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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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Roldán‐Gómez, P. J., Luca, P. D., Bernardello, R., & Donat, M. (2025) · Earth System Dynamics · doi:10.5194/esd-16-1-2025 · Cited by 10
Role of anthropogenic forcing in Antarctic sea ice variability simulated in climate models
Morioka, Y., Zhang, L.-P., Cooke, W., Nonaka, M., Behera, S., & Manabe, S. (2024) · Nature Communications · doi:10.1038/s41467-024-54485-7 · Cited by 10
“In the future scenario runs, we extended the historical forcing run from 2015 to 2100 using different scenario-based anthropogenic forcing 69 , anthropogenic aerosols, land use, solar radiation and volcanic aerosols.”
Simulation of modern and future climate by INM-CM6M
Gritsun, A., Volodin, E., Bragina, V., & Tarasevich, M. (2024) · Russian Journal of Numerical Analysis and Mathematical Modelling · doi:10.1515/rnam-2024-0028 · Cited by 10
Advancing Coastal Flood Risk Prediction Utilizing a GeoAI Approach by Considering Mangroves as an Eco-DRR Strategy
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Predicting the Invasion Risk of the Highly Invasive Acacia mearnsii in Asia under Global Climate Change
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Variations in Rainfall Structure of Western North Pacific Landfalling Tropical Cyclones in the Warming Climates
Tran, T. L., Ritchie, E. A., Perkins-Kirkpatrick, S., Bui, H., & Luong, T. (2024) · Earth's Future · doi:10.1029/2024ef004808 · Cited by 10
“Two Shared Socioeconomic Pathways (SSPs), SSP2‐4.5 and SSP3‐7.0 characterized by medium and high radiative forcings reaching 4.5 and 7.0 W m − 2 by 2100, respectively (Meinshausen et al., 2020; O’Neill et al., 2016), were investigated.”
Influential
Future climate risks to world cultural heritage sites in Spain: A systematic analysis based on shared socioeconomic pathways
Hai-sheng, H., & Hewitt, R. J. (2024) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2024.104855 · Cited by 13
Multi-scale assessment of rainwater harvesting availability across the continental U.S.
Cintura, I., & Arenas, A. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.121776 · Cited by 10
Mid-Century Climate Change Impacts on Tornado-Producing Tropical Cyclones
Forbis, D. C., Patricola, C., Bercos‐Hickey, E., & Gallus, W. (2024) · Weather and Climate Extremes · doi:10.1016/j.wace.2024.100684 · Cited by 10
Quantification of the impact of land cover and climate change on water and sediment yield in sub-tropical Himalayas in upstream Teesta river basin, Sikkim
Lepcha, P. T., Pandey, P. K., & Pandey, V. (2024) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2024.101146 · Cited by 10
Climate policies for carbon neutrality should not rely on the uncertain increase of carbon stocks in existing forests
Roebroek, C. T. J., Caporaso, L., Alkama, R., Duveiller, G., Davin, É. L., Seneviratne, S. I., & Cescatti, A. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad34e8 · Cited by 10
“…by estimating the maximum biomass achievable under given environmental conditions (climate, soil and topographical features, see table 1) using a quantile regression forest (QRF) to estimate the 100th percentile (implementation in the python package sklearn-quantile ) (Meinshausen et al 2020).”
