the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Mar 2021
Thermodynamic processes affecting the winter sea ice changes in the Bering Sea in the Norwegian Earth System Model
Abstract. The Arctic sea ice has changed largely over the last decades and is expected to change in the future. In this study, we assess sea ice changes in the Pacific sector of the Arctic in an Earth System Model. In winter, the first Empirical Orthogonal Function of sea ice concentration in the Pacific sector of the Arctic based on observations are significantly opposite to that in the Atlantic sector during a period from 1976 to 2004, describing 13.4 % of the total Arctic winter sea ice variability. The similar pattern is also confirmed in the Norwegian Earth System Model (NorESM1-M) (15.8 %). Thermodynamics is found to be vital to winter sea ice variability. In this study, we analyze the relationships between some thermodynamical processes (congelation ice, frazil ice, bottom and top ice melting, and conversion of snow to ice) and sea ice changes in the Bering Sea, based on the NorESM1-M coupled climate model results. All these studied thermodynamical processes can influence the variability in winter sea ice concentration and thickness in the Bering Sea. Considering the mean seasonal cycle over the 30-year time period, conversion of snow to ice contributes about 69 % to the increase in sea ice mass during winter in the Bering Sea, and it is thus the main source to the growth of the winter sea ice in NorESM1-M in the Bering Sea. On the interannual time scales, winter sea ice concentration and thickness variability in the Bering Sea are highly related with the studied thermodynamic processes. Among these thermodynamic processes, congelation ice shows the most important effect on the simulated variability in the Bering Sea, especially in the northeastern part.
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Interactive discussion
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RC1: 'Comment on os-2021-16', Anonymous Referee #1, 08 Apr 2021
The authors use NorESM to study changes in the sea ice in the Bering Sea. In particular they examine thermodynamic processes impact on ice concentration and thickness in this region and find that thermodynamic processes are highly related to sea ice mean state and variability. They also find that snow-ice conversion is the dominant contribution to increasing winter ice mass in this region. I have major concerns with the study’s methods as well as their results and cannot recommend publication. Details follow below.
Major concerns
- My biggest concern with the author’s methods is that they list that they’re looking at NorESM1-M, part of the CMIP5 models, from 1979-2005. One of the most important findings in climate science is the importance of using multiple ensembles over the historical period to adequately capture the inherent climate variability of the climate system (e.g. Kay et al. 2011; Jahn et al. 2016). The authors say that they’re looking at “the historical experiment” but there’s no mention of how many ensemble members they’re using and the impact of internal variability. The authors should use at a minimum 3 ensemble members, but ideally at least 10-15 if possible. The authors imply that the simulation well matches PIOMAS (Fig.3) but it really shouldn’t if it’s a single iteration and even an ensemble mean shouldn’t exactly match PIOMAS because of the inherent climate variability but the PIOMAS data should be within the spread of the model variability in ice volume. Additionally, since CMIP6 data, including submissions from NorESM, are widely and freely available now the authors should consider moving the analysis to those datasets.
- The authors find that snow-to-ice conversion is the largest contributor to mass increase for NorESM (Table 1, Figure 4, Figure 9). This is surprising and exactly opposite from what many, many other studies of the Arctic sea ice mass budget have found (e.g. Keen et al. 2020, Holland et al. 2010). The lack of snow-ice dominating the correlation (Fig.5) with sea ice concentration and thickness in January, suggests again that there is something wrong with what the authors are seeing if it is the dominant term but not positively correlated with the ice state. I suspect that there’s some error in the authors’ code and that the order of magnitude is off for snow-ice. Additionally, as I mention above, examining the Arctic sea ice mass budget, including thermodynamic terms, has been done before including with more recent model releases, so I don’t really know what new that authors are contributing. So at line 196 when the authors say “we have shown thermodynamic processes are important for BS in January”, this is obvious since it has been long established that sea ice tendencies are driven by thermodynamic and dynamic processes, so of course the thermodynamics are likely important even though the authors didn’t do any dynamics term analysis.
Minor concerns
- You need a more detailed description of the NorESM model used including the sea ice model (CICE) and what the model provides or what its limitations are.
- Line 43: You say “The freezing (melting) of sea ice will absorb (release) heat”, which is exactly opposite to what happens with energy exchange during freezing and melting.
