Coupled multilayer canopy-permafrost model (CryoGrid) for the simulation of forest trajectories in permafrost underlain boreal forests.

• Main Authors: Stuenzi, Simone Maria (10519946), Boike, Julia (10350427), Gädeke, Anne (10519949), Herzschuh, Ulrike (10350433), Kruse, Stefan (7045733), Pestryakova, Luidmila A. (10350436), Westermann, Sebastian (10350442), Langer, Moritz (10350448)
• Format: Software
• Language: unknown
• Published: 2021
• Subjects: Ecology; Plant Biology; Biological Sciences not elsewhere classified; Chemical Sciences not elsewhere classified; Information Systems not elsewhere classified; Permafrost; Land surface model; CryoGrid; Boreal forest; Zakharov; Spasskaya; Ice; permafrost; Siberia
• Online Access: https://doi.org/10.5281/zenodo.4603668

CryoGrid is a land-surface scheme dedicated to modeling of ground temperatures in permafrost environments. Here, the one-dimensional land surface model (CryoGrid) is adapted for application in vegetated areas by coupling a multilayer canopy model (CLM-ml v0). This model setup is used to reproduce the energy transfer and thermal regime at a study site in mixed boreal forest in Eastern Siberia. The vegetation module forms the upper boundary layer of the coupled vegetation-permafrost model and replaces the surface energy balance equation used for common CryoGrid representations. The coupled model was first described in the following article which has been published in Biogeosciences: Stuenzi, S. M., Boike, J., Cable, W., Herzschuh, U., Kruse, S., Pestryakova, L. A., Schneider von Deimling, T., Westermann, S., Zakharov, E. S., and Langer, M.: Variability of the surface energy balance in permafrost-underlain boreal forest, Biogeosciences , 18, 343–365, https://doi.org/10.5194/bg-18-343-2021 , 2021. The model code for this publication can be found here: https://doi.org/10.5281/zenodo.4317106 In this version we have implemented changes to the Here, we add a paramterization for deciduous forest to simulate the leafless state of deciduous-dominated regions outside of the short vegetative period in summer. This is achieved by allowing for a separate leaf area index defined by a rough parameterization of a leaf-on and a leaf-off season (10. October - 10. April) based on literature values from Spasskaya Pad \cite{Ohta2001a}. Further, more realistic mixed canopy compositions can now be simulated by allowing for a certain percentage of deciduous taxa within the simulated forest stand. In addition, we add a parameterization for coupling forest density (LAI) to fine root biomass. Further, we have implemented a new relationship for phase partitioning of water in frozen soil (freeze curve). The parameters are set to the default values that were used for the simulations in the article. Parameters different from the default values can be specified in the main script <code>run_CG_RUN_1D_STANDARD.m</code> (general parameters, run number, etc.) and in the excel table \results\test_vegetation_snow_1\ test_vegetation_snow_1.xlsx (run-specific parameters). To start the program, run the script <code>run_CG_RUN_1D_STANDARD.m</code>. The default output directory is .\results\. Further updates to the model code can be found here: https://github.com/CryoGrid/CryoGrid/tree/vegetation Updates and documentation of the Permafrost model CryoGrid can be found here: https://github.com/CryoGrid. The model is further described in this publication: Westermann, S., Langer, M., Boike, J., Heikenfeld, M., Peter, M., Etzelmüller, B., & Krinner, G. (2016). Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3. Geosci. Model Dev. , 9(2), 523–546. https://doi.org/10.5194/gmd-9-523-2016 . The multilayer canopy model was first published by Bonan et al. (2018) : Bonan, G. B., Patton, E. G., Harman, I. N., Oleson, K. W., Finnigan, J. J., Lu, Y., and Burakowski, E. A.: Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0), Geosci. Model Dev. , 11, 1467–1496, https://doi.org/10.5194/gmd-11-1467-2018, 2018.