Review of

A comparison between Envisat and ICESat sea ice thickness in the Antarctic

by

Wang, Jinfei, et al.

Summary:

Compared to the Arctic there has been less focus on sea-ice thickness retrieval and evaluation in the Southern Ocean - albeit a few data sets have been produced in the meantime. This paper reports on results of a straightforward evaluation study in which a satellite radar altimeter (Envisat-RA2) sea-ice thickness data set is compared with a respective satellite laser altimeter (ICESat GLAS) data set; in addition both satellite data sets are compared with moored upward looking sonar data in the Weddell Sea. The methodology used is robust, the results achieved plausible. The study contains some reasonable attempts to describe reasons for the observed discrepancies between i) the ULS and the satellite data sets and ii) the two satellite data sets. The study is a useful contribution to the existing literature.

I think the manuscript is written sufficiently well. While I list 5 general comments, only one (number 4) is really a severe one I'd say, which might even require some additional experiments. Otherwise, these general comments attempt to give an umbrella for the various topics touched in my specific comments.

General Comments (GC):

GC1: The paper would benefit from considerable more clarity in the writing - as is expressed in a comparably large number of specific comments mostly refering to issues I had with the way things were written up. Here the authors need to work to avoid misunderstandings.

GC2: The comparison of the two satellite data sets would benefit from an even clearer description of what has been done and also from a better presentation of those parts of the data that were actually used for the comparison. This refers in particular to the large differences in the spatial coverage of end-of-summer SIT maps between Envisat and ICESat which I found confusing.

GC3: While the authors worked on understanding the uncertainties in the data sets used better, there is still room for improvement. One issue I have is that the ICESat data set used potentially is not the sea-ice thickness but the total, i.e. snow + sea-ice thickness, an issue which should i) be mentioned in the paper carefully and which should ii) find its way in the interpretation of the results in such a way, that in the discussion you point out that the true sea-ice thickness values from that ICESat data set are possibly even smaller than those used.

GC4: I have to admit that I am disappointed by the way the authors included the freezing degree day model results into their discussion. Both the representation in the figures and the interpretation are rather poor in my eyes and need some more attention if these are to be kept in the paper. Indeed FDD model results, when adequately converted into net sea-ice thickness growth (in meters), do add valuable information. But these require more careful interpretation in comparison to the observed sea-ice thickness which calls for additional data to be included: precipitation and large-scale ice drift information. 

GC5: At the end, I have a general suggestion with the style of your writing. It would read more fluently and more to the point if you would switch from passive to active mode. Example from line 17: Instead of writing "The inter-comparisons are conducted for the three seasons ..." write: "We compared results from three seasons ..."

Specific Comments: (I abbreviate Line with L)

Title: Since sea ice is an integral part of the Southern Ocean I suggest to use "Southern Ocean" instead of "Antarctic" ... perhaps even throughout the entire paper.

L50: At this point I suggest to provide a summary sentence which states that all these various data sets - despite covering limited regions and/or time periods - are extremely useful for the evaluation of models and satellite retrieval methods. I suggest to also differentiate between data sets that provide sea-ice thickness information at one fixed location (ULS) and hence allow to check the consistency over time, and data sets which have a short duration but with high resolution cover comparably large regions (e.g. Operation ice bridge or AEM) and hence allow to check the spatial variability of the sea-ice thickness retrieved from satellite data. 

L50-56: I suggest to reorganize this information a bit. First of all Kurtz and Markus 2012 and Li et al. 2018 utilize laster altimetry and hence fall into what you describe in the last sentence of the lines referred to here; this should somehow be merged. Secondly, Bernstein et al. is a paper about trying to estimate sea-ice thickness in the Ross/Amundsen Sea only from a very limited set of sea-ice charts. This data does not have the same value as the data sets of the other two papers cited in the same sentence.

L63/64: While I am totally fine with the sentence that snow affects radar altimetry SIT retrievals in two ways, you should first tell the reader the two ways before you come up with details of the shortcoming. First i) snow depth is required to a) correct the radar wave speed in snow and hence to appropriately convert the radar freeboard into the sea-ice freeboard and to b) convert sea-ice freeboard into sea-ice thickness. In both cases, but mostly in b) also the snow density plays a role. Secondly ii) the presence of snow simply modifies how the radar signal is reflected in / by the ice-snow system; the assumption of Beaven et al. is for DRY snow only. Hence, in addition to the more physical/mathematical influence of snow depth, there is this potential violation of the full-penetration assumption made by Beaven et al as is demonstrated by Willatt et al. These issues need to be specified first before you can come up with the details in Lines 65+

L81/82: Here you please need to check recent literature because Kwok and Kacimi or Kacimi and Kwok came up with more VERY useful work based on ICESat-2 data. You should include these references here as well - and ideally already point to the fact that the coverage with ICESat-2 is much better than with ICESat.

