Satellite telemetry of surface ablation observations to inform spatial melt modelling, Place Glacier, British Columbia, Canada

Bevington, Alexandre R.; Menounos, Brian; Ednie, Mark

doi:10.5194/egusphere-2025-2702

Preprints

https://doi.org/10.5194/egusphere-2025-2702

Preprints

27 Jun 2025

| 27 Jun 2025

Satellite telemetry of surface ablation observations to inform spatial melt modelling, Place Glacier, British Columbia, Canada

Alexandre R. Bevington, Brian Menounos, and Mark Ednie

Abstract. Four automated "smart stakes" equipped with ultrasonic sensors, Arduino microcontrollers, and Iridium satellite telemetry were deployed to monitor glacier surface elevation changes at Place Glacier, British Columbia, Canada during the 2024 ablation season. The smart stakes recorded air temperature, relative humidity, and distance to glacier surface every 15 minutes from May 14 to September 21, 2024, providing high-temporal resolution melt data across an elevation gradient. Integration with airborne lidar surveys and satellite snow cover observations enabled validation and spatial extrapolation of point measurements. Temperature-index modeling using smart stake data yielded ice melt factors of -4.26 to -5.63 mm w.e. °C⁻¹ d⁻¹ and snow melt factors of -3.74 to -4.42 mm w.e. °C⁻¹ d⁻¹, consistent with previous studies. The spatial melt model estimated a total seasonal melt volume of 11.61 × 10⁶ m³ water equivalent, representing a summer mass balance of -4.14 m w.e. for the glacier. Validation against manual ablation stakes showed reasonable agreement (R² = 0.58, RMSE = 0.45 m w.e.). Event-scale analysis revealed that three discrete heat events (July 5–22, August 1–12, and August 29–September 9) accounted for over half of the total seasonal melt despite comprising only one-third of the ablation season. Maximum daily melt rates reached -87 mm w.e. d⁻¹ during these extreme events, with higher elevation sites experiencing disproportionately greater melt rates. Non-linear temperature lapse rates were observed across the glacier, highlighting the importance of distributed temperature measurements for accurate melt modeling. The low-cost smart stake system demonstrates significant potential for automated glacier monitoring, providing near real-time data transmission and enabling event-scale melt attribution studies. This multi-scale monitoring approach combining in-situ sensors, airborne lidar, and satellite observations offers a comprehensive framework for understanding glacier melt dynamics in a changing climate, though challenges remain regarding sensor stability, power management, and accounting for glacier dynamics in melt estimates.

Received: 06 Jun 2025 – Discussion started: 27 Jun 2025

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Journal article(s) based on this preprint

30 Jan 2026

Satellite telemetry of surface ablation to inform spatial melt modelling and event-scale monitoring, Place Glacier, Canada

Alexandre R. Bevington, Brian Menounos, and Mark Ednie

The Cryosphere, 20, 811–833, https://doi.org/10.5194/tc-20-811-2026,https://doi.org/10.5194/tc-20-811-2026, 2026

Short summary

Alexandre R. Bevington, Brian Menounos, and Mark Ednie

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-2702', Anonymous Referee #1, 21 Jul 2025

Review in attached PDF

Citation: https://doi.org/10.5194/egusphere-2025-2702-RC1
- AC1: 'Reply on RC1', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC1
CC1:
'Reviewer Comment on egusphere-2025-2702', Mauri Pelto, 27 Jul 2025

