Articles | Volume 15, issue 23
https://doi.org/10.5194/gmd-15-8831-2022
https://doi.org/10.5194/gmd-15-8831-2022
Model description paper
 | 
12 Dec 2022
Model description paper |  | 12 Dec 2022

Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios

Thomas Bossy, Thomas Gasser, and Philippe Ciais

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Short summary
We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.