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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 LU orcid ; Etzelmüller, Bernd ; Filhol, Simon ; Kääb, Andreas and Renette, Cas , et al. (2023) In Geoscientific Model Development 16(9). p.2607-2647
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... (More)

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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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Geoscientific Model Development
volume
16
issue
9
pages
41 pages
publisher
Copernicus GmbH
external identifiers
  • scopus:85160940672
ISSN
1991-959X
DOI
10.5194/gmd-16-2607-2023
language
English
LU publication?
yes
id
85bf5e88-b37f-4168-95aa-9bbf3c44ea13
date added to LUP
2023-08-21 11:14:13
date last changed
2023-08-21 11:14:13
@article{85bf5e88-b37f-4168-95aa-9bbf3c44ea13,
  abstract     = {{<p>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.</p>}},
  author       = {{Westermann, Sebastian and Ingeman-Nielsen, Thomas and Scheer, Johanna and Aalstad, Kristoffer and Aga, Juditha and Chaudhary, Nitin and Etzelmüller, Bernd and Filhol, Simon and Kääb, Andreas and Renette, Cas and Schmidt, Louise Steffensen and Schuler, Thomas Vikhamar and Zweigel, Robin B. and Martin, Léo and Morard, Sarah and Ben-Asher, Matan and Angelopoulos, Michael and Boike, Julia and Groenke, Brian and Miesner, Frederieke and Nitzbon, Jan and Overduin, Paul and Stuenzi, Simone M. and Langer, Moritz}},
  issn         = {{1991-959X}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{2607--2647}},
  publisher    = {{Copernicus GmbH}},
  series       = {{Geoscientific Model Development}},
  title        = {{The CryoGrid community model (version 1.0) - a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere}},
  url          = {{http://dx.doi.org/10.5194/gmd-16-2607-2023}},
  doi          = {{10.5194/gmd-16-2607-2023}},
  volume       = {{16}},
  year         = {{2023}},
}