the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Clouds drive differences in future surface melt over the Antarctic ice shelves
- 1Department of Geography, UR SPHERES, University of Liège, Belgium
- 2Univ. Grenoble Alpes/CNRS/IRD/G-INP, IGE, Grenoble, France
- 3Department of Geosciences, University of Oslo, Oslo, Norway
- 4Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- 5Department of Meteorology, University of Reading, Whiteknights Rd, Reading, United Kingdom
- 6Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Études de la Neige, Grenoble, France
- 1Department of Geography, UR SPHERES, University of Liège, Belgium
- 2Univ. Grenoble Alpes/CNRS/IRD/G-INP, IGE, Grenoble, France
- 3Department of Geosciences, University of Oslo, Oslo, Norway
- 4Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- 5Department of Meteorology, University of Reading, Whiteknights Rd, Reading, United Kingdom
- 6Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Études de la Neige, Grenoble, France
Abstract. Recent warm atmospheric conditions have damaged the ice shelves of the Antarctic Peninsula through surface melt and hydrofracturing, and could potentially initiate future collapse of other Antarctic ice shelves. However, model projections with similar greenhouse gas scenarios suggest large differences in cumulative 21st century surface melting. So far it remains unclear whether these differences are due to variations in warming rates in individual models, or whether local surface energy budget feedbacks could also play a notable role. Here we use the polar-oriented regional climate model MAR to study the physical mechanisms that will control future melt over the Antarctic ice shelves in high-emission scenarios RCP8.5 and SSP585. We show that clouds enhance future surface melt by increasing the atmospheric emissivity and longwave radiation towards the surface. Furthermore, we highlight that differences in meltwater production for the same climate warming rate depend on cloud properties and particularly cloud phase. Clouds containing a larger amount of liquid water lead to stronger melt, subsequently favouring the absorption of solar radiation due to the snow-melt-albedo feedback. By increasing melt differences over the ice shelves in the next decades, liquid-containing clouds could be a major source of uncertainties related to the future Antarctic contribution to sea level rise.
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Christoph Kittel et al.
Status: closed
-
RC1: 'Comment on tc-2021-263', Anonymous Referee #1, 08 Oct 2021
Review of Kittel et al.
This manuscript is a well written paper that presents the potential uncertainties we might expect in future surface melt predictions due to the role of clouds. The manuscript is well constructed and uses state-of-the-art regional climate model data but simply passes many of the complexities related to the surface melt – albedo feedback. Before this study can be published the authors should consider a much more careful analysis of the contemporary surface melt production, including a robust evaluation of clouds and their phase-differences. In addition, other influencers of the surface albedo feedbacks should at least be mentioned, such as the role of precipitation (snow + rain!) and the role of cloudy and clear-sky conditions. Below I will divide my comments into major and minor comments and hope to explain my concerns.
Major comments
1. Surface melt and cloud evaluation
The major thing missing in this manuscript is a careful evaluation. Yes, the authors cite several of the studies evaluating MAR energy fluxes, SMB and surface melt rates. However, (future) surface melting is extremely sensitive, especially the role of clouds and their phases. See for instance King et al., 2015 and the study of one of the authors Gilbert et al., 2020. I would like to see more convincing evidence that contemporary melting is accurately modelled and for the right reasons (you yourself note the effects of compensating errors) and that the surface albedo feedback is (reasonably) correct. How does MAR represent surface melting in cloudy conditions and in clear-sky conditions? There are ample ways to improve and extend the surface melt evaluation with this paper. An example is Jakobs et al., 2020, which provides a state-of-the-art evaluation dataset publicly accessible against which the contemporary melt climate modelled by MAR can be tested.
In addition, before any weight can be given to the modelled cloud fractions, contemporary cloud fractions should be evaluated in more detail. Examples to do this are the Van Tricht et al., 2016 and Lenaerts et al. 2017 papers (I’m not aware if updates of these products are available yet). They provide extensive Antarctica-wide products of liquid and solid water clouds, against which cloud fractions of MAR can be tested.
