ED33B-0590: Engaging with Complexity in an Undergraduate Climate Science Course Through Debate

Are human or natural influences more important to current climate? The goals of this debate are to get students to see the complexity of the climate system and that both human and natural causes have a significant impact on current climate. We can’t fully describe climate change without considering both. Student facing instructions: • Are natural factors (e.g., solar variability, volcanoes, Milankovitch cycles) or human activities (e.g., fossil fuel combustion, deforestation, industrial emissions) the primary cause of modern climate change? • Each team will prepare a short argument using evidence. • Each team will then have a chance to respond to the argument made by the opposing team. • Each team will give a closing remark. Instructor Notes: • 10 minutes to prepare before assigned a position • 5 minutes to prepare after assigned a position • 5 minutes after initial arguments to prepare a response • 5 minutes after responses to prepare a closing remark Reflection Prompts: • Did any opposing points make you reconsider or refine your argument? • What evidence was most persuasive in the debate? • Did you hear any common misconceptions during the debate? • How can we effectively communicate the difference between natural and human driven climate changes to the public? • What additional data or scientific studies would help strengthen the arguments made in the debate? How has temperature changed during the 20th century? The goals of this debate are to get students to see how data can be manipulated or misrepresented to make a specific claim and to highlight the importance of focusing on what the data is telling you, not what you want to see in it. It is easy to see what you want to see in the data if you go in expecting to see a certain thing. Student facing instructions: • Use the data to support your assigned claim (20 minutes to prep) o Must include at least three rates of change with at least one involving the average over multiple years o Craft a compelling argument to share with the class o Identify and address a limitation or assumption you made • Critique another group’s claim (10 minutes to prep) o Identify the strengths of their argument o Spot potential cherry-picking o Suggest what might be missing from their argument or ways they could strengthen their claim • Full-class Debrief Instructor Notes: • Student handout includes graph and table of contiguous U.S. average temperatures from 1895 through 2024. • Student arguments o Temperatures have increased during the 20th century o Temperatures have decreased during the 20th century o Temperatures have not changed during the 20th century Reflection Prompts: • What did this activity reveal about calculating and interpreting rates of change? • Why do scientists use long-term trends rather than individual intervals? • Where is the line between data interpretation and data manipulation? • What are some real-world consequences of misleading presentations of climate data? • What would you look for if someone showed you a graph to prove a climate trend? Year Temperature [°F] 1895 50.33 1896 51.98 1897 51.54 1898 51.42 1899 50.99 1900 52.76 1901 51.86 1902 51.57 1903 50.61 1904 51.15 1905 50.99 1906 51.72 1907 51.47 1908 52.07 1909 51.42 1910 52.41 1911 52.02 1912 50.22 1913 51.53 1914 51.83 1915 51.43 1916 50.84 1917 50.05 1918 51.85 1919 51.54 1920 51.07 1921 53.79 1922 52.02 1923 51.63 1924 50.57 1925 52.51 1926 51.94 1927 52.14 1928 51.91 1929 50.85 1930 51.97 1931 53.52 1932 51.72 1933 52.98 1934 54.09 1935 51.88 1936 52.14 1937 51.54 1938 53.17 1939 53.25 1940 51.88 1941 52.64 1942 51.83 1943 52.06 1944 51.82 1945 51.74 1946 52.94 1947 51.91 1948 51.6 1949 52.01 1950 51.38 1951 51.11 1952 52.27 1953 53.35 1954 53.32 1955 51.68 1956 52.33 1957 52.03 1958 51.92 1959 52.1 1960 51.43 1961 51.86 1962 51.89 1963 52.25 1964 51.67 1965 51.67 1966 51.48 1967 51.75 1968 51.31 1969 51.49 1970 51.6 1971 51.65 1972 51.36 1973 52.28 1974 52.26 1975 51.49 1976 51.46 1977 52.54 1978 51.04 1979 50.88 1980 52.38 1981 53.11 1982 51.33 1983 51.87 1984 51.97 1985 51.29 1986 53.31 1987 53.32 1988 52.62 1989 51.82 1990 53.5 1991 53.15 1992 52.59 1993 51.25 1994 52.85 1995 52.65 1996 51.88 1997 52.19 1998 54.22 1999 53.87 2000 53.25 2001 53.68 2002 53.2 2003 53.24 2004 53.08 2005 53.63 2006 54.24 2007 53.64 2008 52.28 2009 52.38 2010 52.98 2011 53.17 2012 55.27 2013 52.42 2014 52.53 2015 54.38 2016 54.9 2017 54.54 2018 53.51 2019 52.66 2020 54.36 2021 54.5 2022 53.38 2023 54.36 2024 55.51 Does the distance to the Sun or Earth’s albedo have a greater impact on Earth’s temperature? The goal of this debate is to highlight the complexity of the climate system. These