Articles | Volume 13, issue 1
Development and technical paper
07 Jan 2020
Development and technical paper |  | 07 Jan 2020

The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0

Ewan Pinnington, Tristan Quaife, Amos Lawless, Karina Williams, Tim Arkebauer, and Dave Scoby


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 Ewan Pinnington on behalf of the Authors (09 Jul 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (14 Aug 2019) by Adrian Sandu
RR by Anonymous Referee #1 (29 Aug 2019)
RR by Anonymous Referee #2 (10 Sep 2019)
ED: Publish as is (19 Nov 2019) by Adrian Sandu
AR by Ewan Pinnington on behalf of the Authors (26 Nov 2019)  Author's response    Manuscript
Short summary
We present LAVENDAR, a mathematical method for combining observations with models of the terrestrial environment. Here we use it to improve estimates of crop growth in the UK Met Office land surface model. However, the method is model agnostic, requires no modification to the underlying code and can be applied to any part of the model. In the example application we improve estimates of maize yield by 74 % by assimilating observations of leaf area, crop height and photosynthesis.