the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Aug 2023
Evolution of layered density and microstructure in near‐surface firn around Dome Fuji, Antarctica
Abstract. To better understand the near‐surface evolution of polar firn in low accumulation areas (<30 mm w.e. yr−1), we investigated the physical properties: density, microstructural anisotropy of ice matrix and pore space, and specific surface area (SSA), of six firn cores collected within 60 km around Dome Fuji, East Antarctica. The physical properties were measured at the intervals of ≤0.02 m over the top 10 m of the cores. The main findings are: (i) lack of significant density increase in the top ~4 m, (ii) lower density near the dome summit (~330 kg m−3) than the surrounding slope area (~355 kg m−3), (iii) developments of vertically elongated microstructure and its contrast between layers within the top ~3 m, (iv) more pronounced vertical elongation at sites and periods with lower accumulation rates than those with higher accumulation rates, (v) rapid decrease in SSA in the top ~3 m, and (vi) lower SSA at lower accumulation sites, but this trend is less pronounced than that of microstructural anisotropy. These observations can be explained by the combination of the initial physical properties on the surface set by wind conditions and the metamorphism driven by water vapor transport through the firn column under a strong vertical temperature gradient (temperature gradient metamorphism, TGM). The magnitude of TGM depends on the duration of firn layers under temperature gradient, determined by accumulation rate; longer exposure causes a more vertically elongated microstructure and lower SSA. Overall, we highlight the significant spatial variability in the near-surface physical properties over the scale of ~100 km around Dome Fuji. These findings will help better understand the densification over the whole firn column and the gas trapping process in deep firn, and possible difference in them between existing deep ice cores and the upcoming “Oldest-Ice” cores collected tens of kilometers apart.
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RC1: 'Comment on egusphere-2023-1838', Ghislain Picard, 10 Oct 2023
Review of “Evolution of layered density and microstructure in near‐surface firn around Dome Fuji, Antarctica” by Ryo Inoue et al.
The article presents and analyzes measurements of the snow microstructure in the top 10 m of the firn around Dome Fuji in Antarctica. In total, 6 cores retrieved within 30 km are analyzed with unique carefully-designed techniques at 2 cm resolution for three important properties: density, specific surface area, and dielectric anisotropy. The analysis aims to explain the vertical profile characteristics and the spatial differences as a function of the meteorological variations (accumulation mainly). This study sheds light on post-depositional processes and snow metamorphism operating in the dome regions in East Antarctica and provide experimental evidences from the surface to help understand firnification processes operating at depth. While the results mainly confirm previous work, the empirical material is abundant, hence allowing a very detailed analysis that draws almost everywhere interesting and stronger conclusions. This study is important because the processes dominating the snow evolution in this region are very different and poorly investigated compared to other regions in the world (alpines and arctic regions). The role of the post-deposional processes / bloxing snow is highlighted. The targeted audience is polar snow and ice core scientists. It is in the scope of The Cryosphere.
The paper is well written and the structure is logical. The figures and tables are abundant and adequate. Only changes are required to improve the readability of the challenging Fig 3 that presents all the raw available materials. The analysis is overall carefully conducted with some statistical information. However, I’ve noted many minor issues, that result in a large number of comments below that may require significant work. Despite this, I’d like to stress that the overall quality and the value of all these rare observations for the snow and ice core community are very high. This is why I strongly recommend the publication of this study and of the open dataset.
Detailed comments:
Regarding the title:
- “Evolution” evokes time to me rather than the vertical spatial dimension.
- The horizontal spatial component of the study (the 6 cores in a >30km region) is not present while I think this is a value of this study.
- “layered”. As it is apparent in my comments below, I believe (this is an opinion) that the snowpack on the High Plateau is not layered, due to the tremendous and permanent redistribution by wind. This paper draw conclusions in this direction as well to my understanding. The use of “layer” should therefore be reduced as much as possible because it conveys a message that reinforces the unconscious and dominant picture of the highly layered alpine /arctic snowpack that most of snow scientists know by daily experience, far from the complexity of the high plateau in Antarctica that only a few expeditioners have experienced. I let the authors agree or not on this point, and make the necessary changes if appropriate. It is a subjective comment.Overall, I suggest to include the idea of “vertical profiles” and “spatial distribution” in the title.
