracks after a long and dry summer, West Russian Steppe (2009)
4. Sebastian Schmitt, burning crop residues on an agricultural field in West Russia (2009)
5. Francis W. Zwiers, Hamburg, City Centre, Germany
6. Francis W. Zwiers, Xiaoqikong Bridge, Libo Zhangjiang Scienic Area, Libo County, Guizhou, China
7. Francis W. Zwiers, Xijiang Village, Leishan County, Guizhou, China
8. Sebastian Schmitt, heavy summer rainfall in Volgograd, Russia (2009)
Publisher: Candice Janco
Acquisition Editor: Laura S. Kelleher
Editorial Project Manager: Hilary Carr
Production Project Manager: Swapna Srinivasan
Cover Designer: Mark Rogers
Typeset by SPi Global, India
Contributors
Michael Bahn
Department of Ecology, University of Innsbruck, Innsbruck, Austria
Richard D. Bardgett
Department of Earth and Environmental Sciences, The University of Manchester, Manchester, United Kingdom
Martin Bauch
Leibniz-Centre for the History and Culture of Eastern Europe, Leipzig, Germany
Tamara Ben-Ari
Centre International de Recherche sur l’Environnement et le Développement, Nogent-sur-Marne, France
Kate Boylan
Tonkin + Taylor International, Auckland, New Zealand
Alex J. Cannon
Climate Research Division, Environment and Climate Change Canada,Victoria, BC, Canada
Raphaël d’Andrimont
European Commission, Joint Research Centre, Ispra, Italy
R.J. Dawson
School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
Bart van den Hurk
Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
Marijn van der Velde
European Commission, Joint Research Centre, Ispra, Italy
Markus G. Donat
Barcelona Supercomputing Center, Barcelona, Spain
Karlheinz Erb
Institute of Social Ecology, University of Natural Resources and Life Sciences,Vienna, Vienna, Austria
Bapon (SHM) Fakhruddin
Tonkin + Taylor International; Science Committee Member, IRDR, Auckland, New Zealand
Erich M. Fischer
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
A. Ford
School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
Dorothea Frank
Max-Planck-Institute for Biogeochemistry, Jena, Germany
Carlos F. Gaitán
Benchmark Labs, San Francisco, CA, United States
Fabian Gans
Max Planck Institute for Biogeochemistry, Jena, Germany
Antonio Gasparrini
Department of Public Health, Environments and Society; Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United Kingdom
Debarati Guha-Sapir
Centre for Research on the Epidemiology of Disasters, School of Public Health, Université Catholique de Louvain, Brussels, Belgium
Benoit Guillod
Institute for Environmental Decisions; Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
D. Jaroszweski
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom
Thomas Knoke
TUM School of Life Sciences Weihenstephan, Institute of Forest Management, Technical University of Munich, Freising, Germany
Guido Kraemer
Max Planck Institute for Biogeochemistry, Jena, Germany
Sandra Lavorel
Alpine Ecology Laboratory, UMR 5553, CNRS-Université Grenoble Alpes-Université
Savoie Mont-Blanc, Grenoble, France
Rémi Lecerf
European Commission, Joint Research Centre, Ispra, Italy
Miguel D. Mahecha
Max Planck Institute for Biogeochemistry, Jena, Germany
Marcel Van Oijen
Centre for Ecology & Hydrology, Penicuik, United Kingdom
Brian C. O’Neill
University of Denver, Denver, CO, United States
Carola Paul
Department of Forest Economics and Sustainable Land Use Planning, University of Göttingen; Centre of Biodiversity and Sustainable Land Use, Göttingen, Germany
Claudio Piani
American University of Paris, Paris, France
M. Pregnolato
Department of Civil Engineering, University of Bristol, Bristol, United Kingdom
Anja Rammig
TUM School of Life Sciences Weihenstephan, Technical University of Munich, Professorship for Land Surface-Atmosphere Interactions, Freising, Germany
Markus Reichstein
Max-Planck-Institute for Biogeochemistry, Jena, Germany
Rebekah Robertson
Tonkin + Taylor International, Auckland, New Zealand
Jürgen Scheffran
Institute of Geography, Research Group Climate Change and Security, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, Germany
Carl-Friedrich Schleussner
Climate Analytics, Berlin; Integrative Research Institute on Transformations of HumanEnvironment Systems (IRI THESys), Humboldt-Universität zu Berlin, Berlin; Potsdam Institute for Climate Impact Research, Potsdam, Germany
Francesco Sera
Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom
Jana Sillmann
Center for International Climate Research Oslo (CICERO), Oslo, Norway
Sebastian Sippel
Norwegian Institute of Bioeconomy Research, Ås, Norway; ETH Zürich, Zürich, Switzerland
Jeroen Smits
Global Data Lab, Nijmegen Center for Economics (NiCE), Institute for Management Research, Radboud University, Nijmegen, The Netherlands
