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
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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)...
