Climate change scenario

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See also: Climate change mitigation scenarios
Global CO2 emissions and probabilistic temperature outcomes of different policies

Climate change scenarios or socioeconomic scenarios are projections of future greenhouse gas (GHG) emissions used by analysts to assess future vulnerability to climate change.[1] Producing scenarios requires estimates of future population levels, economic activity, the structure of governance, social values, and patterns of technological change. Economic and energy modelling (such as the World3 or the POLES models) can be used to analyze and quantify the effects of such drivers.

Scientists can develop separate international, regional and national climate change scenarios. These scenarios are designed to help stakeholders understand what kinds of decisions will have meaningful effects on climate change mitigation or adaptation. Most countries developing adaptation plans or Nationally Determined Contributions will commission scenario studies in order to better understand the decisions available to them.

International goals for mitigating climate change through international processes like the Intergovernmental Panel on Climate Change (IPCC), Paris Agreement and Sustainable Development Goals are based on reviews of these scenarios. For example, the Special Report on Global Warming of 1.5 °C was released in 2018 order to reflect more up-to-date models of emissions, Nationally Determined Contributions, and impacts of climate change than its predecessor IPCC Fifth Assessment Report published in 2014 before the Paris Agreement.[2]

Emissions scenarios[]

Global futures scenarios[]

These scenarios can be thought of as stories of possible futures. They allow the description of factors that are difficult to quantify, such as governance, social structures, and institutions. Morita et al. assessed the literature on global futures scenarios.[3] They found considerable variety among scenarios, ranging from variants of sustainable development, to the collapse of social, economic, and environmental systems. In the majority of studies, the following relationships were found:

  • Rising GHGs: This was associated with scenarios having a growing, post-industrial economy with globalization, mostly with low government intervention and generally high levels of competition. Income equality declined within nations, but there was no clear pattern in social equity or international income equality.
  • Falling GHGs: In some of these scenarios, GDP rose. Other scenarios showed economic activity limited at an ecologically sustainable level. Scenarios with falling emissions had a high level of government intervention in the economy. The majority of scenarios showed increased social equity and income equality within and among nations.

Morita et al. (2001) noted that these relationships were not proof of causation.

No strong patterns were found in the relationship between economic activity and GHG emissions. Economic growth was found to be compatible with increasing or decreasing GHG emissions. In the latter case, emissions growth is mediated by increased energy efficiency, shifts to non-fossil energy sources, and/or shifts to a post-industrial (service-based) economy.

Factors affecting emissions growth[]

Development Trends[]

In producing scenarios, an important consideration is how social and economic development will progress in developing countries.[4] If, for example, developing countries were to follow a development pathway similar to the current industrialized countries, it could lead to a very large increase in emissions. Emissions do not only depend on the growth rate of the economy. Other factors include the structural changes in the production system, technological patterns in sectors such as energy, geographical distribution of human settlements and urban structures (this affects, for example, transportation requirements), consumption patterns (e.g., housing patterns, leisure activities, etc.), and trade patterns the degree of protectionism and the creation of regional trading blocks can affect availability to technology.

Baseline scenarios[]

A baseline scenario is used as a reference for comparison against an alternative scenario, e.g., a mitigation scenario.[5] In assessing baseline scenarios literature, Fisher et al., it was found that baseline CO2 emission projections covered a large range. In the United States, electric power plants emit about 2.4 billion tons of carbon dioxide (CO
2) each year, or roughly 40 percent of the nation's total emissions. The EPA has taken important first steps by setting standards that will cut the carbon pollution from automobiles and trucks nearly in half by 2025 and by proposing standards to limit the carbon pollution from new power plants.[6]

Factors affecting these emission projections are:

  • Population projections: All other factors being equal, lower population projections result in lower emissions projections.
  • Economic development: Economic activity is a dominant driver of energy demand and thus of GHG emissions.
  • Energy use: Future changes in energy systems are a fundamental determinant of future GHG emissions.
    • Energy intensity: This is the total primary energy supply (TPES) per unit of GDP.[7] In all of the baseline scenarios assessments, energy intensity was projected to improve significantly over the 21st century. The uncertainty range in projected energy intensity was large (Fisher et al. 2007) .
    • Carbon intensity: This is the CO2 emissions per unit of TPES. Compared with other scenarios, Fisher et al. (2007) found that the carbon intensity was more constant in scenarios where no climate policy had been assumed. The uncertainty range in projected carbon intensity was large. At the high end of the range, some scenarios contained the projection that energy technologies without CO2 emissions would become competitive without climate policy. These projections were based on the assumption of increasing fossil fuel prices and rapid technological progress in carbon-free technologies. Scenarios with a low improvement in carbon intensity coincided with scenarios that had a large fossil fuel base, less resistance to coal consumption, or lower technology development rates for fossil-free technologies.
  • Land-use change: Land-use change plays an important role in climate change, impacting on emissions, sequestration and albedo. One of the dominant drivers in land-use change is food demand. Population and economic growth are the most significant drivers of food demand.[8][dubious – discuss]

Quantitative emissions projections[]

A wide range of quantitative projections of greenhouse gas emissions have been produced.[9] The "SRES" scenarios are "baseline" emissions scenarios (i.e., they assume that no future efforts are made to limit emissions),[10] and have been frequently used in the scientific literature (see Special Report on Emissions Scenarios for details). [11] Greenhouse gas#Projections summarizes projections out to 2030, as assessed by Rogner et al.[12] Other studies are presented here.

Individual studies[]

In the reference scenario of World Energy Outlook 2004,[13] the International Energy Agency projected future energy-related CO2 emissions. Emissions were projected to increase by 62% between the years 2002 and 2030. This lies between the SRES A1 and B2 scenario estimates of +101% and +55%, respectively.[14] As part of the IPCC Fourth Assessment Report, Sims et al. (2007) compared several baseline and mitigation scenarios out to the year 2030.[15] The baseline scenarios included the reference scenario of IEA's World Energy Outlook 2006 (WEO 2006), SRES A1, SRES B2, and the ABARE reference scenario. Mitigation scenarios included the WEO 2006 Alternative policy, ABARE Global Technology and ABARE Global Technology + CCS. Projected total energy-related emissions in 2030 (measured in GtCO2-eq) were 40.4 for the IEA WEO 2006 reference scenario, 58.3 for the ABARE reference scenario, 52.6 for the SRES A1 scenario, and 37.5 for the SRES B2 scenario. Emissions for the mitigation scenarios were 34.1 for the IEA WEO 2006 Alternative Policy scenario, 51.7 for the ABARE Global Technology scenario, and 49.5 for the ABARE Global Technology + CCS scenario.

Garnaut et al. (2008)[16] made a projection of fossil-fuel CO2 emissions for the time period 2005-2030. Their “business-as usual” annual projected growth rate was 3.1% for this period. This compares to 2.5% for the fossil-fuel intensive SRES A1FI emissions scenario, 2.0% for the SRES median scenario (defined by Garnaut et al. (2008) as the median for each variable and each decade of the four SRES marker scenarios), and 1.6% for the SRES B1 scenario. Garnaut et al. (2008) also referred to projections over the same time period of the: US Climate Change Science Program (2.7% max, and 2.0% mean), International Monetary Fund's 2007 World Economic Outlook (2.5%), Energy Modelling Forum (2.4% max, 1.7% mean), US Energy Information Administration (2.2% high, 1.8% medium, and 1.4% low), IEA's World Energy Outlook 2007 (2.1% high, 1.8 base case), and the base case from the Nordhaus model (1.3%).

The central scenario of the International Energy Agency publication World Energy Outlook 2011 projects a continued increase in global energy-related CO
2 emissions, with emissions reaching 36.4 Gt in the year 2035.[17] This is a 20% increase in emissions relative to the 2010 level.[17]

UNEP 2011 synthesis report[]

The United Nations Environment Programme (UNEP, 2011)[18]: 7  looked at how world emissions might develop out to the year 2020 depending on different policy decisions. To produce their report, UNEP (2011)[18]: 8  convened 55 scientists and experts from 28 scientific groups across 15 countries.

