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

Viewed

Total article views: 2,196 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,743 410 43 2,196 21 31
  • HTML: 1,743
  • PDF: 410
  • XML: 43
  • Total: 2,196
  • BibTeX: 21
  • EndNote: 31
Views and downloads (calculated since 25 Aug 2022)
Cumulative views and downloads (calculated since 25 Aug 2022)

Viewed (geographical distribution)

Total article views: 2,196 (including HTML, PDF, and XML) Thereof 2,015 with geography defined and 181 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 18 Apr 2024
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

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.