Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 7
Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4307-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4307-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 7
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: 3,194 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,397 692 105 3,194 145 74 90
  • HTML: 2,397
  • PDF: 692
  • XML: 105
  • Total: 3,194
  • Supplement: 145
  • BibTeX: 74
  • EndNote: 90
Views and downloads (calculated since 05 Jun 2020)
Cumulative views and downloads (calculated since 05 Jun 2020)

Viewed (geographical distribution)

Total article views: 3,194 (including HTML, PDF, and XML) Thereof 2,856 with geography defined and 338 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Nov 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.
Read more