ORCHIDEE_v2_r5968

This version of ORCHIDEE has been used in the publication "Exploring the Potential of History Matching for Land Surface Model Calibration" by Raoult et al.

Abstract

With the growing complexity of land surface models used to represent the terrestrial part of wider Earth system models, the need for sophisticated and robust parameter optimisation techniques is paramount. Quantifying parameter uncertainty is essential for both model development and more accurate projections. In this study, we assess the power of history matching by comparing results to variational data assimilation, commonly used in land surface models for parameter estimation. Although both approaches have different setups and goals, we can extract posterior parameter distributions from both methods and test the model-data fit of ensembles sampled from these distributions. Using a twin experiment, we test whether we can recover known parameter values. Through variational data assimilation, we closely match the observations. However, the known parameter values are not always contained in the posterior parameter distribution, highlighting the equifinality of the parameter space. In contrast, while more conservative, history matching still gives a reasonably good fit and provides more information about the model structure by allowing for non-Gaussian parameter distributions. Furthermore, the true parameters are contained in the posterior distributions. We then consider history matching’s ability to ingest different metrics targeting different physical parts of the model, helping to reduce parameter space further and improve model-data fit. We find the best results when history matching is used with multiple metrics; not only is the model-data fit improved, but we also gain a deeper understanding of the model and how the different parameters constrain different parts of the seasonal cycle. We conclude by discussing the potential of history matching in future studies.

• See the version on the webinterface here: ​https://forge.ipsl.jussieu.fr/orchidee/browser/branches/publications/ORCHIDEE_v2_r5968
• Extract it on a terminal as follows, typing anonymous as password:

  svn co --username anonymous svn://forge.ipsl.jussieu.fr/orchidee/branches/publications/ORCHIDEE_v2_r5968 ORCHIDEE
  

Metadata

DOI	[under request]
Creator	Nina Raoult
Affiliation	LSCE
Title	ORCHIDEE_v2_r5968
Publisher	Institut Pierre Simon Laplace (IPSL)
PublicationYear	2024
ResourceType	Software
Rights	This software is distributed under the CeCILL license.
rightsURI	​http://www.cecill.info/
Subject	History Matching, ORCHIDAS
DataManager	Vincent Drouet (IPSL)
DataCurator	Josefine Ghattas (IPSL)
ContactPerson	Nina Raoult (LSCE)
FundingReference	-