Problem 5. Why do most of the forecasts of climate science fail?
If climate science had a history of accurate forecasts, it would have a foundation for greater credibility. That is what is expected in other fields. Instead, it is “denialist” to say that climate science has a lousy record of predictions.
When I started analysing ecological models in my doctoral studies, it wasn’t ideologically unsound to say that the models did a lousy job, and I spent 3 years trying to work out why. Wouldn’t you think that something could be learned by diagnosing why predictions fail, and coming up with solutions?
What do these examples have in common?
Example 1. Arctic Ice
June 5th, 2009: On Climate Progress, NSIDC director Serreze explains the â€œdeath spiralâ€ of Arctic ice, (and the â€œbreathtaking ignoranceâ€ for blogs like WattsUpWithThat).
April 4, 2010: Dr. Serreze said this week in an interview with The Sunday Times: “In retrospect, the reactions to the 2007 melt were overstated.” (not breathtakingly ignorant?)
Example 2. Australian Drought
Sept 8th 2003: Dr James Risbey, Monash University: “That means in southern Australia weâ€™d see more or less permanent drought conditions…”
Jan 2009-10: Less permanent drought conditions …
Example 3. Global Temperature and Sea Level Rise
4 May 2007: Rahmstorf et.al. claims that previous projections of the IPCC have underestimated climate change, particularly temperatures and sea level rise.
21 June 2009: “In hindsight, the averaging period of 11 years that we used in the 2007 Science paper was too short to determine a robust climate trend.”
Example 4. Hurricanes
July 31, 2005 : MIT Professor Kerry Emanuel “My results suggest that future warming may lead to an upward trend in [hurricanes’] destructive potential.”
24 Feb 2010: WMO: â€œ. . . we cannot at this time conclusively identify anthropogenic signals in past tropical cyclone data.â€
One of the most common reasons for failure of models is statistical extrapolation of trends, and the failures above qualify. You don’t see any climate predictions that run counter to the trend. In all cases, they mistook a natural variation for an anthropogenic effect.
Presumably the authors of projections justified them with physical reasons (e.g. increases in energy, sensitivity, etc.), in order to link with the (apparently) deterministic increase in CO2.
Even though the mistakes appear to be caused by naive extrapolation, they are based on both extrapolation of CO2 increases (uncontentious) AND the assumption of a deterministic link with CO2 levels (contentious).
The lack of climate predictions that run counter to the short-term trend is typical of ex post facto (after-the-fact) physical explanations, and what appears to be a false assumption of deterministic relationships.
Here is the complete list of things caused by global warming.