Proper orthogonal decomposition of ice velocity identifies drivers of flow variability at Sermeq Kujalleq (Jakobshavn Isbræ)

• Published in: The Cryosphere
• Main Authors: D. W. Ashmore, D. W. F. Mair, J. E. Higham, S. Brough, J. M. Lea, I. J. Nias
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2022
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Greenland; Jakobshavn Isbræ; Kujalleq; glacier; Jakobshavn; Jakobshavn isbræ; Sermeq Kujalleq; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-16-219-2022; https://doaj.org/article/e86012e134bc440f9ae0bdd90f0c235e

The increasing volume and spatio-temporal resolution of satellite-derived ice velocity data have created new exploratory opportunities for the quantitative analysis of glacier dynamics. One potential technique, proper orthogonal decomposition (POD), also known as empirical orthogonal functions, has proven to be a powerful and flexible technique for revealing coherent structures in a wide variety of environmental flows. In this study we investigate the applicability of POD to an openly available TanDEM-X/TerraSAR-X-derived ice velocity dataset from Sermeq Kujalleq (Jakobshavn Isbræ), Greenland. We find three dominant modes with annual periodicity that we argue are explained by glaciological processes. The primary dominant mode is interpreted as relating to the stress reconfiguration at the glacier terminus, known to be an important control on the glacier's dynamics. The second and third largest modes together relate to the development of the spatially heterogenous glacier hydrological system and are primarily driven by the pressurisation and efficiency of the subglacial hydrological system. During the melt season, variations in the velocity shown in these two subsidiary modes are explained by the drainage of nearby supraglacial melt ponds, as identified with a Google Earth Engine Moderate Resolution Imaging Spectroradiometer (MODIS) dynamic thresholding technique. By isolating statistical structures within velocity datasets and through their comparison to glaciological theory and complementary datasets, POD indicates which glaciological processes are responsible for the changing bulk velocity signal, as observed from space. With the proliferation of optical- and radar-derived velocity products (e.g. MEaSUREs, ESA CCI, PROMICE), we suggest POD, and potentially other modal decomposition techniques, will become increasingly useful in future studies of ice dynamics.