Research ArticleCLIMATOLOGY

Past warming trend constrains future warming in CMIP6 models

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Science Advances  18 Mar 2020:
Vol. 6, no. 12, eaaz9549
DOI: 10.1126/sciadv.aaz9549
  • Fig. 1 Global mean temperature anomaly and its decadal trend in CMIP6 models in response to different radiative forcings.

    (A) Simulated global mean surface air temperature (GSAT) anomaly relative to 1850–1900 in CMIP6 models forced with different forcings during the historical period: anthropogenic aerosols (blue), natural forcing (solar irradiance and stratospheric aerosol; yellow), well-mixed greenhouse gases (GHG; red), and all natural and anthropogenic forcings (historical; gray). The shaded area indicates the likely range (17 to 83% percentile). Note that the ensemble sizes differ for the experiments, and in particular, the historical experiment is available for a larger set of CMIP6 models. (B) Trend in GSAT from 1981 to 2014 (as not all models have simulations available until the year 2017), using the same set of simulations with different sets of forcings as in (A). The dashed horizontal lines indicate multimodel mean decadal trends for each simulation type. Note that for CESM2, the aerosol-only simulation was not available.

  • Fig. 2 Correlation of the simulated warming trend for the period 1981–2014 with TCR.

    (A) Correlation based on CMIP6 models, (B) based on CMIP5 models, and (C) based on the joint distribution of CMIP6 models (circles) and CMIP5 models (triangles). The emergent constraint is based on the mean of two observational datasets [Cowtan and Way (27) and GISTEMP (28, 29)], adjusted for the blending effects (gray vertical line). If a model had more than one ensemble member, its ensemble mean is shown and was used in the regression. On (A) to (C), the dark gray rectangle shows the ±1σ uncertainty range in the observed trends for the period 1981–2014 (with the uncertainty range encompassing effects of internal variability, blending, and structural uncertainties), and the light gray rectangle shows the ±2σ range (see Materials and Methods). The blue rectangle indicates the likely range (>66%) of the emergent constraint on future warming (TCR). The median value is shown by dashed blue line, and dotted blue lines indicate the 5 to 95% uncertainty range (see Materials and Methods on how the uncertainty range on constrained TCR was derived). (D) Constrained and unconstrained ranges of TCR based on CMIP6 and CMIP5 models [following from (A) to (C)], compared with the IPCC AR5 likely range. Unconstrained ranges (gray box plots) are based on raw CMIP models, shown to the left of each box plot by individual dots. Constrained ranges (blue box plots) are based on the emergent constraint (as in top panels). The last box plot in (D) shows the IPCC AR5 likely (>66% probability; equivalent to 17 to 83% range) range. Each box plot shows 5 to 95% range, likely range, and median value, as illustrated in the legend.

  • Fig. 3 Correlation of the simulated warming trend for the period 1981–2014 with ECS.

    (A) Based on CMIP6 models, (B) based on CMIP5 models, and (C) based on the joint distribution of CMIP6 models (circles) and CMIP5 models (triangles). Gray rectangles show the ±1σ and ±2σ ranges of uncertainty in the observed trend for the period 1981–2014, based on the mean of the Cowtan and Way (27) and GISTEMP (28, 29) datasets (as in Fig. 2).

  • Fig. 4 Pattern covariance between each model’s trend map (global mean trend removed) and multimodel mean fingerprint.

    (A) Multimodel mean deviation of regional warming trends from the global mean warming trend (fingerprint of regional trend variation). (B) Correlation of the pattern covariance metric [that is, the covariance of each model’s regional trend pattern (global mean removed) with the multimodel mean fingerprint shown in (A)] with each model’s TCR. The dashed black line in (B) indicates an observational estimate, based on the mean of the observational datasets [Cowtan and Way (27) and GISTEMP (28, 29)], and the gray rectangles indicate estimate of uncertainty in the observations due to internal variability at 1σ and 2σ levels (based on the large ensembles simulations listed in table S2). Spatial pattern information reveals that high TCR models simulate a large magnitude of a regional warming pattern without global mean information.

  • Fig. 5 Future warming constrained by the observed warming trend in comparison with the Paris Agreement target.