BackgroundMethodInfluential
Response of plant species to impact of climate change in Hugumbrda Grat-Kahsu forest, Tigray, Ethiopia: Implications for domestication and climate change mitigation
Abrha, H., Dodiomon, S., Ongoma, V., Hagos, H., Birhane, E., Gebresamuel, G., & Manaye, A. (2024) · Trees Forests and People · doi:10.1016/j.tfp.2023.100487 · Cited by 14
Effect of global warming on the potential distribution of a holoparasitic plant (Phelypaea tournefortii): both climate and host distribution matter
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Future Increase in Aridity Drives Abrupt Biodiversity Loss Among Terrestrial Vertebrate Species
Liu, X., Guo, R., Xu, X., Shi, Q., Li, X., Yu, H., Ren, Y., & Huang, J. (2023) · Earth s Future · doi:10.1029/2022ef003162 · Cited by 15
Spatio-temporal pattern of cross-continental invasion: Evidence of climatic niche shift and predicted range expansion provide management insights for smooth cordgrass
Banerjee, A., Liang, X., Harms, N., Tan, F., Lin, Y., Feng, H., Wang, J.-K., Li, Q., Jia, Y., Lu, X.-Y., et al. (2022) · Ecological Indicators · doi:10.1016/j.ecolind.2022.109052 · Cited by 10
GLOBAL LAND-USE AND LAND-COVER DATA: HISTORICAL, CURRENT AND FUTURE SCENARIOSPreprint
Vale, M. M., Lima-Ribeiro, M. S., & Rocha, T. (2021) · bioRxiv · doi:10.1101/2021.05.06.442941 · Cited by 10
Modifying emission scenario projections to account for the effects of COVID-19: protocol for Covid-MIP
Lamboll, R., Jones, C. D., Skeie, R., Fiedler, S., Samset, B., Gillett, N., Rogelj, J., & Forster, P. (2020) · doi:10.5194/gmd-2020-373 · Cited by 10
A Climate Intervention Dynamical Emulator (CIDER) for scenario space exploration
Farley, J., MacMartin, D. G., Visioni, D., Kravitz, B., Bednarz, E., Duffey, A., Henry, M., & Akherati, A. (2026) · Geoscientific model development · doi:10.5194/gmd-19-1809-2026 · Cited by 9
“…global mean climate variables changes in response to anthropogenic changes in radiative forcing using both CO 2 equivalent data for the Shared Socioeconomic Pathway (SSP) scenarios from Meinshausen et al. (2020) as underlying global warming scenarios, and stratospheric AOD derived from step 1.”
Coastal flood impacts and lost ecosystem services along Europe’s outermost regions and overseas countries and territories
Vousdoukas, M., Paprotny, D., Mentaschi, L., Monioudi, I., & Feyen, L. (2026) · Nature Communications · doi:10.1038/s41467-025-66391-7 · Cited by 9
“The literature cited also shows the importance of adaptation and the study has extensive discussion of adaptation following the results.”
Lancet Countdown on health and climate change in Africa: an international collaboration for locally led research and action.
Ali, Z., Abubakar, I., Amegah, A., Caussy, D., Cissé, G., Denton, F., Esievo, E. M., Ihekweazu, V., Kaseya, J., Kimani-Murage, E. W., et al. (2025) · The Lancet · doi:10.1016/s0140-6736(25)02174-9 · Cited by 9
Impacts of sea level rise and adaptation across Asia and the Pacific
Monioudi, I., Vousdoukas, M., Giardino, A., Stocchino, A., Mentaschi, L., & Feyen, L. (2025) · Scientific Reports · doi:10.1038/s41598-025-11517-6 · Cited by 9
“5, that depicts a trajectory of high fossil fuel reliance throughout the 21st century 57 (similar to 8 ).”
Projected land-use change emissions surpass climate change-induced carbon sinks in Sub-Saharan African biomes
Sakala, D., & Santos, M. J. (2025) · Global Environmental Change · doi:10.1016/j.gloenvcha.2025.103039 · Cited by 9
Disentangling the uncertainties in regional projections for Australia
Narsey, S., Grose, M., Delage, F., Tolhurst, G., Chung, C., Takbash, A., Boschat, G., King, M. J., Pepler, A., Thatcher, M., et al. (2025) · Journal of Southern Hemisphere Earth Systems Science · doi:10.1071/es25015 · Cited by 9
Shellfish Aquaculture Complements Nutrient Reduction in Mitigating Climate-Exacerbated Coastal Hypoxia
Yu, L.-Q., Gan, J.-P., Li, D., Cheng, W.-C., Zhang, Y., Kung, H., Hui, C., & Chen, Z. (2025) · Environmental Science and Technology · doi:10.1021/acs.est.5c06682 · Cited by 9
Limitation of super-resolution machine learning approach to precipitation downscaling
Reddy, P. J., Matear, R., Taylor, J. A., & Thatcher, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-05880-7 · Cited by 9
Spatiotemporal patterns of methane fluxes across alpine permafrost region on the Tibetan Plateau
Huang, L., Qin, S.-Q., Kou, D., Ciais, P., Xu, X.-F., Peňuelas, J., Xi, Y., Yang, G., Song, Y., Yao, S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62699-6 · Cited by 9
“Historical atmospheric CO 2 and CH 4 concentrations were derived from a combination of ice core records and atmospheric observations for the period 1860 − 2018 78 , while the atmospheric CO 2 and CH 4 concentrations under different scenarios were obtained from Meinshausen et al. 78 .”
