Lateral thermokarst patterns in permafrost peat plateaus in northern Norway

Abstract

Abstract. Subarctic peatlands underlain by permafrost contain significant amounts of organic carbon. Our ability to quantify the evolution of such permafrost landscapes in numerical models is critical for providing robust predictions of the environmental and climatic changes to come. Yet, the accuracy of large-scale predictions has so far been hampered by small-scale physical processes that create a high spatial variability of thermal surface conditions, affecting the ground thermal regime and thus permafrost degradation patterns. In this regard, a better understanding of the small-scale interplay between microtopography and lateral fluxes of heat, water and snow can be achieved by field monitoring and process-based numerical modeling. Here, we quantify the topographic changes of the Šuoššjávri peat plateau (northern Norway) over a three-year period using drone-based repeat high-resolution photogrammetry. Our results show thermokarst degradation is concentrated on the edges of the plateau, representing 77 % of observed subsidence, while most of the inner plateau surface exhibits no detectable subsidence. Based on detailed investigation of eight zones of the plateau edge, we show that this edge degradation corresponds to an annual volume change of 0.13±0.07 m3 yr−1 per meter of retreating edge (orthogonal to the retreat direction). Using the CryoGrid3 land surface model, we show that these degradation patterns can be reproduced in a modeling framework that implements lateral redistribution of snow, subsurface water and heat, as well as ground subsidence due to melting of excess ice. By performing a sensitivity test for snow depths on the plateau under steady-state climate forcing, we obtain a threshold behavior for the start of edge degradation. Small snow depth variations (from 0 to 30 cm) result in highly different degradation behavior, from stability to fast degradation. For plateau snow depths in the range of field measurements, the simulated annual volume changes are broadly in agreement with the results of the drone survey. As snow depths are clearly correlated with ground surface temperatures, our results indicate that the approach can potentially be used to simulate climate-driven dynamics of edge degradation observed at our study site and other peat plateaus worldwide. Thus, the model approach represents a first step towards simulating climate-driven landscape development through thermokarst in permafrost peatlands.

Explicitly modelling microtopography in permafrost landscapes in a land-surface model (JULES vn5.4_microtopography)

“…Interestingly, this is of the same order of magnitude as the 0.13 m 3 yr -1 m -1 of volumetric loss of permafrost peat plateau edge found by Martin et al, (2021). Of course, not all the lateral heat flux would go into melting ice, so this rate of thaw would be smaller.…”

“…However, for areas of peat plateau, and 935 for the expansion of thermokarst lakes, it may be more suitable to consider an area-based lateral thaw approach as this may require fewer tiles. We note that the modelled lateral heat conduction between tiles for Iškoras corresponds to melting 0.28 m 3 of ice per year per metre of palsa-mire border, which is of the same order of magnitude as the 0.13 m 3 yr -1 m -1 of volumetric loss of permafrost peat plateau edge found by Martin et al, (2021), indicating that such an approach may work. Recently, remote sensing and machine learning tools have enabled the mapping of the location and areas of different permafrost 940 landforms for large regions, and the mapping of how these are changing (Nitze et al, 2018).…”

“…Modelling efforts have been hampered by a lack of long-term high-resolution observations. Nevertheless, at a handful of field sites the local variability has been well quantified and at these sites 'tiling' approaches to modelling micro-and mesotopography have been tested as a route to representing sub-grid processes in ESMs (Langer et al, 2016;Aas et al, 2016Aas et al, , 2019Nitzbon et al, 2019Nitzbon et al, , 2020aCai et al, 2020;Martin et al, 2021). These authors have primarily focused on the future evolution https://doi.org/10.5194/gmd-2021-285 Preprint.…”

“…It would therefore be reasonable to associate a given elevation difference with 930 a particular landform. Previously, thaw models based on the thawing of excess ice and subsequent vertical elevation change have been used to simulate the future evolution of polygonal landscapes and palsas / peat plateaus (Langer et al, 2016;Aas et al, 2016Nitzbon et al, 2019Nitzbon et al, , 2020aCai et al, 2020;Martin et al, 2021). These approaches are particularly suited to polygonal landforms where the relative elevations of tiles determine the transformation between low centred and high centred polygons, affecting the hydrology of these landscapes (Nitzbon et al, 2019(Nitzbon et al, , 2020a.…”

Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)

“…The observed palsa at Iškoras was 0.68 m above the mire. Some polygon rims can reach 1 m in height, while Palsas can reach larger elevations of around to 3 m. 2020; Martin et al, 2021). The reduced computational burden of the latter approach has been pursued as a possible route to representing sub-grid processes in ESMs.…”