Archive for the ‘forecasting’ Category
In his talk on March 9, 2009 at the International Climate Change Conference in New York City, Wharton Professor J. Scott Armstrong will announce the launch of a prediction market on the outcome of the „Climate Bet‟ he proposed to Mr. Gore in 2007. Prediction markets are a structured scientific approach to eliciting and summarizing peoples‟ opinions. The Climate Bet prediction market is part of a project led by Andreas Graefe, a researcher at the Karlsruhe Institute of Technology (KIT) in Germany, to examine the use of prediction markets for controversial public policy issues. Are prediction markets useful in aiding the democratic process? Read the rest of this entry »
As they did in 2008, organizers of The International Climate Change Conference are hosting a similar forum entitled “Global Warming Canceled” in New York on March 8-10 of 2009. The Conference, sponsored The Heartland Institute, is intended to encourage an unbiased scientific evaluation of global warming.
Dan Miller, executive vice president of The Heartland Institute explains, “No corporate dollars earmarked for the event were solicited or accepted.” This creates a unique setting for a discussion of global warming; an issue that often incorporates political and corporate interests. Nearly 1000 scientists and experts from around the world will be attending the conference…more
In a recent interview conducted by LA VANGUARDIA, Scott Armstrong takes on challenges regarding his stance on climate change. Armstrong defends his position and explains why the global warming scare is a sham. The interview appeared in La Contra in Spanish, but has also been translated to English
Armstrong counters interviewer Laura Guerrero with his own “Inconvenient Truth” in explaining the fabrication of global warming. Armstrong calls global warming:
A falseness with ulterior motives, because thousands of bureaucrats and politicians make a living on convincing us that the world is in danger and that we need them and their salaries to save us.
The precautionary principle is a political principle, not a scientific one. The principle is used to urge the cessation or avoidance of a human activity in situations of uncertainty, just in case that activity might cause harm to human health or the natural environment. There is an interesting discussion of the history of the term in Wikipedia.
In practice, the precautionary principle is invoked when an interest group identifies an issue that can help it to achieve its objectives. If the interest group is successful in its efforts to raise fears about the issue, the application of the scientific method is rejected and a new orthodoxy is imposed. Government dictates follow. People who dissent from the orthodox view are vilified, ostracized, and may have their livelihoods taken away from them.
Consider the case of “climate change”. Warnings of dangerous manmade global warming from scientists, politicians, and celebrities have received much publicity. They admonish us to dramatically reduce emissions of CO2 in order to prevent disaster over the course of the 21st Century. Efforts have been made to stifle a scientific approach to the issue. In an article titled “Veteran climate scientist says ‘lock up the oil men’“, James Hanson, who heads the NASA Goddard Institute for Space Studies, was quoted as suggesting that those who promote the ideas of global warming skeptics should be “put on trial for high crimes against humanity.” The skeptics themselves have been ejected from, for example, State Climatologist positions and prevented from publishing research in mainstream journals, and they and their views are routinely attacked.
Much complexity and uncertainty surround climate change. The cumulative empirical evidence on proper forecasting procedures suggests that the most appropriate method in this case is naïve extrapolation. In simple terms, this means to forecast no change. Of course there will be change, but with current knowledge there is no more reason to expect warming than to expect cooling.
As we describe in our paper, we have been unable to find any forecast derived from evidence-based (scientific) forecasting methods that supports the contention that the world faces dangerous manmade global warming.
Appeals for urgent curtailment of human activity “just in case” are often couched in ways that imply that industrial societies are inherently sinful, rather than that there might be a problem to be dealt with. Indeed, interpretation of the precautionary principle is subjective and it is arguable that it is being misapplied to the issue of climate change.
Firstly, even if forecasts of increasing temperatures turned out to be accurate, predicted temperatures and other conditions are within the range of variations that have been experienced in the past. There is no evidence that the natural environment “prefers” relatively cool to relatively warm average temperatures. In fact, life in general prefers warmth.
Secondly, curtailing human activity would harm people’s health by making them poorer than they would otherwise have been. This is likely to be the case even if curtailing human activity happened to reduce global average temperatures. When the situation is framed in this way, the precautionary principle dictates that it is policies to curtail economically efficient human activity that should themselves be curtailed.
The outlook for the climate over the 21st Century is highly uncertain. There is a word in the English language to express high uncertainty. That word is “ignorance”. And ignorance is not a basis for responsible government action. We should expect our politicians to have the courage to resist interest groups’ calls for action in the face of ignorance.
The precautionary principle brings to mind the slogan on the Ministry of Truth building in George Orwell’s 1984: “Ignorance is Strength.” Instead of this political principle, we hope that politicians will turn to scientific principles for making public policy.
Complex models of climate at odds with forecasting principles predict temperatures will rocket… or plummet
When the situation is complex and there is uncertainty about causal relationships, forecasting principle 6.6 dictates that forecasters should “Use few variables and simple relationships”. The opposite approach was used in the Intergovernmental Panel of Climate Change models, and there have been calls (1 , 2) for even more money to enable modelers to create models that are even more complex. Patrick Frank, in an article in Skeptic (2008, 14:1) titled “A climate of belief”, showed that a very simple model with CO2 as the only causal variable and using the IPCC assumptions about the direct and indirect effects of changes in atmospheric CO2 concentrations makes predictions of global average temperatures that are closer to the IPCC’s “ensemble average” of complex model forecasts than are those of any of the individual complex models. In other words, putting aside whether the forecasts are accurate or not, there is no need to have complex models in order to make those forecasts.
Frank’s simple model illustrates part of the purpose of principle 6.6; namely to aid understanding and reduce forecasting costs. We aren’t sure what the cost of the complex relative to the simple modeling efforts were but, given the number of people and computer time involved in the complex models, a ratio of 1 million to 1 is a conservative guess. Frank’s simple model is simple enough for anyone to understand. That’s a good thing, because the modeler’s assumption are clear and can be tested and disputed, and the disputation can be understood by others. This makes it easier to reject a false model and thereby to advance scientific understanding. Thus the use of simple models reduces mistakes, another purpose of the principle.
The primary purpose of many of the forecasting principles is naturally enough to improve accuracy; principle 6.6 is no exception. Frank demonstrates that the IPCC grossly under-reports the cumulative uncertainty of the model forecasts. The figure below from Frank’s article shows that, when proper allowance is made for uncertainty about the effects of clouds and greenhouse gases on global average temperatures, the complex IPCC models cannot legitimately tell us better than that the temperature change by the end of the century will be somewhere between +120-degrees-C and -120-degrees-C. It would be foolish indeed to base public policy on forecasts from such models.
Patrick Frank’s article is available from the Skeptic site.
Read this article and more at PublicPolicyForecasting.com.
There are 19 forecasting principles that provide guidance on identifying, collecting, and preparing data to be used for forecasting. These principles include 3.3 Avoid biased data sources, 3.4 Use diverse sources of data, 4.1 Use unbiased and systematic procedures to collect data, 4.2 Ensure that information is reliable and that measurement error is low, 4.3 Ensure that the information is valid, 4.4 Obtain all of the important data, 4.6 Obtain the most recent data, 5.1 Clean the data, and 5.4 Adjust for unsystematic past events. While some of these principles at least may appear to be common sense, they are nevertheless often violated in practice with the consequence that forecasts are poor or even invalid. The Climate Audit site reports the findings of the often painstaking detective work required to determine whether the data used by climate scientists are consistent with these principles.