Historical Greenland glacier calving front locations from 1973 until 2013

Metadaten

Für den Inhalt der Forschungsdaten verantwortliche Person(en)	Liebezeit, Charlotte - Technische Universität Dresden
Für den Inhalt der Forschungsdaten verantwortliche Person(en)	Loebel, Erik - Technische Universität Dresden (ORCID: 0000-0001-9874-9295)
Kurzbeschreibung	This product contains 170 Greenland glacier calving front positions from the following glaciers: Hagen Bræ, Helheim Glacier, Kangiata Nunaata Sermia, Nioghalvfjerdsbræ, Tracy Glacier and Zachariae Isstrøm. The glacier calving front positions have been manually derived from multispectral Landsat-8 imagery and are stored in an ESRI shapefile format using the WGS 84 / NSIDC Sea Ice Polar Stereographic North (EPSG:3413) Coordinate Reference System. Hagen Bræ covers the years 1985-2013 and Nioghalvfjerdsbræ between 1985-1994 on a nearly yearly basis. For Zachariae Isstrøm, calving fronts are featured every year between 1985-1993. With two calving fronts per year, except for 1984, Helheim Glacier involves the years 1979-1988. Irregular coverage with up to 3 calving front locations in one year show Kangiata Nunaata Sermia between 1978-2012 and Tracy Glacier covering the years 1973-2013.
Länder, auf die sich die Daten beziehen	GREENLAND	de
Entstehungsjahr oder Entstehungszeitraum	2022-2023
Veröffentlichungsjahr	2023
Herausgeber	Technische Universität Dresden
Referenzen auf ergänzende Materialien	IsPartOf: 123456789/5680 (Handle)
Inhalt der Forschungsdaten	Dataset: Calving front locations of Greenland Glaciers
Inhaber der Nutzungsrechte	Technische Universität Dresden
Nutzungsrechte des Datensatzes	CC-BY-SA-4.0
Angabe der Fachgebiete	Geography	de
Angabe der Fachgebiete	Geological Science	de
Titel des Datensatzes	Historical Greenland glacier calving front locations from 1973 until 2013

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Change pattern identification of marine-terminating outlet glaciers [5]
Marine-terminating outlet glaciers experience a combination of seasonal and climate-driven change. Nearby glaciers exhibit very different retreat and advance behavior despite being situated in similar climatic conditions. This highlights the demand to essentially improve our understanding of the driving mechanisms and to provide a basis for parameterizations of oceanic forcing that are fed into mass-loss projections. Temporal changes of glacial flow velocities are presumably linked to the evolution of the subglacial hydrological system. Depending on the type of subglacial system, the temporal acceleration of the glacier is represented by different characteristics. While this is typically investigated only along a central flow line, the spatial distribution contains more information on the cause of the acceleration. In a similar way, the spatial pattern of acceleration due to changes at the calving front is likely driven by upstream propagation of changes in stresses. Hence, understanding the mechanisms in detail requires an analysis of different physical variables in high temporal and spatial resolution and combination with ice modelling. With the new generation of satellites the era of big data has started in glaciology, and new efficient methods to analyze change patterns are required.

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