Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 27, issue 22
Articles | Volume 27, issue 22
https://doi.org/10.5194/hess-27-4087-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-4087-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 27, issue 22
Research article
 | 
14 Nov 2023
Research article |  | 14 Nov 2023

Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe

Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo

Viewed

Total article views: 2,513 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,970 471 72 2,513 61 55
  • HTML: 1,970
  • PDF: 471
  • XML: 72
  • Total: 2,513
  • BibTeX: 61
  • EndNote: 55
Views and downloads (calculated since 20 Dec 2022)
Cumulative views and downloads (calculated since 20 Dec 2022)

Viewed (geographical distribution)

Total article views: 2,513 (including HTML, PDF, and XML) Thereof 2,504 with geography defined and 9 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Read more