Projections, assuming no new efforts to reduce emissions or based on the "business-as-usual" hypothetical trend,[19] suggested global emissions in 2020 of 56 gigatonnes CO
2-equivalent (GtCO
2-eq), with a range of 55-59 GtCO
2-eq.[18]: 12  In adopting a different baseline where the pledges to the Copenhagen Accord were met in their most ambitious form, the projected global emission by 2020 will still reach the 50 gigatonnes CO
2.[20] Continuing with the current trend, particularly in the case of low-ambition form, there is an expectation of 3° Celsius temperature increase by the end of the century, which is estimated to bring severe environmental, economic, and social consequences.[21] For instance, warmer air temperature and the resulting evapotranspiration can lead to larger thunderstorms and greater risk from flash flooding.[22]

Other projections considered the effect on emissions of policies put forward by UNFCCC Parties to address climate change. Assuming more stringent efforts to limit emissions lead to projected global emissions in 2020 of between 49-52 GtCO
2-eq, with a median estimate of 51 GtCO
2-eq.[18]: 12  Assuming less stringent efforts to limit emissions lead to projected global emissions in 2020 of between 53-57 GtCO
2-eq, with a median estimate of 55 GtCO
2-eq.[18]: 12 

National climate (change) projections[]

National climate (change) projections (also termed "national climate scenarios" or "national climate assessments") are specialized regional climate projections, typically produced for and by individual countries. What distinguishes national climate projections from other climate projections is that they are officially signed off by the national government, thereby being the relevant national basis for adaptation planning. Climate projections are commonly produced over several years by countries' national meteorological services or academic institutions working on climate change.

Typically distributed as a single product, climate projections condense information from multiple climate models, using multiple greenhouse gas emission pathways (e.g. RCPs) to characterize different yet coherent climate futures. Such a product highlights plausible climatic changes through the use of narratives, graphs, maps, and perhaps raw data. Climate projections are often publicly available for policy-makers, public and private decision makers, as well as researchers to undertake further climate impact studies, risk assessments, and climate change adaptation research. The projections are updated every few years, in order to incorporate new scientific insights and improved climate models.

Aims[]

National climate projections illustrate plausible changes to a country's climate in the future. By using multiple emission scenarios, these projections highlight the impact different global mitigation efforts have on variables, including temperature, precipitation, and sunshine hours. Climate scientists strongly recommend the use of multiple emission scenarios in order to ensure that decisions are robust to a range of climatic changes. National climate projections form the basis of national climate adaptation and climate resilience plans, which are reported to UNFCCC and used in IPCC assessments.

Design[]

To explore a wide range of plausible climatic outcomes and to enhance confidence in the projections, national climate change projections are often generated from multiple general circulation models (GCMs). Such climate ensembles can take the form of perturbed physics ensembles (PPE), multi-model ensembles (MME), or initial condition ensembles (ICE).[23] As the spatial resolution of the underlying GCMs is typically quite coarse, the projections are often downscaled, either dynamically using (RCMs), or statistically. Some projections include data from areas which are larger than the national boundaries, e.g. to more fully evaluate catchment areas of transboundary rivers. Some countries have also produced more localized projections for smaller administrative areas, e.g. States in the United States, and Länder in Germany.

Various countries have produced their national climate projections with feedback and/or interaction with stakeholders.[24] Such engagement efforts have helped tailoring the climate information to the stakeholders' needs, including the provision of sector-specific climate indicators such as degree-heating days. In the past, engagement formats have included surveys, interviews, presentations, workshops, and use-cases. While such interactions helped not only to enhance the usability of the climate information, it also fostered discussions on how to use climate information in adaptation projects. Interestingly, a comparison of the British, Dutch, and Swiss climate projections revealed distinct national preferences in the way stakeholders were engaged, as well as how the climate model outputs were condensed and communicated.[24]

Examples[]

Over 30 countries have reported national climate projections / scenarios in their most recent to United Nations Framework Convention on Climate Change. Many European governments have also funded national information portals on climate change.[25]

