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  • 1
    In: Permafrost and Periglacial Processes, Wiley, Vol. 28, No. 4 ( 2017-10), p. 605-618
    Kurzfassung: The currently observed climate warming will lead to widespread degradation of near‐surface permafrost, which may release substantial amounts of inorganic nitrogen (N) into arctic ecosystems. We studied 11 soil profiles at three different sites in arctic eastern Siberia to assess the amount of inorganic N stored in arctic permafrost soils. We modelled the potential thickening of the active layer for these sites using the CryoGrid2 permafrost model and representative concentration pathways (RCPs) 4.5 (a stabilisation scenario) and 8.5 (a business as usual emission scenario, with increasing carbon emissions). The modelled increases in active‐layer thickness (ALT) were used to estimate potential annual liberation of inorganic N from permafrost soils during the course of climate change. We observed significant stores of inorganic ammonium in permafrost, up to 40‐fold higher than in the active layer. The modelled increase in ALT under the RCP8.5 scenario can result in substantial liberation of N, reaching values up to the order of magnitude of annual fixation of atmospheric N in arctic soils. However, the thaw‐induced liberation of N represents only a small flux in comparison with the overall ecosystem N cycling. Copyright © 2017 John Wiley & Sons, Ltd.
    Materialart: Online-Ressource
    ISSN: 1045-6740 , 1099-1530
    URL: Issue
    RVK:
    Sprache: Englisch
    Verlag: Wiley
    Publikationsdatum: 2017
    ZDB Id: 1479993-5
    SSG: 14
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  • 2
    Online-Ressource
    Online-Ressource
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 23 ( 2022-12-02), p. 6107-
    In: Remote Sensing, MDPI AG, Vol. 14, No. 23 ( 2022-12-02), p. 6107-
    Kurzfassung: Ground subsidence and erosion processes caused by permafrost thaw pose a high risk to infrastructure in the Arctic. Climate warming is increasingly accelerating the thawing of permafrost, emphasizing the need for thorough monitoring to detect damages and hazards at an early stage. The use of unoccupied aerial vehicles (UAVs) allows a fast and uncomplicated analysis of sub-meter changes across larger areas compared to manual surveys in the field. In our study, we investigated the potential of photogrammetry products derived from imagery acquired with off-the-shelf UAVs in order to provide a low-cost assessment of the risks of permafrost degradation along critical infrastructure. We tested a minimal drone setup without ground control points to derive high-resolution 3D point clouds via structure from motion (SfM) at a site affected by thermal erosion along the Dalton Highway on the North Slope of Alaska. For the sub-meter change analysis, we used a multiscale point cloud comparison which we improved by applying (i) denoising filters and (ii) alignment procedures to correct for horizontal and vertical offsets. Our results show a successful reduction in outliers and a thorough correction of the horizontal and vertical point cloud offset by a factor of 6 and 10, respectively. In a defined point cloud subset of an erosion feature, we derive a median land surface displacement of −0.35 m from 2018 to 2019. Projecting the development of the erosion feature, we observe an expansion to NNE, following the ice-wedge polygon network. With a land surface displacement of −0.35 m and an alignment root mean square error of 0.99 m, we find our workflow is best suitable for detecting and quantifying rapid land surface changes. For a future improvement of the workflow, we recommend using alternate flight patterns and an enhancement of the point cloud comparison algorithm.
    Materialart: Online-Ressource
    ISSN: 2072-4292
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2513863-7
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  • 3
    Online-Ressource
    Online-Ressource
    Elsevier BV ; 2013
    In:  Remote Sensing of Environment Vol. 135 ( 2013-08), p. 12-24
    In: Remote Sensing of Environment, Elsevier BV, Vol. 135 ( 2013-08), p. 12-24
    Materialart: Online-Ressource
    ISSN: 0034-4257
    Sprache: Englisch
    Verlag: Elsevier BV
    Publikationsdatum: 2013
    ZDB Id: 1498713-2
    SSG: 11
    SSG: 14
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  • 4
    In: Earth System Science Data, Copernicus GmbH, Vol. 11, No. 1 ( 2019-02-22), p. 261-299
    Kurzfassung: Abstract. Most of the world's permafrost is located in the Arctic, where its frozen organic carbon content makes it a potentially important influence on the global climate system. The Arctic climate appears to be changing more rapidly than the lower latitudes, but observational data density in the region is low. Permafrost thaw and carbon release into the atmosphere, as well as snow cover changes, are positive feedback mechanisms that have the potential for climate warming. It is therefore particularly important to understand the links between the energy balance, which can vary rapidly over hourly to annual timescales, and permafrost conditions, which changes slowly on decadal to centennial timescales. This requires long-term observational data such as that available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, processing, and data quality control. Furthermore, we present a merged data set of the parameters, which were measured from 1998 onwards. Additional data include a high-resolution digital terrain model (DTM) obtained from terrestrial lidar laser scanning. Since the data provide observations of temporally variable parameters that influence energy fluxes between permafrost, active-layer soils, and the atmosphere (such as snow depth and soil moisture content), they are suitable for calibrating and quantifying the dynamics of permafrost as a component in earth system models. The data also include soil properties beneath different microtopographic features (a polygon centre, a rim, a slope, and a trough), yielding much-needed information on landscape heterogeneity for use in land surface modelling. For the record from 1998 to 2017, the average mean annual air temperature was −12.3 ∘C, with mean monthly temperature of the warmest month (July) recorded as 9.5 ∘C and for the coldest month (February) −32.7 ∘C. The average annual rainfall was 169 mm. The depth of zero annual amplitude is at 20.75 m. At this depth, the temperature has increased from −9.1 ∘C in 2006 to −7.7 ∘C in 2017. The presented data are freely available through the PANGAEA (https://doi.org/10.1594/PANGAEA.891142) and Zenodo (https://zenodo.org/record/2223709, last access: 6 February 2019) websites.
