the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jan 2026
A Century of Mean Sea-Level Change in Ireland (1925–2024)
Abstract. Understanding mean sea level (MSL) change is crucial for assessing coastal vulnerability and guiding adaptation planning, particularly by identifying regions most at risk. Central to this understanding is the availability of long-term sea-level data. In Ireland, digitized records longer than 40 years are rare and mostly confined to the northeast; however, data archaeology—including the digitization of historical marigrams—can fill spatial and temporal gaps where undigitized records exist. Previous studies have focused primarily on individual sites in the north and east. Here we show that integrating previously undocumented records from the southwest with well-documented datasets provides a comprehensive assessment of MSL change across the country. We find clear regional variability, with the highest mean rates in the south and west. Long-term mean instantaneous rates—representing the modelled rate of sea-level change at each site—vary systematically between regions, reflecting coherent spatial patterns. Rates range from ~1.07 mm yr⁻¹ in the north to 2.48–2.74 mm yr⁻¹ in the south and west, with the highest observed at Cork (2.74 mm yr⁻¹). The regional mean is 1.96 ± 0.1 mm yr⁻¹ for 1925–2024, decreasing to 1.88 ± 0.1 mm yr⁻¹ after accounting for Glacial Isostatic Adjustment (GIA). Annual rates increased from below 1 mm yr⁻¹ during 1925–2000 to above 4 mm yr⁻¹ during 2000–2024, peaking at ~6 mm yr⁻¹ in 2024, highlighting pronounced 21st-century acceleration. After applying atmospheric and datum adjustments and accounting for GIA within a Bayesian framework, these historical records provide a robust basis for reconstructing regional sea-level rise and contextualizing future coastal risk, with implications for coastal planning and adaptation strategies globally.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-6404', Laurent Testut, 14 Apr 2026
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RC2: 'Comment on egusphere-2025-6404', Peter Hogarth, 04 May 2026
A Century of Mean Sea-Level Change in Ireland (1925-2024)
General comments:
Abstract: 10 to 30. A nice concise abstract for a huge and detailed account of painstaking work. General: The heroic scale of the work underlying this paper runs the risk of it being unwieldy for all but the specialist audience, but it is difficult to encapsulate this amount of work in a conventional paper format. It is overwhelming on first read. In agreement with the first reviewer, some of the sections could be compacted by more use of tables like table 2, rather than the explicit but repetitive paragraphs on processing steps for each site. I appreciate it is difficult to be concise but still give sufficient detail to understand each step in the data recovery and analysis. The work on each site alone could merit a single paper, but it would be nice to find a way of keeping the work inside one structure with one point of access. Another alternative to splitting the work is to shift the detailed analysis into a supplement, this could minimise overall restructuring and any major text revision if the target publication permits. An example would be the supplements in some of the Talke and Jay papers e.g.
Talke, S. A., Mahedy, A., Jay, D. A., Lau, P., Hilley, C., & Hudson, A. (2020). Sea level, tidal, and river flow trends in the lower Columbia River Estuary, 1853–present. Journal of Geophysical Research: Oceans, 125(3), e2019JC015656..https://doi.org/10.1029/2019JC015656
In general agreement with comments from the other reviewer, I recommend the authors consider ways of condensing the paper prior to acceptance, if some way can be found to avoid compromising the significance (in my view) of the overall achievement. In effect this is a recommendation for borderline major restructuring, but more minor content change. Otherwise comments are minor.
Regardless, the additional site data, the focus on areas of Ireland where data is sparse, and more complete picture of Irish sea level presented is crucially important and the results deserve to be published after some consideration of the above. The authors are commended for persevering.
The publication of the digitised records (and complete site time series?) will be a big step forward for Irish and regional sea level studies.
Detailed comments (minor).
