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  • 1
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    Ice wedge polygon stability on steep slopes in West Greenland related to temperature and moisture dynamics of the active layer (2023)
    Details
    Publication Date: 2024-02-15
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Ice wedge polygons on steep slopes have generally been described as being covered by periglacial sediments and, typically, the active layer on slopes becomes mobile during thaw periods, which can lead to solifluction. In West Greenland close to the ice margin, however, the active layer and ice wedge polygons are stable despite their occurrence on steep slopes with inclinations of ≥30°. We conducted a soil survey (including sampling for soil analyses and radiocarbon dating) in the Umimmalissuaq valley and installed a field station ~4 km east of the current ice margin to monitor soil temperature and water tension at depths of 10, 20 and 35 cm of the active layer on a steep, north‐facing slope in the middle of an ice wedge polygon from 2009 to 2015. Thawing and freezing periods lasted between 2 and 3 months and the active layer was usually completely frozen from November to April. We observed simultaneous and complete water saturation at all three depths of the active layer in one summer for 1 day. The amount of water in the active layer apparently was not enough to trigger solifluction during the summer thaw, even at slope inclinations above 30°. In addition, the dense shrub tundra absorbs most of the water during periods between thawing and freezing, which further stabilizes the slope. This process, together with the dry and continental climate caused by katabatic winds combined with no or limited frost heave, plays a crucial role in determining the stability of these slopes and can explain the presence of large‐scale stable ice wedge polygon networks in organic matter‐rich permafrost, which is about 5,000 years old. This study underlines the importance of soil hydrodynamics and local climate regime for landscape stability and differing intensities of solifluction processes in areas with strong geomorphological gradients and rising air temperatures.〈/p〉
    Keywords: ddc:551.3 ; permafrost ; soil temperature ; soil water tension ; solifluction
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
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    SalaciaML: A Deep Learning Approach for Supporting Ocean Data Quality Control (2021)
    Frontiers
    Details
    Publication Date: 2021-05-03
    Description: We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to algorithmically support and partly automate the quality control of ocean data profiles are especially helpful for the gross errors in the data. Range filters, spike detection, and data distribution checks remove reliably the outliers and errors in the data, still wrong classifications occur. Various automated quality control procedures have been successfully implemented within the main international and EU marine data infrastructures (WOD, CMEMS, IQuOD, SDN) but their resulting data products are still containing data anomalies, bad data flagged as good and vice-versa. They also include visual inspection of suspicious measurements, which is a time consuming activity, especially if the number of suspicious data detected is large. A deep learning approach could highly improve our capabilities to quality assess big data collections and contemporary reducing the human effort. Our algorithm SalaciaML is meant to complement classical automated quality control procedures in supporting the time consuming visually inspection of data anomalies by quality control experts. As a first approach we applied the algorithm to a large dataset from the Mediterranean Sea. SalaciaML has been able to detect correctly more than 90% of all good and/or bad data in 11 out of 16 Mediterranean regions.
    Description: This project has received funding from the European Union Horizon 2020 and Seventh Framework Programmes under grant agreement number 730960 SeaDataCloud.
    Description: Published
    Description: 611742
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Keywords: 05.06. Methods
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 3
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    SalaciaML: A Deep Learning Approach for Supporting Ocean Data Quality Control (2021)
    In:  EPIC3Frontiers in Marine Science, 8, pp. 314
    Details
    Publication Date: 2021-06-05
    Description: We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to algorithmically support and partly automate the quality control of ocean data profiles are especially helpful for the gross errors in the data. Range filters, spike detection, and data distribution checks remove reliably the outliers and errors in the data, still wrong classifications occur. Various automated quality control procedures have been successfully implemented within the main international and EU marine data infrastructures (WOD, CMEMS, IQuOD, SDN) but their resulting data products are still containing data anomalies, bad data flagged as good and vice-versa. They also include visual inspection of suspicious measurements, which is a time consuming activity, especially if the number of suspicious data detected is large. A deep learning approach could highly improve our capabilities to quality assess big data collections and contemporary reducing the human effort. Our algorithm SalaciaML is meant to complement classical automated quality control procedures in supporting the time consuming visually inspection of data anomalies by quality control experts. As a first approach we applied the algorithm to a large dataset from the Mediterranean Sea. SalaciaML has been able to detect correctly more than 90% of all good and/or bad data in 11 out of 16 Mediterranean regions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 4
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    A new concept for estimating the influence of vegetation on throughfall kinetic energy using aerial laser scanning (2021)
    Details
    Publication Date: 2021-07-03
