Largely because of Newsweek's cover story today (The Truth About Denial), I feel the need to rant a little. Naturally, living in a liberal area of California and being conservative, I expect some degree of disagreement and even hostility towards me and my beliefs. But quite frankly, I am tired of having high school dropout hippies telling me that I am "uninformed, uneducated, and in denial". For instance, a guy who dropped out of school at the age of 15told me in no uncertain terms that I was "uneducated" simply because I disagreed with him about global warming. Does my background in science and the research I did in college (as well as after college) mean nothing? My research was not in climate changes, but the experience did at least give me some understanding of how to perform experiments and how easily the data can be corrupted. And now we come to this Newsweek article that is nothing more than a conspiracy theory about how everyone who does not buy into the global warming scare is either being bought off or is only listening to false information. Whatever happened to people being allowed to have their own opinions?!? And to think all of this is primarily coming from the liberals who also call me "closed-minded" and "anti-academic" (largely because I am a Christian, but also because of my political and environmental stance). So why is it no longer permissible for someone to genuinely have a differing opinion?
So why doI disagree with the whole global warming bit? Because the science is not at all conclusive (note: some of the following was taken from my previous forum posts).
To start with, the computer models of climate change were created with no initial relations between climate and input variable (i.e. how the climate state changes the input variables and how those variables affect the climate). The models are based entirely off data collected. This data is primarily in the form of temperature (found from deuterium to hydrogen ratios which have now been found to be affected my more than temperature change) and atmospheric composition. So we must first look at the data collection to see if the foundation of the models is reliable. The data is collected in two ways: ice core examination and direct measurement. The ice cores are the only way we have of looking much more than a century into the past, and the direct measurement is the most reliable and readily availablemethod for current measurement. The ice cores, though, only measure the atmospheric composition at the surface when the ice was initially frozen. Observations have shown that atmospheric composition varies with altitude, and the effect of greenhouse gases increases with altitude, so we are limited in the accuracy of such measurements. It can also be noted that many people conveniently overlook Dansgaard-Oeschger events which were discovered by studying the Greenland ice cores (these events mark periods of rapid climate change; the most recent was 8 degrees Celsius over a 40 year period, and fossil records from the Sahara also suggest that rapid climate changes can occur naturally). Then it falls upon our direct measurement methods to give us data from the last century, but there is virtually no regulation or proper documentation of how such measurements were taken. The data collection points have changed over the years by adding more points (naturally, a good thing, but left unmentioned in the analysis), moving points without documenting the move, placing the equipment in bad locations (some are located at airports where heat radiates off the tarmac and the passing of planes and jets continually alters the measurements), leaving the equipment in locations as cities develop around them, etc. Furthermore, there is no standard for the measuring devices. There is no documentation to track how the temperature was measured at a location or when a thermometer was changed. There is no calibration for the thermometers, and yet, they are being used to detect changes of less than one tenth of one degree when some are designed, for cost, to have an error of up to 2 degrees. And this is what the entire climate models are based on.
So if we overlook the lack of reliable data, how good are the models? Is there any way of knowing when they are reliable? We have been told that there is such great correlation between the models and the collected data that the models have a ninety some percent accuracy. However, there is still much that goes largely unnoticed. First is the large amount of error present in the models when compared to the data used to create these models. While the IPCC reported accurately predicting the temperature change from 1990 to 2000 while refining their models through that period, the accuracy completely lacks precision. Even in the 4th assessment report, looking back over the last century, the period where we get the most accurate and precise data for creating the models, the models have a range of possible outcomes that is sometimes greater than one degree Celsius when they are predicting a 1 degree Celsius change. That means their compilations of 14 models have over 50% error... which brings up yet another point. If they actually knew what caused the climate to change and the relations between warming/cooling factors and the climate, why would they need 14 models instead of one? But I digress... with over 50% error when predicting the very data points used to create the models, can we actually consider predictions of future conditions to be accurate? NO! However, I do not want to leave this as purely statistical, so let us look at actual problems with the models.
