| 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.
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.