Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3539-2021
https://doi.org/10.5194/gmd-14-3539-2021
Development and technical paper
 | 
11 Jun 2021
Development and technical paper |  | 11 Jun 2021

A Markov chain method for weighting climate model ensembles

Max Kulinich, Yanan Fan, Spiridon Penev, Jason P. Evans, and Roman Olson

Viewed

Total article views: 2,327 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,577 673 77 2,327 51 43
  • HTML: 1,577
  • PDF: 673
  • XML: 77
  • Total: 2,327
  • BibTeX: 51
  • EndNote: 43
Views and downloads (calculated since 01 Oct 2020)
Cumulative views and downloads (calculated since 01 Oct 2020)

Viewed (geographical distribution)

Total article views: 2,327 (including HTML, PDF, and XML) Thereof 2,161 with geography defined and 166 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Nov 2024
Download
Short summary
We present a novel stochastic approach based on Markov chains to estimate climate model weights of multi-model ensemble means. This approach showed improved performance (better correlation with observations) over existing alternatives during cross-validation and model-as-truth tests. The results of this comparative analysis should serve to motivate further studies in applications of Markov chain and other nonlinear methods to find optimal model weights for constructing ensemble means.