Rethinking Climate Forecasts: IPCC Climate Models Take Hit in Credibility

Here is a fascinating Wharton Business School audit of the reliability of climate forecasting by GCM models. The image of climate modelers becomes more tarnished, the closer one looks at their methods, apparently.

In apparent contradiction to claims by some climate experts that the IPCC provides “projections” and not “forecasts, the word “forecast” and its derivatives occurred 37 times, and “predict” and its derivatives occur 90 times in the body of Chapter 8. Recall also that most of our respondents (29 of whom were IPCC authors or reviewers) nominated the IPCC report as the most credible source of forecasts (not projections) of global average temperature.

....Global climate is complex. Scientific evidence on many key relationships is weak or absent; e.g., does increased CO2 in the atmosphere cause high temperatures or do high temperatures increase CO2 (e.g. Jaworowski 2007)? Measurements of key variables such as local temperatures and a representative global temperature are contentious in the case of modern measurements, because of possible artifacts such as the urban heat island effect, and often speculative in the case of ancient ones, such as those climate proxies derived from tree ring and ice-core data (Carter 2007). Finally, it is difficult to forecast the causal variables.
The already high level of uncertainty rises rapidly as the forecast horizon increases.

While the authors of Chapter 8 claim that the forecasts of global mean temperature are well-founded, their language is imprecise and relies heavily on such words as “generally,” “reasonable well,” “widely,” and “relatively” [to what?]. The report makes many explicit references to uncertainty. For example, the phrases “. . . it is not yet possible to determine which estimates of the climate change cloud feedbacks are the most reliable” and “Despite advances since the TAR, substantial uncertainty remains in the magnitude of cryospheric feedbacks within AOGCMs” appear on p. 593. In discussing the modeling of temperature, the authors wrote, “The extent to which these systematic model errors affect a model’s response to external perturbations is unknown, but may be significant” (p. 608), and, “The diurnal temperature range… is generally too small in the models, in many regions by as much as 50%” (p. 609), and “It is not yet known why models generally underestimate the diurnal temperature range.” The following words and phrases appear at least once in the Chapter: unknown, uncertain, unclear, not clear, disagreement, uncertain, not fully understood, appears, not well observed, variability, variety, difference, unresolved, not resolved, and poorly understood.
Given the high uncertainty, the naïve method for this situation would be the “no-change” model. Remarkably, nowhere does the IPCC Report address the issue of forecastability. It should have been addressed prior to spending enormous sums on complex forecasting models.

In effect, given the current state of uncertainty regarding climate, prior evidence on forecasting methods suggests that attempts to improve upon the naïve model might increase forecast error. To reverse this conclusion, one would have to produce validated evidence in favor of certain methods. Such evidence is not provided in Chapter 8 of the IPCC report.

....It is not clear to what extent the models produced by the IPCC are either based on, or have been tested against, sound empirical data. However, some statements were made about the ability of the models described in Chapter 8 to fit historical data, after tweaking of their parameters. Extensive research has shown that the ability of models to fit historical data has little relationship to forecast accuracy (See “Evaluating Methods” in Armstrong 2001.) It is well known that fit can be improved by making the model more complex. The consequence of increasing complexity to improve fit, however, is to decrease the accuracy of forecasts. The 12 authors of Chapter 8 appeared to be unaware of this principle.

....A list of the 72 violations of forecasting principles by the authors of IPCC Chapter 8 is provided on the Public Policy Special Interest Group Page at forecastingprinciples.com. The many violations provide further evidence that the authors were unaware of evidence-based principles for forecasting. If they were aware of them, it would have been incumbent on them to present evidence to justify their departures from best forecasting practice. They did not do so. We conclude that because the forecasting processes described in the Chapter overlook scientific evidence on forecasting, the IPCC forecasts of climate change are not scientific.

...History is filled with the poor treatment of those who attempt to introduce science into arenas where emotions are high and vested interests are threatened. Galileo springs to mind. Scientists in the West at least no longer face death when presenting their findings. Nevertheless, the scientific review system currently acts to prevent the publication of research findings that conflict with commonly held beliefs (for a review of research on this matter, see Armstrong 1997).
We recommend the use of objective evidence-based (scientific) procedures to assess the validity of global warming forecasts. Our belief is that science will win out in the long run. The problem is that we may waste enormous resources over a short-run that might last for the next few decades.

Read much more at the Source

For a closer look at this audit of the recent IPCC report, and for a particularly lively discussion in comments, go here.

None of this incriminating information is news to those who follow the more credible climate sites, such as Climate Science and Climate Audit. But for those who pliantly believe that RealClimate.org is the final word on all things climate, the future is rife with disillusionment. Many billions of dollars are at stake, in research grants, carbon credits, Al Gore movies and rock concerts, and other areas.

This is not a time to place your faith in another corrupt UN agency. Although most recent university graduates (last 10 to 15 years) are academically lobotomised, thus compromised in their ability to think independently, this is definitely a time to think for yourself.