Articles | Volume 15, issue 11
https://doi.org/10.5194/tc-15-5017-2021
© Author(s) 2021. 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-15-5017-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Nov 2021
Research article |
| 01 Nov 2021
| 01 Nov 2021
Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter
Johannes Marian Landmann
CORRESPONDING AUTHOR
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Hans Rudolf Künsch
Seminar for Statistics, ETH Zurich, Zurich, Switzerland
Matthias Huss
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Christophe Ogier
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Markus Kalisch
Seminar for Statistics, ETH Zurich, Zurich, Switzerland
Daniel Farinotti
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
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Cited
12 citations as recorded by crossref.
- Automated ablation stakes to constrain temperature-index melt models A. Wickert et al. 10.1017/aog.2024.21
- GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence A. Wells et al. 10.1017/jog.2024.54
- Rescue and homogenization of 140 years of glacier mass balance data in Switzerland L. Geibel et al. 10.5194/essd-14-3293-2022
- DAS to discharge: using distributed acoustic sensing (DAS) to infer glacier runoff J. Manos et al. 10.1017/jog.2024.46
- Bayesian parameter estimation in glacier mass-balance modelling using observations with distinct temporal resolutions and uncertainties K. Sjursen et al. 10.1017/jog.2023.62
- Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022 A. Voordendag et al. 10.5194/tc-17-3661-2023
- Characterising englacial R-channels using artificial moulins A. Pohle et al. 10.1017/jog.2022.4
- Constraining sub-seasonal glacier mass balance in the Swiss Alps using Sentinel-2-derived snow-cover observations A. Cremona et al. 10.1017/jog.2025.1
- Machine Learning Approaches to Automatically Detect Glacier Snow Lines on Multi-Spectral Satellite Images C. Prieur et al. 10.3390/rs14163868
- European heat waves 2022: contribution to extreme glacier melt in Switzerland inferred from automated ablation readings A. Cremona et al. 10.5194/tc-17-1895-2023
- A scenario–neutral approach to climate change in glacier mass balance modeling L. van der Laan et al. 10.1017/aog.2024.22
- Hydrological response to warm and dry weather: do glaciers compensate? M. Van Tiel et al. 10.5194/hess-25-3245-2021
11 citations as recorded by crossref.
- Automated ablation stakes to constrain temperature-index melt models A. Wickert et al. 10.1017/aog.2024.21
- GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence A. Wells et al. 10.1017/jog.2024.54
- Rescue and homogenization of 140 years of glacier mass balance data in Switzerland L. Geibel et al. 10.5194/essd-14-3293-2022
- DAS to discharge: using distributed acoustic sensing (DAS) to infer glacier runoff J. Manos et al. 10.1017/jog.2024.46
- Bayesian parameter estimation in glacier mass-balance modelling using observations with distinct temporal resolutions and uncertainties K. Sjursen et al. 10.1017/jog.2023.62
- Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022 A. Voordendag et al. 10.5194/tc-17-3661-2023
- Characterising englacial R-channels using artificial moulins A. Pohle et al. 10.1017/jog.2022.4
- Constraining sub-seasonal glacier mass balance in the Swiss Alps using Sentinel-2-derived snow-cover observations A. Cremona et al. 10.1017/jog.2025.1
- Machine Learning Approaches to Automatically Detect Glacier Snow Lines on Multi-Spectral Satellite Images C. Prieur et al. 10.3390/rs14163868
- European heat waves 2022: contribution to extreme glacier melt in Switzerland inferred from automated ablation readings A. Cremona et al. 10.5194/tc-17-1895-2023
- A scenario–neutral approach to climate change in glacier mass balance modeling L. van der Laan et al. 10.1017/aog.2024.22
1 citations as recorded by crossref.
Latest update: 29 May 2025
Short summary
In this study, we (1) acquire real-time information on point glacier mass balance with autonomous real-time cameras and (2) assimilate these observations into a mass balance model ensemble driven by meteorological input. For doing so, we use a customized particle filter that we designed for the specific purposes of our study. We find melt rates of up to 0.12 m water equivalent per day and show that our assimilation method has a higher performance than reference mass balance models.
In this study, we (1) acquire real-time information on point glacier mass balance with...
