Ricard Lucile, Falasca Fabrizio, Runge Jakob, Nenes Athanasios
Laboratory of Atmospheric Processes and their Impacts (LAPI), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Courant Institute of Mathematical Sciences, New York University, New York, NY, USA.
Nat Commun. 2024 Aug 13;15(1):6942. doi: 10.1038/s41467-024-50813-z.
The 2015 Paris agreement was established to limit Greenhouse gas (GHG) global warming below 1.5°C above preindustrial era values. Knowledge of climate sensitivity to GHG levels is central for formulating effective climate policies, yet its exact value is shroud in uncertainty. Climate sensitivity is quantitatively expressed in terms of Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR), estimating global temperature responses after an abrupt or transient doubling of CO. Here, we represent the complex and highly-dimensional behavior of modelled climate via low-dimensional emergent networks to evaluate Climate Sensitivity (netCS), by first reconstructing meaningful components describing regional subprocesses, and secondly inferring the causal links between these to construct causal networks. We apply this methodology to Sea Surface Temperature (SST) simulations and investigate two different metrics in order to derive weighted estimates that yield likely ranges of ECS (2.35-4.81°C) and TCR (1.53-2.60°C). These ranges are narrower than the unconstrained distributions and consistent with the ranges of the IPCC AR6 estimates. More importantly, netCS demonstrates that SST patterns (at "fast" timescales) are linked to climate sensitivity; SST patterns over the historical period exclude median sensitivity but not low-sensitivity (ECS < 3.0°C) or very high sensitivity (ECS ≥ 4.5°C) models.
2015年的《巴黎协定》旨在将全球温室气体（GHG）导致的全球变暖限制在比工业化前时代水平高1.5°C以下。了解气候对温室气体水平的敏感性是制定有效气候政策的核心，但确切数值仍存在不确定性。气候敏感性通过平衡气候敏感性（ECS）和瞬态气候响应（TCR）进行定量表达，用于估计二氧化碳突然或瞬态加倍后全球温度的响应。在此，我们通过低维涌现网络来表示模拟气候的复杂且高维行为，以评估气候敏感性（netCS），首先重建描述区域子过程的有意义组件，其次推断这些组件之间的因果联系以构建因果网络。我们将此方法应用于海表面温度（SST）模拟，并研究两种不同的指标，以得出加权估计值，从而得出ECS（2.35 - 4.81°C）和TCR（1.53 - 2.60°C）的可能范围。这些范围比无约束分布更窄，且与IPCC AR6估计的范围一致。更重要的是，netCS表明SST模式（在“快速”时间尺度上）与气候敏感性相关；历史时期的SST模式排除了中等敏感性，但未排除低敏感性（ECS < 3.0°C）或非常高敏感性（ECS ≥ 4.5°C）模型。
