In this paper, Dangendorf and colleagues present a reconstruction of regional and global mean sea-level change and its different drivers since 1900, based only on observations and statistical methods (to reconstruct sea level back in time). The dataset presented in this manuscript is a valuable addition to the field, and can be used in a range of scientific applications. The manuscript explains well the method and discusses some of the regional patterns of the reconstruction, displaying the multitude of processes that can be investigated with this dataset. My only concern here is that it should be made clearer to the reader that this is an update of a previous reconstruction, with some, albeit very important, alterations, so that the novelty of the dataset is not overstated.  With this made it clear, and some small alterations, the manuscript deserves to be published to the scientific community.

Main comments:

• Novelty in relation to Dangendorf et al (2019).: The need to update the reconstructions available is well delineated in the introduction, which makes the issue and novelty of the study very clear. But I think it should be more explicit the differences and updates regarding the previous reconstruction from the lead author (Dangendorf et al., 2019). This is study is very briefly mentioned in the introduction, but it deserved more attention at the beginning to make it clear that this is an update/improvement of the previous reconstruction. From the introduction, that is not clear, and the reader is led to think that this is an update of Hay et al (2013; 2015). In the discussion, however, it becomes slightly more clear that this is an update of Dangendorf et al (2019) [Lines 608-610]. Only in the discussion [Lines 608-610] the authors say explicitly that this is an update of Dangendorf et al. (2019), extending the previous reconstruction by 6 years.
• Colormap of figures: In all sea-level literature, warm colors are related to positive trends, and cold colors to negative. The colormap used by all the authors is the opposite, which is very confusing. I really urge the authors to flip the colormap, so that blue will be negative and red positive.

Minor comments:

• Not sure if there is space in the abstract, but just by reading it, it was unclear what was the ‘novelty’ regarding the previous reconstructions.
• L21: make it clear that the reconstructions were larger (though with larger reconstructed trends in three out of six regions).
• L24: “most recent rates”… unclear to what period this refers. Please give a year.
• L49: Is there a more recent GMSL acceleration that could be mentioned (instead of a 2018 publication)?
• L127: I’m not so familiar with these methods, but how are the tide-gauge observations, which is in RSL, and satellite altimetry, which is ASL, combined in the state vector?
• L154: does this mean than that everything before 1955 is only based on statistical modelling?
• L161 (and L203): Why only one IBE estimate? Were there no other reanalysis available, to have a larger number, like for GRD and GIA…? And this IBE estimate is the combination of two reanalysis (one 1900-2015 and one 2016-2021), were there no single one that covered the entire study period? Do these two dataset have any significant differences (apart from period)?
• L191: Why only 5 years were considered to extrapolate the last year of GRD?
• L205: Use the grid resolution instead of number of grid cells (same for other occasions when the number of grids is mentioned (e.g., Section 4)). For example, L222: Does this mean that you at the end have a 4-degree resolution dataset?
• L213: Satellite altimetry was also used as input into the state matrix of the Kalman filter, no?
• Validation with satellite altimetry: If altimetry was used in the Kalman filter, is this a fair validation?
• L231: A suggestion, but you could use this value (r=0.89), or another as a reference contour line in the global map (Figure 2a).
• L241: Does this mean that there is a resolution limit to the reconstruction?
• L255: Is there a way of indicating which regions that have a significant residual? If hatching all the areas that are insignificant would make the figure “too dirty”, maybe you could mention in the text, since its such a small percentage, where the residuals are significant?
• Figure 3: The differences (last row) in the accelerations seems much larger, but this is probably an artefact of the color range. Maybe for these panels, both the trend and acceleration should be on similar color range, or the differences should be normalized.
• Sterodynamic estimates: There are some regional budgets, such as Wang et al (2021), Royston et al (2020) and Camargo et al (2023), that do have sterodynamic estimates. So these could be used to validate the sterodynamic of the reconstructions, instead of only independent steric estimates.
• L283: Here and also L287 you say ‘Northwest Pacific’, but on the table 1 and 2 is only ‘West Pacific”.
• L238: The agreement of the reconstruction is better with satellite altimetry than with tide gauge records, reflecting the dependence of the reconstruction on the quality of the altimetry in the coastal zone. In addition to the processes you mention here that altimetry measurements might misrepresent in the coastal zone, there are also a large number of correction issues in the coastal zone (see Vignudelli et al, 2019, for example). If the reconstruction is made with ‘standard’ altimetry product, and not dedicated coastal products (e.g., X-TRACT (Birol et al., 2017), ALES+ (Passaro, 2018)), it will inherit these issues. So, does this mean that the user should take care when using this product in the coastal zone (and say, not consider the most inshore grids?) In this case, a sentence saying this should be added. On the same note, I was wondering: (1) could the reconstruction be improved by including coastal altimetry products? (2) would the validation with the ‘virtual tide gauges’ (Cazenave et al., 2022) give better results than the validation with the standard tide gauges?
• L353: here you mention ‘64%’ and ‘33%’ of the tide gauges…what about the other 3%?
• L355-358: these are also locations with large non-linear (and non-GIA) VLM, such as earthquakes hot spots (U.S. west coast) and land subsidence (Gulf of Mexico). Could this also add to the large differences?
• L364: Could add a comment about why the differences with the tide gauges have so much larger uncertainties than the differences with satellite altimetry?
• L377-384: This part was very confusing for me, and required me to read several times to understand the different what trend values and number of tide gauges (90, 516, 119) were referring to. For example, the 0.27±1.67 and 0.1±1.8 mm/yr trends, are these average of the 90 and 516 locations? And the difference refers to KS reconstructed with GIA – tide gauges?
• L400-402: Please add the periods of Church & White (2011) and jevrejeva (2014), instead of just say ‘for shorter periods’. And add uncertainties to these trends, if provided.
• Table 3: You could also add the acceleration rates to the table (so similar to Table 1)
• L424 (and Fig 8): Why is the comparison made with D19 only from 1930-1939? And in the discussion (L612-614) the results are compared for 1993-2021?
• L428-429: This information should be given before, either in the introduction or methods.
• In Figure 10 you compare the accelerations with Palmer et al (2022), but this comparison never comes up in the text.
• L497: And to a smaller extent also due to GRD contribution
• L515: It seems like there is something missing in this sentence “The local maxima result from additional around…”
• L590: Are the codes ready for publication already? Or does this mean that there will be another publication for the code? It was unclear.
• L630: It’s a bit circular that the peak matches better with the ones from Frederikse et al (2020), since the barystatic GRD used in the reconstruction is from Frederikse et al (2020).

