Examining Crucial Flaws in the Scientific Methodology Used in Global Warming Forecasts

12 05 2008

Today politicians of both U.S. political parties are stating that a “scientific consensus” exists regarding the presence of global warming. However, objective scientific evidence exists regarding critical flaws in the scientific methodology used to develop the model based forecasts used to support global warming.

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Following is an Executive Summary of the National Center for Policy Analysis (http://www.ncpa.org/) report titled “Global Warming: Experts’ Opinions versus Scientific Forecasts” (full report available here) by Kesten Green and J. Scott Armstrong, published February 2008. This report was discussed in a more general manner in a previous post (here). Following the contents of the Executive Summary, some additional comments will be provided about the challenge of developing accurate forecasts from my perspective as an agricultural economist.



Executive Summary:”Global Warming: Experts’ Opinions versus Scientific Forecasts”

National Center for Policy Analysis Report No. 308, by Kesten Green and J. Scott Armstrong

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.

(end of Executive Summary)

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(K-2 in the Himalayas)


Following are my own opinions regarding the reliability of “model based forecasts”…..

Over the last decade or more much debate has occurred within the discipline of agricultural economics regarding the reliability of forecasts derived from econometric models. It is my understanding that at the present time within the discipline of economics (general economics as well as the agricultural branch of the discipline) model-based forecasts of the future are judged to be inherently problematic and prone to inaccuracy.

The difficulty that economists have in developing accurate forecasts is due at least in part to the challenges we have on the one hand in accurately modeling underlying economic processes. In addition, economists have found it difficult to accurately project future values of the key explanatory variables in these same models from which we hope to make exante conditional projections of future values the models’ dependent variables. In normal human speech, what I have just said is that it is important for economists to be extremely humble and cautious about the accuracy of forecasts of the future based on our economic modeling efforts. It is an extremely difficult task to first model economic reality, and then second, to attempt to make forecasts of the future based on your current understanding of underlying economic processes (represented by these same models). The processes themselves may change over time to go along with the fact that we often have inadequate understanding of the critical economic factors involved in such economic processes.

As an agricultural economist with at least a working knowledge of the inherent difficulties of using models to forecast such things as future grain prices, and realizing the need to identify if at all possible the confidence intervals within which any economic forecast may fall, it is extremely troubling to me to consider the “fast and loose” manner in which model-based forecasts of global warming impacts have been developed by climatologists. Problems exist with a) the climatological data being relied upon, b) with the climate models themselves that are being used in an attempt to accurately and comprehensively represent extremely complicated weather – environmental systems, and c) the evident bias in findings of such groups as the Intergovernmental Panel on Climate Change (IPCC) in selecting models that support their presuppositions about global warming without the required scientific rigor and discipline needed for such an economically and socially critical subject.

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There is much to ponder in regards to the “group think” being thrust upon the public in regards to Global Warming ideas and beliefs.

The Longer Term Risks to Universities of Ill-founded Climatological Forecasting Efforts

Academics should consider the risk of damage to their professional credibility that could occur if their climatological model forecasts of global warming impacts are proven wrong by the climate itself in 5, 10, 15 years. We in the university system appear to be entrusting ourselves to the findings of some very questionable climate change forecast model methodologies.

Will the public still be willing to support us as Universities if, after instituting costly “cap and trade” schemes and other “green” economic and environmental prescriptions motivated by our global warming supportive forecasts, the possibility of disruptive catastrophic energy supply shortfalls come to fruition and associated economic and social crises ensue? Given that the economic well-being of the U.S. economy and our very families are at stake, we as academics should be more prudent and judicious in adherence to our scientific principles in this matter of deriving forecasts supportive of global warming impacts. And, given that the scientific principles of forecasting appear to have not been adequately adhered to in the development of global warming-related climatological models, well, we have now placed ourselves in a very, very risky position indeed.

God help us to be wise and judicious and balanced in our scientific recommendations on the issues of climate change, global warming, and energy development.


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