Articles | Volume 12, issue 7
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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (13 May 2019)  Author's response
ED: Referee Nomination & Report Request started (24 May 2019) by Carlos Sierra
RR by Anonymous Referee #2 (02 Jun 2019)
ED: Publish subject to minor revisions (review by editor) (03 Jun 2019) by Carlos Sierra
AR by Svenja Lange on behalf of the Authors (12 Jun 2019)  Author's response
ED: Publish as is (17 Jun 2019) by Carlos Sierra
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.