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<article language="en">
	<journal>
		<journal_title>Ocean Science</journal_title>
		<journal_url>www.ocean-sci.net</journal_url>
		<issn>1812-0784</issn>
		<eissn>1812-0792</eissn>
		<volume_number>2</volume_number>
		<issue_number>2</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/os-2-147-2006</doi>
	<article_url>http://www.ocean-sci.net/2/147/2006/</article_url>
	<abstract_html>http://www.ocean-sci.net/2/147/2006/os-2-147-2006.html</abstract_html>
	<fulltext_pdf>http://www.ocean-sci.net/2/147/2006/os-2-147-2006.pdf</fulltext_pdf>
	<start_page>147</start_page>
	<end_page>159</end_page>
	<publication_date>2006-10-12</publication_date>
	<article_title content_type="html">Temporal and spatial characteristics of sea surface height  variability in the North Atlantic Ocean</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>D. Cromwell</name>
			<email>ddc@noc.soton.ac.uk</email>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Ocean Observing and Climate, National Oceanography Centre, Southampton (NOCS),  Room 254/35, European Way, Southampton SO14 3ZH, UK</affiliation>
	</affiliations>
	<abstract content_type="html">We investigate the spatial and temporal variability of sea surface height
(SSH) in the North Atlantic basin using satellite altimeter data from
October 1992&amp;ndash;January 2004. Our primary aim is to provide a detailed
description of such variability, including that associated with propagating
signals. We also investigate possible correlations between SSH variability
and atmospheric pressure changes as represented by climate indices.

&lt;P&gt;
We first investigate interannual SSH variations by deriving the complex
empirical orthogonal functions (CEOFs) of altimeter data lowpass-filtered at
18 months. We determine the spatial structure of the leading four modes
(both in amplitude and phase) and also the associated principal component
(PC) time series. Using wavelet analysis we derive the time-varying spectral
density of the PCs, revealing when particular modes were strongest between
1992&amp;ndash;2004. The spatial pattern of the leading CEOF, comprising 30% of the
total variability, displays a 5-year periodicity in phase; signal
propagation is particularly marked in the Labrador Sea. The second mode,
with a dominant 3-year signal, has strong variability in the eastern basin.

&lt;P&gt;
Secondly, we focus on the Azores subtropical frontal zone. The leading mode
(35%) is strong in the south and east of this region with strong
variations at 3- and 5-year periods. The second mode (21%) has a
near-zonal band of low variance between &amp;nbsp;22&amp;deg;&amp;ndash;27&amp;deg;&amp;nbsp;N,
sandwiched between two regions of high variance. Thirdly, we lowpass filter
the altimeter data at a cutoff of 30 days, instead of 18 months, in order to
retain signals associated with propagating baroclinic Rossby waves and/or
eddies. The leading mode is the annual steric signal, around 46% of the
SSH variability. The third and fourth CEOFs, &amp;nbsp;11% of the remaining
variability, are associated with westward propagation which is particularly
dominant in a &quot;waveband&quot; between 32&amp;deg;&amp;ndash;36&amp;deg;&amp;nbsp;N.

&lt;P&gt;
For all three cases considered above, no significant cross-correlation is
found between the North Atlantic Oscillation index and the amplitude of the
leading four PCs of interannual SSH variability. The only exception is an
anti-correlation found over the North Atlantic basin between the NAO and the
4th PC. In the subtropical front, the East Atlantic Pattern index is
anti-correlated with the leading PC for SSH variations lowpass filtered at
30 days. Further investigation of forcing mechanisms is suggested using
hindcasts from ocean general circulation models.</abstract>
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</article>