Large biases in the frequency of water limitation across Earth system models
Giardina, F., Padrón, R. S., Stocker, B. D., Schumacher, D., & Seneviratne, S. (2025) · Communications Earth & Environment · doi:10.1038/s43247-025-02426-7 · Cited by 9
How marine cloud brightening could also affect stratospheric ozone
Bednarz, E., Haywood, J., Visioni, D., Butler, A. H., & Jones, A. (2025) · Science Advances · doi:10.1126/sciadv.adu4038 · Cited by 9
“5 scenario ( 25 ) as the underlying GHG emission scenario.”
Predicted yield and soil organic carbon changes in agroforestry, woodland, grassland, and arable systems under climate change in a cool temperate Atlantic climate
Giannitsopoulos, M. L., Burgess, P. J., Graves, A. R., Olave, R. J., Eden, J., & Herzog, F. (2025) · Agronomy for Sustainable Development · doi:10.1007/s13593-025-01020-7 · Cited by 14
Comprehensive assessment of air pollutant emissions, climate scenario projections, and mitigation strategies in Iran
Sharafi, S., & Lorvand, M. (2025) · Atmospheric Environment: X · doi:10.1016/j.aeaoa.2025.100330 · Cited by 9
Ecologo-Geographic Distribution Patterns of the Italian Locust Calliptamus italicus (Linnaeus) (Orthoptera: Acrididae) in the Easternmost Part of Its Range
Sergeev, M. G., Childebaev, M. K., Ji, R., Molodtsov, V. V., Baturina, N. S., Van'kova, I. A., Kim-Kashmenskaya, M. N., Popova, K., Zharkov, V. D., & Yefremova, O. V. (2025) · Insects · doi:10.3390/insects16020211 · Cited by 9
“…Météorologiques and Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique, France) [72,73] and GISS-E2-1-G (NASA Goddard Institute for Space Studies, USA) [74,75] at the 30 arcsecond spatial resolution and for the three Shared Socioeconomic Pathways (1-2.6, 2-4.5, 3-7.0) [76].”
Influential
Projecting and Downscaling Future Temperature and Precipitation Based on CMIP6 Models Using Machine Learning in Hatay Province, Türkiye
Ozbuldu, M., & Irvem, A. (2025) · Pure and Applied Geophysics · doi:10.1007/s00024-024-03656-0 · Cited by 9
“These scenarios, known as Shared Socioeconomic Pathways (SSP), are referred to as SSPx-y (Meinshausen et al., 2020).”
Projected future changes in extreme precipitation over China under stratospheric aerosol intervention in the UKESM1 climate model
Wang, O., Liang, J., Gu, Y., Haywood, J., Chen, Y., Fang, C., & Wang, Q. (2024) · Atmospheric chemistry and physics · doi:10.5194/acp-24-12355-2024 · Cited by 15
“Section 4 summarizes and discusses the ﬁndings”
Projected Changes to Characteristics of El Niño‐Southern Oscillation, Indian Ocean Dipole, and Southern Annular Mode Events in the CMIP6 Models
Chung, C., Power, S., Boschat, G., Gillett, Z. E., & Narsey, S. (2024) · Earth's Future · doi:10.1029/2024ef005166 · Cited by 9
“The SSP585 (“Fossil Fueled Development”) scenario corresponds to a global mean CO 2 concentration of approximately 1,135 ppm and 5°C of projected warming by 2100 (Meinshausen et al., 2020).”
Lower grass stomatal conductance under elevated CO2 can decrease transpiration and evapotranspiration rates despite carbon fertilization
Ahmad, S., Yiotis, C., Xu, W.-M., Knappe, J., Gill, L., & McElwain, J. C. (2024) · Plant Direct · doi:10.1002/pld3.70013 · Cited by 9
“…set at 400 ppm (ambient, labeled as ASP), while the other two were running at 800 ppm of CO 2 (elevated, labeled as CSP), which is the projected atmospheric concentration for 2074 – 75 (shared socioeconomic pathway [SSP] 5 – 8.5) and 2091 – 92 (SSP3 – 7.0), according to Meinshausen et al. (2020).”
BackgroundInfluential
Changes in Four Decades of Near‐CONUS Tropical Cyclones in an Ensemble of 12 km Thermodynamic Global Warming Simulations
Zarzycki, C. M., Zhang, T., Jones, A. D., Rastogi, D., Vahmani, P., & Ullrich, P. A. (2024) · Geophysical Research Letters · doi:10.1029/2024gl110535 · Cited by 13
“While we apply the Shared Socioeconomic Pathway (SSP585, Meinshausen et al., 2020) scenario here, we encourage readers to focus on the CONUS warming levels (WLs), also shown in Table 1, rather than the precise scenario.”