2. The role of snowfall and rain
This study solely looks at the radiative fluxes and their role in influencing surface melt production. However, especially in a future climate, precipitation rates are also going to increase, including a change in the fractions of rain and snow. Where obviously rain should be added to the surface melt rates (is it?) rain and snow also affect the melt-albedo feedback in several ways. This effect should be discussed. As of now, snow- or rainfall is not even mentioned once in the manuscript, while its relation to clouds is rather obvious. Additionally, a discussion can be added how future precipitation itself is influenced by cloud fraction, as it is likely just as important for ice shelf stability in a future climate as surface melting is.
3. Regional climate
Throughout the manuscript ice sheet wide averages are used, even though about 30% to 50% of all (contemporary) surface melt occurs in the Antarctic Peninsula. Not only will the numbers presented therefore not be completely representative of all Antarctic ice shelves and the Antarctica Peninsula climate will dominate your results, you are also losing a lot of the local climate signals by averaging this way.
It is known (King et al., 2015 and other studies) that the surface energy budget (and hence melting) is heavily influenced by the partitioning of ice/water cloud particles, and that this process is very uncertain (like is concluded by yourselves) and very local. Some attention should therefore be spent on how these processes are governed elsewhere in Antarctica; e.g. do the same sensitivities exist over other ice shelves than Larsen C ice shelf? Some regional case studies should be performed to strengthen the conclusions in this study.
4. Are the melt differences really due to clouds?
If I am not mistaken, the only forcing parameters from the ESMs that directly influence cloud phase and fractions are temperature and specific humidity. Hence, the results of this study mainly highlight the different equilibrium states of MAR given a set of forcing conditions, as you state in Section 3.2.1. Then, it is not completely clear to what extent the results are related to the actual cloud physics, or just to a different climate state that corresponds with a different cloud setup, including influences of other internal feedbacks you are not discussing. I would like to see some more discussion about this and the fact that the results you present are not due to differences in model physics, but due to differences in forcing conditions. What cloud differences do we see in the forcing ESMs themselves? Are they similar or does MAR really change the cloud behavior? In other studies such as King et al., 2015 or specific ESM intercomparison studies, differences in clouds are really due to differences in model physics which strengthen the case that the cloud representation in climate models should be improved, but that is not the case in this study. Your concluding remark: “…our study stresses the need to improve cloud representation in climate models to better constrain SLR projections” therefore does not really relate to the results of this study.
Minor comments
P1l10-12: What do you mean by “increasing melt differences”? Do liquid containing clouds increase the melt differences, or do you mean something else? Please rephrase.
P2l17: If you emphasize surface albedo, you should also note the effects of snowfall and fresh snow albedo due to differences in cloud(cover)
P2l36: “Bright surfaces”. Why does this matter? You do not come back to this
P2l36-44: This paragraph is not logically arranged. You note the lack of observations but you do not repeat this and why do high ECSs matter? Try to rephrase and shorten this paragraph.
P2l43: The term RCM should be introduced here, after you did introduce the ESMs. And how is an ESM not polar oriented, and a high-resolution model is polar oriented?
P2L61-62: “correctly represents present Antarctic surface melt” -> “present-day” and this should be much shown in much more detail. Compensating errors might result in a correct modelling of surface melt production, but a more comprehensive study should be done. For instance: if the compensating errors are due to compensating clear-sky and cloudy conditions, your results will be hard to believe. Try to show that the contemporary contribution of cloud radiative feedbacks to the surface melt is accurately modelled.
P3l63: “compensating errors” is too vague. Just leave this sentence as “This suggest a correct representation of the SEB, but….”
P3L64-66: “the projected spread in melt” comes out of the blue; can you introduce this in more detail as it is the focus of this manuscript?
P5L126: You average over the ESMs as well? This is not completely clear.
P5L132: Why are you using cumulative numbers? Either convert them into SLR equivalents, or just use the climatological averages in mmWE or Gt…These very large numbers are hard to interpret
P5L138: Same as above but now with cumulative fluxes. How to interpret a cumulative flux of 443.7 W?
