Articles | Volume 7, issue 6
Geosci. Model Dev., 7, 2683–2692, 2014
https://doi.org/10.5194/gmd-7-2683-2014
Geosci. Model Dev., 7, 2683–2692, 2014
https://doi.org/10.5194/gmd-7-2683-2014
Development and technical paper
13 Nov 2014
Development and technical paper | 13 Nov 2014

Response of microbial decomposition to spin-up explains CMIP5 soil carbon range until 2100

J.-F. Exbrayat et al.

Related authors

Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging
S. Multsch, J.-F. Exbrayat, M. Kirby, N. R. Viney, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 8, 1233–1244, https://doi.org/10.5194/gmd-8-1233-2015,https://doi.org/10.5194/gmd-8-1233-2015, 2015
Short summary
Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model
J.-F. Exbrayat, A. J. Pitman, and G. Abramowitz
Biogeosciences, 11, 6999–7008, https://doi.org/10.5194/bg-11-6999-2014,https://doi.org/10.5194/bg-11-6999-2014, 2014
Short summary

Related subject area

Climate and Earth system modeling
Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset
Sébastien Gardoll and Olivier Boucher
Geosci. Model Dev., 15, 7051–7073, https://doi.org/10.5194/gmd-15-7051-2022,https://doi.org/10.5194/gmd-15-7051-2022, 2022
Short summary
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022,https://doi.org/10.5194/gmd-15-6985-2022, 2022
Short summary
Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects
Shixuan Zhang, Kai Zhang, Hui Wan, and Jian Sun
Geosci. Model Dev., 15, 6787–6816, https://doi.org/10.5194/gmd-15-6787-2022,https://doi.org/10.5194/gmd-15-6787-2022, 2022
Short summary
HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor
Christian R. Steger, Benjamin Steger, and Christoph Schär
Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022,https://doi.org/10.5194/gmd-15-6817-2022, 2022
Short summary
LPJ-GUESS/LSMv1.0: a next-generation land surface model with high ecological realism
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022,https://doi.org/10.5194/gmd-15-6709-2022, 2022
Short summary

Cited articles

Ahlström, A., Smith, B., Lindström, J., Rummukainen, M., and Uvo, C. B.: GCM characteristics explain the majority of uncertainty in projected 21st century terrestrial ecosystem carbon balance, Biogeosciences, 10, 1517–1528, https://doi.org/10.5194/bg-10-1517-2013, 2013.
Allison, S. D., Wallenstein, M. D., and Bradford, M. A.: Soil-carbon response to warming dependent on microbial physiology, Nat. Geosci., 3, 336–340, https://doi.org/10.1038/ngeo846, 2010.
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models, J. Clim., 26, 6801–6843, https://doi.org/10.1175/JCLI-D-12-00417.1, 2013.
Arora, V. K. and Boer, G. J.: Uncertainties in the 20th century carbon budget associated with land use change, Glob. Chang. Biol., 16, 3327–3348, https://doi.org/10.1111/j.1365-2486.2010.02202.x, 2010.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Download
Short summary
Pre-industrial soil organic carbon (SOC) stocks vary 6-fold in models used in the 5th IPCC Assessment Report. This paper shows that this range is largely determined by model-specific responses of microbal decomposition during the equilibration procedure. As SOC stocks are maintained through the present and to 2100 almost unchanged, we propose that current SOC observations could be used to constrain this equilibration procedure and thereby reduce the uncertainty in climate change projections.