Claudia Tebaldi
Joint Global Change Research Institute, College Park, MD, United States
Kirsten Thonicke
Earth System Analysis, Potsdam Institute for Climate Impact Research, Potsdam, Germany
Carolina Vera
Department of Atmospheric and Ocean Sciences, Faculty of Exact and Natural Sciences, University of Buenos Aires; Center for Atmosphere and Ocean Research (CIMA), CONICET-University of Buenos Aires; National Center for Scientific Research (CNRS), Unidad Mixta Internacional (UMI), Argentinean-French Institute for Climate Studies (IFAECI), Buenos Aires, Argentina
Ana M. Vicedo-Cabrera
Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom
Björn Vollan
Working Group for Sustainable Use of Natural Resources, School of Business and Economics, Philipps-University Marburg, Marburg, Germany
Philip J. Ward
Institute for Environmental Studies,Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
Michael F. Wehner
Lawrence Berkeley National Laboratory, Berkeley, CA, United States
Seth Westra
School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, Australia
Alec Wild
Tonkin + Taylor International, Auckland, New Zealand
Miguel A. Zavala
Grupo de Ecología y Restauración Forestal, Departamento de Ciencias de la Vida, Universidad de Alcalá, Edificio de Ciencias, Madrid, Spain
Jakob Zscheischler
Climate and Environmental Physics; Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Acknowledgments
If we want something we have never had, we must do something we have never done before to produce [transformative] results.
The editors would like to acknowledge two interdisciplinary workshops (supported by Future Earth (Berlin 2016) and the European Commission’s Joint Research Centre (Ispra 2017)) that brought together the climate, impact, and stakeholder communities, and that motivated and inspired the present book. The editors further thank the World Climate Research Programme (WCRP) under the Grand Challenge on Weather and Climate Extremes and the Integrated Research on Disaster Risk (IRDR) program for supporting work related to this book and for supporting important collaboration between the climate and disaster risk reduction communities. Both programs, together with Future Earth, have significantly supported the establishment of the global Knowledge Action Network on Emergent Risks and Extreme Events (Risk KAN). The book is meant to contribute to the Risk KAN activities and encourage future work.
Jana Sillmann acknowledges the Research Council of Norway for providing funding to various projects that enabled international and interdisciplinary collaboration with many of the chapter authors and the editors. Relevant projects are Interaction of climate extremes, air pollution and agroecosystems (CiXPAG grant #244551), Physical and statistical analysis of climate extremes in large datasets (ClimateXL grant #243953), Translating weather extremes into the future – a case for Norway (TWEX grant #255037), and Co-design of climate information to support financial decisions (ClimINVEST grant #274250).
CHAPTER 1
Climate extremes and their implications for impact and risk assessment: A short introduction
Jana Sillmanna, Sebastian Sippelb,c
aCenter for International Climate Research Oslo (CICERO), Oslo, Norway
bNorwegian Institute of Bioeconomy Research, Ås, Norway
cETH Zürich, Zürich, Switzerland
1 Introduction
Present and future climate extremes imply adverse impacts, and therefore often pose severe societal challenges across a range of sectors, including, for instance, agriculture, terrestrial and marine ecosystems, health, infrastructure, and might even exacerbate or trigger human conflict (IPCC, 2012). About 90% of all disasters are caused by weather-related hazards, such as floods, storms, extreme temperatures, and droughts (UNISDR, 2015). A combination of these hazards, either sequentially such as a tropical cyclone followed by a heatwave (Lin, 2019), or a concurrent compounding of hazardous factors such as heat and drought (e.g., Mazdiyasni and AghaKouchak, 2015), can be even more disastrous than a single hazard. Moreover, not only the interdependence between hazards but also interactions between hazards, ecosystem or societal responses, and vulnerabilities can amplify the risk (IPCC, 2012).
Extreme event impacts are increasingly recognized, methodologies to address such impacts and the degree of our understanding and prediction capabilities, however, vary widely among different sectors and disciplines. Moreover, traditional climate extreme indices and large-scale multimodel intercomparisons that are used for future projections of extreme events and associated impacts often fall short in capturing the full complexity of impact systems.