P7L153: Some latex errors here?
P7L156-159: Sensible heat can be a very local effect and might be smoothed out by your choice of presenting Antarctica wide averages. Your results might be dominated by the Antarctic Peninsula, which has the largest melt rates by far. It would be interesting to add a bit more regional studies to this study and grasp whether the LWN/SWN – melt correlation is consistent and homogenous across the continent.
P8L185-190: Why so many supplementary Figures referenced? If you need them in the main manuscript, use them! TC has no figure limit, and they can easily be added as an additional column in Fig.2 as well. (this argument holds for all other references of supplementary figures in the rest of the paper).
P10L217: Sentence is unclear. I do not see the value 0.7 reached and surely not by 2040-2060.
P12L260: What is the effect of rain? Should you add this to the melt flux? As this is very important for surface albedo. (and more..)
P12L264: Again, please consider the effects of precip (snow and rain) on the surface albedo
P12L268: Isn’t this strong increase in CNRM-CR6 (not also) explained by the larger amounts of liquid precipitation?
P13L274: Again, I think the influence of precipitation changes should not be passed
Figures:
Figure 1: What is the colorbar for 1b, and what is the orange coloring we see?
Figure 2: What is happening with CC in CNRM from 2060 onwards?
Figure 4-6: Isn’t there a way to combine these plots (and make room for some of the supplementary figures to be included in the main?)
References
- King, J. C., Gadian, A., Kirchgaessner, A., Kuipers Munneke, P., Orr, A., Reijmer, C., Broeke, M. R., Van Wessem, J. M., and Weeks, M. (2015). Validation of the summertime surface energy budget of Larsen C Ice Shelf (Antarctica) as represented in three high-resolution atmospheric models. Journal of Geophysical Research: Atmospheres, 120(4), 1335–1347. doi:10.1002/2014JD022604.
- Jakobs, C. L., Reijmer, C. H., Smeets, C. J. P. P., Trusel, L. D., Van De Berg, W. J., Van Den Broeke, M. R., and Van Wessem, J. M. (2020). A benchmark dataset of in situ Antarctic surface melt rates and energy balance. Journal of Glaciology, 66(256), 291–302. doi:10.1017/jog.2020.6. issn:00221430.
- Van Tricht, K., Lhermitte, S., Gorodetskaya, I. V., and van Lipzig, N. P. M. (2016). Improving satellite-retrieved surface radiative fluxes in polar regions using a smart sampling approach. The Cryosphere, 10(5), 2379–2397. doi:10.5194/tc-10-2379-2016. issn:1994-0424.
- Lenaerts, J. T. M., Van tricht, K., Lhermitte, S., and L’Ecuyer, T. S. (2017). Polar clouds and radiation in satellite observations, reanalyses, and climate models. Geophysical Research Letters. doi:10.1002/2016GL072242. issn:19448007.
- AC1: 'Reply on RC1', Christoph Kittel, 04 Jan 2022
-
RC2: 'Comment on tc-2021-263', Rajashree Datta, 11 Oct 2021
This manuscript presents an analysis of the importance of cloud properties in driving surface melt over Antarctic ice shelves in the future (to 2100) , comparing these to a 1981-2010 reference period. This uses the MAR model forced at the boundaries with 4 ESMs (ACCESS1.3, NorESM-1-M, CRNM-CM6-1 and CESM2) in the RCP8.5 (for CMIP5 models) and SSP585 (for CMIP6 models). The authors examine potential drivers for surface melt beginning with energy balance components, identify the importance of clouds, and present a strong analysis of properties which contribute most to differences in melt produced by each ESM-forced-version of MAR. I commend the authors on a very well-organized argument and believe that this will eventually be a strong contribution to the understanding of future surface melt in Antarctica, although several important aspects are currently missing, which could be addressed with additional figures and analysis.