Detailed comments:L46: “the layers are tens of centimeters thick”. To my experience of the Dome C area, especially sampling a 50m long trench, it is even difficult to identify layers. Considering the wide audience of The Cryosphere, and the widespread belief that snow accumulates as layer everywhere, I’d suggest the authors (if they share the same experience and point of view) to elaborate this point that may lead to incorrect assumptions in modeling. For instance Picard et al. 2019 showed that the age of snow on the surface can vary spatially on short scales from 0 to 300 days, with potential consequences on the microstructure, isotopic composition, etc of that snows.
L49. “the firn layers undergo metamorphism over time by packing and rounding of snow grains”. While this sentence is true in general, and applies well to alpine snow, on the Antarctic plateau rounding is very rare at depth to my experience, owing to the permanent temperature gradients >20 K/m.
L62 Mord → Maud
L82. “in the Megadune region” → “a Megadune region”. This region is not unique, megadunes are widespread in inner Antarctica.
L94-97. “detailed observations of firn microstructure” is subjective, may be I do not understand the idea expressed by the authors, but they are many measurements of SSA and density (i.e. beyond visual inspection) published in (self citation): Picard et al. 2014, Libois et al. 2014, Picard et al. 2022, Leduc-Leballeur et al. 2015, Brucker et al. 2009. The SumUP database also contains density measurements.
L110. I suggest to add a reference here for the gamma ray technique.L120. The abstract is mentioning “six cores” which may be misunderstood with “five sites”, so maybe add “six cores” here as well.
147. Using ERA5 to investigate spatial variability with 30 km is inadequate, due to the coarse resolution of this dataset and the even coarser resolution of the underlying models. I suggest to remove the information coming from ERA5. It is likely that the conditions are more variable than registered in ERA5, especially for the wind speed.
L165. What about the conditions of transport (temperature?). The SSA can change quite within month at temperature higher than ~-35°C.
L178. How the error is determined ? May be add a reference.
L198. Given the non symmetrical geometry in the resonator and of the sample, I’d expect that the measurements in the two axis are subject to different error (bias and random variations). How are the vertical and horizontal measurements intercalibrated ?
L210. I’d expect that some theoretical mixing formula could be used here instead of empirical fits. The comparison below using Polder van Santen mixing formula and Mätzler 2006 ice permittivity formula as a function of temperature shows the agreement of Oyabu’s -16°C curve, but not -30°C curve. The temperature dependence seems very important for such a small difference in °C. This potentially leads to density estimation differences larger than the error stated in L241. 6 – 14 kg m-3. I suggest the authors to re-analyse the derivation of the relationship at -30°C and its experimental error.
L240. In this optical configuration (directional-directional reflectance), it is likely that the reflectance depends on density in addition to SSA, especially for low densities. Given that Fig A1 shows a very significant variability for high SSA (correlated with highly variable and low density in the cores), I suggest to explore this dependency, which is possible with this large dataset. Adding a figure comparing the hemispherical reflectance and the directional reflectance of the 60 samples is also useful in order to distinguish (and quantify) the error due to the non-hemispherical reflectance and that due to the inherent imprecision of the SSA – hemispherical reflectance relationship. In addition, because of the two apparent distinct regimes in Figure A1, the main text should be amended to provide separate error values for SSA< 5 m2 / kg and SSA > 5 m2/kg. In fact, the 15% error is an average but does not highlight this major difference of regime. Also you may indicate the range of applicability of the fit in the main text (SSA < 14 m2/kg). It is not uncommon to get higher SSA near the surface in the ridge region.
L275. I find the notation kg m-3 m-1 clearer than with the power of 4. A matter of preference.
L277. “agree with each other within the measurement error”. It seems that the variability is larger than the error, isn’t it ? Maybe add the error as shaded areas in the Fig 4a plot, at least in your response to the reviews, because I acknowledge it might be too difficult to read for the main text.
L281 “on a scale of ~0.1 m, reflecting the density layering of firn (Fig. 3)". It is not visible in Fig 3 that the variation scale is 0.1 m, the individual measurements are not represented. A more precise quantification of the correlation length, using an AR(1) model for instance, would be valubale as the layering (and its origin) are crucial in ice core interpretation (interpretation of isotops f.i.).
