The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere

Abstract

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.

TopoPyScale: A Python Package for Hillslope Climate Downscaling

“…The results can then be exported in a number of formats that can be used as forcing for specialized land surface models for snow, permafrost or hydrology via readily extendable plugins. Currently, this includes the models Cryogrid (Westermann et al, 2023), Crocus (Vionnet et al, 2012), SNOWPACK (Bartelt & Lehning, 2002), Snowmodel (Liston & Elder, 2006), Geotop (Endrizzi et al, 2014), and the data assimilation toolkit MuSA (Alonso-González et al, 2022). Finally, 1D results can be mapped back to the full DEM in order to generate spatially complete results.…”

Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling

“…The simulation of soil freezing and thawing processes is an active research topic for cold climate region due to their important roles in climate change, active layer and permafrost depths, hydrologic regimes, and cold region infrastructure sustainability (Hjort et al, 2022;Matzner & Borken, 2008;Painter et al, 2012Painter et al, , 2016Walvoord & Kurylyk, 2016). Various numerical models were developed to solve the coupled heat and moisture dynamics of frozen soil (Harlan, 1973;Mu & Ladanyi, 1987;Painter & Karra, 2014;Sheshukov & Nieber, 2011;Taylor & Luthin, 1978;Tubini et al, 2021;Westermann et al, 2016Westermann et al, , 2023Zhang et al, 2007). In this study, we adopt the solution for the saturated frozen soil from Sheshukov and Egorov (2002).…”

Simulating the Thermal Regime and Surface Energy Balance of a Permafrost‐Underlain Forest in Mongolia

“…We force our simulations with time series of near-surface atmospheric variables, which are downscaled to account for blocking of solar radiation from surrounding terrain in the mountainous terrain of the study area (see Text S1.1 in Supporting Information S1 for details). For further information on the CryoGrid community model, we refer to the overview paper by Westermann et al (2023).…”

“…The aerodynamic resistances governing the heat and moisture exchange between the atmosphere and the canopy air space (r ah and r aw ) are equal to the resistances between atmosphere and the ground for unvegetated surfaces (described in Westermann et al, 2023), but are expected to be smaller than for unvegetated surfaces due to the higher roughness length of vegetation (described later). Furthermore, the aerodynamic resistance between the surface and canopy air is implemented as described in D. M. Lawrence et al (2018):…”