L106/107: If I am not mistaken, then the Paul et al reference point to some data analysis and algorithm development but is not specifically the reference to cite the sensor properties of Envisat RA-2. Please find a more appropriate reference which also details the footprint issue. I doubt that also Connor et al. 2009 is the adequate reference here. I am sure that are papers from the early 2000s when the altimeter was just up or about to be launched in which the system specifications are laid out well.

L115: It might make sense to add that Laxon et al. applied this method to ERS altimeter data, i.e. the predecessor of the Envisat RA-2 instrument.

L120/121: "revised version ... Cavalieri et al (2014)" I recommend to not refer to a data set description here but refer to the main core paper of the apporach used which is the one by Markus and Cavalieri, 1998, and then it is the Comiso et al (2003) reference which points to the AMSRE sea ice processing.

I suggest to make clear what the "revision" is (different tie point retrieval plus addition of retrieval errors). It would also be good if you could tell the reader on data of which years the snow depth climatology is based - because it extends well into the AMSR2 period. Finally, you may please change the URL into https://www.cen.uni-hamburg.de/icdc .

L122/123: "the actual SIT (... mean thickness ... of the grid cell area)" --> this does not go together well. The actual SIT would be the thickness of the ice floes as they float around in the grid cell. The mean SIT takes into account that the grid cell might not be fully covered by sea ice. Hence the actual SIT is always larger or equal than the mean SIT and it is important that you write this down in a clear way.

L138-140 / Eq. 3: I guess it is important to check this equation and the wording. If I am not mistaken, then the authors of these data claim on the respective web page that it is actually not the sea-ice thickness that is retrieved with this equation but it is the total (sea ice plus snow) thickness. Hence it is in a way the same type of thickness as is observed by that famous airborne EM sensor (see your introduction). In order to obtain the sea ice thickness from I retrieved using (3) one should possibly substract the snow depth and/or reformulate equation (3) such that this effect is somehow included.

L141: Please check whether this product contains the mean gridded sea-ice freeboard or whether this is perhaps in fact the total (sea ice + snow) freeboard.

L147: "at more than 900 m underwater" --> I don't think that this is a relevant information because the actual sensor is mounted further up anyways - otherwise the comparably small footprint would not be possible to achieve and the footprint would possibly also change between ULS sensor locations.

L166: When I look at Fig. 8 I have difficulties to fully understand what you did. First of all, the annotation in the Figure is opposite to what you write here. Secondly, what are the start and end days for the FDD computation using, e.g. the period from FM to MJ? The same question for MJ to ON. I find it strange and not easy to understand that you kept the FDD in degrees C and did not attempt to translate this into a net ice thickness growth. With that it remains a very qualitative comparison.

L167: "neglects ice growth from snowfall, freezing rain or ridging" --> I suggest to be more specific with your formulation. "snowfall" per se does not lead to ice growth. It requires the process of flooding. "freezing rain" does not trigger ice growth - at least not to my knowledge. While melting of ice crystals requires energy, formation of ice from undercooled water releases energy; hence freezing rain, although contributing millimeters of ice - mostly on top of snow - warms the snow / ice. Finally ridging is no form of ice growth. It causes dynamic thickening of the ice using ice which is already there.

L174-177: While this is possibly a good approach it leads to the observed partly considerably larger coverage with Envisat SIT data in Figs. 4 to 6, particularly Fig. 5, which at first glance is a bit puzzling. It is of course not relevant for the comparison as long as you only consider grid cells where both, Envisat and ICESat provide values. But as shown it implies that Envisat, e.g., has much more ice in summer 2005 (Ross Sea) or 2007 (several regions) but this is just because your Envisat SIT map shows data of the entire month, e.g. April, into which an ICESat period overlaps. You could include a comment about this into your text or, alternatively, only show Envisat SIT values where both satellites provide a SIT estimate.

L186-189: What is the motivation to use these sea-ice concentration data which I assume are based on the ASI algorithm? If you keep this product please make sure that you refer to the algorithm name and to also provide information about the native spatial resolution of this product (which is much finer than 100 km). It might also make sense to provide the URL to the data set web page at ICDC if there is any.

L207: The statement about the SIT uncertainties in the Worby 1-layer SIT data set is potentially not correct. I checked the data set and found uncertainties for both freeboard and thickness. Reading the paper Kern et al. 2016 it seems relatively clear that their computation of the SIT uncertainty included in the product is similar to their SICCI-2 SIT product from ICESat and hence based on uncertainties in densities and freeboard; only - and here you are correct - snow depth uncertainty is not included. You might want to rephrase you text accordingly. Also, if I am not mistaken, then the uncertainty estimates provided with the Envisat SIT data set are possibly too large because the data set producers those days did not adequately take potential correlations between the error contribution into account. I am quite sure that, for instance, for the currently available (from AWI) CS-2 sea-ice thickness data the uncertainty is considerably smaller than for the SICCI-2 project data set and I am sure the same applies to the Envisat RA-2 data set. But you have the producers among your co-authors. So you simply need to ask!

