[LIST OF POSTS ON THIS SITE]

 

THE MOLECULAR WEIGHT AND MASS OF CO2 IS TOO HIGH FOR IT TO STAY IN THE ATMOSPHERE AND TRAP HEAT WITH THE GREENHOUSE EFFECT. 

THE HIGHER MOLECULAR WEIGHT AND MASS OF CARBON DIOXIDE IMPLIES ONLY A VERTICAL PATTERN IN ITS CONCENTRATION FROM THE SURFACE TO 3,000 METERS ABOVE GIVE OR TAKE WITH THE TREND HIGHER IN THE ATMOSPHERE AT UNDETECTABLE LEVELS. IT IS TRUE THAT THE MOLECULAR WEIGHT ISSUE HAS AN EFFECT ON CO2 DISTRIBUTION IN THE ATMOSPHERE BUT NO EVIDENCE IS FOUND THAT THIS EFFECT MAKES THE HEAT TRAPPING EFFECT OF CARBON DIOXIDE IRRELEVANT IN THE CLIMATE CHANGE CONTEXT

 

SEPTEMBER MINIMUM ARCTIC SEA ICE EXTENT

Sea ice in on the Arctic Ocean goes through a steep seasonal cycle with large and dense sea ice extent in winter and spring months but with a steep decline to a dramatical seasonal low in September. The data show that September minimum sea ice extent is declining year to year both in extent and in volume and climate science has raised an alarm with respect to the decline in September minimum sea ice extent in terms of the dangers of lost ice feedback and what kind of warming trend that could generate, but more importantly in terms of lower and lower September minimum sea ice extent that could make it difficult for polar bears to hunt for seals. In this context we we often find comments critical of climate science with data for a relatively high level of winter or spring sea ice, perhaps even higher than at some historical reference year, as evidence against the climate science alarm about decline in sea ice and the fate of the polar bear. These data are not relevant to the climate science position which refers only to September minimum sea ice extent.

 

ATMOSPHERIC CO2 CONCENTRATION TOO SMALL TO CAUSE WARMING

(1) 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.

(2) 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.

(3) 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.

 

DIURNAL AND SEASONAL CYCLES IN TEMPERATURE MEASUREMENTS

(4) 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.

(5) 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.

(6) 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.

(7) 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] .

 

(8) A similar argument often seen in climate blogs is that a temperature anomaly plot against time that appears to show warming on the chart at a certain temperature axis resolution can be shown to be illusory because that warming is not visible to the naked eye at a coarser temperature axis resolution. For example, the CRU chart below makes a warming of 0.5C from 1850 to 2010 visible to the naked eye and it is argued that the apparent warming visible to the naked eye disappears if the resolution of the vertical axis is changed from 0.1C to 1C and that therefore the warming shown and claimed by the CRU is illusory and non-existent. However, the real test of the trend lies not in visual impressions but on the statistical significance of the OLS trend line. In those terms, the relevant variable is the uncertainty in the temperature estimations found in the excellent work of Colin Morice of CRU  (Morice, Colin P., et al. “Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set.” Journal of Geophysical Research: Atmospheres 117.D8 (2012). As shown in a related post [LINK] , these uncertainties are rather large in the early part of the CRU reconstruction 1850-2010 and that is part of the issue in the confusion in climate science about the mystery of the so called ETCW or early twentieth century warming [LINK] . Whether a trend is visible to the naked eye is not an issue in the statistics of OLS linear regression procedures used in trend analysis. 

(9) 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

 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.

 

 

FAILURE TO SEPARATE EXTERNAL CARBON FROM CARBON CYCLE CARBON

(11) 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 with “external carbon” that was removed from the atmosphere millions of years ago, can only be assessed in terms of carbon that can be described in these terms.

(12) 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.

 

ICE CORE DATA SHOW CO2 LAGS WARMING AND THEREFORE IT IS NOT POSSIBLE FOR CO2 TO CAUSE WARMING  

(14) 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.

(15) 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.

(16) 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.

 

A novel argument against global warming is that there is no such thing as a global mean temperature [LINK] .

