TESTING – AND REFUTING – THE CENTRAL PREDICTION OF THE ‘AGW HYPOTHESIS’

Preamble

A presentation such as this, going as straight to the point as this one does, will necessarily rely on a fairly extensive ‘back catalogue’ of supporting graphs, figures and clarifications, most of which were generated in response to the likely questions and objections that might arise along the way, in the course of the argument being set up. Seeing how addressing these at every turn and having to substantiate all choices made at each single step would bog down and/or sidetrack the presentation to such an extent that the overall message would ultimately become lost in the noise, they will however have to remain in the background for now, rather kept ready at hand for the next round, so to speak. My point is this: Let the argument, as it stands, be presented first, to its completion – and then bring on the critique.

INTRODUCTION – THE THEORY BEHIND

The ‘AGW (CO2) warming hypothesis’ (really just another name for ‘the general idea of an «enhanced greenhouse effect» causing global warming’) says that, as the total content of CO2 in the atmosphere rises over time, so will global temperatures – in short: «Temps should go up». The scientific method demands that any scientific hypothesis should be able to make predictions like this, statements or claims about the world that can be tested, thus allowing us to either strengthen or weaken our trust in the explanatory power of our hypothesis. However, if there is to be any point in performing such a test, the prediction being tested needs to be relevant, i.e. it should be more or less unique to our particular hypothesis. So is «Temps should go up» a relevant prediction? No. It’s a prediction, but it’s not a relevant one. Because it isn’t specific enough. It isn’t unique to the ‘CO2 warming hypothesis’. It cannot separate between one proposed cause and another. For example, ‘more solar heat being absorbed by the Earth system over time’ would be an alternative explanation of multidecadal global warming to the «enhanced-greenhouse-effect» proposition. Both would predict the world to get warmer. So how do you choose one over the other? You hone in on an observation that would be unique to your favoured explanation. And now you’ve got yourself a relevant prediction to be tested …!

We, after all, want to find the cause behind the observed effect (‘global warming’), not the effect itself – that has already been found. That’s merely our starting point.

So what would be the relevant – the core – prediction of the ‘CO2 warming hypothesis’? In order to find that out, we must look at what ‘the idea of an «enhanced greenhouse effect» causing global warming’ really says. What is the proposed ‘greenhouse warming mechanism’, how does it work, and what is its identifying feature or physical fingerprint, distinguishing it from all other warming mechanisms?

Figure 1: From Held and Soden (2000).

Raymond Pierrehumbert explains the general idea:

«Adding more greenhouse gas [like CO2] to the atmosphere makes higher, more tenuous, formerly transparent portions of the atmosphere opaque to IR and thus increases the difference between the ground temperature [Ts] and the radiating temperature [Te]. The result, once the system comes into equilibrium, is surface warming.»

Note well what the caption of Fig.1 says: «(…) the effective emission temperature (Te) remains unchanged.» As Earth’s effective emission level (Ze) is forced up into generally higher (and thus colder) air layers, Earth’s average emission to space is reduced (lower temp = lower emission flux), which will have to be compensated for by warming at all altitude-specific layers from surface to tropopause, in order for the outgoing flux to be maintained at the same level as the incoming flux from the Sun. So, across each incremental step of the process, Te ends up at the same value as before (cooling first, then warming back up), while Ts (average global surface temp) and Ttropo (average global tropospheric temp) both end up at a higher value than before (Fig.1). And that is the gist of how the ‘greenhouse warming mechanism’ is supposed to work.

THE RELEVANT ‘CO2 PREDICTION

Now, the question is: How can we determine whether or not such a process, of gradually (incrementally) raising the planet’s effective emission level as the atmosphere becomes more opaque to outgoing IR, is in fact at work in the Earth system? Enter the one relevant prediction of the ‘CO2 warming hypothesis’, which unambiguously points out what we’re theoretically meant to see, if this process really is the cause of ‘modern global warming’:

  • The surface/troposphere temperature (Ts/Ttropo) should be observed to rise consistently over time, while Earth’s effective emission temperature (Te) stays at substantially the same level; ideally like this:

Figure 2.

Which would give a ‘difference curve’ (Ts/Ttropo minus Te) looking like this:

Figure 3.

A pretty clear signal of systematic divergence over time. So let’s turn to the climate models. They are the instruments – basing their output directly on the ‘greenhouse warming hypothesis’ outlined above – used by ‘Mainstream Climate Science’ to prognosticate about the future, and purportedly to explain the past. So let’s see how these models explain ‘global warming’ over the last few decades, using the so-called ‘CMIP5 model mean’ as our guide, by letting them compare our two variables: Ts/Ttropo, and Te*. (My data source (KNMI Climate Explorer) only provides temp data for the surface (Ts), not the troposphere (Ttropo), which would be more useful, considering how at least 85% of Earth’s final emission flux to space is drawn from the troposphere, and only about 10% from the surface. The two are, however, supposed to rise at equal rates (Fig.1).)

