Articles | Volume 15, issue 19
https://doi.org/10.5194/bg-15-5801-2018
https://doi.org/10.5194/bg-15-5801-2018
Research article
 | 
04 Oct 2018
Research article |  | 04 Oct 2018

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

Istem Fer, Ryan Kelly, Paul R. Moorcroft, Andrew D. Richardson, Elizabeth M. Cowdery, and Michael C. Dietze

Viewed

Total article views: 6,022 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,914 1,956 152 6,022 114 125
  • HTML: 3,914
  • PDF: 1,956
  • XML: 152
  • Total: 6,022
  • BibTeX: 114
  • EndNote: 125
Views and downloads (calculated since 26 Feb 2018)
Cumulative views and downloads (calculated since 26 Feb 2018)

Viewed (geographical distribution)

Total article views: 6,022 (including HTML, PDF, and XML) Thereof 5,614 with geography defined and 408 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (preprint)

Latest update: 24 Apr 2024
Download
Short summary
The computer models we use to understand and forecast the ecosystem changes have multiple components that determine their outcomes. Due to our limited observation capacities, these components bear uncertainties that in return affect our predictions. While there are techniques for reducing these uncertainties, they are not applicable to every model due to computational and statistical barriers. This research presents a method that lowers those barriers and allows us to improve model predictions.
Altmetrics
Final-revised paper
Preprint