The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Glacier Mass Change in High Mountain Asia Through 2100 Using the Open-Source Python Glacier Evolution Model (PyGEM)
Open accessAbstract
Glaciers in High Mountain Asia are an important freshwater resource for large populations living downstream who rely on runoff for hydropower, irrigation, and municipal use. Projections of glacier mass change and runoff therefore have important socio-economic impacts. In this study, we use a new dataset of geodetic mass balance observations of almost all glaciers in the region to calibrate the Python Glacier Evolution Model (PyGEM) using Bayesian inference. The new dataset enables the model to capture spatial variations in mass balance and the Bayesian inference enables the uncertainty associated with the model parameters to be quantified. Validation with historical mass balance observations shows the model performs well and the uncertainty is well captured. Projections of glacier mass change for 22 General Circulation Models (GCMs) and four Representative Concentration Pathways (RCPs) estimate that by the end of the century glaciers in High Mountain Asia will lose between 3311% (RCP2.6) and 689% (RCP8.5) of their total mass relative to 2015. Considerable spatial and temporal variability exists between regions due to the climate forcing and glacier characteristics (hypsometry, ice thickness, elevation range). Projections of annual glacier runoff reveal most monsoon-fed river basins (Ganges, Brahmaputra) will hit a maximum (peak water) prior to 2050, while the Indus and other westerlies-fed river basins will likely hit peak water after 2050 due to significant contributions from excess glacier meltwater. Monsoon-fed watersheds are projected to experience large reductions in end-of-summer glacier runoff. Uncertainties in projections at regional scales are dominated by the uncertainty associated with the climate forcing, while at the individual glacier level, uncertainties associated with model parameters can be significant.
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Cites
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Self-citationA Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009
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Self-citationConsistent increase in High Asia's runoff due to increasing glacier melt and precipitation
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Cited by
Global glacier change in the 21st century: Every increase in temperature matters
Rounce, D. R., Hock, R., Maussion, F., Hugonnet, R., Kochtitzky, W., Huss, M., Berthier, E., Brinkerhoff, D., Compagno, L., Copland, L., et al. (2023) · Science · doi:10.1126/science.abo1324 · Cited by 676
Self-citationA Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance
Shean, D. E., Bhushan, S., Montesano, P., Rounce, D. R., Arendt, A., & Osmanoglu, B. (2020) · Frontiers in Earth Science · doi:10.3389/feart.2019.00363 · Cited by 665
Self-citationGlacial change and hydrological implications in the Himalaya and Karakoram
Nie, Y., Pritchard, H. D., Liu, Q., Hennig, T., Wang, W., Wang, X., Liu, S., Nepal, S., Samyn, D., Hewitt, K., et al. (2021) · Nature Reviews Earth & Environment · doi:10.1038/s43017-020-00124-w · Cited by 523
Bhattacharya, A., Bolch, T., Mukherjee, K., King, O., Menounos, B., Kapitsa, V., Neckel, N., Yang, W., & Yao, T. (2021) · Nature Communications · doi:10.1038/s41467-021-24180-y · Cited by 369
Climate change decisive for Asia’s snow meltwater supply
Kraaijenbrink, P. D. A., Stigter, E. E., Yao, T., & Immerzeel, W. W. (2021) · Nature Climate Change · doi:10.1038/s41558-021-01074-x · Cited by 355
Metadata
- Authors
- Rounce, D. R., Hock, R., & Shean, D. E.
- Venue
- Frontiers in Earth Science
- Publisher
- Frontiers Media SA
- Published
- 2020-01-23
- Volume
- 7
- ISSN
- 2296-6463 (ISSN-L)
- OpenAlex
- W3001777192
- Cited by
- 316
- References
- 38
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- gold
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- Rounce, D. R., Hock, R., & Shean, D. E. (2020). Glacier Mass Change in High Mountain Asia Through 2100 Using the Open-Source Python Glacier Evolution Model (PyGEM). Frontiers in Earth Science. https://doi.org/10.3389/feart.2019.00331
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