- Line 125-130: Congelation growth is on the bottom of any established ice. What do you mean congelation volume may determine an ice floe? Time of sea water to ice? What?
- Line 211 doesn’t make sense.
- Figure 2. In the caption you say that the Bering Sea is 0-18W longitude, which is not correct. Additionally, you’re really looking at ice fraction, not concentration. You need to multiply by 100 and then the units are %.
- Figure 4: You could use better color bars and labeling of what we’re seeing in this map because the land masses and Bering Strait are not clear. Additionally, you should mask snow-ice where ice concentration is less than 15% because you’re implying there is ice growth well into the North Pacific where there is now sea ice.
- Fig 5c – The positive correlation between bottom melt and ice concentration and thickness needs to be better described. I think what you’re seeing is that bottom melt is negative, so an increasing value means less bottom melt and then it makes sense that the concentration or thickness would increase as well. But this is poorly described.
References
Holland, M. M., Serreze, M. C., & Stroeve, J. (2008). The sea ice mass budget of the Arctic and its future change as simulated by coupled climate models. Climate Dynamics, 34, 185–200. https://doi.org/10.1007/s00382-008-0493-4
Jahn, A., Kay, J. E., Holland, M. M., & Hall, D. M. (2016). How predictable is the timing of a summer ice-free Arctic? Geophysical Research Letters, 43(17), 9113–9120. https://doi.org/10.1002/2016GL070067
Kay, J. E., Holland, M. M., & Jahn, A. (2011). Inter-annual to multi-decadal Arctic sea ice extent trends in a warming world. Geophysical Research Letters, 38(15). https://doi.org/10.1029/2011GL048008
Keen, A., Blockley, E., Bailey, D., Boldingh Debernard, J., Bushuk, M., Delhaye, S., et al. (2020). An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models (preprint). Sea ice/Sea Ice. https://doi.org/10.5194/tc-2019-314
Citation: https://doi.org/10.5194/os-2021-16-RC1 -
RC2: 'Comment on os-2021-16', Anonymous Referee #2, 12 May 2021
Review of the manuscript “Thermodynamic processes affecting the winter sea ice changes in the
Bering Sea in the Norwegian Earth System Model” by Huiling Zou et al. [OS-2021-16]
General comments:
The authors examined the role of the thermodynamic process on the wintertime sea ice variability in the Bering Sea, which is the Pacific-side of the seasonal sea ice region in the Arctic, based on the CMIP-type model output under the present climate condition for the past several decades. In this study, the authors diagnostically examined the simulated outputs of the sea ice growth rate and melting processes on seasonal to interannual timescales, and found that the seasonal cycle of the sea ice volume is determined by snow ice formation process and the interannual variability of sea ice is well explained by the thermodynamic process due to congelation ice formation process.
The physical process controlling the sea ice distribution in the Bering Sea has been investigated by many researchers through statistical examination of atmosphere-ice variables (Sasaki and Minobe, 2005) and an ice-ocean coupled model simulation technique (Zhang et al. 2010). Although the importance of the congelation ice in the Bering Sea is consistent with the above research, the importance of snow ice on the Bering sea ice fluctuations seems to be new and this study actually promotes the understanding of future projection of sea ice cover in the seasonal sea ice region and contributes to the climate modeling community. However, the several results of statistical analyses based on climate model simulation and their interpretations are still questionable for me. I feel, therefore, major revisions are required for the recommendation to be published in Ocean Science.
Major comments:
- The authors evaluated the representation of sea ice variability derived from the historical experiment of NorESM1-M by using the EOF analysis of sea ice concentration in the Northern Hemisphere. However, this study focuses on only the Bering Sea ice variability and thus the authors should evaluate the reliability of the simulated sea ice variability based on the EOF analysis of sea ice concentration in the Bering Sea. Moreover, I recommend to evaluate the representation of ocean temperature and current fields in NorESM1-M, because the sea ice advance in the Bering Sea is highly influenced by ocean heat advection (e.g., Nakanowatari et al. 2015, Stabeno et al. 2017).
