Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within the Coupled Model Intercomparison Project Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century encompassing the Tier 1 experiments (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by 1.15 °C) reached at the upper end of the 5–95 % envelope of the highest scenario, SSP5-8.5. This is due to both the wider range of radiative forcing that the new scenarios cover and to higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensembles' spread, according to a set of initial condition ensemble simulations available under SSP3-7.0. The same experiments suggest a tendency for internal variability to decrease along the course of the century, a new result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP, but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades in mid-century, as represented in SSP5-3.4OS, does not affect the end outcome in terms of temperature and precipitation changes by 2100, which return to the same level as those reached by the gradually increasing SSP4-3.4. Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering 20–28 years from present. 2 °C of warming is reached as early as the late '30s by the ensemble mean under SSP5-8.5, but as late as the late '50s under SSP1-2.6. The highest warming level considered, 5 °C, is reached only by the ensemble mean under SSP5-8.5, and not until the mid-90s.

[1]  A. Timmermann,et al.  Increasing ENSO–rainfall variability due to changes in future tropical temperature–rainfall relationship , 2021, Communications Earth & Environment.

[2]  Tian Tian,et al.  The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6 , 2021 .

[3]  N. Gillett,et al.  Making climate projections conditional on historical observations , 2021, Science Advances.

[4]  Carlos A. Cruz,et al.  CMIP6 Historical Simulations (1850–2014) With GISS‐E2.1 , 2020, Journal of Advances in Modeling Earth Systems.

[5]  C. Heinze,et al.  Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations , 2020 .

[6]  T. Carter,et al.  Achievements and needs for the climate change scenario framework , 2020, Nature Climate Change.

[7]  Christopher J. Smith,et al.  Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response , 2020, Geoscientific Model Development.

[8]  M. Dix,et al.  Configuration and spin-up of ACCESS-CM2, the new generation Australian Community Climate and Earth System Simulator Coupled Model , 2020, Journal of Southern Hemisphere Earth Systems Science.

[9]  M. Webb,et al.  An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence , 2020, Reviews of geophysics.

[10]  K. Calvin,et al.  The DOE E3SM v1.1 Biogeochemistry Configuration: Description and Simulated Ecosystem‐Climate Responses to Historical Changes in Forcing , 2020, Journal of Advances in Modeling Earth Systems.

[11]  T. Ziehn,et al.  The Australian Earth System Model: ACCESS-ESM1.5 , 2020 .

[12]  P. Cox,et al.  Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models , 2020 .

[13]  N. Meinshausen,et al.  The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500 , 2020, Geoscientific Model Development.

[14]  S. Malyshev,et al.  The GFDL Earth System Model Version 4.1 (GFDL‐ESM 4.1): Overall Coupled Model Description and Simulation Characteristics , 2020, Journal of Advances in Modeling Earth Systems.

[15]  R. Stouffer,et al.  Representation of Southern Ocean Properties across Coupled Model Intercomparison Project Generations: CMIP3 to CMIP6 , 2020, Journal of Climate.

[16]  Carlos A. Cruz,et al.  GISS‐E2.1: Configurations and Climatology , 2020, Journal of advances in modeling earth systems.

[17]  Nuno Carvalhais,et al.  Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP , 2020, Geoscientific Model Development.

[18]  S. Bony,et al.  Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model , 2020, Journal of Advances in Modeling Earth Systems.

[19]  H. Douville,et al.  The CNRM Global Atmosphere Model ARPEGE‐Climat 6.3: Description and Evaluation , 2020, Journal of Advances in Modeling Earth Systems.

[20]  F. Chéruy,et al.  LMDZ6A: The Atmospheric Component of the IPSL Climate Model With Improved and Better Tuned Physics , 2020, Journal of Advances in Modeling Earth Systems.

[21]  J. Jungclaus,et al.  Multiple drivers of the North Atlantic warming hole , 2020, Nature Climate Change.

