Heat wave contribution to 2022’s extreme glacier melt from automated real-time ice ablation readings
- 1Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
- 2Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
- 3Department of Geosciences, University of Fribourg, Fribourg, Switzerland
- 4Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich-Airport, Switzerland
- 5WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
- 1Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
- 2Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
- 3Department of Geosciences, University of Fribourg, Fribourg, Switzerland
- 4Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich-Airport, Switzerland
- 5WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Abstract. Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance at the daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of color-taped ablation stakes from camera images, and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019–2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e d−1, which is about half of the accuracy obtained from manual read outs. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analyzing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 days with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snow fall and a suite of summer heat waves led to unprecedented glacier mass loss. The Swiss-wide glacier storage change during the 25 days of heat waves in 2022 is estimated as 1.27±0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. Compared to the average course of the past decade, the 25 days of heat waves in 2022 caused a glacier mass loss that corresponds to 56 % of the overall mass loss experienced on average during summers 2010–2020, demonstrating the relevance of heat waves for seasonal melt.
Aaron Cremona et al.
Status: open (until 08 Feb 2023)
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RC1: 'Comment on tc-2022-247', Anonymous Referee #1, 08 Jan 2023
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The authors showcase the potential of near real time ablation monitoring in combination with long term mass balance data and modeling to assess the impacts of heat waves on Alpine glaciers. The manuscript explains an image analysis algorithm developed by the authors to automatically process images from their camera-based ablation measurement system. In a further step, the temporally highly resolved ablation data extracted from the images are used in a more general assessment of the extremely warm 2022 ablation season, which is then compared to a decadal regional average of glacier mass balance. This is an interesting and very timely contribution that shows the immense value of high resolution, real time glacier monitoring and data assimilation for impact assessments of extreme heat events. I have a few relatively minor comments/questions that I am sure can be addressed. I look forward to seeing this work published in TC. Please see the pdf for specific comments.
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RC2: 'Comment on tc-2022-247', Anonymous Referee #2, 11 Jan 2023
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Review to Cremona et al. (2022): "Heat wave contribution to 2022's extreme glacier melt from automated real-time ice ablation readings" submitted to The Cryosphere.
The authors present a study of a novel ablatometer measuring ablation at selected locations of a glacier in daily resolution. The method applies a computer-vision technique to automatically derive glacier surface elevation change from a series of time lapse images of ablation stakes marked with tapes at regular length intervals. In conjunction with a mass balance model the ablation at individual points is upscaled to glacier wide and even regional values of ablation anomalies in the past four years.
The study is well designed, thoughtful structured and easy to read. The method is novel and results may have impact on the glaciological and hydrological communities, on researchers focusing on observational techniques as well as on scientists interested in data sets at high temporal resolution for model validation. I'm looking forward seeing this manuscript published in the Cryosphere soon, as I have only minor comments to add.
Terminology: For the process that the stake melts out of the ice due to ablation and hence increasing its length of the "free end", the author use the term (vertical) displacement (L52 and others). This causes some confusion as displacement is usually connected to ice flow, which is not intended to be detected in the presented method and apart from tilting the ablation stake has no direct influence here. I suggest using the term surface elevation change (or something equivalent) instead.
Preselection of images: In the method section the authors describe that images are taken every 20 minutes. I wonder if the method analyses all images or if a preselection using which criteria was applied.
Threshold for extreme melt event (L185-196): In Tab. 1 the authors show that there is an altitude difference of almost 800 m between the stations used for deriving daily ablation values. This difference might largely explain the spread in the mass balance anomaly in Fig. 8. However, the altitudinal distribution of the stations is skewed to lower altitudes and thus taking the mean of the stations for defining the threshold should be reconsidered. I think the median is more significant than the mean, although the number of stations is low. Speaking of which, the number of observations presumably might change over the ablation period, as higher stations experience a longer snow cover. There should be a note how the number of observations affects the interpretation of the mass balance anomaly.
Specific comments:
L32-34: I do not agree with these two sentences. A number of studies assess reasonable short term mass balance variations from geodetic measurements (e.g., Klug et al., 2018; Zeller et al., 2022; Beraud et al., 2022; Vincent et al., 2021). Consider rephrasing or omitting.
L77: Please rephrase and consider the width of the tape as well.
Eq. 1: Please explain how you determine the stake inclination. Is it measured during the field visits or derived from the images or…?
L257: Consider depicting these periods also in Fig. 8.
L305-307: Please better explain how winter snow accumulation impacts melt anomalies between individual stations. Winter snow accumulation might have an influence on the length of the ablation season, but how does it alter the ablation anomaly during core summer, when winter snow has melted since long?
References:
Beraud, L., Cusicanqui, D., Rabatel, A., Brun, F., Vincent, C., and Six, D.: Glacier-wide seasonal and annual geodetic mass balances from Pléiades stereo images: application to the Glacier d’Argentière, French Alps, Journal of Glaciology, 1–13, https://doi.org/10.1017/jog.2022.79, 2022.
Klug, C., Bollmann, E., Galos, S. P., Nicholson, L., Prinz, R., Rieg, L., Sailer, R., Stötter, J., and Kaser, G.: Geodetic reanalysis of annual glaciological mass balances (2001-2011) of Hintereisferner, Austria, The Cryosphere, 12, 833–849, https://doi.org/10.5194/tc-12-833-2018, 2018.
Vincent, C., Cusicanqui, D., Jourdain, B., Laarman, O., Six, D., Gilbert, A., Walpersdorf, A., Rabatel, A., Piard, L., Gimbert, F., Gagliardini, O., Peyaud, V., Arnaud, L., Thibert, E., Brun, F., and Nanni, U.: Geodetic point surface mass balances: a new approach to determine point surface mass balances on glaciers from remote sensing measurements, The Cryosphere, 15, 1259–1276, https://doi.org/10.5194/tc-15-1259-2021, 2021.
Zeller, L., McGrath, D., Sass, L., O’Neel, S., McNeil, C., and Baker, E.: Beyond glacier-wide mass balances: parsing seasonal elevation change into spatially resolved patterns of accumulation and ablation at Wolverine Glacier, Alaska, Journal of Glaciology, 1–16, https://doi.org/10.1017/jog.2022.46, 2022.
Aaron Cremona et al.
Aaron Cremona et al.
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