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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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Zhang, Q., Ito, T., & Bracco, A. (2024) · Frontiers in Marine Science · doi:10.3389/fmars.2024.1304193 · Cited by 3
Decline in The Potential Distribution of Fern Species Under Climate Change Scenarios
Silva, D. C., Oliveira, J. P. J., Athayde, F. D. P., & da Silva, J. M. (2024) · Revista de Gestão Social e Ambiental · doi:10.24857/rgsa.v18n7-029 · Cited by 3
Risk assessment of habitat suitability decline for the endangered riparian tree Pterocarya tonkinensis (Juglandaceae): conservation implications
Walas, Ł., Tung, D. Q., Sękiewicz, K., Pietras, M., Bravo, F., Kozlowski, G., & Sâm, H. V. (2024) · European Journal of Forest Research · doi:10.1007/s10342-024-01679-9 · Cited by 3
“85 (CO 2 emissions tripled by 2075; Meinshausen et al. 2020, IPCC 2021).”
BackgroundMethod
The need for nonuniform risk acceptability across climate change scenarios
Nasr, A., Ivanov, O. L., Björnsson, Í., & Johansson, J. (2024) · Risk Analysis · doi:10.1111/risa.14293 · Cited by 3
“Subsequently, the radiative forcings associated with these reference scenarios were evaluated by the scientiﬁc community (Meinshausen et al., 2020).”
Air-sea coupling influence on projected changes in major Atlantic hurricane events
Danso, D., Patricola, C., Kurian, J., Chang, P., Klotzbach, P., & Lin, I.-I. (2024) · Weather and Climate Extremes · doi:10.1016/j.wace.2024.100649 · Cited by 3
The potential of growing soybean in Saskatchewan and its irrigation water needs under climate change scenarios—a modelling study
Qian, B., Bonsal, B., Jing, Q., Smith, W., Jégo, G., Zhang, Y.-S., Brannen, R., Grant, B., & Crépeau, M. (2024) · Canadian Journal of Plant Science · doi:10.1139/cjps-2023-0148 · Cited by 3
“5 scenarios (Meinshausen et al. 2020) were downloaded from Greenhouse Gas Fact-sheets (http://greenhousegases.science.unimelb.edu.au).”
Method
Modelled Climate Change Impacts on Spring Canola Production Across British Columbia, Canada
Ball, M. (2023) · International Journal of Environment · doi:10.3126/ije.v12i2.65469 · Cited by 3
“5, a “middle of the road” scenario, where some progress has been made to reduce the overreliance on fossil fuels for development (Meinshausen et al., 2020).”
BackgroundInfluential
Deterministic and stochastic components of atmospheric CO 2 inside forest canopies and consequences for predicting carbon and water exchange
Muñoz, E., & Sierra, C. A. (2023) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2023.109624 · Cited by 4
Modeling the Wintering Habitat Distribution of the Black Stork in Shaanxi, China: A Hierarchical Integration of Climate and Land Use/Land Cover Data
Tuohetahong, Y., Lu, R., Gan, F., Li, M., Ye, X.-P., & Yu, X.-P. (2023) · Animals · doi:10.3390/ani13172726 · Cited by 3
Buoyancy forcing: a key driver of northern North Atlantic sea surface temperature variability across multiple timescales
Risebrobakken, B., Jensen, M., Langehaug, H., Eldevik, T., Sandø, A., Li, C., Born, A., McClymont, E., Salzmann, U., & de Schepper, S. (2023) · Climate of the Past · doi:10.5194/cp-19-1101-2023 · Cited by 3
“CO2 concentrations reach 445 ppm by 2100 (Meinshausen et al., 2020), which is at the high end of the Pliocene CO2 range (Bartoli et al., 2011; de la Vega et al., 2020).”