The authors have provided a detailed examination of the efficacy and operational approach to using smart stakes. Place Glacier, British Columbia is the location for this detailed field test. This location has a combination of long-term mass balance records, ongoing mass balance observations, automatic weather station, PlanetScope and recent annual Lidar observations. This makes for a perfect test site location. The authors emphasize repeatedly that smart stakes are low cost as a key part of this study but have not provided a cost range for the product or its operation. The cost is as essential as identifying their accuracy, for determining if they are best suited as a supplement to an existing stake network, adding high temporal resolution data or can be deployed in place of that network. There have been other detailed ablation surveys conducted during specific heat events that should be noted as part of this important growing data set. Smart stakes can be a valuable tool for expanding this data set. Melt models based on data with limited temporal resolution can be impaired by temporal and spatial variations in ice dynamics, albedo variations, and wind effects. The smart stakes can be effective in identifying the temporal variations that impact all ablation stake studies.
I applaud the authors for a thorough test of a new system and providing a best-case approach to utilization of extensive complimentary data sets for both analysis and validation. In future it would be wonderful to see how much melt context smart stake data can provide from a glacier that otherwise has limited field monitoring but has ongoing LIDAR or other geodetic observation.
Specific Comments
93: It is noted the upper part of the accumulation area was not instrumented due to logistical and safety reasons. However, earlier it was noted that the glacier has minimal crevassing. Is it worth being more specific on this constraint.
220: Other studies have utilized snow line migration across areas of previously measured snow depth to identify ablation. Is this what is being done with PlanetScope?
269: This is substantial tipping, did the manual stakes suffer this level of tilt due to near melt out? Are the smart stakes not emplaced as deeply or are they simply top heavy and prone to tilt earlier? The 4.88 m long stakes were drilled how deeply, it is noted that at least 0.8 m is exposed?
286: Figure 4A provides an excellent visual of snowpack variation. I recommend that the accumulation area ratio be reported for each. Given the difference in melt rates for snow surface vs ice surface this is important.
316: This similarity in ablation from stake to stake has been noted for other regional glaciers, which maybe worth noting that this is not unusual.
339: The number of melt days is a crucial variable to identify for a melt model to work accuartely, the mapping of this variable in Figure 9 is quite valuable as a an example of best practice
400: Important to note the increased specific melt rates observed during 24 recent heat wave event in the Nooksack Basin, North Cascades (Pelto et al. 2022) that supports observations provided here.
412: Providing a better reference to more specific regional studies where melt factors were derived demonstrates contrast and context. Bidlake et al (2010) noted melt factors for South Cascade Glacier of 0.0039+ 0.0006 for snow and 0.0056 + 0.0008 for ice. On Mount Baker in the North Cascades, Pelto et al (2022) reported under overall weather conditions DDFs for snow is 0.0035 m w.e. °C⁻¹d⁻¹. For ice, the DDFi is 0.0053 m w.e. °C⁻¹d⁻¹ During heat waves this rose to a DDFs snow of 0.0043 m w.e. °C⁻¹d⁻¹. For ice, the DDFi is 0.0067 m w.e. °C⁻¹d⁻¹.
425: The four smart stakes did provide high resolution temporal data but at a low spatial resolution raising again the cost issue.
442: Good description of the challenges posed by the vertical component of velocity. Make sure to note that this poses the same challenge for any ablation stake system . Smart stakes may in fact allow for better understanding of this.
References
Bidlake, W.R., Josberger, E.G. and Savoca, M.E.: Modelled and Measured Glacier Change and Related Glacioloical, Hydrological and Meterorological conditions at South Cascade Galcier, WA, Balance and water years 2006-2007. USGS Science Investigation Report 2010-5143, US Geological Survey, Reston VA USA, 2010.
Pelto, M. S., Dryak, M., Pelto, J., Matthews, T., & Perry, L. B.: Contribution of Glacier Runoff during Heat Waves in the Nooksack River Basin USA. Water (7), 1145. https://doi.org/10.3390/w14071145, 2022.

Citation: https://doi.org/10.5194/egusphere-2025-2702-CC1
- AC3: 'Reply on CC1', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC3
RC2:
'Comment on egusphere-2025-2702', Anonymous Referee #2, 21 Aug 2025

