NOTE:
One by one the long term temperature data sets have been ‘adjusted’ to better match greenhouse model projections. That includes some of the balloon and one of the satellite data sets (RSS) which had shown a distinct pause approaching 20 years. The recent paper by Christy etal (2018 showed why their analysis (UAH) is most trustworthy and that the changes made to RSS TLT data was based on the inclusion of shown to be dodgy data.
Regarding any particular, relevant temperature data, the magnitude and statistical significance of its Linear Trend’s Slope is irrelevant to the key question - which is ‘did increasing atmospheric CO2 concentration levels have a statistically significant positive impact on this temperature data’? For UAH TLT 6.0 data, this paper provides mathematically rigorous proof that it did not.
Besides the fraud involving official Global Average Surface Temperature data that the authors have previously demonstrated, there are a number of critical mathematical errors to which many well-intentioned climate scientists have continued to seem oblivious. These errors have led many climate scientists to claim that increasing CO2 concentrations have had a statistically significant impact on (properly measured) temperature. If this were truly the case, in the U.S., the Clean Air Act would force at least some level of regulation of CO2 emissions.
Regulations come with a huge penalty to our economy and therefore, it is absolutely critical that climate science deliver an unbiased test of this hypothesis. And, a great deal of work has been published related to this issue. But very little work directly addresses this critical hypothesis test using appropriate mathematical methods - and where all the work can be replicated by other experts in the relevant fields. This paper properly preforms such a hypothesis test.
If EPA elects to grant a Reconsideration of the 2009 Endangerment Finding as as a result of its ANPRM CPP Replacement Comment request, only research meeting these criteria will be viewed as relevant based on EPA’s announced new rules. This paper would pass such new rule tests and provide climate scientists with assistance regarding mathematical and process errors to avoid. As usual, all work was done on a Pro Bono basis.
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Comment on “Examination of space-based bulk atmospheric temperatures used in climate research” by Christy et al (2018)
Research Report
Third Edition, May, 2018
EF DATA Comment on Christy et al Paper Final 042818V4
A just released peer reviewed Climate Science Research Report has once again proven that it is all but certain that EPA’s basic claim that CO2 is a pollutant is totally false. All research was done pro bono.
This research was carried out using as its temperature data the UAH TLT 6.0 atmospheric temperature data. UAH data has been clearly shown to be the very best data available (1) . This research involved the use of mathematical methods of econometrics specifically designed for structural analysis of time series data. These methods have been demonstrated to be highly credible when applied to data such as the UAH temperature data (2) .
The Christy et al (2018) paper discussed in this Research Report does provide lower temperature linear trend positive slope estimates than do many other researchers. However, quite properly, the Christy et al (2018) paper does not claim that this lower linear trend positive slope finding implies anything whatsoever regarding a proof that CO2 has had a statistical significant impact on the Earth’s temperature over the last 50 years or so (1).
This Research Report argues that this statistical significance issue must be addressed using appropriate mathematical methods. Such methods are once again used in this new research and prove that increasing atmospheric CO2 concentrations did not have a statistically significant impact on the UAH TLT 6.0 temperature data set over the period 1979 to 2016.
In fact, this Research Report demonstrates that there was a “Pause” in UAH TLT temperature trend increases over the 1995 to 2016 period. This is a time period over which atmospheric CO2 concentrations increased by over 12.0%.
Furthermore, based on a well-known solar activity forecast (Abdussamatov 2015 (3)) and specific assumptions on the other natural explanatory variables (i.e., volcanic and oceanic/ENSO activity), this new Research Report also provides a long-term forecast that UAH TLT temperatures are very likely to exhibit a declining trend over the period through 2026 at the least.
But, the Research Report points out that, even if temperature data had happened to have had a statistically significant downward sloping trend, it would not have guaranteed that CO2 had not had a statistically significant positive impact on temperature. It simply would have required the use of the proper mathematical tools to obtain the statistical results to have proved it. This is why all of the focus on the magnitude of the slope of linear temperature trends by most climate scientists makes no sense to analysts experienced in econometrics-based structural analysis.
Finally, making another key technical point, the Research Report argues against the use of reanalysis data in structural analysis since its use makes mathematically rigorous hypothesis testing virtually impossible.
The merits of the econometrics-based statistical methodology used in this Research Report and its predecessors versus that used in developing the Climate Models relied upon in EPA’s CO2 Endangerment Finding becomes more obvious every day, the explanation for which has been further discussed in highly relevant Congressional Testimony quoted at length in this Comment.
(4)
1 See: Link
2 See: Link
3 See: Link page S282
4 See: U.S. House Committee on Science, Space & Technology March 29, 2017, Testimony of John R. Christy, pages 10-11, Professor of Atmospheric Science, Alabama State Climatologist University of Alabama in Huntsville