BackgroundInfluential
Modulation of daily PM 2.5 concentrations over China in winter by large-scale circulation and climate change
Jia, Z., Ordóñez, C., Doherty, R. M., Wild, O., Turnock, S. T., & O’Connor, F. M. (2023) · Atmospheric chemistry and physics · doi:10.5194/acp-23-2829-2023 · Cited by 7
“…and vegetation land cover fraction are prescribed as in CMIP6 historical (1999–2014) and SSP3-7 0 future (2015–2019) simulations conducted by UKESM1 (Meinshausen et al., 2017, 2020) There is little difference between the shared socio-economic pathways (SSPs; O’Neill et al., 2014; van Vuuren et…”
Method
Probabilistic Sea Level Rise Hazard Analysis Based on the Current Generation of Data and Protocols
Luo, X., & Lin, T. (2022) · Journal of Structural Engineering · doi:10.1061/jsendh.steng-11413 · Cited by 3
Sea-level rise in Denmark: paleo context, recent projections and policy implications
Colgan, W., Henriksen, H. J., Bennike, O., Riberio, S., Keiding, M., Seidenfaden, I. K., Graversgaard, M., Busck, A., Fruergaard, M., Knudsen, M., et al. (2022) · GEUS Bulletin · doi:10.34194/geusb.v49.8315 · Cited by 3
Cropland Exposed to Drought Is Overestimated without Considering the CO2 Effect in the Arid Climatic Region of China
Jiang, S., Zhou, J., Wang, G.-J., Lin, Q., Chen, Z., Wang, Y.-J., & Su, B. (2022) · Land · doi:10.3390/land11060881 · Cited by 3
Marine CO 2 system variability along the Inside Passage of the Pacific Northwest coast of North America determined from an Alaskan ferry
Evans, W., Lebon, G., Harrington, C. D., Takeshita, Y., & Bidlack, A. (2021) · doi:10.5194/bg-2021-266 · Cited by 3
“…CO2 mole fractions based on observations and projected atmospheric CO2 for the shared 335 socio-economic pathways (SSP) were obtained from Meinshausen et al. (2020) using their data portal (http://greenhousegases.science.unimelb.edu.au) and converted to pCO2 assuming standard atmospheric…”
BackgroundMethod
Impact of bioenergy crops expansion on climate-carbon cycle feedbacks in overshoot scenarios
Melnikova, I., Boucher, O., Cadule, P., Tanaka, K., Gasser, T., Hajima, T., Quilcaille, Y., Shiogama, H., Séférian, R., Tachiiri, K., et al. (2021) · doi:10.5194/esd-2021-72 · Cited by 3
Evading the Entrepreneurship: A Study to Discover Implementable Online Approaches to Avoid Greenhouse Consequences
Feng, L., Hu, W., Akhter, T., Albasher, G. I., Aamir, A., & Imran, A. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.713957 · Cited by 7
“The information available on the usage of green products clearly changes the mind of target customers (Meinshausen et al., 2020).”
Background
Using Machine Learning to Make Computationally Inexpensive Projections of 21st Century Stratospheric Column Ozone Changes in the Tropics
Keeble, J., Yiu, Y., Archibald, A., O'Connor, F., Sellar, A., Walton, J., & Pyle, J. (2021) · Frontiers in Earth Science · doi:10.3389/feart.2020.592667 · Cited by 3
“All SSP scenarios assume compliance with the Montreal Protocol, and so the trajectory of CFC-11 and CFC-12 is the same across the scenarios, with only minor differences associated with differences in the chemical lifetime of CFC-11 and CFC-12 under different SSP scenarios (Meinshausen et al., 2020).”
Background
Weather extremes over Europe under 1.5 °C and 2.0 °C global warming from HAPPI regional climate ensemble simulations
Sieck, K., Nam, C., Bouwer, L., Rechid, D., & Jacob, D. (2020) · doi:10.5194/esd-2020-4 · Cited by 3
Multi-objective optimization for robust optimal green retrofit design of public buildings under multiple SSP scenarios
An, J., Jung, D., Hong, T., Kim, J., Jang, H., & Oh, D. (2026) · Renewable & Sustainable Energy Reviews · doi:10.1016/j.rser.2026.116900 · Cited by 3
The social welfare value of the global food system
Dietz, S., Bodirsky, B. L., Crawford, M., Kanbur, R., Leip, D., Lord, S., Lotze‐Campen, H., & Popp, A. (2025) · Ecological Economics · doi:10.1016/j.ecolecon.2025.108771 · Cited by 5
“MAGICC is run in a probabilistic setup following the IPCC ’ s latest WG1 report (Cross-Chapter Box 7.1 in Forster et al., 2021).”
