Preprints
https://doi.org/10.5194/tc-2022-138
https://doi.org/10.5194/tc-2022-138
14 Sep 2022
 | 14 Sep 2022
Status: a revised version of this preprint was accepted for the journal TC and is expected to appear here in due course.

Greenland and Canadian Arctic ice temperature profiles

Anja Løkkegaard, Kenneth Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel Doyle, Henrik Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat Abbas Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Robert S. Fausto, and William T. Colgan

Abstract. Here, we present a compilation of 85 ice temperature profiles from 79 boreholes from the Greenland Ice Sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Only 25 profiles (32 %) were previously available in open-access data repositories. The remaining 54 profiles (68 %) are being made digitally available here for the first time. These newly available profiles, which are associated with pre-2010 boreholes, have been submitted by community members or digitized from published graphics and/or data tables. All 85 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales, and are accompanied by extensive metadata. This metadata includes a transparent description of data provenance. The ice temperature profiles span 70 years, with the earliest profile being from 1950 at Camp VI, West Greenland. To highlight the value of this database in evaluating ice flow simulations, we compare the ice temperature profiles from the Greenland Ice Sheet with an ice flow simulation by the Parallel Ice Sheet Model (PISM). We find a cold bias in modeled near-surface ice temperatures within the ablation area, a warm bias in modeled basal ice temperatures at inland cold-bedded sites, and an apparent underestimation of deformational heating in high-strain settings. These biases provide process-level insight on simulated ice temperatures.

Anja Løkkegaard et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-138', Anonymous Referee #1, 15 Oct 2022
    • AC1: 'Reply on RC1', Anja Løkkegaard, 13 Dec 2022
  • RC2: 'Comment on tc-2022-138', Brice Van Liefferinge, 20 Oct 2022
    • AC2: 'Reply on RC2', Anja Løkkegaard, 13 Dec 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-138', Anonymous Referee #1, 15 Oct 2022
    • AC1: 'Reply on RC1', Anja Løkkegaard, 13 Dec 2022
  • RC2: 'Comment on tc-2022-138', Brice Van Liefferinge, 20 Oct 2022
    • AC2: 'Reply on RC2', Anja Løkkegaard, 13 Dec 2022

Anja Løkkegaard et al.

Data sets

Greenland deep ice temperature database, github Kenneth Mankoff https://github.com/GEUS-Glaciology-and-Climate/greenland_ice_borehole_temperature_profiles

Greenland deep ice temperature database, Dataverse Kenneth Mankoff, Anja Løkkegaard, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel Doyle, Henrik Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat Abbas Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Robert S. Fausto, and William T. Colgan https://dataverse.geus.dk/dataset.xhtml?persistentId=doi:10.22008/FK2/3BVF9V

Anja Løkkegaard et al.

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Short summary
This study presents a database compiling 85 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow is highly sensitive to ice temperature. To highlight the value of the data base in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Re-occurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.