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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-222
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-222
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 01 Oct 2019

Submitted as: development and technical paper | 01 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

The SSP greenhouse gas concentrations and their extensions to 2500

Malte Meinshausen1,2,3, Zebedee Nicholls1,2, Jared Lewis1, Matthew J. Gidden4,5, Elisabeth Vogel1,2, Mandy Freund1,6, Urs Beyerle7, Claudia Gessner7, Alexander Nauels1,5, Nico Bauer3, Joseph G. Canadell8, John S. Daniel9, Andrew John1,10, Paul Krummel11, Gunnar Luderer3, Nicolai Meinshausen12, Stephen A. Montzka13, Peter Rayner2,1, Stefan Reimann14, Steven J. Smith15, Marten van den Berg16, Guus J. M. Velders17,18, Martin Vollmer14, and Hsaing Jui Wang19 Malte Meinshausen et al.
  • 1Climate & Energy College, The University of Melbourne, Parkville, Victoria, Australia
  • 2School of Earth Sciences, The University of Melbourne, Parkville, Victoria, Australia
  • 3Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
  • 4IIASA Institute for Applied Systems Analysis, Laxenburg, Austria
  • 5Climate Analytics, Berlin, Germany
  • 6Marine and Atmospheric Research, CSIRO, Hobart, Tasmania, Australia
  • 7Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology, Zurich (ETH Zurich), Switzerland
  • 8Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia
  • 9NOAA, Earth System Research Laboratory, Chemical Sciences Division, Boulder, Colorado, USA
  • 10Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia
  • 11CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
  • 12Seminar for Statistics, Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland
  • 13NOAA, Earth System Research Laboratory, Global Monitoring Division, Boulder, Colorado, USA
  • 14Empa, Laboratory for Air Pollution/Environmental Technology, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
  • 15Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
  • 16PBL Netherlands Environmental Assessment Agency, the Netherlands
  • 17National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
  • 18nstitute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands
  • 19School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332-0340, USA

Abstract. Anthropogenic increases of atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The Integrated Assessment community quantified anthropogenic emissions for the Shared Socioeconomic Pathways (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentration for these SSP scenarios – using the reduced complexity climate-carbon cycle model MAGICC7.0. We extend historical, observationally-based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios respectively. We also provide the concentration extensions beyond 2100 based on assumptions in the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from today 66 % to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterisations that reflect the Oslo Line by Line model results. In comparison to the RCPs, the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are more evenly spaced in terms of their expected global-mean temperatures, extend to lower 2100 temperatures and sea level rise than the RCP set. Performing 2 pairs of 6-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the MAM season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼ 5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies’ projections over the next 100 to 500 years unequivocally depict a ‘hockey-stick’ upwards shape – it is a collective choice whether the hothouse pathway is pursued or whether we manage climate damages to the SSP1-1.9 equivalent of around 1.5 °C warming.

Malte Meinshausen et al.
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Malte Meinshausen et al.
Data sets

Greenhouse gas concentration data SSP4-6.0- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9863

Greenhouse gas concentration data SSP5-8.5- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9868

Greenhouse gas concentration data SSP4-3.4- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9862

Greenhouse gas concentration data SSP1-1.9- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9864

Greenhouse gas concentration data SSP1-2.6- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9865

Greenhouse gas concentration data SSP2-4.5- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9866

Greenhouse gas concentration data SSP3-7.0- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9861

Greenhouse gas concentration data SSP3-7.0-lowNTCF- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9824

Greenhouse gas concentration data SSP5-3.4-over- greenhousegases.science.unimelb.edu.au M. Meinshausen, Z. Nicholls, J. Lewis, M. Gidden, E. Vogel, M. Freund, U. Beyerle, C. Gessner, A. Nauels, N. Bauer, J. Canadell, J. Daniel, A. John, P. Krummel, G. Luderer, N. Meinshausen, S. Montzka, P. Rayner, S. Reimann, S. Smith, M. van den Berg, G. Velders, M. Vollmer, and H. Wang https://doi.org/10.22033/ESGF/input4MIPs.9867

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Short summary
This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous RCP scenarios). The projected CO2 concentrations range from 350 ppm for low emission scenarios by 2150 to more than 2000 ppm under the high emission scenarios. We also provide concentrations, latitudinal gradients and seasonality for most of the other 42 considered GHGs. The possible resulting warming is compared to previous RCP scenarios.
This study provides the future greenhouse gas (GHG) concentrations under the new set of...
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