L215/216: I suggest to differentiate a bit better here between ICESat and Envisat - because Envisat provides a larger data set and hence your comparison is based on more data pairs.

While not possible for ICESat it would be possible for Envisat SIT to come up with a statement about the agreemen of the seasonal cycle. Do ULS and satellite data sets provide the same seasonal cycle qualitatively?

L221/222: "one satellite SIT grid cell is scanned only one of twice through a month" --> Please make sure to be more specific here. Not all these grid cells are covered only one / twice a month. Also this is valid for ICESat but possibly not for Envisat.

L225-227: "However ... fixed ULS positions." --> While I agree that thanks to the ice motion and the integration period used the ULS point measurement kind of gains a larger representativity, it might be worthwhile to check i) how large the ice drift actually was and what their average direction was. You could use the NSIDC V4.1 sea-ice motion data set to figure this out.

L237: Not clear what you mean by "The same feature is found ..." --> Are you referring to the existance of a polynya? Or are you referring to the fact that for both polynya regions, Ross Sea and Weddell Sea Envisat SIT is much higher than ICESat SIT? Please be more specific.

L239: "possibly fails ..." --> This is not a specific enough wording. There are two things involved with that. A) using a 100 km grid naturally results in a land mask at the same grid resolution. Hence it is very likely that the land mask used in the ICESat product extends further into the open ocean than the landmask which is used in the Envisat product. B) As stated in Kern and Spreen, it is not overly bad to not take ICESat freeboard estimates close to the coast not into acount because there the freeboard often is less accurate here compared to the open ocean due to various issues, mostly because of a lack of enough open leads detected by ICESat and hence a less accurate approximation of the local sea surface height and with that less accurate total freeboard.

L247/248: This apparent discrepancy could be mitigated by showing Envisat SIT only for those grid cells where ICESat has SIT values - as I mentioned earlier already. Otherwise it might be difficult to understand why the small difference between the sea-ice concentration thresholds used (60% vs. 70% ?) has such a large impact on the spatial coverage with SIT data.

L253-254: "probably ... resolve thick ice" --> while the statement made is correct for along-track data you need - in my eyes - to consider two issues here. The first one is that the ICESat product is gridded on a 100 km grid. Given the sparseness of ICESat overpasses with valid data such a 100 km grid SIT estimate in that region might be biased by the presence of thick landfast ice. The second one is that thanks to its finer along-track resolution ICESat can expected to be more sensitive to ocean swell. Ocean swell can result in anomalously high freeeboard values which then convert into too high sea-ice thickness values. While this is a local phenomenon again the sparseness of ICESat overpasses with valid data can results in a similar effect as described above for landfast ice.

Fig. 8: I am wondering whether you could perhaps change the color table used for the FDD. It is not intuitive. A high number of FDD denotes cold conditions while a low number comparably warm conditions. I suggest you use a color table which goes from white (0 FDD) to blue (3000degC FDD). Please check whether it is common to express FDD this way. I find it strange to read about temperatures of 1500 and 3000 deg C. Also switching to the unit Kelvin does not solve the problem; ideally, as mentioned earlier, you would translate this to a net growth of sea ice (in meters).

Did you check that the FDD shown for MJ-ON is in fact for that period and not for the full FM to ON period? Please note that the notation MJ-FM and ON-MJ is opposite to what you write in the text. Since you aim is to express that the maps in the right two columns show a SIT difference of, e.g. ON minus MJ you might need to invest more annotation elements to not confuse the reader.

L273/274: "This pattern ..." --> I suggest to add the fact that the thick ice found in the southwestern Weddell Sea at the end of summer is advected northward. If you look at the SIT distributions it is both the tail at large SIT which is decreasing and the tail at small SIT which is increasing. In the particular case you mention here, the thick old ice is replaced by the thin younger ice formed in the polynya (plus other comparably thin ice that is recirculated from the Eastern Weddell Sea in winter.

L274-276: "The adverse ... reveal them" --> I would have wished for a more detailed discussion here because one can interpret a lot from these maps - provided one takes into account knowledge about typical snow fall patterns and ice motion. Here you could substantially add some more interesting information and interpretation to your paper.

Fig. 9: Please add to the caption what the black line and the dashed colored lines stand for. 

You might also give the information whether you took data from all seasons available or whether we only look at data of years 2004, 2005 and 2006 as only from these years data from all three seasons are available from ICESat.

L322-326: Please note that the "nominal adjustement" suggested by Nandan et al. is derived for cases in the Arctic which might be special and not necessarily transferrable to the Southern Ocean. You could mitigate focussing too much on this exact value of 7 cm by providing a table into which you put sea-ice thickness changes in response to freeboard biases between 2 amd 10 cm in steps of 2 cm.