- The authors examined the influence of the thermodynamic process on wintertime sea ice variability based on the climate model outputs, and found that a large amount of the sea ice fluctuation is explained by the thermodynamic process. However, an ice-ocean coupled modeling study pointed out that the wind-induced sea ice drift is crucial for the sea ice advance in the offshore area in winter (Zhang et al., 2010). Therefore, the authors should discuss the weakness of the sea ice drift process in NorESM1-M. I guess that the model resolution of NorESM1-M might underestimate the influence of the sea ice drift due to the insufficient representation of sea ice velocity and ocean current system.
- Based on the statistical analysis between sea ice area and the thermodynamic process derived from NorESM1-M, the authors found that the interannual variability of sea ice is well explained by the thermodynamic process due to congelation ice formation. However, I suppose that this term includes the sea ice formation at the interface between atmosphere and ocean, which is known to be a large contribution on the sea ice variability (Zhang et al. 2010). Since this term does not appeared in this sea ice model, the authors should make effort to explain the configuration of the sea ice model and the derived term in details in section 2.2 or 2.3.
- The authors found that the conversion of snow to ice process is crucial for the seasonal evolution of sea ice in the Bering Sea. This result seems to be new finding, but the supportive information such as snow fall rate seems to be lack in this paper. If this result is a main body in this study, the authors should show the observed evidence or additional results to support the importance of the snow ice in the Bering Sea.
Minor comments:
- Line 11: Please specify the season focused in this study here.
- Lines 12-14: Although the authors present the result for EOF analysis based on sea ice concentration in the Arctic region, the meaning of this result is not clear for me. I recommend that the authors should describe the result for the evaluation of the simulated SIC variability in the Bering Sea.
- Line 26-29: Please specify the season focused in this section at first, because the possible mechanism for the Arctic sea ice change is different in season and area. The authors provide the information of the possibility of the active role of the sea ice reduction in winter on the climate change in lower latitudes, but the description seems to be insufficient. The authors carefully should describe the possible mechanisms of the linkage between the Arctic sea ice reduction and the mid-latitude climate by citing the earlier studies (e.g., Honda et al. 2009; Inoue et al. 2012; Petoukhov and Semenov 2010; Vihma 2014; Screen 2014; Cohen et al. 2014; Mori et al. 2014).
- Line 30: dynamic mechanism -> thermodynamic mechanism?
- Line 32: The authors describe the role of the remote influence of atmospheric and ocean process related to the NAO on the Arctic sea ice change, but the description seems to be insufficient for some readers. Please describe the finding shown in the earlier study more clearly.
- Line 36: The authors introduce the research papers for interannual variability in the Barents Sea and the Greenland Sea and the importance of ocean heat transport as driving force of sea ice variability. These earlier studies seem to be the motivation of this study, but these studies are not related to the Bering Sea. So far, the interannual variability of wintertime sea ice area in the Bering Sea has been investigated by many researchers by using numerical modeling (Zhang et al., 2010) and observational data (Overland and Pease, 1982; Sasaki and Minobe, 2005; Nakanowatari et al., 2015). The authors should explain the remained questions and motivation of your study based on these earlier studies.
- Line 40: Although the author used the CMIP type model output in this study, the motivation of the usage of the CMIP-type model output is unclear for me. Please describe the reason why the CMIP-type model is used in this study.
- Line 60: The authors show the EOF patterns for the observed SIC in winter in the Northern Hemisphere during 1976-2004 with positive anomalies in the Bering sea and Greenland Sea and negative anomalies in the Okhotsk Sea and Barents-Kara seas, but this anomalous sea ice pattern has already been reported by Yamamoto et al. (2006, GRL) based on the observed SIC data. Therefore, the authors should show the EOF analysis of SIC based on NorESM1-M and discuss the validity of the simulated sea ice data (Please see general comment #1).
- Line 92: Please add the model configuration of NorESM1-M used in this study (what kind of the sea ice model, atmospheric model, ocean model including their spatial resolution), although the authors cited the reference. Also, the authors should describe the reason why this CMIP type model output is adopted in this study.
- Line 101: The authors evaluate the NorESM1-M sea ice conditions by comparing with the observed SIC or PIOMAS outputs. Overall, it seems that the NorESM1-M has non negligible bias on sea ice conditions in the Bering Sea on seasonal to interannual timescales. The authors should explain the validity of the NorESM1-M sea ice conditions for your purpose, here.
