Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada

Roads constructed on permafrost can have a significant impact on the surrounding environment, potentially inducing permafrost degradation. These impacts arise from factors such as snow accumulation near the road, which affects the soil's thermal and hydrological regime, and road dust that decreases the snow's albedo, altering the timing of snowmelt. However, our current understanding of the magnitude and the spatial extent of these effects is limited. In this study we addressed this gap by using remote sensing techniques to assess the spatial effect of the Inuvik to Tuktoyaktuk Highway (ITH) in Northwest Territories, Canada, on snow accumulation, snow albedo and snowmelt patterns. With a new, high resolution snow depth raster from airborne laser scanning, we quantified the snow accumulation at road segments in the Trail Valley Creek area using digital elevation model differencing. We found increased snow accumulation up to 36 m from the road center. The magnitude of this snow accumulation was influenced by the prevailing wind direction and the embankment height. Furthermore, by analyzing 43 Sentinel-2 satellite images between February and May 2020, we observed reduced snow albedo values within 500 m of the road, resulting in a 12-days-earlier onset of snowmelt within 100 m from the road. We examined snowmelt patterns before, during and after the road construction using the normalized difference snow index from Landsat-7 and Landsat-8 imagery. Our analysis revealed that the road affected the snowmelt pattern up to 600 m from the road, even in areas which appeared undisturbed. In summary, our study improves our understanding of the spatial impact of gravel roads on permafrost due to enhanced snow accumulation, reduced snow albedo and earlier snowmelt. Our study underscores the important contribution that remote sensing can provide to improve our understanding of the effects of infrastructure development on permafrost environments.</p

Linking tundra vegetation, snow, soil temperature, and permafrost

Connections between vegetation and soil thermal dynamics are critical for estimating the vulnerability of permafrost to thaw with continued climate warming and vegetation changes. The interplay of complex biophysical processes results in a highly heterogeneous soil temperature distribution on small spatial scales. Moreover, the link between topsoil temperature and active layer thickness remains poorly constrained. Sixty-eight temperature loggers were installed at 1-3 cm depth to record the distribution of topsoil temperatures at the Trail Valley Creek study site in the northwestern Canadian Arctic. The measurements were distributed across six different vegetation types characteristic for this landscape. Two years of topsoil temperature data were analysed statistically to identify temporal and spatial characteristics and their relationship to vegetation, snow cover, and active layer thickness. The mean annual topsoil temperature varied between -3.7 and 0.1°C within 0.5 km2. The observed variation can, to a large degree, be explained by variation in snow cover. Differences in snow depth are strongly related with vegetation type and show complex associations with late-summer thaw depth. While cold winter soil temperature is associated with deep active layers in the following summer for lichen and dwarf shrub tundra, we observed the opposite beneath tall shrubs and tussocks. In contrast to winter observations, summer topsoil temperature is similar below all vegetation types with an average summer topsoil temperature difference of less than 1°C. Moreover, there is no significant relationship between summer soil temperature or cumulative positive degree days and active layer thickness. Altogether, our results demonstrate the high spatial variability of topsoil temperature and active layer thickness even within specific vegetation types. Given that vegetation type defines the direction of the relationship between topsoil temperature and active layer thickness in winter and summer, estimates of permafrost vulnerability based on remote sensing or model results will need to incorporate complex local feedback mechanisms of vegetation change and permafrost thaw

Simulating ice segregation and thaw consolidation in permafrost environments with the CryoGrid community model

