Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 11, issue 3
Articles | Volume 11, issue 3
https://doi.org/10.5194/gmd-11-1181-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-1181-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 11, issue 3
Methods for assessment of models
 | 
29 Mar 2018
Methods for assessment of models |  | 29 Mar 2018

Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

Volkmar Sauerland, Ulrike Löptien, Claudine Leonhard, Andreas Oschlies, and Anand Srivastav

Viewed

Total article views: 3,071 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,270 703 98 3,071 105 96
  • HTML: 2,270
  • PDF: 703
  • XML: 98
  • Total: 3,071
  • BibTeX: 105
  • EndNote: 96
Views and downloads (calculated since 20 Jun 2017)
Cumulative views and downloads (calculated since 20 Jun 2017)

Viewed (geographical distribution)

Total article views: 3,071 (including HTML, PDF, and XML) Thereof 2,877 with geography defined and 194 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 22 Apr 2024
Download
Short summary
We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
Read more