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https://doi.org/10.5194/egusphere-2022-802
https://doi.org/10.5194/egusphere-2022-802
25 Aug 2022
 | 25 Aug 2022

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

Thomas Bossy, Thomas Gasser, and Philippe Ciais

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.

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Journal article(s) based on this preprint

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
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022,https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model, designed to fill a perceived gap within the existing...
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