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. 2024 Apr 19;10(16):eadk9461.
doi: 10.1126/sciadv.adk9461. Epub 2024 Apr 17.

Last Glacial Maximum pattern effects reduce climate sensitivity estimates

Vincent T Cooper  1 , Kyle C Armour  1   2 , Gregory J Hakim  1 , Jessica E Tierney  3 , Matthew B Osman  4 , Cristian Proistosescu  5 , Yue Dong  6 , Natalie J Burls  7 , Timothy Andrews  8 , Daniel E Amrhein  9 , Jiang Zhu  9 , Wenhao Dong  10   11 , Yi Ming  12 , Philip Chmielowiec  5
Affiliations

Last Glacial Maximum pattern effects reduce climate sensitivity estimates

Vincent T Cooper et al. Sci Adv. .

Abstract

Here, we show that the Last Glacial Maximum (LGM) provides a stronger constraint on equilibrium climate sensitivity (ECS), the global warming from increasing greenhouse gases, after accounting for temperature patterns. Feedbacks governing ECS depend on spatial patterns of surface temperature ("pattern effects"); hence, using the LGM to constrain future warming requires quantifying how temperature patterns produce different feedbacks during LGM cooling versus modern-day warming. Combining data assimilation reconstructions with atmospheric models, we show that the climate is more sensitive to LGM forcing because ice sheets amplify extratropical cooling where feedbacks are destabilizing. Accounting for LGM pattern effects yields a median modern-day ECS of 2.4°C, 66% range 1.7° to 3.5°C (1.4° to 5.0°C, 5 to 95%), from LGM evidence alone. Combining the LGM with other lines of evidence, the best estimate becomes 2.9°C, 66% range 2.4° to 3.5°C (2.1° to 4.1°C, 5 to 95%), substantially narrowing uncertainty compared to recent assessments.

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Figures

Fig. 1.
Fig. 1.. Patterns of SST anomalies from data assimilation at the LGM compared to modern-day doubling of CO2 (2xCO2).
LGM reconstructions include (A) LGMR (32), (B) Amrhein (34), (C) lgmDA (3), (D) Annan (33), and (E) shows the mean of the four LGM patterns. (F) Pattern of the multimodel mean from near-equilibrium 2xCO2 simulations in LongRunMIP (39), initialized from preindustrial control. To show SST patterns, local SST anomalies are divided by absolute values of global mean SST anomalies. All panels show annual means. LGM reconstructions are infilled to modern coastlines (Materials and Methods).
Fig. 2.
Fig. 2.. LGM and 2xCO2 climate feedbacks and LGM pattern effect (Δλ).
Different AGCMs, all using the LGMR pattern for the LGM, are indicated by symbols; different LGM patterns (in CAM5 and CAM4) are indicated by colors. Error bars for Annan and LGMR represent first and fourth quartiles of ensemble members (Materials and Methods); central values indicate ensemble mean. For comparison with AGCM results using LGM data assimilation, the following feedbacks (in a mixed-layer ocean coupled to AGCM) from previous studies are also included: CESM1-CAM5 (23), CESM2-CAM6 (48), and CESM2-PaleoCalibr (49) (modified version of CAM6). (A) Scatterplot of 2xCO2 feedbacks, λ2x, versus LGM feedbacks, λLGM, with λ2x = λLGM shown as dotted line. (B) LGM pattern effect, Δλ = λ2x − λLGM, using feedbacks shown in (A), with Δλ = 0 shown as dotted line. Note that Δλ includes SST pattern effects and contributions from temperature dependence.
Fig. 3.
Fig. 3.. Zonal mean patterns of ERF and SST anomalies.
All anomalies are normalized through division by global mean anomalies. (A to C) Model simulations in CESM1-CAM5 from Zhu and Poulsen (23). (A) ERF directly from three fixed-SST simulations using AGCM with LGM greenhouse gas (GHG) and ice-sheet (Ice) forcing, 2xCO2, and LGM ice-sheet forcing alone (including coastline changes) (23). (B) Equilibrium SST patterns, corresponding to (A), in the coupled mixed-layer ocean model. (C) Quasi-equilibrium SST patterns from fully coupled atmosphere-ocean model, comparing LGM forcings (23) with abrupt-4xCO2 forcing (88); no long-run 2xCO2 simulation is available. Note vertical-axis scales. (D) Mean and range of SST patterns from four data assimilation reconstructions (, –34) of the LGM compared to 2xCO2 multimodel mean from LongRunMIP (39).
Fig. 4.
Fig. 4.. Inference of modern-day climate sensitivity including the LGM pattern effect.
Results from WCRP20 (1) with no LGM pattern effects and original assumption of ΔTLGM ~ N(μ = −5, σ = 1) K (gray) and with revised ΔTLGM ~ N(−6, 1) K (black) based on IPCC AR6 (2). Revised climate sensitivity including LGM pattern effects from this study (light and dark blue) assuming Δλ ~ N(μ = −0.37, σ = 0.23) Wm−2 K−1. Climate sensitivity shown is effective sensitivity (S) representing 150-year response, as in WCRP20 (1). (A) Likelihood functions for S based on only the LGM line of evidence. (B) Posterior probability density function (PDF) after combining LGM with other lines of evidence, assuming a uniform-λ prior (top) or a uniform-S prior (bottom). Outlier lines indicate 5th to 95th percentiles, dots indicate 66% “likely” range, and box indicates 25th to 75th percentiles and median.
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