Editorial comments:

• L33: add comma after warming climate.
• L36: add comma after parenthesis.
• L50: add comma after parenthesis.
• L78: “unrelated through GIA”: should this ‘through’ be a ‘to’?
• L92: Add comma after observations.
• L102: I always see only ‘IB’ instead of ‘IBE’…
• L107: change ‘or’ to ‘and’
• L108: ‘MSL’ is introduced here, but not used again afterwards…
• Equation 2: first symbol on the right-hand side is not introduced/explained in the text.
• L128: modification instead of adjustment? (adjustment has a more negative connotation, seems like the previous work was wrong). And same for L129.
• Equation 3: Should the ‘and’ be in a new line?
• L166: use VLM, which was already introduced.
• L171: should it be 4000 (L162)?
• Figure 1a: Some of the symbols on the dark red and blue are a bit hard to see. Maybe using lighter shades for the background colors might improve it.
• L275: Reference should be Camargo (2020).
• L349: Change ‘Fig.’ to Figure (as it has been in all other instances)
• L381: Here you have ‘-0.14±1.00 mm/yr’, but Fig 6c says -0.13.
• L400: Here you have 1.5±0.19, but Table 3 is 1.5±0.20.
• L501: I would suggest using ‘scarcity’ instead of ‘paucity’, but that’s because I had to look up this word.

References

• Royston, S., Vishwakarma, B. D., Westaway, R., Rougier, J., Sha, Z., and Bamber, J.: Can We Resolve the Basin-Scale Sea Level Trend Budget From GRACE Ocean Mass?, J. Geophys. Res.-Oceans, 125, 1–16, https://doi.org/10.1029/2019JC015535, 2020.
• Wang, J., Church, J. A., Zhang, X., Gregory, J. M., Zanna, L., and Chen, X.: Evaluation of the Local Sea-Level Budget at Tide Gauges Since 1958, Geophys. Res. Lett., 48, 1–12, https://doi.org/10.1029/2021GL094502, 2021.
• Camargo, C. M. L., Riva, R. E. M., Hermans, T. H. J., Schütt, E. M., Marcos, M., Hernandez-Carrasco, I., and Slangen, A. B. A.: Regionalizing the sea-level budget with machine learning techniques, Ocean Sci., 19, 17–41, https://doi.org/10.5194/os-19-17-2023, 2023.
• Vignudelli, S., Birol, F., Benveniste, J. et al.Satellite Altimetry Measurements of Sea Level in the Coastal Zone. Surv Geophys 40, 1319–1349 (2019). https://doi.org/10.1007/s10712-019-09569-1
• Birol, F., N. Fuller, F. Lyard, M. Cancet, F. Niño, C. Delebecque, S. Fleury, F. Toublanc, A. Melet, M. Saraceno, F. Léger, 2017. “Coastal Applications from Nadir Altimetry: Example of the X-TRACK Regional Products.” Advances in Space Research, 2017, 59 (4), p.936-953. doi:10.1016/j.asr.2016.11.005
• Passaro, Marcello, Stine Kildegaard Rose, Ole B. Andersen, Eva Boergens, Francisco M. Calafat, Denise Dettmering, Jérôme Benveniste, ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters, Remote Sensing of Environment, Volume 211, 2018, Pages 456-471, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2018.02.074.
• Passaro, M. et al. ALES: A multi-mission adaptive subwaveform retracker for coastal and open ocean altimetry. Remote Sensi. Environ.145, 173–189 (2014).
• Cazenave, A., Gouzenes, Y., Birol, F. et al.Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations. Commun Earth Environ 3, 117 (2022). https://doi.org/10.1038/s43247-022-00448-z

