Influence of glacier inventories on ice thickness estimates and future glacier change projections in the Tian Shan range, Central Asia

Fei Li, Fabien Maussion, Guangjian Wu*, Wenfeng Chen, Zhengliang Yu, Yaojun Li, Guohua Liu

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

7 Citations (Scopus)

Abstract

The Tian Shan mountain range, known as the water towers of Central Asia, plays a key role in local water supply, yet large uncertainties remain about the amount of water that is stored in its glaciers. In this study, we assess the impact of the boundary conditions on ice thickness estimates using two inversion models: a mass conservation (MC) model and a basal shear stress (BS) model. We compare the widely used Randolph Glacier Inventory version 6 with the updated Glacier Area Mapping for Discharge from the Asian Mountains glacier inventory, as well as two digital elevation models (SRTM DEM and Copernicus DEM). The results show that the ice volume (in ~2000 CE) in the Tian Shan range is 661.0 ± 163.5 km3 for the MC model and 552.8 ± 85.3 km3 for the BS model. There are strong regional differences due to inventory, especially for glaciers in China (17-25%). However, the effect of different DEM sources on ice volume estimation is limited. By the end of the 21st century, the projected mass loss differences between inventories are higher than between adjacent emission scenarios, illustrating the vital importance of high-quality inventories. These differences should be carefully considered during water resource planning.

Original languageEnglish
Pages (from-to)266-280
Number of pages15
JournalJournal of Glaciology
Volume69
Issue number274
Early online date15 Jul 2022
DOIs
Publication statusPublished - 15 Apr 2023

Bibliographical note

Funding Information:
This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences [grant No. XDA20060201], the National Natural Science Foundation of China [grant No. 41725001], the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [grant No. 2019QZKK0201] and the scholarship provided by the University of Chinese Academy of Sciences (UCAS). The simulations were run on the Climate Lab supercomputer, University of Bremen. We are grateful to the detailed comments and suggestions from Rijan Bhakta Kayastha and the other three anonymous reviewers, the Editorial Assistant, Lynsey Rowland, the Scientific Editor, Rakesh Bhambri, and the Chief Editor, Hester Jiskoot, which were of great help in improving the manuscript. We also thank the European space agency for the provision of COPDEM. Fei Li acknowledges Matthias Dusch and other OGGM contributors for their help during the development phase of the basal shear stress model. Fei Li is also thankful for the help and support from colleagues at the Department of Atmospheric and Cryospheric Sciences (ACINN), Innsbruck University, Austria and Miss Zhao, who helped him have a happy and fulfilling year even in the unusual year 2020.

Publisher Copyright:
Copyright © The Author(s), 2022. Published by Cambridge University Press.

Keywords

  • Glacier modelling
  • glacier volume
  • mountain glaciers

Fingerprint

Dive into the research topics of 'Influence of glacier inventories on ice thickness estimates and future glacier change projections in the Tian Shan range, Central Asia'. Together they form a unique fingerprint.

Cite this