While at present most scientific studies are studying individual sectors only, an improved exchange between sectors around methodologies in terms of impact and risk assessment will yield a better understanding of mechanisms and processes driving impacts and systemic risk.
Climate Extremes and Their Implications for Impact and Risk Assessment
Further, on a broader scale, the analysis and understanding of multiple or compound hazards, leading to interconnected and cascading risk, constitute an important emerging research topic (AghaKouchak et al., 2018). Such broad understanding of societal risk related to extreme events might eventually provide the basis for appropriate planning and action for preparedness and increased resilience to these types of events.
The overall aim of this book is to generate synergies across a range of sectors in which the impacts of present and future climate extremes are felt and studied, and how this information can be used in risk assessment. The present book is therefore intended to describe challenges, opportunities, and methodologies for addressing the impacts of climate extremes and the associated risks for different sectors and the society in general, thereby facilitating cross-sectoral discussions and exchange among climate and impact scientists around the human-environment nexus.
2 The quest for impact-relevant climate extreme indices and sectoral impact assessment
In the climate science community, “extremes indices” are widely used to illustrate and quantify changes in the occurrence of weather and climate extremes on regional-to-global scales (Zhang et al., 2011; Sillmann et al., 2013a) and into the future using climate model projections under different emission and socioeconomic scenarios (e.g., Sillmann et al., 2013b). These indices are continuously being further refined (e.g., Russo et al., 2014, 2015) and find widespread application (e.g., IPCC, 2012, 2013). These extreme indices have also been used to constrain allowable CO2 emissions on the basis of regional impact-related climate targets (Seneviratne et al., 2016). However, the definition of these extremes indices is commonly based on a univariate and purely climatological framework, which hinders application in a more impact-oriented setting (e.g., Lemos and Rood, 2010), especially when different types of impacts, across the sectors and potentially interconnected and/or driven by multiple hazards, are to be considered.
To assess the impacts of climate variability and extremes on various sectors, large-scale intercomparison projects using multiple impact models driven by multiple climate models are used (e.g., Frieler et al., 2017). These modeling approaches clearly go beyond simple climate extreme indices, and yield crucial information about the impacts of climate variability and climate extremes. However, the accuracy of the impact estimates generated by these modeling approaches clearly depend on the ability of the impact
models to accurately represent and resolve the relevant mechanisms and processes. Furthermore, accurate impact and risk estimates related to weather and climate extremes that are generated by process models would require a realistic representation of the respective societal or ecosystem vulnerability to these events (IPCC, 2012), which may require, in many sectors, a very good understanding of vulnerability even at local scales (e.g., Birkmann and Wisner, 2006). Moreover, the interconnectedness of risk between different subsystems and complexities along risk cascades during extreme events (AghaKouchak et al., 2018) might lead potentially to an overall underestimation of societal risks in such projects (e.g., Schewe et al., 2019).
3 Embracing complexity and interdisciplinarity in impact and risk assessment
Overall, novel approaches to assess society-relevant impacts and risks related to extreme weather and climate events are needed that put a strong emphasis on transdisciplinary research approaches, methodological exchange across sectors, and building on new capabilities to collect, process, and interpret data.
From a decision-making perspective, a first and crucial step toward society-relevant climate information (or products) is to distinguish between usefulness and usability of climate information (Ehrler, 2015). In that sense, usefulness is about functionality and desirability, and usability is about application and fit. As Lemos and Rood (2010) emphasize: “what scientists ideally perceive as useful may not be applicable or be fit for decisionmaking processes and decision environments in practice.” In order to arrive at useful knowledge, science and scientists must participate in the different decision-making contexts of end users, and together coproduce usable metrics in a demand-driven process. Such a coproduction process is by no means a linear, straightforward process of delivering readily packaged information; rather it implies engaging in a mutual learning process involving numerous trade-offs between salience (relevance and timeliness), credibility (high-quality knowledge), and legitimacy (a fair and transparent process) (Cash et al., 2003; Mitchell et al., 2006). Lourenco et al. (2015) argue “[A] group of researchers and entrepreneurs will need to focus on use-inspired research” as part of a research agenda on climate services. As a first step, such a research agenda should take stock of the vast literature on societal uptake of scientific knowledge (see e.g., Wynne, 1993; Jasanoff, 2004; Hulme, 2009), including the limits of science as a basis for decision-making
(Ford et al., 2013; Rose, 2014). Science, policymaking, decision-making, and innovation are all activities that aim to learn what works under what circumstances (Argyris and Schön, 1978; Latour, 1987; Bennett and Howlett, 1992; Edquist, 1997; Röling and Jiggins, 1998). To develop society-relevant understanding and guidance for adaptation planning, novel and complementary approaches needed to learn about climate impacts in concert, rather than separately, taking into account the multivariate nature of hazards (e.g., Zscheischler et al., 2018), and the connectedness and cascades of societal and ecosystem risks.