This paper provides a new probabilistic reconstruction of historical global and regional sea-level changes by combining two methods (RSOI and Kalman smoothing) and using recently published results to constrain the reconstruction. Overall, the paper is clearly written, the methods used are well explained (although some improvements could be made I think - see below) and the results bring new information on historical sea level, which makes this paper and the related dataset definitely of interest for future research and operational studies. I only have a list of minor comments, suggested corrections and questions that I have listed below.

• Please include more carriage return in the introduction to make it easier to read.
• P2l48: 3.4 mm/yr over which period ? please clarify.
• P4l122: “control input parameter” or “control input parameters” ?
• P4l123: please revise the equations (1) and (2). The “k” subscript on the right hand side should be replaced by “k-1” in (1) and the “O with stroke” in (2) should be replaced by phi (state transition matrix) I presume.
• P4l128: “the latter […]” please reformulate. I don’t really understand what is the first adjustement compared to Hay et al.
• P4l130-132: were all individual GRD estimates used from Frederikse et al. (2020) or the total contribution (i.e. 1 GRD estimate for all components)? Please clarify.
• P6l171: replace 4,0000 by 4,000
• Although this not done either in Hay et al. (2017), I’d suggest to add a flowchart Figure that illustrate the various steps of section 2.1 to guide the reader through the methodology and also underline in this flowchart, where the present work differs from Hay et al. (2017) (and Dangendorf et al., 2019) to better capture the novelty.
• What is the time step of the procedure? annual? Please clarify.
• P7l213: “ […], which we interpret as sterodynamic” (?)
• Figure 2: please recall in the caption the time period over which correlation is calculated for clarity.
• Figure 4: I’ve the impression that the mismatch between the present reconstruction and Frederikse et al. (2020) is well pronounced before ~1990, while from 1990-onwards, the comparison seems good. Could that be the effect that the RSOI-based reconstructed sterodynamic component is strongly constrained by the availability of altimetry data? Please comment.
• P14l340-342:”This limitation is evident […] smaller amplitude signal in the tide gauge record of San Fransisco”. This statement is unclear to me. I rather see a larger amplitude signal in the TG record (?). Also, figuring where the 1997/1998 El Nino signals pops-up is not straightforward.
• P15l367-369: GNSS datasets used should be described in section 2.2 (Data). I supposed the ULR7A solution from Gravelle et al. (2023) was used? If yes, please clarify this too (as four solutions are available on SONEL actually).
• P15l381: -0.14 or -0.13 ? Please make the main text and Figure 6c consistent.
• P17l415: Maybe it would be relevant to cite the corresponding Figure of Frederikse et al. (2020). Fig1c right ?
• Figure 7: colors in the plot and the legend for Frederikse (2020) budget don’t match. Please correct this.
• P18l445: please refers to Figure 9 by quoting Figure 9 already there.
• Figure 9: the Sterodynamic component rates suggests ~30yrs oscillation. Is that possibly related to climate variability or is it related to the reconstruction processing? Such an oscillation is not obvious in e.g. Frederikse et al (2020) (see their Figure 1c)
• P21l473: “2.2 +/- 0.11” while Table 3 gives 2.2 +/- 0.12. Please make the main text and Table information fully consistent.
• P22l477-479: here also main text and Table 3 rates estimates are not always consistent. Please adjust
• P23l495-496: Figure 11a colorscale does not allow appraising such larges ranges as it ranges from -3 to 3 mm/yr. Maybe modify the caption or adjust the main text to clarify this.
• P23l497-498: “are therefore by the GIA signal”. A word is probably missing (?).
• P23l515-516: “The local maxima […] reflect gyre dynamics”. unclear. Reformulate ?
• P24l519 : Would it be worth and reasonably feasible to test a different SLP dataset ? E.g. HadSLP? or in light of what is done for GIA, using various ensemble members of the 20CR reanalysis dataset?
• P28l608-610: this information should be made very clear in the introductory part too I believe.
• P29l638 typo ‘aimpacted’