Specific Comments:
1) The integration of all ice shelves may be hiding processes which vary spatially
As an example, the authors specifically admit that the SEB is impacted by SHF values only in certain regions. We note that one such region is the Larsen C ice shelf, where a substantial amount of total surface melt occurs. At the 35 km spatial resolution, surface melt would necessarily be poorly-represented over the Larsen C ice shelf in this version of MAR. A more meaningful analysis (making this manuscript an excellent companion to Gilbert and Kittel, 2021) would be to essentially conduct the organisation of this study, but with ice shelves divided regionally.
For plots (i.e. Figures 2,4, 6, S1, S2) these would benefit from a map showing differences ( as in Fig. S3). We note that on line 164, the authors mention the thickening of the future planetary boundary layer over ice shelves of West Antarctica – it would be relevant to show whether this was demonstrated in East Antarctica as well independently.
Additionally, it would be beneficial to see similar maps of averaged values for forcing fields (in Supplemental Figures) to illustrate the spatial characteristic of the differences in forcing. By integrating, we have no picture on the spatial characteristics which are driving this (i.e. are the differences in moisture at lower altitudes vs higher altitudes dominant in West Antarctica but not East Antarctica)
2) A more rigorous account of changes in albedo
The differences in albedo are mentioned briefly, but this seems to be a major driver in the overall differences shown, and there is no discussion about how this impacted by snowfall events. While I think that a thorough examination of precipitation trends is outside the scope of this manuscript, an analysis of albedo differences (in a map) as well as snowfall differences (in a map) would strengthen the manuscript significantly.
3) A greater discussion of biases in cloud properties that are present in historical runs of MAR
To my knowledge, none of the evaluations of MAR present a comparison of biases in cloud properties (as compared to observations, i.e. CALIPSO). If I’ve missed something, a reference and a short discussion would be relevant. If not, then some level of validation of MAR’s representation of cloud properties in the historical record would be directly germaine to this study.
Technical Corrections:
L 42: I could not find the reference to lower future melt changes in ESMs in Kittel et al., 2021. Could the authors clarify (identify a figure/section)?
L 61: Use of the word “correct” twice in proximity. Additionally. I would suggest, “presents well” as opposed to “correctly”. Additionally, Kittel et al., 2021 refers to future runs, rather than an evaluation of a historical run. Perhaps referencing Agosta et al., 2019 would be more accurate.
L 64: “difficult to assess”. This is a good way to declare this complexity without making dishonest claims. Thanks for that.
L 110: Make clearer exactly how these melt projections used climate models.
L 171: Awkward sentence. Suggestion: “This could be explained by accounting for the ECS capturing the greater warming over the Antarctic region simulated by CNRM-CM6-1 (+8.5°C vs 7.7°C for CESM2 in 2100 compared to 1981-2010).
L 173: replace “this ESM” with “CRNM-CM6-1” for clarity
L 176: relatively – (remove dash)
L 182: “suggests a low influence on LWD”. Clarify the discrepancy by comparing the quantity
L 206: “southern” == “austral”
L 210: Why are clear and cloud sky conditions treated separately? Could you clarify the reason or separate the analysis accordingly?
L 220: Could you demonstrate the saturation of LWD for large COD increases in supplemental?
Sincerely,
R. Tri Datta
- AC2: 'Reply on RC2', Christoph Kittel, 04 Jan 2022
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RC3: 'Comment on tc-2021-263', Anonymous Referee #3, 14 Oct 2021
The authors provide an overview of the driving forces of surface melt over the ice shelves over Antarctica. Although the work is mainly confirming the results of other studies, it is one of the first to provide a quantitative assessment of these driving forces towards the future, which is a step forward in the scientific understanding of how models interact with the surface.
Main comments:
- The paper is well structured & contains a lot of interesting information regarding the representation of melt in future simulations. One aspect that is not discussed however is the effect of precipitation on surface melt. A higher number of clouds would possibly also result in higher preciptiation numbers, which would increase the surface albedo. This counteracts part of the warming induced by the increase in liquid clouds and LWD. It would be nice to see the contribution of precipitation and surface albedo in the results.
- The paper mainly discusses averages changes towards the future. However, most of the large melting occurs during 'events' nowadays. With the increase in general surface temperatures towards the future, I am wondering if these individual melt events become of lesser / higher importance & that individual events will still be the driver of most melt or that temperatures will increase to such a level that melt will occur during the whole summer.