This manuscript describes the design and deployment of a novel “smart stake” system that monitors surface melt and air temperature in near real time. The authors apply the data collected to a simple spatial melt modelling framework and use them to evaluate the influence of heat waves on glacier melt at Place Glacier, British Columbia.
The manuscript presents a clear and detailed description of the smart stake design and deployment. The use of low-cost sensors and satellite telemetry is interesting and has the potential to make glaciological monitoring more accessible. The real-time transmission capability is a valuable feature, and the overall approach contributes to ongoing conversations about alternatives to traditional on-ice AWS.
While the smart stake concept is promising, I was not fully convinced of its added value relative to a conventional on-ice AWS setup, and I found the melt modelling and event attribution to be fairly simplistic. The manuscript covers many topics but could benefit from more depth in each of them. Addressing some of these limitations would be important before publication.
In summary, I enjoyed reading about the smart stake setup and seeing its performance and data outputs. However, I found the presentation of the subsequent analyses too simplistic. I detail these comments below.
Major comments
Cost argument: The main stated benefit of the smart stakes is their low cost, but no cost assessment is provided in the manuscript. Including such an assessment would be very useful for evaluating this setup. Without an explicit comparison, the argument for “low-cost” deployment remains difficult to evaluate. Furthermore, several suggested improvements (e.g., adding sensors to address tipping or solar heating) could make the smart stakes nearly as complex as an on-ice AWS, which would further weaken the cost advantage.
Increased spatial resolution: While the smart stakes did improve temporal resolution compared to seasonal mass balance surveys, the gain over a single on-ice AWS is less clear, particularly when combined with mass balance stake measurements. The poor performance of the upper site further reduces the usefulness of deploying four sites. Would a single smart stake or on-ice AWS at mid-elevation, combined with the off-glacier stations for lapse rates, provide comparable results? A stronger case for the sensors’ value could be made by explicitly testing the added benefit relative to existing approaches, especially given the availability of two off-ice AWS at this site.
Spatial melt modelling: The modelling approach is quite rudimentary, applying uniform melt factors across snow and ice despite calculating melt factors at four individual stakes. As a result, it is not clear how the smart stake data meaningfully enhance the analysis. The model performs reasonably, but not particularly well, and the value added by the smart stakes is not evident.
Heat wave analysis: Much of the main ablation season is classified as “heat waves,” making it unsurprising that a large fraction of melt occurred during those periods. More detail on how heat waves were defined, and how these events compare with other years, would strengthen this section. As currently framed, the analysis feels shallow, particularly since it relies heavily on site 4, which performed poorly compared to the lidar. The paper might benefit from focusing more deeply on either the melt modelling or the heat wave analysis, rather than presenting both at a fairly simplified level.
Minor comments
It was not clear to me why the ECCC station is included in the lapse rate calculation. This choice made the glacier sites appear bundled together and harder to interpret. Clarification would be helpful.
In several places, the writing alternates between very detailed and overly casual phrasing, which occasionally disrupted the flow. For example, line 99: “some 400 m away” . Could this be made more precise?
When justifying sensor or method choices, referencing prior use is not always sufficient. For example, line 140 states that a method was “used in other glaciological studies.” It would be stronger to explain whether it worked well in those studies and what was gained by its use.
If the issue with using GOES is that the station might move and lose connection, could an option such as transmitting data by radio signal to the main off-ice station, and then using GOES, be feasible?

Citation: https://doi.org/10.5194/egusphere-2025-2702-RC2
- AC2: 'Reply on RC2', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-2702', Anonymous Referee #1, 21 Jul 2025

Review in attached PDF

Citation: https://doi.org/10.5194/egusphere-2025-2702-RC1
- AC1: 'Reply on RC1', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC1
CC1:
'Reviewer Comment on egusphere-2025-2702', Mauri Pelto, 27 Jul 2025

