This paper presents a novel and valuable contribution to our understanding of intrinsic sea level variability along the U.S. East Coast. The authors use high-resolution ocean model simulations to demonstrate for the first time that 10–30% of the shelf sea level standard deviation may originate from ocean-internal processes alone. They also examine lead-lag relationships to assess predictability and explore possible mechanisms underlying a major mode of variability that is dominant south of Cape Hatteras. Overall, this study represents an important step toward identifying the full range of processes contributing to monthly-to-interannual sea level variability along the Northeast U.S. coastline.

The overall presentation of the results, methods, data, and conclusions—along with the manuscript's structure, language, and conciseness—is very strong and concise. I have only a few questions that should potentially be addressed. Note that most of my questions aim to clarify which processes could be relevant in the setup where only intrinsic variability is allowed, compared to the setup that includes external variability. Some of these comments may be somewhat subjective, as I occasionally found it difficult to determine which previous studies should be referenced here, or not.

Major comments:

Previous studies on mechanisms linking open-ocean and coastal sea level changes:

There is a substantial body of literature investigating the drivers of sea level variability along the U.S. East Coast (e.g., Frederikse et al., 2017; Calafat et al., 2018; Piecuch et al., 2018; Dangendorf et al., 2021, 2023; Steinberg et al., 2024; Wang et al., 2024). However, these studies are not cited or discussed in the introduction.  I think this is likely because some of the previously discussed mechanisms are not relevant (with regards to intrinsic variability), or because these works primarily analyze historical observations or model simulations that include externally forced variability, rather than isolating intrinsic (unforced) variability, as is done in this study.

That said, I wonder whether some of the physical mechanisms proposed in those earlier studies—such as the link between offshore steric height anomalies and bottom pressure fluctuations on the shelf in modulating coastal sea level (including the communication along the coast via coastally trapped waves)—might also be relevant in the context of intrinsic variability. If such mechanisms are indeed applicable regardless of the forcing source, then it would be appropriate to acknowledge relevant studies and situate your findings within the broader framework of previously proposed mechanisms.

In the conclusions, you note: “the ocean mechanisms involved in the communication of off-shelf anomalies to the coast (and from Cape Hatteras to the Gulf of Mexico) are likely the same as those regulating the transfer of other sea-level signals, regardless of their forced or intrinsic nature.” This statement suggests that some mechanisms identified in earlier studies (e.g., Calafat et al., 2018; Dangendorf et al., 2021; 2023; Steinberg et al., 2024) could in fact be relevant to your results, particularly given your finding of significant coherence between the leading coastal principal component (PC1) and off-shelf sea level, especially at periods longer than one year. Overall, it may be helpful for the reader to explain (maybe in introduction), which of the previously discussed forcings (e.g., wind forcing) are not relevant for your study focusing on intrinsic variability (just to provide a little bit more context).

I think that, if some of the previously investigated mechanisms are relevant, the authors should try to emphasize a bit better why and how their findings, e.g., the detection of the dominating and coherent first mode south of Cape Hatteras, is different or similar to previous findings, or novel, considering the study on coherent sea level in that region by Calafat et al., 2018. That ‘This coastal mode is coherent with sea level along the Gulf Stream axis after detachment from Cape Hatteras’ is a central point of this paper (in the abstract), and therefore it’s novelty needs to better clarified in light of previous research. You address several of these points in the discussion section (citing Wise et al., 2018; Hughes et al., 2019; Wise et al., 2020), but it may strengthen the manuscript to introduce some of these mechanisms earlier, in the introduction.

Another key finding of the study is that “Intrinsic sea level variability in the detached Gulf Stream leads the coastal mode by 2–3 months, suggesting that intrinsic coastal sea level variability may exhibit predictability.” I agree that this is an intriguing result from a mechanistic standpoint. However, I wonder how relevant this is in practical terms—specifically, what implications it holds for the predictability of sea level in the real world.

If I understand the results correctly, intrinsic variability accounts for roughly 20–30% of the total standard deviation in sea level (based on monthly data), relative to the forced simulations. Assuming a maximum coherence of ~0.6 between offshore sea level and the leading coastal mode (for periods >1 year), this corresponds to roughly 36% of the variance in the coastal mode being explained by offshore signals. Even if we assume that the first mode captures all of the intrinsic sea level variability, the offshore signal would then explain about 7–11% of the total sea level variability (i.e., 0.36 × 0.2–0.3) in a realistically forced setup.