two factors each have a large impact, and we can’t fully describe Earth’s climate without considering both. Student facing instructions: • Which has a greater impact on Earth’s temperature: Earth’s distance from the Sun or changes in Earth’s albedo? • Each team will prepare a short argument using evidence. • Each team will then have a chance to respond to the argument made by the opposing team. • Each team will give a closing remark. Reflection Prompts: • Which factor has the potential to cause faster temperature changes and why? • How might these two factors interact over long timescales? • If you could control only one of these – solar input or Earth’s albedo – to stabilize Earth’s temperature, which would you choose and why? Which radiative forcing should be targeted to best mitigate climate change? The goals of this debate are to put students into the shoes of policy makers and help them to understand why climate mitigation has been difficult to manage. This brings a more real life and human element to the class and forces them to consider perspectives that are not their own. Student facing instructions: • Each student will be randomly assigned to represent a particular group at our climate summit focused on radiative forcings. Use your perspective to evaluate the information about each forcing and negotiate with other representatives to come to an agreement on how best to move forward. • Structure • Opening Statements: Read about your perspective and share a short opening statement on how you think the global community can best respond to climate change, keeping the priorities of the group you are representing in mind. • Alliance Building / Negotiation Round: Rotate through the stations to learn more about the different radiative forcings and use the information to either modify or support your argument. Mingle with other participants and start forming alliances. Negotiate if needed. • New Proposals + Responses: We will meet again as a large group and each representative (or coalition) will share an updated proposal. Share any responses and prepare to vote. • Final Agreement: A final vote will be taken to determine which proposal we want to move forward with. • Debrief Instructor Notes: • Perspectives and information about forcings were taken from the Encyclopedia of Climate Change. Additional information is on the following pages. • Perspectives include representatives from various countries, organizations, and companies. There should be a mix of pro-mitigation and anti-mitigation perspectives. • Timing was tight – could work better to require prep outside of class. Timing • 10 minutes to read about perspective • Opening statements – shouldn’t take more than about 5 minutes total • 5 minutes for alliance building • 15 minutes at each station – visit 2 stations, choose wisely • 5 minutes for negotiation • New proposals and responses – shouldn’t take more than 10 minutes total • Final agreement – vote, shouldn’t take long • Should have ~10 minutes remaining to debrief Questions to ask during • What is your group willing to commit to reduce forcing? • How will your proposal contribute to keeping RF low? • What support do you need from others? • Can this group reach consensus? If not, what compromises are needed? • What is your proposed RF reduction target? • What actions will your group take? • What are your non-negotiables? • Who are your likely opponents? • Who pays for mitigation in low-emissions countries? • Should developing nations be held to the same cuts? • How do wealthier nations support adaptation? • Which source(s) of radiative forcing should your group prioritize addressing or monitoring? • What specific action or policy should your group advocate for at this summit? Reflection Prompts: • Were your priorities the same as others’? Why or why not? • Which radiative forcing source do you think is most overlooked? • What made some solutions harder to advocate for than others? • What tradeoffs did your group have to make between scientific urgency and political or economic realities? • Which countries or groups had the most power in negotiations—and why? • How did learning about specific radiative forcing agents help you argue for or against certain climate actions? • If the class had to meet again next year, what kind of progress or follow-up would you want to see? Carbon Dioxide • Type: Anthropogenic • Direction of Forcing: Positive (warming) • Magnitude: +1.68 W/m² • Mechanism: CO₂ is a long-lived greenhouse gas that absorbs outgoing infrared radiation from Earth’s surface, trapping heat in the atmosphere. • Primary Sources: Fossil fuel combustion, deforestation, cement production • Temporal Scale: Centuries • Spatial Scale: Global • Uncertainty: Low • Key Feedbacks: