Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2899-2023
https://doi.org/10.5194/gmd-16-2899-2023
Methods for assessment of models
 | 
26 May 2023
Methods for assessment of models |  | 26 May 2023

Various ways of using empirical orthogonal functions for climate model evaluation

Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren

Viewed

Total article views: 1,819 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,344 431 44 1,819 56 27 28
  • HTML: 1,344
  • PDF: 431
  • XML: 44
  • Total: 1,819
  • Supplement: 56
  • BibTeX: 27
  • EndNote: 28
Views and downloads (calculated since 08 Feb 2023)
Cumulative views and downloads (calculated since 08 Feb 2023)

Viewed (geographical distribution)

Total article views: 1,819 (including HTML, PDF, and XML) Thereof 1,773 with geography defined and 46 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 05 May 2024
Download
Short summary
A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.