Quantifying Decarbonization Speed Across Climate Scenarios

This working paper introduces a simple numerical metric that measures the decarbonization speed implied by Integrated Assessment Model (IAM) climate scenarios. The metric enables high-dimensional, narrative-based scenario datasets to be ranked and compared in a transparent way, while providing a concise summary of the mitigation ambition embedded in each scenario.

Author(s)

Fangyuan Zhang, Senior Research Engineer, EDHEC Climate Institute

Climate scenarios are a fundamental tool for studying the interplay between economic activity, transition policy and climate change. However, their high dimensionality makes direct comparison across scenarios challenging. This paper addresses this challenge by defining a simple metric that summarizes the decarbonization speed implied by each scenario.

The analysis covers 126 publicly available IAM scenarios produced by six leading modelling teams. The decarbonization speed provides a numerical summary of the improvement in carbon intensity trajectories, allowing scenarios to be ranked and compared on a common scale. The results show that the ranking is consistent with Representative Concentration Pathway (RCP) assumptions, indicating that the metric is a useful summary of a scenario's mitigation policy.

The paper also constructs an empirical distribution of decarbonization speed estimates and fits a stylized parametric distribution to represent the ensemble of scenarios. Key statistics, including the mean, median and confidence intervals obtained through bootstrap resampling, provide a concise statistical characterization of decarbonization speeds across the IAM scenarios