Increases in water vapor (positive feedback) Methane • Type: Anthropogenic and Natural • Direction of Forcing: Positive (warming) • Magnitude: +0.97 W/m² (per molecule ~25x stronger than CO₂) • Mechanism: CH₄ is a potent greenhouse gas that traps infrared radiation; it is shorter-lived than CO₂ but highly effective. • Primary Sources: Agriculture (especially livestock), landfills, fossil fuel production, wetlands • Temporal Scale: Decades (~12-year atmospheric lifetime) • Spatial Scale: Global but concentrated around emissions • Uncertainty: Moderate Aerosols • Type: Anthropogenic • Direction of Forcing: Negative (cooling) • Magnitude: Approx. -0.9 W/m² (high variability) • Mechanism: Aerosols scatter incoming solar radiation and increase cloud reflectivity (albedo), reducing net solar absorption. • Primary Sources: Industrial pollution, biomass burning, transportation • Temporal Scale: Days to weeks • Spatial Scale: Regional (especially over industrial areas) • Uncertainty: High Aerosols contribute an ERF of –1.3 [–2.0 to –0.6] W m–2 over the industrial era (1750–2014) (medium confidence). The ERF due to aerosol–cloud interactions (ERFaci) contributes most to the magnitude of the total aerosol ERF (high confidence) and is assessed to be –1.0 [–1.7 to –0.3] W m–2 ( medium confidence), with the remainder due to aerosol–radiation interactions (ERFari), assessed to be –0.3 [–0.6 to 0.0] W m– 2 ( medium confidence). There has been an increase in the estimated magnitude but a reduction in the uncertainty of the total aerosol ERF relative to AR5, supported by a combination of increased processunderstanding and progress in modelling and observational analyses. ERF estimates from these separate lines of evidence are now consistent with each other, in contrast to AR5, and support the assessment that it is virtually certain that the total aerosol ERF is negative. Compared to AR5, the assessed magnitude of ERFaci has increased, while the magnitude of ERFari has decreased . The total aerosol ERF over the period 1750–2019 is less certain than the headline statement assessment. It is also assessed to be smaller in magnitude at –1.1 [– 1.7 to –0.4] W m–2, primarily due to recent emissions changes (medium confidence). {7.3.3, 7.3.5, 2.2.6} Radiative Forcing (relative to 1750) (Data from IPCC AR6 - approximate values) • CO₂: +1.68 W/m² • CH₄: +0.97 W/m² • Aerosols (net): -0.9 W/m² • Albedo/land use: -0.15 W/m² • Solar: +0.05 W/m² • Volcanic: episodic, ~-0.5 to -1.0 W/m² for major eruptions Which models perform better? The goal of this debate is to highlight how complex data analysis can be. What is meant by “better” and what makes a good climate model? Student facing instructions: • Claim: The CMIP6 models perform better than the CMIP5 models. • Use the figures to argue for or against the claim. • Structure: o 5 minutes to prepare before being assigned a position o 5 additional minutes to prepare after being assigned a position o Opening Arguments o 5 minutes to prepare a response to opposing argument o Responses and closing statements Instructor Notes: • Student handout includes figures from Loechli, M., Stephens, B. B., Commane, R., Chevallier, F., McKain, K., Keeling, R. F., et al. (2023). Evaluating northern hemisphere growing season net carbon flux in climate models using aircraft observations. Global Biogeochemical Cycles, 37, e2022GB007520. https://doi.org/10.1029/2022GB007520 • Questions to encourage thinking during prep: o What do the z-score trends show for individual model improvement? o How does the spread of CMIP6 models compare to CMIP5 across fluxes and seasonal metrics? Is better agreement among models necessarily tied to better accuracy? o What is the value of consistency and ensemble agreement, even with some bias? o Are ensemble means for CMIP5 closer to observations in some key metrics? o How might diversity among models be important for uncertainty assessment? Reflection Prompts: • What evidence did you find most convincing in support of or against the claim? • Was there a moment where you changed your perspective or saw the other side’s point? • If you were writing a conclusion for a paper on this topic, how would you summarize the relationship between model generation and performance? • Would you rather use a model ensemble that is more consistent but systematically wrong, or one that’s more variable but includes the true value? • What are the risks of focusing on spread without considering directional bias? • What does this discussion tell us about how scientific models are evaluated in real practice? • How should scientists and policymakers weigh consistency, accuracy, and bias when selecting models for use in decision-making? Which SSP is most likely? The goals of this