In a Future Earth workshopa on Extreme Events and Environments (E3S) in 2016, scientists and stakeholders from diverse fields met to “codesign” research questions addressing urgent societal challenges regarding risks from changing extremes (Nature Editorial, 2016). Among these challenges is the need for a better integration and exchange across various sectors and methodological approaches and eventually be able to predict societal and ecological risks, mediated through vulnerability and exposure of the specific system, and the natural hazards arising from a changing climate. This thread was followed up at a World Climate Research Program (WCRP) supported workshopb in 2017 that aimed to discuss and codevelop “Indicators for climate extremes and socioeconomic impacts under different emission targets” (Sillmann et al., 2018), again with the participation of scientists and stakeholders. It became clear from these discussions that translating an assessment of hazards into an understanding of societal-relevant risk is far from being straightforward. Moreover, impact and risk assessment methods differ widely across sectors.
4 Scope and overview of book content
The present book therefore aims to embrace the different approaches to assess societal-relevant impacts and the risk of climate and weather-related extreme events, including the complexity and interconnectedness of societal risk. The book might serve to create synergies across a range of sectors on how information, data, and methodologies on various levels can be used in impact and risk assessment.
In the first part of the book (Chapters 2–6) an introduction to the physical understanding and modeling of climate extremes and the resulting
hazards is given (a comprehensive review is also available, e.g., IPCC, 2012). This not only includes an introduction to climate scenarios and their relevance for impact studies (Tebaldi and O’Neill, Chapter 2) that provide the basis for modeling future climate change and socioeconomic impact assessment, but also indicates pathways for the human dimension of future change. Donat, Sillmann, and Fischer (Chapter 3) provide an overview of observed changes in univariate indices of climate extremes and expectations for future change. Zscheischler et al. extend the univariate perspective into a multivariate dimension of hazards and argue that it is crucial to take the compounding of various hazards into account for impact and risk assessment (Chapter 4). Next, Piani, Cannon, and Sippel provide an overview of methodologies and challenges related to the correction of biases in model simulations compared to observations, which represents an undesired but unavoidable step in the modeling chain, in order to arrive at usable datasets for quantitative impact modeling (Chapter 5). Wehner (Chapter 6) discusses the occurrence, prediction capabilities, and changes in tropical cyclones as an example for a weather-related extreme event that is in its most direct consequences immediately relevant to society.
In the second part of the book (Chapters 7–11), methodologies to assess the impacts of climate extremes are presented, along with respective case studies, using both state-of-the-art empirical, data-driven impact assessment methods and process-oriented impact models.
In an era with much improved capacities for remote Earth observations, the data-driven impact assessment of climate extremes is expected to become more common in the near future, and an overview of such approaches is given for agricultural impacts in Chapter 7 (Gaitan). Next, van der Velde et al. focus on one specific extreme event that resulted in severe loss in wheat yields in 2016 in France, and showed that traditional crop modeling failed to anticipate the event due to the complexities in its multivariate hazards and the chain of events that led to impacts (Chapter 8). Furthermore, van Oijen used tree growth observations in a probabilistic risk analysis method to analyze both hazard probability and ecosystem vulnerability (Chapter 9). In Chapter 10,Vicedo-Cabrera et al. present an overview of methodologies used for projecting health impacts of climate extremes and discuss the related assumptions and limitations along with a case study on the projection of temperature-related mortality in London. Pregnolato et al. (Chapter 11) finally illustrate and discuss approaches and case studies that analyze the impact of pluvial flooding on the transport infrastructure in the UK and argue for the necessity to adopt systems approaches
in order to address the complexities of extreme event impacts on urban environments.