L281-290. To interpret the S.D., the error on the S.D estimator should be calculated. Given the large amplitude of the S.D. and the relatively small number of observations (50 per meter at,most) it is possible that the S.D estimates are subject to uncertainties of the order of the interpreted differences. In fact, a question is whether the oscillations of the S.D. in Fig 6 are real or statistical artifacts.
L337. Similar question. Are these oscillations real or due to a few particularly high variations in some specific layers. Based on Fig 5, I see a few infrequent large variations. Are they the causes of these oscillations ?
L345. Since Epsilon is related to density, it is expected that part of Delta Epsilon changes with density. That is, when the density increases both vertical and horizontal permittivities logically increase, and since the horizontal one is typically larger than the vertical one, the difference should increase as well. To separate this “obvious” contribution from the anisotropy contribution, which is the one of geophysical interest, is it possible to investigate the ratio Delta Epsilon / Epsilon instead of the difference ? This comment is also related to the discussion L 505-510.
L359. I suggest to change “at the surface” by “near the surface” because it is unlikely the surface SSA is so low (11 m2 /kg). Satellite optical observations show much larger SSA values in this area of the Antarctic. Also, to my experience in the field, SSA measured on the surface and along snow core very close to the surface always shows a large difference. The conditions of transport from Antarctica to Japan may also have altered the highest SSA.
L396-397. “Generally, the density of near‐surface firn is expected to increase with depth due to settling of snow grains under overburden pressure”. Overburden pressure is not the main process of densification near the surface to my knowledge. At least in Alpine snowpack most of the early stage densification is due to metamorphism (packing caused by self-gravity of the grains), without requiring any pressure, which is insufficient anyway near the surface. The observations of the paper conform with the common knowledge, the first sentence should be revised to remove the opposition with the second sentence.
L406. “However, slow densification due to the slight overburden pressure cannot explain the observed density decrease for the top ~2 m”. I don’t understand “however”. How does this oppose with the previous sentence ?
L414. Champollion et al. 2019 investigates decannal temporal variations at Dome C, there are indeed surprisingly large, but I’m not sure if they can explain the data in Fig 3a. Note that the same methodology could be applied to Dome F, but this is certainly out of the scope of the present paper and only provide a few decades (a few meters). There are certainly other references to illustrate the same point, I’m sorry for the high number of self citation in this review.
L414. Another aspect is the significance of such a low value. How to conclude based on a single core (~<10 cm in diameter) considering the randomness due to the wind ? The presence of long dunes as evidenced at Dome C (Picard et al. 2014) may also jeopardize any interpretation of a few cores.
L424. This is true up to ~ 50 m, as demonstrated in Fujita et al. (2009)
L426. “Delta SSA” missing Delta in the parenthesis
L454 “The intense IHDFs are formed by wind‐packing (Koerner, 1971; Fujita et al.,
2009), and their densities depend on wind speed (e.g., Sugiyama et al., 2012). Thus, wind is probably a key environmental factor controlling density variability (Fig. 6a).” if this is true, some correlation in the density profiles between the nearby sites should be seen. This can be tested with this dataset. An alternative hypothesis is that the IHDF and ILDF are due to local randomness, i.e. due to the deposition of ten-centimeter thick patches of snow as shown in Picard et al. 2019. In such case, no correlation will be see in kilometer-distant cores.Figure 9. Is is possible to add accumulation rate, either on the map or as value in the graphs.
L528. an inverse correlation → negative correlation
L 578-568. This part is less credible than the remaining of the analysis. The visual determination of the maximums and minimums is subjective, especially the maximums in this particular case. The MC method is not detailed enough, especially how the temporal correlation in the series is taken into account (the 8-year moving average introduces very significant correlation). Also given that six cores are available, the method should start from this raw material, not from their average.
L612. “And the minor role of sintering for densification.”. I don’t understand.
Data availability: the site is not accessible.