debate are to show the range of future possibilities being considered and to help students see why it is important to consider a wide range of futures. Student facing instructions: • Read about a specific SSP and prepare: o Short description of the future it describes in your own words o Argument for why this is the most likely future and why others are not likely Instructor Notes: • Questions to use during arguments to foster discussion: o Can anyone add to or challenge that point? o Do you agree or disagree with what was just said? Why? o How does your SSP compare to what was just described? o What do the rest of you think about that? o Does anyone see things differently? o Between SSP2 and SSP3, which seems more aligned with current global trends? o SSP1 and SSP5 both assume technological advancement, how are the outcomes so different? • Leave lots of time to debrief at the end • Student handouts include general information about the SSPs and specific information about one of the SSPs. Reflection Prompts: • What are SSPs designed to represent in climate science, and why do we need more than one? • What types of assumptions differentiate one SSP from another? • What are the limitations of SSPs? • Why is it useful to debate which SSP is most likely? What did you gain from having to defend one SSP? Does it matter if we get the most likely one exactly right? • What is one way that understanding SSPs changes how you think about climate projections? General SSP Information Source: O’Neill, B.C., Kriegler, E., Riahi, K. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2014). https://doi.org/10.1007/s10584-013-0905-2 The SSPs describe plausible alternative trends in the evolution of society and natural systems over the 21st century at the level of the world and large world regions. They consist of two elements: a narrative storyline and a set of quantified measures of development. SSPs are “reference” pathways in that they assume no climate change or climate impacts, and no new climate policies (Kriegler et al. 2012). The choice to define SSPs in this way was made in order to serve a methodological purpose. The intention is that by not incorporating such effects, SSPs can be more easily used by other researchers across a broad set of studies to evaluate how varying levels of climate change and types of policies affect the “reference” socioeconomic and environmental conditions described in the SSPs. Because SSPs do not include the effects of climate change and climate policy, they may not describe plausible assumptions for the future, but this is an intentional component of the design. To help ensure that the set of SSPs developed actually spans a range of outcomes that will allow the characterization of uncertainty in mitigation, adaptation, and impacts, we define an outcome space in which socioeconomic and environmental challenges are represented on two axes: one axis depicts challenges pertaining to adaptation; the other axis challenges to mitigation (Fig. 1). The logic here is that for characterizing uncertainties in the implications of mitigating climate change to a given level, or of adapting to that level (key goals of the scenario framework), we need to describe future socioeconomic conditions that would make mitigation and adaptation relatively hard or relatively easy. In the figure axes, and in the text, “socioeconomic” is intended to be shorthand for a wide range of aspects of society or, more broadly, socioecological systems. These include demographic, political, social, cultural, institutional, life-style, economic, and technological aspects, and the conditions of ecosystems and ecosystem services that have been affected by human activity such as air and water quality, biodiversity, and ecosystem form and function. The intention of this “socioeconomic” label is primarily to communicate that we exclude conditions related to future climate change itself. Figure 1 The “challenges space” to be spanned by SSPs (based on Kriegler et al. 2012, Fig. 3), divided into five “domains” with one SSP located within each domain, represented by a star SSP1 Information Source: KeywanRiahi, et al., The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environmental Change, Volume 42, 2017, Pages 153-168, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2016.05.009. The SSP narratives (O’Neill et al., 2016a) comprise a textual description of how the future might unfold in terms of broad societal trends. Their main purpose is to provide an internally consistent logic of the main causal relationships, including a description of trends that are traditionally difficult to capture by models. In this sense, the SSP narratives are an important complement to the quantitative model projections. By