You choose typical first-year sea-ice density. Did you expereiment with other density values to see how dominant the freeboard change is compared to a density change? You could use densities between 880 and 940 kg/m3 in steps of 20 kg/m3 to illustrate this.

Why can the differences found here not also account for the differences between Envisat and ICESat in spring? And why do you consider the end of summer a season when this difference might apply?

L356-359: Please state that you took the same values for water and sea-ice density as in Eq. 5.

While your computation is of course correct, I am wondering whether the 2 cm bias assumed isn't a strong under-estimation. Yes, the analysis is based on monthly data, I agree. But the recommendation of Nandan et al you used in Eq. 5 is not tied to monthly data, is it? The monthly mean retrieval uncertainty you used should be considered the precision and not the potential bias which can be much larger - as you learned from Worby et al., Ozsoy-Cicek et al and as you could also see in the Kern and Ozsoy-Cicek paper in Remote Sensing from 2016; there we easily talk about 20 cm bias. Also te work of Kwok and Maksym from 2014 supports the notion that biases can be much higher over large regions. Hence, considering that also on a monthly scale the bias is an order of magnitude larger does not hurt and I invite you to, as suggested for Eq 5 provide a table into which you put sea-ice thickness changes in response to snow biases between 5 and 30 cm in steps of 5 cm; that would provide a much more realistic view of the potential bias due to using a snow depth data set that does not reflect the actual conditions.

L365-367: "While a snow ..." --> I agree to this and suggest to also stress one more time that sea-ice thickness differences you observe in your paper between different summer seasons (e.g. between Feb/Mar 2004, 2005, ... 2008) might, to a large extent, also simply be the result that the climatology does not match the actual conditions.

L374-386: You might want to mention here that possibly the approach by Kern et al. (2016) is providing the total (sea ice plus snow depth) thickness. Taking this into account, the actual 1-layer sea-ice thickness values shown in this paper would possibly even be a bit smaller - with the respective consequences for your results. See also my comments in the context of Eq. 3.

L402-404: "Compared to the FDD ..." --> In order to make this quite general statement you should investigate these maps in more detail and write more text in the respective section. See also my comments about your usage of FDD.

Editoral remarks / Typos:

L31: Actually, to obtain the sea-ice volume you need to combine the sea-ice thickness with the sea-ice area. I strongly recommend to change the working accordingly.

L57++: Please check the paper for the typo: CyroSat-2. It needs to read "CryoSat-2"

L104: "aboard on" --> either "aboard" or "on".

L112/113: "The delay correction ... " I suggest to delete this sentence here and instead add it in the discussion section when you discuss error sources / the uncertainties of the Envisat data.

L129: As ICESat is not operating anymore it is grammatically possibly more correct to write "lasted" instead of "lasts".

L153/154: "The uncertainty ... height calibration" --> I suggest to rewrite this: "The uncertainty in summer is smaller than in other seasons because open water occurs more frequently in the ULS footprint and with that the estimate of the sea surface height is more accurate.

L241/242: "However, ... near zero." -->perhaps better: "However, these differences have to be seen in the light of the standard deviations of ~0.6 m."

L258/259: "According to Table 5 ..." --> you could point out better that DESPITE the large difference and RMSD the correlation is actually the highest of the three seasons investigated.

L281: What are "splashes"?

L294/295: "though it is known ..." --> please support this knowledge with respective references.

L296: "footprint of" --> "footprint of the radar altimeter of"

L372: The perfect place for the Kwok and Maksym paper from 2014 (JGR-Oceans I think) and possibly for one of his more recent papers where he looked into ICESat-2.

L389/390: --> This sentence reads a bit strange in the context of what follows. My suggestion: "In this study, we compare estimates of the sea-ice thickness obtained from satellite altimeter observations by Envisat RA-2 (radar) and ICESat GLAS (laser) in the Southern Ocean." 

L391: "Envisat-ULS" --> please make sure the reader understands the "-" as a minus so that it is clear that ULS sea-ice thickness values are smaller than Envisat (and ICESat) values. Currently, this is not clear from the text.

L392: "The results ..." --> I don't understand this sentence in the context of the previous one. Consider to remove.

L394/395: "According ..." --> three time usage of difference / different. Consider to re-phrase.

L395/396: "difference of ... between Envisat SIT minus ICESat SIT" reads strange. Please consider re-phrasing.

I note: In contrast to L391 here you spell out the "-".

L406-408: You might want to re-phrase this sentence after you have considered by comments in the context of Eq. 5 and 6.

Figure 3: I suggest that you avoid to write "ENV-ULS" and the like because it is easily misinterpreted as a difference Envisat SIT minus ULS SIT which I doubt is the quantity you are showing here.