24: Perhaps uncertainty levels as used in line 24 would be better than “~” and 2 decimal point precision used elsewhere. Should line 26 read “a rise of ~6 mm during 2024” or is this a computed instantaneous annual rate similar to that explained later in the text (in which case is the confidence interval large?). A rate or change derived purely from one year of data would of course be unusable so this needs explaining (or a later explanation pointed to) where the term instantaneous is first used.
38: It appears to me that the authors are making a point about overall 21st Century sea level acceleration based on the global satellite altimetry record, but it’s unclear what the uncertainties are, and the rates for given overlapping time periods 1993 to 2021 (Guérou et al., 2023) and 2006 to 2016 (Llovel et al. 2023) are confusing in this context. I believe Llovel et al. were highlighting the impact of interannual variability. As Llovel et al. 2023 cite Guérou et al., 2023, the section “and ~4 mm yr⁻¹ from 2006–2016” could be removed without further amendment to avoid confusion? The authors then give the instantaneous rates for 1993 and 2023 citing Hamlington et al. 2024 in line 42. I think this best reinforces and supports their point.
138-139: only the months of June to August were digitised. It’s not completely clear why, and what impact this might have on uncertainties or seasonal effects on annual averages at this site.
Figure 5, 6: Are these plots of MSL before seasonal correction? It isn’t clear if the monthly MSL plots have the average seasonal MSL variation removed before the atmospheric adjustments, or whether the regression coefficients (510, Eq. 6) in the annual and semiannual components of the atmospheric pressure adjustments are effectively accounting for the seasonal MSL variation (i.e. the seasonal MSL variation may have other causes than purely atmospheric even if they correlate). I’m not sure what difference this might make (if any!). Tests using SD (line 545) could easily determine.
576: can linearly interpolate between 20CRv3 1 degree grid points to the exact location instead of averaging (to avoid spatial smearing), although it probably won’t make a significant difference here. It will in theory better match ERA5. However -the use of best correlating ERA5 point? Within what spatial range? Why two approaches?
597 to 598: Elsewhere in the world, there are often small but consistent pressure offsets between 20CRv3 and ERA5 reconstructions which could create a step in the atmospheric adjustments for MSL. I’m sure this was tested for an overlap period for the two products? - brief details of matching would be sufficient.
616: Interesting. Similar divergence between GIA models and eventual conclusions were found for UK.
Figure 13: I am unfamiliar with the NI-GAM processing, please forgive my ignorance. What is the significance of the near horizontal alignment of large portions of data points for Belfast, Dublin and Malin Head? To my eye these don’t closely follow the 1:1 line at all, but do something else.
763: Given long term sea level acceleration and particularly high global and UK rates over the past 10 years, the lower linear rate reported at Belfast relative to Malin Head will likely be due to a longer record starting at an earlier date? This question could be bypassed if rates were compared over an identical (maximum overlapping) period, as this would isolate any regional GIA component, as in the “fair comparison” of Table 8, where any apparent regional differences are reduced (Belfast being the outlier, but having 9 less years of likely highest rate recent data). A point about the need for overlapping periods and start/end times could be made earlier, and the authors could consider condensing the section with rates estimated over differing time periods.
This is reinforced in the observation (766 to 768) that the rates at Cork, Tarbert and Galway are statistically identical over similar time periods, whilst (773), identical modelled rates are estimated at Belfast and Dublin for the identical 1925 to 2000 period.
If so, any reduced SLR differences could better reflect the small regional GIA differences from the later Peltier model given by the authors (−0.07 to 0.21 mm yr⁻¹).
I think Fig.14 neatly encapsulates any regional differences and perhaps could be referred to to deflect the above points in advance.
Considering Fig. 14, It looks like if the instantaneous rate curves of, for example, Malin Head and Tarbert (far apart spatially) are superimposed, then the very close to constant offset (representing a linear rate difference?) between them could be entirely due to GIA differences. In effect, this mean offset difference could be interpreted as an instrumentation based long term measurement of relative VLM/GIA?