References:
G. Picard, H. Löwe, F. Domine, L. Arnaud, F. Larue, V. Favier, E. Le Meur, E. Lefebvre, J. Savarino, A. Royer, The microwave snow grain size: a new concept to predict Satellite observations over snow-covered regions, AGU Advances, 3, 4, e2021AV000630, doi:10.1029/2021AV000630M. Leduc-Leballeur, G. Picard, A. Mialon, L. Arnaud, E. Lefebvre, P. Possenti, Y. Kerr, Modeling L-band brightness temperature at Dome C, Antarctica and comparison with SMOS observations, IEEE Transactions on Geoscience and Remote Sensing , 53 (7), 4022 – 4032, doi:10.1109/TGRS.2015.2388790, 2015
Q. Libois, G. Picard, L. Arnaud, S. Morin, E. Brun, Modeling the impact of snow drift on the decameter-scale variability of snow properties on the Antarctic Plateau, Journal of Geophysical Research - Atmosphere, 119 (20), doi:10.1002/2014JD022361, 2014
G. Picard, A. Royer, L. Arnaud, M. Fily. Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica, The Cryosphere, 8, 1105-1119, 2014, doi:10.5194/tc-8-1105-2014
Brucker, L., G. Picard, L. Arnaud, Barnola, JM, Schneebeli, M., Brunjail, H., Lefebvre, E., Fily, M. Modeling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements, Journal of Glaciology, 57(201),171-182, 2011, doi:10.3189/002214311795306736
Champollion, N., Picard, G., Arnaud, L., Lefebvre, É., Macelloni, G., Rémy, F., and Fily, M.: Marked decrease of the near surface snow density retrieved by AMSR-E satellite at Dome C, Antarctica, between 2002 and 2011, The Cryosphere, 13, 1215-1232, doi:10.5194/tc-13-1215-2019, 2019
Citation: https://doi.org/10.5194/egusphere-2023-1838-RC1 - AC2: 'Reply on RC1', Ryo Inoue, 30 Nov 2023
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RC2: 'Comment on egusphere-2023-1838', Z.R. Courville, 29 Oct 2023
Overall, this is a very interesting and impressive set of high resolution firn physical property measurements from relatively closely spaced (i.e., within 60 km of one another) low accumulation rate sites in Eastern Antarctica. The paper presents a suite of complementary measurements of high vertical resolution density, anisotropy and SSA. Some of the more interesting conclusions of the paper include that there may exist a positive feedback between temperature gradient metamorphism and anisotropy, which makes sense intuitively and is supported by the results, and that post-depositional changes in SSA are not overcome by initial SSA variations formed by surface depositional conditions. The paper also presents evidence that at least for this low accumulation site that there is a lack of significant density in the top 4m of the firn column and that firn at the summit of the dome is less than the surrounding area, and points to the role of wind and, related to wind, topography, in the determination of initially high density layers which impact firn densification rates in addition to snow accumulation and temperature (as are typically used to determine firn density with depth profiles empirically). Furthermore, the paper does an excellent job of describing the environmental factors driving the density and microstructure variations in the firn in the context of previous studies in order to interpret the results, and discuss the interrelation of the snow microstructural parameters (i.e., pore and grain size and anisotropy) and environmental conditions to explain density variations.
Science and methodology questions:
Table 1: How well does the NDF18 10 meter temperature reflect the 10 m temperatures at NDF13 and NDFN? Same question for the Dome Fuji temperature being used for the DFS10 site (and likely more differences between the actual values for these two sites)?
Line 165: How were the cores transported? Specifically, what temperatures were the cores shipped and stored at and what measures were taken to ensure minimal grain size changes?
Figure 8: not sure if this figure is needed? It is confusing to interpret, and seems to be conveying much of the same info that is in Figure 7.
Minor/technical issues:
Line 30: “For example, accurate density profile of near-surface firn is essential to derive the surface mass balance from the change in surface height” should be “For example, an accurate density profile of near-surface firn is essential to derive the surface mass balance from the change in surface height..” (just missing the article “an”)
Figure 1: This is a really great figure that really helps to clarify the context of wind and accumulation.
Table 1, caption for “a” should be “The number after the letter designation…” or “The number in the alphanumeric designation..”
Line 185 (Figure 2 caption): should be, or more precisely, is more commonly written “perpendicular to the page”
Line 538: “suggesting that the spatial difference in the microstructural anisotropy developed by TGM are maintained in the deeper firn.” Should be, “suggesting that the spatial differences in the microstructural anisotropy developed by TGM are maintained in the deeper firn.”