The ground ice content in cold environments influences the permafrost thermal regime and the thaw trajectories in a warming climate, especially for soils containing excess ice. Despite their importance, the amount and distribution of ground ice are often unknown due to lacking field observations. Hence, modeling the thawing of ice-rich permafrost soils and associated thermokarst is challenging as ground ice content has to be prescribed in the model setup. In this study, we present a model scheme, capable of simulating segregated ice formation during a model spinup together with associated ground heave. It provides the option to add a constant sedimentation rate throughout the simulation. Besides ice segregation, it can represent thaw consolidation processes and ground subsidence under a warming climate. The computation is based on soil mechanical processes, soil hydrology by the Richards equation and soil freezing characteristics. The code is implemented in the CryoGrid community model (version 1.0), a modular land surface model for simulations of the ground thermal regime. The simulation of ice segregation and thaw consolidation with the new model scheme allows us to analyze the evolution of ground ice content in both space and time. To do so, we use climate data from two contrasting permafrost sites to run the simulations. Several influencing factors are identified, which control the formation and thaw of segregated ice. (i) Model results show that high temperature gradients in the soil as well as moist conditions support the formation of segregated ice. (ii) We find that ice segregation increases in fine-grained soils and that especially organic-rich sediments enhance the process. (iii) Applying external loads suppresses ice segregation and speeds up thaw consolidation. (iv) Sedimentation leads to a rise of the ground surface and the formation of an ice-enriched layer whose thickness increases with sedimentation time. We conclude that the new model scheme is a step forward to improve the description of ground ice distributions in permafrost models and can contribute towards the understanding of ice segregation and thaw consolidation in permafrost environments under changing climatic conditions.</p

Pathways of ice-wedge degradation in polygonal tundra under different hydrological conditions

Ice-wedge polygons are common features of lowland tundra in the continuous permafrost zone and prone to rapid degradation through melting of ground ice. There are many interrelated processes involved in ice-wedge thermokarst and it is a major challenge to quantify their influence on the stability of the permafrost underlying the landscape. In this study we used a numerical modelling approach to investigate the degradation of ice wedges with a focus on the influence of hydrological conditions. Our study area was Samoylov Island in the Lena River delta of northern Siberia, for which we had in situ measurements to evaluate the model. The tailored version of the CryoGrid 3 land surface model was capable of simulating the changing microtopography of polygonal tundra and also regarded lateral fluxes of heat, water, and snow. We demonstrated that the approach is capable of simulating ice-wedge degradation and the associated transition from a low-centred to a high-centred polygonal microtopography. The model simulations showed ice-wedge degradation under recent climatic conditions of the study area, irrespective of hydrological conditions. However, we found that wetter conditions lead to an earlier onset of degradation and cause more rapid ground subsidence. We set our findings in correspondence to observed types of ice-wedge polygons in the study area and hypothesized on remaining discrepancies between modelled and observed ice-wedge thermokarst activity. Our quantitative approach provides a valuable complement to previous, more qualitative and conceptual, descriptions of the possible pathways of ice-wedge polygon evolution. We concluded that our study is a blueprint for investigating thermokarst landforms and marks a step forward in understanding the complex interrelationships between various processes shaping ice-rich permafrost landscapes.</p

Observation and modelling of snow at a polygonal tundra permafrost site: spatial variability and thermal implications

The shortage of information on snow properties in high latitudes places a major limitation on permafrost and more generally climate modelling. A dedicated field program was therefore carried out to investigate snow properties and their spatial variability at a polygonal tundra permafrost site. Notably, snow samples were analysed for surface-normal thermal conductivity (Keff − z) based on X-ray microtomography. Also, the detailed snow model SNOWPACK was adapted to these Arctic conditions to enable relevant simulations of the ground thermal regime. Finally, the sensitivity of soil temperatures to snow spatial variability was analysed.Within a typical tundra snowpack composed of depth hoar overlain by wind slabs, depth hoar samples were found more conductive (Keff − z = 0.22±0.05&thinsp;W&thinsp;m−1&thinsp;K−1) than in most previously published studies, which could be explained by their high density and microstructural anisotropy. Spatial variations in the thermal properties of the snowpack were well explained by the microtopography and ground surface conditions of the polygonal tundra, which control depth hoar growth and snow accumulation. Our adaptations to SNOWPACK, phenomenologically taking into account the effects of wind compaction, basal vegetation, and water vapour flux, yielded realistic density and Keff − z profiles that greatly improved simulations of the ground thermal regime. Also, a density- and anisotropy-based parameterization for Keff − z lead to further slight improvements. Soil temperatures were found to be particularly sensitive to snow conditions during the early winter and polar night, highlighting the need for improved snow characterization and modelling over this period.</p

