Here are the results of my simple multi-layer greenhouse experiment, conducted in December when the weather was hot and stable, not mild and rainy as it is now. The experimental setup is shown below, with two laboratory thermometers, and a mercury one to check. One sensor was attached to a 6in black tile sitting on the EPS box, the other on the glass surface. On top were up to 5 alternating layers of EPS and picture glass, as shown below.
CommentsMy forecast for the economy – back to the 50’s.
Barrick’s Munk coy on gold at Davos.
Atlas Shrugged Movie with Angela Jolie?
Search research tool from Google.
Davos Delegates in ‘Denial’ as $25 Trillion of Wealth Vanishes – More fedoras at Davos.
This is not the sort of news I usually pick up on, but I quote below the retired senior NASA atmospheric scientist Dr. John S. Theon, and former supervisor of James Hansen, both because of the relevance to modelling practise, and because he captures so exactly what has driven me out of science over the last 5 years, and onto the blogosphere.
CommentsI have tweaked the interface of WikiChecks and added some new analysis. It will take a range of analysis before I get a good enough sample, but already there is an amazing degree of insight coming out of this technique. Below is a list of some of the new additions, and whether the last digit deviates from randomness.
CommentsA reported increase in the longwave downward radiation in the Swiss Alps, proves the ‘‘theory’’ of greenhouse warming with direct radiation observations according to this paper, “Radiative forcing – measured at Earth’s surface – corroborate the increasing greenhouse effect”, by Rolf Philipona, Bruno Durr, Christoph Marty, Atsumu Ohmura and Martin Wild.
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Beautiful image. Cute article. Temperatures back to normal. It’s a ill wind that carries no good they say.
CommentsWhile reading Hansen’s latest mailout I came upon an intriguing reference that I followed up. I suspect this paper is as important as Douglass et al. in describing an important way the models do not agree with the observations. It may be more important, in redefining the role of the Sun in recent warming.
CommentsThe next step in the statistical forensics process is to breakdown the data in ways that reveal where the anomolous divergences are coming from. Here I am indulging in classical scientific reduction methodology by examining overall phenomena in terms of the sum of its parts.
CommentsThermodynamic Efficiency and Entropy Production in the Climate System
Authors: Valerio Lucarini
(Submitted on 14 Jan 2009)
Cross posted at WikiChecks.
I pasted in monthly data from the Swiss bank UBS and found significant management. The file used was this. The digit frequency shows an excess of zeros and ones and a deficiency of 7s and 8s. One possible explanation is that figures slightly below a whole number have been boosted to slightly above a whole number (eg. 3.9% to 4.1%).
CommentsDetecting ‘massaging’ of data by human hands is an area of statistical analysis I have been working on for some time, and devoted one chapter of my book, Niche Modeling, to its application to environmental data sets.
The WikiChecks web site now incorporates a script for doing a Benford’s analysis of digit frequency, sometimes used in numerical analysis of tax and other financial data.
I have posted some initial tests on the site: random numbers and the like. I also ran each of the major monthly global temperature indices through the site: GISS, RSS, UAH and CRU. The results, listed from lowest deviation to highest are listed below.
CommentsDr Roy Spencer has a new blog. His latest post describes a study demonstrating another possible negative feedback produced by clouds. Of more interest to me, he exposes the bias in the academic publication system, due to no explicit mention of the possible relevance of this negative feedback to moderating warming in climate models. Simply, he thinks it would not have got published if it did.
CommentsAnother way to predict — lie about your success rate.
Mathematical analysis in 1999 showed Madoff’s returns were impossible and repeated warnings went unheeded. Competitor Markopolos complained to the SEC’s Boston office in May 1999, saying it was impossible for the kind of profit Madoff was reporting to have been gained legally. Markopolos reached his conclusion with the help of mathematicians like Dan diBartolomeo, whose analysis of the Madoff’s methods in 1999 helped fuel Markopolos’ suspicions. Read the rest of this entry…
Nassim Taleb, author of “The Black Swan”; gives us another example of how to predict. His strategy is to predict eventualities that are possible only remotely, yet are highly consequential. This is also called the Chicken Little Strategy – ‘the sky is falling’. Like global warming.
CommentsPrediction is dangerous to your reputation.
If you don’t make a clear prediction (a climate cycle, a solar cycle, a financial trend…) then you are just doing your best. What comes does not damage your reputation.
CommentsLatest results from RSS for global temperature in the lower atmosphere show a decline in December 2008 to 0.174 from 0.216 in the previous month. Two early leaders in the ‘Guess the monthly global temperatures’ competition have emerged: CoRev and Jan Pompe. Below are the questions so-far, and all the punters with at least one correct prediction of the direction of monthly global temperature.
CommentsJennifer Marohasy concurs that the AIMS GBR study presents level 5 evidence (merely expert opinion) that measured decline in coral growth is due to anthropogenic global warming.
CommentsThis newly released study from the Australian Institute of Marine Science in Townsville is getting a lot of press. An interview with the author Glen De’ath by the ABC claims a tipping point for coral growth has already been reached in 1990. Mongabay.com claims the growth of coral in Australia’s Great Barrier Reef has slowed its lowest rate in at least 400 years as a result of warming waters and ocean acidification.
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