Influential
Divergent evolution of nitrogen cycling along gradients of landscape water velocities.
Wu, S.-J., Soulsby, C., Zheng, Y., Musolff, A., & Tetzlaff, D. (2026) · Science · doi:10.1126/science.aed0399 · Cited by 2
Improving terrestrial carbon flux simulations with machine learning and global Earth observations
Seiler, C. (2026) · Earth System Dynamics · doi:10.5194/esd-17-651-2026 · Cited by 2
Tropical oceans drive variability in soil moisture and malaria in Malawi
Elling, M., Karnauskas, K., Kowalcyk, M., Mategula, D., Chirombo, J., Livneh, B., McCann, R. S., & Buchwald, A. (2026) · Communications Medicine · doi:10.1038/s43856-026-01681-9 · Cited by 2
“We evaluateSharedSocioeconomicPathway(SSP)experiments,whichsimulate climateunderstandardizedgreenhousegasemissionstrajectories 41 (Supplementary Table 2).”
Projected Changes in Yield and Water Use Efficiency of Cold-Region Rice and the Role of CO2 Under Climate Change
Li, Z.-N., Liu, Y., Nie, T.-Z., Xiao, X.-T., Guo, H., Wang, T., & Han, Y. (2026) · Plants · doi:10.3390/plants15111625 · Cited by 2
“5 [42].”
Influential
Projections of changes in extreme storm surges for European coasts using statistical downscaling
Apecechea, M. I., Melet, A., Menéndez, M., Lobeto, H., & Valle-Rodriguez, J. B. (2026) · Natural Hazards and Earth System Sciences · doi:10.5194/nhess-26-2269-2026 · Cited by 2
“This conﬁguration yields average correlation, RMSE, and MB values of 0.89, 5.5, and 8.6 cm, respectively, which is comparable to other state-of-the-art data-driven reconstructions in Europe (e.g., Tadesse et al., 2020). more detail evaluation of the capability of the SDM to reconstruct past storm…”
Influential
When cities overheat: Urban heat exposure under the Swiss Climate CH2025 Scenarios
Senoner, A. E., Burger, M., & Kotlarski, S. (2026) · City and Environment Interactions · doi:10.1016/j.cacint.2026.100385 · Cited by 2
The pace of meeting carbon emission targets alters regional climate risks
Park, I., Yeh, S., & King, A. D. (2026) · Science Advances · doi:10.1126/sciadv.aec4566 · Cited by 2
“Using different shared socioeconomic pathway (SSP) emission scenarios ( 29 ), we compare a slow scenario (i.e., SSP1-2.”
A Preliminary Comparison of SOC Storage Between the Traditional Farmland and Well‐Facilitated Farmland Management
Wang, Z., Zhao, R., Xue, J., Lu, R., Chen, Z.-X., Yu, Q.-Y., Chen, W., Zhang, Q.-C., Shi, Z., & Chen, S.-C. (2026) · Earth's Future · doi:10.1029/2025ef007810 · Cited by 2
“Comparative analysis of SOCD changes under different management and climate scenarios revealed a substantially greater SOC sequestration potential in well‐facilitated farmland compared to traditional farmland, evident under both SSP1‐2.6 and SSP5‐8.5 climate pathways (Figures 5b–5e).”
Influential
Fish and Zooplankton Co‐Responses to Environmental Gradients Under Different Climate Change Scenarios
Paquette, C. H., Girolamo, D. J. D., Pham, J., Ovaskainen, O., Gagné, S., Leclerc, V., Beisner, B., Fugère, V., & Taranu, Z. (2026) · Global Change Biology · doi:10.1111/gcb.70845 · Cited by 2
“5) using the WorldClim version 2.1 and the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework (https:// www. world clim. org; O'Neill et al. 2016; Meinshausen et al. 2020).”