Line 541: “The sensitivity of Δε to accumulation rate is higher at lower accumulation rates (Fig. 11a), may implying the existence of positive feedback between TGM and microstructural anisotropy.” Should be “The sensitivity of Δε to accumulation rate is higher at lower accumulation rates (Fig. 11a), may imply the existence of positive feedback between TGM and microstructural anisotropy.”
Line 542: “The firn with more vertically elongated structure (created by TGM) become more permeable, thereby facilitating vertical vapor transport and potentially leading to stronger TGM (e.g., Albert, 2002).” Should be, “The firn with more vertically elongated structure (created by TGM) becomes more permeable, thereby facilitating vertical vapor transport and potentially leading to stronger TGM (e.g., Albert, 2002).”
Line 724: fieldworks should be fieldwork
Citation: https://doi.org/10.5194/egusphere-2023-1838-RC2 - AC1: 'Reply on RC2', Ryo Inoue, 30 Nov 2023
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1838', Ghislain Picard, 10 Oct 2023
Review of “Evolution of layered density and microstructure in near‐surface firn around Dome Fuji, Antarctica” by Ryo Inoue et al.
The article presents and analyzes measurements of the snow microstructure in the top 10 m of the firn around Dome Fuji in Antarctica. In total, 6 cores retrieved within 30 km are analyzed with unique carefully-designed techniques at 2 cm resolution for three important properties: density, specific surface area, and dielectric anisotropy. The analysis aims to explain the vertical profile characteristics and the spatial differences as a function of the meteorological variations (accumulation mainly). This study sheds light on post-depositional processes and snow metamorphism operating in the dome regions in East Antarctica and provide experimental evidences from the surface to help understand firnification processes operating at depth. While the results mainly confirm previous work, the empirical material is abundant, hence allowing a very detailed analysis that draws almost everywhere interesting and stronger conclusions. This study is important because the processes dominating the snow evolution in this region are very different and poorly investigated compared to other regions in the world (alpines and arctic regions). The role of the post-deposional processes / bloxing snow is highlighted. The targeted audience is polar snow and ice core scientists. It is in the scope of The Cryosphere.
The paper is well written and the structure is logical. The figures and tables are abundant and adequate. Only changes are required to improve the readability of the challenging Fig 3 that presents all the raw available materials. The analysis is overall carefully conducted with some statistical information. However, I’ve noted many minor issues, that result in a large number of comments below that may require significant work. Despite this, I’d like to stress that the overall quality and the value of all these rare observations for the snow and ice core community are very high. This is why I strongly recommend the publication of this study and of the open dataset.
Detailed comments:
Regarding the title:
- “Evolution” evokes time to me rather than the vertical spatial dimension.
- The horizontal spatial component of the study (the 6 cores in a >30km region) is not present while I think this is a value of this study.
- “layered”. As it is apparent in my comments below, I believe (this is an opinion) that the snowpack on the High Plateau is not layered, due to the tremendous and permanent redistribution by wind. This paper draw conclusions in this direction as well to my understanding. The use of “layer” should therefore be reduced as much as possible because it conveys a message that reinforces the unconscious and dominant picture of the highly layered alpine /arctic snowpack that most of snow scientists know by daily experience, far from the complexity of the high plateau in Antarctica that only a few expeditioners have experienced. I let the authors agree or not on this point, and make the necessary changes if appropriate. It is a subjective comment.Overall, I suggest to include the idea of “vertical profiles” and “spatial distribution” in the title.
Detailed comments:L46: “the layers are tens of centimeters thick”. To my experience of the Dome C area, especially sampling a 50m long trench, it is even difficult to identify layers. Considering the wide audience of The Cryosphere, and the widespread belief that snow accumulates as layer everywhere, I’d suggest the authors (if they share the same experience and point of view) to elaborate this point that may lead to incorrect assumptions in modeling. For instance Picard et al. 2019 showed that the age of snow on the surface can vary spatially on short scales from 0 to 300 days, with potential consequences on the microstructure, isotopic composition, etc of that snows.
L49. “the firn layers undergo metamorphism over time by packing and rounding of snow grains”. While this sentence is true in general, and applies well to alpine snow, on the Antarctic plateau rounding is very rare at depth to my experience, owing to the permanent temperature gradients >20 K/m.
L62 Mord → Maud
L82. “in the Megadune region” → “a Megadune region”. This region is not unique, megadunes are widespread in inner Antarctica.