    Description: Soil loss caused by erosion has enormous economic and social impacts. Splash effects of rainfall are an important driver of erosion processes; however, effects of vegetation on splash erosion are still not fully understood. Splash erosion processes under vegetation are investigated by means of throughfall kinetic energy (TKE). Previous studies on TKE utilized a heterogeneous set of plant and canopy parameters to assess vegetation's influence on erosion by rain splash but remained on individual plant‐ or plot‐levels. In the present study we developed a method for the area‐wide estimation of the influence of vegetation on TKE using remote sensing methods. In a literature review we identified key vegetation variables influencing splash erosion and developed a conceptual model to describe the interaction of vegetation and raindrops. Our model considers both amplifying and protecting effect of vegetation layers according to their height above the ground and aggregates them into a new indicator: the Vegetation Splash Factor (VSF). It is based on the proportional contribution of drips per layer, which can be calculated via the vegetation cover profile from airborne LiDAR datasets. In a case study, we calculated the VSF using a LiDAR dataset for La Campana National Park in central Chile. The studied catchment comprises a heterogeneous mosaic of vegetation layer combinations and types and is hence well suited to test the approach. We calculated a VSF map showing the relation between vegetation structure and its expected influence on TKE. Mean VSF was 1.42, indicating amplifying overall effect of vegetation on TKE that was present in 81% of the area. Values below 1 indicating a protective effect were calculated for 19% of the area. For future work, we recommend refining the weighting factor by calibration to local conditions using field‐reference data and comparing the VSF with TKE field measurements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd
    Description: The Vegetation Splash Factor maps the amplification or reduction of rain‐fall kinetic energy based on the three‐dimensional vegetation structure. The presented approach allows the area‐wide application based on aerial lidar point clouds and can improve the representation of vegetation in erosion models. This study features a literature review and a case study documenting the development of the new approach.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 551 ; splash erosion ; throughfall kinetic energy ; remote sensing ; LiDAR ; Vegetation Splash Factor
    Type: article
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  • 5
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    Ice wedge polygon stability on steep slopes in West Greenland related to temperature and moisture dynamics of the active layer (2023)
    Wiley
    In:  EPIC3Permafrost and Periglacial Processes, Wiley, 34(2), pp. 194-207, ISSN: 1045-6740
    Details
    Publication Date: 2023-08-28
    Description: Ice wedge polygons on steep slopes have generally been described as being covered by periglacial sediments and, typically, the active layer on slopes becomes mobile during thaw periods, which can lead to solifluction. In West Greenland close to the ice margin, however, the active layer and ice wedge polygons are stable despite their occurrence on steep slopes with inclinations of ≥30°. We conducted a soil survey (including sampling for soil analyses and radiocarbon dating) in the Umimmalissuaq valley and installed a field station ~4 km east of the current ice margin to monitor soil temperature and water tension at depths of 10, 20 and 35 cm of the active layer on a steep, north-facing slope in the middle of an ice wedge polygon from 2009 to 2015. Thawing and freezing periods lasted between 2 and 3 months and the active layer was usually completely frozen from November to April. We observed simultaneous and complete water saturation at all three depths of the active layer in one summer for 1 day. The amount of water in the active layer apparently was not enough to trigger solifluction during the summer thaw, even at slope inclinations above 30°. In addition, the dense shrub tundra absorbs most of the water during periods between thawing and freezing, which further stabilizes the slope. This process, together with the dry and continental climate caused by katabatic winds combined with no or limited frost heave, plays a crucial role in determining the stability of these slopes and can explain the presence of large-scale stable ice wedge polygon networks in organic matter-rich permafrost, which is about 5,000 years old. This study underlines the importance of soil hydrodynamics and local climate regime for landscape stability and differing intensities of solifluction processes in areas with strong geomorphological gradients and rising air temperatures.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 6
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    A research agenda for nonvascular photoautotrophs under climate change (2023)
    Wiley
    In:  EPIC3New Phytologist, Wiley, 237(5), pp. 1495-1504, ISSN: 0028-646X
    Details
    Publication Date: 2024-03-19
    Description: Nonvascular photoautotrophs (NVP), including bryophytes, lichens, terrestrial algae, and cyanobacteria, are increasingly recognized as being essential to ecosystem functioning in many regions of the world. Current research suggests that climate change may pose a substantial threat to NVP, but the extent to which this will affect the associated ecosystem functions and services is highly uncertain. Here, we propose a research agenda to address this urgent question, focusing on physiological and ecological processes that link NVP to ecosystem functions while also taking into account the substantial taxonomic diversity across multiple ecosystem types. Accordingly, we developed a new categorization scheme, based on microclimatic gradients, which simplifies the high physiological and morphological diversity of NVP and world-wide distribution with respect to several broad habitat types. We found that habitat-specific ecosystem functions of NVP will likely be substantially affected by climate change, and more quantitative process understanding is required on: (1) potential for acclimation; (2) response to elevated CO2; (3) role of the microbiome; and (4) feedback to (micro)climate. We suggest an integrative approach of innovative, multimethod laboratory and field experiments and ecophysiological modelling, for which sustained scientific collaboration on NVP research will be essential.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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