The third part of the book illustrates challenges and opportunities of inter- and transdisciplinary research on weather and climate extremes and its complexities along with the human-environment nexus and coupled socio-ecological systems (Chapters 12–17). Fakhruddin et al. (Chapter 12) reviews different existing vulnerability and risk frameworks, their strengths and weaknesses, and concludes that risk and vulnerability assessments in the context of disaster risk reduction require multiscale, dynamic, and crossscale approaches and need to consider resilience dimensions. Mahecha et al. (Chapter 13) outline challenges when working with multiple data sets to perform global empirical analyses related to assessing societal risk on a global scale considering different aspects of hazard, exposure, and vulnerability and suggest a way forward. In Chapter 14, Rammig et al. explain the concept of social-ecological resilience using different examples and conclude that diversification of ecosystems as well as societal processes such as ecosystem management and communication strategies is an asset for increased resilience of socio-ecological systems to climate extremes. Bauch (Chapter 15) gives a climate historians’ perspective on the reconstruction of past extreme events with an overview of what kinds of extreme events are described in written historical sources and discusses how this knowledge about past extreme events could be useful to reduce the impacts of and to increase the societal resilience to current and future extreme events. Scheffran focuses (Chapter 16) on the factors and conditions as well as the mechanisms and pathways connecting climate extremes and conflict dynamics, outlines methodological issues in recent literature, and shows results for a diversity of conditions and mechanisms under which climate extremes and policies affect conflict risk or peaceful management and cooperation. Schleussner and Guillod discuss in Chapter 17 discernible differences in the objectives, scope, and methodology in impact science that informs either mitigation policy or adaptation action, and point to the need for identifying synergies and integration between these two domains.
The book concludes with an outlook (Chapter 18, Reichstein et al.) that first describes the role of climate extremes within the broader inter national agenda of climate change mitigation, sustainable development goals, and disaster risk reduction. The “Knowledge Action Network on Emergent Risks and Extreme Events”c is introduced as an opportunity for an open platform
cwww.risk-kan.org
for scientific communities and stakeholders to engage in international and transdisciplinary research to strengthen the resilience of human and natural systems to the impacts of climate extremes and systemic risks under global environmental change.
While impact and risk assessment is inevitably a broad and diverse topic that cannot be conclusively treated in a single book, the present book is meant to facilitate cross-sectoral discussions and exchange that may encourage transdisciplinary research despite the complexities of impact systems. The book is also intended to serve as introduction and educational resource to climate extremes and their impacts at the human-environment interface as well as to outline the challenges and complexities, and thus is hopefully useful and interesting to a wide audience.
Acknowledgments
The authors thank all the participants of the E3S workshop in Berlin and WCRP workshop in Ispra for the interesting discussions that were very inspiring for this book. We particularly acknowledge Erlend Andre T. Hermansen for his contribution to and support in proposing and conducting the E3S workshop session and his input regarding the usefulness of science for decision-making.
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Further reading
Birkmann, J. (2013): Towards Disaster Resilient Societies: Climate Change, Human Security, Risk & Vulnerabilities, second ed., United Nations University Press, 720 pp., ISBN-13: 978-92-808-1202-2.
CHAPTER 2
Climate scenarios and their relevance and implications for impact studies
Claudia Tebaldia, Brian C. O’Neillb
aJoint Global Change Research Institute, College Park, MD, United States
bUniversity
of Denver, Denver, CO, United States
1 Motivation
Future impacts of climate change on societies and the natural environment will be the result of the convergence of several factors. The physical climate characteristics will change, producing hazards whose statistics will differ from current in their frequency and intensity. At the same time, the human dimension of the problem will be changing, with population growing and moving, income levels and distributional aspects evolving, geographic disparity taking new forms, technological progress and policy choices shaping society ways to face the new environment. As societies and their interaction at the national and international scales change, so will exposure and vulnerability to the new climate hazards.
It is relatively easier to confine the analysis of future changes to the physical hazard dimension. Extending the analysis further to impacts, in this case, is done by assuming the same societal conditions as the present. A more realistic view of future changes should tackle a characterization of the dynamics of society as well. Not only different impact outcomes unfold as a consequence, but the possibility of separating the relative importance of the changes in the physical system from the changes in the human system presents itself, and for some analyses, those results may be surprising, especially for physical climate scientists used to focus on their type of change only.
In this chapter, we aim at describing a new scenario framework that has developed over the course of this decade. Through the use of this integrated approach, analysis of future impacts can include, in a consistent manner, both the physical and the societal dimension of the climate change problem. The focus is going to be on integrated assessment models (IAMs) and
Climate Extremes and Their Implications for Impact and Risk Assessment
impacts, adaptation, vulnerability (IAV) sciences side, but we will connect to the climate modeling dimension to elucidate the integrated nature of the scenario framework.
At the end of this chapter we hope to make clear how pathways of emissions driving climate model simulations relate to the socioeconomic pathways developed by the IAM/IAV community, and what type of information these latter types of pathways contain, that can be paired with climate model output to perform a more complete analysis of future impacts.
