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The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

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Meinshausen, Malte, Nicholls, Zebedee R. J., Lewis, Jared, Gidden, Matthew J., Vogel, Elisabeth, Freund, Mandy, Beyerle, Urs, Gessner, Claudia, Nauels, Alexander, Bauer, Nico, Canadell, Josep G., Daniel, John S., John, Andrew, Krummel, Paul B., Luderer, Gunnar, Meinshausen, Nicolai, Montzka, Stephen A., Rayner, Peter J., Reimann, Stefan, Smith, Steven J., van den Berg, Marten, Velders, Guus J. M., Vollmer, Martin K., Wang, Ray H. J.·2020·Geoscientific Model Development

DOI 10.5194/gmd-13-3571-2020

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Abstract

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations 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. CO 2 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 regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO 2 emissions. By 2150, CO 2 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 CO 2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO 2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (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 and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-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 March–April–May (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. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘ C warming on the other.

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Minganti, D., Chabrillat, S., Errera, Q., Prignon, M., Kinnison, D. E., García, R. R., Ábalos, M., Alsing, J., Schneider, M. F., Smale, D., et al. (2022) · Journal of Geophysical Research Atmospheres · doi:10.1029/2021jd036390 · Cited by 17
Daytime warming during early grain filling offsets the CO2 fertilization effect in rice
Zhang, G.-Y., Ujiie, K., Yoshimoto, M., Sakai, H., Tokida, T., Usui, Y., Wakatsuki, H., Arai, M., Ikawa, H., Nakamaura, H., et al. (2022) · Environmental Research Letters · doi:10.1088/1748-9326/aca038 · Cited by 8
“from the windward sides to maintain the CO2 concentration measured at the central point approximately 200 μmol mol−1 above AC, which is projected to reach in the mid-century under high emission scenarios [28].”
Background
Modeling and Prediction of the Species’ Range of Neurobasis chinensis (Linnaeus, 1758) under Climate Change
Liao, J., Wang, H., Xiao, S., Guan, Z., Zhang, H.-M., Dumont, H., & Han, B.-P. (2022) · Biology · doi:10.3390/biology11060868 · Cited by 8
“5 W m−2), approximately 376 ppm, 650 ppm, 1011 ppm and 1228 ppm CO2-equivalent in 2100 [25].”
Causal effect of the tropical Pacific sea surface temperature on the Upper Colorado River Basin spring precipitation
Zhao, S., & Zhang, J. (2021) · Climate Dynamics · doi:10.1007/s00382-021-05944-0 · Cited by 9
From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: MAGICC (v7.5.1) – MESMER (v0.8.1) coupling
Beusch, L., Nicholls, Z., Gudmundsson, L., Hauser, M., Meinshausen, M., & Seneviratne, S. (2021) · doi:10.5194/gmd-2021-252 · Cited by 8
Self-citation
23rd Century surprises: Long-term dynamics of the climate and carbon cycle under both high and net negative emissions scenarios
Koven, C., Arora, V., Cadule, P., Fisher, R., Jones, C. D., Lawrence, D., Lewis, J., Lindsey, K., Mathesius, S., Meinshausen, M., et al. (2021) · doi:10.5194/esd-2021-23 · Cited by 8
Self-citation
Financial Policy, Green Transition and Recovery after the COVID-19Preprint
Pan, D.-Y., Chen, C.-Q., Grubb, M., & Wang, Y. (2020) · Social Science Research Network · doi:10.2139/ssrn.3719695 · Cited by 8
“019 so that the GHG stock in the year 2100 under the “No Policy” scenario can match the Shared Socioeconomic Pathways 5 (SSP5, fossil-fuelled development) predicted by Meinshausen et al. (2020). Considering the cost of scientists mastering a particular speciality, the switch of research type is not very easy, the scie…”
BackgroundInfluential
Climate impacts from North American boreal forest fires
van Gerrevink, M. J., Veraverbeke, S., Cooperdock, S. C., Potter, S., Zhong, Q., Moubarak, M. F., Virkkala, A., Goetz, S. J., Mack, M. C., Randerson, J. T., et al. (2026) · Nature Geoscience · doi:10.1038/s41561-026-01940-3 · Cited by 7
“…they can be directly compared using the metric of radiative forcing (W m −2 ) 25–27 , defined by the Intergovernmental Panel on Climate Change 28 , as the change in net radiative flux at the top-of-atmosphere after allowing atmospheric temperatures to readjust to radiative equilibrium 28,29 .”