Thaw processes in ice-rich permafrost landscapes represented with laterally coupled tiles in a land surface model

Earth system models (ESMs) are our primary tool for projecting future climate change, but their ability to represent small-scale land surface processes is currently limited. This is especially true for permafrost landscapes in which melting of excess ground ice and subsequent subsidence affect lateral processes which can substantially alter soil conditions and fluxes of heat, water, and carbon to the atmosphere. Here we demonstrate that dynamically changing microtopography and related lateral fluxes of snow, water, and heat can be represented through a tiling approach suitable for implementation in large-scale models, and we investigate which of these lateral processes are important to reproduce observed landscape evolution. Combining existing methods for representing excess ground ice, snow redistribution, and lateral water and energy fluxes in two coupled tiles, we show that the model approach can simulate observed degradation processes in two very different permafrost landscapes. We are able to simulate the transition from low-centered to high-centered polygons, when applied to polygonal tundra in the cold, continuous permafrost zone, which results in (i) a more realistic representation of soil conditions through drying of elevated features and wetting of lowered features with related changes in energy fluxes, (ii) up to 2&thinsp;∘C reduced average permafrost temperatures in the current (2000–2009) climate, (iii) delayed permafrost degradation in the future RCP4.5 scenario by several decades, and (iv) more rapid degradation through snow and soil water feedback mechanisms once subsidence starts. Applied to peat plateaus in the sporadic permafrost zone, the same two-tile system can represent an elevated peat plateau underlain by permafrost in a surrounding permafrost-free fen and its degradation in the future following a moderate warming scenario. These results demonstrate the importance of representing lateral fluxes to realistically simulate both the current permafrost state and its degradation trajectories as the climate continues to warm. Implementing laterally coupled tiles in ESMs could improve the representation of a range of permafrost processes, which is likely to impact the simulated magnitude and timing of the permafrost–carbon feedback.</p

Langzeit-Datenreihe (2007 - 2017) von Eddy-Kovarianz CO2- und Energieflüssen der arktischen Bayelva-Station, Spitzbergen