The authors have provided a detailed examination of the efficacy and operational approach to using smart stakes. Place Glacier, British Columbia is the location for this detailed field test. This location has a combination of long-term mass balance records, ongoing mass balance observations, automatic weather station, PlanetScope and recent annual Lidar observations. This makes for a perfect test site location. The authors emphasize repeatedly that smart stakes are low cost as a key part of this study but have not provided a cost range for the product or its operation. The cost is as essential as identifying their accuracy, for determining if they are best suited as a supplement to an existing stake network, adding high temporal resolution data or can be deployed in place of that network. There have been other detailed ablation surveys conducted during specific heat events that should be noted as part of this important growing data set. Smart stakes can be a valuable tool for expanding this data set. Melt models based on data with limited temporal resolution can be impaired by temporal and spatial variations in ice dynamics, albedo variations, and wind effects. The smart stakes can be effective in identifying the temporal variations that impact all ablation stake studies.
I applaud the authors for a thorough test of a new system and providing a best-case approach to utilization of extensive complimentary data sets for both analysis and validation. In future it would be wonderful to see how much melt context smart stake data can provide from a glacier that otherwise has limited field monitoring but has ongoing LIDAR or other geodetic observation.
Specific Comments
93: It is noted the upper part of the accumulation area was not instrumented due to logistical and safety reasons. However, earlier it was noted that the glacier has minimal crevassing. Is it worth being more specific on this constraint.
220: Other studies have utilized snow line migration across areas of previously measured snow depth to identify ablation. Is this what is being done with PlanetScope?
269: This is substantial tipping, did the manual stakes suffer this level of tilt due to near melt out? Are the smart stakes not emplaced as deeply or are they simply top heavy and prone to tilt earlier? The 4.88 m long stakes were drilled how deeply, it is noted that at least 0.8 m is exposed?
286: Figure 4A provides an excellent visual of snowpack variation. I recommend that the accumulation area ratio be reported for each. Given the difference in melt rates for snow surface vs ice surface this is important.
316: This similarity in ablation from stake to stake has been noted for other regional glaciers, which maybe worth noting that this is not unusual.
339: The number of melt days is a crucial variable to identify for a melt model to work accuartely, the mapping of this variable in Figure 9 is quite valuable as a an example of best practice
400: Important to note the increased specific melt rates observed during 24 recent heat wave event in the Nooksack Basin, North Cascades (Pelto et al. 2022) that supports observations provided here.
412: Providing a better reference to more specific regional studies where melt factors were derived demonstrates contrast and context. Bidlake et al (2010) noted melt factors for South Cascade Glacier of 0.0039+ 0.0006 for snow and 0.0056 + 0.0008 for ice. On Mount Baker in the North Cascades, Pelto et al (2022) reported under overall weather conditions DDFs for snow is 0.0035 m w.e. °C⁻¹d⁻¹. For ice, the DDFi is 0.0053 m w.e. °C⁻¹d⁻¹ During heat waves this rose to a DDFs snow of 0.0043 m w.e. °C⁻¹d⁻¹. For ice, the DDFi is 0.0067 m w.e. °C⁻¹d⁻¹.
425: The four smart stakes did provide high resolution temporal data but at a low spatial resolution raising again the cost issue.
442: Good description of the challenges posed by the vertical component of velocity. Make sure to note that this poses the same challenge for any ablation stake system . Smart stakes may in fact allow for better understanding of this.
References
Bidlake, W.R., Josberger, E.G. and Savoca, M.E.: Modelled and Measured Glacier Change and Related Glacioloical, Hydrological and Meterorological conditions at South Cascade Galcier, WA, Balance and water years 2006-2007. USGS Science Investigation Report 2010-5143, US Geological Survey, Reston VA USA, 2010.
Pelto, M. S., Dryak, M., Pelto, J., Matthews, T., & Perry, L. B.: Contribution of Glacier Runoff during Heat Waves in the Nooksack River Basin USA. Water (7), 1145. https://doi.org/10.3390/w14071145, 2022.

Citation: https://doi.org/10.5194/egusphere-2025-2702-CC1
- AC3: 'Reply on CC1', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC3
RC2:
'Comment on egusphere-2025-2702', Anonymous Referee #2, 21 Aug 2025

