Preprints
https://doi.org/10.5194/tc-2021-70
https://doi.org/10.5194/tc-2021-70

  08 Apr 2021

08 Apr 2021

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

Brief communication: Evaluation of multiple empirical, density-dependent snow conductivity relationships at East Antarctica

Minghu Ding1, Tong Zhang1,2, Diyi Yang1, Ian Allison3, Tingfeng Dou4, and Cunde Xiao2 Minghu Ding et al.
  • 1State Key Laboratory of Severe Weather and Institute of Tibetan Plateau & Polar Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 2State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
  • 3Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Tasmania, Australia
  • 4College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract. Nine density-dependent empirical thermal conductivity relationships for firn were compared against data from three Automatic Weather Stations at climatically-different East Antarctica sites (Dome A, Eagle and LGB69). The empirical relationships were validated using a vertical, one-dimensional thermal diffusion model and a phase-change based firn diffusivity estimation method. The best relationships for these East Antarctica sites were identified by comparing the modeled and observed firn temperature at the depth of 1 m and 3 m, and from the mean heat conductivities over two depth intervals (1–3 m and 3–10 m). Among the nine relationships, that proposed by Calonne et al. (2011) appears to have the best performance. This study provides useful reference for firn thermal conductivity parameterizations in land modeling or snow-air interaction studies on the Antarctica Ice Sheet.

Minghu Ding et al.

Status: open (until 03 Jun 2021)

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Minghu Ding et al.

Minghu Ding et al.

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Short summary
The snow heat conductivity is essential for energy balance between atmosphere and firn but still not clear in Antarctica. Here we used 3 AWS data located in different types climate, and evaluated 9 schemes which is used to calculated the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity-density relationship is optimal at all sites and the performance of each varies with depth.