Seasonal Patterns of Greenland Ice Velocity From Sentinel-1 SAR Data Linked to Runoff
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Seasonal Patterns of Greenland Ice Velocity From Sentinel-1 SAR Data Linked to Runoff. / Solgaard, A. M.; Rapp, D.; Noël, B. P.Y.; Hvidberg, C. S.
I: Geophysical Research Letters, Bind 49, Nr. 24, e2022GL100343, 2022.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Seasonal Patterns of Greenland Ice Velocity From Sentinel-1 SAR Data Linked to Runoff
AU - Solgaard, A. M.
AU - Rapp, D.
AU - Noël, B. P.Y.
AU - Hvidberg, C. S.
N1 - Funding Information: We thank the editor and two anonymous reviewers for their helpful comments on the original manuscript. Ice velocity maps were produced as part of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) using Copernicus Sentinel‐1 SAR images distributed by ESA, and were provided by the Geological Survey of Denmark and Greenland (GEUS) at http://www.promice.dk . Brice Noël was funded by the NWO VENI grant VI.Veni.192.019. Anne Solgaard was supported by the Programme for Monitoring the Greenland Ice Sheet (PROMICE). Landsat images in Supporting Information S1 courtesy of the U.S. Geological Survey. Funding Information: We thank the editor and two anonymous reviewers for their helpful comments on the original manuscript. Ice velocity maps were produced as part of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) using Copernicus Sentinel-1 SAR images distributed by ESA, and were provided by the Geological Survey of Denmark and Greenland (GEUS) at http://www.promice.dk. Brice Noël was funded by the NWO VENI grant VI.Veni.192.019. Anne Solgaard was supported by the Programme for Monitoring the Greenland Ice Sheet (PROMICE). Landsat images in Supporting Information S1 courtesy of the U.S. Geological Survey. Publisher Copyright: © 2022. The Authors.
PY - 2022
Y1 - 2022
N2 - Accurate projections of the mass loss from the Greenland Ice Sheet (GrIS) require a complete understanding of the ice-dynamic response to climate forcings on seasonal and interannual timescales and would greatly benefit from more observational evidence. Here, we analyze a 5-year, high-resolution data set of ice velocities of the GrIS using K-means, an unsupervised clustering algorithm, to identify ice-sheet wide characteristic seasonal flow patterns. We include all areas flowing >0.3 m/d and obtain an ice-sheet wide overview of the seasonality and the interannual variability. It shows both a spatial and interannual variability in seasonal flow patterns, both along individual glaciers and between glaciers. We compare with runoff from a regional climate model and infer that the ice-sheet wide patterns are linked to the availability of water penetrating to the base of the ice.
AB - Accurate projections of the mass loss from the Greenland Ice Sheet (GrIS) require a complete understanding of the ice-dynamic response to climate forcings on seasonal and interannual timescales and would greatly benefit from more observational evidence. Here, we analyze a 5-year, high-resolution data set of ice velocities of the GrIS using K-means, an unsupervised clustering algorithm, to identify ice-sheet wide characteristic seasonal flow patterns. We include all areas flowing >0.3 m/d and obtain an ice-sheet wide overview of the seasonality and the interannual variability. It shows both a spatial and interannual variability in seasonal flow patterns, both along individual glaciers and between glaciers. We compare with runoff from a regional climate model and infer that the ice-sheet wide patterns are linked to the availability of water penetrating to the base of the ice.
KW - Greenland Ice Sheet
KW - ice dynamics
KW - ice velocity
KW - machine learning
KW - seasonality
KW - subglacial hydrology
U2 - 10.1029/2022GL100343
DO - 10.1029/2022GL100343
M3 - Journal article
AN - SCOPUS:85145193527
VL - 49
JO - Geophysical Research Letters
JF - Geophysical Research Letters
SN - 0094-8276
IS - 24
M1 - e2022GL100343
ER -
ID: 334013060