General comments:

This work compares the Antarctic sea ice thickness products by radar and laser altimetry with upward looking sonar and the meteorological indicator FDD as reference datasets, which has its specific value in estimating and understanding the two satellite altimetry products to some degree. However, since the two SIT products used in this study seems not consistent (with low correlation coefficients and high RMSDs) and even have opposite results, and the causes leading to the differences have not been analyzed thoroughly, more work is needed to be done before published in . The authors are encouraged to quantify and compare the various uncertainties of SIT by the two sensors, exhibiting the principle factors that cause the differences between the products, and even proposing a strategy or a method to assimilate the two kinds of altimetry to a decent degree (as stated by the authors in L411), which would be more worthwhile for the authors to dig into. Based on these considerations, I suggest to decline the paper at its current status. My comments are as follows:

Major concerns:

L90-92. I think the comparison of the two SIT products with ULS is not appropriate since the single measurement point (6-8 m) cannot represent a grid with 50 km or even 100 km. Moreover, only the uncertainty of sea ice draft derived with ULS 5-12 cm is presented (L152-153), the uncertainty of SIT derived with Eq. 4 is missing and Fig.3 also lacks error bars for ULS, thus making the comparison unreliable. “Both Envisat and ICESat SIT have been interpolated onto each ULS location in the nearest neighbour way” (L183-184) further introduces huge uncertainties. Based on these considerations, it is not recommended to use ULS as a comparison data source. ULS can be used if the Envisat or ICESat footprints spatio-temporally coincide with it, and the uncertainty of SIT derived with ULS is clear.

The difference between the Envisat-based actual SIT, i.e., the mean thickness of the ice-covered fraction of the grid cell area (without open water areas) (L122-123), and the ICESat effective sea ice thickness, i.e., mean thickness per grid cell including open water areas (L141-142), is not tackled nor discussed for the two datasets.

Considering the huge differences between Envisat and ICESat SIT products (as can be seen in Fig. 9 and Table 7), the main object of this work should not stay at just comparing those products, but concentrating on the qualitative and quantitative analysis of the causes leading to the differences. Currently, these issures are only simply discussed in Section 4. Following works may be considered by the authors:

• L253-254 About the sentence “Probably inferring that …” Is it really the key reason for SIT overestimation of Envisat than ICESat in autumn? The similar doubt also appears in summer (L262-263).
• L21 and L256-257. Why on earth the mean Envisat SIT decreases while the mean ICESat SIT increases from autumn to spring? This should be supported with supplement experiments.
• L360-361. “The largest effect might not come from the impact of ice deformation on the snow-depth retrieval but might be due to the difference between actual snow depth from that represented by the climatology.” Can the influence of climatology quantified?
• I didn’t see solid evidences supporting the statement “The potential overestimation of sea ice freeboard caused by range biases accounts for much of the differences between Envisat and ICESat SIT in summer and autumn, while the biases of snow depth are not the dominant cause of the differences.”

L124 The sea ice thickness derived with the modified ice density approach, i.e., Eq.3 can be considered to be updated to the new OLMi method (Xu, et al. (2021). "Deriving Antarctic Sea-Ice Thickness from Satellite Altimetry and Estimating Consistency for NASA's ICESat/ICESat-2 Missions." Geophysical Research Letters. http://dx.doi.org/10.1029/2021GL093425), which showed the modified ice density approach in Kern et al. (2016) would overestimate SIT.

Minor concerns:

L22-24 Please quantify the percentage of the uncertainties caused by the radar backscatter and snow depth products respectively.

L64 “the radar altimetry SIT retrievals” to “SIT retrieval by the radar altimetry”

Are the densities used in Eq. 1 and Eq.2/3 the same? If not, how does it influence the SIT retrieved by the two sensors?

L166 and L271 MF-MJ or MJ-MF? MJ-ON or ON-MJ? Please unify them throughout the paper, such as those 'MJ-ON' (in the text) or 'ON-MJ' (Fig. 8).

Why is it called snow depth climatology (L66, L118), snow-depth climatology (L119), or snow climatology (L363), and what is the real difference between them and the actual snow depth? Besides, what is the meaning of “have the character of a climatology” (L386)?

L270 “from the model” is unclear.

L274-276 I don't think it is an adverse pattern comparing MJ-ON with FM-MJ. Please also make "different abilities" clear.

L284-285 the weighted average is in the first row instead of in the last column?

L379-381. The sentence “Therefore, …the ice-snow column” is hard to understand. For example, “underestimations of sea ice and snow observations” is not clear, is it sea ice thickness and snow depth underestimation? What is the “apparent ice density”?

Fig.8 Suggest to use the same Antarctica background (in grey) as that in the other figures such as Fig. 4/5/6 since we can notice the big blank area along the Ross Sea coast in this figure.

Table 4 what's N? It should be introduced in the title. Same happens in Table 5/6/7.

Table 5. I suggest to also compute the difference between ENV and ICE at grid scale instead of just subtract with the computed statistical values (the “Difference” column). I mean, the mean of the third column of Figure 4/5/6 should be computed. Based on the figures, I think the two values would be different.