- Line 120: Please move this sentence about earlier study (Sandø et al., 2014) to the introduction section, because this study is quite important motivation for your study.
- Line 155: In terms of sea ice … -> The monthly mean sea ice mass increase is …
- Line 162: In this paragraph, the authors show the spatial distribution of sea ice formation type and found that the conversion of snow to ice is prominent in the northwestern BS. Since this result is interesting and seems to be new finding in this study, the authors should explore the possible cause of the dominance of snow ice, which is also related to bottom ice melting, in this area. I suppose that the snow fall rate and ocean heat flux seems to be crucial for the conversion of snow to ice.
- Line 179: The authors examined the effect of thermodynamic process on the sea ice variability (SIC and thickness) in the Bering Sea in January by lead-lag correlation analysis. However, I suppose that the thermodynamic process in February-March is not needed to be examined, because the SIC in January does not lead the sea ice formation in the following months.
- Line 186: The authors mentioned the correlation between SIC and the bottom ice melting is -0.75, but Figure 5a shows the positive value.
- Line 199: Since this sentence is somewhat abrupt, it may be moved to the next section.
- Line 211: …that the increase in sea ice concentration is accompanied with the decrease in surface air temperature…?
- Line 212: opposite -> positive?
- Line 216: Figure 5e -> Figure 6e
- Line 215: The authors mentioned that the interannual variability of SIC is well explained by the congelation ice, which is caused by the local surface air temperature based on the correlation map. I guess that the turbulent heat flux is a main factor for the local sea ice production and thus sea ice concentration. However, the authors mentioned that the correlation between the sensible (and/or latent heat flux) and sea ice change in BS is very low (Line 134). Could the authors explain the physical meaning of the negative correlation between surface air temperature and congelation ice and/or sea ice concentration?
- Line 226: The authors discuss the imbalance between sea ice formation and melting rate in January, but I suppose that the dominance of sea ice formation is natural in winter season.
- Lines 224-235: Overall this paragraph includes quite complicated logic. Therefore, it is very difficult for me to follow the point of this paragraph.
- Line 227: In the seasonally covered regions -> In seasonal sea ice zone
- Figure 2: the reanalysis datasets -> the observed datasets
- Figure 2: Please change the unit for the SIC from 0-1 to 0-100%.
- Figure 2: The additional map for the climatological raw SIC value (%) would be helpful for readers.
- Figure 3: Since the year-to-year variability has no meaning in this comparison, I recommended that the spatial pattern for the climatological SIT distribution in winter is shown here despite of the time series of PIOMAS and NorESM1-M.
- Figure 4: The original sign seems to be better in panel c.
- Figure 4: The additional information for the spatial distribution of total ice mass would be helpful for readers.
- Figure 9: red line-> purple line
- Table 1: The additional column for the total sea ice mass in each month is helpful for readers.
Citation: https://doi.org/10.5194/os-2021-16-RC2
Interactive discussion
Status: closed
-
RC1: 'Comment on os-2021-16', Anonymous Referee #1, 08 Apr 2021
The authors use NorESM to study changes in the sea ice in the Bering Sea. In particular they examine thermodynamic processes impact on ice concentration and thickness in this region and find that thermodynamic processes are highly related to sea ice mean state and variability. They also find that snow-ice conversion is the dominant contribution to increasing winter ice mass in this region. I have major concerns with the study’s methods as well as their results and cannot recommend publication. Details follow below.
Major concerns
- My biggest concern with the author’s methods is that they list that they’re looking at NorESM1-M, part of the CMIP5 models, from 1979-2005. One of the most important findings in climate science is the importance of using multiple ensembles over the historical period to adequately capture the inherent climate variability of the climate system (e.g. Kay et al. 2011; Jahn et al. 2016). The authors say that they’re looking at “the historical experiment” but there’s no mention of how many ensemble members they’re using and the impact of internal variability. The authors should use at a minimum 3 ensemble members, but ideally at least 10-15 if possible. The authors imply that the simulation well matches PIOMAS (Fig.3) but it really shouldn’t if it’s a single iteration and even an ensemble mean shouldn’t exactly match PIOMAS because of the inherent climate variability but the PIOMAS data should be within the spread of the model variability in ice volume. Additionally, since CMIP6 data, including submissions from NorESM, are widely and freely available now the authors should consider moving the analysis to those datasets.
