the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Winter Arctic polynyas in CMIP6 models
Abstract. Winter Arctic polynyas, openings in the pack ice, play a crucial role for the climate from sea ice production to cloud formation and are hotspots for the ecosystem and human activity. Their area has significantly increased since satellite records began. Yet their representation has yet to be evaluated in any generation of global climate models, most likely because their automatic multi-model retrieval is challenging. We here use a newly-developed machine-learning based method and evaluate polynya activity against the satellite-derived one over 1979–2024 in the 18 models with daily sea ice concentration available. We find that models overestimate winter Arctic polynya area but underestimate its frequency, and limit their opening to the seasonally ice-covered regions. Polynya area is increasing in most models, but the bias of these trends are inconsistent. Although the model with the highest resolution has both the highest areas and frequencies, the sea ice model component is a more robust predictor of polynya activity, with most activity in the models whose thermodynamics scheme enhances ice growth/melt and least activity in models whose dynamics scheme dampens the influence of wind on ice. Accordingly, we found more polynyas in the models with a larger seasonal cycle, in particular those with a warmer autumn that would delay ice growth. Finally, we confirm preliminary findings that polynya activity does not seem to impact the representation of the water column; if anything, we find less-dense water at the bottom of the continental shelf following larger polynya activity, i.e. supposedly with dense water formation.
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Status: open (until 07 May 2026)
- RC1: 'Comment on egusphere-2026-901', Anonymous Referee #1, 14 Apr 2026 reply
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RC2: 'Comment on egusphere-2026-901', Anonymous Referee #2, 20 Apr 2026
reply
This interesting and generally well-written manuscript is the first systematic study of CMIP model performance in terms of the Arctic polynyas, including their area and evolution. The topic and scope are suitable for the Cryosphere journal. However, there are some issues that the authors should address before I can recommend the publication of the manuscript in the journal. I list these points next in no particular order.
- line 61. I suppose 'the threshold' is based on sea-ice concentration. That should be clarified.
- lines 73-74. '(Brodzik et al. 2012)'
- line 110. Are the 'large errors' compared to observed sea-ice thickness?
- line 121. Here, the definition of sivol should be clarified. I suppose it is the sea-ice volume [m**3/m**2] in a grid cell per unit area, so that the mean sea-ice thickness in a grid cell is sivol divided by sea-ice concentration.
- line 122. Explain what 'unreliable' daily sea-ice thickness means.
- line 125. Is the ice density in these models constant?
- Table 1. Column 2 indicates the model horizontal resolution in square kilometres. But the models' grid cell area is not constant. Is the value presented the largest grid cell area north of 70 N?
- Table 1. Column 3 lists the sea-ice model components, but is quite confusing in places. For example, what is the difference between '~CICE', 'CICE' and 'CICE5'? Optimally, precise versions of LIM, CICE and COCO should be listed.
- line 172. I wonder how much difference the results would be when using single-model ensemble means instead of the first member. What would be the ensemble spread?
- line 190. This subsection title is confusing.
- line 195. Even though CanESM5 and NESM3 use the same ocean model NEMO, with nearly the same version (3.4.1 and 3.4), their sea-ice models differ. This difference could cause the bias.
- line 207. 'seasonally ice covered area' is a confusing term in this context. Do you mean Marginal Ice Zone (MIZ)?
- line 208. The claim that 'in observations there are polynyas in the permanent ice pack' seems misleading as the coastal regions, e.g. in the continental shelf, where winter polynyas occur, become ice-free in summer, so their ice-cover is not permanent. Would inner pack ice be a better expression?
- lines 213-215. Despite using the MIZ classification method, the data still contain noise from the MIZ, which the authors claim is unavoidable. This raises the question of why then use the MIZ classification methods at all?
- Figure 3. Just north of Region 1 and Svalbard lies an active polynya region that was excluded. Wouldn't it make sense to include it in the analysis by extending Region 1 northward?
- Section 3.2, general comment. Based on some earlier studies, in winter, the MIZ area is underestimated and the pack area is overestimated (e.g., Chevallier et al. 2017). Could such a shortcoming affect the CMIP model polynya evolution and extent?
- line 232. Which eight models underestimate the frequent-opening areas? This might be useful information.
- line 234. Which locations (referring to 'too many locations')?
- line 241. Is 'the 45-year mean bias' in the polynya area?
- line 252. Seems that the LIM models are in fact quite scattered in Fig. 4 in the Chukchi Sea.
- Table 2. How robust is the test limit: more than 25 out of 45 winters? What if you change that to 20 or 30? Percentages in the table and text are expressed with a rather high accuracy. How meaningful are the differences between the models? When are they statistically significant?
- In Figure 5 some panel labels are greek letters which is strange.
- In Figure 6, are all correlations significant at the 95% level, as there are no NaNs? What about regression slopes, what are they confidence limits? Seems that in panel 4. Lap, the regression may not be significant.
