Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 19, issue 12
Articles | Volume 19, issue 12
https://doi.org/10.5194/hess-19-4811-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-4811-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 19, issue 12
Research article
 | 
16 Dec 2015
Research article |  | 16 Dec 2015

Comparing the ensemble and extended Kalman filters for in situ soil moisture assimilation with contrasting conditions

D. Fairbairn, A. L. Barbu, J.-F. Mahfouf, J.-C. Calvet, and E. Gelati

Viewed

Total article views: 3,213 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,824 1,253 136 3,213 522 145 165
  • HTML: 1,824
  • PDF: 1,253
  • XML: 136
  • Total: 3,213
  • Supplement: 522
  • BibTeX: 145
  • EndNote: 165
Views and downloads (calculated since 05 Aug 2015)
Cumulative views and downloads (calculated since 05 Aug 2015)
Latest update: 02 Dec 2025
Download
Short summary
The ensemble Kalman filter (EnKF) and simplified extended Kalman filter (SEKF) root-zone soil moisture analyses are compared when assimilating in situ surface observations. In the synthetic experiments, the EnKF performs best because it can stochastically capture the errors in the precipitation. The two methods perform similarly in the real experiments. During the summer period, both methods perform poorly as a result of nonlinearities in the land surface model.
Read more
Share