describing major socioeconomic, demographic, technological, lifestyle, policy, institutional and other trends, the narratives add important context for a broad user community to better understand the foundation and meaning of the quantitative SSP projections. At the same time, the narratives have been a key input into the modeling process, since they underpin the quantifications and guided the selection of assumptions for the socioeconomic projections and the SSP energy and land-use transitions described in this special issue. SSP1 Sustainability – Taking the Green Road (Low challenges to mitigation and adaptation) The world shifts gradually, but pervasively, toward a more sustainable path, emphasizing more inclusive development that respects perceived environmental boundaries. Management of the global commons slowly improves, educational and health investments accelerate the demographic transition, and the emphasis on economic growth shifts toward a broader emphasis on human well-being. Driven by an increasing commitment to achieving development goals, inequality is reduced both across and within countries. Consumption is oriented toward low material growth and lower resource and energy intensity. Source: Our World In Data https://ourworldindata.org/explorers/ipcc-scenarios Each of the five SSPs also have variations of each scenario that would deliver a particular climate target. These variations correspond to the level of radiative forcing that they would lead to. Let’s take ‘SSP1 – 2.6’ as an example. It is a scenario with the socioeconomic development pathway of SSP1 (the same scenario in terms of population and economic growth) that would lead to a forcing of 2.6 watts per meter squared. To achieve that under these socioeconomic conditions would mean that something else would have to change to reduce emissions. For example, it lays out a future in which the world implements a carbon price globally; or total energy consumption is lower because we improve efficiency; or we have more nuclear energy; or we have much more carbon capture and storage. For some SSPs, the changes would have to be extreme to meet these climate pathways. For example, in SSP5 – the fossil-fuel-heavy development path – we would need a very high carbon price, and lots of carbon capture and storage. Go to Our World In Data to explore even more. General SSP Information Source: O’Neill, B.C., Kriegler, E., Riahi, K. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2014). https://doi.org/10.1007/s10584-013-0905-2 The SSPs describe plausible alternative trends in the evolution of society and natural systems over the 21st century at the level of the world and large world regions. They consist of two elements: a narrative storyline and a set of quantified measures of development. SSPs are “reference” pathways in that they assume no climate change or climate impacts, and no new climate policies (Kriegler et al. 2012). The choice to define SSPs in this way was made in order to serve a methodological purpose. The intention is that by not incorporating such effects, SSPs can be more easily used by other researchers across a broad set of studies to evaluate how varying levels of climate change and types of policies affect the “reference” socioeconomic and environmental conditions described in the SSPs. Because SSPs do not include the effects of climate change and climate policy, they may not describe plausible assumptions for the future, but this is an intentional component of the design. To help ensure that the set of SSPs developed actually spans a range of outcomes that will allow the characterization of uncertainty in mitigation, adaptation, and impacts, we define an outcome space in which socioeconomic and environmental challenges are represented on two axes: one axis depicts challenges pertaining to adaptation; the other axis challenges to mitigation (Fig. 1). The logic here is that for characterizing uncertainties in the implications of mitigating climate change to a given level, or of adapting to that level (key goals of the scenario framework), we need to describe future socioeconomic conditions that would make mitigation and adaptation relatively hard or relatively easy. In the figure axes, and in the text, “socioeconomic” is intended to be shorthand for a wide range of aspects of society or, more broadly, socioecological systems. These include demographic, political, social, cultural, institutional, life-style, economic, and technological aspects, and the conditions of ecosystems and ecosystem services that have been affected by human activity such as air and water quality, biodiversity, and ecosystem form and function. The intention of this “socioeconomic” label is primarily to communicate that we