For countries which lack adequate resources to develop their own climate change projections, organisations such as UNDP or FAO have sponsored development of projections and national adaptation programmes (NAPAs).[33][34]

Applications[]

National climate projections are widely used to predict climate change impacts in a wide range of economic sectors, and also to inform climate change adaptation studies and decisions. Some examples include:

Comparisons[]

A detailed comparison between some national climate projections have been carried out.[24][49]

See also[]

External links[]

References[]

  1. ^ Carter, T.R.; et al. (2001). "Developing and Applying Scenarios. In: Climate Change 2001: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change [J.J. McCarthy et al. Eds.]". Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A. Retrieved 2010-01-10.
  2. ^ Press release: Special Report on Global Warming of 1.5ºC (PDF) (Report). Incheon, Republic of Korea: Intergovernmental Panel on Climate Change (IPCC). 8 October 2018. Retrieved 7 October 2018.
  3. ^ Morita, T.; et al. (2001). "Greenhouse Gas Emission Mitigation Scenarios and Implications. In: Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz et al. Eds.]". Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A. Retrieved 2010-01-10.
  4. ^ Fisher, B.S.; et al. (2007). "Issues related to mitigation in the long term context. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz et al. Eds.]". Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A. Retrieved 2009-05-20.
  5. ^ IPCC (2007c). "Annex. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz et al. Eds.]". Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A. Retrieved 2009-05-20.
  6. ^ "Using the Clean Air Act to Sharply Reduce Carbon Pollution from Existing Power Plants". Natural Resources Defense Counsel. Retrieved October 9, 2013.
  7. ^ Rogner, H.-H.; et al. (2007). "Introduction. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz et al. Eds.]". Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A. Retrieved 2009-05-20.
  8. ^ Fisher, B.S.; et al. (2007). ""3.2.1.6 Land-use change and land-use management." In [book chapter]: "Issues related to mitigation in the long term context." In [book]: "Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz et al. Eds.]". Print version: Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A.. This version: IPCC website. Archived from the original on 2010-04-25. Retrieved 2010-03-18.
  9. ^ Fisher; et al., "Chapter 3: Issues related to mitigation in the long-term context", Sec. 3.1 Emissions scenarios Missing or empty |title= (help), in IPCC AR4 WG3 2007
  10. ^ Morita; et al., "Chapter 2, Greenhouse Gas Emission Mitigation Scenarios and Implications", Sec. 2.5.1.1 IPCC Emissions Scenarios and the SRES Process Missing or empty |title= (help), in IPCC TAR WG3 2001.
  11. ^ Karl, TR; et al., eds. (2009), "Global climate change", Global Climate Change Impacts in the United States, New York, NY, USA: Cambridge University Press, p. 22, ISBN 978-0-521-14407-0, archived from the original on 2012-09-15
  12. ^ Rogner, H.-H.; et al., "Introduction", Sec 1.3.2 Future outlook Missing or empty |title= (help), in IPCC AR4 WG3 2007
  13. ^ IEA (2004). World Energy Outlook 2004 (PDF). World Energy Outlook website. p. 74.
  14. ^ Section 4.3.1, Fossil fuels Archived 2012-09-10 at the Wayback Machine, in IPCC AR4 WG3 2007.
  15. ^ Section 4.4.1, Carbon dioxide emissions from energy supply by 2030 Archived 2012-09-10 at the Wayback Machine, in IPCC AR4 WG3 2007.
  16. ^ Garnaut, R.; Howes, S.; Jotzo, F.; Sheehan, P. (2008). "Emissions in the Platinum Age: the implications of rapid development for climate-change mitigation" (PDF). Oxford Review of Economic Policy. 24 (2): 392. doi:10.1093/oxrep/grn021. Archived from the original (PDF) on 2012-03-21. Retrieved 2012-09-08.