- line 321. 'and often with a stronger value'
- line 325-328. To confirm this, you should calculate correlations between the polynya area and the sea-ice thickness in the following summer.
- lines 329-331. These claims seem subjective. For example, the FJL correlation is -0.66 in JJA and -0.69 in DJF. Is this difference truly significant or a result of chance?
- line 340. Mention the sea-ice concentration threshold value. Is it 0.8?
- Table 3. Calling sivol 'the mean sea-ice thickness' is obscure. Use the term 'effective sea-ice thickness' or 'the sea-ice volume per unit area' or similar.
- line 359. In sea-ice models, not only the rheology matters, but also the form and skin drag at the air-ice and ice-ocean interfaces, plus atmospheric and oceanic boundary layer stratifications and mixing parametrisations. The importance of rheology is comparatively small when the sea-ice concentration is low, say below 0.7.
- line 360. The EVP rheology implemented in CICE, and actually also in LIM2/3, produces practically similar results to the VP rheology. The elastic waves were added for a faster numerical solution (Hunke & Dukowicz 1997). But there are other more important differences between CICE and LIM. In fact, in LIM2, there is no sub-grid-scale sea-ice thickness distribution, unlike in CICE and LIM3.
- Section 4.2. The analysis related to winds is really confusing. First, it is quite unfriendly for a reader to go and look for values from tables in the Appendices. Could the key findings be visualised e.g. in a bar plot or similar? It is also not convincing to separate the analysis between winds and temperatures. Instead, cold and warm air advection cases should be compared. For example, cyclones from the Atlantic bring in warm air and strong winds, which have entirely different effects on polynyas than cold air off-ice or off-land advection.
- line 399. Also, FJL, Kara and Chuk correlation with T2m in SON in Table 3. Why not mention them?
- line 400. 'the absolute value of the correlation'
- line 404. I do not think it is justified to call these relationships strong.
- line 407. An explanation for why warmer models have thinner ice in autumn is that when the air temperature is warmer, but below zero, the ice growth is slower.
- line 409. 'polynya area is evident, but lack'
- line 434. Makes sense that there is no sea-ice production in these modelled polynyas.
- line 465. 'fresh and warm waters.' This finding could be backed up by theory and you could mention that instead of latent heat polynyas, the models simulate sensible heat polynyas.
- lines 496-499. As mentioned before, see the one related to line 359, this explanation appears implausible.
Literature:
- Chevallier, M. et al.: Intercomparison of the Arctic sea ice cover in global ocean–sea ice reanalyses from the ORA-IP project, Climate Dynamics, 49, 1107–1136, https://doi.org/10.1007/s00382-016-2985-y, 2017.
- Hunke, E. C. and Dukowicz, J. K.: An Elastic–Viscous–Plastic Model for Sea Ice Dynamics, Journal of Physical Oceanography, 27, 1849–1867, https://doi.org/10.1175/1520-0485(1997)027%253C1849:AEVPMF%253E2.0.CO;2, 1997.
Citation: https://doi.org/10.5194/egusphere-2026-901-RC2
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- 1
I have reviewed the manuscript titled „Winter Arctic polynyas in CMIP6 models“ by Heuzé et al..
Their study evaluates and compares how current (CMIP6) climate models represent polynyas. To my knowledge, such a study was missing for the Arctic (but exists for the Antarctic), despite the important role polynyas play in the Arctic climate system (e.g., sea ice production, biological hotspots/biodiversity, coupling of ocean to the atmosphere, etc.).
The authors use a newly developed polynya detection method (Wong et al., 2026) based on sea ice concentration (SIC) to compare yearly/winter mean polynya area, frequency and trends across models and against satellite observations. The writing is clear and the methodology is sound as the authors also discuss (the limits of) their detection method (e.g. testing different thresholds, the limitations in the marginal ice zone, the dependence of the results on grid resolution, etc.) as well as their statistical diagnostics (e.g. using cumulative polynya area instead of winter mean area, using monthly instead of daily SIC data, etc.). Data and methods are well described (Section 2) and data and source code are mostly openly available (or will be made available soon). Also, the results sections benefit from a clear structure with summaries at the end of subsections. The potential causes of biases are thoroughly and concisely analyzed, using correlations as main (and available) tool, and discussed in Section 4. The impact on the ocean (deep) water representation, a question motivating this study, is exemplarily discussed with well chosen indicators of the water column.
The figures and tables are overall well done.
The last chapter summarizes the main findings and new insights of the study and provides an outlook on how to improve the representation of polynyas in climate model but could benefit from minor improvements. Overall, the study is of high quality and a step towards understanding how polynya (processes) are biased in climate models.
Below, I provide more specific comments and suggestions for improvement. I am highlighting the comments I find most important as bold:
- Figure 2: are the models ordered in any particular way (e.g., based on resolution or the sea ice model used)?