L94-97. “detailed observations of firn microstructure” is subjective, may be I do not understand the idea expressed by the authors, but they are many measurements of SSA and density (i.e. beyond visual inspection) published in (self citation): Picard et al. 2014, Libois et al. 2014, Picard et al. 2022, Leduc-Leballeur et al. 2015, Brucker et al. 2009. The SumUP database also contains density measurements.
L110. I suggest to add a reference here for the gamma ray technique.L120. The abstract is mentioning “six cores” which may be misunderstood with “five sites”, so maybe add “six cores” here as well.
147. Using ERA5 to investigate spatial variability with 30 km is inadequate, due to the coarse resolution of this dataset and the even coarser resolution of the underlying models. I suggest to remove the information coming from ERA5. It is likely that the conditions are more variable than registered in ERA5, especially for the wind speed.
L165. What about the conditions of transport (temperature?). The SSA can change quite within month at temperature higher than ~-35°C.
L178. How the error is determined ? May be add a reference.
L198. Given the non symmetrical geometry in the resonator and of the sample, I’d expect that the measurements in the two axis are subject to different error (bias and random variations). How are the vertical and horizontal measurements intercalibrated ?
L210. I’d expect that some theoretical mixing formula could be used here instead of empirical fits. The comparison below using Polder van Santen mixing formula and Mätzler 2006 ice permittivity formula as a function of temperature shows the agreement of Oyabu’s -16°C curve, but not -30°C curve. The temperature dependence seems very important for such a small difference in °C. This potentially leads to density estimation differences larger than the error stated in L241. 6 – 14 kg m-3. I suggest the authors to re-analyse the derivation of the relationship at -30°C and its experimental error.
L240. In this optical configuration (directional-directional reflectance), it is likely that the reflectance depends on density in addition to SSA, especially for low densities. Given that Fig A1 shows a very significant variability for high SSA (correlated with highly variable and low density in the cores), I suggest to explore this dependency, which is possible with this large dataset. Adding a figure comparing the hemispherical reflectance and the directional reflectance of the 60 samples is also useful in order to distinguish (and quantify) the error due to the non-hemispherical reflectance and that due to the inherent imprecision of the SSA – hemispherical reflectance relationship. In addition, because of the two apparent distinct regimes in Figure A1, the main text should be amended to provide separate error values for SSA< 5 m2 / kg and SSA > 5 m2/kg. In fact, the 15% error is an average but does not highlight this major difference of regime. Also you may indicate the range of applicability of the fit in the main text (SSA < 14 m2/kg). It is not uncommon to get higher SSA near the surface in the ridge region.
L275. I find the notation kg m-3 m-1 clearer than with the power of 4. A matter of preference.
L277. “agree with each other within the measurement error”. It seems that the variability is larger than the error, isn’t it ? Maybe add the error as shaded areas in the Fig 4a plot, at least in your response to the reviews, because I acknowledge it might be too difficult to read for the main text.
L281 “on a scale of ~0.1 m, reflecting the density layering of firn (Fig. 3)". It is not visible in Fig 3 that the variation scale is 0.1 m, the individual measurements are not represented. A more precise quantification of the correlation length, using an AR(1) model for instance, would be valubale as the layering (and its origin) are crucial in ice core interpretation (interpretation of isotops f.i.).
L281-290. To interpret the S.D., the error on the S.D estimator should be calculated. Given the large amplitude of the S.D. and the relatively small number of observations (50 per meter at,most) it is possible that the S.D estimates are subject to uncertainties of the order of the interpreted differences. In fact, a question is whether the oscillations of the S.D. in Fig 6 are real or statistical artifacts.
L337. Similar question. Are these oscillations real or due to a few particularly high variations in some specific layers. Based on Fig 5, I see a few infrequent large variations. Are they the causes of these oscillations ?
L345. Since Epsilon is related to density, it is expected that part of Delta Epsilon changes with density. That is, when the density increases both vertical and horizontal permittivities logically increase, and since the horizontal one is typically larger than the vertical one, the difference should increase as well. To separate this “obvious” contribution from the anisotropy contribution, which is the one of geophysical interest, is it possible to investigate the ratio Delta Epsilon / Epsilon instead of the difference ? This comment is also related to the discussion L 505-510.
