A tighter constraint on Earth-system sensitivity from long-term temperature and carbon-cycle observations

TL;DR

This paper refines estimates of Earth-system sensitivity (ESS) by integrating deep-time CO2 and temperature data with a Bayesian approach, resulting in a narrower and more reliable range of ESS values over the last 420 million years.

Contribution

It introduces a Bayesian method to constrain ESS using long-term data, improving accuracy and reducing uncertainty compared to previous approaches.

Findings

Median ESS estimate of 3.4°C with a 5-95% range of 2.6-4.7°C

Weaker chemical weathering improves model-data agreement during the Cretaceous

Constraining weathering mechanisms can further refine ESS estimates

Abstract

The long-term temperature response to a given change in CO2 forcing, or Earth-system sensitivity (ESS), is a key parameter quantifying our understanding about the relationship between changes in Earth's radiative forcing and the resulting long-term Earth-system response. Current ESS estimates are subject to sizable uncertainties. Long-term carbon cycle models can provide a useful avenue to constrain ESS, but previous efforts either use rather informal statistical approaches or focus on discrete paleoevents. Here, we improve on previous ESS estimates by using a Bayesian approach to fuse deep-time CO2 and temperature data over the last 420 Myrs with a long-term carbon cycle model. Our median ESS estimate of 3.4 deg C (2.6-4.7 deg C; 5-95% range) shows a narrower range than previous assessments. We show that weaker chemical weathering relative to the a priori model configuration via reduced weatherable land area yields better agreement with temperature records during the Cretaceous. Research into improving the understanding about these weathering mechanisms hence provides potentially powerful avenues to further constrain this fundamental Earth-system property.