Effects of multi-scale heterogeneity on the simulated evolution of ice-rich permafrost lowlands under a warming climate

Abstract

Abstract. In continuous permafrost lowlands, thawing of ice-rich deposits and melting of massive ground ice lead to abrupt landscape changes called thermokarst, which have widespread consequences on the thermal, hydrological, and biogeochemical state of the subsurface. However, macro-scale land surface models (LSMs) do not resolve such localized subgrid-scale processes and could hence miss key feedback mechanisms and complexities which affect permafrost degradation and the potential liberation of soil organic carbon in high latitudes. Here, we extend the CryoGrid 3 permafrost model with a multi-scale tiling scheme which represents the spatial heterogeneities of surface and subsurface conditions in ice-rich permafrost lowlands. We conducted numerical simulations using stylized model setups to assess how different representations of micro- and meso-scale heterogeneities affect landscape evolution pathways and the amount of permafrost degradation in response to climate warming. At the micro-scale, the terrain was assumed to be either homogeneous or composed of ice-wedge polygons, and at the meso-scale it was assumed to be either homogeneous or resembling a low-gradient slope. We found that by using different model setups and parameter sets, a multitude of landscape evolution pathways could be simulated which correspond well to observed thermokarst landscape dynamics across the Arctic. These pathways include the formation, growth, and gradual drainage of thaw lakes; the transition from low-centred to high-centred ice-wedge polygons; and the formation of landscape-wide drainage systems due to melting of ice wedges. Moreover, we identified several feedback mechanisms due to lateral transport processes which either stabilize or destabilize the thermokarst terrain. The amount of permafrost degradation in response to climate warming was found to depend primarily on the prevailing hydrological conditions, which in turn are crucially affected by whether or not micro- and/or meso-scale heterogeneities were considered in the model setup. Our results suggest that the multi-scale tiling scheme allows for simulating ice-rich permafrost landscape dynamics in a more realistic way than simplistic one-dimensional models and thus facilitates more robust assessments of permafrost degradation pathways in response to climate warming. Our modelling work improves the understanding of how micro- and meso-scale processes affect the evolution of ice-rich permafrost landscapes, and it informs macro-scale modellers focusing on high-latitude land surface processes about the necessities and possibilities for the inclusion of subgrid-scale processes such as thermokarst within their models.

Lateral thermokarst patterns in permafrost peat plateaus in northern Norway

“…When excess ice melts in a grid cell, the grid cell size shrinks accordingly. This excess ice scheme was first implemented by Westermann et al (2016) and later used in Nitzbon et al (2019Nitzbon et al ( , 2020Nitzbon et al ( , 2021 to represent the transient evolution of polygonal tundra landscapes for different future climate scenarios. In the present study, this scheme is adapted to simulate microtopography changes and thermokarst patterns of the Šuoššjávri peat plateau.…”

“…Its thawing has major consequences on arctic and boreal ecosystems and landscapes (Beck et al, 2015;Farquharson et al, 2019;Liljedahl et al, 2016) and potentially represents an important climate feedback through the decomposition of thawed organic matter (Koven et al, 2015;Schuur et al, 2009Schuur et al, , 2015. Carbon emis-3424 L. C. P. Martin et al: Lateral thermokarst patterns in permafrost peat plateaus in northern Norway sions from permafrost regions towards the atmosphere are already observed (Natali et al, 2019); field measurements show that these emissions are influenced by the timing of the active layer deepening (Morgalev et al, 2017) and by the state of degradation of the permafrost terrains (Langer et al, 2015;Nwaishi et al, 2020;Serikova et al, 2018). In particular, abrupt thawing of ice-rich permafrost is expected to become a significant factor for carbon emissions, potentially offsetting the negative feedback by increased ecosystem productivity that is expected for gradual thaw (McGuire et al, 2018;Turetsky et al, 2020).…”

“…Subsequently, we adapt the laterally coupled, tiled version of the CryoGrid3 model (Langer et al, 2016;Nitzbon et al, 2019;Westermann et al, 2016) to reproduce observed patterns of microtopography change, including an analysis of model sensitivity towards snow depth. The work presented here builds on field observations and simulations for peat plateaus in northern Norway (Martin et al, 2019) and other arctic landscapes (Aas et al, 2019;Nitzbon et al, 2019Nitzbon et al, , 2020Nitzbon et al, , 2021.…”

Standardized monitoring of permafrost thaw: a user-friendly, multiparameter protocol

“…Shrub growth can in turn reduce (Blok et al, 2010) or promote (Wilcox et al, 2019) permafrost thaw, depending on how shrub height affects snow accumulation and snow melt. The hydrological conditions in ice-rich permafrost lowlands determine the thawing of permafrost; inundated and wetter areas favour degradation, while drainage and drier soil conditions favour stabilization (Nitzbon et al 2020).…”

“…Collocated and consistent measurements of multiple variables are needed to explain changes in permafrost conditions, and therefore to upscale or to make future projections of future permafrost thaw. In addition, particular parameters are required as inputs for numerical and conceptual models (including Earth system models and specialized permafrost models, such as CryoGrid; Nitzbon et al 2020). The focus of our study was to design such a multi-parameter protocol.…”