ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

• Published in: Geoscientific Model Development
• Main Authors: M. Guimberteau, D. Zhu, F. Maignan, Y. Huang, C. Yue, S. Dantec-Nédélec, C. Ottlé, A. Jornet-Puig, A. Bastos, P. Laurent, D. Goll, S. Bowring, J. Chang, B. Guenet, M. Tifafi, S. Peng, G. Krinner, A. Ducharne, F. Wang, T. Wang, X. Wang, Y. Wang, Z. Yin, R. Lauerwald, E. Joetzjer, C. Qiu, H. Kim, P. Ciais
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2018
• Subjects: Geology; QE1-996.5; Arctic; permafrost
• Online Access: https://doi.org/10.5194/gmd-11-121-2018; https://doaj.org/article/42376695a7bc4035acc5ace4e4bcc8a0

The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance – those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest – are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO 2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.