exclude conditions related to future climate change itself. Figure 4 The “challenges space” to be spanned by SSPs (based on Kriegler et al. 2012, Fig. 3), divided into five “domains” with one SSP located within each domain, represented by a star SSP4 Information Source: KeywanRiahi, et al., The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environmental Change, Volume 42, 2017, Pages 153-168, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2016.05.009. The SSP narratives (O’Neill et al., 2016a) comprise a textual description of how the future might unfold in terms of broad societal trends. Their main purpose is to provide an internally consistent logic of the main causal relationships, including a description of trends that are traditionally difficult to capture by models. In this sense, the SSP narratives are an important complement to the quantitative model projections. By describing major socioeconomic, demographic, technological, lifestyle, policy, institutional and other trends, the narratives add important context for a broad user community to better understand the foundation and meaning of the quantitative SSP projections. At the same time, the narratives have been a key input into the modeling process, since they underpin the quantifications and guided the selection of assumptions for the socioeconomic projections and the SSP energy and land-use transitions described in this special issue. SSP4 Inequality – A Road Divided (Low challenges to mitigation, high challenges to adaptation) Highly unequal investments in human capital, combined with increasing disparities in economic opportunity and political power, lead to increasing inequalities and stratification both across and within countries. Over time, a gap widens between an internationally-connected society that contributes to knowledgeand capital-intensive sectors of the global economy, and a fragmented collection of lower-income, poorly educated societies that work in a labor intensive, low-tech economy. Social cohesion degrades and conflict and unrest become increasingly common. Technology development is high in the high-tech economy and sectors. The globally connected energy sector diversifies, with investments in both carbon-intensive fuels like coal and unconventional oil, but also low-carbon energy sources. Environmental policies focus on local issues around middle and high income areas. Source: Our World In Data https://ourworldindata.org/explorers/ipcc-scenarios Each of the five SSPs also have variations of each scenario that would deliver a particular climate target. These variations correspond to the level of radiative forcing that they would lead to. Let’s take ‘SSP1 – 2.6’ as an example. It is a scenario with the socioeconomic development pathway of SSP1 (the same scenario in terms of population and economic growth) that would lead to a forcing of 2.6 watts per meter squared. To achieve that under these socioeconomic conditions would mean that something else would have to change to reduce emissions. For example, it lays out a future in which the world implements a carbon price globally; or total energy consumption is lower because we improve efficiency; or we have more nuclear energy; or we have much more carbon capture and storage. For some SSPs, the changes would have to be extreme to meet these climate pathways. For example, in SSP5 – the fossil-fuel-heavy development path – we would need a very high carbon price, and lots of carbon capture and storage. Go to Our World In Data to explore even more. General SSP Information Source: O’Neill, B.C., Kriegler, E., Riahi, K. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2014). https://doi.org/10.1007/s10584-013-0905-2 The SSPs describe plausible alternative trends in the evolution of society and natural systems over the 21st century at the level of the world and large world regions. They consist of two elements: a narrative storyline and a set of quantified measures of development. SSPs are “reference” pathways in that they assume no climate change or climate impacts, and no new climate policies (Kriegler et al. 2012). The choice to define SSPs in this way was made in order to serve a methodological purpose. The intention is that by not incorporating such effects, SSPs can be more easily used by other researchers across a broad set of studies to evaluate how varying levels of climate change and types of policies affect the “reference” socioeconomic and environmental conditions described in the SSPs. Because SSPs do not include the effects of climate change and climate policy, they may not describe plausible assumptions for the future, but this is an intentional component of the design. To help ensure that the set of SSPs developed actually spans