Table 6. “sea ice thickness differences” should be followed by “with standard deviation in brackets”

*General comments*

This manuscript presents an intercomparison of sea ice thickness derived from Envisat and ICESat satellite altimetry for the Southern Ocean, compared with sea ice thickness derived from draft observations from upward looking sonars (ULS) in the Weddell Sea. The comparison suggests a better agreement between ICESat and ULS sea ice thickness and differences between ICESat and Envisat, including differences in resolving the Ross Ice Shelf polynya, thicker ice in summer from Envisat than from ICESat, and differences in SIT variations from autumn to spring. The results are compared and discussed with the help of accumulative freezing-degree-days (FDD). 

The intercomparison of the ESA SICCI sea ice thickness products with independent sea ice thickness observations is very useful and contributes to our understading of the uncertanties and limitations of the datasets. Recently more focus has been on intercomparing the more recent CryoSat-2 part of this dataset, so this intercomparison of the Envisat period is particularly welcome. 

I would judge this manuscript good on the criteria for originality and significance. However, improvements can be made in the categories for scientific and presentation quality. I have some doubts on the methods used for retrieving sea ice thickness from freeboard observations. Why is a different threshold sea ice concentration used for both altimeters, and why is the updated method by Li et al. (2018) for ICESat not used? I also have doubts about comparing and discussing the differences due to the sensors and the snow depth by just looking at the sensitivity of the hydrostatic balance equation. It would be good to see an analysis of what the actual effect of using different snow depth products would be. 

The manuscript would also improve from a thorough read-through and rewrite of sentences that are now confusing or even causing misunderstanding. I have laid out my main comments and suggested technical corrections below. 

*Specific comments*

GC1: Why not use same snow product and methods for ICESat and Envisat? Now the discussion of the differences due to sensors and snow depth only include a sensitivity of the hydrostatic equilibrium to snow depth/freeboard, but not the actual effect. It would be an option to calculate sea ice thickness from ICESat with the AMSR-E snow depths as well so you can compare what part of the difference is a direct effect from the difference in sensors and what is caused by the difference in snow depth. I understand that this involves quite some more work, but I think a the statement that is now made in the summary (L406-408) is a bit strong for the amount of proof you have for this, as you've not made the actual comparison.

GC2: Why is a different sea ice concentration threshold used for ICESat (60%, L143) than for Envisat (70%, L123)?

GC3: In lines 381-386 you introduce an improvement of the method you have used to obtain ICESat sea ice thickness. What is the reason for not using this improved method?

GC4: L229: 'an overall comparison between Envisat and ICESat effective SIT'. In the methods it said the Envisat SIT product 'represents the actual SIT (i.e., mean thickness of the ice-covered fraction of the grid cell area)' (L122-123) and that the ICESat SIT product is the 'effective sea ice thickness (i.e., mean thickness per grid cell including open water ares)' (L141-142). Are these two products compared here? This would not be a fair comparison, as the effective sea ice thickness is by definition going to be thinner than the actual sea ice thickness. If you are comparing actual sea ice thickness products please clarify here and in the methods section. 

GC5: What values or products have been used for water, snow, and ice density in the calculations of sea ice thickness with Eq 1, Eq 2, and Eq 3? Are they the same for Envisat and ICESat? If not, discuss the effect on the results.

GC6: ULS and satellite altimetry SIT distributions would be interesting to see as well, if possible.

GC7: There are some significant issues with interpreting sentences throughout the manuscript. I have added some key examples below, but the clarity of the manuscript could improve from a thorough read-through. 

L77-78: 'Several freeboard- ... compared (Kern et al., 2016).' This sentence feels unrelated to the rest of the paragraph and is therefore confusing. If you want to go into this you need to explain the different retrieval algortihms. But I think it's better to leave this sentence out of the introduction and leave this to the methods (as you've explained this more clearly in section 2.2). 

L148-149: 'The signals ... travel time.' This sentence makes it sound like travel time is used to differentiate observations of sea ice bottom vs. sea surface, but I think you are trying to say that the distance is determined from the travel time measurement. It also sounds like only two measurements are made, one from the sea ice bottom and one from the sea surface. Please rewrite this. 

L254: 'ICESat is more sensitive to thick ice than Envisat', but the Envisat SIT product is thicker than ICESat? You describe this bias well in section 4.1, but here it's a bit confusing, as you seem to say that ICESat should show thicker ice.

L262: 'Envisat has a positive difference with respect to ICESat'. I do not understand what this means.

Have a look at the suggestions for technical corrections too.

*Techinical corrections*

L24: 'while the uncertainties of *the* snow depth product are' or 'while the uncertainties of snow depth product*s* are'

L30: 'it is still unclear if ... sea ice thickness'. Change 'also associated with' to 'accompanied by', these changes do not have to be related (or associated) but can be seperate.

L39-40: 'from the ASPeCt can provide' change to 'by the ASPeCt expert group can provide'

L42: 'airborne electromagnetic data which measure total freeboard', data don't measure things, maybe rephrase.