Long-term planning requires climate projections beyond 2100
Easterling, D., Kunkel, K., Crimmins, A. R., & Wehner, M. (2024) · Nature Climate Change · doi:10.1038/s41558-024-02085-0 · Cited by 9
Plant response to decreasing soil moisture under rising atmospheric CO2 levels
Jahren, A., & Schubert, B. (2024) · Communications Earth & Environment · doi:10.1038/s43247-024-01576-4 · Cited by 9
“87,88).”
Little evidence of hysteresis in regional precipitation, when indexed by global temperature rise and fall in an overshoot climate simulation
Walton, J., & Huntingford, C. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad60de · Cited by 9
“Similarly, CO 2 emissions from land use are linearly increased [24] from their negative value at 2100 to zero at 2170, whilst aerosol emissions fall sharply at 2040 to a low value in 2070, decreasing to zero in 2250 [24].”
How much methane removal is required to avoid overshooting 1.5 ∘C?
Smith, C. J., & Mathison, C. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad5853 · Cited by 9
“Another consideration is the simplified radiative forcing relationship used in FaIR, having its origins in [29, 41].”
Method
Physical inconsistencies in the representation of the ocean heat-carbon nexus in simple climate models
Séférian, R., Bossy, T., Gasser, T., Nichols, Z., Dorheim, K., Su, X., Tsutsui, J., & Santana-Falcón, Y. (2024) · Communications Earth & Environment · doi:10.1038/s43247-024-01464-x · Cited by 9
Modeling the impacts of extreme climate scenarios on soil acidity (pH and exchangeable aluminum) in Abbay River Basin, Ethiopia
Chalchissa, F. B., & Kuris, B. K. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e33448 · Cited by 9
“The CMIP6 scenarios consider feedback mechanisms and other factors that were not included in previous models, making them more comprehensive tools for understanding the complex dynamics of climate change on soil health [39,40].”
Background
Carbon Dioxide as a Risky Asset
Bauer, A. M., Proistosescu, C., & Wagner, G. (2024) · Climatic Change · doi:10.1007/s10584-024-03724-3 · Cited by 10
“8 As our model extends out to 2250, we require extensions of the SSPs in the database; we follow the prescription of Meinshausen et al. (2020) for each baseline, which assumes that (a) positive fossil fuel emissions and any net-negative fossil fuel emissions are ramped down to zero by 2250, (b)…”
Future changes in society and climate may strongly shape wild large-herbivore faunas across Europe
Davoli, M., & Svenning, J. (2024) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2023.0334 · Cited by 8
“5 scenarios are associated with higher temperatures and a higher potential for future land use and resource exploitation, which could pose significant economic challenges to wilderness conservation [31,37].”
Background
Atmospheric methane removal may reduce climate risks
Abernethy, S., & Jackson, R. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad3b22 · Cited by 9
“6 [4]), anthropogenic methane emissions must be cut by nearly 50% from today’s ∼ 380 million metric tons (Mt) per year down to ∼ 200 Mt yr − 1 or less by 2050 [4, 5].”
BackgroundInfluential
Significant Reduction of Unequal Population Exposure to Climate Extremes by Achieving the Carbon Neutrality
Oh, S.-G., Jung, C., Kang, M.-J., Son, S.-W., Jeong, S., Min, S.-K., Yeh, S.-W., & Kim, Y.-H. (2024) · Earth s Future · doi:10.1029/2023ef004381 · Cited by 9
“The year of net‐zero carbon emissions in the SSP1‐1.9 scenario is decades earlier than in other mitigation scenarios (e.g., SSP1‐2.6), resulting in weaker warming in the late 21st century (Meinshausen et al., 2020).”
BackgroundInfluential
Climatic projections vs. grapevine phenology: a regional case study
Colibaba, L., Bosoi, I., Pușcalău, M., Bodale, I., Luchian, C., Rotaru, L., & Cotea, V. (2024) · Notulae Botanicae Horti Agrobotanici Cluj-Napoca · doi:10.15835/nbha52113381 · Cited by 9
“The Shared Socioeconomic Pathway (SSP) scenarios, which include nine different pathways, were proposed to account for the uncertainty and variability in future greenhouse gas emissions (Meinshausen et al. , 2020).”
