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  • 1
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    Atmospheric methane consumption by upland soils in the Western Canadian Arctic and Finnish Lapland (2018–2021) (2023)
    PANGAEA
    Details
    Publication Date: 2023-09-09
    Description: This dataset includes two data tables of methane (CH4) fluxes measured in Arctic uplands. Dataset 1 contains CH4 fluxes measured at high temporal resolution (hourly fluxes) collected over two snow-free seasons (June–August; 2019, 2021) at Trail Valley Creek, an Arctic tundra site in the Western Canadian Arctic. Fluxes were measured with automated chambers installed in replication of six at three individual landcover vegetation units (Lichen, Shrub, Tussock) within dwarf-shrub dominated tundra. Site meteorological data are provided with the flux data at hourly resolution. Dataset 2 includes campaign-based, manual chamber measurements at sites displaying net CH4 uptake. These manual measurements were conducted during the growing season at typical, well-drained upland sites, which included, besides Trail Valley Creek, three additional sites in the Canadian and European Arctic (Havikpak Creek, Scotty Creek, Kilpisjärvi). Besides CH4 flux observations, dataset 2 contains measured greenhouse gas concentration profiles of CH4, carbon dioxide (CO2) and nitrous oxide (N2O) at 2 cm, 5 cm, 10 cm, and 20 cm soil depths, as well as site meteorological data. While wetlands are known CH4 emitters, drier arctic and boreal uplands may act as sinks of atmospheric CH4. The scope of the study and this dataset is to improve the spatial and temporal coverage of low CH4 emitting and sites displaying net CH4 uptake across the Arctic. Both datasets are meant as supplement to the published study, where further, detailed information on site conditions and methodology can be found.
    Keywords: Arctic; automated chambers; Methane; methane oxidation; Tundra; Uplands
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Atmospheric methane consumption by upland soils - dataset 2: campaign-based manual chamber measurements (2023)
    PANGAEA
    Details
    Publication Date: 2023-09-09
    Description: This dataset includes campaign-based, manual chamber measurements at sites displaying net methane (CH4) uptake. These manual measurements were conducted during the growing season at typical, well-drained upland sites, which included, besides Trail Valley Creek, three additional sites in the Canadian and European Arctic (Havikpak Creek, Scotty Creek, Kilpisjärvi). Besides CH4 flux observations, the dataset contains measured greenhouse gas concentration profiles of CH4, carbon dioxide (CO2) and nitrous oxide (N2O) at 2 cm, 5 cm, 10 cm, and 20 cm soil depths, as well as site meteorological data.
    Keywords: Air temperature at 2 m height; Arctic; automated chambers; Carbon dioxide; Date; DATE/TIME; Event label; Friction velocity; Greenness; Havikpak Creek; Humidity, relative; Kilpisjärvi; Land cover classes; Land cover type; LATITUDE; Location ID; LONGITUDE; Long-wave downward radiation; Long-wave upward radiation; Methane; Methane, flux; methane oxidation; MULT; Multiple investigations; Nitrous oxide; Photosynthetic photon, flux density; Precipitation; Pressure, atmospheric; Replicate; Scotty Creek; Short-wave downward (GLOBAL) radiation; Short-wave upward (REFLEX) radiation; Site; SoilChamber_HavikpakCreek; SoilChamber_Kilpisjaervi; SoilChamber_ScottyCreek; SoilChamber_TrailValley; Soil moisture; Temperature, soil; Thaw depth of active layer; Trail Valley; Tundra; Uplands; Vapour pressure deficit; Vegetation, cover; Water filled pore space; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 6426 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    T-MOSAiC 2021 myThaw data set (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: The Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) 2021 permafrost thaw data set provides standardized measurements for permafrost thaw and the linked parameters snow depth, vegetation height, water level and soil texture as suggested by Boike et al., 2021. It contains measurements from eight circumpolar permafrost sites where data was obtained using the myThaw app which is based on the user-friendly, multiparameter protocol for standardized monitoring of permafrost thaw for the year 2021. The data set contains detailed metadata for each site including data on the timing of data collection, geographical coordinates and land surface characteristics (vegetation, ground surface and water features).
