25 Aug 2022
25 Aug 2022
Status: this preprint is open for discussion.

Pathfinder v1.0: a Bayesian-inferred simple carbon-climate model to explore climate change scenarios

Thomas Bossy1,2,, Thomas Gasser1,, and Philippe Ciais2 Thomas Bossy et al.
  • 1International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
  • 2Laboratoire des Sciences du Climat et de l’Environnement (LSCE), Gif-sur-Yvette, France
  • These authors contributed equally to this work.

Abstract. The Pathfinder model was developed to fill a perceived gap within the range of existing simple climate models. Pathfinder is a compilation of existing formulations describing the climate and carbon cycle systems, chosen for their balance between mathematical simplicity and physical accuracy. The resulting model is simple enough to be used with Bayesian inference algorithms for calibration, which enables assimilation of the latest data from complex Earth system models and the IPCC 6th assessment report, as well as a yearly update based on observations of global temperature and atmospheric CO2. The model’s simplicity also enables coupling with integrated assessment models and their optimization algorithms, or running the model in a backward temperature-driven fashion. In spite of this simplicity, the model accurately reproduces behaviours and results from complex models – including uncertainty ranges – when ran following standardized diagnostic experiments. Pathfinder is open-source, and this is its first comprehensive description.

Thomas Bossy et al.

Status: open (until 25 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on egusphere-2022-802', Juan Antonio Añel, 21 Sep 2022 reply
    • AC1: 'Reply on CEC1', Thomas Bossy, 21 Sep 2022 reply
  • RC1: 'Comment on egusphere-2022-802', Anonymous Referee #1, 22 Sep 2022 reply
  • RC2: 'Comment on egusphere-2022-802', Ian Enting, 29 Sep 2022 reply

Thomas Bossy et al.

Model code and software

Pathfinder: v1.0 Thomas Gasser, Thomas Bossy

Thomas Bossy et al.


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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, possibility of coupling with integrated assessment models, and capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model, its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.