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  • 1
    Publication Date: 2014-03-24
    Print ISSN: 0022-1430
    Electronic ISSN: 1727-5652
    Topics: Geography , Geosciences
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  • 2
    Publication Date: 2019-07-17
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
    Format: application/pdf
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  • 3
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 94 (2013): 1131–1144, doi:10.1175/BAMS-D-12-00100.1.
    Description: The recent retreat and speedup of outlet glaciers, as well as enhanced surface melting around the ice sheet margin, have increased Greenland's contribution to sea level rise to 0.6 ± 0.1 mm yr−1 and its discharge of freshwater into the North Atlantic. The widespread, near-synchronous glacier retreat, and its coincidence with a period of oceanic and atmospheric warming, suggests a common climate driver. Evidence points to the marine margins of these glaciers as the region from which changes propagated inland. Yet, the forcings and mechanisms behind these dynamic responses are poorly understood and are either missing or crudely parameterized in climate and ice sheet models. Resulting projected sea level rise contributions from Greenland by 2100 remain highly uncertain. This paper summarizes the current state of knowledge and highlights key physical aspects of Greenland's coupled ice sheet–ocean–atmosphere system. Three research thrusts are identified to yield fundamental insights into ice sheet, ocean, sea ice, and atmosphere interactions, their role in Earth's climate system, and probable trajectories of future changes: 1) focused process studies addressing critical glacier, ocean, atmosphere, and coupled dynamics; 2) sustained observations at key sites; and 3) inclusion of relevant dynamics in Earth system models. Understanding the dynamic response of Greenland's glaciers to climate forcing constitutes both a scientific and technological frontier, given the challenges of obtaining the appropriate measurements from the glaciers' marine termini and the complexity of the dynamics involved, including the coupling of the ocean, atmosphere, glacier, and sea ice systems. Interdisciplinary and international cooperation are crucial to making progress on this novel and complex problem.
    Description: 2014-02-01
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 4
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    PANGAEA
    In:  Supplement to: Weber, Samuel; Beutel, Jan; Da Forno, Reto; Geiger, Alain; Gruber, Stephan; Gsell, Tonio; Hasler, Andreas; Keller, Matthias; Lim, Roman; Limpach, Philippe; Meyer, Matthias; Talzi, Igor; Thiele, Lothar; Tschudin, Christian; Vieli, Andreas; Vonder Mühll, Daniel; Yücel, Mustafa (2019): A decade of detailed observations (2008-2018) in steep bedrock permafrost at Matterhorn Hörnligrat (Zermatt, CH). Earth System Science Data, 11, 1203-1237, https://doi.org/10.5194/essd-11-1203-2019
    Publication Date: 2023-03-08
    Description: The data presented is a unique ten+ year data record obtained from in-situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland at 3500 m a.s.l. during the time period 2008-2018 by the PermaSense project. This data set constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over the past decade. By documenting and sharing this data in this form we contribute to making our past research reproducible and facilitate future research based on this data e.g. in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models (code for generating, processing and validating this data set is published on Zenodo https://doi.org/10.5281/zenodo.2542715, 2019). This data set provides primary data products as well as derived data products: GNSS raw data: GNSS observables in the form of daily RINEX 2.11 files GNSS derived data products: Daily positions computed using double-differencing GNSS processing Timelapse images: High-resolution visible light images Timeseries data raw: Per-year and location files or raw sampled data: Weather station, ground temperature, ground resistivity, fracture displacement and inclinometer data Timeseries derived data products: Cleaned and aggregated hourly values of the above Timeseries sanity plots: Standardized plots to obtain a visual overview and check data All data contained in this data set including updates to newer data can also be retrieved using the toolset available at https://doi.org/10.5281/zenodo.2542715, 2019 from the online PermaSense data repository at http://data.permasense.ch.
    Keywords: File content; File format; File name; File size; Long-term monitoring; Matterhorn_Hoernligrat; Matterhorn, Switzerland; Mountain Permafrost; MULT; Multiple investigations; Natural hazards; PermaSense; Uniform resource locator/link to file; Wireless sensors
    Type: Dataset
    Format: text/tab-separated-values, 40 data points
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  • 5
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    Unknown
    PANGAEA
    In:  Supplement to: Mölg, Nico; Bolch, Tobias; Walter, Andrea; Vieli, Andreas (2019): Unravelling the evolution of Zmuttgletscher and its debris cover since the end of the Littel Ice Age. The Cryosphere, 13(7), 1889-1909, https://doi.org/10.5194/tc-13-1889-2019
    Publication Date: 2023-02-04
    Description: Here we provide in-situ measurements on debris cover thickness on Zmuttgletscher, Switzerland. It is one of the largest heavily debris-covered glaciers in the Alps. We further provide 2 DEMs based on UAV imagery and the respective orthophotos, as well as surface flow velocities derived from the orthophotos by automated feature tracking. Further information can be found in the research paper by Mölg et al. (2019) published in The Cryosphere.
