netEC: an emergent constraint on Climate Sensitivity based on network analysis

Abstract

The 2015 Paris agreement was established to limit Greenhouse gas global warming below 1.5°C above preindustrial era values. Knowledge of climate sensitivity to greenhouse gas 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 CO2. Here, we use a holistic approach to summarize the behavior of modelled climate systems. Network analysis for Emergent Constraint (netEC) infers networks from complex and highly-dimensional datasets, 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 an emergent constraint that yields likely ranges of ECS (2.34-4.79°C) and TCR (1.53-2.50°C). These ranges are narrower than the unconstrained distributions and consistent with the ranges of the Intergovernmental Panel on Climate Change (IPCC). More importantly, our simplified representation of simulations suggests the low-sensitivity models (ECS < 3.0°C) and high sensitivity models (ECS ≥ 4.5°C) remain two groups of plausible models.