The argument goes that the surface of the earth covers more than 500 million square km and on this vast surface we find local temperatures that vary over a wide range. So therefore the temperature of any point location on this surface has an interpretation because it can be measured and tracked and these temperatures contain a large variance across time and space. Therefore the concept of a single temperature to represent the whole of this surface is not possible. Though made in a convincing way and with very powerful language, the argument has a fatal weakness in terms of paleo temperature data across the globe that shows that our climate goes through a glaciation cycle. If the earth has no temperature then what is a glaciation cycle? And what are interglacials? And in our own little interglacial what was the Younger Dryas cold event and what was the Holocene Optimum warm event that gave us the Neolithic Revolution and human civilization? The violent millennial time scale warming and cooling cycles of the Holocene is described more fully in a related post [LINK].

 

 

Is It Global Warming or Climate Change? 

It is often claimed by skeptics that the term for the post LIA warming used to be Global Warming and then they couldn’t prove the warming (or for various other reasons cited) so they changed it to Climate Change. This is not true. Both terms have been used interchangeably for more than a hundred years. See for example, the peer  review comments for the world’s first paper on AGW climate change – Callendar 1938 [LINK] . (Brooks, Paragraph#15).

 

 

Temperature Change Unrelated to CO2 Change 

In this challenge to AGW, the skeptic presents a number of surface temperature and atmospheric CO2 changes over a decadal or multi-decadal time scale where no correlation is evident between the two time series. The case against AGW made by Howard Brady in the article “Are We Really in a New Climate Era” serves as an example. Bradypdf . Here the author argues as follows:  “The warming rate was 0.163ºC per decade in the 1860-80 period (CO2 levels rising 2.2 parts per million per decade), then 0.15ºC per decade in the period 1910-1940 (CO2 levels rising around 5 parts per million per decade) and then 0.161ºC per decade in the 1975-2009 period (CO2 levels rising around 15 parts per million per decade). That is, at a time scale of 20 to 30 years, observed decadal warming rates are: 0.163, 0.15, and 0.161 and the corresponding decadal atmospheric CO2 concentration changes in ppm are 2.2, 5.0, 15.0. The two time series are not correlated and therefore there can be no role for changes in atmospheric CO2 concentration in the determination of the rate of surface warming. There are two issues that nullify this argument. First, the change in CO2 forcing should be computed as the difference between the natural logarithms of the two atmospheric concentrations and not between the concentrations themselves; and Second, the 20 to 30-year time scale  is too short to test the claimed CO2 effect. The theory says it takes much longer to detect net of natural forcings. Also, other than the Lacis (2010) paper and various anomalous pronouncements by James Hansen [LINK] , climate science in general relies on a forcing portfolio such as CMIP5 that includes other factors in addition to CO2 forcing and these forcings portfolios work better at shorter time scales than CO2 forcing alone [LINK] .

 

 

Trends in Tropical Cyclones 

It is shown that no rising trend is found in the number of tropical cyclones in a selected cyclone basin. The absence of the trend is then claimed as evidence that the claim by climate science on the impact of AGW on tropical cyclones is false. As an example, in the Brady pdf document cited above, Bradypdf , it is reported that no trend is found in the number of tropical cyclones that formed in the South Pacific Cyclone Basin in the period 1970-2012 and that therefore the climate science claim about the effect of AGW climate change on tropical cyclones is proven false. This empirical test is flawed because climate science makes testable AGW impact claims only about the average of all six tropical cyclone basins and not about individual cyclone basins. Please see item 6 below. Skeptical arguments against climate science claims of the impact of AGW on tropical cyclones should be responsive to Knutson and not to arbitrary impacts that they made up. Specifically, in terms of the Brady paper, climate science does not claim that there will be trends in individual basins and it does not claim an increase in the frequency of tropical cyclones.

DETAILS OF THE KNUTSON PAPER:

(21): Knutson (2010). CITATION: Knutson, Thomas R., et al. “Tropical cyclones and climate change.” Nature geoscience 3.3 (2010): 157-163.  In the paper, Tom Knutson spells out exactly what climate science claims in terms of the impact of AGW climate change on tropical cyclones with climate model predictions of the effect of rising SST on tropical cyclones. His main points are as follows: (1) Globally averaged intensity of tropical cyclones will rise as AGW increases SST.  Models predict globally averaged intensity increase of 2% to 11% by 2100. (2). Models predict falling globally averaged frequency of tropical cyclones with frequency decreasing 6%-34% by 2100. (3). The globally averaged frequency of “most intense tropical cyclones” should increase as a result of AGW. The intensity of tropical cyclones is measured as the ACE (Accumulated Cyclone Energy). (4). Models predict increase in precipitation within a 100 km radius of the storm center. A precipitation rise of 20% is projected for the year 2100. (5) Extremely high variance in tropical cyclone data at an annual time scale suggests longer, perhaps a decadal time scale which in turn greatly reduces statistical power. (6) Model projections for individual cyclone basins show large differences and conflicting results. Thus, no testable implication can be derived for studies of individual basins.