L52: Remove 'basically', this sounds very unscientific.

L54-55: Consider more recent studies that have retrieved Antarctic sea ice thickness, e.g. Kurtz & Markus (2012) and Kacimi & Kwok (2020).

L83-84: 'also how the different ... distribution.' Very vague, what are 'the different retrieval methods', ICESat and Envisat?

L88: 'the former inter-comparison study', which study is this?

L147: change 'underwater' to 'below sea level'

L150-151: 'once several minutes', do you mean 'every several minutes'? Please rewrite and maybe be more specific (what is several minutes)?

L153: seasons -> season

L166: 'FM-MJ and MJ-ON'. I guess you are referring to February/March-May/June and May/June-October/November. Please specify the first time you mention these abbreviations.

L182: 'Before ... first.' Repetitive, just use 'before' or 'first'.

L193: Remove 'during the comparison'.

L197: 'We provide ... SIT products.' Rewrite this sentence. I would suggest something like 'The error bars in the figure show the uncertainty estimates of/from the SIT products'. 

L197-200: 'The Envisat SIT ... Li et al., 2018).' Move these sentences to the methods? Also: I think adding an estimate of the ULS uncertainty to Figure 3 as well would improve the interpretation of this figure. You mentioned an estimate of the ULS uncertainty in L152-154. You now mention when the error bars of the altimetry sensors do not overlap with the ULS points, but it would be interesting to see if they do overlap with the ULS error bars. 

L207: Why are the uncertainties of freeboard and snow depth not considered for the ICESat SIT uncertainties?

L208-209: 'ICESat does not capture ... on thicker ice.' I'm not sure where I can see this in Figure 3?

L210: 'error bars can cover' -> remove 'can'

L210: 'However, since many contributions are not well characterized and quantified'. What contributions is this about and how are they not well characterized and quantified?

L225-226: 'considering the typical sea ice motion'. Briefly characterize this typical sea ice motion (fast, direction?), so the reader can see why the monthly average ULS SIT can be referred to as a spatial average value. 

L235: What are 'the ship-based observations'? This is not introduced in the paper before.

L237: change 'feature' to 'dissimilarity' or another more descriptive word.

L249: 'but with thickness estimates of up to 1.5 m'. Make sure it is clear to the reader that this is thinner than elsewhere. 

L264: 'the two datasets coincide with each other', this sounds a bit like they temporally coincide instead of the distributions being similar (which is I think what you want to say here). Please rewrite.

L269-270: 'We calculate the period-average SIT from the model'. This might be my lack of experience with freezing-degree-days: the FDD in Figure 8 and Table 6 show the total negative temperatures between these months right? I do not understand how it shows SIT. I understand that FDD and SIT are related but I don't see how the model actually calculates average SIT? Please make this more clear in the methods. If 'the model' is not FDD, maybe specify what model you mean?

L271: 'Envisat SIT has opposite developments from ICESat and FDD during MJ-ON'. Envisat and ICESat do not really show the opposite? They both show the strongest thinning in the western Weddell Sea and both show thickening near the coast in the Amundsen Sea. Please rewrite this to describe the difference, I think something like that Envisat shows more thinning all around the Southern Ocean and ICESat generally more thickening? 

L271, Figure 8, and Table 6: Please be consistent in how you refer to these periods (MJ-ON or ON-MJ and FM-MJ or MJ-FM). I would suggest for summer to autumn you use FM-MJ (instead of the subtraction MJ-FM you used in Figure 8) as this order is more intuitive. 

L272: 'both products', which two products? Envisat and ICESat, or satellite altimetry and FDD?

L274: 'The adverse patterns', adverse (preventing success or development; harmful; unfavourable) might not be the right word here? 

L279-280: 'the regression lines have large positive intercepts in all three seasons, indicating that Envisat SIT tends to exceed ICESat SIT for thin ice'. I can see in Figure 9 that this is true, but the latter does not necessarily follow from the former. A large positive intercept could also be caused by Envisat SIT being lower than ICESat SIT for thick ice. Again, in the figure I can see this is not the case here, but maybe just rephrase the explanation to just say 'For all five locations, Envisat SIT tends to exceed ICESat SIT for thin ice', without referring to the intercept.

L281: change 'splashes' to 'cloud' which is more often used to describe a collection of points in scatterplots. 'Exceed' in what way? Envisat or ICESat or both?

L284-285: 'The numbers in the last ... values per season'. This might be something to replace to the caption of the table. Also, in the table it does not look like this is in the last column, but in the first row? 

L294-295: 'it is known that ... homogenous stratigraphy'. This statement could use a citation.

L296: 'considering the large ... of about 70 m'. Maybe specify that the pulse-limited footprint is Envisat and the laser beams ICESat.

L341: maybe just say 'may come from the AMSR-E snow depth' here as you haven't yet discussed why it might be biased.