The paper is clear and well written, i only have a few specific comments: :
- When first reading the title of the paper, I immediately thought of the paper of Van Tricht (https://doi.org/10.1038/ncomms10266). Despite dealing about a similar subject (although another ice sheet), I think a reference to this work is valid somewhere in the introduction. A same set of techniques is also used in the methodology & results section and in the discussion, one could relate to the differences between the Greenland & Antarctic Ice Sheet
- Specify on line 134 that NorEsm is the lowest range model & CNRM is the upper range (instead of line 140)
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AC3: 'Reply on RC3', Christoph Kittel, 04 Jan 2022
The comment was uploaded in the form of a supplement: https://tc.copernicus.org/preprints/tc-2021-263/tc-2021-263-AC3-supplement.pdf
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AC3: 'Reply on RC3', Christoph Kittel, 04 Jan 2022
Status: closed
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RC1: 'Comment on tc-2021-263', Anonymous Referee #1, 08 Oct 2021
Review of Kittel et al.
This manuscript is a well written paper that presents the potential uncertainties we might expect in future surface melt predictions due to the role of clouds. The manuscript is well constructed and uses state-of-the-art regional climate model data but simply passes many of the complexities related to the surface melt – albedo feedback. Before this study can be published the authors should consider a much more careful analysis of the contemporary surface melt production, including a robust evaluation of clouds and their phase-differences. In addition, other influencers of the surface albedo feedbacks should at least be mentioned, such as the role of precipitation (snow + rain!) and the role of cloudy and clear-sky conditions. Below I will divide my comments into major and minor comments and hope to explain my concerns.
Major comments
1. Surface melt and cloud evaluation
The major thing missing in this manuscript is a careful evaluation. Yes, the authors cite several of the studies evaluating MAR energy fluxes, SMB and surface melt rates. However, (future) surface melting is extremely sensitive, especially the role of clouds and their phases. See for instance King et al., 2015 and the study of one of the authors Gilbert et al., 2020. I would like to see more convincing evidence that contemporary melting is accurately modelled and for the right reasons (you yourself note the effects of compensating errors) and that the surface albedo feedback is (reasonably) correct. How does MAR represent surface melting in cloudy conditions and in clear-sky conditions? There are ample ways to improve and extend the surface melt evaluation with this paper. An example is Jakobs et al., 2020, which provides a state-of-the-art evaluation dataset publicly accessible against which the contemporary melt climate modelled by MAR can be tested.
In addition, before any weight can be given to the modelled cloud fractions, contemporary cloud fractions should be evaluated in more detail. Examples to do this are the Van Tricht et al., 2016 and Lenaerts et al. 2017 papers (I’m not aware if updates of these products are available yet). They provide extensive Antarctica-wide products of liquid and solid water clouds, against which cloud fractions of MAR can be tested.
2. The role of snowfall and rain
This study solely looks at the radiative fluxes and their role in influencing surface melt production. However, especially in a future climate, precipitation rates are also going to increase, including a change in the fractions of rain and snow. Where obviously rain should be added to the surface melt rates (is it?) rain and snow also affect the melt-albedo feedback in several ways. This effect should be discussed. As of now, snow- or rainfall is not even mentioned once in the manuscript, while its relation to clouds is rather obvious. Additionally, a discussion can be added how future precipitation itself is influenced by cloud fraction, as it is likely just as important for ice shelf stability in a future climate as surface melting is.
3. Regional climate
Throughout the manuscript ice sheet wide averages are used, even though about 30% to 50% of all (contemporary) surface melt occurs in the Antarctic Peninsula. Not only will the numbers presented therefore not be completely representative of all Antarctic ice shelves and the Antarctica Peninsula climate will dominate your results, you are also losing a lot of the local climate signals by averaging this way.