    Keywords: debris cover; glacier elevation; MULT; Multiple investigations; Switzerland; velocity; Zmuttgletscher
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 6
    Publication Date: 2023-02-04
    Keywords: debris cover; File format; File name; File size; glacier elevation; MULT; Multiple investigations; Switzerland; Uniform resource locator/link to file; velocity; Zmuttgletscher
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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  • 7
    Publication Date: 2023-02-04
    Keywords: Ablation; DATE/TIME; debris cover; Debris thickness; glacier elevation; Identification; MULT; Multiple investigations; Switzerland; velocity; Zmuttgletscher
    Type: Dataset
    Format: text/tab-separated-values, 21 data points
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  • 8
    Publication Date: 2024-03-23
    Description: The dataset described in this document has been put together for the purposes of numerical ice sheet modelling of the Antarctic Ice Sheet (AIS), containing data on the ice sheet configuration (e.g. ice surface and ice thickness) and boundary conditions, such as the surface air temperature and accumulation. It is now possible to download a community ice sheet model (e.g. Glimmer-CISM, Rutt et al., 2009 doi:10.1029/2008JF001015), but without adequate data it is difficult to utilise such models. More specifically, ice sheet models that are initialised and run forward from the present day ice sheet configuration, need input data to represent the present-day ice sheet configuration as closely as possible (unlike those spun-up from ice free conditions, which only require the bed/bathymetry). Whilst the BEDMAP dataset (Lythe et al., 2001) was a step forward when it was made, there are a number of inconsistencies within the dataset (see Section 3), and since its release, more data has become available. The dataset described here incorporates some major new datasets (e.g. AGASEA/BBAS ice thickness, Nitsche et al. (2006) bathymetry doi:10.1029/2007GC001694), but by no means incorporates all the new data available. This considerable task is left for a 'BEDMAP2', (an updated version of BEDMAP), however, the processing carried out in this document illustrates the requirements of a dataset for the purpose of high resolution ice sheet modelling, and bridges the gap until a BEDMAP2 is published. It is envisaged, however, that updated versions of the data set will be made available periodically when new regional data sets become available and can be readily incorporated.
    Type: Dataset
    Format: application/zip, 15.1 MBytes
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  • 9
    Publication Date: 2024-05-08
    Description: The data presented is a unique ten+ year data record obtained from in-situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland at 3500 m a.s.l. during the time period 2008-2019 by the PermaSense project. This data set constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over the past decade. By documenting and sharing this data in this form we contribute to making our past research reproducible and facilitate future research based on this data e.g. in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models. This data set provides primary data products as well as derived data products: GNSS raw data: GNSS observables in the form of daily RINEX 2.11 files GNSS derived data products: Daily positions computed using double-differencing GNSS processing Timelapse images: High-resolution visible light images Timeseries data raw: Per-year and location files or raw sampled data: Weather station, ground temperature, ground resistivity, fracture displacement and inclinometer data Timeseries derived data products: Cleaned and aggregated hourly values of the above Timeseries sanity plots: Standardized plots to obtain a visual overview and check data All data contained in this data set including updates to newer data can also be retrieved using the toolset available at https://gitlab.ethz.ch/tec/public/permasense/permasense_datamgr from the online PermaSense data repository at http://data.permasense.ch. The version/tag used for the 2020 edition of the Matterhorn data is https://gitlab.ethz.ch/tec/public/permasense/permasense_datamgr/tree/matterhorn_data_2020.
    Keywords: File content; File format; File name; File size; Long-term monitoring; Matterhorn_Hoernligrat; Matterhorn, Switzerland; Mountain Permafrost; MULT; Multiple investigations; Natural hazards; Uniform resource locator/link to file; Wireless sensors
    Type: Dataset
    Format: text/tab-separated-values, 85 data points
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  • 10
    Publication Date: 2024-04-20
    Description: This dataset collates data of continuously acquired kinematic observations obtained through in-situ Global Navigation Satellite Systems (GNSS) instruments that have been designed and implemented in a large-scale multi field-site monitoring campaign across the whole Swiss Alps. The landforms covered include rock glaciers, high-alpine steep bedrock bedrock as well as landslide sites, most of which are situated in permafrost areas. The dataset was acquired at 54 different stations situated at locations from 2304 to 4003 meter a.s.l and comprises 209'948 daily positions derived through double-differential GNSS post-processing. Apart from these, the dataset contains down-sampled and cleaned time series of weather station and inclinometer data as well as the full set of GNSS observables in RINEX format. Furthermore the dataset is accompanied by tools for processing and data management in order to facilitate reuse, open alternate usage opportunities and support the life-long living data process with updates.
    Keywords: Binary Object; Binary Object (File Size); Cryosphere; File content; GNSS; kinematics; Landslides; mass movements; MULT; Multiple investigations; Natural hazards; Permafrost; Rockfall; Swiss_Alps
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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