[22]  N. Gillett,et al.  Climate Model Projections of 21st Century Global Warming Constrained Using the Observed Warming Trend , 2020 .

[23]  K. Taylor,et al.  Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models , 2020, Science Advances.

[24]  Zhenya Song,et al.  FIO‐ESM Version 2.0: Model Description and Evaluation , 2020, Journal of Geophysical Research: Oceans.

[25]  H. Martins,et al.  Warmer climate projections in EC-Earth3-Veg: the role of changes in the greenhouse gas concentrations from CMIP5 to CMIP6 , 2020, Environmental Research Letters.

[26]  A. Ito,et al.  Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks , 2020, Geoscientific Model Development.

[27]  R. Knutti,et al.  Reduced global warming from CMIP6 projections when weighting models by performance and independence , 2020, Earth System Dynamics.

[28]  L. Parsons,et al.  Magnitudes and Spatial Patterns of Interdecadal Temperature Variability in CMIP6 , 2020, Geophysical Research Letters.

[29]  J. Dufresne,et al.  Implementation of the CMIP6 Forcing Data in the IPSL‐CM6A‐LR Model , 2020, Journal of Advances in Modeling Earth Systems.

[30]  J. Randerson,et al.  Insights from Earth system model initial-condition large ensembles and future prospects , 2020, Nature Climate Change.

[31]  Axel Lauer,et al.  Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP , 2020, Geoscientific Model Development.

[32]  Klaus Zimmermann,et al.  Earth System Model Evaluation Tool (ESMValTool) v2.0 – technical overview , 2020, Geoscientific Model Development.

[33]  Christopher J. Smith,et al.  Past warming trend constrains future warming in CMIP6 models , 2020, Science Advances.

[34]  C. Deser,et al.  Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6 , 2020, Earth System Dynamics.

[35]  Q. Bao,et al.  Progress in climate modeling of precipitation over the Tibetan Plateau , 2020, National science review.

[36]  W. G. Strand,et al.  The Community Earth System Model Version 2 (CESM2) , 2020, Journal of Advances in Modeling Earth Systems.

[37]  Michel Rixen,et al.  The CMIP6 Data Request (DREQ, version 01.00.31) , 2020, Geoscientific Model Development.

[38]  Christopher J. Smith,et al.  Effective radiative forcing and adjustments in CMIP6 models , 2020, Atmospheric Chemistry and Physics.

[39]  K. Taylor,et al.  Causes of Higher Climate Sensitivity in CMIP6 Models , 2020, Geophysical Research Letters.

[40]  C. Heinze,et al.  Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2) , 2020, Geoscientific Model Development.

[41]  L. Mu,et al.  Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1 , 2020, Journal of Advances in Modeling Earth Systems.

[42]  D. Saint‐Martin,et al.  Present‐Day and Historical Aerosol and Ozone Characteristics in CNRM CMIP6 Simulations , 2020, Journal of Advances in Modeling Earth Systems.

[43]  Bettina K. Gier,et al.  Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP , 2020, Geoscientific Model Development.

[44]  B. Sanderson Relating climate sensitivity indices to projection uncertainty , 2019, Earth System Dynamics.

[45]  Pierre Friedlingstein,et al.  Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models , 2019, Biogeosciences.

[46]  A. J. Hewitt,et al.  UKESM1: Description and Evaluation of the U.K. Earth System Model , 2019, Journal of Advances in Modeling Earth Systems.

[47]  R. Waldman,et al.  Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future Climate , 2019, Journal of Advances in Modeling Earth Systems.

[48]  J. Rogelj,et al.  Path Independence of Carbon Budgets When Meeting a Stringent Global Mean Temperature Target After an Overshoot , 2019, Earth's Future.

[49]  N. Maher,et al.  How large does a large ensemble need to be? , 2019, Earth System Dynamics.

[50]  Shian-Jiann Lin,et al.  Structure and Performance of GFDL's CM4.0 Climate Model , 2019, Journal of Advances in Modeling Earth Systems.

