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Posted on: March 21, 2021

What is the IPCC and what does it do? | Environment| All topics from  climate change to conservation | DW | 25.09.2019


EXCERPT: PAGE 1033: Equilibrium Climate Sensitivity

Estimates of the equilibrium climate sensitivity (ECS) based on observed climate change, climate models and feedback analysis, as well as paleoclimate evidence indicate that ECS is

likely in the range 1.5°C to 4.5°C with high confidence,

extremely unlikely less than 1°C (high confidence) and

very unlikely greater than 6°C (medium confidence).


Estimate of the ECS: mean = 3, standard deviation = 0.915. The estimate of ECS=3 is statistically significant at alpha=0.01 if it is an average of more than 8 independent estimates and at alpha=0.05 if it is an average of more than 3 independent estimates. The crucial information about the number of independent estimates used in the computation of the mean and standard deviation is not provided and instead, what we have is a long and useless essay about confidence intervals.

Charney 1979: The estimate of ECS=3 with a 90% confidence interval of 1.5 to 4.5 is of course the Charney 1979 estimate derived from Manabe’s climate model and therefore not observational data.

In a related post we present a large number of empirical observational ECS values published in the climate science literature in the period 1970 to 2018. LINK: These observational values are mostly described as either climate model estimates constrained by observations or observations constrained by climate models. Of about a hundred values reported, only 20% fall into the Charney/IPCC range of {1.5 to 4.5}. It should be mentioned that the Charney estimate is a purely climate model estimate and not constrained by observations. The climate model used by Charney was the Manabe model. The many climate sensitivity estimates published by Manabe himself with co-author Wetherald in the many Manabe-Wetherald papers has consistently been mean=2 and not 3.

If the IPCC does not limit itself to Charney and if they read the extensive literature on empirical and climate model estimates of ECS they would have a more realistic understanding of the ECS issue. What the literature may imply, if fully and objectively studied, is that the estimate of ECS involves large uncertainties that cannot and must not be ignored nor overlooked nor hidden in bureaucratic language of likely and exremely likely values.

COP24: Key outcomes agreed at the UN climate talks in Katowice

EXCERPT: PAGE 1033: Transient Climate Response

The transient climate response (TCR) likely in the range 1°C to 2.5ºC and extremely unlikely greater than 3°C, based on observed climate change and climate models.

TRANSLATION: The IPCC estimate of TCRE is mean=1.75 with a standard deviation of 0.46 such that the estimate of 1.75 is statistically significant at alpha=0.05 if it is the average of more than two independent estimates and at alpha=0.01 if it is the average of more than 4 independent estimates.

Howver the bigger issue in the TCRE is its mathematical weakness described in a number of related posts on this site the primary post being: LINK: . What we find in these related posts is that the TCRE relationship between emissions and temperature is a spurious correlation that has no interretation in the real world.

The only information content of this strong correlation between cumulative values of time series data is that they happen to follow certain sign patterns where annual emissions are always positive and in a time of warming, annual warming rates are mostly positive. The further interpretation of these correlations and regression coefficients in terms of human cause of warming and in terms of carbon budgets is not possible. 

Climate science has fallen afoul of fundamental statistical considerations in the use of the specious TCRE metric not only to validate cause and effect in natural phenomena but also as a policy tool for setting carbon budgets. 

A more fundamental issue with regard to the TCRE is that it is inconsistent with climate science theory that relates warming to emissions. The theory of anthropogenic global warming is a causation sequence from fossil fuel emissions to rising atmospheric CO2 concentration and from there by way of the greenhouse effect of atmospheric CO2 to higher temperatures. There is no role for a TCRE parameter in this theory as highlighted in its mathematical inconsistency in a related post: [LINK] .

The statistical issue with respect to only positive values for emissions is demonstrated in a related post where it is shown that not just emissions but any variable with only positive values works just as well, even UFOs.  [LINK]

Tip of the Week: What's with all the inconsistency? | Change ...

THE MATHEMATICAL INCONSISTENCY argument is simply that the ECS measure of the impact of fossil fuel emissions on warming holds that atmospheric CO2 concentration at any given time is a linear function of cumulative emissions and that surface temperature is a logarithmic function of atmospheric CO2 concentration. These two relationships imply that surface temperature is a logarithmic function of cumulative emissions. The TCR measure of the impact of fossil fuel emissions on warming holds that the amount of warming is a linear function of cumulative emissions. This linearity is mathematically inconsistent with the ECS measure which implies that the amount of warming is proportional to the difference between the logarithms of the cumulative emissions before and after the period of warming under study.

The mathematical inconsistency described above shows that the significant research effort in climate science to resolve the ECS and TCR measures of anthropogenic warming in terms of fossil fuel emissions with Earth System Models {ESM} is not possible because the two methods of computing the impact of emissions on temperature are not mathematically consistent and that makes it impossible for them to describe the same phenomenon in nature.



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  • Irving Prentice: If we want to err on the side of caution and try to reduce manmade CO2 emissions, let’s not “throw the baby out with the bath water”. There may
  • chaamjamal: Thanks. A specific issue in climate science is correlation between time series data where spurious correlations are the creations of shared trends, s
  • Jack Broughton: I remember a paper published in the 1970s by Peter Rowe of UCL in which he showed how even random numbers can be processed to seem to correlate by usi
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