Residual correlation and ensemble modelling to improve crop and grassland models

Renáta Sándor* (Corresponding Author), Fiona Ehrhardt, Peter Grace, Sylvie Recous, Pete Smith, Val Snow, Jean François Soussana, Bruno Basso, Arti Bhatia, Lorenzo Brilli, Jordi Doltra, Christopher D. Dorich, Luca Doro, Nuala Fitton, Brian Grant, Matthew Tom Harrison, Ute Skiba, Miko U.F. Kirschbaum, Katja Klumpp, Patricia LavilleJoel Léonard, Raphaël Martin, Raia Silvia Massad, Andrew D. Moore, Vasileios Myrgiotis, Elizabeth Pattey, Susanne Rolinski, Joanna Sharp, Ward Smith, Lianhai Wu, Qing Zhang, Gianni Bellocchi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Multi-model ensembles are becoming increasingly accepted for the estimation of agricultural carbon-nitrogen fluxes, productivity and sustainability. There is mounting evidence that with some site-specific observations available for model calibration (with vegetation data as a minimum requirement), median outputs assimilated from biogeochemical models (multi-model medians) provide more accurate simulations than individual models. Here, we evaluate potential deficiencies in how model ensembles represent (in relation to climatic factors) the processes underlying biogeochemical outputs in complex agricultural systems such as grassland and crop rotations including fallow periods. We do that by exploring the correlation of model residuals. We restricted the distinction between partial and full calibration to the two most relevant calibration stages, i.e. with plant data only (partial) and with a combination of plant, soil physical and biogeochemical data (full). It introduces and evaluates the trade-off between (1) what is practical to apply for model users and beneficiaries, and (2) what constitutes best modelling practice. The lower correlations obtained overall with fully calibrated models highlight the centrality of the full calibration scenario for identifying areas of model structures that require further development.

Original languageEnglish
Article number105625
Number of pages12
JournalEnvironmental Modelling and Software
Early online date24 Jan 2023
Publication statusPublished - 1 Mar 2023


  • Biogeochemical models
  • Correlation matrices
  • Ensemble modelling
  • Model calibration
  • Residual plot analysis


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