Influential
Anthropogenically-driven escalating impact of soil-based compound dry-hot extremes on vegetation productivity
Liang, Y.-N., Wang, J., Hao, Z., Wang, H.-J., Cui, H., & Ge, Q.-S. (2026) · Nature Communications · doi:10.1038/s41467-026-68878-3 · Cited by 7
“6) emission scenario 42 , the regional mean frequency ofexternally forcedsoil-based CDHEs in China is projected to rise by the mid-twenty-ﬁ rst century, followed by a slight decline through the end of the twenty-ﬁ rst century (i.e., 2071 – 2100) (Fig.”
Permafrost and wildfire carbon emissions indicate need for additional action to keep Paris Agreement temperature goals within reach
Schädel, C., Gasser, T., Rogers, B., Treharne, R., Turetsky, M., Smith, T., Macdonald, E., & Natali, S. (2026) · Communications Earth & Environment · doi:10.1038/s43247-026-03189-5 · Cited by 7
Recent history and future demise of Jostedalsbreen, the largest ice cap in mainland Europe
Åkesson, H., Sjursen, K. H., Schuler, T. V., Dunse, T., Andreassen, L., Gillespie, M. K., Robson, B., Schellenberger, T., & Yde, J. C. (2025) · The Cryosphere · doi:10.5194/tc-19-5871-2025 · Cited by 7
“D simulations of historical and future changes of the complex ice cap.”
Projected Future Changes in Burn Probability in Canada’s Forests and Communities Under Different Climate Change Scenarios
Mulverhill, C., Coops, N., Wulder, M., Hermosilla, T., White, J., & Bater, C. (2025) · Canadian journal of remote sensing · doi:10.1080/07038992.2025.2560347 · Cited by 7
Strengthening Ecosystem Sustainability and Climate Resilience Through Integrative Nature-Based Solutions in Bontioli Natural Reserve, West African Drylands
Kiribou, I. A. R., Dimobe, K., & Dejene, S. W. (2025) · Earth · doi:10.3390/earth6030111 · Cited by 7
“5) from the CMIP6 dataset [44].”
Combined effects of ocean acidification and warming on phytoplankton productivity and community structure in the coastal water of Southern East
Zhang, Y., Beardall, J., & Gao, K. (2025) · Marine Environmental Research · doi:10.1016/j.marenvres.2025.107352 · Cited by 7
Climate variability amplifies the need for vector-borne disease outbreak preparedness
Hart, W., Hurrell, J., Kaye, A. R., Chand, M., Keeling, M., & Thompson, R. N. (2025) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2507311122 · Cited by 7
Assessing Climate-Driven Phenological Responses of Tomato Crops under Future Climate Change Trajectories: A Central India Perspective
Singh, P. N., Srivastava, P. K., Sharma, B., & Mall, R. (2025) · Smart Agricultural Technology · doi:10.1016/j.atech.2025.101256 · Cited by 7
Declining coral calcification to enhance twenty-first-century ocean carbon uptake by gigatonnes
Kwiatkowski, L., Planchat, A., Pyolle, M., Torres, O., Bouttes, N., Comte, A., & Bopp, L. (2025) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2501562122 · Cited by 7
“Although the RCPs have been updated to Shared Socioeconomic Pathways (SSPs) in the latest coupled model intercompar-ison project (63), each of the RCPs used here has an SSP analogue that exhibits similar—although generally greater—surface ocean warming and acidification for a comparable radiative…”
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Ma, J., Arneth, A., Smith, B., Anthoni, P. M., Xu-Ri, Eliasson, P., Wårlind, D., Wittenbrink, M., & Olin, S. (2025) · Geoscientific model development · doi:10.5194/gmd-18-3131-2025 · Cited by 9
Potential deficit irrigation adaptation strategies under climate change for sustaining cotton production in hyper–arid areas
Chen, X., Dong, H., Qi, Z., Dongwei, G. U. I., Ma, L., Thorp, K. R., Malone, R. W., Wu, H., Liu, B., & Feng, S. (2025) · Agricultural Water Management · doi:10.1016/j.agwat.2025.109417 · Cited by 7
Escalating Heatwave Exposure of the Elderly across China.