    Materialart: Online-Ressource
    ISSN: 1866-3516
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2019
    ZDB Id: 2475469-9
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  • 5
    In: Earth System Science Data, Copernicus GmbH, Vol. 9, No. 1 ( 2017-06-06), p. 317-348
    Kurzfassung: Abstract. Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 104 m2, have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 106 km2 across the Arctic, about 17 % of the Arctic lowland ( 〈  300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 106 m2 down to 1. 0 × 102 m2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 101 km−2. Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349.
    Materialart: Online-Ressource
    ISSN: 1866-3516
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2017
    ZDB Id: 2475469-9
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  • 6
    In: Frontiers in Earth Science, Frontiers Media SA, Vol. 7 ( 2019-1-29)
    Materialart: Online-Ressource
    ISSN: 2296-6463
    Sprache: Unbekannt
    Verlag: Frontiers Media SA
    Publikationsdatum: 2019
    ZDB Id: 2741235-0
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  • 7
    In: Biogeosciences, Copernicus GmbH, Vol. 14, No. 22 ( 2017-11-17), p. 5143-5169
    Kurzfassung: Abstract. It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.
    Materialart: Online-Ressource
    ISSN: 1726-4189
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2017
    ZDB Id: 2158181-2
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  • 8
    In: The Cryosphere, Copernicus GmbH, Vol. 15, No. 3 ( 2021-03-19), p. 1399-1422
    Kurzfassung: 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.
    Materialart: Online-Ressource
    ISSN: 1994-0424
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2021
    ZDB Id: 2393169-3
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  • 9
    Online-Ressource
    Online-Ressource
    Copernicus GmbH ; 2023
    In:  The Cryosphere Vol. 17, No. 10 ( 2023-10-05), p. 4179-4206
    In: The Cryosphere, Copernicus GmbH, Vol. 17, No. 10 ( 2023-10-05), p. 4179-4206
    Kurzfassung: Abstract. 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.
    Materialart: Online-Ressource
    ISSN: 1994-0424
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2023
    ZDB Id: 2393169-3
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  • 10
    In: Biogeosciences, Copernicus GmbH, Vol. 18, No. 2 ( 2021-01-18), p. 343-365
    Kurzfassung: Abstract. Boreal forests in permafrost regions make up around one-third of the global forest cover and are an essential component of regional and global climate patterns. Further, climatic change can trigger extensive ecosystem shifts such as the partial disappearance of near-surface permafrost or changes to the vegetation structure and composition. Therefore, our aim is to understand how the interactions between the vegetation, permafrost and the atmosphere stabilize the forests and the underlying permafrost. Existing model setups are often static or are not able to capture important processes such as the vertical structure or the leaf physiological properties. There is a need for a physically based model with a robust radiative transfer scheme through the canopy. A one-dimensional land surface model (CryoGrid) is adapted for the application in vegetated areas by coupling a multilayer canopy model (CLM-ml v0; Community Land Model) and is used to reproduce the energy transfer and thermal regime at a study site (63.18946∘ N, 118.19596∘ E) in mixed boreal forest in eastern Siberia. An extensive comparison between measured and modeled energy balance variables reveals a satisfactory model performance justifying its application to investigate the thermal regime; surface energy balance; and the vertical exchange of radiation, heat and water in this complex ecosystem. We find that the forests exert a strong control on the thermal state of permafrost through changing the radiation balance and snow cover phenology. The forest cover alters the surface energy balance by inhibiting over 90 % of the solar radiation and suppressing turbulent heat fluxes. Additionally, our simulations reveal a surplus in longwave radiation trapped below the canopy, similar to a greenhouse, which leads to a magnitude in storage heat flux comparable to that simulated at the grassland site. Further, the end of season snow cover is 3 times greater at the forest site, and the onset of the snow-melting processes are delayed.
    Materialart: Online-Ressource
    ISSN: 1726-4189
    Sprache: Englisch
    Verlag: Copernicus GmbH
    Publikationsdatum: 2021
    ZDB Id: 2158181-2
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