L347-348: 'the differences that AMSR-E snow depths minus the ASPeCt observations are positive ...', rephrase this sentence to something like 'AMSR-E snow depth minus the ASPeCt oservations is positive'

L349: 'the satellite passive microwave snow depth'. Maybe introduce AMSR-E as a passive microwave sensor in the methods, so readers that don't know the AMSR-E snow depth product know what you are referring to here.

L351: '... lead to underestimations' and '... lead to overestimations', under- and overestimations of what? SIT?

L357: The retrieval uncertainty of AMSR-E?

L357-358: 'suggesting that sea ice thickness change is insensitive to the snow depth', I would suggest change to 'the sensitivity is low', as SIT does change with snow depth, just not by a lot.

L363-364: 'The usage of snow climatology allows reducing the relative uncertainties', it's a bit unclear what these 'relative uncertainties' are and how they are reduced.

L389: Remove 'firstly'

L392: change 'not comparible to' to 'overestimating' or something else more descriptive of the difference between the two.

This paper presents a comparison of sea ice thickness estimates between Envisat and ICESat in the Southern Ocean. These estimates are further assessed with a comparison to upward looking sonar (ULS) data in the Weddell Sea. Results show that estimates from both satellites are in better agreement during the spring. The assessment with ULS data shows an overestimation of SIT from the satellites. This study aims to explore the possible factors responsible for the observed differences between the two satellite datasets and concludes that these differences are mostly explained by radar range biases rather than snow depth configuration for ice thickness retrieval. I believe this paper could represent a valuable contribution to the field of sea ice remote sensing as we have limited large scale observations of sea ice thickness in the Southern Ocean. However, I believe that more work needs to be done, I therefore recommend to decline the manuscript in its current state. See my comments below.

Major comments:

-One of my main concerns has to do with the actual validity and usefulness of the comparison between the satellite estimates and the ULS data. As clearly stated by the authors, there are significant differences in temporal and spatial sampling. The authors even point out that the results are not consistent. I believe it would be more beneficial to the paper to focus solely on the intercomparison between Envisat and ICESat data.

- Another major concern is the way that the comparison between the Envisat and ICESat-2 SIT is carried out. I think the paper would be more robust if a comparison of the actual freeboards and snow depths (total freeboards for ICESat) was introduced. The assumption made on snow depth can have a huge impact on the mean and variability of the derived sea ice thickness.

- While the authors explored the possible causes of the observed differences between the two satellite datasets, I think this should be looked at more carefully and in more detail. Based on their uncertainty analysis, the authors conclude that most of the bias is probably explained by radar penetration issues. I do not believe that the authors successfully demonstrated this, especially given that the assumptions on snow depth and snow density are different for the two instruments.

- Some of the phrasing needs to be reviewed carefully. Especially in the introductory part of the paper, some sentences are poorly constructed and lack clarity. It challenges the understanding of the paper.

Minor comments:

P1L9: the sentence” The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness” does not really mean anything. Maybe you mean that thickness is important to evaluate the role of Antarctic sea ice in the global climate system?

P1L10-11: What do you mean by “on a hemispheric scale, satellite radar altimetry data can be applied with a promising prospect”? Do you mean that large scale estimates of SIT are achievable with radar altimetry? Again revise the wording to make clearer statements.

P1L28: Replace “declines” by “decline”.

P2L59: Replace “CyroSat-2” by “CryoSat-2”.

P2L60-61: I suggest rephrasing this sentence:” The SICCI product covers the entire Antarctic sea ice for the complete annual cycle from 2002 to 2017, and it is finally a combined data set of Envisat and CyroSat-2” to “The SICCI product is derived using measurements from Envisat and CryoSat-2 and covers the entire Antarctic sea ice for the complete annual cycle from 2002 to 2017”.

P3L76:” This data set has been investigated for many years”. I believe this dataset has been used in several investigations, not investigated.

P4L94:”between the two datasets” please specify that you are referring to the satellite data.

P5L127: Replace “are conducted with” by “are characterized by”

P6L163: Replace “derived” by “from”

P6L171: Please revise:” For each period, we choose the corresponding time period during which Envisat monthly data are used”.

P6, L175-177: Please revise :” The weighting has taken into account periods where only Envisat SIT of one month are present, i.e., we use this equation for grid cells where we have valid SIT data from both months, while we only use the Envisat SIT of the respective month without weighing for those grid cells where we only have valid data from either month.”.

P8L236: I suggest to replace “Envisat does not show the young ice in the Ross Sea” by “Thin ice in the Ross Sea is not captured by Envisat”.

P9L244-255: Revise “Compared to summer, the differences in the western Weddell Sea spread to the whole Weddell Sea sector and decrease from west to east.”. The statement is not clear.

P12L345: Replace “Previous study reveals” by “Previous studies show”.

P14L389: Remove “Firstly”. The comparison to ULS data is carried out first.

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