Influential
Climate as the Main Driver of Large‐Scale Genetic Patterns and Connectivity in the Expanding Golden Jackal
Flores‐Manzanero, A., Bogdanowicz, W., Stefanović, M., Adavoudi, R., Khosravi, R., Sosa, F. M., Doan, K., Srinivas, Y., Banea, O. C., Ćirović, D., et al. (2026) · Global Change Biology · doi:10.1111/gcb.70879 · Cited by 3
“…ESM2-0, MIROC6, and MPI- ESM1- 2-HR) under two Shared Socioeconomic Pathways (SSPs), which imply alterations to temperature and hydrological regimes (Meinshausen et al. 2020): SSP 2.6 (named as “optimistic,” representing minimum green-house gas emissions) and SSP 8.5 (named as “pessimistic,”…”
Influential
Enhancing soil carbon storage in water-limited environments with multispecies cover cropping: Insights from DayCent® model simulation
Arije, D., Bista, P., Gautam, S., Steele, C. M., Mishra, U., & Ghimire, R. (2026) · Field crops research (Print) · doi:10.1016/j.fcr.2026.110384 · Cited by 2
High-resolution regional climate projections and tourism impacts in the Macaronesian archipelagos
Rodríguez-Rull, J., Expósito, F. J., Díaz, J. P., Carrillo, J., Pérez, J. C., & Henriques, D. (2026) · Scientific Reports · doi:10.1038/s41598-026-43092-9 · Cited by 2
“These projections leverage the Shared Socioeconomic Pathways (SSPs) 16,17 , covering two future periods (2030–2059 and 2070–2099) under two contrasting scenarios: a lower-emissions pathway (SSP1-2.”
Vulnerability metrics and climate analogues inform tree species selection and climate bottleneck in a changing climate
Dendoncker, M., Messier, C., Esperón‐Rodríguez, M., & Villemaire‐Côté, O. (2026) · Climate Change Ecology · doi:10.1016/j.ecochg.2026.100114 · Cited by 3
Imbalances in climate outcomes in net-zero pathways with fossil fuel CO2 emissions and reforestation-based CO2 removals
MacIsaac, A., Zickfeld, K., Banville, P. E., & Matthews, H. D. (2026) · Communications Earth & Environment · doi:10.1038/s43247-026-03329-x · Cited by 2
Severe rapid indian monsoon weakening due to emissions from extreme Canadian wildfires
Roșu, I., Mourgela, R.-N., Kasoar, M., Petrakis, M. P., & Voulgarakis, A. (2026) · npj Natural Hazards · doi:10.1038/s44304-026-00184-w · Cited by 2
“…wild ﬁ re events is crucial, as projections indicate a marked escalation in ﬁ re activity across multiple regions worldwide in the coming decades 10 – 12 , and, generally, climate models suggest that the extreme conditions observed in 2023 are likely to become a baseline by the 2050 s 13 .”
Large regional differences in Antarctic ice shelf mass loss from Southern Ocean warming and meltwater feedbacks
Muilwijk, M., Hattermann, T., Beadling, R., Swart, N. C., Nummelin, A., Guo, C.-C., Chandler, D., Langebroek, P., Zhou, S., Dutrieux, P., et al. (2026) · The Cryosphere · doi:10.5194/tc-20-1087-2026 · Cited by 2
Projection of Changes in Coastal Water Temperature of the Baltic Sea up to 2100
Ptak, M., Sojka, M., Haddout, S., & Amnuaylojaroen, T. (2026) · Forecasting · doi:10.3390/forecast8010012 · Cited by 2
“This temporal divergence aligns with global studies showing significant differences in late-century climate conditions between high-and low-emission pathways [52,53].”
Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations
Egli, M., Sippel, S., Knutti, R., & Humphrey, V. (2026) · Nature Communications · doi:10.1038/s41467-025-67748-8 · Cited by 2
“5 forcing scenarios 47 .”
