Preprints
https://doi.org/10.5194/egusphere-2024-122
https://doi.org/10.5194/egusphere-2024-122
05 Feb 2024
 | 05 Feb 2024
Status: this preprint is open for discussion.

An improved firn densification model by integrating the Bucket scheme and Darcy’s law over the Greenland Ice Sheet

Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo

Abstract. Modelling firn densification is conducive to enhancing the accuracy of monitoring glacier mass changes from satellite altimetry and extracting climate records from ice cores. As snowmelt is increasing in a warming climate on the Greenland Ice Sheet (GrIS), quantifying the role of liquid water within the firn layer becomes critical for simulating firn properties. Nevertheless, previously published firn densification models do not accurarely capture the extensive density fluctuations caused by liquid water refreezing in observations. In this study, an improved firn densification model is developed by integrating the Bucket scheme and Darcy’s law to assess the capillary retention, refreezing, and runoff of liquid water within the firn layer. Moreover, the improved model is employed for two study sites, KAN_U and Dye-2, over the GrIS to evaluate its performance. At the KAN_U site, characterized by high snowfall and snowmelt rates, the model captures high-density peaks (~917 kg · m-3) caused by the refreezing of liquid water, which corresponds to the formation of ice lenses or ice layers. At Dye-2 with comparatively limited liquid water, the model also captures the features of high-density layers resulting from refreezing. In general, the modelled firn depth-density profiles at the two study sites agree well with the in situ measurements obtained from 12 firn cores drilled between 2012 and 2019. For the regions with limited liquid water, low-density peaks are probably overestimated due to excess refreezing or limited knowledge of ice lenses or ice layers. Future work is expected to enhance the understanding and further improve numerical simulation of the mechanisms involved in firn densification, and subsequently integrate data-driven and physical mechanisms into firn densification modelling.

Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo

Status: open (until 20 Mar 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo

Viewed

Total article views: 189 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
138 46 5 189 3 2
  • HTML: 138
  • PDF: 46
  • XML: 5
  • Total: 189
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 05 Feb 2024)
Cumulative views and downloads (calculated since 05 Feb 2024)

Viewed (geographical distribution)

Total article views: 181 (including HTML, PDF, and XML) Thereof 181 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 04 Mar 2024
Download
Short summary
In this study, an improved firn densification model is developed by integrating the Bucket scheme and Darcy’s law to assess the capillary retention, refreezing, and runoff of liquid water within the firn layer. This model captures high-density peaks (~917 kg · m-3) or the features of high-density layers caused by the refreezing of liquid water. In general, the modelled firn depth-density profiles at KAN_U and Dye-2 agree well with the in situ measurements.