Die Messung von ganzjährigen CO2-, Wasser- und Energieflüssen zwischen Erdoberfläche und Atmosphäre in arktischen Regionen wird bisher nur an wenigen Standorten durchgeführt. Derartige Messungen sind aber insbesondere insofern relevant, als dass arktische Tundren bedeutende CO2-Senken darstellen, unter einem sich erwärmenden Klima möglicherweise aber zukünftig im Permafrost gespeicherten Kohlenstoff freisetzen. Durch den Einsatz bodengebundener in situ Messungen können Kohlenstoff- und Energiedynamik bilanziert werden. Des Weiteren sind die gemessenen Gas- und Energieflüsse wertvoll für die Kalibration und Validierung globaler Klimamodelle. Eine Messstation in der europäischen Arktis ist die Bayelva-Messstation (78� 55‘ N, 11� 50‘ O) nahe Ny Ålesund auf Spitzbergen. Der starke Einfluss des Nordatlantikstroms führt dort zu einem maritimen Klima mit kühlen Sommertemperaturen von durchschnittlich 5 °C im Juli und relativ milden Wintertemperaturen von -13 °C im Januar. Es handelt sich somit um eine vergleichsweise warme Permafrostregion mit Jahresmitteltemperaturen von etwa -2.5 °C. Der Jahresniederschlag liegt bei etwa 400 mm und die schneefreie Zeit beträgt typischerweise drei Monate. An der Bayelva-Station fanden von 2007 bis 2017 Messungen von Wasserdampf- und CO2-Konzentrationen (mittels open-path LiCor LI-7500 CO2 und H2O Gasanalysierer) sowie dreidimensionale Messungen der Windgeschwindigkeit (mittels Campbell CSAT 3D sonic anemometer) mit einer Messfrequenz von 20 Hz statt. Mithilfe der Eddy-Kovarianz-Software TK3 ermitteln wir hieraus halbstündliche Gas- und Energieflüsse und führen Qualitätsprüfungen durch. Erste Ergebnisse für das Jahr 2008/2009 zeigen, dass die jährliche CO2-Bilanz des Standortes nahezu bei null liegt, was durch die lange, winterliche Freisetzung von CO2 in die Atmosphäre zu erklären ist. Allerdings sind die Prozesse, welche diese winterliche CO2-Emission bedingen bisher nicht untersucht. Unser Ziel besteht daher nun darin, die Analyse der Gas- und Energieflüsse auf den gesamten Messzeitraum von 2007 bis 2017 auszuweiten. Insbesondere für die Zeiträume Oktober 2012 bis August 2014 sowie Januar 2015 bis September 2016 sind die Messreihen nahezu komplett mit Datenlücken von nur wenigen Tagen pro Zeitraum. Auf der Grundlage der entstehenden Langzeit-Datenreihe können wir durch den Klimawandel bedingte Änderungen der CO2-Flüsse von zwischenjährlicher Variabilität unterscheiden sowie saisonale und jahreszeitliche Schwankungen bilanzieren. Außerdem ermöglicht es uns der mehrjährige Datensatz die Umstände der ablaufenden Prozesse genauer zu beschreiben und dadurch möglicherweise Rückschlüsse auf deren Auslöser zu ziehen. Im weiteren Verlauf ist es zudem vorstellbar Wechselwirkungen zwischen den beobachteten Gas- und Energieflüssen und weiteren Eigenschaften verschiedener Komponenten des Klimasystems wie zum Beispiel Wolkeneigenschaften zu untersuchen

Subpixel heterogeneity of ice-wedge polygonal tundra: a multi-scale analysis of land cover and evapotranspiration in the Lena River Delta, Siberia

Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3m resolution) with coarse-scale (upto 30m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes

Climate change reduces winter overland travel across the Pan-Arctic even under low-end global warming scenarios

Amplified climate warming has led to permafrost degradation and a shortening of the winter season, both impacting cost-effective overland travel across the Arctic. Here we use, for the first time, four state-of-the-art Land Surface Models that explicitly consider ground freezing states, forced by a subset of bias-adjusted CMIP5 General Circulation Models to estimate the impact of different global warming scenarios (RCP2.6, 6.0, 8.5) on two modes of winter travel: overland travel days (OTDs) and ice road construction days (IRCDs). We show that OTDs decrease by on average −13% in the near future (2021–2050) and between −15% (RCP2.6) and −40% (RCP8.5) in the far future (2070–2099) compared to the reference period (1971–2000) when 173 d yr−1 are simulated across the Pan-Arctic. Regionally, we identified Eastern Siberia (Sakha (Yakutia), Khabarovsk Krai, Magadan Oblast) to be most resilient to climate change, while Alaska (USA), the Northwestern Russian regions (Yamalo, Arkhangelsk Oblast, Nenets, Komi, Khanty-Mansiy), Northern Europe and Chukotka are highly vulnerable. The change in OTDs is most pronounced during the shoulder season, particularly in autumn. The IRCDs reduce on average twice as much as the OTDs under all climate scenarios resulting in shorter operational duration. The results of the low-end global warming scenario (RCP2.6) emphasize that stringent climate mitigation policies have the potential to reduce the impact of climate change on winter mobility in the second half of the 21st century. Nevertheless, even under RCP2.6, our results suggest substantially reduced winter overland travel implying a severe threat to livelihoods of remote communities and increasing costs for resource exploration and transport across the Arctic