The set of activities and products that we describe reflects the evolution of the so-called parallel process. The process was envisioned at the outset of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) at an Expert Meeting of the IPCC in Noordwijkerhout, Netherlands, in 2007 (Moss et al., 2008); was further described in Moss et al. (2010); and started with the production of the four Representative Concentration Pathways (RCPs) (van Vuuren et al., 2011a) that underpinned future climate experiments within CMIP5 by providing the external forcings (greenhouse gas emissions and concentrations, aerosols, and land-use changes) as input to the model simulations of the 21st century and beyond (Taylor et al., 2012).
Parallel activities started in 2013 by the IAM and IAV communities, aimed at developing the conceptual framework for the Shared Socioeconomic Pathways, SSPs from now on (Ebi et al., 2014; O’Neill et al., 2014), and their integration with the RCP framework (van Vuuren et al., 2014). In the following sections, we describe these various components, their development, and their connections.
2 Representative concentration pathways for CMIP5
Model output characterizing 21st-century changes from CMIP5 experiments was produced by utilizing four different RCPs describing the evolution of anthropogenic forcings over the course of the century, with idealized extensions to 2300 (van Vuuren et al., 2011b).
The four RCPs were designed to span a wide range of radiative forcing levels: 2.6–8.5 W/m2 by 2100, with two (4.5 and 6.0 W/m2) intermediate levels. In that way, they represent a wide range of future outcomes with regard to the choices of future society and the ability of future technology to curb (or not) the emissions of greenhouse gases and other pollutants, and change the way land is utilized, to face the future evolution of world population and economies and their energy needs. At the time of their development, the range of radiative forcing levels in the RCPs at the end
of the century was representative of the emission scenario literature, as was the case for the major constituent variables representing individual forcing agents. In fact, the word “representative” was chosen to reflect the ability of these pathways, individually and as a set, to be consistent with the wide range of socioeconomic storylines/evolutions in place up to that point.
Pathways of forcings for input to climate model simulations are produced by IAMs. These models take as input, in turn, aggregated drivers like population and gross domestic product (GDP) growth over the century typically at a national or large world regional scale, and, by utilizing assumptions about the level of technological progress, international collaboration, and environmental preservation, produce internally consistent coevolving paths of forcing agents (greenhouse gases, aerosols and ozone, and land use). For the lower, highly mitigated pathways, formalized mitigation policies, usually in the form of carbon taxes, are implemented in order to achieve specified radiative forcing levels or other environmental targets. In the case of the four RCPs, the main drivers of these IAM calculations were taken from existing scenarios in the literature based on SRES storylines (Nakicenovic and Swart, 2000), with mitigation measures (absent in the SRES scenarios, and therefore a new feature of the RCPs and in fact a motivation for their development) added in all cases but for the RCP8.5 predecessor scenario. These preexisting scenarios were updated, and the forcing agents redeveloped at a resolved geographical (gridded in some cases) scale, with harmonization of historical (i.e., observation-based) and future (modeled) forcings.
RCP8.5 represented a future with no mitigation of greenhouse gas emissions and produced climate model simulations resulting in global warming between 2.6°C and 4.8°C (5%–95% probability range based on a Gaussian approximation to the CMIP5 model distribution) compared to the average temperature during the 1986–2005 reference period. At the opposite end of the scenario range, the highly mitigated forcing pathway of RCP2.6 produced the corresponding probability range of 0.3°C–1.7°C, relative to the same reference, with the other two pathways falling in between [see Table 12.2 in Collins et al., 2013]. Socioeconomic drivers for the four RCPs are described in individual papers in the special issue on the RCPs. In particular, RCP2.6 was obtained by applying mitigation policies and hypothesizing the availability of negative emissions through biomass energy with carbon capture and storage (BECCS) to a baseline scenario derived from SRES B2 assumptions, a medium development scenario for population, income, energy use, and land use (van Vuuren et al., 2011c). At the other end of the range, RCP8.5 is a baseline scenario where no
mitigation measures are adopted, derived from updating an SRES A2 scenario. The socioeconomic assumptions that underlie it are of high population and relatively slow income growth, modest rates of technological change, and modest improvements in energy efficiency. The world under RCP8.5 sees high-energy demand and, in the absence of climate change policies, high greenhouse gas emissions.That said, scenario analysis based on RCP8.5 has shown that mitigation policies applied to this scenario could produce pathways consistent with the lower range of radiative forcings, even down to 2.6 W/m2 (Riahi et al., 2011). RCP4.5 and RCP6.0 are described in two separate papers of the same special issue (Thomson et al., 2011; Masui et al., 2011).
