Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4307-2021
https://doi.org/10.5194/gmd-14-4307-2021
Methods for assessment of models
 | 
08 Jul 2021
Methods for assessment of models |  | 08 Jul 2021

Multi-variate factorisation of numerical simulations

Daniel J. Lunt, Deepak Chandan, Alan M. Haywood, George M. Lunt, Jonathan C. Rougier, Ulrich Salzmann, Gavin A. Schmidt, and Paul J. Valdes

Viewed

Total article views: 3,031 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,271 660 100 3,031 134 70 75
  • HTML: 2,271
  • PDF: 660
  • XML: 100
  • Total: 3,031
  • Supplement: 134
  • BibTeX: 70
  • EndNote: 75
Views and downloads (calculated since 05 Jun 2020)
Cumulative views and downloads (calculated since 05 Jun 2020)

Viewed (geographical distribution)

Total article views: 3,031 (including HTML, PDF, and XML) Thereof 2,702 with geography defined and 329 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Jun 2024
Download
Short summary
Often in science we carry out experiments with computers in which several factors are explored, for example, in the field of climate science, how the factors of greenhouse gases, ice, and vegetation affect temperature. We can explore the relative importance of these factors by swapping in and out different values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.