a range of outcomes that will allow the characterization of uncertainty in mitigation, adaptation, and impacts, we define an outcome space in which socioeconomic and environmental challenges are represented on two axes: one axis depicts challenges pertaining to adaptation; the other axis challenges to mitigation (Fig. 1). The logic here is that for characterizing uncertainties in the implications of mitigating climate change to a given level, or of adapting to that level (key goals of the scenario framework), we need to describe future socioeconomic conditions that would make mitigation and adaptation relatively hard or relatively easy. In the figure axes, and in the text, “socioeconomic” is intended to be shorthand for a wide range of aspects of society or, more broadly, socioecological systems. These include demographic, political, social, cultural, institutional, life-style, economic, and technological aspects, and the conditions of ecosystems and ecosystem services that have been affected by human activity such as air and water quality, biodiversity, and ecosystem form and function. The intention of this “socioeconomic” label is primarily to communicate that we exclude conditions related to future climate change itself. Figure 5 The “challenges space” to be spanned by SSPs (based on Kriegler et al. 2012, Fig. 3), divided into five “domains” with one SSP located within each domain, represented by a star SSP5 Information Source: KeywanRiahi, et al., The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environmental Change, Volume 42, 2017, Pages 153-168, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2016.05.009. The SSP narratives (O’Neill et al., 2016a) comprise a textual description of how the future might unfold in terms of broad societal trends. Their main purpose is to provide an internally consistent logic of the main causal relationships, including a description of trends that are traditionally difficult to capture by models. In this sense, the SSP narratives are an important complement to the quantitative model projections. By describing major socioeconomic, demographic, technological, lifestyle, policy, institutional and other trends, the narratives add important context for a broad user community to better understand the foundation and meaning of the quantitative SSP projections. At the same time, the narratives have been a key input into the modeling process, since they underpin the quantifications and guided the selection of assumptions for the socioeconomic projections and the SSP energy and land-use transitions described in this special issue. SSP5 Fossil-fueled Development – Taking the Highway (High challenges to mitigation, low challenges to adaptation) This world places increasing faith in competitive markets, innovation and participatory societies to produce rapid technological progress and development of human capital as the path to sustainable development. Global markets are increasingly integrated. There are also strong investments in health, education, and institutions to enhance human and social capital. At the same time, the push for economic and social development is coupled with the exploitation of abundant fossil fuel resources and the adoption of resource and energy intensive lifestyles around the world. All these factors lead to rapid growth of the global economy, while global population peaks and declines in the 21st century. Local environmental problems like air pollution are successfully managed. There is faith in the ability to effectively manage social and ecological systems, including by geo-engineering if necessary. Source: Our World In Data https://ourworldindata.org/explorers/ipcc-scenarios Each of the five SSPs also have variations of each scenario that would deliver a particular climate target. These variations correspond to the level of radiative forcing that they would lead to. Let’s take ‘SSP1 – 2.6’ as an example. It is a scenario with the socioeconomic development pathway of SSP1 (the same scenario in terms of population and economic growth) that would lead to a forcing of 2.6 watts per meter squared. To achieve that under these socioeconomic conditions would mean that something else would have to change to reduce emissions. For example, it lays out a future in which the world implements a carbon price globally; or total energy consumption is lower because we improve efficiency; or we have more nuclear energy; or we have much more carbon capture and storage. For some SSPs, the changes would have to be extreme to meet these climate pathways. For example, in SSP5 – the fossil-fuel-heavy development path – we would need a very high carbon price, and lots of carbon capture and storage. Go to Our World In Data to explore even more.