- The authors find that snow-to-ice conversion is the largest contributor to mass increase for NorESM (Table 1, Figure 4, Figure 9). This is surprising and exactly opposite from what many, many other studies of the Arctic sea ice mass budget have found (e.g. Keen et al. 2020, Holland et al. 2010). The lack of snow-ice dominating the correlation (Fig.5) with sea ice concentration and thickness in January, suggests again that there is something wrong with what the authors are seeing if it is the dominant term but not positively correlated with the ice state. I suspect that there’s some error in the authors’ code and that the order of magnitude is off for snow-ice. Additionally, as I mention above, examining the Arctic sea ice mass budget, including thermodynamic terms, has been done before including with more recent model releases, so I don’t really know what new that authors are contributing. So at line 196 when the authors say “we have shown thermodynamic processes are important for BS in January”, this is obvious since it has been long established that sea ice tendencies are driven by thermodynamic and dynamic processes, so of course the thermodynamics are likely important even though the authors didn’t do any dynamics term analysis.
Minor concerns
- You need a more detailed description of the NorESM model used including the sea ice model (CICE) and what the model provides or what its limitations are.
- Line 43: You say “The freezing (melting) of sea ice will absorb (release) heat”, which is exactly opposite to what happens with energy exchange during freezing and melting.
- Line 125-130: Congelation growth is on the bottom of any established ice. What do you mean congelation volume may determine an ice floe? Time of sea water to ice? What?
- Line 211 doesn’t make sense.
- Figure 2. In the caption you say that the Bering Sea is 0-18W longitude, which is not correct. Additionally, you’re really looking at ice fraction, not concentration. You need to multiply by 100 and then the units are %.
- Figure 4: You could use better color bars and labeling of what we’re seeing in this map because the land masses and Bering Strait are not clear. Additionally, you should mask snow-ice where ice concentration is less than 15% because you’re implying there is ice growth well into the North Pacific where there is now sea ice.
- Fig 5c – The positive correlation between bottom melt and ice concentration and thickness needs to be better described. I think what you’re seeing is that bottom melt is negative, so an increasing value means less bottom melt and then it makes sense that the concentration or thickness would increase as well. But this is poorly described.
References
Holland, M. M., Serreze, M. C., & Stroeve, J. (2008). The sea ice mass budget of the Arctic and its future change as simulated by coupled climate models. Climate Dynamics, 34, 185–200. https://doi.org/10.1007/s00382-008-0493-4
Jahn, A., Kay, J. E., Holland, M. M., & Hall, D. M. (2016). How predictable is the timing of a summer ice-free Arctic? Geophysical Research Letters, 43(17), 9113–9120. https://doi.org/10.1002/2016GL070067
Kay, J. E., Holland, M. M., & Jahn, A. (2011). Inter-annual to multi-decadal Arctic sea ice extent trends in a warming world. Geophysical Research Letters, 38(15). https://doi.org/10.1029/2011GL048008
Keen, A., Blockley, E., Bailey, D., Boldingh Debernard, J., Bushuk, M., Delhaye, S., et al. (2020). An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models (preprint). Sea ice/Sea Ice. https://doi.org/10.5194/tc-2019-314
Citation: https://doi.org/10.5194/os-2021-16-RC1 -
RC2: 'Comment on os-2021-16', Anonymous Referee #2, 12 May 2021
Review of the manuscript “Thermodynamic processes affecting the winter sea ice changes in the
Bering Sea in the Norwegian Earth System Model” by Huiling Zou et al. [OS-2021-16]
General comments:
The authors examined the role of the thermodynamic process on the wintertime sea ice variability in the Bering Sea, which is the Pacific-side of the seasonal sea ice region in the Arctic, based on the CMIP-type model output under the present climate condition for the past several decades. In this study, the authors diagnostically examined the simulated outputs of the sea ice growth rate and melting processes on seasonal to interannual timescales, and found that the seasonal cycle of the sea ice volume is determined by snow ice formation process and the interannual variability of sea ice is well explained by the thermodynamic process due to congelation ice formation process.
