Brief communication: The Glacier Loss Day as indicator for extreme glacier melt in 2022
Abstract. In the hydrological year 2021/22 Alpine glaciers showed unprecedented mass loss. On Hintereisferner (Ötztal Alps, Austria), the glacier-wide mass balance was −3319 kg m−2. Near-daily observations of surface elevation changes from a permanent terrestrial laser scanning setup allowed determining the day when the mass balance of Hintereisferner started to become negative. This Glacier Loss Day (GLD) was already reached on 24 June in 2022 and gave way to a long ice ablation period. In 2021/22, this and the high cumulative positive degree days explain the record mass loss. By comparing the GLDs of 2019/20–2021/22, we found a gross yet expressive indicator of the glacier’s imbalance with the persistently warming climate.
Annelies Voordendag et al.
Status: final response (author comments only)
RC1: 'Comment on tc-2023-49', Anonymous Referee #1, 07 Apr 2023
- AC1: 'Reply on RC1', Annelies Voordendag, 23 May 2023
- CC1: 'Comment on tc-2023-49', Aaron Cremona, 20 Apr 2023
RC2: 'Comment on tc-2023-49', Aaron Cremona, 25 Apr 2023
- AC2: 'Reply on RC2', Annelies Voordendag, 23 May 2023
Annelies Voordendag et al.
Annelies Voordendag et al.
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Review comments on :
The Glacier Loss Day as indicator for extreme glacier melt in 2022
by A. Voordendag, R. Prinz, L. Schuster, and G. Kaser
submitted to publication in The Cryosphere journal as a Brief Communication.
The paper employs near-daily observations of surface elevation changes from a permanent terrestrial laser scanning on Hintereisferner (Ötztal Alps, Austria) to retrieve the day when the glacier-wide mass balance becomes negative. Applying the concept during the record-breaking mass loss that occurred in 2022, this Glacier Loss Day (GLD) was reached in late June which gave way to a long ice ablation period. From a comparison with the two previous years, the authors conclude that the GLD can be considered as predictive proxy of the glacier’s imbalance for the current hydrological year.
The paper is concise, almost quite clear and easy to read. The paper would be a bit more complete and understandable were it also to detail how the glacier-wide balance is obtained form observations that only cover a limited surface area (how the spatial interpolation is processed) and how the observed thickness change is converted into a mass change (how vertical velocities are accounted for).
A minor point would be to explain what the concept of Glacier Loss Day is primarily (or could potentially be) dedicated to: public communication, current year water resources estimations, glacial hazards… and the degree of approximations and uncertainties accepted for that purpose.
There follow several detailed questions, comments, and suggestions.
Figure 1. Here you fit annual balances to a Gaussian distribution which is the distribution that fits averages (standard limit theorem). However, in search of extreme mass balance the rareness should be better analysed with extreme values distribution (GEV=Generalized Extreme Value distribution) instead of Gaussian. This should not be too difficult with the very long and highly valuable record of mass balance at HEF.
In connexion with the above comment is title of the paper. What was specific in 2022? Extreme melt? Extreme annual balance? Perhaps both. And does extreme mean that 2022 just ranks first? Or does extreme refer to a calculated probability of exceedance?
Line 17. Wouldn't an objective of the method be to also estimate for the current year the exceedance probability of the mass loss relative to a given threshold and estimate the rareness of the current mass balance time-plot? I would suggest to use a standard time-plot of mass balance (70-year or 10 last-year standard) reconstructed form the very long series of mass balance at HEF and from a simple degree day model. Here, your analysis is limited by a comparison with the two previous years which is very frustrating knowing the long series of observations at HEF.
Line 25. Not clear what “analogous” means.
Do you refer here to the density conversion? This assumption is not just a density conversion but strongly depends whether the volume change is measured on the overall glacier surface or not.
Do you set that assimilating a local thickness change to a wide mass balance is sufficient for the GLD approach? This should be established using the three years of observation (or on synthetic data) with an error assessment to conclude.
Lines 20-25. Here you point two majors issues:
In the section 2 (Data&Method), you may explain in more details how you solve these 2 points.
Line 50. There is a large surface which is not observed when you cross the different surveys. How to you get a glacier-wide mass change? Do you use a flow model to account for the glacier dynamics? As far as I understand the process, you need to first estimate the surface mass balance in the area where you scan with a flow model to correct from vertical velocity, and then extrapolate the mass balance to the overall glacier surface from the spatial dependence of the mass balance (altitudinal gradient or something more complex).
Figure 2. It is not clear to me if it is the glacier-wide thickness change in which case it would more be convenient to plot the glacier-wide mass balance applying a density conversion. I would suggest to plot in different slots the local thickness change, the local mass change, and then the glacier-wide change compared to a standard plot (70-year or 10 last-year standard).