Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-3119-2019
https://doi.org/10.5194/gmd-12-3119-2019
Development and technical paper
 | 
22 Jul 2019
Development and technical paper |  | 22 Jul 2019

Comparison of different sequential assimilation algorithms for satellite-derived leaf area index using the Data Assimilation Research Testbed (version Lanai)

Xiao-Lu Ling, Cong-Bin Fu, Zong-Liang Yang, and Wei-Dong Guo

Viewed

Total article views: 4,794 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,574 1,160 60 4,794 71 66
  • HTML: 3,574
  • PDF: 1,160
  • XML: 60
  • Total: 4,794
  • BibTeX: 71
  • EndNote: 66
Views and downloads (calculated since 03 Jan 2019)
Cumulative views and downloads (calculated since 03 Jan 2019)

Viewed (geographical distribution)

Total article views: 4,794 (including HTML, PDF, and XML) Thereof 4,022 with geography defined and 772 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 06 Dec 2024
Download
Short summary
Observation and simulation can provide the temporal and spatial variation of vegetation characteristics, while they are not satisfactory for understanding the mechanism of the exchange between ecosystems and atmosphere. Data assimilation (DA) can combine the observation and models via mathematical statistical analysis. Results show that the ensemble adjust Kalman filter (EAKF) is the optimal algorithm. In addition, models perform better when the DA accepts a higher proportion of observations.