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

Author:

Westermann Sebastian,Ingeman-Nielsen ThomasORCID,Scheer Johanna,Aalstad KristofferORCID,Aga JudithaORCID,Chaudhary NitinORCID,Etzelmüller BerndORCID,Filhol Simon,Kääb AndreasORCID,Renette CasORCID,Schmidt Louise SteffensenORCID,Schuler Thomas VikhamarORCID,Zweigel Robin B.ORCID,Martin Léo,Morard SarahORCID,Ben-Asher MatanORCID,Angelopoulos MichaelORCID,Boike JuliaORCID,Groenke BrianORCID,Miesner FrederiekeORCID,Nitzbon JanORCID,Overduin PaulORCID,Stuenzi Simone M.ORCID,Langer Moritz

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.

Funder

Horizon 2020 Framework Programme

Norges Forskningsråd

European Space Agency

Bundesministerium für Bildung und Forschung

Publisher

Copernicus GmbH

Subject

General Medicine

Reference142 articles.

1. Aalstad, K., Westermann, S., Schuler, T. V., Boike, J., and Bertino, L.: Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites, The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, 2018. a, b, c

2. Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H., van den Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and Fettweis, X.: Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes, The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, 2019. a

3. Alonso-González, E., Gutmann, E., Aalstad, K., Fayad, A., Bouchet, M., and Gascoin, S.: Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area, Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, 2021. a, b, c

4. Angelopoulos, M., Westermann, S., Overduin, P., Faguet, A., Olenchenko, V., Grosse, G., and Grigoriev, M. N.: Heat and salt flow in subsea permafrost modeled with CryoGRID2, J. Geophys. Res.-Earth Surf., 124, 920–937, https://doi.org/10.1029/2018JF004823, 2019. a, b

5. Angelopoulos, M., Overduin, P. P., Westermann, S., Tronicke, J., Strauss, J., Schirrmeister, L., Biskaborn, B. K., Liebner, S., Maksimov, G., Grigoriev, M. N., and Grosse, G.: Thermokarst lake to lagoon transitions in eastern Siberia: Do submerged taliks refreeze?, J. Geophys. Res.-Earth Surf., 125, e2019JF005424, https://doi.org/10.1029/2019JF005424, 2020. a, b

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3