Status: this preprint is open for discussion and under review for Ocean Science (OS).
An Improvement to short term variability in Global Mean Sea level reconstruction
Andrew Shaw,Svetlana Jevrejeva,and Francisco Calafat
Abstract. We hypothesise that there is an overestimation of Global Mean Sea Level (GMSL) variability from GMSL empirical orthogonal function (EOF) reconstructions due to differences between the tide gauge observations and their corresponding altimetry data. We show that these differences are correlated well with local winds along coastlines, suggesting that observations from tide gauges at the coast and satellite altimetry near the coast could partially be explained by the wind forcing. Correcting these differences through a mainly wind-driven regression model prior to the EOF reconstruction, reduces the standard deviation (SD) of the reconstructed GMSL variability by 26 % and significantly increases the correlation to 0.46 with respect to the observed averaged GMSL calculated from altimetry grid points (1994 to 2020). The model was used to extrapolate these differences prior to 1993 and a corrected GMSL reconstruction is presented.
Received: 12 Feb 2026 – Discussion started: 23 Feb 2026
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
This manuscript proposes a correction to the Empirical Orthogonal Function (EOF) model used for estimating historical global mean sea level prior to the satellite altimeter period. This correction relies on local winds, the SOI and the signal of tide gauges to “correct” for these local effects impacting coastal sea level that are not captured by the large scale altimeter signal, particularly as expressed through EOFs.
I think this is a useful approach and it is well described in the manuscript. Congratulations to the authors.
I was a little surprised that there was not a larger difference between the corrected and uncorrected GMSL estimates (Figure 12). Perhaps further improvements would result from correcting for the effect of Gravity, Rotational and Deformational (GRD) impacts from changes in the distribution of mass of water stored on land on sea levels, during ENSO events for example. Note Wang et al. (2024) has attempted to include these GRD impacts on reconstructions. There are alternate (possibly better) ways of including these effects the authors might wish to investigate in subsequent studies.
I was surprised that there was no discussion of coastal trapped waves known to be important on the American and Australian coasts. These waves are consistent with the idea behind these corrections of winds affected coastal sea levels with a much reduced impact on sea levels off shore at altimeter grid points. These waves also allow the impacts of remote winds affecting local sea levels, again as studied on the American and Australian coasts. Similarly, ENSO impacts can travel very large distances on the American and Australian coasts. I think the authors should discuss the implication of coastal trapped waves and propagation of remote signal such as those associated with ENSO and distant coastal winds.
There remains some trend differences in Figure 12. Although they are not significant, it would be useful to understand the reasons for the differences. I suspect that GIA differences may be at the heart of these differences. Could the authors comment please rather than just state they are not significantly different.
I recommend that the paper is published after consideration of these comments.
Detailed Comments for the authors to consider:
Lines 60-64: It may be useful to note that Wang et al. (2024) has extended the EOF technique by dispensing with mode zero and instead including spatially variable fingerprints.
Lines 269-282: Would using winds parallel and perpendicular to the coast be useful?
Line 559-560: Can you make the quantitative (and statistical) reasons for preferring on model 3 clearer. I did not pick up this clear preference given the additional parameters used in this more complex model.
References
Wang, Jinping, et al. 2024. Improved sea-level reconstruction from 1900 to 2019. Journal of Climate, 37 (24), 6453-6474. DOI 10.1175/JCLI-D-23-0410.1
This study shows a novel improvement of short term variability in Global Mean Sea level (GMSL) reconstruction. The GMSL is an important measure to assess the health of the planet and good GMSL variability (trend removed) measurements are vital to understanding the sea level budget. Studies have shown that EOF GMSL reconstructions are able to capture the underlying long-term trend in GMSL with reasonable accuracy but fail to reconstruct the shorter-term variability.
This study shows a novel improvement of short term variability in Global Mean Sea level (GMSL)...
General Comments:
This manuscript proposes a correction to the Empirical Orthogonal Function (EOF) model used for estimating historical global mean sea level prior to the satellite altimeter period. This correction relies on local winds, the SOI and the signal of tide gauges to “correct” for these local effects impacting coastal sea level that are not captured by the large scale altimeter signal, particularly as expressed through EOFs.
I think this is a useful approach and it is well described in the manuscript. Congratulations to the authors.
I was a little surprised that there was not a larger difference between the corrected and uncorrected GMSL estimates (Figure 12). Perhaps further improvements would result from correcting for the effect of Gravity, Rotational and Deformational (GRD) impacts from changes in the distribution of mass of water stored on land on sea levels, during ENSO events for example. Note Wang et al. (2024) has attempted to include these GRD impacts on reconstructions. There are alternate (possibly better) ways of including these effects the authors might wish to investigate in subsequent studies.
I was surprised that there was no discussion of coastal trapped waves known to be important on the American and Australian coasts. These waves are consistent with the idea behind these corrections of winds affected coastal sea levels with a much reduced impact on sea levels off shore at altimeter grid points. These waves also allow the impacts of remote winds affecting local sea levels, again as studied on the American and Australian coasts. Similarly, ENSO impacts can travel very large distances on the American and Australian coasts. I think the authors should discuss the implication of coastal trapped waves and propagation of remote signal such as those associated with ENSO and distant coastal winds.
There remains some trend differences in Figure 12. Although they are not significant, it would be useful to understand the reasons for the differences. I suspect that GIA differences may be at the heart of these differences. Could the authors comment please rather than just state they are not significantly different.
I recommend that the paper is published after consideration of these comments.
Detailed Comments for the authors to consider:
Lines 60-64: It may be useful to note that Wang et al. (2024) has extended the EOF technique by dispensing with mode zero and instead including spatially variable fingerprints.
Lines 269-282: Would using winds parallel and perpendicular to the coast be useful?
Line 559-560: Can you make the quantitative (and statistical) reasons for preferring on model 3 clearer. I did not pick up this clear preference given the additional parameters used in this more complex model.
References
Wang, Jinping, et al. 2024. Improved sea-level reconstruction from 1900 to 2019. Journal of Climate, 37 (24), 6453-6474. DOI 10.1175/JCLI-D-23-0410.1