Positive feedbacks drive the Greenland ice sheet evolution in millennial-length MAR–GISM simulations under a high-end warming scenario
Paice, C. M., Fettweis, X., & Huybrechts, P. (2026) · The Cryosphere · doi:10.5194/tc-20-309-2026 · Cited by 2
“5 scenario and its extension (Meinshausen et al., 2020).”
The observed September 2023 temperature jump was nearly impossible under standard anthropogenic forcing
Seeber, S., Schumacher, D., Gudmundsson, L., & Seneviratne, S. (2026) · Communications Earth & Environment · doi:10.1038/s43247-026-03178-8 · Cited by 2
“5,theprobabilityrisesfromnearzeroin2023to5%by 2028andreaches60%by2034(Fig.1d),withlittlescenariodependence before2050,aspathwaysonlydivergemarkedlyafterwards 34 .”
Economic assessment of SRM under socio-political and geophysical tipping dynamics
Estrada, F., Bastien-Olvera, B. A., Calderón-Bustamante, Ó., Altamirano, M. A., Muñoz-Sánchez, R., Moreno‐Cruz, J., & Botzen, W. J. W. (2026) · Environmental Research Climate · doi:10.1088/2752-5295/ae33df · Cited by 2
“The global temperature change scenarios in this paper were generated using the MAGICC7 reduced complexity climate model available at https://live.magicc.org/ (Meinshausen et al 2011, 2020, Nicholls et al 2021).”
Restoration based on cost–benefit optimization: A grasslands pilot study
Weiskopf, S. R., Morelli, T. L., Mozelewski, T. G., Shiklomanov, A., & Lerman, S. B. (2026) · Ecological Applications · doi:10.1002/eap.70174 · Cited by 2
“0, a medium – high reference scenario (Meinshausen et al., 2020; van Vuuren et al., 2017).”
Simulating climate change impacts on soil carbon storage in agroecosystems from Brazilian drylands
Greschuk, L. T., Ogle, S. M., Locatelli, J. L., Gurung, R., Schiebelbein, B. E., Signor, D., Tonucci, R. G., Frazão, L. A., & Cherubin, M. R. (2025) · Journal of Environmental Management · doi:10.1016/j.jenvman.2025.128462 · Cited by 2
Ventilation and buffering capacity effects on ocean acidification in low oxygen environments
Xue, L., Sabine, C. L., Chen, J., Lauvset, S. K., Wei, Q., Li, K., & Cai, W. (2025) · Nature Communications · doi:10.1038/s41467-025-67807-0 · Cited by 2
“3), a level projected around 2075 under SSP2 ‑ 4.5 and around 2050 under SSP5 ‑ 8.5 86 .”
Influential
Meta-modelling paths of simple climate models using neural networks and dirichlet polynomials: an application to DICE
Gobet, E., Liu, Y., & Vermandel, G. (2025) · European Actuarial Journal · doi:10.1007/s13385-025-00438-3 · Cited by 2
Forest expansion and glacial retreat in the Central Himalaya indicated by past observations and future projections
Bhatta, K., Mishra, O., Joshi, D. P., Yadav, B. K., Aryal, A., Ayer, S., & Hölscher, D. (2025) · Environmental Challenges · doi:10.1016/j.envc.2025.101332 · Cited by 2
Projecting the future of a threatened marine mammal in relation to climate warming
Regehr, E., Quakenbush, L., Duyke, A. V., Citta, J., & Lindsay, J. M. (2025) · Ecological Applications · doi:10.1002/eap.70127 · Cited by 2
“5 (30,000 seals), which represents the high end of potential fossil-fuel development (Meinshausen et al., 2020).”
Impact of Future Methane Emission Trajectories on Atmospheric Composition and Climate in a Future Hydrogen Economy
Chua, G., Naïk, V., Paulot, F., Feng, J., & Horowitz, L. W. (2025) · Earth s Future · doi:10.1029/2025ef006254 · Cited by 6
“…∼ 38% increase in CH 4 emissions in 2050 compared to 2015 in the Shared Socioeconomic Pathway (SSP) with no policies to reduce GHG and air pollutant emissions (SSP3‐7.0) (Meinshausen et al., 2020; Rao et al., 2017), so it is a reasonable high‐end projection for future anthropogenic CH 4 emissions.”
