Temperature drives CO2, NOT the other way round

Written by Bevan Dockery on November 10, 2021. Posted in Current News

Data from across the globe shows that temperature change always precedes CO2 change so it is impossible for the later CO2 change to be the cause of the earlier temperature change.

Weekly Mauna Loa CO2 data shows that the draconic 27.2 day and the 29.5 day synodic periods of the Moon are reflected in the variation in the rate of change of the CO2 concentration. This confirms that the small temperature change that occurs when the Moon passes between the Sun and the Earth thereby reducing the radiation received from the Sun and causing a diminished Earth temperature. CO2 is not causing the Moon to rotate around the Earth!

The major question to be answered is why have so many scientists told lies? I believe, as a result of the PSI articles, that the same forces of evil are at work with the fake pandemic and fake vaccine.

Atmospheric CO2 concentration

Here in Figure 1 is the monthly atmospheric CO₂ concentration measured at the Mauna Loa Observatory, Hawaii, Latitude19.5̊ N, Longitude 155̊ W, elevation 3397m, for the 64 year period from March 1958 to September 2021.

The monthly CO₂ concentration had an average rate of increase over the 64 year period from March 1958 to September 2021 of 1.59 ppm pa. For the 5 year period March 1958 to March 1963 the rate was 0.68 ppm pa and for the 5 year period September 2016 to September 2021 the rate was 2.55 ppm pa, that is, the rate of increase has steadily accelerated over time to be almost four times greater than it was 59 years earlier. The range is from a minimum of 312.44 to a maximum of 418.95 ppm.

The amplitude of the seasonal variation was estimated to range from 5.2 ppm to 8.03 ppm, increasing in amplitude over time, in an irregular fashion. The maxima occurred, on average, in early May, which is the beginning of Summer, and the minima in late September, at the end of Summer. The greatest seasonal variation took place between September 2015 and April 2016.

This means that the CO₂ concentration rose during the cool of Winter and fell during the heat of Summer, which is out of phase with the UN IPCC claim that increased CO₂ concentration causes an increase in temperature. Nor does the UN IPCC hypothesis provide an explanation for the steady increase in the rate of increase of the CO₂ concentration.

Temperature and CO₂ concentration

Here is 514 months of empirical data, showing a distinct lack of a relationship between the Tropics satellite lower troposphere temperature [ Ref.1] and the seasonally adjusted atmospheric CO₂ concentration at the Mauna Loa Observatory.

Figure 2 shows the monthly satellite lower troposphere temperature for the Tropics zone, 20̊ South to 20̊ North, in blue, and the relevant monthly CO₂ concentration in red after removal of the seasonal variation so as to match the residual temperature series. The range for the monthly CO₂ concentration is from 335.78 ppm to 416.42 ppm. The range for the Tropics temperature is from -0.99̊ Celsius to +1.15̊ Celsius with respect to a 30 year average base value. The clear and obvious difference between the two raises the possibility that there may be no common causal factor whereby the CO₂ concentration drives the temperature as claimed by the UN IPCC.

Calculation of the Ordinary Linear Regression between the two time series gave a correlation coefficient of 0.471 from the 514 monthly data pairs. This is a measure of the relationship between the background linear trend of each of the time series as shown by an almost identical correlation of 0.470 between the temperature and the time. The correlation between the CO₂ concentration and the time was 0.995, that is, the seasonal adjusted CO₂ concentration time series was practically a linear trend with respect to time. Any pair of linear trends, no matter what their source, will have a high correlation coefficient of about 1.0 which is necessarily of no causal significance as a background linear trend with respect to time can be calculated for any time series.

Detrending of the pair of time series in order to assign a statistical significance to the correlation coefficient gave a value of  0.042 showing that the above correlation of 0.471 was mainly the result of the positive linear trend for each series. Statistical tests of both time series indicated that neither series was a random Normal statistical distribution. The Spearman Rank test gave a value of 0.045 with a 31 percent probability that the correlation could be zero.