[51]  B. Santer,et al.  Quantifying stochastic uncertainty in detection time of human-caused climate signals , 2019, Proceedings of the National Academy of Sciences.

[52]  Y. Byun,et al.  Evaluation of the Korea Meteorological Administration Advanced Community Earth-System model (K-ACE) , 2019, Asia-Pacific Journal of Atmospheric Sciences.

[53]  N. Gillett,et al.  The Canadian Earth System Model version 5 (CanESM5.0.3) , 2019, Geoscientific Model Development.

[54]  Guoxiong Wu,et al.  CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation , 2019, Advances in Atmospheric Sciences.

[55]  H. Douville,et al.  Evaluation of CMIP6 DECK Experiments With CNRM‐CM6‐1 , 2019, Journal of Advances in Modeling Earth Systems.

[56]  Philip W. Jones,et al.  The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution , 2019, Journal of Advances in Modeling Earth Systems.

[57]  H. Tsujino,et al.  The Meteorological Research Institute Earth System Model Version 2.0, MRI-ESM2.0: Description and Basic Evaluation of the Physical Component , 2019, Journal of the Meteorological Society of Japan. Ser. II.

[58]  The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6 , 2019, Geoscientific Model Development.

[59]  Guoxiong Wu,et al.  Evaluation of FAMIL2 in Simulating the Climatology and Seasonal‐to‐Interannual Variability of Tropical Cyclone Characteristics , 2019, Journal of Advances in Modeling Earth Systems.

[60]  Alexander J. Winkler,et al.  Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2 , 2019, Journal of advances in modeling earth systems.

[61]  S. V. Emelina,et al.  Simulation of the modern climate using the INM-CM48 climate model , 2018, Russian Journal of Numerical Analysis and Mathematical Modelling.

[62]  S. Gualdi,et al.  Global Mean Climate and Main Patterns of Variability in the CMCC‐CM2 Coupled Model , 2018, Journal of Advances in Modeling Earth Systems.

[63]  T. Zhou,et al.  The CAMS Climate System Model and a Basic Evaluation of Its Climatology and Climate Variability Simulation , 2018, Journal of Meteorological Research.

[64]  Jochem Marotzke,et al.  Quantifying the irreducible uncertainty in near‐term climate projections , 2018, WIREs Climate Change.

[65]  K. Calvin,et al.  Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century , 2018, Geoscientific Model Development.

[66]  Antony Siahaan,et al.  The Low‐Resolution Version of HadGEM3 GC3.1: Development and Evaluation for Global Climate , 2018, Journal of advances in modeling earth systems.

[67]  Dai Yamazaki,et al.  Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6 , 2018, Geoscientific Model Development.

[68]  J. Marotzke,et al.  A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR) , 2018, Journal of Advances in Modeling Earth Systems.

[69]  J. Schwinger,et al.  Ocean Carbon Cycle Feedbacks Under Negative Emissions , 2018 .

[70]  R. Krishnan,et al.  Long‐Term Climate Simulations Using the IITM Earth System Model (IITM‐ESMv2) With Focus on the South Asian Monsoon , 2018 .

[71]  David P. Keller,et al.  The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6 , 2018 .

[72]  S. Rahmstorf,et al.  Observed fingerprint of a weakening Atlantic Ocean overturning circulation , 2017, Nature.

[73]  Bin Wang,et al.  The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation , 2017, Geoscientific Model Development.

[74]  C. Deser,et al.  Precipitation variability increases in a warmer climate , 2017, Scientific Reports.

[75]  D. N. Walters,et al.  The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations , 2017 .

[76]  Larry W. Thomason,et al.  A global space-based stratospheric aerosol climatology: 1979–2016 , 2017 .

[77]  Spencer A. Hill,et al.  Change in the magnitude and mechanisms of global temperature variability with warming , 2017, Nature climate change.

[78]  Paul Charbonneau,et al.  Solar Forcing for CMIP6 (v3.1) , 2016 .

