Preprints
https://doi.org/10.5194/tc-2020-67
https://doi.org/10.5194/tc-2020-67
07 Apr 2020
 | 07 Apr 2020
Status: this preprint has been withdrawn by the authors.

Effects of surface roughness and light-absorbing impurities on glacier surface albedo, August-one ice cap, Qilian Mountains, China

Junfeng Liu, Rensheng Chen, Yongjian Ding, Chuntan Han, Yong Yang, Zhangwen Liu, Xiqiang Wang, Shuhai Guo, Yaoxuan Song, and Wenwu Qing

Abstract. Surface albedo is the main influence on surface melt for Qilian mountain glaciers. Fluctuations in surface albedo are due primarily to variations in micro scale surface roughness (ξ) and light-absorbing impurities (LAIs) in this region. However, combined ξ and LAIs effects over glacier surface albedo are rarely studied and surface roughness rarely considered in the albedo parameterization methods in this region. The present study was conducted in tandem with an intensive photogrammetric survey of glacier surface roughness, LAIs samples and albedo observations along the main flow-line of August-one ice cap during the 2018 melt season. Automatic photogrammetry of surface roughness and automatic observation of glacier surface albedo was conducted at middle of the ice cap in 2018. Detailed analysis indicates a negative power function and positive linear relationship exist between ξ and albedo for snow and ice surface, respectively. ξ could explain 68% of snow surface albedo and 38 % of ice surface albedo variation in melt season. Effective LAIs concentration (Cξ) calculated by consider ξ effect over LAIs deposition account for more than 63 % of albedo variation at ice surface. Using either ξ or Cξ to estimate ice surface albedo would be a great improvement over some current parameterization methods, such as assuming a constant mean ice surface albedo. A finer resolution of above 50 mm and above 100 mm is recommended for ice and snow ξ calculations, which explain more albedo variation than coarse resolutions below it. With advances in topographic surveys to improve the resolution, extent and availability of topographic datasets and surface roughness, appropriate parameterizations of albedo based on ξ have exciting potential to be applied over large scale snow cover and glacier.

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Junfeng Liu, Rensheng Chen, Yongjian Ding, Chuntan Han, Yong Yang, Zhangwen Liu, Xiqiang Wang, Shuhai Guo, Yaoxuan Song, and Wenwu Qing

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Junfeng Liu, Rensheng Chen, Yongjian Ding, Chuntan Han, Yong Yang, Zhangwen Liu, Xiqiang Wang, Shuhai Guo, Yaoxuan Song, and Wenwu Qing
Junfeng Liu, Rensheng Chen, Yongjian Ding, Chuntan Han, Yong Yang, Zhangwen Liu, Xiqiang Wang, Shuhai Guo, Yaoxuan Song, and Wenwu Qing

Viewed

Total article views: 1,267 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
770 413 84 1,267 80 83
  • HTML: 770
  • PDF: 413
  • XML: 84
  • Total: 1,267
  • BibTeX: 80
  • EndNote: 83
Views and downloads (calculated since 07 Apr 2020)
Cumulative views and downloads (calculated since 07 Apr 2020)

Viewed (geographical distribution)

Total article views: 1,160 (including HTML, PDF, and XML) Thereof 1,155 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Nov 2024
Download

This preprint has been withdrawn.

Short summary
we try to investigate the spatial and temporal variability of albedo, micro scale surface roughness, and LAIs, with the objective to better understanding and simulating surface albedo variability over snow and dirty ice surface at the August-one ice cap in Qilian Mountain. Snow and ice surface albedo parameterization methods are established based on either surface roughness or both surface roughness and LAIs.