2013
DOI: 10.1007/s12145-013-0114-6
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Sea level in the Mediterranean Sea: seasonal adjustment and trend extraction within the framework of SSA

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Cited by 23 publications
(7 citation statements)
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References 60 publications
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“…Bonaduce et al (2016) showed that, during the period from 1993 to 2012, the estimated mean sea level trend over the Mediterranean had a positive value of 2.44 ± 0.5 mm/year. This is the same result as for Haddad et al (2013) obtained by performing a singular spectrum analysis with altimetry data to estimate the seasonal cycle and trends over the same period. However, changes in the local sea level were substantial and altogether different in the two studies.…”
Section: Introductionsupporting
confidence: 78%
“…Bonaduce et al (2016) showed that, during the period from 1993 to 2012, the estimated mean sea level trend over the Mediterranean had a positive value of 2.44 ± 0.5 mm/year. This is the same result as for Haddad et al (2013) obtained by performing a singular spectrum analysis with altimetry data to estimate the seasonal cycle and trends over the same period. However, changes in the local sea level were substantial and altogether different in the two studies.…”
Section: Introductionsupporting
confidence: 78%
“…The trend for η MSL , shows a rise of 2.44 ± 0.5 mm year −1 from 1993 to 2012, after first removing the seasonally repeating cycle and considering the contribution of GIA as a mean value (Peltier 2004b(Peltier , 2009Stocchi and Spada 2009;Meyssignac et al 2011). The observed positive sea-level trend is in agreement with the resuts of Haddad et al (2013) obtained by performing a singular spectrum analysis (SSA) with satellite altimetry data to estimate the seasonal cycle and trend, in almost the same analysis period.…”
Section: Significance Of the Linear Sea-level Trendsupporting
confidence: 78%
“…Until now, there has been no unified principle for selecting the optimal embedding dimension, and the suggested ranges are based on experience and specific types of signals. Many methods have been developed based on SSA, including Auto‐SSA (Haddad et al., 2013), multichannel SSA (Ghil et al., 2002), and Monte Carlo SSA (Allen & Smith, 1996). However, none of these methods achieve adaptive selection of the optimal embedding dimension.…”
Section: Introductionmentioning
confidence: 99%
“…SSA is another commonly used method for sea level data analysis (Haddad et al, 2013;Jevrejeva et al, 2006;Nitsche et al, 2005;Unal & Ghil, 1995;Watson, 2011Watson, , 2016a. It is a superior analytical tool capable of decomposing sea level records into the sum of interpretable components including slowly varying trends, oscillatory components with variable amplitudes and noise, and without a priori information on the time series structure.…”
mentioning
confidence: 99%
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