This manuscript describes the design and deployment of a novel “smart stake” system that monitors surface melt and air temperature in near real time. The authors apply the data collected to a simple spatial melt modelling framework and use them to evaluate the influence of heat waves on glacier melt at Place Glacier, British Columbia.
The manuscript presents a clear and detailed description of the smart stake design and deployment. The use of low-cost sensors and satellite telemetry is interesting and has the potential to make glaciological monitoring more accessible. The real-time transmission capability is a valuable feature, and the overall approach contributes to ongoing conversations about alternatives to traditional on-ice AWS.
While the smart stake concept is promising, I was not fully convinced of its added value relative to a conventional on-ice AWS setup, and I found the melt modelling and event attribution to be fairly simplistic. The manuscript covers many topics but could benefit from more depth in each of them. Addressing some of these limitations would be important before publication.
In summary, I enjoyed reading about the smart stake setup and seeing its performance and data outputs. However, I found the presentation of the subsequent analyses too simplistic. I detail these comments below.
Major comments
Cost argument: The main stated benefit of the smart stakes is their low cost, but no cost assessment is provided in the manuscript. Including such an assessment would be very useful for evaluating this setup. Without an explicit comparison, the argument for “low-cost” deployment remains difficult to evaluate. Furthermore, several suggested improvements (e.g., adding sensors to address tipping or solar heating) could make the smart stakes nearly as complex as an on-ice AWS, which would further weaken the cost advantage.
Increased spatial resolution: While the smart stakes did improve temporal resolution compared to seasonal mass balance surveys, the gain over a single on-ice AWS is less clear, particularly when combined with mass balance stake measurements. The poor performance of the upper site further reduces the usefulness of deploying four sites. Would a single smart stake or on-ice AWS at mid-elevation, combined with the off-glacier stations for lapse rates, provide comparable results? A stronger case for the sensors’ value could be made by explicitly testing the added benefit relative to existing approaches, especially given the availability of two off-ice AWS at this site.
Spatial melt modelling: The modelling approach is quite rudimentary, applying uniform melt factors across snow and ice despite calculating melt factors at four individual stakes. As a result, it is not clear how the smart stake data meaningfully enhance the analysis. The model performs reasonably, but not particularly well, and the value added by the smart stakes is not evident.
Heat wave analysis: Much of the main ablation season is classified as “heat waves,” making it unsurprising that a large fraction of melt occurred during those periods. More detail on how heat waves were defined, and how these events compare with other years, would strengthen this section. As currently framed, the analysis feels shallow, particularly since it relies heavily on site 4, which performed poorly compared to the lidar. The paper might benefit from focusing more deeply on either the melt modelling or the heat wave analysis, rather than presenting both at a fairly simplified level.
Minor comments
It was not clear to me why the ECCC station is included in the lapse rate calculation. This choice made the glacier sites appear bundled together and harder to interpret. Clarification would be helpful.
In several places, the writing alternates between very detailed and overly casual phrasing, which occasionally disrupted the flow. For example, line 99: “some 400 m away” . Could this be made more precise?
When justifying sensor or method choices, referencing prior use is not always sufficient. For example, line 140 states that a method was “used in other glaciological studies.” It would be stronger to explain whether it worked well in those studies and what was gained by its use.
If the issue with using GOES is that the station might move and lose connection, could an option such as transmitting data by radio signal to the main off-ice station, and then using GOES, be feasible?

Citation: https://doi.org/10.5194/egusphere-2025-2702-RC2
- AC2: 'Reply on RC2', Alexandre Bevington, 26 Nov 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2702/egusphere-2025-2702-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-2702-AC2

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (27 Nov 2025) by Stephen Howell

AR by Alexandre Bevington on behalf of the Authors (27 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (08 Dec 2025) by Stephen Howell

RR by Anonymous Referee #1 (12 Dec 2025)

Suggestions for revision or reasons for rejection

Re-Review - Bevington et al. “Satellite telemetry of surface ablation to inform spatial melt modelling and event-scale monitoring, Place Glacier, Canada”, submitted to the Cryosphere.

The re-submitted manuscript presents a novel setup of automated ‘smart stakes’ that transmit temperature, humidity and ultrasonic surface height data via Iridium satellite telemetry from the Place Glacier in Canada. The manuscript presents results from a summer campaign during 2024 finding a range of melt factors for snow and ice, which is variable based upon the unique temperature records stemming from each of the four smart stakes. The study finds that such networks can be highly valuable to improve attribution of melt to specific warm events with a near-realtime transmission of data.
The authors now present a much improved modelling approach and consideration of lapse rate relevance and I appreciate their efforts in addressing several of the concerns I and other reviewers had. Nevertheless, I find that the manuscript still contains some unclear statements regarding ETI and lapse rates as well as the occurrence of inversions under heatwave events. The authors have produced some nice new figures of the data and modelling outputs, but the clarity of results and discussion sections still needs improvement to better fit the goal of the manuscript, in my opinion. There are several formatting errors that still need to be addressed and I feel that the authors did not directly answer one or two of the review questions from myself and others. I still consider minor corrections necessary before consideration for publication by the journal.

