Articles | Volume 17, issue 1
https://doi.org/10.5194/tc-17-211-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-211-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jan 2023
Research article |
| 17 Jan 2023
| 17 Jan 2023
Estimating degree-day factors of snow based on energy flux components
Muhammad Fraz Ismail
CORRESPONDING AUTHOR
TUM School of Engineering and Design, Technical University of Munich, Munich, Germany
Department of Civil Engineering, Koblenz University of Applied
Sciences, Koblenz, Germany
Wolfgang Bogacki
Department of Civil Engineering, Koblenz University of Applied
Sciences, Koblenz, Germany
Markus Disse
TUM School of Engineering and Design, Technical University of Munich, Munich, Germany
Michael Schäfer
Department of Civil Engineering, Koblenz University of Applied
Sciences, Koblenz, Germany
Faculty of Agriculture, Yamagata University, Tsuruoka, Japan
Lothar Kirschbauer
Department of Civil Engineering, Koblenz University of Applied
Sciences, Koblenz, Germany
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Cited
14 citations as recorded by crossref.
- Spatiotemporal mass-balance variability of Jostedalsbreen Ice Cap, Norway, revealed by a temperature-index model using Bayesian inference K. Sjursen et al. 10.1017/aog.2024.41
- Glacier projections sensitivity to temperature-index model choices and calibration strategies L. Schuster et al. 10.1017/aog.2023.57
- A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks M. Guidicelli et al. 10.1016/j.hydroa.2024.100190
- The effect of a bench on leakage through a cover: A field and numerical assessment Y. Fan et al. 10.1016/j.geotexmem.2025.02.005
- Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia W. Ren et al. 10.3390/rs16060956
- A minimal machine-learning glacier mass balance model M. van der Meer et al. 10.5194/tc-19-805-2025
- Measurement and estimation of temporal variations of roof snow load on semi-full-scale building model Y. Tominaga et al. 10.1016/j.coldregions.2025.104445
- A study on the runoff prediction mechanism of “water-soil-heat” in cold alpine regions with complex spatial distribution Q. Yu et al. 10.1016/j.scitotenv.2024.178059
- Impact of Climate Change on Snowmelt Erosion Risk J. Podhrázská et al. 10.3390/land14010055
- Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022 Y. Zheng et al. 10.5194/tc-17-3667-2023
- On the Dependence of the ice Formation in the Lake Ladoga on the Air Temperature S. Karetnikov 10.31857/S2076673423020096
- Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments V. Premier et al. 10.5194/tc-17-2387-2023
- Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques R. Anilkumar et al. 10.5194/tc-17-2811-2023
- Influence of Slope Aspect and Vegetation on the Soil Moisture Response to Snowmelt in the German Alps M. Schaefer et al. 10.3390/hydrology11070101
13 citations as recorded by crossref.
- Spatiotemporal mass-balance variability of Jostedalsbreen Ice Cap, Norway, revealed by a temperature-index model using Bayesian inference K. Sjursen et al. 10.1017/aog.2024.41
- Glacier projections sensitivity to temperature-index model choices and calibration strategies L. Schuster et al. 10.1017/aog.2023.57
- A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks M. Guidicelli et al. 10.1016/j.hydroa.2024.100190
- The effect of a bench on leakage through a cover: A field and numerical assessment Y. Fan et al. 10.1016/j.geotexmem.2025.02.005
- Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia W. Ren et al. 10.3390/rs16060956
- A minimal machine-learning glacier mass balance model M. van der Meer et al. 10.5194/tc-19-805-2025
- Measurement and estimation of temporal variations of roof snow load on semi-full-scale building model Y. Tominaga et al. 10.1016/j.coldregions.2025.104445
- A study on the runoff prediction mechanism of “water-soil-heat” in cold alpine regions with complex spatial distribution Q. Yu et al. 10.1016/j.scitotenv.2024.178059
- Impact of Climate Change on Snowmelt Erosion Risk J. Podhrázská et al. 10.3390/land14010055
- Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022 Y. Zheng et al. 10.5194/tc-17-3667-2023
- On the Dependence of the ice Formation in the Lake Ladoga on the Air Temperature S. Karetnikov 10.31857/S2076673423020096
- Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments V. Premier et al. 10.5194/tc-17-2387-2023
- Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques R. Anilkumar et al. 10.5194/tc-17-2811-2023
1 citations as recorded by crossref.
Latest update: 28 Mar 2025
Short summary
Fresh water from mountainous catchments in the form of snowmelt and ice melt is of critical importance especially in the summer season for people living in these regions. In general, limited data availability is the core concern while modelling the snow and ice melt components from these mountainous catchments. This research will be helpful in selecting realistic parameter values (i.e. degree-day factor) while calibrating the temperature-index models for data-scarce regions.
Fresh water from mountainous catchments in the form of snowmelt and ice melt is of critical...