* Te is found by converting the average OLR (‘Outgoing Long-wave Radiation’) flux anomalies at the ToA, designated ‘rlut’ in Climate Explorer, to the corresponding emission temperature anomalies by appropriately applying the Stefan-Boltzmann equation, in effect multiplying the radiation data by 0.266 (cf. Fig.4 below).

Here are the results (01/1985 – 04/2020):

Figure 4.

Figure 5.

Which more or less exactly match the theoretical templates in Figs. 2 and 3 above:

Figure 6.

The only significant discrepancy between the model output (Figs. 4 and 5) and the ideal cases (Fig.6) arises from the (cooling) volcanic influence in the former derived from two massive eruptions in 1982 (El Chichón) and 1991 (Pinatubo) respectively, pulling the model curves down somewhat prior to about 2001.

THE TEST

And with that we have reached the point where we are finally ready to put the ‘CO2 warming hypothesis’ to the test, by its one unique prediction.

Let’s first have our basic premise spelled out by the IPCC themselves, from the time, in their infancy, when they still bothered upholding a certain semblance of adherence to the scientific method, to ordinary logic and rational reasoning, in short, to an honest philosophy of always searching for the truth; from their 1990 First Assessment Report (FAR WG1, Section 8.1.2):

«The word ‘detection’ has been used to refer to the identification of a significant change in climate (such as an upward trend in global mean temperature). However, identifying a change in climate is not enough for us to claim that we have detected the enhanced greenhouse effect, even if statistical methods suggest that the change is statistically significant (i.e., extremely unlikely to have occurred by chance). To claim detection in a useful and practical way, we must not only identify a climatic change, but we must attribute at least part of such a change to the enhanced greenhouse effect. It is in this stricter sense that the word ‘detection’ is used here. Detection requires that the observed changes in climate are in accord with detailed model predictions of the enhanced greenhouse effect, demonstrating that we understand the cause or causes of the changes.»

They quickly moved away from this well-advised approach, of course, adopting instead the novel and – it would seem – near-magical detection standard of ‘unprecedented changes’. Apparently it is sufficient, after all, to simply look at the effect (like «an upward trend in global mean temperature») and then determine its cause directly from that, as long as the effect is significant enough, i.e. somehow ‘lacking historical precedent’. The only prediction you need from that point on is: «Temps should go up».

Problem is that this rather convenient change of mind revealed their mission to no longer be a scientific one, because employing a methodology where an effect is basically allowed to explain itself enables you to insert whatever cause or ‘driving mechanism’ that you wish to promote in the conclusion, from the beginning, effectively creating your own circular argument.

Which is why we will rather go back to 1990 to do a proper – real scientific – test of the ‘CO2 warming hypothesis’. And the test is simply this:

How well, if at all, does our theoretical/modelled prediction, highlighted in Figs. 2 & 3 (theoretical) and Figs. 4 & 5 (modelled) above, stack up against reality?

We have consistent, high-quality ToA radiation flux satellite observations from the real Earth system going back to 1985. In other words, we have a total of just over 35 years of reliable data, which should be more than sufficient to lend high confidence to a test like this. So here are the observation-based results – Ttropo (represented by UAHv6 TMT anomaly data) versus Te (represented by the combined ERBS Ed4 + CERES EBAF Ed4.1 series IR flux anomaly data, converted into corresponding emission temp anomalies), 01/1985 – 04/2020:

Figure 7.

Bear in mind that this is the equivalent relationship on display, between our two relevant climatic variables, to the one in Fig.2 (theoretical) and the one in Fig.4 (modelled) above.

And here’s the resulting ‘difference curve’ between the two (TtropoTe):

Figure 8.

What do we see? The radiative temperature variable (Te) appears simply to be tracking the altitude-specific temperature variable (Ttropo) over time (Fig.7). Which is fully in line with the fundamental physical knowledge that increasing temp → increasing emission, but obviously in direct contradiction to what the ‘CO2 warming hypothesis’ – the theory itself and the models based on it – all the same says we should observe as the world gets warmer.

Overall, the difference curve (Fig.8) lies pretty flat (along the 0 axis) from 1985 to 2020; even though there are of course quite significant ups and downs along the way, this only points to the fact that we are after all observing the progression in time of a complex, dynamic natural system, also known as the global climate. Taking this into account, I would say that the fairly tight overall correlation between the two curves in Fig.7, the clear tendency for them to converge over time rather than diverge, is rather impressive to behold. The keen eye might spot how the difference between Ttropo and Te (Fig.8) results in a pattern curiously reminiscent of the ENSO sequence (represented by the NINO3.4 SSTa data). In particular, the major ENSO events between 1985 and 2020 seem to leave their distinct mark on the Ttropo Te residual curve, strongly suggesting that their well-established influence on the global climate in some way affects the direct relationship between the two variables being compared.