Specific comments

Original Comment - “The reported wake up times are naturally very short, due to battery life considerations, as is well reported by the authors. The equilibrium response times of the sensor according to the manufacturer are up to 30 seconds for the 63% range, but did the authors make any tests of these values compared to a continuously logging temperature sensor at the other weather stations, for example? Are the sensors also comparing well when placed together? Some short report of this would be beneficial.”

Author Response: "We apologize about this confusion. The battery consumption is a scenario with assumptions on timing. We reworded to add clarity. In reality, the startup time is about 10 seconds, and the Temp/RH measurement takes about 3 seconds, and the ultrasonic is sampled 10 times and the median value is reported. These points are now included in section 3.1 Sensors. "

This is fine, but does not really address my question, which perhaps was not clear. Does the wake up time have any notable impact on the air temperature accuracy when compared to continually logging instrumentation when tested before installation on the glacier? What about a ‘huddle test’ of all 4 smart stakes in the same space… are there large deviations in the recorded temperatures? Essentially, should the reader have faith in the accuracy of the derived temperatures and their differences across the glacier? The authors later remark in their responses (now L151-154) that comparison to other sensors show a correlation of 0.96, but refer to Fig. S2 which is not showing this. When measuring the same (or similar) space, the systematic bias is also important to know. Please revise and take care to check all figure references and formatting.

L318: Fig.S5 deals with the interpolated temperatures, not the interpolated DEMs.

L326-327: The authors should clarify that effects of the katabatic boundary layer are not explicitly resolved, but may be partially accounted for by using on-glacier stations for lapse rates (lapse rate options 2, 4, 5, 6).

Page 17-20 / L361-376: A formatting error has occurred whereby Figure 6 has been replicated 4 times over successive pages and section 5.2 has an absence of text that has also lost its correct formatting seemingly. Please check and revise. It is perhaps a compile error or artefact of file conversion.

L393-394: The authors need to define somewhere clearly what a negative lapse rate refers to (i.e. decrease of air temperature with elevation following the glaciological convention, but not the atmospheric one). The term for “our glacier stations.. “ is imprecise. State clearly if using combination 4 (e.g.) lapse rates experienced frequency temperature inversions (mean value + frequency) related to warm (non-glacier) temperatures (of => X°C). Can the authors show a scatter of lapse rates on glacier vs mean air temperatures off-glacier to make this point clearer?

L399: Dynamics of what?

Fig. 8: This provides a nice summary of how off-glacier data struggle to represent on-glacier temperatures under warm conditions (or “heat events”). I think it would be useful to give some numbers for the amount of melt estimated by the different methods for those conditions. E.g. how much melt would be over-estimate in a season/during heat events by using ECCC and a -6.5°C km1 lapse rate?

L427-429: This segment is very unclear and should be re-written to state clearly what was tested and how/why “We selected the ETI with the on–glacier linear lapse rate as a visual inspection of the ETI with the upper station polynomial lapse rate did not perform well outside of the air temperature observations in the higher elevations of the glacier. “

Figures 10/11: It is useful to see these evaluations, but they should be leveraged better to demonstrate the value of smart stakes. What happens if the authors use the better model (ETI) but using off-glacier AWS only? There has been an established need for representing on-glacier temperatures before (Greuell and Böhm, 1998; Shea and Moore, 2010; Ayala et al., 2015; Shaw et al., 2025), but the smart stakes provide a novel view over a time series to see under which days and which conditions does accounting for local temperatures over glaciers make the most difference, and crucially, by how much? I think exploring the residuals of model-observed mass loss (Fig 10) using a few key model-lapse rate combinations would provide much more wealth of information here.

