Facts to fit the theory
<p>On 12 Oct 2009, climatologist and &#8220;hockey-team&#8221; member Kevin Trenberth <a href="http://www.eastangliaemails.com/emails.php?eid=1048&#038;filename=1255352257.txt">wrote</a>:</p>
<blockquote><p>
The fact is that we canâ€™t account for the lack of warming at the moment and it is a travesty that we canâ€™t. The CERES data published in the August BAMS 09 supplement on 2008 shows there should be even more warming: but the data are surely wrong.
</p></blockquote>
<p>Eyebrows have quite rightly been raised over this quote.  It is indeed a travesty that AGW theory cannot account for the lack of warming, and bears out what I and other AGW critics have been saying for years about the fallaciousness and lack of predictive power of AGW models.</p>
<p>But the second sentence is actually far more damning.  &#8220;The data is surely wrong.&#8221;  This is how and where most scientific fraud begins.</p>
<p>Scientific fraudsters are not, in general, people pushing theories they know to be false.  Outright charlatanism is not actually common, because it&#8217;s relatively easy to detect.  Humans are evolved for a social competitive environernt<br />
 and are rather good at spotting lies, <em>except when they&#8217;re fooling themselves because they want to believe.</em></p>
<p>In general, scientific fraudsters are people who are overinvested in a theory that they believe. Because they know it must be true, they interpret predictive failures as &#8220;The data is surely wrong&#8221;.  It is only a short step from  &#8220;The data is surely wrong&#8221; to fixing the pesky data until it looks right &#8212; see my previous post  for an immediate example.</p>
<p>It&#8217;s only slightly longer step after that to destroying the inconvenient data that fails to fit your theory &#8212; something one of the hockey-teamers actually <a href="http://www.eastangliaemails.com/emails.php?eid=891&#038;filename=1212063122.txt">called for</a> and there is strong reason to suspect they actually did.</p>
<p>Sometimes, actually, the data <em>is</em> wrong.  Occasionally, experimental error will appear to falsify a theory that is actually correct.  But  research groups are entitled to the benefit of that doubt only when they meet the most rigorous standards of full disclosure about the &#8220;wrong&#8221; data.  Not when their reaction is to conceal and destroy it.</p>