An autocorrelation test of both detrended series confirmed that neither series was a random sequence, that is, each measured value was partly dependent, in time, on the previous value. The Durbin-Watson test of the joint time series gave a result of 0.28 which indicates positive autocorrelation. The autocorrelation was estimated to be 0.86.

This mandated the application of a First Order Autoregressive Model for the analysis of  the combined time series whereby the transformed series gave a correlation coefficient of 0.051 with a 27 percent probability that the correlation coefficient could be zero from the Spearman Rank test. Calculation of the cross correlation between the detrended pair of Tropics zone temperature and seasonally adjusted CO₂ concentration showed that the CO₂ changes lagged the temperature changes by eleven months.

Applying the above procedure using the Tropics Land component of the satellite lower troposphere temperature gave a correlation of 0.57 between the temperature and the seasonal adjusted CO₂ concentration. On detrending, the correlation was 0.049, the Durbin-Watson test was 0.44 and the autocorrelation was estimated to be 0.78.

Applying the First Order Autoregressive Model gave a correlation of 0.04 with a 40 percent probability that the correlation could be zero from the Spearman Rank test. Calculation of the cross correlation between the detrended pair of Tropics Land temperature and seasonally adjusted CO₂ concentration showed that the CO₂ changes lagged the temperature changes by eleven months.

Applying the procedure using the Tropics Ocean component of the satellite lower troposphere temperature gave a correlation of 0.43 between the temperature and the seasonal adjusted CO₂ concentration. On detrending, the correlation was 0.04, the Durbin-Watson test was 0.27 and the autocorrelation was estimated to be 0.87.

Applying the First Order Autoregressive Model gave a correlation of 0.051 with an 22 percent probability that the correlation could be zero from the Spearman Rank test. Calculation of the cross correlation between the detrended pair of Tropics Ocean temperature and seasonally adjusted CO₂ concentration also showed that the temperature changes preceded the CO₂ changes by eleven months.

In summary, the correlation between the satellite lower troposphere temperature and the CO₂ concentration for the Mauna Loa Observatory was of the order of 0.05 with an indeterminate probability as to whether or not the relationship is significant. Cross correlation determined that the changes in CO₂ concentration lagged the temperature change by eleven months so it could not possibly be the cause of the earlier temperature changes.

The result was supported by analysis of data from:

(1) Macquarie Island in the Southern Ocean at Latitude 54.48̊ South, Longitude 158.97̊ East, altitude 12 m,

(2) Mt Waliguan, Tibetan Plateau, China, Lat. 36.28̊ N, Long. 100.9̊ E, altitude 3810 m,

(3) Point Barrow, Alaska,

(4) South Pole Station, Antarctica, and

(5) Cape Grim, Tasmania,

as may be seen on the accompanying pages at www.climateauditor.com .

In every case, as the probabilities of a positive correlation coefficient were not statistically significant, the UN IPCC proposition that increased CO₂ caused increased temperature could not be supported and the conclusion must be that the null hypothesis applies, namely that the correlation coefficients were zero.

The above conclusion is totally at odds with the statements from the United Nations climate body, the Intergovernmental Panel on Climate Change. The Policymakers Summary from Climate Change, The IPCC Scientific Assessment, 1990, being the, then, final Report of Working Group 1 of the IPCC, opened with the statement, page XI:

“EXECUTIVE SUMMARY

We are certain of the following:

• there is a natural greenhouse effect which already keeps the Earth warmer than it would otherwise be
• emissions resulting from human activities are substantially increasing the atmospheric concentrations of the greenhouse gases carbon dioxide, methane, chlorofluorocarbons (CFCs) and nitrous oxide. These increases will enhance the greenhouse effect, resulting on average in an additional warming of the Earth’s surface. The main greenhouse gas, water vapour, will increase in response to global warming and further enhance it.” – end quote.