The physical process controlling the sea ice distribution in the Bering Sea has been investigated by many researchers through statistical examination of atmosphere-ice variables (Sasaki and Minobe, 2005) and an ice-ocean coupled model simulation technique (Zhang et al. 2010). Although the importance of the congelation ice in the Bering Sea is consistent with the above research, the importance of snow ice on the Bering sea ice fluctuations seems to be new and this study actually promotes the understanding of future projection of sea ice cover in the seasonal sea ice region and contributes to the climate modeling community. However, the several results of statistical analyses based on climate model simulation and their interpretations are still questionable for me. I feel, therefore, major revisions are required for the recommendation to be published in Ocean Science.
Major comments:
- The authors evaluated the representation of sea ice variability derived from the historical experiment of NorESM1-M by using the EOF analysis of sea ice concentration in the Northern Hemisphere. However, this study focuses on only the Bering Sea ice variability and thus the authors should evaluate the reliability of the simulated sea ice variability based on the EOF analysis of sea ice concentration in the Bering Sea. Moreover, I recommend to evaluate the representation of ocean temperature and current fields in NorESM1-M, because the sea ice advance in the Bering Sea is highly influenced by ocean heat advection (e.g., Nakanowatari et al. 2015, Stabeno et al. 2017).
- The authors examined the influence of the thermodynamic process on wintertime sea ice variability based on the climate model outputs, and found that a large amount of the sea ice fluctuation is explained by the thermodynamic process. However, an ice-ocean coupled modeling study pointed out that the wind-induced sea ice drift is crucial for the sea ice advance in the offshore area in winter (Zhang et al., 2010). Therefore, the authors should discuss the weakness of the sea ice drift process in NorESM1-M. I guess that the model resolution of NorESM1-M might underestimate the influence of the sea ice drift due to the insufficient representation of sea ice velocity and ocean current system.
- Based on the statistical analysis between sea ice area and the thermodynamic process derived from NorESM1-M, the authors found that the interannual variability of sea ice is well explained by the thermodynamic process due to congelation ice formation. However, I suppose that this term includes the sea ice formation at the interface between atmosphere and ocean, which is known to be a large contribution on the sea ice variability (Zhang et al. 2010). Since this term does not appeared in this sea ice model, the authors should make effort to explain the configuration of the sea ice model and the derived term in details in section 2.2 or 2.3.
- The authors found that the conversion of snow to ice process is crucial for the seasonal evolution of sea ice in the Bering Sea. This result seems to be new finding, but the supportive information such as snow fall rate seems to be lack in this paper. If this result is a main body in this study, the authors should show the observed evidence or additional results to support the importance of the snow ice in the Bering Sea.
Minor comments:
- Line 11: Please specify the season focused in this study here.
- Lines 12-14: Although the authors present the result for EOF analysis based on sea ice concentration in the Arctic region, the meaning of this result is not clear for me. I recommend that the authors should describe the result for the evaluation of the simulated SIC variability in the Bering Sea.
- Line 26-29: Please specify the season focused in this section at first, because the possible mechanism for the Arctic sea ice change is different in season and area. The authors provide the information of the possibility of the active role of the sea ice reduction in winter on the climate change in lower latitudes, but the description seems to be insufficient. The authors carefully should describe the possible mechanisms of the linkage between the Arctic sea ice reduction and the mid-latitude climate by citing the earlier studies (e.g., Honda et al. 2009; Inoue et al. 2012; Petoukhov and Semenov 2010; Vihma 2014; Screen 2014; Cohen et al. 2014; Mori et al. 2014).
- Line 30: dynamic mechanism -> thermodynamic mechanism?
- Line 32: The authors describe the role of the remote influence of atmospheric and ocean process related to the NAO on the Arctic sea ice change, but the description seems to be insufficient for some readers. Please describe the finding shown in the earlier study more clearly.
- Line 36: The authors introduce the research papers for interannual variability in the Barents Sea and the Greenland Sea and the importance of ocean heat transport as driving force of sea ice variability. These earlier studies seem to be the motivation of this study, but these studies are not related to the Bering Sea. So far, the interannual variability of wintertime sea ice area in the Bering Sea has been investigated by many researchers by using numerical modeling (Zhang et al., 2010) and observational data (Overland and Pease, 1982; Sasaki and Minobe, 2005; Nakanowatari et al., 2015). The authors should explain the remained questions and motivation of your study based on these earlier studies.