L359. I suggest to change “at the surface” by “near the surface” because it is unlikely the surface SSA is so low (11 m2 /kg). Satellite optical observations show much larger SSA values in this area of the Antarctic. Also, to my experience in the field, SSA measured on the surface and along snow core very close to the surface always shows a large difference. The conditions of transport from Antarctica to Japan may also have altered the highest SSA.
L396-397. “Generally, the density of near‐surface firn is expected to increase with depth due to settling of snow grains under overburden pressure”. Overburden pressure is not the main process of densification near the surface to my knowledge. At least in Alpine snowpack most of the early stage densification is due to metamorphism (packing caused by self-gravity of the grains), without requiring any pressure, which is insufficient anyway near the surface. The observations of the paper conform with the common knowledge, the first sentence should be revised to remove the opposition with the second sentence.
L406. “However, slow densification due to the slight overburden pressure cannot explain the observed density decrease for the top ~2 m”. I don’t understand “however”. How does this oppose with the previous sentence ?
L414. Champollion et al. 2019 investigates decannal temporal variations at Dome C, there are indeed surprisingly large, but I’m not sure if they can explain the data in Fig 3a. Note that the same methodology could be applied to Dome F, but this is certainly out of the scope of the present paper and only provide a few decades (a few meters). There are certainly other references to illustrate the same point, I’m sorry for the high number of self citation in this review.
L414. Another aspect is the significance of such a low value. How to conclude based on a single core (~<10 cm in diameter) considering the randomness due to the wind ? The presence of long dunes as evidenced at Dome C (Picard et al. 2014) may also jeopardize any interpretation of a few cores.
L424. This is true up to ~ 50 m, as demonstrated in Fujita et al. (2009)
L426. “Delta SSA” missing Delta in the parenthesis
L454 “The intense IHDFs are formed by wind‐packing (Koerner, 1971; Fujita et al.,
2009), and their densities depend on wind speed (e.g., Sugiyama et al., 2012). Thus, wind is probably a key environmental factor controlling density variability (Fig. 6a).” if this is true, some correlation in the density profiles between the nearby sites should be seen. This can be tested with this dataset. An alternative hypothesis is that the IHDF and ILDF are due to local randomness, i.e. due to the deposition of ten-centimeter thick patches of snow as shown in Picard et al. 2019. In such case, no correlation will be see in kilometer-distant cores.Figure 9. Is is possible to add accumulation rate, either on the map or as value in the graphs.
L528. an inverse correlation → negative correlation
L 578-568. This part is less credible than the remaining of the analysis. The visual determination of the maximums and minimums is subjective, especially the maximums in this particular case. The MC method is not detailed enough, especially how the temporal correlation in the series is taken into account (the 8-year moving average introduces very significant correlation). Also given that six cores are available, the method should start from this raw material, not from their average.
L612. “And the minor role of sintering for densification.”. I don’t understand.
Data availability: the site is not accessible.
References:
G. Picard, H. Löwe, F. Domine, L. Arnaud, F. Larue, V. Favier, E. Le Meur, E. Lefebvre, J. Savarino, A. Royer, The microwave snow grain size: a new concept to predict Satellite observations over snow-covered regions, AGU Advances, 3, 4, e2021AV000630, doi:10.1029/2021AV000630M. Leduc-Leballeur, G. Picard, A. Mialon, L. Arnaud, E. Lefebvre, P. Possenti, Y. Kerr, Modeling L-band brightness temperature at Dome C, Antarctica and comparison with SMOS observations, IEEE Transactions on Geoscience and Remote Sensing , 53 (7), 4022 – 4032, doi:10.1109/TGRS.2015.2388790, 2015
Q. Libois, G. Picard, L. Arnaud, S. Morin, E. Brun, Modeling the impact of snow drift on the decameter-scale variability of snow properties on the Antarctic Plateau, Journal of Geophysical Research - Atmosphere, 119 (20), doi:10.1002/2014JD022361, 2014
G. Picard, A. Royer, L. Arnaud, M. Fily. Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica, The Cryosphere, 8, 1105-1119, 2014, doi:10.5194/tc-8-1105-2014
Brucker, L., G. Picard, L. Arnaud, Barnola, JM, Schneebeli, M., Brunjail, H., Lefebvre, E., Fily, M. Modeling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements, Journal of Glaciology, 57(201),171-182, 2011, doi:10.3189/002214311795306736