Zhou, Y., Gu, S., Yang, H., Ge, Z.-X., Dong, G., Zhao, Y., & Yang, Q.-Y. (2025) · Environmental Research · doi:10.1016/j.envres.2025.121986 · Cited by 7
Assessing Stone Material Recession of Cultural Heritage: New Approach Based on Satellite-Based Rainfall Data and Dose-Response Functions—Case of UNESCO Site of Matera
Visone, F., Abate, N., Sileo, M., & Masini, N. (2025) · Remote Sensing · doi:10.3390/rs17081443 · Cited by 7
Drivers for the trends of atmospheric inorganic nitrogen deposition in China under the past and future scenarios
Zhang, Z.-H., Yan, D., Li, M.-M., Lu, Y.-T., Zhou, Y.-T., Wang, T.-J., Zhuang, B.-L., Li, S., & Huang, X. (2025) · Atmospheric Environment · doi:10.1016/j.atmosenv.2025.121221 · Cited by 7
Future water requirements of the wheat crop in Northern Algeria under climate change scenarios
Mokhtari, S., Benmehaia, A. M., Nourani, A., & Hadjeb, A. (2025) · Regional Environmental Change · doi:10.1007/s10113-025-02378-w · Cited by 7
Evaluation and Projection of Arctic sea ice concentration under various emission scenarios using CMIP6 models
Sardana, D., Kulkarni, S., & Agarwal, A. (2025) · Climate Dynamics · doi:10.1007/s00382-025-07646-3 · Cited by 7
Estimating the sea level rise responsibility of industrial carbon producers
Sadai, S., Ranganathan, M., Nauels, A., Nicholls, Z., Merner, D., Dahl, K., Licker, R., & Ekwurzel, B. (2025) · Environmental Research Letters · doi:10.1088/1748-9326/adb59f · Cited by 7
“5 (Meinshausen et al 2020).”
InfluentialSelf-citation
Spatial and temporal evolution of future atmospheric reactive nitrogen deposition in China under different climate change mitigation strategies
Ma, M., Cao, J., Tong, D., Zheng, B., & Zhao, Y. (2025) · Atmospheric chemistry and physics · doi:10.5194/acp-25-2147-2025 · Cited by 7
Safeguarding tourism economies: Managing the financial and ecological challenges of oil spills on coastal destinations.
Jameel, A., Imran, M., Adam, N., Mirzaliev, S., Khidirov, M., & Gao, Y. (2025) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2025.117668 · Cited by 7
Maize Yield Changes Under Sulfate Aerosol Climate Intervention Using Three Global Gridded Crop Models
Clark, B., Robock, A., Xia, L.-L., Rabin, S. S., Guarin, J., Hoogenboom, G., & Jägermeyr, J. (2025) · Earth's Future · doi:10.1029/2024ef005269 · Cited by 7
“Crop model simulations followed transient CO 2 concentrations under SSP2‐4.5 (Meinshausen et al., 2020).”
Influential
A targeted study to determine the conservation status of a Data Deficient montane lizard, the Eungella shadeskink (Saproscincus eungellensis)
Scott, N. A., Mulder, J. A., Pili, A., Oliver, P., Hines, H. B., Farquhar, J., & Chapple, D. G. (2024) · Pacific Conservation Biology · doi:10.1071/pc24050 · Cited by 7
Is there a direct benefit of using electronic commerce and electronic banking in mitigating climate change?
Manta, A. G., Doran, N. M., Hurduzeu, G., Bădîrcea, R. M., Doran, M. D., & Manta, L. F. (2024) · Climatic Change · doi:10.1007/s10584-024-03809-z · Cited by 11
“Providing valuable information to customers plays a key role in changing their perspective towards green products (Meinshausen et al. 2020).”
How can Future Climate Change Affect the Corn Production System in Nebraska, USA?
Gonçalves, I. Z., Fattori, I. M., Neale, C. M. U., dos Santos, C. A. C., Ruane, A. C., Phillips, M., & Marin, F. R. (2024) · International Journal of Plant Production · doi:10.1007/s42106-024-00310-6 · Cited by 9
“Furthermore, to represent the changes in CO 2 concentrations between 2015 and 2100 for each SSP scenario, we used the yearly future scenarios of CO 2 concentration available in Meinshausen et al. (2020) as input for the crop model simulations (Fig.”
Drivers of decadal trends in the ocean carbon sink in the past, present, and future in Earth system models
Terhaar, J. (2024) · Biogeosciences · doi:10.5194/bg-21-3903-2024 · Cited by 14
Challenges to Viticulture in Montenegro under Climate Change
Fernandes, A., Kovač, N., Fraga, H., Fonseca, A., Radonjić, S., Simeunović, M., Ratković, K., Menz, C., Costafreda-Aumedes, S., & Santos, J. A. (2024) · ISPRS Int. J. Geo Inf. · doi:10.3390/ijgi13080270 · Cited by 7
“Future climate scenarios are derived from the Coupled Model Intercomparison Project Phase 6 scenarios (CMIP6) [85], more specifically the Shared Socio-Economic Pathways [86]: SSP1-2.”