It is known (King et al., 2015 and other studies) that the surface energy budget (and hence melting) is heavily influenced by the partitioning of ice/water cloud particles, and that this process is very uncertain (like is concluded by yourselves) and very local. Some attention should therefore be spent on how these processes are governed elsewhere in Antarctica; e.g. do the same sensitivities exist over other ice shelves than Larsen C ice shelf? Some regional case studies should be performed to strengthen the conclusions in this study.
4. Are the melt differences really due to clouds?
If I am not mistaken, the only forcing parameters from the ESMs that directly influence cloud phase and fractions are temperature and specific humidity. Hence, the results of this study mainly highlight the different equilibrium states of MAR given a set of forcing conditions, as you state in Section 3.2.1. Then, it is not completely clear to what extent the results are related to the actual cloud physics, or just to a different climate state that corresponds with a different cloud setup, including influences of other internal feedbacks you are not discussing. I would like to see some more discussion about this and the fact that the results you present are not due to differences in model physics, but due to differences in forcing conditions. What cloud differences do we see in the forcing ESMs themselves? Are they similar or does MAR really change the cloud behavior? In other studies such as King et al., 2015 or specific ESM intercomparison studies, differences in clouds are really due to differences in model physics which strengthen the case that the cloud representation in climate models should be improved, but that is not the case in this study. Your concluding remark: “…our study stresses the need to improve cloud representation in climate models to better constrain SLR projections” therefore does not really relate to the results of this study.
Minor comments
P1l10-12: What do you mean by “increasing melt differences”? Do liquid containing clouds increase the melt differences, or do you mean something else? Please rephrase.
P2l17: If you emphasize surface albedo, you should also note the effects of snowfall and fresh snow albedo due to differences in cloud(cover)
P2l36: “Bright surfaces”. Why does this matter? You do not come back to this
P2l36-44: This paragraph is not logically arranged. You note the lack of observations but you do not repeat this and why do high ECSs matter? Try to rephrase and shorten this paragraph.
P2l43: The term RCM should be introduced here, after you did introduce the ESMs. And how is an ESM not polar oriented, and a high-resolution model is polar oriented?
P2L61-62: “correctly represents present Antarctic surface melt” -> “present-day” and this should be much shown in much more detail. Compensating errors might result in a correct modelling of surface melt production, but a more comprehensive study should be done. For instance: if the compensating errors are due to compensating clear-sky and cloudy conditions, your results will be hard to believe. Try to show that the contemporary contribution of cloud radiative feedbacks to the surface melt is accurately modelled.
P3l63: “compensating errors” is too vague. Just leave this sentence as “This suggest a correct representation of the SEB, but….”
P3L64-66: “the projected spread in melt” comes out of the blue; can you introduce this in more detail as it is the focus of this manuscript?
P5L126: You average over the ESMs as well? This is not completely clear.
P5L132: Why are you using cumulative numbers? Either convert them into SLR equivalents, or just use the climatological averages in mmWE or Gt…These very large numbers are hard to interpret
P5L138: Same as above but now with cumulative fluxes. How to interpret a cumulative flux of 443.7 W?
P7L153: Some latex errors here?
P7L156-159: Sensible heat can be a very local effect and might be smoothed out by your choice of presenting Antarctica wide averages. Your results might be dominated by the Antarctic Peninsula, which has the largest melt rates by far. It would be interesting to add a bit more regional studies to this study and grasp whether the LWN/SWN – melt correlation is consistent and homogenous across the continent.
P8L185-190: Why so many supplementary Figures referenced? If you need them in the main manuscript, use them! TC has no figure limit, and they can easily be added as an additional column in Fig.2 as well. (this argument holds for all other references of supplementary figures in the rest of the paper).
P10L217: Sentence is unclear. I do not see the value 0.7 reached and surely not by 2040-2060.
P12L260: What is the effect of rain? Should you add this to the melt flux? As this is very important for surface albedo. (and more..)
P12L264: Again, please consider the effects of precip (snow and rain) on the surface albedo
P12L268: Isn’t this strong increase in CNRM-CR6 (not also) explained by the larger amounts of liquid precipitation?