824: This gives confidence. Similar results reported in other studies over similar periods.
Figure 15 as presented, however, would also accommodate an unrealistic (in my view) horizontal “no change” trend within the 95% credible interval, whereas the (also similar to other coastlines around North Atlantic) coherence of the pattern of long term change at each site suggests confidence intervals that should be reduced due to averaging over more than one site. I am likely missing something, but still trying to understand why these intervals are so large (approximately ±100mm).
950 to 954: is 1.96 ± 0.1 mm yr⁻¹ any lower than 2.12 mm yr⁻¹ (assuming similar confidence limits are included)? These look very close, and this could reasonably be reworded. Although corroboration is not always validation, the total number of sites involved in these studies gives higher confidence in these convergent estimates of SLR, as in line 979.
981 to 988: an important point is made about unknowns during gaps in individual site data, and “smoothing”, but any doubts about real site specific variability during gaps at one location can be mitigated to some extent (in a probabilistic sense) by considering the actual unsmoothed intersite variability over other overlapping periods of similar time length to the gaps. I assume this must be implicit in the model. It might also be interesting (but not necessary for the paper) to estimate and plot an annual intersite Standard Deviation if enough sites have overlapping years.
1023: Typo here I think, the GIA-free result is Relative SLR (i.e. land surface relative, as would be experienced by local residents and as measured on the actual tide gauges)? Absolute SLR is usually defined as geocentric.
1045 to 1053 more than validates this study. Well done.
I’ll also comment on the suggested use of altimetry in order to identify datum errors through comparison. I discussed this last year with Richard Ray, we concluded that comparison with other tide gauge sites and comparison with altimetry are complementary approaches. As in Richards paper, for post-1993 studies using altimetry gives optimum results for island sites surrounded by deep ocean. For coastal sites on continental shelves as here, and if nearby tide gauges are available, then the tide gauge/tide gauge residuals will usually display lower variability, comparable with best case altimetry/tide gauge comparisons on island sites. If possible, I would try both approaches and use which works best.
Citation: https://doi.org/10.5194/egusphere-2025-6404-RC2
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The scope of this article is extremely ambitious and bears much more resemblance to a dissertation manuscript than to an article. The problem is that it is formatted as an article. The scope of the topics covered is very broad; it includes aspects of the digitization of data, the validation of historical and modern data, their referencing to a common datum, the adjustment of these data using a multiple linear regression model to reduce their variability and enable the calculation of long-term trends, the intercomparison of GIA models, and much more. Added to this is the fact that the number of stations analyzed is also significant (more than a dozen). This makes the article very difficult to read and hard to digest. It’s truly a shame because the subject is of paramount importance, and it’s clear that the work done is substantial. Publishing this article as is would be a real shame, as the underlying work deserves greater visibility and better presentation. I think the best solution is to split the article into two papers (a data paper + a trend analysis paper). The first paper would explain all aspects of the data archaeology work more clearly, describing in greater detail the quality control steps, the underlying assumptions, and the data validation. The second paper would be dedicated to the analysis of the dataset. My comments below will focus primarily on the data archaeology portion, as the rest of the analysis will depend entirely on the robustness of this work and the confidence we have in the quality of the final dataset.
MAJOR COMMENTS
Page 4 : "Data Collection and Digitization"
Readers can quickly become confused about the source of the data used; it is important to summarize the data in a table or even in Figure 1 to help readers gain a clear understanding of the data used in this study. For example a table summuraizing the data collection, the origin of the data (PSMSL,MI, newly digitized, Murdy et al.) and the period would help the reader a lot.
Page 12 : "Validation of Tide Gauge data"
This section is not detailed enough. You should describe exactly the validation protocol more accurately. Why only M2 is computed and not the others tidal constituents ? What do you mean by M2 or z0 of poor quality ? Important information on the evolution of the main tidal constituent both in amplitude and phase would help detecting errors. With regard to the modern observation period (after 1993), comparison with satellite altimetry has demonstrated its ability to aid in data quality control and, in some cases, even to identify ofssets in tide gauge records (Ray et al., 2023). I recommend that you use the altimetry data for your validation protocol with the modern data. The daily or monthly gridded data are easy to use and allow for independent verification of average sea levels over the 1993–2025 period.