    Keywords: Accessibility, description; active layer thaw depth; Bayelva; Bayelva_2021_transect; Cambridge Bay; CambridgeBay_2021_transect; Climate station information (true/false); CNR_at_Bayelva_2021_transect; CNR@Bayelva; Comment; Data availability (true/false); DATE/TIME; Distance; Disturbance description; Disturbance Type; ELEVATION; Elevation description; Field measurement; Ground surface, presence of rock (true/false); Ground surface, presence of soil (true/false); Ground wetness description; Identification; Image; Image, earth surface (water, ice, land); Kevo_Vaisejaeggi_2021_transect; Kevo Vaisejaeggi; LATITUDE; Latitude description; LONGITUDE; Longitude description; myThaw app; Organic matter, layer thickness; Parameter; permafrost monitoring protocol; Presence of ice (true/false); Presence of moss or lichen (true/false); Presence of rocks (true/false); Presence of treecover (true/false); Protocol ID; Samoylov; Samoylov_2021_transect; Siksik_Creek_2021_transect; Siksik Creek (TVC); Site; snow depth; Snow depth; Snow depth, error; soil characteristics; Soil texture; Soil type, presence of clay (true/false); Soil type, presence of gravel (true/false); Soil type, presence of peat (true/false); Soil type, presence of sand (true/false); Soil type, presence of silt (true/false); Soil type, presence of unknown (true/false); Thaw depth of active layer; Thaw depth of active layer, error; Toolik_Field_Station_2021_transect; Toolik Field Station; Tree type, presence of broadleaf (true/false); Tree type, presence of deciduous needleleaf (true/false); Tree type, presence of evergreen needleleaf (true/false); vegetation height; Vegetation height; Vegetation type; Vegetation type, presence of deciduous shrub (true/false); Vegetation type, presence of evergreen shrub (true/false); Vegetation type, presence of forbs (true/false); Vegetation type, presence of graminoids (true/false); Vegetation type, presence of lichen (true/false); Vegetation type, presence of moss (true/false); Water feature, presence of lake (true/false); Water feature, presence of none (true/false); Water feature, presence of river/creek (true/false); Water feature, presence of unknown (true/false); Water feature, presence of water tracks (true/false); Water feature, presence of wet depressions (true/false); Water feature, presence of wetland (true/false); Water feature description; Water level; Water level, error; Zackenberg_2021_dry_transect; Zackenberg_2021_wet_transect; Zackenberg CALM dry transect; Zackenberg CALM wet transect
    Type: Dataset
    Format: text/tab-separated-values, 105358 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
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    Multitemporal terrestrial laser scanning point clouds for thaw subsidence observation at Arctic permafrost monitoring sites (2021)
    Details
    Publication Date: 2021-07-04
    Description: This paper investigates different methods for quantifying thaw subsidence using terrestrial laser scanning (TLS) point clouds. Thaw subsidence is a slow (millimetre to centimetre per year) vertical displacement of the ground surface common in ice‐rich permafrost‐underlain landscapes. It is difficult to quantify thaw subsidence in tundra areas as they often lack stable reference frames. Also, there is no solid ground surface to serve as a basis for elevation measurements, due to a continuous moss–lichen cover. We investigate how an expert‐driven method improves the accuracy of benchmark measurements at discrete locations within two sites using multitemporal TLS data of a 1‐year period. Our method aggregates multiple experts’ determination of the ground surface in 3D point clouds, collected in a web‐based tool. We then compare this to the performance of a fully automated ground surface determination method. Lastly, we quantify ground surface displacement by directly computing multitemporal point cloud distances, thereby extending thaw subsidence observation to an area‐based assessment. Using the expert‐driven quantification as reference, we validate the other methods, including in‐situ benchmark measurements from a conventional field survey. This study demonstrates that quantifying the ground surface using 3D point clouds is more accurate than the field survey method. The expert‐driven method achieves an accuracy of 0.1 ± 0.1 cm. Compared to this, in‐situ benchmark measurements by single surveyors yield an accuracy of 0.4 ± 1.5 cm. This difference between the two methods is important, considering an observed displacement of 1.4 cm at the sites. Thaw subsidence quantification with the fully automatic benchmark‐based method achieves an accuracy of 0.2 ± 0.5 cm and direct point cloud distance computation an accuracy of 0.2 ± 0.9 cm. The range in accuracy is largely influenced by properties of vegetation structure at locations within the sites. The developed methods enable a link of automated quantification and expert judgement for transparent long‐term monitoring of permafrost subsidence. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd
    Description: This paper investigates methods using terrestrial laser scanning point clouds for quantifying thaw subsidence in permafrost‐underlain tundra fully automatically and by including information collected from expert analysts. Results of the developed methods achieve higher accuracies compared to manual in‐situ measurements, which are found to vary from reference measurements in the magnitude of the actual ground surface displacement observed in a 1‐year period. A link of automated quantification and expert judgement can enable transparent long‐term monitoring of thaw subsidence.