Champollion, N., Picard, G., Arnaud, L., Lefebvre, É., Macelloni, G., Rémy, F., and Fily, M.: Marked decrease of the near surface snow density retrieved by AMSR-E satellite at Dome C, Antarctica, between 2002 and 2011, The Cryosphere, 13, 1215-1232, doi:10.5194/tc-13-1215-2019, 2019
Citation: https://doi.org/10.5194/egusphere-2023-1838-RC1 - AC2: 'Reply on RC1', Ryo Inoue, 30 Nov 2023
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RC2: 'Comment on egusphere-2023-1838', Z.R. Courville, 29 Oct 2023
Overall, this is a very interesting and impressive set of high resolution firn physical property measurements from relatively closely spaced (i.e., within 60 km of one another) low accumulation rate sites in Eastern Antarctica. The paper presents a suite of complementary measurements of high vertical resolution density, anisotropy and SSA. Some of the more interesting conclusions of the paper include that there may exist a positive feedback between temperature gradient metamorphism and anisotropy, which makes sense intuitively and is supported by the results, and that post-depositional changes in SSA are not overcome by initial SSA variations formed by surface depositional conditions. The paper also presents evidence that at least for this low accumulation site that there is a lack of significant density in the top 4m of the firn column and that firn at the summit of the dome is less than the surrounding area, and points to the role of wind and, related to wind, topography, in the determination of initially high density layers which impact firn densification rates in addition to snow accumulation and temperature (as are typically used to determine firn density with depth profiles empirically). Furthermore, the paper does an excellent job of describing the environmental factors driving the density and microstructure variations in the firn in the context of previous studies in order to interpret the results, and discuss the interrelation of the snow microstructural parameters (i.e., pore and grain size and anisotropy) and environmental conditions to explain density variations.
Science and methodology questions:
Table 1: How well does the NDF18 10 meter temperature reflect the 10 m temperatures at NDF13 and NDFN? Same question for the Dome Fuji temperature being used for the DFS10 site (and likely more differences between the actual values for these two sites)?
Line 165: How were the cores transported? Specifically, what temperatures were the cores shipped and stored at and what measures were taken to ensure minimal grain size changes?
Figure 8: not sure if this figure is needed? It is confusing to interpret, and seems to be conveying much of the same info that is in Figure 7.
Minor/technical issues:
Line 30: “For example, accurate density profile of near-surface firn is essential to derive the surface mass balance from the change in surface height” should be “For example, an accurate density profile of near-surface firn is essential to derive the surface mass balance from the change in surface height..” (just missing the article “an”)
Figure 1: This is a really great figure that really helps to clarify the context of wind and accumulation.
Table 1, caption for “a” should be “The number after the letter designation…” or “The number in the alphanumeric designation..”
Line 185 (Figure 2 caption): should be, or more precisely, is more commonly written “perpendicular to the page”
Line 538: “suggesting that the spatial difference in the microstructural anisotropy developed by TGM are maintained in the deeper firn.” Should be, “suggesting that the spatial differences in the microstructural anisotropy developed by TGM are maintained in the deeper firn.”
Line 541: “The sensitivity of Δε to accumulation rate is higher at lower accumulation rates (Fig. 11a), may implying the existence of positive feedback between TGM and microstructural anisotropy.” Should be “The sensitivity of Δε to accumulation rate is higher at lower accumulation rates (Fig. 11a), may imply the existence of positive feedback between TGM and microstructural anisotropy.”
Line 542: “The firn with more vertically elongated structure (created by TGM) become more permeable, thereby facilitating vertical vapor transport and potentially leading to stronger TGM (e.g., Albert, 2002).” Should be, “The firn with more vertically elongated structure (created by TGM) becomes more permeable, thereby facilitating vertical vapor transport and potentially leading to stronger TGM (e.g., Albert, 2002).”
Line 724: fieldworks should be fieldwork
Citation: https://doi.org/10.5194/egusphere-2023-1838-RC2 - AC1: 'Reply on RC2', Ryo Inoue, 30 Nov 2023
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Shuji Fujita
Kenji Kawamura
Ikumi Oyabu
Fumio Nakazawa
Hideaki Motoyama
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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