Preprints
https://doi.org/10.5194/tc-2022-193
https://doi.org/10.5194/tc-2022-193
 
14 Oct 2022
14 Oct 2022
Status: this preprint is currently under review for the journal TC.

Mapping snow depth over lake ice in Canada’s sub-arctic using ground-penetrating radar

Alicia F. Pouw1,2, Homa Kheyrollah Pour1,2, and Alex Maclean1,2 Alicia F. Pouw et al.
  • 1Remote Sensing of Environmental Change (ReSEC) Research Group, Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, N2L 3C5, Canada
  • 2Cold regions Research Centre, Wilfrid Laurier University, Waterloo, N2L 3C5, Canada

Abstract. Ice thickness across lake ice is influenced mainly by the presence of snow and its distribution, as it directly impacts the rate of lake ice growth. The spatial distribution of snow depth over lake ice varies and is driven by wind redistribution and snowpack metamorphism, creating variability in the lake ice thickness. The accuracy and consistency of snow depth measurement data on lake ice are challenging and sparse to obtain. However, high spatial resolution lake snow depth observations are necessary for the next generation of thermodynamic lake ice models. Such information is required to improve the knowledge and understanding of snow depth distribution over lake ice. This study maps snow depth distribution over lake ice using ground-penetrating radar (GPR) two-way travel-time (TWT) with ~9 cm spatial resolution along transects totalling ~44 km over four freshwater lakes in Canada’s sub-arctic. The accuracy of the snow depth retrieval is assessed using in situ snow depth observations (n =2,430). On average, the snow depth derived from GPR TWTs for the early winter season is estimated with a root mean square error (RMSE) of 1.58 cm and a mean bias error of -0.01 cm. For the late winter season on a deeper snowpack, the accuracy is estimated with RMSE of 2.86 cm and a mean bias error of 0.41 cm. The GPR-derived snow depths are interpolated to create 1 m spatial resolution snow depth maps. Overall, this study improved lake snow depth retrieval accuracy and introduced a fast and efficient method to obtain high spatial resolution snow depth information, which is essential for the lake ice modelling community.

Alicia F. Pouw et al.

Status: open (until 09 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-193', Anonymous Referee #1, 15 Oct 2022 reply
  • CC1: 'Review on “Mapping snow depth over lake ice in Canada’s sub-arctic using ground-penetrating radar” by Pouw et al.', Fei Xie, 20 Oct 2022 reply
  • RC2: 'Review of tc-2022-193', Anonymous Referee #2, 20 Oct 2022 reply

Alicia F. Pouw et al.

Alicia F. Pouw et al.

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Short summary
Collecting spatial lake snow depth data is essential for improving lake ice models. Lake ice growth is directly affected by snow on the lake. However, snow on lake ice is highly influenced by wind redistribution making it important but challenging to measure accurately in a fast and efficient way. This study introduces a method capable of capturing the lake snow depth spatially using ground-penetrating radar and introduces a fully automated method to capture shallow snow depths within 10 % error.