There are two articles today at the American Thinker dealing with climate change. The first is by G. K. Mitchell, Jr. entited Global Warming and the Earth's Land Mass. Mitchell brings a very technical approach to debunking the climate alarmism that is blared out of every MSM organ. He starts off by showing the methodology used by the National Oceanographic and Atmospheric Administration (NOAA), and showing that this is fundamentally flawed. Flawed methodology yields flawed results.
Peer-reviewed, published scientific research reports are structured in a specific way for a specific purpose. They usually contain the following sections: Title, Abstract, Introduction, Methods, Results, Conclusions, Discussion, and References. Many will also contain Figures, Tables, Equations, and an Appendix. The purpose of this level of detail is to permit other scientific investigators to replicate the experiment to test the methods and results and verify the conclusions. Although it may seem contradictory, the cornerstone of the scientific method is the ability to falsify, not prove, a hypothesis. If there is no means to disprove a hypothesis, there is no means to verify its validity. As Einstein famously stated, "no amount of experimentation can ever prove me right; a single experiment can prove me wrong."
The principal means to measure the average temperature of the Earth's land mass is administered by the National Oceanic and Atmospheric Administration (NOAA). At present, NOAA employs a system of about 21,000 metropolitan surface area temperature stations (MSATS) worldwide to collect temperature data. The MSATS monitoring stations are located 2 meters above the ground, and volunteers collect the temperature data twice daily in an effort to obtain the maximum and minimum temperature readings for the day. Then the readings are "adjusted" for time-of-day observations, homogeneity, and changes in equipment technology or station location. Finally, the maximum and minimum temperature readings are averaged to obtain the daily, monthly, and yearly averages.
The temperature data are gathered by volunteers, who may visit the MSATS at different times of the day over a period of time. Since the temperature at a given MSATS location may change widely during the day, climate scientists will adjust the readings obtained by the observer by adding or subtracting a value to compensate for the variance from the preferred observation time in what is known as a "time of day" adjustment. In addition, if a maximum or minimum temperature reading at a given MSATS location on a given day varies by a certain amount from the maximum or minimum reading at an adjacent station(s), climate scientists will adjust the particular reading at that station by adding or subtracting a value to compensate for the variance from the adjacent MSATS location in what is known as a "homogeneity" adjustment. Finally, if the sampling equipment at a given MSATS location is changed or if the equipment is relocated, then a climate scientist may adjust the readings obtained by the new equipment or at the new location to account for the differing sampling technology or different environmental conditions at the new location.
So far, so good. But the problem with using volunteers to collect such data is that they are inconsistent. Think about it. Who wants to wake up at 0 dark thirty every day, day in and day out, to go and get the temperature data and report this data to some office in the United States. To take care of this problem, NOAA employs "adjustments" to the data reported by volunteers. What could go wrong? Well, a lot, as the graph embedded in Mitchell's article illustrates.
It should be noted that the sum of the homogeneity and time of day adjustments during the period 1980 to 2010 increased in value in each succeeding decade. These adjustments have contributed to an increase in average MSATS temperature readings of 0.56°C per decade for the period, well in excess of the U.N. IPCC predictions of 0.3°C global warming. In effect, adjustments to temperature readings have artificially "created" global warming.
This looks like a case of confirmation bias, wherein the person looking for a given result finds what he is looking for and in this case "adjusts" the data to fit.
Notwithstanding the fact that the MSATS land temperature data have been corrupted by adjustments, and the Earth has no average temperature to measure or calculate, NOAA reported that the "average" temperature of the Earth's land mass for the period 1880–2020 increased by only 0.14°F/decade (0.08°C/decade). This amounts to an annual increase of 0.014°F or 0.008°C for the period. It should be obvious to even the most uninformed observer that such an increase is within the margin of error over such a long period when temperatures were recorded by thermometers graduated by 1°F increments or more. Contrast that de minimis increase with the decadal adjustments to the MSATS data.
The other article is by Anthony J. DiBlasi entitled Cooling the Heat on Climate. DiBlasi writes:
I learned of these cycles and of the interglacial periods between them when I studied geology at Brooklyn College. I have learned, too, of the fluctuating mini-cycles of earth temperature changes within a major swing. Whether the earth is entering another Ice Age, as1970s doomsayers alarmed the public with, or is still warming from the last global “chill,” must be predicated on reliable weather data assembled from very wide sampling and connected over very long periods of time. The assumption that all the relevant data regarding mini-cycles needed to arrive at a comprehensive and intelligent analysis could even be gathered, let alone assembled, to establish a long-range trend is false to begin with. In common parlance, this is known as guessing.
Back in engineering school, we had a term for such guessing: wild ass guess or WAG. If the WAG involved some degree of engineering intuition, we would call it a scientific wild ass guess, or SWAG. The point is that in engineering, there are unknowns that none the less have to be given a numerical value to proceed with designing a system that the public can trust. These are essentially very conservative SWAGs. Such are the live loads placed on beams to calculate the size of the beam. The dead loads on the other hand can be calculated rather precisely by knowing the weight of each component of the dead load.
That global warming is caused by CO2 is another shot in the dark, since a global so-called “greenhouse effect” attributed to CO2 cannot be finally established, let alone form the basis for attempting to control a gas that is in fact essential to life.
No one can seriously deny that climate changes. It always has. But so-called “climate change denying” is a phony political smear term. Those at the receiving end of this accusation justifiably cry foul against politically branded “climate change” policy that calls for fleecing the public and subjecting millions (billions?) of people to extreme hardship and possible starvation. And for what? A miniscule rise in temperature since the last Ice Age?
To design programs, allocate funds, and recruit labor and resources toward averting a climate-change disaster based on guessing is hugely ridiculous, unless it be to leverage political power through alarmist politics.
Who can seriously deny that climate alarmists have been wrong in their predictions over and over and over again, within a single century? Blame this not on computer modelling per se but on computer modelers who keep forgetting or ignoring the GIGO factor (Garbage In, Garbage Out) in any computer model that uses incomplete or faulty data, which guarantees a flawed output.
Man made climate change simply doesn't exist, and climate alarmism is an attempt to stampede the public into giving up their freedon for some imagined safety. But of course, as DeBlasi notes, the goal of climate alarmism is to redistribute wealth. Only the redistribution is not from the wealthy to thoooose less fortunate, but the other way around. They mean to deceive, and the legal definition of fraud is the intention to deceive.
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