Abstract. The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice/water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2 and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parametrizations, are realized as classes (i.e. objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g. soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using e.g. different soil freezing characteristics, drainage regimes and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework, but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

Abstract. The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice–water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid  1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parameterizations, are realized as classes (i.e., objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover, which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g., soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using, e.g., different soil freezing characteristics, drainage regimes, and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

Supplement 1: Quick start for CryoGrid community model Software requirements: CryoGrid is written in Matlab, version 2018 or higher is required. For parallel applications, the Matlab parallel toolbox is required. 1.1 Download and set up file structure a) select or create a folder for the model code and results, e.g. "CryoGrid_git" -download zip-file with CryoGrid source code, CryoGridCommunity_source.zip, from https://doi.org/10.5281/zenodo.6522424 and unpack in "CryoGrid_git".b) download the zip-file with run files to be modified by the user, "CryoGridCommunity_run.zip", from https://doi.org/10.5281/zenodo.6522424 and unpack unpack in "CryoGrid_git".c) "CryoGrid_git" should now contain the subfolders "CryoGrid_git/CryoGridCommunity_source" and "CryoGrid_git/CryoGridCommunity_run", and "CryoGrid_git/CryoGridCommunity_source" the subfolders "source" and "UMLs", while "CryoGrid_git/CryoGridCommunity_run" should contain the file "run_CG.m" (in addition to other files and folders).d) Create a folder for parameter files and simulation results. For the default setting, create a folder "CryoGridCommunity_results" in "CryoGrid_git", which should look like this:1.2 Set up parameter files -using existing parameter files from Supplement 4 (recommended as first step) download and unpack the file "CryoGridCommunity_parameter_files.zip" from https://doi.org/10.5281/zenodo.6522424.Copy the herein contained folders (i.e. "forcing", "glacier", etc.) in the folder "CryoGrid_git/CryoGridCommunity_results" (see Suppl. 1.1 above). Each of the folders represents a simulation from Sect. 3.2, with folders named according to the run names (see Suppl. 4). The common model forcing is provided in the folder "forcing".-use automatic parameter file creator (recommended for advanced users) a) edit and run the script "create_parameter_file_EXCEL.m" in "CryoGrid_git/ CryoGridCommunity_run". A list of class names, their index and class options (for some classes) must be provided in the header of the file, as well as the folder in which he parameter files and results are stored (in this case "../CryoGridCommunity_results"). The script generates a parameter file

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