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Mean sea level is a variable of considerable interest in meteorologicaland oceanographic studies, particularly long-term sea level variationand its relation to climate changes.This study concerns the analysis of monthly mean sea level data fromtide gauge stations in the Northeast Atlantic with long and continuousrecords.Much research effort on mean sea level studies has been focused onidentifying long-term linear trends, usually estimated through least-squaresfitting of a deterministic function. Here, we estimate nonparametricand robust trends using lowess, a robust smoothing procedure basedon locally weighted regression. This approach is more flexible thana linear trend to describe the deterministic part of the variationin tide gauge records, which has a complex structure.A common trend pattern of reduced sea levels around 1975 is foundin all the analysed records and interpreted as the result of hydrologicaland atmospheric forcing associated with drought conditions at the tidegauge sites. This feature is overlooked by a linear regression model.Moreover, nonlinear deterministic behaviour in the time series, suchas the one identified, introduces a bias in linear trends determinedfrom short and noisy records.  <b>Key words.</b> Oceanography: physical (sea level variations);Hydrology (water balance

Nonlinear sea level trends from European tide gauge records