 

 

CORRELATION ANALYSIS AT 50-100 MILLION YEAR TIME SCALE ACROSS GLACIATION AND DEGLACIATION CYCLES AND MULTIPLE ICE AGES

1. The chart above plots a CO2 concentration time series (in blue) overlaid with a temperature time series (in green) over a time span of 600 million years and a time span of approx 50 million years. It is claimed that this chart demonstrates that atmospheric CO2 concentration and surface temperature are not correlated. It is further claimed that the visual absence of correlation in this chart proves that the theory of anthropogenic global warming of about 1C over a period of 100 years by way of rising atmospheric CO2 is not possible. This argument is flawed.
2. First, the correlation needed is not between CO2 concentration and temperature but that between the logarithm of CO2 concentration and temperature preferably with the other forcings normally used by climate science also included.
3. Second, the anthropogenic global warming being tested is begins and ends in an interglacial of the Quaternary Ice Age over a centennial time span and a decadal or perhaps multi-decadal time scale. The 600 million year chart shown above is not wholly inside an interglacial. It spans not only glaciation and interglacial cycles within the Quaternary ice age but in fact spans multiple ice ages going beyond the Quaternary to the Karoo and the Andean.
4. evidence against anthropogenic global warming in the Holocene since the Little Ice Age because no correlation between CO2 concentration and temperature is evident in the chart.
5. In the chart below we see that the time span of the correlation chart above spans three different ice ages – the Quarternary (where we are now) and the Karoo and Andean ice ages that came before it  {See Chart Below}.  Ice ages are periods of millions of years and often hundreds of millions of years during which the earth goes through cycles of glaciation and deglaciation. These cycles vary greatly from one ice age to the next in terms of the periodic and temperature characteristics.
6. A chart of paleo data on temperature and atmospheric CO2 that spans glaciation cycles across multiple ice ages over a period of hundreds of millions of years does not contain useful information for the behavior of temperature in a specific interglacial of the Quaternary Ice Age over a centennial time span.

THE ETCW ISSUE: EARLY TWENTIETH CENTURY WARMING

The World’s first anthropogenic global warming paper was Callendar 1938 in which Guy Callendar reported to the Royal Society that during a time of coal burning and fossil fuel emissions in the period 1900 to 1938, atmospheric CO2, and surface temperature went up. He concluded from this finding without evidence that the these events were causally related – specifically that CO2 emissions from coal burning caused atmospheric CO2 to go up. Citing Tyndall and using a climate sensitivity of ECS=2 with atmospheric CO2 data from Eurpoean measurement records, he concluded that the warming in the mean of European temperaure readings 1900-1938 was thus explained by the fossil fuel emissions of the industrial economy and therefore human caused. However, in the modern version of AGW theory with ECS={1.5 to 3.5} and with Mauna Loa CO2 data does not accommodate the Callendar theory. The 1930s warming and the cooling that began in the 1940s are unresolved anomalies in climat science as described in the ETCW issue described by climate science. The frequently cited 1930s warming and 1940s cooling by skeptics as evidence against the theory of AGW overlooks these details in AGW theory.

Details in a related post on the ETCW: LINK: https://tambonthongchai.com/2020/10/09/the-etcw-issue-in-climate-science/

No warming found at decadal time scales:

In a related post we show that steady and statistically signigficant long term warming trends at time scales longer than 30 years consist of a wide variety of decadal trends that include warming, cooling, and no trend. LINK: https://tambonthongchai.com/2021/01/11/global-warming-dec2020/ . These data imply that a decade has been found that had no warming or that showed cooling does not in itself provide evidence against global warming. In addition, the use of the decadal time scale violates the internal climate variability principle in climate science explained in another related post: LINK: https://tambonthongchai.com/2020/07/16/the-internal-variability-issue/