Seasonal Patterns of Greenland Ice Velocity From Sentinel-1 SAR Data Linked to Runoff

• Published in: Geophysical Research Letters
• Main Authors: Solgaard, A.M., Rapp, D., Noël, Brice, Hvidberg, C.S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: John Wiley and Sons Inc 2022
• Subjects: Greenland Ice Sheet; ice dynamics; ice velocity; machine learning; seasonality; subglacial hydrology; Green land; Ice sheet; Interannual variability; Machine-learning; Seasonal patterns; Geophysics; Earth and Planetary Sciences (all); General Earth and Planetary Sciences; Physical; chemical; mathematical & earth Sciences; Earth sciences & physical geography; Physique; chimie; mathématiques & sciences de la terre; Sciences de la terre & géographie physique; Greenland; Ice Sheet
• Online Access: https://orbi.uliege.be/handle/2268/302203; https://orbi.uliege.be/bitstream/2268/302203/1/Solgaard_2022_GRL.pdf; https://doi.org/10.1029/2022GL100343

peer reviewed 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.