Abrupt changes, multidecadal variability and long-term trends in sea surface temperature and sea level datasets within the southeastern Bay of Biscay

Abstract

Multidecadal variability and long-term trends of Sea Surface Temperature (SST) and Sea Level (SL) datasets for the southeastern Bay of Biscay have been examined. The SST dataset (Aquarium of San Sebastián), measured on a nearly daily basis, extends from 1947 to 2010. The daily SL data utilised are those from Santander (IEO tide gauge network) and from St. Jean de Luz (SHOM), spanning the periods 1943–2004 and 1964–1997, respectively. This paper presents an approach for the extraction of multidecadal variability and long-term trends. First of all, the KZA (Kolmogorov–Zurbenko Adaptive) filter was used to detect possible discontinuities in time-series. Subsequently, the seasonal and multidecadal variability was identified by spectral analysis and further quantified by least squares fitting. Finally, prior to the trend determination, the long-term natural variability was removed. The results revealed significant contribution of the annual component to the SST and SL, with a weaker contribution of the semiannual signal. The sea level air pressure and long-term tides also contributed to the SL variability. The estimated trends were less than those obtained by other authors. The analysis revealed no trend in the SST and the Jean de Luz SL series, whilst an increasing trend was detected for the Santander SL dataset.