Fig. 11 clarify that the model period is different in caption

Sect 5.6 can be more concise and clear with the comparison of models + forcing. What is the value of the manual stakes here? Once more, the authors present a clear and useful analysis of the sensor setup and its benefits and drawbacks, but the subsequent analyses like that presented in this section do not lend themselves to a clear result and statement that can be beneficial to the reader.

Fig. 13 - The authors should mask the off-glacier areas and nunataks.

L510: This is a very unclear statement that should be revised: “The importance of these heat events is facilitated by temperature inversions during the heat events (Figure 8), also reported by Ayala et al. (2015).” How have inversions facilitated the importance of heat events? If anything, such near-surface cooling complicates the relationship of glacier response to heat events.

Line 533-535: This sentence belongs at the end of the previous paragraph, as the ETI model described above does separate the sensible and radiative components.

L537: This may still result in a linear lapse rate… just one that is inverted. The authors should clarify that this is substantially different from a linear lapse rate applied from a single AWS off-glacier.

Supplementary

Fig. S1 and elsewhere: I think that some more context is required for the figure captions to meaningfully interpret what they are showing.

Fig S3, compile error for the citation in the figure caption. Is this lapse rate produced from all stations?

Cited works

Ayala, A., Pellicciotti, F., & Shea, J. (2015). Modeling 2m air temperatures over mountain glaciers: Exploring the influence of katabatic cooling and external warming. Journal of Geophysical Research: Atmospheres, 120, 1–19. https://doi.org/https://doi.org/10.1002/2015JD023137

Greuell, Wouter., & Böhm, Reinhard. (1998). 2 m temperatures along melting mid-latitude glaciers , and implications for the sensitivity of the mass balance to variations in temperature. Journal of Glaciology, 44(146), 9–20. https://doi.org/https://doi.org/10.3189/S0022143000002306

Shaw, T. E., Miles, E. S., McCarthy, M., Buri, P., Guyennon, N., Salerno, F., Carturan, L., Brock, B., & Pellicciotti, F. (2025). Mountain glaciers recouple to atmospheric warming over the twenty-first century. Nature Climate Change. https://doi.org/10.1038/s41558-025-02449-0

Shea, J. M., & Moore, R. D. (2010). Prediction of spatially distributed regional-scale fields of air temperature and vapor pressure over mountain glaciers. Journal of Geophysical Research, 115(D23), D23107. https://doi.org/10.1029/2010JD014351

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RR by Anonymous Referee #2 (18 Dec 2025)

ED: Publish subject to minor revisions (review by editor) (19 Dec 2025) by Stephen Howell

AR by Alexandre Bevington on behalf of the Authors (09 Jan 2026) Author's response Author's tracked changes Manuscript

ED: Publish as is (13 Jan 2026) by Stephen Howell

AR by Alexandre Bevington on behalf of the Authors (17 Jan 2026)

Journal article(s) based on this preprint

30 Jan 2026

Satellite telemetry of surface ablation to inform spatial melt modelling and event-scale monitoring, Place Glacier, Canada

Alexandre R. Bevington, Brian Menounos, and Mark Ednie

The Cryosphere, 20, 811–833, https://doi.org/10.5194/tc-20-811-2026,https://doi.org/10.5194/tc-20-811-2026, 2026

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Alexandre R. Bevington, Brian Menounos, and Mark Ednie

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https://doi.org/10.5194/egusphere-2025-2702-supplement

Alexandre R. Bevington, Brian Menounos, and Mark Ednie

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Cumulative views and downloads (calculated since 27 Jun 2025)

Month	HTML	PDF	XML	Total
Jun 2025	50	10	4	64
Jul 2025	103	65	10	178
Aug 2025	171	10	4	185
Sep 2025	389	11	2	402
Oct 2025	55	18	1	74
Nov 2025	66	39	7	112
Dec 2025	54	45	5	104
Jan 2026	25	42	2	69

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We developed automated "smart stakes" to study how quickly glaciers melt during hot weather. The low-cost devices were placed on Place Glacier in British Columbia and sent data by satellite in 2024. We show that just three heat periods caused more than half of the glacier's total summer melt, even though these events lasted only one-third of the melt season. This system provided measurements that would be impossible with traditional methods and improved models.


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