After decades of research into the relationship between the atmospheric CO₂ concentration and temperature, the latest, Fifth Assessment Report, 2015, of the IPCC, the Synthesis Report, Summary for Policymakers, page 8, made the claim:

“SPM 2.1    Key drivers of future climate

Cumulative emissions of CO₂ largely determine global mean surface warming by the late 21st century and beyond. …….” –  end quote.

Temperature and Rate of Change of CO₂ concentration

Here is 42 years of empirical data clearly showing a positive relationship between the detrended variables, satellite temperature and the rate of change of atmospheric CO₂ concentration at the Mauna Loa Observatory.

Figure 3 shows the monthly satellite lower troposphere temperature for the Tropics zone, in blue, and the annual change in CO₂ concentration in red. The obvious correlation between the two raises the possibility that there may be some common causal factor whereby the temperature drives the rate of change of CO₂ concentration. It is not possible for the rate of change of CO₂ to cause the temperature level as a time rate of change does not define a base.

For example a rate of 2 ppm per annum could be from 0 to 2 ppm in 12 months, 456 to 458 ppm in 12 months or any other pair of numbers that differ by 2.

Note that the satellite temperature data is supplied as a residual after adjustment for the estimated seasonal variation. This makes it directly comparable to the annual rate of change of CO₂ concentration as taking the annual rate eliminates the seasonal variation. The range, after detrending, for the Tropics Zone temperature is from -0.72̊ Celsius to +1.26̊ Celsius with respect to a 30 year average base value and the range for the CO₂ annual increment is -1.57 to 1.90 ppm per annum.

Calculation of the Ordinary Linear Regression between the two time series gave a correlation coefficient of 0.65 from the 508 monthly data pairs. Detrending of the time series in order to determine the statistical significance gave a correlation coefficient of  0.54. However the Durbin-Watson test of the time series gave a value of 0.86 indicating positive autocorrelation which means that Ordinary Linear Regression is inapplicable.

The autocorrelation was estimated to be 0.57. When applied to transform both time series, that is, applying a First Order Autoregressive Model, it resulted in a correlation coefficient of 0.26 with a minuscule probability of the order of 10^-9 that the coefficient could be zero from the Spearman Rank test.

It follows that this synthesis of empirical data conclusively reveals that CO₂ has not caused temperature change over the past 42 years but that the rate of change in CO₂ concentration has been influenced to a statistically significant degree by the temperature level. Note that it is not likely for a rise in CO₂ concentration to cause the temperature to increase and for the temperature level to control the rate of change of CO₂ concentration as this would mean that there was a positive feedback loop causing both CO₂ concentration and temperature to rise continuously and the oceans could have evaporated long ago.

Support for this thesis is seen in a statistical analysis of the annual rate of change of the monthly CO₂ concentration with respect to the 13 month average lower troposphere temperature for Macquarie Island in the Southern Ocean and for Mt Waliguan, Tibetan Plateau, China.

Chronological Sequence

The above conclusions are supported by the sequence of events recorded at Mauna Loa Observatory for the major 1997 -‘98 El Nino event displayed in Figure 4 below.

The graph displays the time relationship between atmospheric CO₂ concentration at the Mauna Loa Observatory, Hawaii, from the Scripps Institution, compared to the satellite lower troposphere Tropics-Land temperature provide by the University of Alabama, Huntsville, for the major 1997-‘98 El Nino event.

The maximum in the annual increment of the temperature, at October 1997, preceded the maximum in the annual increment in the CO₂ concentration, at March 1998, by 5 months revealing that the CO₂ change could not possibly have caused the temperature change. The maximum in the annual increment in the CO₂ concentration occurred as the temperature reached its maximum, confirming the conclusion in the previous section.

Figure 4: CO₂ annual increment relative to temperature average and annual increment.

Cumulative temperature vs. CO2 concentration

If the temperature determines the rate of generation of CO₂, that is, d/dt CO₂ equals a constant multiplied by the temperature level then, mathematically, this implies that the CO₂ concentration at a given time is proportional to the integral of the temperature up to that time relative to a base value at which no CO₂ is generated. This would be the temperature at which there is a balance between the various sources and sinks of CO₂ at the Earth’s surface.