    (A) Future constrained warming by mid-century (years 2041–2060) in the high-emission SSP5-8.5 scenario. (B) As (A) but in the ambitious mitigation SSP1-2.6 scenario. (C) Constrained warming by the end of the century (2081–2100) in SSP5-8.5 scenario. (D) As (C) but in SSP1-2.6 scenario. (E and F) Resulting constrained and unconstrained (raw) ranges, as labeled. Future warming is with respect to the 1850–1900 baseline in all panels. Gray rectangles show observed warming trends for the period 1981–2017, using the mean of the observational datasets [Cowtan and Way (27) and GISTEMP (28, 29)], with ±1σ and ±2σ uncertainty ranges. Blue rectangle indicates the likely range (>66%) of the emergent constraints on future warming. The median value is shown by dashed blue lines, and dotted blue lines indicate 5 to 95% uncertainty range. Yellow lines indicate the Paris Agreement thresholds of 1.5° and 2.0°C, and the yellow shaded area indicates warming interval consistent with achieving the Paris Agreement. Note: Future GSAT warming was adjusted for each model to make simulated warming consistent with the definition of a Paris Agreement temperature metric (35). For full model names, see Fig. 2.

  • Fig. 6 Future warming in CMIP5 and CMIP6 models (with respect to 1995–2014 baseline), constrained by the observed warming trend (1981–2017).

    (A) Constrained warming in SSP5-8.5 scenario (based on CMIP6 ensemble), in RCP 8.5 scenario, and estimated CMIP5 response to SSP5-8.5 scenario (i.e., CMIP5 scaled by the total forcing ratio, for a like-for-like comparison of responses to SSP and RCP scenarios). (B) In SSP1-2.6 scenario. Colored dots on each panel show the full CMIP6 simulated range by mid-century (years 2041–2060) and by the end of the century (years 2081–2100), with respect to the 1995–2014 baseline. The panels have different vertical axis limits. Note: The baseline for the future warming (ΔT with respect to 1995–2014) is different than in Fig. 5 (1850–1900). See fig. S4 for scatter plots and correlations and fig. S5 for constrained warming of the SSP2-4.5 and SSP3-7.0 scenarios. Constrained warming is based on the mean of the observational datasets [Cowtan and Way (27) and GISTEMP (28, 29)] as in fig. S4.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/6/12/eaaz9549/DC1

    Fig. S1. Estimated contribution of Pacific and Atlantic internal variability to GSAT in °C per decade during 1981–2014 and 1981–2017.

    Fig. S2. Correlation of the simulated warming trend for the period 1981–2017 with TCR.

    Fig. S3. Correlation of the simulated warming trend for the period 1981–2014 with TCR, showing different types of regression and methods of estimating the uncertainty of the regression.

    Fig. S4. Correlations of future warming in CMIP5 and CMIP6 models (with respect to 1995–2014 baseline), with the simulated past warming trend (1981–2017).

    Fig. S5. Correlations of future warming in CMIP6 models (with respect to 1995–2014 baseline), with the simulated past warming trend (1981–2017).

    Fig. S6. Correlations of TCR and ECS with future warming in CMIP6 and CMIP5 models.

    Table S1. CMIP6 models used in this study with their TCR and ECS values.

    Table S2. GSAT trends for the periods 1981–2017 and 1981–2014 and estimates of the effect of internal variability of CMIP5 and CMIP6 models.

    Table S3. TCR ranges (constrained and unconstrained) in CMIP6 and CMIP5 models.

    Table S4. Future warming (constrained and unconstrained) in CMIP6 models under different SSP scenarios, as labeled.

    References (55, 56)

  • Supplementary Materials

    This PDF file includes:

    • Fig. S1. Estimated contribution of Pacific and Atlantic internal variability to GSAT in °C per decade during 1981–2014 and 1981–2017.
    • Fig. S2. Correlation of the simulated warming trend for the period 1981–2017 with TCR.
    • Fig. S3. Correlation of the simulated warming trend for the period 1981–2014 with TCR, showing different types of regression and methods of estimating the uncertainty of the regression.
    • Fig. S4. Correlations of future warming in CMIP5 and CMIP6 models (with respect to 1995–2014 baseline), with the simulated past warming trend (1981–2017).
    • Fig. S5. Correlations of future warming in CMIP6 models (with respect to 1995–2014 baseline), with the simulated past warming trend (1981–2017).
    • Fig. S6. Correlations of TCR and ECS with future warming in CMIP6 and CMIP5 models.
    • Table S1. CMIP6 models used in this study with their TCR and ECS values.
    • Table S2. GSAT trends for the periods 1981–2017 and 1981–2014 and estimates of the effect of internal variability of CMIP5 and CMIP6 models.
    • Table S3. TCR ranges (constrained and unconstrained) in CMIP6 and CMIP5 models.
    • Table S4. Future warming (constrained and unconstrained) in CMIP6 models under different SSP scenarios, as labeled.
    • References (55, 56)

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