Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-7177-2022
https://doi.org/10.5194/gmd-15-7177-2022
Development and technical paper
 | 
23 Sep 2022
Development and technical paper |  | 23 Sep 2022

Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0

Chahan M. Kropf, Alessio Ciullo, Laura Otth, Simona Meiler, Arun Rana, Emanuel Schmid, Jamie W. McCaughey, and David N. Bresch

Viewed

Total article views: 3,396 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,495 846 55 3,396 45 32
  • HTML: 2,495
  • PDF: 846
  • XML: 55
  • Total: 3,396
  • BibTeX: 45
  • EndNote: 32
Views and downloads (calculated since 25 Apr 2022)
Cumulative views and downloads (calculated since 25 Apr 2022)

Viewed (geographical distribution)

Total article views: 3,396 (including HTML, PDF, and XML) Thereof 3,172 with geography defined and 224 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 18 Apr 2024
Download
Short summary
Mathematical models are approximations, and modellers need to understand and ideally quantify the arising uncertainties. Here, we describe and showcase the first, simple-to-use, uncertainty and sensitivity analysis module of the open-source and open-access climate-risk modelling platform CLIMADA. This may help to enhance transparency and intercomparison of studies among climate-risk modellers, help focus future research, and lead to better-informed decisions on climate adaptation.