[79]  Meng Li,et al.  Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS) , 2017 .

[80]  E. Volodin,et al.  Simulation of the present-day climate with the climate model INMCM5 , 2017, Climate Dynamics.

[81]  Veronika Eyring,et al.  CMIP5 Scientific Gaps and Recommendations for CMIP6 , 2017 .

[82]  P. Kyle,et al.  The SSP4: A world of deepening inequality , 2017 .

[83]  K. Calvin,et al.  Future air pollution in the Shared Socio-economic Pathways , 2017 .

[84]  M. Strubegger,et al.  Shared Socio-Economic Pathways of the Energy Sector – Quantifying the Narratives , 2017 .

[85]  J. Eom,et al.  The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview , 2017 .

[86]  K. Calvin,et al.  Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century , 2017 .

[87]  G. Myhre,et al.  Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing , 2016 .

[88]  N. Keenlyside,et al.  Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model , 2016 .

[89]  Brian C. O'Neill,et al.  The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6 , 2016 .

[90]  George C. Hurtt,et al.  The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6:rationale and experimental design , 2016 .

[91]  Pierre Friedlingstein,et al.  C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6 , 2016 .

[92]  J. Lamarque,et al.  AerChemMIP: quantifying the effects of chemistry and aerosols in CMIP6 , 2016 .

[93]  Veronika Eyring,et al.  Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization , 2015 .

[94]  Hans Joachim Schellnhuber,et al.  Long-term response of oceans to CO2 removal from the atmosphere , 2015 .

[95]  C. Stock,et al.  A more productive, but different, ocean after mitigation , 2015 .

[96]  R. Knutti,et al.  Sensitivity of carbon budgets to permafrost carbon feedbacks and non-CO2 forcings , 2015 .

[97]  Shingo Watanabe,et al.  The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results , 2015 .

[98]  K. Zickfeld,et al.  The effectiveness of net negative carbon dioxide emissions in reversing anthropogenic climate change , 2015 .

[99]  Brian C. O'Neill,et al.  Sensitivity of regional climate to global temperature and forcing , 2015 .

[100]  Reto Knutti,et al.  Improved pattern scaling approaches for the use in climate impact studies , 2015 .

[101]  Claudia Tebaldi,et al.  Pattern scaling: Its strengths and limitations, and an update on the latest model simulations , 2014, Climatic Change.

[102]  Keywan Riahi,et al.  A new scenario framework for climate change research: the concept of shared climate policy assumptions , 2014, Climatic Change.

[103]  T. Carter,et al.  Climate and socio-economic scenarios for climate change research and assessment: reconciling the new with the old , 2014, Climatic Change.

[104]  Keywan Riahi,et al.  A new scenario framework for Climate Change Research: scenario matrix architecture , 2014, Climatic Change.

[105]  C. Tebaldi,et al.  Delayed detection of climate mitigation benefits due to climate inertia and variability , 2013, Proceedings of the National Academy of Sciences.

[106]  P. Jones,et al.  No increase in global temperature variability despite changing regional patterns , 2013, Nature.

[107]  Keywan Riahi,et al.  A new scenario framework for climate change research: the concept of shared socioeconomic pathways , 2013, Climatic Change.

[108]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[109]  R. Allan,et al.  Energetic Constraints on Precipitation Under Climate Change , 2012, Surveys in Geophysics.

[110]  E. Hawkins,et al.  A Simple, Coherent Framework for Partitioning Uncertainty in Climate Predictions , 2011 .

[111]  K. Calvin,et al.  The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 , 2011 .

[112]  John F. B. Mitchell,et al.  The next generation of scenarios for climate change research and assessment , 2010, Nature.

[113]  Nir Y. Krakauer,et al.  How much will precipitation increase with global warming , 2008 .

[114]  Keith W. Dixon,et al.  Review of simulations of climate variability and change with the GFDL R30 coupled climate model , 2002 .