Published in

European Geosciences Union, Geoscientific Model Development, 23(15), p. 8831-8868, 2022

DOI: 10.5194/gmd-15-8831-2022

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

Journal article published in 2022 by Thomas Bossy ORCID, Thomas Gasser ORCID, Philippe Ciais ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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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 sixth 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 several uncertainty ranges – when run following standardized diagnostic experiments. Pathfinder is an open-source model, and this is its first comprehensive description.