Explaining the natural bias in global warming studies

I have been asked why I believe that many global climate change studies are flawed …

(1)     Natural selection – the propensity of researchers to propose research that is likely to attract professional and public interest, funding, media attention and personal awards for outstanding achievements. To this end, it is highly probable that researchers will take the positions of their sponsors and mentors into account, thus slanting research toward popular and fundable directions. That is not to say individual institutions and scientists are corrupt, but that their propensity to attract funding for facilities and personnel may influence their choice of projects. While the private energy companies have a vested interest in global warming research, to refute research findings that may lead to public polices adverse to their self-interests, it should remember that the combined total of funding provided by energy companies is relatively miniscule when compared to the funding of governments and foundations (non-governmental organizations) who have a vested interest in promoting ideologically- driven public policies which favor larger government and the special interests who provide campaign funding and support.

(2)     Redundant work – field work is expensive and time consuming, therefore many scientists chose to analyze the scientific field work of others – aggregating and analyzing studies as if the researchers were doing original science. If that work is biased by natural selection as stated in point (1), one might assume that the redundant work would be similarly biased, thus giving rise to the “consensus” view of the science. Since we know, for a fact, that consensus is not fact and often not even scientifically supportable without disclaimer, consensus is often worthless when the underlying work is less than reliable and independently tested.

(3)     Regional results – scientists, with due diligence, explore a very small portion of our vast planet and derive results which suggests a particular answer to a hypothesis. Unfortunately, these findings may be regional and cannot be mapped onto the universe of a broader planetary finding due to the variability of nature over diverse geographical areas and over large timespans. Results from tree ring analysis in Russia, even considering the reasonable errors of using climate proxy data, cannot be simply mapped to a larger planetary scale.

(4)     Mathematical manipulation of the raw data – unfortunately if one is to calculate averages, trends and means, one must account for missing or erroneous data points and the data collection methodology which may change over time. Because of the statistical manipulation of the raw data over time, many original datasets have been corrupted and only the manipulated data may be available. Thus leading to computational errors of unknown magnitudes.

(5)     Flawed models – at best models are a “best guess” approximation of the rules which appear to govern physical phenomena. Because global climate is a chaotic system whose individual phenomena may never be known in our lifetimes, most models are deeply flawed. In some cases, models consist of little more than calculating an equation to fit past data points and then extending that trend line into the future. In most GCM (Global Circulation Models), the greatest greenhouse gas, water vapor, is never fully considered and thus significant errors may be introduced into an incomplete model.

Bottom line …

Because of the chaotic nature of our global climate, with the significant variables being the solar output, the Earth’s position from the Sun, the rotational dynamics of the Earth, volcanic activity and plate tectonics, the behavior of deep ocean currents, and the greatest greenhouse gas, water vapor, we may never be able to correctly model the global climate with any degree of certainty since we do not understand nature’s inherent variability, the periodicity of the individual cycles, the maxima and minima of the cycles – nor the mean to which they regress. We have approximations but that is not good enough to claim understanding.

Science, in and of itself, is a process of controlled skepticism, where one proposes a hypothesis, conducts experiments or field work, produces a result – which then must be independently confirmed by neutral observers before it can be accepted as being accurate enough to rely on for more practical purposes.

Since public policy is driving the science – in the hopes that “science” will allow politicians to convince populations to surrender more of their assets and accept fewer freedoms, we should be very, very careful about what we call science.

In the case of global science studies, we have seen through the revelations of Climategate, that the corrupt United Nations and a relatively few number of scientists have befouled the peer-review process when it comes to global warming research. Thus, there is a role for skeptics on all levels: amateur through trained scientists. Many of our most important discoveries have been created by credentialed amateurs who were unafraid to question the hypothesis, the data, the methodology and the reported results.

And since we know that most politicians, by definition, are corrupt and self-serving, it is high time to reduce the tolerance limits on our personal bullshit detectors and be willing to call bullshit when supposition like the crap spewed by politicians like Al Gore is presented either as science or fact. In fact, I would like to sit Al Gore down in front of Congress – this time with sworn testimony – and see him discuss global climate change with Christopher Lord Monckton or any one of the so-called skeptics who could demolish his arguments in a matter of minutes – with or without mathematics.

We are entering a time period where politicians openly lie to the American public. It is time we held them and their scientists to account.

-- steve

“Nullius in verba.”-- take nobody's word for it!

“Beware of false knowledge; it is more dangerous than ignorance.”-- George Bernard Shaw

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