the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Feb 2026
In-situ tracer percolation experiments to constrain the influence of near-surface melting on Svalbard snow signatures
Abstract. The Arctic is at the forefront of global warming. More frequent and intense rain-on-snow events during winter are altering the annual snowpack with its environmental proxy records, so that Svalbard glaciers are not only rapidly losing mass but are endangered as climate archives. In this study, we aim to visualise and better constrain the influence of near-surface melt caused by small-scale rain-on-snow events on stable water isotope signatures in seasonal snow in the vicinity of Ny-Ålesund in Svalbard. To this end, we first introduce a simple in-situ melt tracer experiment approach and subsequently present new insights into structural imprint and stable water isotope alteration gained during field experiments near Ny-Ålesund in March 2023. We document diverse features resulting from meltwater infiltration, including unprecedented observations of internal layering within melt lenses, and discuss the importance of snow temperature and stratigraphy for percolation behaviour, ranging from preferential to matrix flow in the non-ripe snowpack. Comparisons of δ18O and δ2H signatures before and after each experiment further reveal that percolation-induced stable water isotope changes are localized, i.e. confined to melt structures, so that sub-annual stable water isotope information can be retrieved from unaffected profile parts where annual accumulation is sufficient.
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Status: open (until 15 Apr 2026)
- RC1: 'Comment on egusphere-2026-399', Anonymous Referee #1, 16 Mar 2026 reply
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RC2: 'Comment on egusphere-2026-399', Anonymous Referee #2, 20 Mar 2026
reply
This study has addressed the role of snowpack stratigraphy on the percolation of water through the snowpack, with the specific goal of quantifying the impact of rain-on-snow events on stable water isotope signatures which are highly important as climate proxy records in ice cores. The study carries out a well-planned field campaign to simulate the impact of ROS close to Ny Ålesund in Svalbard, with results that I consider to be significant outside of the objectives of this study too. Specifically, while the experiments simulate a minor ROS event, the results reveal that variables related to the snowpack history plays an important role in determining ROS impacts on the cryosphere – and thus ecosystems that are dependent on snow and snowmelt. Furthermore, I believe that the results also highlight why some ROS events can be more impactful than others despite similar meteorological characteristics. It would be very interesting to see results from a follow-up experiment simulating a longer and/or more intense ROS event which percolates deeper into the snowpack. I consider the manuscript to be well-written and worthy of publishing with only minor changes.
Minor comments
Line 77-78: “Consequently, the seasonal snowpack covering 60–100% of Svalbard”. Typically seasonal snow often refers to the non-glaciated part of Svalbard, which is ca. 40% since glaciers account for just under 60% of the total area. Perhaps consider amending this sentence to specify what you mean by seasonal snow.
L255-257: “above-freezing temperatures were reached on at least three occasions (5th – 6th, 14th – 15th, and 25th – 26th February 2023) and two day-long warm spells caused near-melting conditions (21st –24th February and 1st – 2nd March 2023).”
Possibly I have misunderstood here, but were the two warm spells from 21-24th February and 1-2 March different to the occasions with “above-freezing” temperatures? Or could you just say that there were five occasions with warm/near-melting conditions?
L395 onwards. The discussion of the MLRA results is interesting, in particular how difference in grain size at stratigraphic boundaries can constrain the vertical flow but it was not obvious to me whether there were cases used in the analysis where the tracer had percolated deep enough to reach ice layers from previous ROS events/warm spells, and if so how did it interact with the ice layers eg. Does the water pool and refreeze at existing ice layers (thereby thickening them) or do they melt out the ice layers?? I think it was already mentioned elsewhere in the literature that it can be challenging to disentangle the signatures of multiple ROS events in the snowpack and I think this is an important result too since the number of ice layers in the snowpack will not necessarily correlate with the number of ROS events.
Citation: https://doi.org/10.5194/egusphere-2026-399-RC2
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- 1
This was a worthwhile project, suitable for publication in TC. I have a general comment, a major comment, and several minor comments.
General comment: Many numbers are given to higher precision than warranted. The precision of the average should not exceed the value of the standard deviation. For example, on line 246, change “69.5±8.8” to “70±9”. This change also makes the result easier to read. As another example, on line 295, change “-14.6±7.6” to “-15±8”.
Major comment: I am skeptical of the snow surface temperatures (SST) reported in Figure 5. The reported SST is often nearly 10 K colder than the air temperature, and is never warmer than the air temperature, although the temperature at 10-cm depth (measured by a different method) exceeds the air temperature until 30th March. How was the SST measured (maybe by IR emission)? Has the SST method been verified by in-situ thermistor measurements? [This verification should be done at night, so that solar heating of the thermistor does not cause a bias.]
Minor comments:
Title (and elsewhere). “Constrain” is a synonym of “inhibit”. So to “constrain” the influence of near-surface melting suggests that you are looking for ways to reduce its influence. I suggest changing “constrain” to “quantify” everywhere it appears. Or say “determine”, as you do on line 394.
Throughout: I suggest writing dD instead of d2H. dD is commonly used, and d2 looks like delta-squared.
Line 27. “increased by 4-5 C”. Since what year?
Line 36. Explain why melting generally leads to 18O enrichment.
Line 78. “snowpack covering 60-100% of Svalbard”. Is this a seasonal variation, i.e. 100% in winter and 60% in summer?
Figure 1. Point out that all these sites are near sea-level, none on the mountain or on a glacier.
Lines 171-172. “maximum percolation depth . . . and average percolation depth”. Table E2 gives average but not maximum.
Line 176. Change “percolation depth dependent” to “percolation depth to be dependent”
Table 1, Liquid water content. Give a reference for NESA-SM1, and ideally briefly say how the method works.
Line 226. Change “temperature gradient” to “temperature difference”.
Figure 4c (also on Figure C1). What is the green line plotting? Its horizontal position moves back and forth slightly, but there is no scale for it on the horizontal axis.
Figure 4 caption line 1. Change “with” to “versus”.
Line 253. The LWC is not given on Figure C1. Figure C1 includes a label “LWC”, but only gives a symbol, “D”, always the same, not a number. The symbol D is also undefined.
Line 295 says “average -14.6±7.6‰”, but line 297 says “mean of -14.55±2.5‰”. What distinction is being made here? They seem like two slightly different averages for the same thing.
Line 353 cites the extreme rainfall event of 24th March 2007. I actually was in Ny-Alesund during that event; it was dramatic. Then during the next two days the wet snow froze into a crust that the reindeer could not break through. But the reindeer knew what to do; they walked up to higher elevation where it had snowed rather than rained. According to my log for that time, the rainstorm occurred in early evening of the 23rd, not the 24th.
Line 421. Define “matrix flow”.
Line 421. Define Ø.