Past warming trend constrains future warming in CMIP6 models

Tokarska, Katarzyna; Stolpe, Martin B.; Sippel, Sebastian; Fischer, Erich M.; Smith, Christopher J.; Lehner, Flavio; Knutti, Reto

doi:10.1126/sciadv.aaz9549

Cited by 462 publications

(419 citation statements)

References 51 publications

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“…We show warming relative to the same historical baseline of 1986-2005 used by CMIP5 (Taylor et al, 2012) and to 1850-1900. We further show how observational constraints applied to the range of trajectories from the new models based on recently published work (Tokarska et al, 2020) result in lower and narrower projections at the end of the century, and have the effect of bringing CMIP6 projections in closer alignment to CMIP5 end-of-the century warming.…”

Section: Comparison Of Climate Projections From Cmip6 and Cmip5 For Tmentioning

confidence: 86%

“…The higher climate sensitivities in CMIP6 compared to CMIP5 (Meehl et al, 2020;Zelinka et al, 2020) become more critical for higher forcings, explaining the differential in the higher warming across the range of new scenarios, with the largest difference evident for SSP5-8.5. Tokarska et al (2020) and Liang et al (2020) are at the time of writing the only published studies that sought to constrain the ensemble projections according to the evaluation of the ensemble historical behavior (Ribes et al, 2020 adopts a similar approach and is currently in revision). All studies find a strong correlation between the simulated warming trends over the observed historical period and the warming in SSP scenarios, which suggested constraining future warming using observed warming trends estimated from several observational products.…”

Section: Comparison Of Climate Projections From Cmip6 and Cmip5 For Tmentioning

confidence: 99%

“…The focus of this paper is to provide physical climate context for these more detailed analyses. Other Model Intercomparison Projects within CMIP6 have prescribed experiments that complement the ScenarioMIP design to address questions about the effects of small radiative forcing differences, specific (and often local) forcings like from land-use and short-lived climate forcers (SLCFs), the differential effects of emission versus concentration driven experiments testing the strength of the carbon cycle (Arora et al, 2019), and the effectiveness of emergent constraints in reshaping the uncertainty ranges of the new multi-model ensemble (Nijsse et al, 2020;Tokarska et al, 2020). They are the Land Use MIP (LUMIP, Lawrence et al, 2016), the Aerosol Chemistry MIP (AerChemMIP, Collins et al, 2017), the Coupled Climate-Carbon Cycle MIP (C4MIP, Jones et al, 2016), the Geoengineering MIP (GeoMIP, Kravitz et al, 2015) and the Carbon Dioxide Removal MIP (CDRMIP, Keller et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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

Tebaldi¹,

Debeire²,

Eyring³

et al. 2020

Preprint

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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.

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Section: Comparison Of Climate Projections From Cmip6 and Cmip5 For Tmentioning

confidence: 86%

Section: Comparison Of Climate Projections From Cmip6 and Cmip5 For Tmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Tebaldi¹,

Debeire²,

Eyring³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Models performed passively across diverse topography and geography for their sensitivity/passiveness to variations such as mountains, with resolution issues all functioning simultaneously [76]. Moreover, higher climate sensitivity caused overestimations and underestimations, leading to biases in present and future climate estimates [29].…”

Section: Discussionmentioning

confidence: 99%

“…Utilizing recalibrated/constrained models, robust use of ensembles based on process links, use of past trends, and climatology for current observation and consistent future projections are recommended procedures against biases. The high equilibrium climate sensitivity models better access the earth system behavior at higher levels of warming to estimate increase in extreme events [29].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014

et al. 2020

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This work employed recent model outputs from coupled model intercomparison project phase six to simulate surface mean temperature during the June–July–August (JJA) and December–January–February (DJF) seasons for 1970–2014 over Pakistan. The climatic research unit (CRU TS4.03) dataset was utilized as benchmark data to analyze models’ performance. The JJA season exhibited the highest mean temperature, whilst DJF displayed the lowest mean temperature in the whole study period. The JJA monthly empirical cumulative distribution frequency (ECDF) range (26 to 28 °C) was less than that of DJF (7 to 10 °C) since JJA matched closely to CRU. The JJA and DJF seasons are warming, with higher warming trends in winters than in summers. On temporal scale, models performed better in JJA with overall low bias, low RMSE (root mean square error), and higher positive CC (correlation coefficient) values. DJF performance was undermined with higher bias and RMSE with weak positive correlation estimates. Overall, CanESM5, CESM2, CESM2-WACCM, GFDL-CM4, HadGEM-GC31-LL, MPI-ESM1-2-LR, MPI-ESM1-2-HR, and MRI-ESM-0 performed better for JJA and DJF.

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Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

Semmler

Danilov

Gierz

et al. 2020

Preprint

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The Alfred Wegener Institute Climate Model (AWI-CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice-ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max Planck Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI-CM performs better than the average of CMIP5 models. AWI-CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea-ice extent in September over the past 30 years is 20-30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present-day climate under the strong emission scenario SSP585 are similar to the multi-model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2°C to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical, and Southern Ocean. Furthermore, in the northern middle latitudes in boreal summer and autumn as well as in the southern middle latitudes, a more zonal atmospheric flow is projected throughout the year.Plain Language Summary The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) participates for the first time with a global climate model in the Coupled Model Intercomparison Project 6 (CMIP6). The results of CMIP6 and previous model comparison projects feed into the next assessment report of the Intergovernmental Panel on Climate Change (IPCC). The IPCC assessment reports include information on past and expected climate change in the future and is written for policy-and decision-makers as well as for the general public. The main characteristics of the AWI climate model are described and compared to models from previous intercomparison projects. The projected global warming in AWI-CM is similar to the average warming predicted by climate models in the previous intercomparison project. However, the Arctic sea-ice extent declines faster than typical previous estimates. Areas that are wet in present-day climate become wetter, and areas that are dry in present-day climate become drier in the future-consistent with previous climate model simulations. The ocean currents remain rather stable in the AWI climate projections, which leads to a continued warm Gulf stream and therefore an only slightly reduced warming of the North Atlantic and parts of Europe compared to other middle-latitude regions.

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Past warming trend constrains future warming in CMIP6 models

Cited by 462 publications

References 51 publications

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

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

Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014

Simulations for CMIP6 with the AWI climate model AWI-CM-1-1

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