Thongchai Thailand

Weak Arguments Against AGW

Posted on: April 17, 2019






The argument is often seen in online discussions and social media that the claimed GHG effect of CO2 as a cause of global warming is not possible because CO2 is a “trace gas” with an extremely low concentration of around 400 parts per million equivalent to 0.04% such that only one out of 2,500 molecules is a carbon dioxide molecule. It should therefore be obvious that there can be no measurable impact of a substance at such a low concentration.

Yet there are many examples in nature that very small concentrations of substances can have a measurable impact. In the area of toxicity for example, many snake venoms are  neurotoxins that can kill at a concentration of 1 ppm. Other strong toxins include Arsenic that can kill at 13 ppm and botulinum toxins that kill at a fraction of a part per billion. In terms of atmospheric composition, stratospheric ozone protects life on the surface of the earth from harmful high energy band ultraviolet radiation at less than 10 ppm.

Although there are valid arguments against the causation sequence proposed by climate science that CO2 in fossil fuel emissions accumulate in the atmosphere and cause warming,  (related post  [LINK] ) the low concentration argument in and of itself is not sufficient even though 400 ppm may seem like a small concentration.




In the climate change debate, critics of AGW often present a chart of absolute temperature measurements that appear to contain no visible evidence of a long term trend as shown in the chart below. The chart is used to imply that the warming trend claimed by AGW theorists is fake and misleading because it is not seen in the data.



This line of reasoning as a challenge to AGW theory contains a fatal statistical flaw.

Temperature data taken at weather stations contain a diurnal cycle, a seasonal cycle, and random natural variations. Along with these they may also contain a long term trend over a period of many years. Typically, the diurnal and seasonal cycles represent more than 80-90% of the total variance in the actual temperature measurements. The remaining 10-20% or so consists mostly of unexplained random variations.

In cases where a statistically significant trend is found with OLS linear regression, no more than a small portion of the variance, around 3%-5% or so, can be ascribed to a long term warming or cooling trend. It is for these reasons that in the study of long term temperature trends over many decades, regression coefficients for long term trends are relatively a very weak feature of the time series that must be teased out of the data net of the greater diurnal, seasonal, and random variations.

The study of long term temperature trends must therefore be carried out after the diurnal cycle and the seasonal cycle are removed from the data. The diurnal cycle may be removed by taking daily means or by studying either the daily maximum or daily minimum temperatures as shown in a related post [LINK] . The seasonal cycle can be removed by studying one calendar month at a time [LINK] or by computing a de-seasonalized annual mean either with dummy variables to represent calendar months; or by subtracting temperatures in a reference period to compute what is referred to as “temperature anomalies”. A related post presents a critical evaluation of the temperature anomaly procedure [LINK] .


It is only in the absence of the much larger diurnal and seasonal cycles that a trend, if any, can become visible to the naked eye as shown in the chart below. Although the trend represents a small portion of the total variance, its persistence over a long period of many years can have significant effects as seen in the Little Ice Age (LIA) described in a related post [LINK] . The LIA was a period of great hardship for Europeans. Canals and rivers were frozen, growth of sea ice around Iceland closed down harbors and shipping, hailstorms and snowstorms were heavy and frequent, and road and water transport was made difficult or impossible. Agricultural failure and consequent starvation and death devastated Europe. The Scandinavian colonies in Greenland starved to death and disappeared. And yet it was the creation of a long term cooling trend that explained about 3% of the total variance and that could not have been visible to the naked eye in a plot of temperature measurements that contained the diurnal and seasonal cycles.


AN ALTERNATE FORM OF THIS ARGUMENT is that the possible effects of projected global warming is unrealistic because the amount of warming is insignificant. As an example, a projected warming of 1C is described as waking up the next morning when it is 1C warmer or driving south until you find a place that is 1C warmer. And yet the very different condition of the world between the MWP and the LIA are the result of a global mean temperature difference of less than 1C. It should also be noted that the difference in global mean temperature between glaciation and interglacials is about 10C or less and yet seasonal differences of 40C are common; and many Asian and African migrants who move to northern or southern latitudes adapt to temperature differences of greater than 10C. Therefore the magnitude of temperature changes in sustained long term trends in mean global temperature cannot be compared with seasonal or geographical changes in terms of impact.







In theory, the concern in “human cause” of global warming (Anthropogenic Global Warming or AGW) is that in the industrial economy, considered to have started in the late nineteenth century, humans were bringing up fossil fuels from under the ground, where they had been sequestered from the carbon cycle for millions of years, and injecting that carbon into the current account of the carbon cycle. It is proposed that this injection of external carbon into nature’s carbon cycle is an artificial and unnatural perturbation of the carbon cycle and therefore of the climate system. However, this narrow definition often becomes corrupted with consideration for carbon emissions that are not the creation of the industrial economy. In these discussions, the perturbation of the current account of the carbon cycle with external carbon no longer applied so that any carbon emission that can be ascribed to humans are counted as AGW perturbation of the carbon cycle. Here we argue that this extension of AGW theory about the impact of the “industrial economy” on climate to human activities that are natural and that predate the Industrial Revolution is arbitrary and capricious and that the perturbation of the current account of the carbon cycle by “external carbon” can only be assessed in terms of non-surface phenomena that are peculiar to the industrial economy.

BRIEFLY: The case against fossil fuels in AGW theory is that fossil fuel reservoirs deep under the ground contain a large inventory of carbon that has been sequestered for millions of years from the delicately balanced surface-atmosphere carbon cycle that sustains a stable climate system and life on earth as we know it. The theory of anthropogenic global warming and climate change addresses this issue in terms of the response of the surface-atmosphere system to a perturbation caused by fossil fuel emissions that inject extraneous carbon into it. Natural carbon cycle flows are not a relevant consideration in that context.






The charts above show that in the ice core record going back to 400,000 years we find that CO2 lags temperature. That is, a rise in temperature precedes a rise in CO2 and conversely, a fall in temperature precedes a fall in CO2. If this relationship could be shown to be causal, it would be consistent with Henry’s Law that relates to the solubility of CO2 in the ocean.

These data are presented by AGW skeptics as evidence that the CO2 to warming causation proposed in AGW is backwards and therefore not possible because the data show that warming causes rising CO2 and not that rising CO2 causes warming.  It is thus claimed that this discrepancy between ice core data and AGW theory serves as proof that the CO2 warming mechanism in AGW is not possible.

This argument is flawed in at least two ways. First, the observed lagged correlation with temperature leading CO2 does not prove causation. For that, one must propose the mechanism for temperature to change atmospheric CO2 at an 800-year time scale. No such mechanism has been proposed and none exists. Recently, a paper was published describing that causation of CO2 by temperature at an annual time scale. The authors then presented correlation analysis showing a statistically significant relationship to support the causation theory that temperature causes CO2 and not the other way around. This finding is generally taken as empirical evidence against AGW theory. However the study contains a statistical flaw described in a related post [LINK] . The critical evaluation of the study shows that the correlations used to support causation are spurious.






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