If this reasoning is approximately correct, then a key question arises: To what extent does this lead–lag relationship actually translate into meaningful predictability of sea level in the real world, where forced variability dominates? Clarifying this point would strengthen the practical interpretation of the findings and help position the study within the broader context of coastal sea level forecasting.

Minor comments (some points are related to the major comments):

Abstract L14-17: I think it would be helpful to more clearly articulate what distinguishes your study from existing research. The separation of sea level correlation patterns around Cape Hatteras has already been documented in observational studies. Therefore, I would suggest emphasizing what makes your work novel. Is this the first study to shows that this separation also exists in intrinsic SSH variability, or is this the first study that shows this phenomenon using climate or ocean models? And/or is your key contribution the finding that this separation may be predictable? Clarifying this would strengthen the positioning of your study.

L52-55: Related to the 1. major comment: Are the results of previous studies investigating the causes of sea-level variability along the U.S. East Coast (e.g., Frederikse et al., 2017; Calafat et al., 2018; Piecuch et al., 2018; Dangendorf et al., 2021; 2023; Steinberg et al., 2024; Wang et al., 2024) relevant here, or not?

L63: Minor comment: Shouldn’t the methods not be in the main text in this journal?

Methods/Appendix:

L194: Please explain what ‘four consecutive cycles’ means here already.

L202: ‘The HR RYF simulation was carried out by applying a single year of JRA55 boundary conditions (May 2003 to the end of April 2004).‘ What if that year has a substantially different atmospheric variability (or annual cycle amplitude) than the average of 1958-2018? Wouldn’t that not bias your estimates? Would it make sense to use the 1958-2018 average as a forcing?

Fig1. b) It may be helpful to improve visibility of TGs (add white marker edge color?). It would also be interesting to see some more available TGs in this region (showing STD). C-e) What are the numbers at the bottom in the time series plots? g) as you write in the text, this fraction can be as large as 1 (100%). Could it actually be larger than visible by the color scale (that is cut off at 1, or 100%)?

Fig1. What about having a look at the differences in the power spectrum between the two experiments. At what frequencies is the variance on the shelf most strongly reduced?

L75: I assume that ’Total sea level standard deviation (mean across the FOSI members; Fig. 1a)’ is the temporal STD of the ensemble mean, correct?

L81: It may be helpful to quantify this agreement (correlation, rms), even if that’s from Little et al., 2024.

L89-90. I think it would be helpful to include some interpretation of the patterns observed in the intrinsic variability from an ocean dynamics perspective. For example, what causes intrinsic variability to be smaller or larger in certain regions?

L96: It may be nice for the reader if you’d better explain why you apply the EOF analysis overall.

L105: ‘Specifically, the PCs exhibit fluctuations at sub-annual to interannual time scales, including significant multi-year sea level trends (for example PC1, over a 5-year period beginning around month 90) (Penduff et al., 2019).‘ Is the significance based on visual inspection? A spectral analysis incl. significance test could be useful here.

Section 2.2.: The intrinsic variability north of Cape Hatteras appears to be much weaker compared to south of it, causing the EOF’s to mostly pickup regions in the south. It’s probably difficult to answer, but do you have any idea why the intrinsic variability North of Cape Hatteras is weaker (from an ocean dynamics perspective)? 

L120. What is the 0.3 threshold based on? Did you take into account autocorrelation in the time series?

L123-125: Why do you compare these correlation pattern with the minimum offshore intrinsic fraction?

2.3. Considering previous work, what about having a look at offshore steric and coastal SL correlations (maybe also at different frequencies). Or what about adding the steric averages in Fig. 4. computed over the same offshore-region?

Fig 3. If the geographical extent shown in the figure were expanded, would similar lagged correlations emerge in other regions—for example, in the Caribbean? This could be worth exploring, particularly in light of previous findings (e.g., Dangendorf et al., 2024, Supplementary Fig. 6; Calafat et al., 2018).

Discussion

L157-167 and 180 -189: You also mention that the processes communicating signals to the coast are “likely the same as those regulating the transfer of other sea-level signals, regardless of their forced or intrinsic nature.” It would be useful to clearly rule out previously discussed processes (e.g., Dangendorf et al., 2021, Calafat et al., 2018) that are not possible within the framework of a setup that includes only intrinsic variability.