Influential
Seasonal variations of tropical cyclone genesis and landfall patterns impacting Southeast Asia in a warmer climate
Weaver, M. M., Garner, A. J., Samanta, D., Mann, M. E., & Horton, B. (2025) · Communications Earth & Environment · doi:10.1038/s43247-025-02566-w · Cited by 2
“The moderate-emission future (2081 – 2100; Shared Socioeconomic Pathway (SSP) 2-4.5): a “ middle of the road ” future climate where modest progress is made toward reducing anthropogenic greenhouse gas emissions, resulting in 4.5 W/m 2 radiative forcing for the planet by the year 2100 20,114,115 ; 4.”
Influential
Assessing the long-term water footprint of olive grove under changing climate (Apulia, Italy)
Leone, M., Attar, O., Brouziyne, Y., Khalki, E. M. E., Bouchaou, L., & Girolamo, A. M. D. (2025) · Agricultural Water Management · doi:10.1016/j.agwat.2025.109875 · Cited by 3
Rising compound heatwave exposure in India: insights from CMIP6 climate model projections
Sahithi, K., Velpuri, M., & Das, J. (2025) · Environmental Research Letters · doi:10.1088/1748-9326/ae1498 · Cited by 2
“…( The climate scenarios SSP126, SSP245, SSP370, and SSP585 represent the ‘sustainability’, ‘middle of the road’, ‘regional rivalry’, and ‘fossil-fuel develop-ment’ pathways, corresponding to radiative forcing levels of 2.6, 4.5, 7.0, and 8.5 W m − 2 , respectively (Meinshausen et al 2020).”
Influential
Impact of future climate change and land-use change on habitat suitability for a long-distance avian migrant under diverse socioeconomic-emission scenarios
Lathouwers, M., Beenaerts, N., Evens, R., Artois, T., Conway, G., Henderson, I. G., Shewring, M. P., Cross, T., Ulenaers, E., & Dendoncker, N. (2025) · Global Ecology and Conservation · doi:10.1016/j.gecco.2025.e03777 · Cited by 2
“Recent work has highlighted the uncertainty in matching recent observational and modelled greenhouse gas concentrations (Meinshausen et al., 2020).”
Modelling climate-driven range shifts in the distribution of Lantana camara in Ethiopia
Gebrewahid, Y., Tesfamariam, B., Berhe, D., Birhane, E., Girmay, M., Abebe, T., Teklehaymanot, T., Eyasu, G., Hagazi, N., Haregeweyn, N., et al. (2025) · Discover Sustainability · doi:10.1007/s43621-025-01666-z · Cited by 2
“The reason could be linked to the fact that SSP585 represents a high-emission scenario characterized by rapid global warming [46, 54].”
Spatiotemporal changes in human thermal comfort across iran: future projections of UTCImin variability for land cover and elevation classes
Zarei, A., & Khoorani, A. (2025) · Theoretical and Applied Climatology · doi:10.1007/s00704-025-05722-6 · Cited by 2
Interplay of climate change, policy, and human behavior in lake basins: identifying key factors and future climate hotspots (case study: Urmia lake basin, Iran)
Mohammadi, M., Delgarm, R., Farahmand, H., Nikraftar, Z., Badiezadeh, S., López-Carr, D., & Tajrishy, M. (2025) · Journal of Hydrology · doi:10.1016/j.jhydrol.2025.134197 · Cited by 2
Insights from Earth Map: Unraveling Environmental Dynamics in the Euphrates–Tigris Basin
Ateşoğlu, A., Aydoğdu, M. H., Yenigün, K., Díaz, A. S.-P., Marchi, G., & Bulut, F. (2025) · Sustainability · doi:10.3390/su17167513 · Cited by 2

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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