P13L274: Again, I think the influence of precipitation changes should not be passed
Figures:
Figure 1: What is the colorbar for 1b, and what is the orange coloring we see?
Figure 2: What is happening with CC in CNRM from 2060 onwards?
Figure 4-6: Isn’t there a way to combine these plots (and make room for some of the supplementary figures to be included in the main?)
References
- King, J. C., Gadian, A., Kirchgaessner, A., Kuipers Munneke, P., Orr, A., Reijmer, C., Broeke, M. R., Van Wessem, J. M., and Weeks, M. (2015). Validation of the summertime surface energy budget of Larsen C Ice Shelf (Antarctica) as represented in three high-resolution atmospheric models. Journal of Geophysical Research: Atmospheres, 120(4), 1335–1347. doi:10.1002/2014JD022604.
- Jakobs, C. L., Reijmer, C. H., Smeets, C. J. P. P., Trusel, L. D., Van De Berg, W. J., Van Den Broeke, M. R., and Van Wessem, J. M. (2020). A benchmark dataset of in situ Antarctic surface melt rates and energy balance. Journal of Glaciology, 66(256), 291–302. doi:10.1017/jog.2020.6. issn:00221430.
- Van Tricht, K., Lhermitte, S., Gorodetskaya, I. V., and van Lipzig, N. P. M. (2016). Improving satellite-retrieved surface radiative fluxes in polar regions using a smart sampling approach. The Cryosphere, 10(5), 2379–2397. doi:10.5194/tc-10-2379-2016. issn:1994-0424.
- Lenaerts, J. T. M., Van tricht, K., Lhermitte, S., and L’Ecuyer, T. S. (2017). Polar clouds and radiation in satellite observations, reanalyses, and climate models. Geophysical Research Letters. doi:10.1002/2016GL072242. issn:19448007.
- AC1: 'Reply on RC1', Christoph Kittel, 04 Jan 2022
-
RC2: 'Comment on tc-2021-263', Rajashree Datta, 11 Oct 2021
This manuscript presents an analysis of the importance of cloud properties in driving surface melt over Antarctic ice shelves in the future (to 2100) , comparing these to a 1981-2010 reference period. This uses the MAR model forced at the boundaries with 4 ESMs (ACCESS1.3, NorESM-1-M, CRNM-CM6-1 and CESM2) in the RCP8.5 (for CMIP5 models) and SSP585 (for CMIP6 models). The authors examine potential drivers for surface melt beginning with energy balance components, identify the importance of clouds, and present a strong analysis of properties which contribute most to differences in melt produced by each ESM-forced-version of MAR. I commend the authors on a very well-organized argument and believe that this will eventually be a strong contribution to the understanding of future surface melt in Antarctica, although several important aspects are currently missing, which could be addressed with additional figures and analysis.
Specific Comments:
1) The integration of all ice shelves may be hiding processes which vary spatially
As an example, the authors specifically admit that the SEB is impacted by SHF values only in certain regions. We note that one such region is the Larsen C ice shelf, where a substantial amount of total surface melt occurs. At the 35 km spatial resolution, surface melt would necessarily be poorly-represented over the Larsen C ice shelf in this version of MAR. A more meaningful analysis (making this manuscript an excellent companion to Gilbert and Kittel, 2021) would be to essentially conduct the organisation of this study, but with ice shelves divided regionally.
For plots (i.e. Figures 2,4, 6, S1, S2) these would benefit from a map showing differences ( as in Fig. S3). We note that on line 164, the authors mention the thickening of the future planetary boundary layer over ice shelves of West Antarctica – it would be relevant to show whether this was demonstrated in East Antarctica as well independently.
Additionally, it would be beneficial to see similar maps of averaged values for forcing fields (in Supplemental Figures) to illustrate the spatial characteristic of the differences in forcing. By integrating, we have no picture on the spatial characteristics which are driving this (i.e. are the differences in moisture at lower altitudes vs higher altitudes dominant in West Antarctica but not East Antarctica)
2) A more rigorous account of changes in albedo
The differences in albedo are mentioned briefly, but this seems to be a major driver in the overall differences shown, and there is no discussion about how this impacted by snowfall events. While I think that a thorough examination of precipitation trends is outside the scope of this manuscript, an analysis of albedo differences (in a map) as well as snowfall differences (in a map) would strengthen the manuscript significantly.