3 The second component of the parallel process: The SSPs
The development of socioeconomic pathways consistent with the RCPs started at the same time as the completion of the RCPs development. Its inception is documented by a special issue of Climatic Change (Ebi et al., 2014 being its introductory article) where motivation, process, and rationale for the design of five SSPs is explained.
The five alternative pathways of development are intended to span a space whose two main dimensions are “Challenges to adaptation” and “Challenges to mitigation.” SSP1 occupies a position in that space where both are low, while SSP3 occupies the opposite corner, describing a global society where both challenges are high. SSP4 and SSP5 describe alternative worlds where only one of the two challenges is high. SSP2 occupies the center of the two-dimensional space, with medium challenges foreseen to both adaptation and mitigation, and the closest to a natural evolution of present society as we find among the five future pathways. Both qualitative narratives and quantitative elements of these alternative worlds have been produced, initially in relatively general terms and coarse spatial scale (the world as a whole, or large regions). Subsequent and ongoing work adds details to many aspects, sometimes in a top-down fashion, but not to the exclusion of further development from the ground up, that is, from very specific regional or sectoral research efforts that can add details salient to their targeted use, still consistent with the general narratives and drivers.The results of this enrichment process are called “extended SSPs.”
An important aspect worth highlighting is that SSPs are intended as “reference pathways” , in the sense that they describe a world evolution without considering the effects of climate change and its impacts, and in the
absence of climate policies. This methodological choice is deliberate, not to preempt the production of integrated studies where SSPs and future climate change projections are used jointly in order to study the effects of climate change on society. Similarly, the basic specification of SSPs stops short of describing outcomes of societal development like emissions and land use. The quantitative elements included in the SSPs (population growth and economic growth) together with assumptions about rates of technological progress and widespread adoption, level of equality, international cooperation, attitudes toward environmental conservation, etc., are drivers of these emissions and land use, and are used by IAMs to produce those in the form of forcing pathways used by climate model future simulations.
We list here the main qualitative characteristics of the five SSPs from O’Neill et al. (2017); the more detailed descriptions in that reference lay out narratives that enrich each SSP through many aspects of societal development and their (qualitative) trends. The labels for the SSPs are taken from the latter paper.
SSP1 (Low challenges for mitigation and adaptation) Sustainability—Taking the green road: Sustainable development proceeds at a reasonably high pace, inequalities are lessened, technological change is rapid and directed toward environmentally friendly processes, including lower-carbon energy sources and high productivity of the land.
SSP2 (Moderate challenges for both) Middle of the road:
An intermediate case between SSP1 and SSP3, in which the main components of development occur in line with historical patterns, at a pace that is neither especially high nor low compared to current expectations.
SSP3 (High challenges for both) Regional rivalry—A rocky road:
Unmitigated emissions are high due to low economic growth, a rapidly growing population, and slow technological change in the energy sector, making mitigation difficult. Investments in human capital are low, inequality is high (especially across countries), a regionalized world leads to reduced trade flows, and institutional development is unfavorable, leaving large numbers of people vulnerable to climate change and many parts of the world with low adaptive capacity.
SSP4 (High challenges for adaptation, low for mitigation) Inequality—A road divided:
This is a mixed world where both cross-country and (especially) within-country inequalities prevail, to the point that conflict and unrest become increasingly common. Economic growth is moderate in
industrialized and middle-income countries, while low-income countries lag behind. Challenges to mitigation are low because of the presence of a small, globally connected elite that is relatively well off and has the means and ability to drive technological change so that there is a relatively large mitigative capacity. Challenges to adaptation are high because of a large proportion of low-income, slow-developing populations coping with environmental stresses with limited adaptive capacity and lacking institutional support.