Method
Anthropogenic CO 2 , air–sea CO 2 fluxes, and acidification in the Southern Ocean: results from a time-series analysis at station OISO-KERFIX (51° S–68° E)
Metzl, N., Monaco, C. L., Leseurre, C., Ridame, C., Reverdin, G., Chau, T. T. T., Chevallier, F., & Gehlen, M. (2024) · Ocean science · doi:10.5194/os-20-725-2024 · Cited by 9
How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?
Kayastha, M., Huang, C.-F., Wang, J., Qian, Y., Yang, Z., Chakraborty, T., Pringle, W. J., Hetland, R., & Xue, P.-F. (2024) · Earth's Future · doi:10.1029/2024ef004622 · Cited by 7
“The Shared Socioeconomic Pathway 5 (SSP5‐8.5) was considered in Case 2a and Case 2b as it represents the higher end of the spectrum of plausible future pathways and closely corresponds to the Representative Concentration Pathway (RCP) 8.5 (Meinshausen et al., 2020; Riahi et al., 2011).”
BackgroundInfluential
Carbon Cycle Response to Stratospheric Aerosol Injection With Multiple Temperature Stabilization Targets and Strategies
Zhao, M., Cao, L., Visioni, D., & MacMartin, D. G. (2024) · Earth s Future · doi:10.1029/2024ef004474 · Cited by 11
“The background CO 2 concentration scenario used here is the Shared Socioeconomic Pathway (SSP) 2–4.5 (Meinshausen et al., 2020), which represents a moderate‐mitigation scenario.”
MethodInfluential
Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models
Blazsek, S., Escribano, A., & Kristóf, E. (2024) · Energy Economics · doi:10.1016/j.eneco.2024.107591 · Cited by 7
Employing gridded-based dataset for heatwave assessment and future projection in Peninsular Malaysia
Sa’adi, Z., Hamed, M. M., Muhammad, M. K. I., Chow, M.-F., Mohamad, N., Basri, M. H. A., Ahmad, M. F., Sa'adi, N., Alias, N., Yusop, Z., et al. (2024) · Theoretical and Applied Climatology · doi:10.1007/s00704-024-04946-2 · Cited by 7
“5 were used to assess potential future changes in Tmax over PM (Meinshausen et al. 2020).”
Assessment of model projections of climate‐change induced extreme storms on the south‐east coast of Australia
Zhu, W., Wang, X.-H., Peirson, W. L., & Salcedo‐Castro, J. (2024) · International Journal of Climatology · doi:10.1002/joc.8446 · Cited by 7
“For the CMIP6, the projections of future scenario are shown in Shared Socioeconomic Path-ways (SSP) which cover the period of 2015 to 2100 (Eyring et al., 2016; Meinshausen et al., 2020; O'Neill et al., 2016).”
BackgroundMethodInfluential
Projections of the North Atlantic warming hole can be constrained using ocean surface density as an emergent constraint
Park, I.-H., & Yeh, S. (2024) · Communications Earth & Environment · doi:10.1038/s43247-024-01269-y · Cited by 7
“Scenario uncertainty increases over time due to the different forcings applied toward the end of the 21st century 35 , while internal variability uncertainty remains relatively constant.”
Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality.
Zhu, J., Yang, Y., Wang, H.-L., Gao, J.-Y., Liu, C., Wang, P.-Y., & Liao, H. (2024) · Science of the Total Environment · doi:10.1016/j.scitotenv.2024.170024 · Cited by 7
What goes in must come out: the oceanic outgassing of anthropogenic carbon
Couespel, D., & Tjiputra, J. (2023) · Environmental Research Letters · doi:10.1088/1748-9326/ad16e0 · Cited by 7
Revisiting the greenhouse effect – a hydrological perspective
Koutsoyiannis, D., & Vournas, C. (2023) · Hydrological Sciences Journal · doi:10.1080/02626667.2023.2287047 · Cited by 7
Constraining CMIP6 estimates of Arctic Ocean temperature and salinity in 2025-2055
Langehaug, H., Sagen, H., Stallemo, A., Uotila, P., Rautiainen, L., Olsen, S., Devilliers, M., Yang, S., & Storheim, E. (2023) · Frontiers in Marine Science · doi:10.3389/fmars.2023.1211562 · Cited by 7
The Mysterious Amurian Grig Paracyphoderris erebeus Storozhenko, 1980 (Orthoptera: Prophalangopsidae): New Data on Its Distribution, Ecology and Biology
Storozhenko, S., Molodtsov, V. V., & Sergeev, M. G. (2023) · Insects · doi:10.3390/insects14100789 · Cited by 7
“…downscaled from the global climate models [33], namely CNRM-ESM2-1 (Centre National de Recherches M é t é orologiques and Centre Eu-rop é en de Recherche et de Formation Avanc é e en Calcul Scientiﬁque, France) [34,35] and for the three Shared Socioeconomic Pathways (1–2.6, 2–4.5, 3–7.0) [36].”
