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	<journal>
		<journal_title>Climate of the Past</journal_title>
		<journal_url>www.clim-past.net</journal_url>
		<issn>1814-9324</issn>
		<eissn>1814-9332</eissn>
		<volume_number>3</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2007</publication_year>
	</journal>
	<doi>10.5194/cp-3-397-2007</doi>
	<article_url>http://www.clim-past.net/3/397/2007/</article_url>
	<abstract_html>http://www.clim-past.net/3/397/2007/cp-3-397-2007.html</abstract_html>
	<fulltext_pdf>http://www.clim-past.net/3/397/2007/cp-3-397-2007.pdf</fulltext_pdf>
	<start_page>397</start_page>
	<end_page>409</end_page>
	<publication_date>2007-07-11</publication_date>
	<article_title content_type="html">On the verification of climate reconstructions</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>G. Bürger</name>
			<email>gerd.buerger@met.fu-berlin.de</email>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">FU-Berlin, Institut für Meteorologie; Carl-Heinrich-Becker-Weg 6&amp;ndash;10, 12165 Berlin, Germany</affiliation>
	</affiliations>
	<abstract content_type="html">The skill of proxy-based reconstructions of Northern hemisphere
temperature is reassessed. Using an almost complete set of proxy and
instrumental data of the past 130 years a multi-crossvalidation is
conducted of a number of statistical methods, producing a distribution
of verification skill scores. Among the methods are multiple
regression, multiple inverse regression, total least squares, RegEM,
all considered with and without variance matching. For all of them the
scores show considerable variation, but previous estimates, such as a
50% reduction of error (&lt;i&gt;RE&lt;/i&gt;), appear as outliers and more realistic
estimates vary about 25%. It is shown that the overestimation of
skill is possible in the presence of strong persistence (trends). In
that case, the classical &quot;early&quot; or &quot;late&quot; calibration sets are
not representative for the intended (instrumental, millennial)
domain. As a consequence, &lt;i&gt;RE&lt;/i&gt; scores are generally inflated, and the
proxy predictions are easily outperformed by stochastic, a priori
skill-less predictions.
&lt;br&gt;&lt;br&gt;
To obtain robust significance levels the multi-crossvalidation is
repeated using stochastic predictors. Comparing the score
distributions it turns out that the proxies perform significantly
better for almost all methods. The scores of the stochastic predictors
do not vanish, nonetheless, with an estimated 10% of spurious skill
based on representative samples. I argue that this residual score is
due to the limited sample size of 130 years, where the memory of the
processes degrades the independence of calibration and validation
sets. It is likely that proxy prediction scores are similarly inflated
and have to be downgraded further, leading to a final overall skill
that for the best methods lies around 20%.
&lt;br&gt;&lt;br&gt;
The consequences of the limited verification skill for millennial
reconstructions is briefly discussed.</abstract>
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