Articles | Volume 19, issue 13
https://doi.org/10.5194/gmd-19-6079-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-6079-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
09 Jul 2026
Development and technical paper |
| 09 Jul 2026
| 09 Jul 2026
Calibration of the MEMS v1 model over a continental soil inventory: a comparison of MCMC and 4DEnVar methods
European Commission, Joint Research Centre (JRC), Ispra, Italy
Tristan Quaife
National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading, United Kingdom
Fernando Fahl
European Commission, Joint Research Centre (JRC), Ispra, Italy
Yao Zhang
Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, USA
Emanuele Lugato
European Commission, Joint Research Centre (JRC), Ispra, Italy
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Toni Viskari, Janne Pusa, Istem Fer, Anna Repo, Julius Vira, and Jari Liski
Geosci. Model Dev., 15, 1735–1752, https://doi.org/10.5194/gmd-15-1735-2022, https://doi.org/10.5194/gmd-15-1735-2022, 2022
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We wanted to examine how the chosen measurement data and calibration process affect soil organic carbon model calibration. In our results we found that there is a benefit in using data from multiple litter-bag decomposition experiments simultaneously, even with the required assumptions. Additionally, due to the amount of noise and uncertainties in the system, more advanced calibration methods should be used to parameterize the models.
Olli Nevalainen, Olli Niemitalo, Istem Fer, Antti Juntunen, Tuomas Mattila, Olli Koskela, Joni Kukkamäki, Layla Höckerstedt, Laura Mäkelä, Pieta Jarva, Laura Heimsch, Henriikka Vekuri, Liisa Kulmala, Åsa Stam, Otto Kuusela, Stephanie Gerin, Toni Viskari, Julius Vira, Jari Hyväluoma, Juha-Pekka Tuovinen, Annalea Lohila, Tuomas Laurila, Jussi Heinonsalo, Tuula Aalto, Iivari Kunttu, and Jari Liski
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Short summary
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Short summary
In this work we examined how different assumptions regarding soil carbon model calibration affect the resulting model performance. We found that how the litter inputs are set have a meaningful impact on the calibrated model parameters. Furthermore, two calibration methods produced parameter sets that differed meaningfully from each other but fit the validation dataset equally well. These results raise meaningful questions how we evaluate soil carbon model performance.
In this work we examined how different assumptions regarding soil carbon model calibration...