To show how significant this connection really is, I’ve superimposed the Ttropo Te difference curve on the down-scaled ENSO signal (NINO3.4 SSTa), after delaying the latter by six months in order to visually optimize the fit:

Figure 9.

I have added a quartic polynomial to both datasets to emphasize their variation tendencies over time; the graph spans a total of 35 years and 4 months.

(Another natural phenomenon strongly affecting the coincidence between the two curves in Fig.7 is the aforementioned large volcanic eruptions, such as that of Mt. Pinatubo in 1991. Note, I have intentionally removed the disproportionately – and thus rather distractingly – large impact of that incident by deleting both the Ttropo and Te data between mid ’91 and late ’92.)

SUMMARY – CONCLUSION

So how did the central prediction of the ‘CO2 warming hypothesis’ stack up against reality?

Short answer: Not at all!

It doesn’t take much to realise this is the simple truth of the matter. Let’s simply juxtapose below all the relevant diagrams presented above in order to carry the message home:

a) . . . . . . . . . . . . . . . . . . . . . . . . . b) . . . . . . . . . . . . . . . . . . . . . . . . c)

d) . . . . . . . . . . . . . . . . . . . . . . . . . e) . . . . . . . . . . . . . . . . . . . . . . . . f)

Figure 10 a), b), c), d), e) & f).

Total divergence from 1985 to 2020 (35+ years) between the Ts/Ttropo curve and the Te curve:

  • MODELS (Fig.b) & e)):                   +0.7 K (+0.2 K/decade)
  • OBSERVATIONS (Fig.c) & f)):      ~ 0.0 K (0.0 K/decade)


Below I provide links to four other posts on this blog. Please read them for relevant background information and supporting material to this one.

«How the CERES EBAF Ed4 data disconfirms ‘AGW’ in 3 different ways …»

«THE DATA: Sun – not Man – is what caused, and causes, ‘global warming’»

«Verifying my near-global 1985-2017 OLR record»

«THE DATA: (…); Supplementary discussions»

In these links you will also find the references to the various data sources used …

11 comments on “TESTING – AND REFUTING – THE CENTRAL PREDICTION OF THE ‘AGW HYPOTHESIS’

  1. Peter McNeall says:

    Very impressed. I believe the gravito-thermal effect is what causes the temperature difference in the atmosphere. I posted an article on LinkedIn about this.

  2. Roy W. Spencer says:

    I don’t think the discrepancy is as large as you are suggesting, but the reasons for what is being observed are still not obvious.

    The LW, SW, and [LW+SW] trends in CMIP5 vs. CERES (March 2000 through April 2020) for 60N-60S latitudes are:

    CMIP5 / CERES (W/m2 per decade)
    LW: +0.09 / +0.25
    SW: -0.24 / -0.71
    NET: -0.15 / -0.45

    The SW and the NET trends show the real climate system (CERES) is accumulating radiant energy faster than the average CMIP5 model suggests from a decrease in clouds. This SHOULD be causing more warming in the observations than the models, which is not the case since 2000. The enhanced LW loss in the observations vs. models is modest, and would suggest a negative feedback from clouds and/or vapor, and not temperature rise, since the troposphere has not warmed as much as models say it should have. Taken together I’d say this is evidence for some natural warming process contributing to warming since 2000, with enhanced LW loss due to a Lindzen-type “Iris” effect. Just my opinion.

    • okulaer says:

      Thanks, Roy.

      Yes, I agree, the net accumulation of energy within the climate system (including the oceans) seems very much to be the result of a natural process, caused by a reduction in global albedo (mostly from a decrease in cloud cover) – more SW absorbed rather than less LW emitted.

      • Alex says:

        “more SW absorbed rather than less LW emitted”

        Which of course is predicted by climate models as a feedback to the warming initiated by CO2. See Donohoe’s work on the issue.

        • okulaer says:

          The only problem being: We don’t see the so-called “CO2 warming” anywhere in the actual record. We only see the solar warming. So the CO2 warming remains a mere speculation, based in models but not in actual observations from the real world. While the solar warming (quite clearly appearing – in the data – to begin without any prior CO2-driven warming) seems quite real, indeed. I’ve addressed this very point here: https://okulaer.com/2018/03/24/the-data-supplementary-discussions/ (Addendum II: What do the models say?)

          • Alex says:

            “We don’t see the so-called “CO2 warming” anywhere in the actual record. We only see the solar warming.”

            Which is what is predicted.

