Armour Kyle C, Proistosescu Cristian, Dong Yue, Hahn Lily C, Blanchard-Wrigglesworth Edward, Pauling Andrew G, Jnglin Wills Robert C, Andrews Timothy, Stuecker Malte F, Po-Chedley Stephen, Mitevski Ivan, Forster Piers M, Gregory Jonathan M
Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195.
School of Oceanography, University of Washington, Seattle, WA 98195.
Proc Natl Acad Sci U S A. 2024 Mar 19;121(12):e2312093121. doi: 10.1073/pnas.2312093121. Epub 2024 Mar 11.
The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.
自20世纪70年代以来观测到的全球变暖速率,被认为是对平衡气候敏感度(ECS)和瞬态气候响应(TCR)的一个强约束条件,这两个指标是全球气候对温室气体强迫响应的关键指标。利用CMIP5/6模型,我们发现变暖与这些气候敏感度指标之间的模型间关系(即约束条件的基础)源于模型内瞬态和平衡变暖模式的相似性,从而产生了一个控制近期变暖的有效气候敏感度(EffCS),它与在CO₂强迫下控制长期变暖的ECS值相当。然而,CMIP5/6的历史模拟并未再现观测到的变暖模式。当由观测模式驱动时,即使是高ECS模型也会产生与观测到的全球变暖速率一致的低EffCS值。因此,CMIP5/6模型无法再现观测到的变暖模式,导致了近期全球变暖和气候敏感度之间模拟关系的偏差。校正这一偏差意味着观测到的变暖与广泛的ECS和TCR范围一致,这些范围延伸到比之前认识到的更高的值。能量平衡模型模拟和耦合模型(CESM1-CAM5)模拟证实了这些发现,这些模拟通过对流层风 nudging或南极融水通量能更好地再现观测模式。由于CMIP5/6模型未能模拟出观测到的变暖模式,基于变暖对ECS、TCR和预估全球变暖所提出的约束存在偏低的偏差。这些结果强化了最近的研究发现,即观测到的独特变暖模式在近几十年减缓了全球平均变暖,并且该模式未来将如何演变是气候预测中不确定性的一个主要来源。