This study evaluates the performance of E3SMv2-MPAS on the Arctic simulation, with emphasize on sea ice concentration, sea ice thickness, SST/SSS, AW layer temperature and depth. The authors find that the E3SMv2-MPAS is superior on some aspects and also some limitations are identified. In general, the manuscript is well written, easy to follow, and the scientific significance of the manuscript is guaranteed. I hope the following comments are useful for the authors to revise their manuscript, most of them are minor, major comments are marked with ***.  

L11: change “Arctic sea ocean-sea ice system” to “Arctic ocean-sea ice system”

L14: please clarify what “multi-scale” refers to.

L23-24: “These systematic biases may be attributed to three principal sources ...... in key gateways”. This speculation should be supported by some evidences in the main text.

L27: change “components” to “area”

L37-38: “Liang and Losch, 2018; Tian et al., 2022” are based on regional ice-ocean model, not climate model.

L48: change “and” to “to”

L53: change “seafloor regions” to “seafloor”

L60: change “shifts” to “shift”

L79: change “temporal” to “spatial” ?

L95: change “FESOM’s” to “FESOM”

L96: delete “then”

L130-132: “The North Atlantic sector ...... in the Gulf Stream extension region”. Please rephrase this sentence.

L134: “subpolar North Pacific sector adjacent to the Arctic Ocean”?

L139: how long is the sea ice dynamic step? The same to ocean dynamic step?

L157: rapidly

***L159-161: “The simulation periods ...... period consistency checks (1995–2020)”. If I understand correctly, you derive the simulation of 1995-2020 using JRA55 forcing during 1995-2020 but initialized at the latest model state of 1980. It is seldom to see such design of model simulation. As the intermediate years only span 15 years, I suggest the authors conduct a continuously simulation from 1960 to 2020.

***Section 2.1: there is no detailed information of sea ice model provided here. Please specify sea ice thermodynamics and dynamics in this configuration. As section 3.1 relates to sea ice validation, sea ice model description is necessary.

L197: EN.4.2.2 dataset     

L244: from Figure 3a, “systematic winter overestimation” is caused partly by positive sea ice bias in the southern Greenland Sea and south extension of sea ice cover in the Barents Sea, suggesting upper ocean temperature bias in these regions. “moderate summer underestimation” may be related to inaccurate ice-albedo feedback and melt pond dynamics.

L249: “overestimated seasonal variability amplitudes” relates to sea ice thermodynamics, as no sea ice thermodynamics information is provided, it is hard to judge its causality.

***L258-269, 279-281: The modeled SIT has large biases in the Beaufort Gyre region, suggesting potential upper ocean thermal biases in the Beaufort Gyre. The author could check whether the ocean-ice heat flux over the Beaufort Gyre region is reasonable.

Figure 4d: given the known biases of the PIOMAS SIT, I suggest the author additionally validate the modeled sea ice volume against that derived from the CS2SMOS SIT from 2012.

L347: Please specify the define of AW layer thickness.

L347-349: This sentence needs to be rephrased as “Amerasian Basin” is not in Figure 8. 

L362-363: “E3SMv2-MPAS maintains systematic temperature overestimation (~0.5C average)”. This statement is not appropriate for the other three regions.

L364-365: systematic salinity underestimation only occurs in western and eastern Eurasian Basin.

L390: ~ 0.5 C at 800 m ?

L417: I understand from section 2 that both the E3SMv1 and E3SMv2 use the same KPP. Why the vertical mixing scheme in E3SMv2 is refined?

Figure 11: please clarify this figure is conducted over the whole Arctic Basin or Eurasian Basin or Amerasian Basin?

***L466-467, 469-470: “likely modulated by differential ocean-ice feedbacks and cross-basin transport dynamics”, “indicating limitations inAW transport pathways and heat redistribution”, such speculations are too arbitrary, it’s better to avoid using such speculations.

L488-490: see the previous comment.

L519: delete “the” before “Fram Strait”. “Similar negative deviations (-0.5 C)”

L527-530: This conclusion can not derived from the observations STRICTLY.

L582: a detailed description of the thermal linkage framework between the upper and intermediate ocean layers is needed here.

The manuscript titled ‘Evaluating the E3SMv2-MPAS Ocean-Sea Ice Coupled Unstructured Model in the Arctic: Atlantification Processes and Systematic Biases’ presents a coupled ocean–sea ice model based on the E3SMv2-MPAS framework from the Energy Exascale Earth System Model, designed for Arctic sea ice and ocean simulations. The model features a high resolution of 10 km in the Arctic Ocean. According to the model validation, it demonstrates good performance in simulating Arctic sea ice and ocean conditions. Utilizing these simulations, the authors further identify a fundamental regime shift in intermediate-to-surface thermal coupling mechanisms in the Arctic under climate warming. In my assessment, the manuscript requires major revision. I offer the following suggestions to enhance its quality:

1. I concur with CC1’s comments. It is not entirely appropriate to compare the E3SMv2-MPAS results with those from E3SM-Arctic-OSI, CMIP6, and OMIP models, due to significant differences in integration lengths and associated model drifts. These discrepancies undermine the fairness of direct comparison. I recommend that the authors remove the model intercomparison from the main text and instead address relevant points briefly in the discussion section.

2. The model configuration requires further clarification. As the simulations do not adhere to the standard OMIP protocol, more detailed information regarding the model integration setup should be provided.

3. Regarding sea ice validation, while sea ice concentration and thickness are evaluated, I encourage the authors to also include assessments of sea ice extent, volume, and their long-term trends.

4. Given that this is a model evaluation study, I suggest a more comprehensive evaluation of the Arctic Ocean simulations. Key metrics should include Arctic Ocean freshwater content and its trend, as well as volume, heat, and freshwater fluxes through major Arctic gateways. These aspects are critical for assessing the model’s performance in simulating Arctic Ocean climate.