Figure 5 shows the sum with respect to time of the global temperature values relative to a base of -0.99, the minimum value from the global list as a calibrated base is not known, with the range minimum to maximum adjusted to match that of the seasonally adjusted CO₂ range. The resulting near linear trend in the cumulative satellite temperature closely matches that for the seasonally adjusted CO₂ trend as expected under the hypothesis that the temperature drives the rate of generation of CO₂.

Applying the Spearman Rank test, as the distributions are not Normal Distributions, gave a Spearman Rank statistic of 0.999895 with a probability that was too small to be represented by a machine number for the correlation between the seasonally adjusted CO₂ concentration and the cumulative temperature to be zero.

The conclusion that the temperature controls the rate of change of CO₂ concentration explains the well known fact that CO₂ change lags temperature change over a large time range. Ice core data has revealed that the cycle of ice ages and inter-glacial warm periods show CO₂ change lagging temperature change by several centuries to more than a millennium while modern CO₂ and global data shows lags of 9.5 to 10 months for atmospheric temperature and 11 to 12 months for sea surface temperature, Humlum et el., 2013 [Ref.5].

Cross correlation of the CO₂ concentration at Mauna Loa and satellite lower tropospheric Tropics Land and Ocean temperatures showed that CO₂ change lagged the temperature change by 9 or 10 months.  If temperature controls the rate of change of CO₂ concentration, local maxima in the CO₂ rate must correspond to temperature maxima which, mathematically, must occur after the maxima in the rate of change of temperature. Likewise the CO₂ concentration maxima must post-date the maxima in the CO₂ rate and thus post-date the corresponding temperature maxima.

Put simply, CO₂ has not caused global warming.

Conclusion

There is no statistical evidence for the claim by the UN IPCC that a rise in CO₂ concentration causes a rise in the temperature of the lower troposphere but there is highly significant evidence that the temperature determines the rate of change of CO₂ concentration.

Added to that is a secondary conclusion that there is a prominent 42 month cycle for the temperature due to a repeated occurrence of a configuration of the Solar system which is expressed in the Earth’s climate as the El Niño event. It also causes the same cycle in the rate of change of CO₂ concentration.

Furthermore other cycles in the temperature and the CO₂ rate spectra may relate to orbital cycles of the planets indicating that, at least in terms of months and years, the orientation of the planets with respect to the Sun determine changes in the Earth’s temperature which result in coincident changes in the rate of change of CO₂. That is, an important factor in the Earth’s climate change arises from the continually changing position of the Moon and the planets relative to the Earth and the Sun and has nothing whatsoever to do with the concentration of CO₂ in the atmosphere as this is a consequence of the natural climate change.

References:

[1]       The satellite lower troposphere temperature data is freely available from the University of Alabama, Huntsville, on Dr Roy Spencer’s Web site at:

http://www.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt

[2]        The CO2 concentration data for the Mauna Loa Observatory is freely available from the Scripps Institute via the Web page:

https://scrippsco2.ucsd.edu/data/atmospheric_co2/mlo.html

Files: monthly_in_situ_co2_mlo.csv and weekly_in_situ_co2_mlo.csv

[5]        Ole Humlum, Kjell Stordahl, Jan-Erik Solheim, “The phase relation between atmospheric carbon dioxide and global temperature”, Global and Planetary Change 100 (2013) 51-69.

[6]        Identification of the driving forces of climate change using the longest instrumental temperature record.     Geli Wang, Peicai Yang & Xiuji Zhou

Scientific Reports 7, Article number: 46091 (2017), doi:10.1038/srep46091

[7]        T.W. Crowther, et el, “Quatifying global soil carbon losses in response to warming” Nature, Vol. 540, 104-108, 01 December 2016,  Letter

Bold emphasis added

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