Scientific theories should be judged on their ability to make predictions, so I am always on the lookout for papers that test theories against new data.
This week, I found an interesting website about climate research. It's the Science and Public Policy Institute (scienceandpublicpolicy.org). So I looked for new developments and found a collection of papers from November 16, 2009: 450 Peer Reviewed Papers Supporting Skepticism of AGW-Caused Global Warming by Anthony Watts.
So I looked through the list of papers, hoping to find a paper that tested the predictions of climate change models and found a July 2009 meta-paper that sounded intriguing: Climate Projections: Past Performance No Guarantee of Future Skill? by C. Reifen and R. Toumi published in Geophysical Research Letters.
Turns out that the 17 climate models used by the Intergovernmental Panel on Climate Change (NASDAQ:IPCC) fit the data very well for whatever period they were designed to explain, but do no better than chance when applied to a different period during the 20th Century. They found:
In our analysis there is no evidence of future prediction skill delivered by past performance-based model selection. There seems to be little persistence in relative model skill, as illustrated by the percentage turnover in Figure 3. We speculate that the cause of this behavior is the non-stationarity of climate feedback strengths. Models that respond accurately in one period are likely to have the correct feedback strength at that time. However, the feedback strength and forcing is not stationary, favoring no particular model or groups of models consistently. For example, one could imagine that in certain time periods the sea-ice albedo feedback is more important favoring those models that simulate sea-ice well. In another period, El Nino may be the dominant mode, favoring those models that capture tropical climate better. On average all models have a significant signal to contribute.The authors are not global warming skeptics. Their conclusion is that all of the models need to be taken as a group in order to have predictive power. But there is a much more obvious explanation that jumps out of the page: All of these models have many many variables (i.e., "feedback strengths") which allow them to fit whatever time period they were designed to fit, but they don't work when applied to a different time period.
In other words, the feedback strengths in these models are all free parameters. If you have enough free parameters you can make almost any model fit anything. These models don't work.
Furthermore, if the group of models is applied to a different time period as a whole, they don't work as a whole. Witness the article just posted this week at Spiegel Online: Climatologists Baffled by Global Warming Time-Out, which points out that global warming appears to have stopped during the 21st Century.
As best as I can make out, the situation in climate prediction science is the following:
- 1. The Anthropogenic Global Warming (AGW) theory was once the best theory available for explaining climate change.
- 2. The new theory of cosmoclimatology, developed since 1996, is now the best theory available for explaining climate change. It involves three factors: cosmic rays, solar activity, and magnetic fields, without requiring innumerable free parameters that must be adjusted. So far it has made excellent predictions whether the period be months, years, or millennia.
The attacks on what the Global Warmers deem as 'solar theory' are the product of disgraceful dishonesty which marks the integrity of the scientific establishment at its lowest level since the Papal Inquisition.The world's leaders are set to meet in Copenhagen in December to discuss a possible treaty to reduce world emissions of CO2, the gas crucial to photosynthesis which is thought by the AGW theorists to cause global warming. Before they do anything they should listen to a talk by cosmoclimatologist Henrik Svensmark of the Danish National Space Center at the Technical University of Denmark. He could tell them about the factors that make correct predictions about climate change.
The main periodical solar activity effect - the largest observed periodicity present in world temperature data - is the 22 year cycle (driven by sun-earth magnetic connectivity). Hence for about half the time, the 11 year cycle of solar activity of particles, sunspots and radiation will move with temperature and half the time move against it. This is well known to solar and climate scientists. All the pseudo-scientists have done is essentially choose time spans where the two move in opposite directions and ignore demonstrated correlations on longer time spans....
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