Many researchers have theoretically quantified the ‘Direct’ effect on the augmentation of the total Greenhouse effect by increased atmospheric levels (particularly carbon dioxide).
These efforts include, for example Wenyi Zhong and Joanna Haigh’s 2013 paper "The greenhouse effect and carbon dioxide".
Any proper scientific approach (approved by Karl Popper, the 20th century philosopher of science) would be to start out with a null hypothesis.
However, all the studies used to verify the assertion ‘Anthropogenic emissions cause Global Warming’ start out by assuming the assertion is true.
This means they axiomatically include the required outcome in their calculations. In the words of Thomas Sowell 'they are based on a flawed, utopian vision rather than empirical evidence and practical consequences'.
This is an example of circular reasoning and confirmation bias research.
It is deeply unscientific and undermines the Anointed's verifying calculations so as to relegate them to the realms of pseudo-science.
This groupthink approach leads most non-scientists and many Climate Change believers in the scientific community to mistakenly consider the asserted ‘fact’ as being verified by application of the scientific method.
It hasn't.
The detailed 'Direct' effect calculation uses the HITRAN spectral database and is more fully described in 'Natural and Anthropogenic Climate Change - Volume Two'.
Although these calculations are carried out in minute detail by earnest scientists they use a fundamentally unscientific approach.
Nevertheless, they are the starting point for the 'scientific' proof that increased levels of carbon dioxide through a process known as 'Spectral Broadening' cause Global Warming.
The general form derived by these modellers is that the increase in global surface temperature bears a logarithmic relationship to the concentration of carbon dioxide.
This form of relationship was first suggested by Arrhenius about 125 years ago. Although widely used in models it has not been verified experimentally. An attempt by a colleague of Arrhenius, Ångström (the father of spectroscopy) found no measurable increase in Greenhouse effect because it was already saturated.
Curiously, no serious experimental verification appears to have been attempted since then.
However, these 'Direct Greenhouse Effect' calculations do not predict as much Greenhouse effect enhancement as the modellers require to be able to predict ‘Climate Apocalypse’.
Therefore, another mechanism must be invoked if a 'Climate Emergency' is to be declared.
This mechanism is termed ‘sensitivity’ or, sometimes, ‘feedbacks’.
Sensitivity is asserted to work (apparently uniquely) on CO2 ‘Direct’ warming and multiplies the ‘Direct’ effect by a factor of between two and four. It appears not apply to any of the many natural warming factors.
The Climate Change belief mandates all warming (or almost all) as anthropogenically caused.
The mechanism for ‘Sensitivity’ is purported, mainly, to involve water (vapour and clouds) but no satisfactory mechanism can be offered.
This pushes the whole ‘Sensitivity’ concept into the realms of pseudo-science.
The huge quantity of published discourse on the subject such ass the IPCC's massive AR6 report, to me come under the category of "how many angels can dance on the head of a pin".
This is a 17th-century metaphor for trivial, overly academic (theoretical) debate.
It mocks medieval scholasticism but is highly relevant to current Climate Change sccholasticism.
Esentially, the Clmate Change Anointed, having a view that humans must be 'to blame', proceed to use circular logic in a very unscientific manner to prove that 'the science is settled'.
It is not.
No self-respecting scientist, once made aware of what the evidence is and how eco-socialist philosophy has manipulated a coincidence into a full-blown dogma, would willingly agree to it in a secret ballot.
There may be good arguments as to why different scientific ideas may be wrong but hurling 'Denier' accusations is deeply unscientific.
I accept that a fundamental calculation of how elevated greenhouse gas concentrations may, through increasing the total greenhouse effect, affect average global surface temperature is impossible.
The simple 'blanket' explanation of the greenhouse effect hides massive complexity.
I have tried to explain some of the complexities as well as referring to the underlying fundamental knowledge in The Greenhouse Effect.
Giving up all hope of a comprehensive theoretical model, I have looked at what observations can tell us.
I developed two models to link observations to the greenhouse effect (The Cardinal Model) and to surface temperatures (The Emission-Temp Model).
I have used empirical parameter modelling which is a data-driven approach that creates mathematical relationships from observations, rather than theory, using techniques like regression to estimate parameters. It enables prediction by fitting equations (linear, exponential, hyperbolic, polynomial) to experimental data.