Background
Projecting contributions of marine protected areas to rebuild fish stocks under climate change
Cheung, W. W. L., Palacios‐Abrantes, J., & Roberts, S. M. (2024) · npj Ocean Sustainability · doi:10.1038/s44183-024-00046-w · Cited by 15
“5 65,66 .”
Evaluating climate change scenarios in the white volta basin: A statistical bias-correction approach
Mensah, J. K., Akpoti, K., Antwi-Ofosu, E., Kabo-bah, A. T., Siabi, E. K., Asare, A., Bakuri, R. W., & Yidana, S. M. (2024) · Physics and Chemistry of the Earth Parts A/B/C · doi:10.1016/j.pce.2024.103584 · Cited by 8
Impacts of climate change on water quality, benthic mussels, and suspended mussel culture in a shallow, eutrophic estuary
Maar, M., Larsen, J., Butenschön, M., Kristiansen, T., Thodsen, H., Taylor, D. P., & Schourup‐Kristensen, V. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25218 · Cited by 12
Modeling and forecasting atmospheric Carbon Dioxide concentrations at Bengaluru city in India
Gogeri, I., Gouda, K. C., & Sumathy, T. (2023) · Stochastic environmental research and risk assessment (Print) · doi:10.1007/s00477-023-02629-4 · Cited by 9
“It allows for the assessment of progress in reducing emissions, evaluating the effectiveness of mitigation strategies, and providing guidance for the policy decisions (Meinshausen et al. 2020; Boswell et al. 2010; Yona et al. 2020).”
Predicted Dynamic of Biodeterioration in Cultural Heritage Stones Due to Climate Changes in Humid Tropical Regions—A Case Study on the Rhodotorula sp. Yeast
Sitzia, F., Lisci, C., Pires, V., Dias, L., Mirão, J., & Caldeira, A. T. (2023) · The Heritage · doi:10.3390/heritage6120406 · Cited by 9
“5) emission scenarios, respectively [19], contrary to the present-day CO 2 atmospheric concentration, which is around 420 ppm.”
Background
Climatic Stress Test of Scots Pine Provenances in Northeastern Europe Reveals High Phenotypic Plasticity and Quasi-Linear Response to Warming
Mátyás, C., Balázs, P., & Nagy, L. (2023) · Forests · doi:10.3390/f14101950 · Cited by 9
Future Bioclimatic Change of Agricultural and Natural Areas in Central Europe: An Ultra-High Resolution Analysis of the De Martonne Index
Charalampopoulos, I., Droulia, F., Kokkoris, I. P., & Dimopoulos, P. (2023) · Water · doi:10.3390/w15142563 · Cited by 9
Identifying climate models based on their daily output using machine learning
Brunner, L., & Sippel, S. (2023) · Environmental Data Science · doi:10.1017/eds.2023.23 · Cited by 9
“Previous research, based on climatological timescales, has shown that models can be separated as well as clustered into families based only on their output (e.g., Masson and Knutti, 2011; Knutti et ; Boé, 2018; Brunner et al., 2020; Merrifield et al., 2020, 2023).”
Background
The projection of climate change impact on the fatigue damage of offshore floating photovoltaic structures
Zou, T., Niu, X.-B., Ji, X.-L., Chen, X., & Tao, L. (2023) · Frontiers in Marine Science · doi:10.3389/fmars.2023.1065517 · Cited by 9
“Some researchers even further extended the time period covered by SSPs to 2500 (Meinshausen et al., 2020).”
Background
TreeGOER: a database with globally observed environmental ranges for 48,129 tree species
Kindt, R. (2023) · bioRxiv · doi:10.1101/2023.05.15.540790 · Cited by 9
Model emulators for the assessment of regional impacts and risks of climate change: A case study of rainfed maize production in Mexico
Estrada, F., Mendoza, A., Murray, G., Calderón-Bustamante, O., Botzen, W., Escobedo, T. G. D. L., & Velasco, J. (2023) · Frontiers in Environmental Science · doi:10.3389/fenvs.2023.1027545 · Cited by 9
“, 2015; IPCC, 2021) and play a central role in integrated assessment modelling (Tol and Fankhauser, 1998; van Vuuren et al., 2011; Nordhaus, 2013; Meinshausen et al., 2020; Estrada and Botzen, 2021).”
Background
The effect of global warming on the Australian endemic orchid Cryptostylis leptochila and its pollinator
Kolanowska, M., & Michalska, E. (2023) · PLoS ONE · doi:10.1371/journal.pone.0280922 · Cited by 9

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)
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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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