Statistical Analysis reveals that natural factors are not responsible for climate changes.

By Zack bu

A new study based on empirical evidences just confirmed that it is extremely unlikely that the current global warming phenomenon is caused by natural factors, the study concluded the result with more than 99% certainty.

The study by Physics Professor Shaun Lovejoy at the McGill University is the first study to have employed empirical data to refute the hypothesis that global warming is merely a point of fluctuation in the larger scale climate variations. Using climate data from institutions such as NOAA (National Oceanic and Atmospheric Administration) and NASA (National Aeronautics and Space Administration) that goes back 1500 years, Lovejoy performed statistical analysis that ruled out the natural factors, such as volcanic and solar influences, as the causes of current global climate landscape. This lends more credibility to the belief that human activity-related factors such as greenhouse emissions are culpable for global warming.

According to Lovejoy, comparing observed warming during industrial epoch against natural variability is the most convincing demonstration of human activity generated warming. Traditionally, climate change predications and calculations are largely based on General Circulation Models; a computerized climate model simulating the factors driving the climate changes. But such comparisons exceed GCM’s current capacity; hence empirical statistical analysis is the only one to examine such comparisons.

“Multi-proxy climate reconstructions” was used to in order to account for natural variability before much human interference. The method is a common practice in climate change researches where scientists use paleontological data such as organisms ice cores, tree rings, and sediment cores to infer past climates. At the same time, the study incorporated fluctuation analysis that compares the amplitude s of natural effects at different time periods. The analysis finds no significant changes between the pre-industrial era and the industrial era that can’t be explained by the randomness of natural climate changes.

The study used CO2 level as the sole variable estimating the magnitude of human influences in global warming. According to Lovejoy, though there are other factors such as long-lived greenhouse gases as well as effects of aerosols, they are all along with CO2 level resulted from economic activities. Thus using CO2 level as the “surrogate” variable is justified since it captures the effects of other factors.

The study also examined climate sensitivity, which is the response of the global climate system to a given influence. The concluding that a doubling of carbon-dioxide levels in the atmosphere would cause the climate to warm by between 2.5 and 4.2 degrees Celsius. The result coincides with the results of International Panel on Climate Change (IPCC)’s calculations. According to Lovejoy, climate sensitivity is also an aspect on which GCM is profusely used and that such reliance has allowed GCM skeptics to bring into question whether if human activaties have at all contributed to global warming.

The result of lovejoy’s statistical analysis is that the hypothesis that natural factors are responsible for global warming can be rejected at more than 99% confidence interval, which means that it is practically impossible. Lovejoy said that he used two nonclasscial statistic features, which would take extreme cases into account and the result still stands at 99%, which strengthened the robustness of his analysis.

There are of course caveats when we are talking about climate changes; Lovejoy himself acknowledges the fact that although his analysis has basically ruled out the natural factors, climate changes cannot be hence simply contributed to human activities because of the complexity of global warming phenomenon. However, lovejoy did claim that the study provides a firmer ground for the argument since natural variation is essentially eliminated as possible explanation according to his study.


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