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

Westermann, Sebastian; Ingeman‐Nielsen, Thomas; Scheer, Johanna; Aalstad, Kristoffer; Aga, Juditha; Chaudhary, Nitin; Etzelmüller, Bernd; Filhol, Simon; Kääb, Andreas; Renette, Cas; Schmidt, Louise Steffensen; Schuler, Thomas; Zweigel, Robin Benjamin; Martin, Léo; Morard, Sarah; Ben-Asher, Matan; Angelopoulos, Michael; Boike, Julia; Groenke, Brian; Miesner, Frederieke; Nitzbon, Jan; Overduin, Paul; Stuenzi, Simone Maria; Langer, Moritz

doi:10.5194/gmd-2022-127-supplement

2022

DOI: 10.5194/gmd-2022-127-supplement

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

Sebastian Westermann¹,

Thomas Ingeman‐Nielsen²,

Johanna Scheer³

et al.

Abstract: 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… Show more

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

et al. 2023

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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.

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

et al. 2023

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Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard

Schmidt¹,

Schuler²,

Thomas³

et al. 2023

The Cryosphere

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Abstract. The Arctic is undergoing increased warming compared to the global mean, which has major implications for freshwater runoff into the oceans from seasonal snow and glaciers. Here, we present high-resolution (2.5 km) simulations of glacier mass balance, runoff, and snow conditions on Svalbard from 1991–2022, one of the fastest warming regions in the world. The simulations are created using the CryoGrid community model forced by Copernicus Arctic Regional ReAnalysis (CARRA) (1991–2021) and AROME-ARCTIC forecasts (2016–2022). Updates to the water percolation and runoff schemes are implemented in the CryoGrid model for the simulations. In situ observations available for Svalbard, including automatic weather station data, stake measurements, and discharge observations, are used to carefully evaluate the quality of the simulations and model forcing. We find a slightly negative climatic mass balance (CMB) over the simulation period of −0.08 mw.e.yr-1 but with no statistically significant trend. The most negative annual CMB is found for Nordenskiöldland (−0.73 mw.e.yr-1), with a significant negative trend of −0.27 mw.e. per decade for the region. Although there is no trend in the annual CMB, we do find a significant increasing trend in the runoff from glaciers of 0.14 mw.e. per decade. The average runoff was found to be 0.8 mw.e.yr-1. We also find a significant negative trend in the refreezing of −0.13 mw.e. per decade. Using AROME-ARCTIC forcing, we find that 2021/22 has the most negative CMB and highest runoff over the 1991–2022 simulation period investigated in this study. We find the simulated climatic mass balance and runoff using CARRA and AROME-ARCTIC forcing are similar and differ by only 0.1 mw.e.yr-1 in climatic mass balance and by 0.2 mw.e.yr-1 in glacier runoff when averaged over all of Svalbard. There is, however, a clear difference over Nordenskiöldland, where AROME-ARCTIC simulates significantly higher mass balance and significantly lower runoff. This indicates that AROME-ARCTIC may provide similar high-quality predictions of the total mass balance of Svalbard as CARRA, but regional uncertainties should be taken into consideration. The simulations produced for this study are made publicly available at a daily and monthly resolution, and these high-resolution simulations may be re-used in a wide range of applications including studies on glacial runoff, ocean currents, and ecosystems.

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

Cited by 2 publications

References 1 publication

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

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

Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard

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