SSP5 (High challenges for mitigation, low for adaptation) Fossil-fueled development—Taking the highway:
In the absence of climate policies, energy demand is high and most of this demand is met with carbon-based fuels. Investments in alternative energy technologies are low, and there are few readily available options for mitigation. Nonetheless, economic development is relatively rapid and itself is driven by high investments in human capital. Improved human capital also produces a more equitable distribution of resources, stronger institutions, and slower population growth, leading to a less vulnerable world better able to adapt to climate impacts. As mentioned, more detailed narratives and rationale for each SSP are available (O’Neill et al., 2017), and quantitative elements for the basic SSPs (population, urbanization, and GDP projections at the country scale) have been produced. In addition, pathways of emissions, land-use changes, energy use and supply and policy costs, elements of which are used as external forcings for the current phase of CMIP future simulations (O’Neill et al., 2016), have been developed by a set of IAMs, with and without applying mitigation policies (Riahi et al., 2017). We describe these scenarios next. Baseline scenarios were developed across IAMs for each of the SSPs, with a resulting range of radiative forcings by 2100 varying between 5 and 8.5 W/m2. Consistently across IAMs the higher level of 8.5 W/m2 was reached only when using quantitative elements consistent with SSP5, suggesting that the level that is sometimes labeled in the popular understanding as “business as usual” is, in fact, the result of only a relatively narrow set of assumptions about the future development of socioeconomic drivers. Mitigation policies applied to the different baseline scenarios produced pathways with radiative forcings down to 6 W/m2 or lower.Two highly mitigated scenarios produced by applying stringent mitigation measures to the baseline scenarios from SSP1 reach the lower end of the radiative forcing range, 1.9 and 2.6 W/m2, and are consistent with scenarios that are likely (given the uncertainty in climate models’ response) to produce warming of
1.5°C and 2.0°C, respectively, above preindustrial warming. Together with higher forcing pathways they are included within ScenarioMIP, which dictates the experimental design for CMIP6 future simulations (O’Neill et al., 2016) in order to inform the analysis of the Paris targets.
These quantitative elements can be downloaded through a database hosted by the International Institute for Applied Systems Analysis (IIASA) at https://tntcat.iiasa.ac.at/SspDb/
Importantly, additional efforts to add details to aspects of the SSP pathways have taken place and continue. One of the added elements is a set of global population projections that are spatially resolved (at a resolution of a one-eighth of a degree) and cover the whole 21st century in decadal increments (Jones and O’Neill, 2016). The population growth in absolute terms and as a rate, and its distinction between rural and urban are consistent with the quantitative and qualitative elements of each SSP at both global and regional scales. Population size and density are important determinants of exposure and vulnerability, and this data set used in recent studies provides us with examples of how SSP information can be combined with information from climate model simulations for an integrated scenario analysis of future changes, which we will describe in the last section of this chapter.
As mentioned above, a deliberate choice was made to develop the SSPs without considering the possible feedbacks on socioeconomic development of climate change impacts. Such feedbacks are in fact the goal of the wide research efforts that SSP development set out to facilitate by providing a baseline case of future development in the absence of climate change effects. Thus, SSPs open the way to analyses that can answer questions about such impacts and, importantly, their uncertainty. The latter aspect is a crucial one, since the level of uncertainty in the size of the impacts and their consequence on socioeconomic development would make any hardwired feedback too limited or rigid in its representation.
4 The integration step: analyzing climate and socioeconomic futures together
A further phase of the integrated scenario framework activities has started. We have described how RCPs for CMIP5 and SSPs have been developed. CMIP6 is underway, and simulations of the 21st century utilize forcing pathways that have been developed from the SSPs quantitative and qualitative specification (Riahi et al., 2017), in most cases with application of mitigation measures according to a formalized set of policy options, costs, and obstacles (Kriegler et al., 2014).
The new set of forcing pathways explores a range of radiative forcing levels that has an additional, lower level added in accordance with the recent post-Paris agreement focus on the low warming target of 1.5C above preindustrial. Trajectories have been developed to reach end-of-century forcing levels similar to the original RCPs, but also to explore new levels according to priorities that the research community has identified since CMIP5. The design of ScenarioMIP (the specific effort within CMIP6 to organize future projections) is fully documented in O’Neill et al. (2016) where the relation between new climate model outcomes and SSPs is also discussed.
In Fig. 1, adapted from O’Neill et al. (2016) the design is represented by colored boxes within the matrix, together with the feasible implementation of trajectories reaching the various radiative forcing targets on the basis of the different SSPs (indicated by white cells).
Shared socioeconomic pa thways
Ens: Initial condition ensemble
Long-ter m extension
Overshoot
Fig. 1 ScenarioMIP design (blue cells—dark gray cells in print version) on the background of feasible combinations of SSPs/RCPs according to Riahi et al. (2017) and Rogelj et al. (2018). Also shown are the levels corresponding to the CMIP5 RCPs as green cells (gray cells in print version). The two lower-right white cells were added to the original figure on the basis of IAM experiments documented in Rogelj et al. (2018) which found that at least one of the IAMs employed in their study was able to mitigate emissions consistently with the 1.9 W/m2 target on the basis of SSP4 and 5. (Adapted from O’Neill, B.C., et al., 2016. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9(9).)
