Self-criticism of the « no evidence » finding

In my yesterday’s article about the lack of evidence tying observed global mean temperature anomalies with atmospheric CO2 concentration, I could have taken a different approach and discussed other relevant aspects.

I didn’t show a straight Ta=f([CO2]) diagram, but took the rate of warming  (dTa/dt) for the y-axis, which had a very poor correlation coefficient (Pearson R2=0.1622). I was just making a point, not looking for alternate explanation, but just for confirmation, or not, of a plausible correlation.

The straight diagram, also eliminating the 7-year filter, looks like this:

Thus, it wakes the attention that a not so good but plausible correlation would tie temperature to [CO2].

As we all know that correlation is no causation, to conclude to an evidence would be wrong. By itself in this diagram, the chosen independent variable excludes all other possible causes for temperature change; thus, all changes would be attributed to the arbitrarily selected [CO2]. It suffices to choose another independent variable, for example the magnetic field declination angle of the Earth, to obtain a very similar correlation, as on the next diagram:

The same can be made with sea level changes (R2=0.7363), although that may not be an independent variable.

Confused? I hope so!

The only point to take here is that single-minded views, also known as biased approaches, lead to simplistic and wrong conclusions.

To distinguish the specific weight of each independent parameter, multi-variable regression analysis should be performed. To obtain any useful result would then require that all these independent variables are known, and, of course, that observational data is available. However, such useful data is not available from the experiment Earth running once only in the historic Solar system laboratory.

Other critique: A temperature vs [CO2] diagram is a static representation, while the climate system has a dynamic response to the anthropogenic CO2 input. The time factor is missing.
That’s right! So, what?
Being fed up by time series that explain nothing, I was seeking other ways of skinning that cat. As IPCC experts didn’t approach it like this, it must have some validity.

A “no evidence” claim cannot pretend to offer an alternative explanation of the system under review. It only falsifies the alleged cause-effect relationship; it tells that the ideal culprit might be totally innocent or only a partial contributor to the observed facts. It tells also that anyone incriminating this alleged culprit for almost all climate ills is bypassing all prudence that a fair evaluation would require.

Warming was observed, and greenhouse gases are claimed to be the overwhelming cause. If this anthropogenic global warming (AGW) hypothesis cannot be sustained with any element of factual proof, then we must believe in another transcendental knowledge, in this case model extrapolations. And please take it literally: the word belief is of the essence.

A climate system’s response to radiative forcing (greenhouse effect) must exist, because the physical phenomena cannot be ignored. With this sentence, I qualify for swimming with the mainstream, but only to a point, because no evidence is available demonstrating the magnitude of that effect, considering all short and long-term feedbacks that it triggers. All other contributing factors, natural or anthropogenic, known or unknown, interact in an impossible to parse haystack.

Considering what models have delivered so far, it would be quite imprudent to accept them as a basis for policy decisions.

This “no evidence” is actually a very useful scientific finding. And there begins my heresy.


Merci de compartir cet article
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3 thoughts on “Self-criticism of the « no evidence » finding”

  1. La relation de cause à effet est un des points centraux de la recherche scientifique et j’en ai fait l’expérience au cours de ma carrière de recherche en biologie.
    L’histoire mérite d’être narrée car je crois avoir été l’un des premiers scientifiques à oser publier des résultats négatifs dans le prestigieux magazine scientifique Science. Cette publication fit grand bruit à l’époque car elle remettait en cause la confiance qu’avaient un grand nombre de biologistes au sujet de ce que l’on appelle dans le jargon du métier les radio-immuno-essais (RIA en anglais). Je recherchais la présence de beta-endorphines dans le placenta humain et la spécificité du RIA dépendait de la spécificité des anticorps utilisés. Brièvement le RIA consiste à marquer avec de l’iode radioactif l’antigène et de mesurer le déplacement de ce dernier par une substance ou un mélange en cours d’étude vis-à-vis de l’anticorps. Il s’agit d’une technique extrêmement sensible compte tenu de la très forte radioactivité de l’iode-125 utilisé pour marquer l’antigène connu et utilisé dans cet essai. J’explosais de joie quand dans mon petit tube se trouvait de putatives beta-endorphines placentaires ! Hélas le séquençage de ce peptide révéla qu’il s’agissait d’un fragment d’immunoglobuline qui comme par un effet du hasard présentait une forte analogie de séquence avec la beta-endorphine. J’ai donc mis en évidence une relation de cause à effet mais elle était totalement artéfactuelle. À la publication de mon papier dans Science j’eus droit à un commentaire presque haineux de John Maddox, alors éditeur en chef de la revue Nature …
    Je remettais en cause avec cet article la validité des RIA à laquelle croyaient aveuglément des milliers de chercheurs dans le monde.
    Il en est de même avec l’AGW. Je ne vois pas comment le CO2 peut contribuer au réchauffement de la surface terrestre puisque le principe même de l’effet de serre est contraire au deuxième principe de la thermodynamique. Il s’agit donc d fausse science et toute tentative d’établissement d’une quelconque relation de cause à effet entre le CO2 et le réchauffement participe également de la même fausse science.

  2. In theory, temperature is supposed to be proportional to the log of CO2. try running a correlation of temperature vs log of change in CO2.

    1. Trying it, the r2 coefficient is getting worse.
      If the primary forcing may be in logarithmic relationship with temperature, after combination of all interferences and feedbacks that “rule” may not be of much help.
      And, again, my point is not to find out any true relationship. I’m not as arrogant to pretend achieve this. I solely provide falsifying arguments on the allegation that GHGs would be the overwhelming cause of climate change.

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