Global Warming: Experts’ Opinions versus Scientific Forecasts
Friday, February 01, 2008
by Kesten C. Green and J. Scott Armstrong
Table of Contents
In 2007, the Intergovernmental Panel on Climate Change (IPCC) issued its Fourth Assessment Report. The report included predictions of big increases in average world temperatures by 2100, resulting in an increasingly rapid loss of the world’s glaciers and ice caps, a dramatic global sea level rise that would threaten low-lying coastal areas, the spread of tropical diseases, and severe drought and floods.
These dire predictions are not, however, the result of scientific forecasting; rather, they are the opinions of experts. Expert opinion on climate change has often been wrong. For instance, a search of headlines in the New York Times found the following:
Sept. 18, 1924 MacMillan Reports Signs of New Ice Age
March 27, 1933 America in Longest Warm Spell Since 1776
May 21, 1974 Scientists Ponder Why World’s Climate Is Changing:
A Major Cooling Widely Considered to be Inevitable
Problems with Computer Models. Climate scientists now use computer models, but there is no evidence that modeling improves the accuracy of predictions. For example, according to the models, the Earth should be warmer than actual measurements show it to be. Furthermore:
- The General Circulation Models (GCMs) that are used failed to predict recent global average temperatures as accurately as fitting a simple curve to the historical data and extending it into the future.
- The models forecast greater warming at higher altitudes in the tropics, whereas the data show the greatest warming has occurred at lower altitudes and at the poles.
- Furthermore, individual models have produced widely different forecasts from the same initial conditions, and minor changes in assumptions can produce forecasts of global cooling.
Skepticism Among the Scientists. Thus it is not surprising that international surveys of climate scientists from 27 countries in 1996 and 2003 found growing skepticism over the accuracy of climate models. Of more than 1,060 respondents, only 35 percent agreed with the statement, “Climate models can accurately predict future climates,” whereas 47 percent disagreed.
Violations of Forecasting Principles. Forty internationally-known experts on forecasting methods and 123 expert reviewers codified evidence from research on forecasting into 140 principles. The empirically-validated principles are available in the Principles of Forecasting handbook and at forecastingprinciples.com. These principles were designed to be applicable to making forecasts about diverse physical, social and economic phenomena, from weather to consumer sales, from the spread of nonnative species to investment strategy, and from decisions in war to egg-hatching rates. They were applied to predicting the 2004 U.S. presidential election outcome and provided the most accurate forecast of the two-party vote split of any published forecast, and did so well ahead of election day (see polyvote.com).
The authors of this study used these forecasting principles to audit the IPCC report. They found that:
- Out of the 140 forecasting principles, 127 principles are relevant to the procedures used to arrive at the climate projections in the IPCC report.
- Of these 127, the methods described in the report violated 60 principles.
- An additional 12 forecasting principles appear to be violated, and there is insufficient information in the report to assess the use of 38.
As a result of these violations of forecasting principles, the forecasts in the IPCC report are invalid. Specifically:
The Data Are Unreliable. Temperature data is highly variable over time and space. Local proxy data of uncertain accuracy (such as ice cores and tree rings) must be used to infer past global temperatures. Even over the period during which thermometer data have been available, readings are not evenly spread across the globe and are often subject to local warming from increasing urbanization. As a consequence, the trend over time can be rising, falling or stable depending on the data sample chosen.
The Forecasting Models Are Unreliable.Complex forecasting methods are only accurate when there is little uncertainty about the data and the situation (in this case: how the climate system works), and causal variables can be forecast accurately. These conditions do not apply to climate forecasting. For example, a simple model that projected the effects of Pacific Ocean currents (El Niño-Southern Oscillation) by extrapolating past data into the future made more accurate three-month forecasts than 11 complex models. Every model performed poorly when forecasting further ahead.
The Forecasters Themselves Are Unreliable. Political considerations influence all stages of the IPCC process. For example, chapter by chapter drafts of the Fourth Assessment Report “Summary for Policymakers” were released months in advance of the full report, and the final version of the report was expressly written to reflect the language negotiated by political appointees to the IPCC. The conclusion of the audit is that there is no scientific forecast supporting the widespread belief in dangerous human-caused “global warming.” In fact, it has yet to be demonstrated that long-term forecasting of climate is possible.