In any real science great care is given to “controlling” for exogenous factors. The whole purpose of the scientific method is to relate the impact of an independent variable upon a dependent variable, removed from any other factors. Y = mX + b + e, is the formula of a linear regression, and e is the error of the model. In order to minimize the “e,” one must control for as many outside factors that may impact the dependent variable as possible. In climate science, efforts to control for exogenous factors is completely absent. In fact, by choosing the highly flawed and “adjusted” ground measurements they are effectively maximizing the impact of exogenous factors on their data set and minimizing the usefullness of their preferred data set to identify and isolate the impact of CO2 on atmospheric temperatures.
Here is the best example I’ve found of the Urban Heat Island Effect:
In climate science, the main model being promoted is Temperature is a function of CO2, or Temp = f (CO2) or ΔT = ΔCO2 + b + e. Given this single variable model, there are obvious exogenous factors that could impact temperature that are unrelated to CO2. They are water vapor, the most potent and abundant greenhouse gas, the sun, the source of almost all incoming energy to the earth, and the Urban Heat Island Effect.
With that understanding, any real scientist would seek to control for water vapor, the Urban Heat Island Effect, and the Sun. Let’s first take a look at water vapor. Water vapor in the lower troposphere is so potent and abundant that it makes CO2 irrelevant. Where water vapor is, heat is, regardless of how much CO2 is present.
To control for water vapor we need to measure the layer of the atmosphere where there is no water vapor, but plenty of CO2. That layer is 4.5 km and higher in the atmosphere. The Mid-Troposphere and Tropopause data sets are what we will be using to control for water vapor. The following charts show the concentration of water vapor and CO2. At the altitude of 4.5 km the temperature reaches 0.00°C, so water vapor is assumed to have precipitated out of the atmosphere.
This graphic demonstrates just how closely related water vapor and temperatures truly are. The charts are nearly identical. Water vapor is represented by the TCWV line.
The introductory image is often published as a measure of Global Temperatures, which it is, but the lower atmosphere is corrupted by the Urban Heat Island Effect, water vapor and variations in the sun and cloud cover. To isolate the impact of CO2 on atmospheric temperatures you have to use the temperature data of the higher layers of the atmosphere.
First, we will look at the Southern Hemisphere. The Southern Hemisphere is mostly water and largely void of the Urban Heat Island Effect, but there is plenty of water vapor and clouds in the lower atmosphere. Even so, the Mid-Troposphere and Tropopause show no material warming. The Mid-Troposphere shows a little more near-term warming, but both layers are within the range of the past 40 years. The spikes seen in the Mid-Troposphere Graph correspond with El Niños, so water vapor does have an impact on this data set. The rapid drop in temperatures post-peak proves the temperature spikes are unrelated to CO2 which remains effectively constant during the time period.
Another way to control for the Urban Heat Island Effect is to simply focus on the upper atmosphere above the oceans. When you do that, you discover no material warming. Certainly nothing like the introductory graphic. The spikes once again correspond to El Niños and are unrelated to CO2.
To control for the Urban Heat Island Effect and water vapor, the poles are the best location, with the South Pole being more effective than the North Pole. The North Pole is more impacted by ocean temperatures. When we look at the upper atmospheric temperatures above the Poles, we find no material warming.
The oceans have an impact on the Poles, so we can further narrow the focus to the extremes of the South Pole, between 20S and 90S. When we do that, we again find no material warming. While the one chart does show a near-term trend, its level was below that of 1980 as recently as 06/2016.
As the above graphics and discussion demonstrate, when care is given to selecting data sets that control for the exogenous factors of water vapor and the Urban Heat Island Effect, the isolated impact of CO2 on the atmosphere is nonexistent. The one factor we didn’t control for was the sun. We do however know that the atmosphere has become more transparent over the past 26 years, so some warming would have been expected. That warming, however, wouldn’t be due to CO2.
Climate alarmists simply choose corrupted data sets to make their alarmist case. That isn’t just bad science, that is deliberate and willful deceit. Not only do they choose the wrong data sets, they “adjust” them to make them fit their desired outcome. No amount of adjusting and cherrypicking data sets will be able to win the scientific debate in the long run. The physics of the CO2 molecule simply doesn’t support the alarmist’s claims, and eventually, reality and the truth will win. The alarmists won’t be able to continually “adjust” their way out of a scientifically indefensible position.
You simply don’t need to “adjust” data like I provided above, or data like this following chart. The data speaks for itself. If you have to “adjust” the data to make your model work, your model is wrong, it is that simple.
Higher up in the atmosphere, it is well documented that an increase in CO2 is associated with greater COOLING. That may sound counter-intuitive until you understand the physics of the atmosphere.
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