3) A greater discussion of biases in cloud properties that are present in historical runs of MAR
To my knowledge, none of the evaluations of MAR present a comparison of biases in cloud properties (as compared to observations, i.e. CALIPSO). If I’ve missed something, a reference and a short discussion would be relevant. If not, then some level of validation of MAR’s representation of cloud properties in the historical record would be directly germaine to this study.
Technical Corrections:
L 42: I could not find the reference to lower future melt changes in ESMs in Kittel et al., 2021. Could the authors clarify (identify a figure/section)?
L 61: Use of the word “correct” twice in proximity. Additionally. I would suggest, “presents well” as opposed to “correctly”. Additionally, Kittel et al., 2021 refers to future runs, rather than an evaluation of a historical run. Perhaps referencing Agosta et al., 2019 would be more accurate.
L 64: “difficult to assess”. This is a good way to declare this complexity without making dishonest claims. Thanks for that.
L 110: Make clearer exactly how these melt projections used climate models.
L 171: Awkward sentence. Suggestion: “This could be explained by accounting for the ECS capturing the greater warming over the Antarctic region simulated by CNRM-CM6-1 (+8.5°C vs 7.7°C for CESM2 in 2100 compared to 1981-2010).
L 173: replace “this ESM” with “CRNM-CM6-1” for clarity
L 176: relatively – (remove dash)
L 182: “suggests a low influence on LWD”. Clarify the discrepancy by comparing the quantity
L 206: “southern” == “austral”
L 210: Why are clear and cloud sky conditions treated separately? Could you clarify the reason or separate the analysis accordingly?
L 220: Could you demonstrate the saturation of LWD for large COD increases in supplemental?
Sincerely,
R. Tri Datta
- AC2: 'Reply on RC2', Christoph Kittel, 04 Jan 2022
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RC3: 'Comment on tc-2021-263', Anonymous Referee #3, 14 Oct 2021
The authors provide an overview of the driving forces of surface melt over the ice shelves over Antarctica. Although the work is mainly confirming the results of other studies, it is one of the first to provide a quantitative assessment of these driving forces towards the future, which is a step forward in the scientific understanding of how models interact with the surface.
Main comments:
- The paper is well structured & contains a lot of interesting information regarding the representation of melt in future simulations. One aspect that is not discussed however is the effect of precipitation on surface melt. A higher number of clouds would possibly also result in higher preciptiation numbers, which would increase the surface albedo. This counteracts part of the warming induced by the increase in liquid clouds and LWD. It would be nice to see the contribution of precipitation and surface albedo in the results.
- The paper mainly discusses averages changes towards the future. However, most of the large melting occurs during 'events' nowadays. With the increase in general surface temperatures towards the future, I am wondering if these individual melt events become of lesser / higher importance & that individual events will still be the driver of most melt or that temperatures will increase to such a level that melt will occur during the whole summer.
The paper is clear and well written, i only have a few specific comments: :
- When first reading the title of the paper, I immediately thought of the paper of Van Tricht (https://doi.org/10.1038/ncomms10266). Despite dealing about a similar subject (although another ice sheet), I think a reference to this work is valid somewhere in the introduction. A same set of techniques is also used in the methodology & results section and in the discussion, one could relate to the differences between the Greenland & Antarctic Ice Sheet
- Specify on line 134 that NorEsm is the lowest range model & CNRM is the upper range (instead of line 140)
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AC3: 'Reply on RC3', Christoph Kittel, 04 Jan 2022
The comment was uploaded in the form of a supplement: https://tc.copernicus.org/preprints/tc-2021-263/tc-2021-263-AC3-supplement.pdf
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AC3: 'Reply on RC3', Christoph Kittel, 04 Jan 2022
Christoph Kittel et al.
Christoph Kittel et al.
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