- Line 218 ff. how could this value (the percentage of region where polynyas have opened for more than 25 years) be impacted by changing SIC/marginal ice zone conditions across models/years, e.g. in the mentioned East Siberian Sea?
- Line 235 ff. Trend: could it be related to retreating sea ice/“false“ detection of polynyas in the marginal ice zone? On page 9 you discuss the relation of SIA/SIE to polynya activity, I suggest you add a sentence about the relation of SIA/SIE trends and polynya trends if possible.
- Line 250 ff.: Clustering by sea ice model: I find this hard to tell from the Figure. I agree that a clustering of star symbols is visible for region 5 but I do not see it for region 6 as stated in line 252, for example. I suggest to either try to illustrate it more clearly in the figure (or an extra figure), maybe with semi-transparent symbols or a reduction to the two most common ice models, or by writing it in the text more explicitely (à la “clustering in the upper right quadrant…“). I find this especially important as part of the conclusions are drawn from this (see Abstract: „with most activity in the models whose thermodynamics scheme enhances ice growth/melt and least activity in models whose dynamics scheme dampens the influence of wind on ice“). Maybe you could indicate which sea ice model is used per ensemble in Figure 2.
- line 257: how short is short-lived?
- Figure 5: please remove the plotting artefact
- Figure 5, j): what is going on around 70°E? The white stripe looks suspicious.
- Section 3.2.: Using monthly SIC data comes with many drawbacks and the section nicely dissects them. However I find its size compared to the other sections disproportional for the (somewhat) expected results and recommendations (at least it distracted me a bit from the main story) and therefore I suggest to consider moving one of the two figures or even part of the text to the appendix.
- Section 4: Please define autumn and summer somewhere here or earlier (as e.g. summer sea ice thickness is often referred to in this section).
- Line 319: „by definition where there is sea ice, polynyas can open“ This could be true also for other regions (?), consider adding a sentence why this is seen only for Svalbard.
- Line 322 ff. and also line 394-396: Have you considered applying methods like time-lagged correlation analysis to back up your statement?
- Line 348: Point 3, correlation to the equilibrium climate sensitivity: This hit me by surprise as the sentence starts with „To summarise“ but climate sensitivity has not been mentioned anywhere before. Please elaborate.
- Line 359 I suggest you add something like „ In sea ice models, it is the rheological formulation and roughness“ (or „ drag“)
- Line 391: As you consider December-March I would rephrase (it sounds as if warm air thins, that is, melts, the ice, I guess what is meant is that growth is slowed down). Another question I have here is whether the warmer winter air temperatures could be a consequence of larger polynya areas. Was this feedback considered?
- Section 4.2. line. 404 ff. : I find the conclusions drawn here plausible, but I am missing a statement about the link of summer thickness and autumn thickness (how are they related/correlated?) or even something like a time-lagged correlation analysis to confirm that the thin summer ice is a consequence of large polynya activity while the thin autumn ice pre-conditiones for polynya opening.
- Section 5.1 line. 521. I would mention that this includes the “outlier“ model“
- Figure 7 and Figure 8: I suggest to use different shadings of blue and red to distinguish between the models
- Section 5.2. Line 464-465: “At the end of Section 4, we suspected that the models with the highest activity formed polynyas by melting the ice rather than by dynamic breaking due to strong winds.“ Where can I find this statement in Section 4? I understood there, that the thin autumn ice (which may or may not be a consequence of more melt, it could also be caused by less growth) preconditions the ice for dynamic breaking. Please explain. Is this based on the clustering by models? I think the study would benefit from a clearer distinction between air temperatures slowing growth and actual melt.
- Line 475: „mosty likely a result of how models open their polynya“. I am curious: could it be also a result of how models close their polynya? Is there a way for a model to dynamically close the polynya (without/little ice growth and thus, no dense-water generation)?
- Line 495: „no consistent correlation at the individual model level“: this seems to contradict what you wrote in lines 366 ff or line 404 ff. Please explain.
- Line 502: „Our results do suggest however that polynya misrepresentation in CMIP6, in particular their too low frequency, may be caused by a reduced effect of wind on ice in climate models“. Please elaborate on this a bit more as this was not my take-away message from section 4. 2. For example, what makes you believe the effect is reduced?
- Line 514: „further suggesting (…) sea ice melt …“: Here, my comment refers more to the previous comment on lines 464 ff.: where was it stated that sea ice indeed melts in the models for polynyas to form? From my understanding of the section 4, the ice thickness is important but this is not necessarily a consequence of more melt. However I agree that the fresh water in the ocean models suggest it.
- Figure A3 caption: I am not sure I understood the red arrows („point in the direction of its polynya area“), does it mean the values are outside of the x-axis limits?
technical:
- Consistent writing of Section vs. section
- Table 1: more complete if sivol is added in „comment“ column
- line 146 missing „and“
- line 154: refer to figure number
- line 426 typo „because of“