    Description: German Federal Ministry of Economics and Technology (BMWi) and German Aerospace Center (DLR)
    Description: Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences, University of Heidelberg http://dx.doi.org/10.13039/501100003801
    Description: Federal Ministry of Economics and Technology (BMWi) and the German Aerospace Centre (DLR), Germany http://dx.doi.org/10.13039/501100002765
    Keywords: 551 ; change analysis ; 3D geoinformation ; ground surface displacement ; permafrost monitoring ; multitemporal LiDAR
    Type: article
    Location Call Number Limitation Availability
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    CITATION GEO-LEO
  • 5
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    Standardized monitoring of permafrost thaw: a user-friendly, multi-parameter protocol (2021)
    In:  EPIC3Arctic Science, ISSN: 2368-7460
    Details
    Publication Date: 2021-09-20
    Description: Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems and human livelihoods. The rate of permafrost thaw is controlled by surface and subsurface properties and processes, all of which are potentially linked with each other. Yet, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists and indigenous groups, to collect standardized metadata and data on permafrost thaw.The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters measured along transects are: snow depth, thaw depth, vegetation height, soil texture, and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. Our hope is that this openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, thus to the broad community represented by the T-MOSAIC project.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , notRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 6
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    Standardized monitoring of permafrost thaw: a user-friendly, multiparameter protocol (T-MOSAiC) (2021)
    In:  EPIC3Svalbard Science Conference 2021, 2021-11-02-2021-11-03
    Details
    Publication Date: 2021-12-06
    Description: Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems and human livelihoods. The rate of permafrost thaw is affected by surface and subsurface properties and processes, all of which are potentially linked with each other. Yet, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists and indigenous groups, to collect standardized metadata and data on permafrost thaw. The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters along transects are: snow depth, thaw depth, and vegetation height, soil texture and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. The comprehensive description and management of all data with metadata, central data storage and controlled data access is applied through the Observation to Archives (O2A) dataflow framework. Through this standardized procedure, data can be monitored in near-real time and their spatial distribution visualized. The dedicated user-friendly application (app) myThaw facilitates the data entry of field measurements and provides standardized data collection and documentation. We started our first measurements during March 2021 with snow depth measurements at the Bayelva site along a 10 meter transect. Several INTERACT sites in Svalbard, Alaska, Canada and Siberia have also agreed to start this data collection. This openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, thus to the broad community represented by the T-MOSAIC project.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 7
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    A user-friendly, multi-parameter protocol for monitoring permafrost thaw (2021)
    In:  EPIC3AGU Fall Meeting, New Orleans, LA, USA/Online, 2021-12-13-2021-12-17
    Details
    Publication Date: 2022-01-09
    Description: There is an urgent need for standardized data collection to better understand permafrost thaw and its interaction with vegetation, hydrology, soil and snow. To enable this, the Permafrost Thaw Action Group of T-MOSAiC have developed a protocol for gathering integrated observations of multiple connected components of permafrost landscapes. It is integrated with a user-friendly app aimed at non-experts to facilitate collection and synthesis of data from across the Arctic. Recognizing the fundamental role of interactions between the different components of the permafrost system, we provide measurement guidelines for variables pertaining to snow, vegetation, hydrology, soil and permafrost in a single protocol. The measured variables include snow depth, vegetation height, water level, soil type, and thaw depth. The protocol locates all measurements on transects that are revisited throughout the year. The co-located measurements of multiple variables facilitate quantification of interactions between these variables and model–data integration. The protocol is geared toward non-experts, including citizen scientists. We provide video tutorials and a user-friendly app. The protocol uses simple measurements that do not require specialist equipment or skills. While variables that are more difficult to measure could not be included, we believe that the simplicity of the protocols will enable greater participation in data collection and thus an improved coverage of the permafrost region. Along with the protocol and app, we present the first results from the data collection which has been live now for several months, and details of how to get involved.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 8
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    Multitemporal terrestrial laser scanning point clouds for thaw subsidence observation at Arctic permafrost monitoring sites (2020)
    Wiley
    In:  EPIC3Earth Surface Processes and Landforms, Wiley, ISSN: 0197-9337
    Details
    Publication Date: 2022-10-21
    Description: This paper investigates different methods for quantifying thaw subsidence using terrestrial laser scanning (TLS) point clouds. Thaw subsidence is a slow (millimetre to centimetre per year) vertical displacement of the ground surface common in ice‐rich permafrost‐underlain landscapes. It is difficult to quantify thaw subsidence in tundra areas as they often lack stable reference frames. Also, there is no solid ground surface to serve as a basis for elevation measurements, due to a continuous moss–lichen cover. We investigate how an expert‐driven method improves the accuracy of benchmark measurements at discrete locations within two sites using multitemporal TLS data of a 1‐year period. Our method aggregates multiple experts’ determination of the ground surface in 3D point clouds, collected in a web‐based tool. We then compare this to the performance of a fully automated ground surface determination method. Lastly, we quantify ground surface displacement by directly computing multitemporal point cloud distances, thereby extending thaw subsidence observation to an area‐based assessment. Using the expert‐driven quantification as reference, we validate the other methods, including in‐situ benchmark measurements from a conventional field survey. This study demonstrates that quantifying the ground surface using 3D point clouds is more accurate than the field survey method. The expert‐driven method achieves an accuracy of 0.1 ± 0.1 cm. Compared to this, in‐situ benchmark measurements by single surveyors yield an accuracy of 0.4 ± 1.5 cm. This difference between the two methods is important, considering an observed displacement of 1.4 cm at the sites. Thaw subsidence quantification with the fully automatic benchmark‐based method achieves an accuracy of 0.2 ± 0.5 cm and direct point cloud distance computation an accuracy of 0.2 ± 0.9 cm. The range in accuracy is largely influenced by properties of vegetation structure at locations within the sites. The developed methods enable a link of automated quantification and expert judgement for transparent long‐term monitoring of permafrost subsidence.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Location Call Number Limitation Availability
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