- Line 40: Although the author used the CMIP type model output in this study, the motivation of the usage of the CMIP-type model output is unclear for me. Please describe the reason why the CMIP-type model is used in this study.
- Line 60: The authors show the EOF patterns for the observed SIC in winter in the Northern Hemisphere during 1976-2004 with positive anomalies in the Bering sea and Greenland Sea and negative anomalies in the Okhotsk Sea and Barents-Kara seas, but this anomalous sea ice pattern has already been reported by Yamamoto et al. (2006, GRL) based on the observed SIC data. Therefore, the authors should show the EOF analysis of SIC based on NorESM1-M and discuss the validity of the simulated sea ice data (Please see general comment #1).
- Line 92: Please add the model configuration of NorESM1-M used in this study (what kind of the sea ice model, atmospheric model, ocean model including their spatial resolution), although the authors cited the reference. Also, the authors should describe the reason why this CMIP type model output is adopted in this study.
- Line 101: The authors evaluate the NorESM1-M sea ice conditions by comparing with the observed SIC or PIOMAS outputs. Overall, it seems that the NorESM1-M has non negligible bias on sea ice conditions in the Bering Sea on seasonal to interannual timescales. The authors should explain the validity of the NorESM1-M sea ice conditions for your purpose, here.
- Line 120: Please move this sentence about earlier study (Sandø et al., 2014) to the introduction section, because this study is quite important motivation for your study.
- Line 155: In terms of sea ice … -> The monthly mean sea ice mass increase is …
- Line 162: In this paragraph, the authors show the spatial distribution of sea ice formation type and found that the conversion of snow to ice is prominent in the northwestern BS. Since this result is interesting and seems to be new finding in this study, the authors should explore the possible cause of the dominance of snow ice, which is also related to bottom ice melting, in this area. I suppose that the snow fall rate and ocean heat flux seems to be crucial for the conversion of snow to ice.
- Line 179: The authors examined the effect of thermodynamic process on the sea ice variability (SIC and thickness) in the Bering Sea in January by lead-lag correlation analysis. However, I suppose that the thermodynamic process in February-March is not needed to be examined, because the SIC in January does not lead the sea ice formation in the following months.
- Line 186: The authors mentioned the correlation between SIC and the bottom ice melting is -0.75, but Figure 5a shows the positive value.
- Line 199: Since this sentence is somewhat abrupt, it may be moved to the next section.
- Line 211: …that the increase in sea ice concentration is accompanied with the decrease in surface air temperature…?
- Line 212: opposite -> positive?
- Line 216: Figure 5e -> Figure 6e
- Line 215: The authors mentioned that the interannual variability of SIC is well explained by the congelation ice, which is caused by the local surface air temperature based on the correlation map. I guess that the turbulent heat flux is a main factor for the local sea ice production and thus sea ice concentration. However, the authors mentioned that the correlation between the sensible (and/or latent heat flux) and sea ice change in BS is very low (Line 134). Could the authors explain the physical meaning of the negative correlation between surface air temperature and congelation ice and/or sea ice concentration?
- Line 226: The authors discuss the imbalance between sea ice formation and melting rate in January, but I suppose that the dominance of sea ice formation is natural in winter season.
- Lines 224-235: Overall this paragraph includes quite complicated logic. Therefore, it is very difficult for me to follow the point of this paragraph.
- Line 227: In the seasonally covered regions -> In seasonal sea ice zone
- Figure 2: the reanalysis datasets -> the observed datasets
- Figure 2: Please change the unit for the SIC from 0-1 to 0-100%.
- Figure 2: The additional map for the climatological raw SIC value (%) would be helpful for readers.
- Figure 3: Since the year-to-year variability has no meaning in this comparison, I recommended that the spatial pattern for the climatological SIT distribution in winter is shown here despite of the time series of PIOMAS and NorESM1-M.
- Figure 4: The original sign seems to be better in panel c.
- Figure 4: The additional information for the spatial distribution of total ice mass would be helpful for readers.
- Figure 9: red line-> purple line
- Table 1: The additional column for the total sea ice mass in each month is helpful for readers.
Citation: https://doi.org/10.5194/os-2021-16-RC2
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