Ray, R. D., Widlansky, M. J., Genz, A. S., and Thompson, P. R.: Offsets in tide-gauge reference levels detected by satellite altimetry: ten case studies, J Geod, 97, 110, https://doi.org/10.1007/s00190-023-01800-7, 2023.
gridded altimetry product available : https://cds.climate.copernicus.eu/datasets/satellite-sea-level-global?tab=overview
Page 13 : "4.1. Validation of Tide Gauge Data: Historical and Modern Records"
In this section, you must explain your data validation process. Why use only the amplitude and phase data from M2 as validation information? For certain stations, you must also use figures to show the trends in M2 (in terms of amplitude and phase) and the months and years that were excluded. This may not be necessary for all stations, but it should be done for certain representative cases.
Page 20 : "4.3. Data Quality Control and Standardization"
If you choose to produce a data paper, it will be important to provide a raw dataset and a validated final dataset (schedules) with a column indicating data quality (good, bad, suspect). This dataset is worthy of publication in its own right and will serve as a reference for your study on trends, as well as for future studies by other users, and will facilitate its integration into global databases. In this era of data reproducibility and open science, this is an important step in your work.
MINOR COMMENTS
Page 1 : "peaking at ~6 mm yr−1 in 2024"
Computing a MSL rate with 1 yr of data does not make sens. See your reference to Hogarth work.
Page 2 : "~4.5 mm yr−1 in 2023 compared to 2.1 mm yr−1 in 1993"
Idem even with GMSL change, 1 year does not really make sens.
Page 2 : "If this trend continues, an additional ~169 mm of global sea-level rise could occur over the next three decades"
Term not consistent with what is said before. Please check. 169/30 = 5.6 mm/year ?
Page 3 : "A minimum of 40 years is generally required to robustly determine trends in MSL (Hogarth et al., 2021)."
Yes that's why 1yr MSL trend is meaningless
Page 3 : "GLAC1D uses physics-based, glaciologically self-consistent ice-sheet simulations (Tarasov et al., 2012), whereas ICE6G models are tuned to fit global relative sea-level (RSL) and crustal motion observations (Peltier, 2015)"
You need to precise that this are GIA model (if they are). All reader are not familiar with GIA.
Page 3 : "BRITICE-CHRONO"
Idem, you need to give a little more precision on what is BRITICE-CHRONO
Page 6 : "The PSMSL holds a Mean Tide Level (MTL) record for Belfast Harbour, but it does not extend beyond 1963"
It is important to make a comparison with between the PSMSL dataset and the Murty et al. 2015 if that make sens.
Page 12 : "Statistical outlier detection was systematically applied across all sites by removing values exceeding ±3 standard deviations from the mean"
How do you ensure that you don’t exclude important data (surge) in your 3-SD test, which seems a bit rudimentary as a validation technique. You should justify and explain this choice.
Page 12 : "Both M2 tidal constituents (amplitudes and phase lags) and z0 (mean sea level) values were examined to identify and flag poor-quality observations"
You need to explain more on how you have examined the M2 (amp,pha) to determine if the data are good or not.
Page 13 : "For the Belfast record, 1925 was chosen as the starting point instead of 1901–1902"
It seems that this dataset is not available in the global repositories (USHSLC, PSMSL, GESLA) it would be important to make this dataset available to the community for further analysis.
Page 13 : "The tidal record"
In Figure 5 it would be more appropriate to call it a MSL record than a tidal record as tide have been filter out
Page 21 : "5. Data Processing and Sea-Level Modelling"
If you decide to split the article into two parts, I'll insert the transition here.