Articles | Volume 11, issue 6
https://doi.org/10.5194/tc-11-2897-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-11-2897-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Dec 2017
Research article |
| 12 Dec 2017
Evaluation of different methods to model near-surface turbulent fluxes for a mountain glacier in the Cariboo Mountains, BC, Canada
Earth Ocean and Atmospheric Sciences Department (EOAS), The University of British Columbia, Vancouver, Canada
Brian Menounos
Natural Resources and Environmental Studies Institute and Geography
Program, University of Northern British Columbia, Prince George, Canada
Joseph Shea
International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal
Centre for Hydrology, University of Saskatchewan, Saskatoon, Canada
Noel Fitzpatrick
Earth Ocean and Atmospheric Sciences Department (EOAS), The University of British Columbia, Vancouver, Canada
Mekdes A. Tessema
Earth Ocean and Atmospheric Sciences Department (EOAS), The University of British Columbia, Vancouver, Canada
Stephen J. Déry
Natural Resources and Environmental Studies Institute and Environmental
Science and Engineering Program, University of Northern British Columbia, Prince George, Canada
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Short summary
Our overall goal is to improve the numerical modeling of glacier melt in order to better predict the future of glaciers in Western Canada and worldwide.
Most commonly used models rely on simplifications of processes that dictate melting at a glacier surface, in particular turbulent processes of heat exchange. We compared modeled against directly measured turbulent heat fluxes at a valley glacier in British Columbia, Canada, and found that more improvements are needed in all the tested models.
Our overall goal is to improve the numerical modeling of glacier melt in order to better predict...