First, it must be noted that the Dansgaard-Oeschger events can not be predicted by the models, partly because they lack precision, but largely because we still do not know what causes such events. So, if rapid global warming occurred in the past, and we do not know what caused it, what makes us think that what we are seeing now is completely unrelated and unnatural? Second, the ice core records show that temperatures increased 800 years before carbon dioxide levels increased, and that 800 years represents the first 1/6 of the warming cycles (looking at recurring 5000 year warming cycles according to Geoscience Professor Jeff Severinghaus). That is a significant contribution to the overall warming cycle, and we don't know the cause. It is also very likely that this cause does not merely disappear after the first 800 years (however, since the source is unknown, it theoretically could disappear). Unfortunately, we still do not know what causes the temperatureto rise so much before the carbon dioxide levels rise. This creates two possibilities for the models:
1. If the models accurately and precisely recreate the collected data from the past with the exception of the 800 year period beginning each warming cycle, then we might have a fairly accurate portrayal of future conditions. However, with a major factor missing, the impact of the other factors will be overestimated. Just for an example, if this unknown factor contributed to 50% of the warming effect in the climate, the other factors would be modeled with twice their actual impact to compensate for the unknown factor being absent from the model.
2. If the models accurately and precisely recreate the collected data from the past including the 800 year period beginning each warming cycle, then we might have a fairly accurate portrayal of future conditions. However, the impact of the factors included in the model would not only be overestimated, but would also be estimated in the wrong proportions to compensate for the unknown factor being absent from the model. Thus, the models might show that factor A has the greatest impact on climate change when in actuality, factor D has the greatest impact.
Unfortunately, these are the best case scenarios until we understand what causes a warming cycle to begin and are able to properly model it. Third, even the IPCC distinguishes water vapor as the primary greenhouse gas in our atmosphere, butwe still do not know how water vapor levels and cloud cover vary over time. Such data can not be obtained from ice bubbles, and even now we have very limited means of obtaining that data. We do know that as temperatures rise, water evaporates more readily, and so water vapor will be a major feedback to climate warming. Since we do not have reliable data on water vapor levels before around 1980, there is virtually no way that water vapor could be accurately depicted in the models. Once again, this adds to the level of uncertainty in analyzing the impact of each contributing factor.
Then we come to the sensitivity of our climate. This simply refers to how quickly and how much the climate will change due to a certain change in the input. Since there is very little known about feedback systems in our climate (how much water evaporates as an effect of temperature increase due to water vapor increase, for example), we can not know the sensitivity of our climate. Without this sensitivity, the climate models can have any range of possible outcomes. These range from massive global warming regardless of what measures we take for high sensitivity to no significant climate change regardless of what measures we take for low sensitivity. So until we understand these feedback systems, all predictions of what effect certain actions will have is purely speculation.
So when I can easily find such obvious errors in the way the data has been collected and the models created, why would I still believe these "scientific" findings? Would it not be completely illogical for me to believe this? Is questioning global warming in this manner what it means to be "uninformed, uneducated, and in denial" or even "closed-minded"? Now this does not mean that I support doing nothing or that I see no problem with pollution. However, in the light of this lack of actual information, I see no reason for government intervention into this matter. The proper action should be for consumers to place pressure on businesses to become more environmentally friendly (while doing so themselves). I am a huge supporter of companies like Mitsubishi Heavy Industries who impose upon themselves stricter regulations than a government would do (the facility that I visited in Japan manufactured very large turbine engines and had zero waste). But we must realize that not every business is in a position to reduce waste and pollution immediately. Government restrictions are likely to force many small businesses out of business simply because they can not afford to change as rapidly as others. We should also be aware of developing countries who need the cheaper, less environmentally-friendly forms of energy in order to develop. We can not rightfully ask them not to develop, so the only alternative to them using cheap energy like coal is for developed countriesto fund the facilities for them to have cleaner forms of energy. I also want to acknowledge that despite all the problems with our current models, they are our best form of prediction at the moment. I do not think they are currently capable of predicting climate changes, but I support continued development of these models so that we may have such predictions in the future.
For further information, I typically enjoy reading Richard S. Lindzen [1][2].
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