  17. ^ Jump up to: a b International Energy Agency (IEA) (2011), World Energy Outlook 2011: Fact Sheets (PDF), Paris, France: IEA, p. 2, ISBN 978-92-64-12413-4
  18. ^ Jump up to: a b c d e UNEP (November 2011), Bridging the Emissions Gap: A UNEP Synthesis Report (PDF), Nairobi, Kenya: United Nations Environment Programme (UNEP), ISBN 978-92-807-3229-0 UNEP Stock Number: DEW/1470/NA
  19. ^ Fozzard, Adrian (2014). Climate Change Public Expenditure and Institutional Review Sourcebook (CCPEIR). Washington, D.C.: World Bank Publications. p. 92.
  20. ^ Alam, Shawkat; Bhuiyan, Jahid; Chowdhury, Tareq; Techera, Erika (2013). Routledge Handbook of International Environmental Law. London: Routledge. p. 373. ISBN 9780415687171.
  21. ^ Govaere, Inge; Poli, Sara (2014). EU Management of Global Emergencies: Legal Framework for Combating Threats and Crises. Leiden: BRILL Nijhoff. p. 313. ISBN 9789004268326.
  22. ^ van Drunen, M.A.; Lasage, R.; Dorland, C. (2006). Climate Change in Developing Countries: Results from the Netherlands Climate Change Studies Assistance Programme. Cambridge, MA: CAB International. p. 52. ISBN 9781845930776.
  23. ^ Parker, Wendy S. (2012). "Whose Probabilities? Predicting Climate Change with Ensembles of Models". Philosophy of Science. 77 (5): 985–997. doi:10.1086/656815. ISSN 0031-8248. S2CID 121314681.
  24. ^ Jump up to: a b c Skelton, Maurice; Porter, James J.; Dessai, Suraje; Bresch, David N.; Knutti, Reto (2017-04-26). "The social and scientific values that shape national climate scenarios: a comparison of the Netherlands, Switzerland and the UK". Regional Environmental Change. 17 (8): 2325–2338. doi:10.1007/s10113-017-1155-z. ISSN 1436-3798. PMC 6959399. PMID 32009852.
  25. ^ Füssel, Hans-Martin (2014). How Is Uncertainty Addressed in the Knowledge Base for National Adaptation Planning?. In Adapting to an Uncertain Climate. pp. 41-66: Springer, Cham. ISBN 978-3-319-04875-8.CS1 maint: location (link)
  26. ^ Climate Change in Australia
  27. ^ California climate change scenarios and climate impact research
  28. ^ KNMI'14 Pictures of the future - Climate scenarios
  29. ^ "Swiss Climate Change Scenarios CH2011 B". ch2011.ch. Retrieved 2018-08-23.
  30. ^ CH2018 - New Climate Scenarios for Switzerland
  31. ^ UKCP18 Project announcement
  32. ^ UKCP18 Demonstration Projects (Met Office)
  33. ^ UNDP - Supporting Integrated Climate Change Strategies
  34. ^ UNFCCC - National Adaptation Programmes of Action - Introduction
  35. ^ European Climatic Energy Mixes (ECEM)
  36. ^ California's Climate Adaptation Strategy for Water
  37. ^ Climate-ADAPT EU sector policies - Agriculture
  38. ^ Switzerland: Climate change impacts on tree species, forest properties, and ecosystem services
  39. ^ []
  40. ^ BACC – The Baltex Assessment of Climate Change for the Baltic Sea basin
  41. ^ Health effects of climate change in the UK 2012
  42. ^ UK's Climate change national adaptation programme: transport
  43. ^ The Netherland's Delta Programme 2018 - Continuing the work on a sustainable and safe delta
  44. ^ Copernicus climate data boosts Europe's tourism sector
  45. ^ SwissRe: The Economics of Climate Adaptation
  46. ^ Infrastructure, Engineering and Climate Change Adaptation – ensuring services in an uncertain future
  47. ^ Australia's National Climate Resilience and Adaptation Strategy
  48. ^ UNISDR -Coherence and mutual reinforcement between the Sendai Framework for Disaster Risk Reduction 2015-2030 and international agreements for development and climate action
  49. ^ National climate change vulnerability and risk assessments in Europe, 2018
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