Distributed glacier mass-balance modelling as an important component of modern multi-level glacier monitoring
Modern concepts of worldwide glacier monitoring include numerical models for (1) interconnecting the different levels of observations (local mass balance, representative length change, glacier inventories for global coverage) and (2) extrapolations in space (coupling with climate models) and time (b...
| Published in: | Annals of Glaciology |
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| Main Authors: | , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
International Glaciological Society
2006
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| Subjects: | |
| Online Access: | https://www.zora.uzh.ch/id/eprint/62170/ https://www.zora.uzh.ch/62170 https://doi.org/10.3189/172756406781812285 |
| Summary: | Modern concepts of worldwide glacier monitoring include numerical models for (1) interconnecting the different levels of observations (local mass balance, representative length change, glacier inventories for global coverage) and (2) extrapolations in space (coupling with climate models) and time (backward and forward). In this context, one important new tool is distributed mass-balance modelling in complex mountain topography. This approach builds on simplified energy-balance models and can be applied for investigating the spatio-temporal representativity of the few mass-balance measurements, for estimating balance values at the tongue of unmeasured glaciers in order to derive long-term average balance values from a great number of glaciers with known length change, and for assessing special effects such as the influence of Sahara dust falls on the albedo and mass balance or autocorrelation effects due to surface darkening of glaciers with strongly negative balances. Experience from first model runs in the Swiss Alps and from applications to the extreme conditions in summer 2003 provides evidence about the usefulness of this approach for glacier monitoring and analysis of glacier changes in high-mountain regions. The main difficulties concern the spatial variability of the input parameters (e.g. precipitation, snow cover and surface albedo) and the uncertainties in the parameterizations of the components of the energy balance. Field measurements remain essential to tie the models to real ground conditions. |
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