Nonlinear sea level trends from European tide gauge records

S M Barbosa,M E Silva,M J Fernandes

doi:10.5194/angeo-22-1465-2004

Abstract

Abstract. Mean sea level is a variable of considerable interest in meteorological and oceanographic studies, particularly long-term sea level variation and its relation to climate changes. This study concerns the analysis of monthly mean sea level data from tide gauge stations in the Northeast Atlantic with long and continuous records. Much research effort on mean sea level studies has been focused on identifying long-term linear trends, usually estimated through least-squares fitting of a deterministic function. Here, we estimate nonparametric and robust trends using lowess, a robust smoothing procedure based on locally weighted regression. This approach is more flexible than a linear trend to describe the deterministic part of the variation in tide gauge records, which has a complex structure. A common trend pattern of reduced sea levels around 1975 is found in all the analysed records and interpreted as the result of hydrological and atmospheric forcing associated with drought conditions at the tide gauge sites. This feature is overlooked by a linear regression model. Moreover, nonlinear deterministic behaviour in the time series, such as the one identified, introduces a bias in linear trends determined from short and noisy records.Key words. Oceanography: physical (sea level variations); Hydrology (water balance)

Highlights

Sea level is a variable of considerable interest in meteorological and oceanographic studies
These long records are the focus of much research effort on mean sea level, as they constitute the only source of historical, precise sea level measurements
Nonparametric and robust lowess trends were estimated from tide gauge records in the Northeast Atlantic

Summary

Introduction

Sea level is a variable of considerable interest in meteorological and oceanographic studies. Satellite altimetry allows global measurements of absolute sea level in a precise reference frame This is a considerably recent technique and altimetric records span a time interval (less than two decades) which is too short to allow the detection of long-term trends. In this study we analyse monthly mean sea level data from tide gauge stations in the Northeast Atlantic with long and continuous records: Newlyn, Brest and Cascais. Previous work using tide gauge records from these stations was carried out by Woodworth et al (1991), who estimated a linear trend of approximately 1–2 mm/year for sea level around the British Isles; Dias and Taborda (1988) studied Cascais data and estimated a linear trend of 1.3 mm/year; Araujo et al (2001, 2002) estimated separate trends for tides, surges and mean sea level from Newlyn and Brest records. Data analysis was carried out using R software for statistical computing (Ihaca and Gentleman, 1996), and maps with Generic Mapping Tools (Wessel and Smith, 1998)

Data analysis

Estimation of trends

Findings

Discussion

Conclusions