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

Cited by 11 publications

(46 citation statements)

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“…In order to simulate the diffusion of heat in permafrost soils, we use a transient heat conduction model based on the same numerical procedures and parameterizations of CryoGrid (Westermann et al, 2016(Westermann et al, , 2022 which solves the 1-dimensional non-linear heat equation with phase change:…”

Section: Transient Heat Conduction Modelmentioning

confidence: 99%

“…These limitations provide a wide range of directions for future work; e.g. (1-3) could be addressed simply by incorporating additional physical processes into the model, such as those described in Westermann et al (2022). However, this typically comes at a heavy computational cost, limiting the feasibility of running large ensembles over longer time periods spanning decades, centuries, or millenia.…”

Section: Limitationsmentioning

confidence: 99%

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Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer

Groenke

Langer

Nitzbon

et al. 2022

Preprint

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Abstract. Long-term measurements of permafrost temperatures do not provide a complete picture of the Arctic subsurface thermal regime. Regions with warmer permafrost often show little to no long-term change in ground temperature due to the uptake and release of latent heat during freezing and thawing. Thus, regions where the least warming is observed may also be the most vulnerable to permafrost degradation. Since direct measurements of ice and liquid water contents in the permafrost layer are not widely available, thermal modeling of the subsurface plays a crucial role in understanding how permafrost responds to changes in the local energy balance. In this work, we first analyze trends in observed air and permafrost temperatures at four sites within the continuous permafrost zone, where we find substantial variation in the apparent relationship between long-term changes in permafrost temperatures (0.02 K yr−1 to 0.16 K yr−1) and air temperature (0.09 K yr−1 to 0.11 K yr−1). We then apply recently developed Bayesian inversion methods to link observed changes in borehole temperatures to unobserved changes in latent heat and thaw depth using a transient model of heat conduction with phase change. Our results suggest that the degree to which recent warming trends correlate with permafrost thaw and variations in latent heat is heavily dependent on both local soil properties as well as historical climatology. At the warmest site, a nine meter borehole near Ny-Ålesund, Svalbard, modeled annual maximum thaw depth increases by an average of (12 ± 1) cm K−1 rise in mean annual ground temperature. In stark contrast, modeled thaw rates for a borehole on Samoylov Island in the Lena River Delta (northeastern Siberia) appear far less sensitive to temperature change, with an almost negligible increase of (1 ± 1) cm K−1. Although our study is limited to just four sites, the results urge caution in the interpretation and comparison of warming trends in Arctic boreholes, indicating substantial uncertainty in their implications for the current and future thermal state of permafrost.

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Section: Transient Heat Conduction Modelmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer

Groenke

Langer

Nitzbon

et al. 2022

Preprint

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“…3.2.2. The land hydrology processes are quantified using the CryoGrid community model (version 1.0) (Westermann et al, 2022) as described in section 3.2.3. Distributed 1D simulations are used to quantify land evaporation and runoff.…”

Section: Conceptual Hydrological Model For the Catchmentmentioning

confidence: 99%

“…To simulate the ground thermo-hydrological regime, we use the CryoGrid community model (Westermann et al, 2022). The CryoGrid community model (CG) is a land surface model designed for applications in cold regions where seasonal frozen ground or permafrost may occur.…”

Section: The Cryogrid Community Model (Version 10)mentioning

confidence: 99%

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Recent ground thermo-hydrological changes in a Tibetan endorheic catchment and implications for lake level changes

Martin

Westermann

Magni

et al. 2022

Preprint

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Abstract. Climate change modifies the water and energy fluxes between the atmosphere and the surface in mountainous regions. This is particularly true over the Qinghai-Tibet Plateau (QTP), a major headwater region of the world, which has shown substantial hydrological changes over the last decades. Among them, the rapid lake level variations observed throughout the plateau remain puzzling and much is still to be understood regarding the spatial distribution of lake level trends (increase/decrease) and paces. The ground across the QTP hosts either permafrost or seasonally frozen ground and both are affected by climate change. In this environment, the ground thermal regime influences liquid water availability, evaporation and runoff. Therefore, climate-driven modifications of the ground thermal regime may contribute to lake level variations. For now, this hypothesis has been overlooked by modelers because of the scarcity of field data and the difficulty to account for the spatial variability of the climate and its influence on the ground thermo-hydrological regime in a numerical framework. This study focuses on the cryo-hydrology of the catchment of Lake Paiku (Southern Tibet) for the 1980–2019 period. We use TopoSCALE and TopoSUB to downscale ERA5 data and capture the spatial variability of the climate in our forcing data. We use a distributed setup of the CryoGrid community model (version 1.0) to quantify thermo-hydrological changes in the ground during the period. Forcing data and simulation outputs are validated with weather station data, surface temperature logger data and the lake level variations. We show that both seasonal frozen ground and permafrost have warmed (1.7 °C per century 2 m deep), increasing the availability of liquid water in the ground and the duration of seasonal thaw. Both phenomena promote evaporation and runoff but ground warming drives a strong increase in subsurface runoff, so that the runoff/(evaporation + runoff) ratio increases over time. Summer evaporation is an important energy sink and we find active layer deepening only where evaporation is limited. The presence of permafrost is found to promote evaporation at the expense of runoff, consistent with recent studies. Yet, this relationship seems to be climate dependent and we show that a colder and wetter climate produces the opposite effect. This ambivalent influence of permafrost may help to understand the contrasting lake level variations observed between the south and north of the QTP, opening new perspectives for future investigations.

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

Zhou,

Zhang,

Sheshukov

et al. 2024

Earth and Space Science

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Ground heat flux (G0) is a key component of the land‐surface energy balance of high‐latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G0 data (measured or modeled) for snow‐free period as a reference. When observed G0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state‐of‐the‐art uncertainty quantification methods, the developed G0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

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

Cited by 11 publications

References 0 publications

Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer

Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer

Recent ground thermo-hydrological changes in a Tibetan endorheic catchment and implications for lake level changes

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

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