Preprints
https://doi.org/10.5194/tc-2021-184
https://doi.org/10.5194/tc-2021-184

  12 Jul 2021

12 Jul 2021

Review status: this preprint is currently under review for the journal TC.

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

David W. Ashmore, Douglas W. F. Mair, Jonathan E. Higham, Stephen Brough, James M. Lea, and Isabel J. Nias David W. Ashmore et al.
  • School of Environmental Sciences, University of Liverpool, Liverpool, L69 7ZT, UK

Abstract. The increasing volume and spatio-temporal resolution of satellite-derived ice velocity data has 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. Mode 1 is interpreted as relating to the stress-reconfiguration at the glacier terminus, known to be an important control on the glacier’s dynamics. Modes 2 and 3 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 Modes 2 and 3 are explained by the drainage of nearby supraglacial melt ponds, as identified with a Google Earth Engine 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.

David W. Ashmore et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-184', Anonymous Referee #1, 06 Aug 2021
    • AC1: 'Reply on RC1', David Ashmore, 05 Oct 2021
  • RC2: 'Comment on tc-2021-184', Bryan Riel, 09 Aug 2021
    • AC2: 'Reply on RC2', David Ashmore, 05 Oct 2021

David W. Ashmore et al.

David W. Ashmore et al.

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Short summary
In this paper we explore the use of a transferrable and flexible statistical technique to try and untangle the multiple influences on marine-terminating glacier dynamics, as measured from space. We decompose a satellite-derived ice velocity record into ranked sets of static maps and temporal coefficients. We present evidence that the approach can identify velocity variability mainly driven by changes in terminus position, and velocity variation mainly driven by subglacial hydrological processes.