            “While the solar warming (quite clearly appearing – in the data – to begin without any prior CO2-driven warming)”

            Of course it had prior CO2 driven warming. Were you not aware that humans caused a CO2 increase PRIOR to the data you are referring to? Are you not aware that the present measurements are all made in the presence of prior warming, which you cannot rule out as being caused by increased CO2 based on present measurements?

            “I’ve addressed this very point here”

            Actually you haven’t. You cherry picked some data and you haven’t initialized and run the models to see what happens for that situation. The models are not perfect, and no climate scientist claims that they are, but it is not news that albedo will change as a feedback to warming. So you would need to produce an attribution of the warming prior to the measurements that shows that CO2 is NOT responsible. And of course you have not done that.

            Blog warriors like you and Charles Anderson are hilarious. Why don’t you write up a paper and get it to appear in a scientific journal?

            All of your nonsense about colder objects not being able to transmit energy to warmer objects leads to absolute nonsense. You can read Anderson’s crankery here:
            https://objectivistindividualist.blogspot.com/2017/11/solving-parallel-plane-black-body.html

            He states that for two parallel gray body plates the cold plate does not emit any radiation and the hot plate emits as:
            PHI = (σ/a) Δe = εH σ TH4 – εC σ TC4

            Can you even tell me why that obviously is wrong? The correct formula for the heat transfer between two graybody plates is

            q = σ (TH4 – TC4)/( 1/εH + 1/εC – 1)

            So, if you agree that Anderson’s formula is nonsense, then how do you derive the correct formula without accounting for the fact that the cold plate does transmit energy to the hot plate?

            • okulaer says:

              “Of course it had prior CO2 driven warming. Were you not aware that humans caused a CO2 increase PRIOR to the data you are referring to? Are you not aware that the present measurements are all made in the presence of prior warming, which you cannot rule out as being caused by increased CO2 based on present measurements?”

              What is this nonsense!? Sorry, I mistook you for someone who wanted to have a discussion based on actual scientific arguments. Now I know you’re simply another one of those dogmatically bound useful idiots of the climate establishment that ‘just know’ because … well, “They” [‘The Powers That Be’] tell you it’s so. Bye 🙂

  3. Peter McNeall says:

    In Physics Today RT2011 Raymond T. Pierrehumbert states :-

    The way it works is really no different from the way adding fiberglass insulation or low-emissivity windows to your home increases its temperature without requiring more energy input from the furnace.

    Carbon dioxide is just planetary insulation.

    But when you add fiberglass insulation to your home it increase the temperature difference between the inside and the outside.

    This is not what happens when you add CO2 because the temperature gradient or lapse rate does not change as shown in Fig 1 – Held and Soden (2000).

    The temperature gradient is set by the gravito-thermal effect and it would be essentially the same if only nitrogen and oxygen were present.

    So the analogy with fiberglass does not hold.

    There is something suspicious about it all.

  4. co2islife says:

    The GHG effect isn’t constant with altitude. At lower altitudes, the highly packed molecules impede the transport of energy to outer space. At higher altitudes, H2O precipitates out leaving only CO2 to impede the outgoing radiation. As the atmosphere thins, so does the distance between molecules, so at higher altitudes, CO2 actually cools the atmosphere, and that is what data shows.

  5. aljo1816 says:

    Why RCP was used for the TOA flux from the CMIP5 ensemble mean? And why have you chosen to use 2-m temperature data from the CMIP5 mean and compared it against troposphere (I think something like 0-10km) temperature observations? I’m not sure these are apples to apples. It’s also not clear to me that the ensemble mean is an appropriate choice at all, here, since it should necessarily balance out the TOA flux, guaranteeing a flat line in your analysis.

    • okulaer says:

      Hi, aljo1816. Thanks for commenting. You ask: “… why have you chosen to use 2-m temperature data from the CMIP5 mean and compared it against troposphere (I think something like 0-10km) temperature observations?”

      I answer this question in the post. I quote: “My data source (KNMI Climate Explorer) only provides temp data for the surface (T_s), not the troposphere (T_tropo), which would be more useful, considering how at least 85% of Earth’s final emission flux to space is drawn from the troposphere, and only about 10% from the surface. The two are, however, supposed to rise at equal rates (Fig.1).”

      You also ask: “Why RCP was used for the TOA flux from the CMIP5 ensemble mean?” I’m guessing here that you mean WHAT RCP I used … I actually don’t remember. What I do remember is that I tried them all out to see if there were any major discrepancies between them. There weren’t, so I just picked one at random, most likely the 4.5 scenario. Sorry, I should’ve made this point. You can check it all out for yourself, though, in KNMI Climate Explorer: http://climexp.knmi.nl/selectfield_cmip5.cgi?id=someone@somewhere

      Hope this answers your questions 🙂

      P.S. I’m not sure I understand your final point. I explain the process quite thoroughly in the post itself, I feel, and why this specific test requires the specific variables chosen.

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