MethodInfluential
A stacked ensemble learning and non‐homogeneous hidden Markov model for daily precipitation downscaling and projection
Jiang, Q., Cioffi, F., Conticello, F., Giannini, M., Telesca, V., & Wang, J. (2023) · Hydrological Processes · doi:10.1002/hyp.14992 · Cited by 7
Context matters when using climate model projections for aquaculture
Falconer, L., Ytteborg, E., Goris, N., Lauvset, S. K., Sandø, A. B., & Hjøllo, S. S. (2023) · Frontiers in Marine Science · doi:10.3389/fmars.2023.1198451 · Cited by 12
“Scenarios are used as it is impossible to account for the infinite number of potential future trajectories, and a set of common scenarios also facilitates comparison between different models and communication across different disciplines (Kriegler et al., 2012; O’Neill et al., 2014; Meinshausen et al., 2020).”
Predicting runoff and sediment responses to climate-resilient land use and management scenarios
Berihun, M., Tsunekawa, A., Haregeweyn, N., Tsubo, M., Fenta, A., Ebabu, K., Bayabil, H., & Dile, Y. (2023) · Environmental science and pollution research international · doi:10.1007/s11356-023-27452-w · Cited by 7
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Teckentrup, L., Kauwe, M. G. D., Abramowitz, G., Pitman, A. J., Ukkola, A., Hobeichi, S., François, B., & Smith, B. (2023) · Earth System Dynamics · doi:10.5194/esd-14-549-2023 · Cited by 11
On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions
Fera, S. D., Fabiano, F., Raspollini, P., Ridolfi, M., Cortesi, U., Barbara, F., & von Hardenberg, J. (2023) · Geoscientific Model Development · doi:10.5194/gmd-16-1379-2023 · Cited by 7
Future trends in wind resources and their consistency in the Indian sub-continent
Zakari, Y., Michel, A., & Lehning, M. (2022) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2022.102460 · Cited by 7
Ocean Acidification and Long‐Term Changes in the Carbonate System Properties of the South Atlantic Ocean
Piñango, A., Kerr, R., Orselli, I. B. M., Carvalho, A. D. C. D. O., Azar, E., Karstensen, J., & Garcia, C. A. E. (2022) · Global Biogeochemical Cycles · doi:10.1029/2021gb007196 · Cited by 11
“ate these changes in the future, we recalculate the trends based on the variation of atmospheric CO2 between occupations (rather than time) and assuming that these trends remain constant and considering the atmospheric CO2 projections of Meinshausen et al. (2020) we found that under the SSP2-4.”
Method
Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
Collette, J. C., Sommerville, K., Lyons, M. B., Offord, C., Errington, G., Newby, Z., von Richter, L., & Emery, N. J. (2022) · Annals of Botany · doi:10.1093/aob/mcac026 · Cited by 7
Disentangling the effects of sea surface temperature and CO$_2$ in global machine learned weather-climate emulators
Clark, S., Arcomano, T., Duncan, J. P. C., Henn, B., Kwa, A., McGibbon, J., Perkins, W., Wu, E., Harris, L. M., Watt-Meyer, O., et al. (2026) · doi:10.48550/arxiv.2606.07928 · Cited by 6
“There are numerous other greenhouse gases, like CH 4 or N 2 O, and aerosols, which are shorter lived and highly spatially heterogeneous, all of which can vary independently of CO 2 (Riahi et al., 2017; Meinshausen et al., 2020).”
