Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 11, issue 1
Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-195-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-195-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 1
Methods for assessment of models
 | 
17 Jan 2018
Methods for assessment of models |  | 17 Jan 2018

On the predictability of land surface fluxes from meteorological variables

Ned Haughton, Gab Abramowitz, and Andy J. Pitman

Viewed

Total article views: 3,936 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,641 1,179 116 3,936 582 160 210
  • HTML: 2,641
  • PDF: 1,179
  • XML: 116
  • Total: 3,936
  • Supplement: 582
  • BibTeX: 160
  • EndNote: 210
Views and downloads (calculated since 12 Jul 2017)
Cumulative views and downloads (calculated since 12 Jul 2017)

Viewed (geographical distribution)

Total article views: 3,936 (including HTML, PDF, and XML) Thereof 3,763 with geography defined and 173 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 25 Oct 2025
Download
Short summary
Previous studies indicate that fluxes of heat, water, and carbon between the land surface and atmosphere are substantially more predictable than the performance of the current crop of land surface models would indicate. This study uses simple empirical models to estimate the amount of useful information in meteorological forcings that is available for predicting land surface fluxes. These models can be used as benchmarks for land surface models and may help identify areas ripe for improvement.
Read more
Share