Preprints
https://doi.org/10.5194/egusphere-2024-2239
https://doi.org/10.5194/egusphere-2024-2239
12 Aug 2024
 | 12 Aug 2024

Brief Communication: Representation of heat conduction into the ice in marine ice shelf melt modeling

Jonathan Wiskandt and Nicolas Jourdain

Abstract. Basal melt of marine terminating glaciers is a key uncertainty in predicting the future climate and the evolution of the Antarctic and Greenland ice sheets. Regional ocean circulation models use parameterizations that depend on the available heat to parameterize basal melt. The heat budget at the ice–ocean interface includes turbulent heat flux from the ocean below, latent heat for phase transition, and heat conduction into the ice. Here we review the estimation of heat conduction into the ice, which has been treated in various ways in modelling studies so far. We show that the formulation of Holland and Jenkins (1999) best captures the variety of temperature profiles measured in boreholes. Accounting for heat conduction into the ice reduces melt rates by up to 28 %.

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Jonathan Wiskandt and Nicolas Jourdain

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2239', Anonymous Referee #1, 10 Sep 2024
    • AC1: 'Reply on RC1', Jonathan Wiskandt, 16 Sep 2024
  • RC2: 'Comment on egusphere-2024-2239', Anonymous Referee #2, 12 Sep 2024
  • RC3: 'Comment on egusphere-2024-2239', Anonymous Referee #3, 16 Sep 2024
Jonathan Wiskandt and Nicolas Jourdain
Jonathan Wiskandt and Nicolas Jourdain

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Short summary
In ocean models, submarine melt of ice shelves is parameterized based on the heat budget at the interface. The heat budget includes the ocean heat transport, the heat conducted into the ice and the heat available for melting. Here we compare three different approaches to estimate the heat conduction. We show that the most accurate approximation is not the one used most, despite it overestimating the melt by up to 25 % and not being computationally more expensive.