Articles | Volume 11, issue 12
Geosci. Model Dev., 11, 4739–4754, 2018
Geosci. Model Dev., 11, 4739–4754, 2018

Development and technical paper 30 Nov 2018

Development and technical paper | 30 Nov 2018

Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

Vladislav Bastrikov et al.


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Vladislav Bastrikov on behalf of the Authors (05 Nov 2018)  Author's response
ED: Publish as is (16 Nov 2018) by David Lawrence
Short summary
In this study, we compare different methods for optimising parameters of the ORCHIDEE land surface model (LSM) using in situ observations. We use two minimisation methods - local gradient-based and global random search - applied either at each individual site or a group of sites characterised by one plant functional type. We demonstrate the advantages and challenges of different techniques and provide some advice on using it for the LSM parameters optimisation.