Groundwater Temperature Processes and Patterns: Implications for Stream Thermal Regimes
Kurylyk, B., Kelleher, C., Irvine, D. J., Tackley, H., Leach, J. A., Neilson, B., & Bense, V. (2026) · WIREs Water · doi:10.1002/wat2.70062 · Cited by 6
Enhanced forest carbon gains from stronger protection in China’s protected areas
Fu, Y., Li, W., Niu, Z., Chen, F., Zhang, B., Qiao, H., Wang, L., & Svenning, J.-C. (2026) · Nature Communications · doi:10.1038/s41467-026-69505-x · Cited by 6
“…interpolated to a 0.5° spatial resolution. remained entirely undisturbed since 1901, the comparison Annual atmospheric CO 2 concentration data for 1901-2020 were sourced from ice-core estimations 97 and Mauna Loa Observatory 98 , while for 2021-2100, data were obtained from the SSP datasets 99 .”
Influential
Beyond Climate Change: The Role of Integrated Soil Fertility Management for Sustaining Future Maize Yield in Sub‐Saharan Africa
Couëdel, A., Falconnier, G. N., Adam, M., Cardinael, R., Six, J., Laub, M., Ruane, A. C., Boote, K. J., Justes, É., Smith, W., et al. (2026) · Global Change Biology · doi:10.1111/gcb.70720 · Cited by 7
“0) by 2050 (Meinshausen et al. 2020; Thrasher et al. 2022).”

Authors: Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., & Wang, R. H. J.
Affiliations: The University of Melbourne (AU)
International Institute for Applied Systems Analysis (AT)
Commonwealth Scientific and Industrial Research Organisation (AU)
ETH Zurich (CH)
Potsdam Institute for Climate Impact Research (DE)
CSIRO Oceans and Atmosphere (AU)
NOAA Chemical Sciences Laboratory (US)
National Oceanic and Atmospheric Administration (US)
Empa (CH)
Joint Global Change Research Institute (US)
Utrecht University (NL)
Georgia Institute of Technology (US)
Corresponding author: Meinshausen, Malte
Gidden, Matthew J.
Vogel, Elisabeth
Beyerle, Urs
Gessner, Claudia
Nauels, Alexander
Canadell, Josep G.
Krummel, Paul B.
Luderer, Gunnar
Montzka, Stephen A.
Rayner, Peter J.
Reimann, Stefan
Smith, Steven J.
Velders, Guus J. M.
Vollmer, Martin K.
Wang, Ray H. J.
ORCID: Meinshausen, Malte
Nicholls, Zebedee R. J.
Lewis, Jared
Gidden, Matthew J.
Vogel, Elisabeth
Freund, Mandy
Beyerle, Urs
Gessner, Claudia
Nauels, Alexander
Bauer, Nico
Canadell, Josep G.
Daniel, John S.
John, Andrew
Krummel, Paul B.
Luderer, Gunnar
Montzka, Stephen A.
Rayner, Peter J.
Reimann, Stefan
Smith, Steven J.
van den Berg, Marten
Velders, Guus J. M.
Vollmer, Martin K.
Wang, Ray H. J.
Venue: Geoscientific Model Development
Publisher: Copernicus GmbH
Published: 2020-08-13
Volume: 13
Issue: 8
Pages: 3571-3605
ISSN: 1991-959X (ISSN-L)
1991-9603
DOI: 10.5194/gmd-13-3571-2020
OpenAlex: W3048501727
Cited by: 1,815
References: 78
Citations by year: 2026: 288 · 2025: 412 · 2024: 396 · 2023: 336 · 2022: 241 · 2021: 107 · 2020: 33
FWCI: 66.93
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Geoscientific model development (publishedVersion, cc-by)
Minerva Access (University of Melbourne) (submittedVersion, cc-by-sa)
IIASA PURE (International Institute of Applied Systems Analysis) (submittedVersion, cc-by-sa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DORA Empa (Swiss Federal Laboratories for Materials Science and Technology (Empa)) (submittedVersion, cc-by)
Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
NOAA Institutional Repository (submittedVersion)
RENATE (submittedVersion, cc-by-nc-nd)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)) (submittedVersion, other-oa)
Rivm (National Institute for Public Health and the Environment) (submittedVersion)
Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
Rivm (National Institute for Public Health and the Environment) (submittedVersion, other-oa)
RENATE (cc-by)
ETH Zürich Research Collection (cc-by)
Funders: Australian Research Council (FT130100809)
Topics: Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
Keywords: Shared Socioeconomic Pathways, greenhouse gas concentrations, long-lived greenhouse gases, radiative forcing, fossil fuel emissions, land use change emissions, net-negative emissions, non-CO2 emissions, surface air temperature, RCP scenarios

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The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

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