Here’s an excellent article at theclimatebet.com that’s well worth a read.
Using a forecasting method that they have developed, Dr. J. Scott Armstrong from the Wharton School and Dr. Kesten C. Green from the International Graduate School of Business at the University of South Australia conclude that alarm over “dangerous manmade global warming” is the latest example of a common social phenomenon involving alarming but unscientific forecasts that prove to be wrong. This is a preliminary finding from the “global warming analogies forecasting project.” The researchers stressed that the findings are preliminary because they are still collecting and coding information on similar situations from the past.
Armstrong and Green used a method known as “structured analogies.” For the global warming analogies forecasting project, the method first involved conducting a wide and objective search for situations similar to the alarm over forecasts of dangerous manmade global warming. For each analogous situation the forecasting procedures used by the alarmists and the actual outcomes of the situations were coded. The structured analogies procedures had previously been shown to provide excellent forecasts compared to those from commonly used alternative procedures.
To date, 71 situations have been proposed and 26 of them were found to meet all criteria of similarity. Of the latter, none were based on forecasts from scientific procedures. Instead they were based on dramatic speculation of one sort or another.
Typically, the alarmists recommend government action, and governments usually respond. They did so in 25 of the 26 analogous situations, and government took action in 23.
We asked: How many of the 26 analogous alarming forecasts were accurate?
The answer is “none”.
In how many of the 23 analogies were the government solutions shown to be helpful?
None. In fact, in 20 situations there was substantial long-term harm from the government solutions.
The authors are hopeful that the continuing evidence on the anti-scientific procedures used by people involved in the manmade global warming alarmist movement, such as has been exposed by ClimateGate, will help to reduce the damage from the alarm in the long run. However, the analogies offered little hope on that score. Most of the previous alarms, such as over DDT and electromagnetic fields, continued to cause substantial harm many years after they had been shown to be false.
Julian Simon and others had suggested that such a pattern exists for forecasts of doom, but we were surprised at the strength of our findings. In retrospect, the findings seem less surprising. Extreme events are difficult to forecast, especially in complex and uncertain situations. So the application of unscientific forecasting procedures supported by politics would be unlikely to produce useful forecasts.
The authors stress that this is an early progress report. They hope to stimulate global warming alarmists to propse analogies that support their forecasts. They also suggest that all important public policy forecasts would benefit by using the structured analogies method.