Natural versus Anthropogenic

The  natural 60 year heat cycle recently observed in the Atlantic implies that the underlying trend of anthropogenic warming since 1942 has been only ~0.45C. This value results in a derived transient climate response (TCR)  of ~1.5C. The conclusions of the AR5 attribution study now look questionable because they ignore any natural warming component post 1970.

Figure 1. A Fit to HADCRUT4 temperature anomaly data

Figure 1. A Fit to HADCRUT4 temperature anomaly data

A new paper Varying planetary heat sink led to global-warming slowdown and acceleration  challenges the AR5 attribution statement that all observed warming can be explained by anthropogenic forcing alone because it shows clear evidence of a natural 60 year ocean heat cycle. This cycle is also evident in the global temperature data – see A 60 year oscillation. A long discussion on this paper can also be seen at Judith Curry’s blog.

Figure 10.5 in the AR5 attribution chapter is based on model comparisons from 1951 to 2010 is now looking rather unlikely because this result leaves no room for any natural component to warming, as shown below.

Fig 10.5 from AR5. ANT is the net anthropogenic forcing. I do not understand how the ANT errors get smaller after adding GHG and OA together !

Fig 10.5 from AR5. ANT is the net anthropogenic forcing. I do not understand how the ANT errors get smaller after adding GHG and OA together !

The new evidence of a significant oceanic warming and cooling cycle means that between 1950 and 2010 anything up to 50% of the rise in observed temperature was actually due to the warming phase of the 60y cycle. The error bars on the ‘ANT’ component in figure 10.5 are just too small to allow for this. If this is the case how can we best estimate the underlying anthropogenic component?

The fit to the H4 data in Figure 1 is based on the assumption of a logarithmic dependence on CO2 forcing and temperature response. The (transient) temperature response includes climate feedbacks and is to be measured. The CO2 forcing is given by \Delta{S} = 5.3\ln{\frac{C}{C_0}} which is derived in Radiative Forcing of CO2 and includes a 60y harmonic cycle which was previously identified  as described in the post “A 60 year oscillation in Global Temperature data and possible explanations” .

The true anthropogenic component of warming can be identified by subtracting off the natural warming/cooling cycle. The peaks of the oscillation occur both in 1942 and 2008 so the rise in temperature between these two dates should measure the underlying human induced CO2 warming.

Date Anomaly (degC) CO2 level (ppm)
1942 -0.01 ± 0.01 308
2008 0.44 ± 0.01 378

Now assuming that this now represents  the underlying anthropogenic warming between 1942 and 2008, we can measure a value for TCR as follows

0.45 = const \times \ln{\frac{378}{308}} \implies const = 2.2


TCR = 2.2\ln{2} = 1.5 C

with an error of about 0.1 C

Conclusion:  The new paper by Chen and Tung provides independent evidence for a global 60 year warming and cooling cycle due to natural variations in AMOC. The IPCC attribution statement is based on model fingerprint evidence that all warming since 1950 can be explained by AGW. However this measured warming must contain a component from the AMOC warming cycle from 1970 to 2000. Only by comparing dates at similar positions in the cycle can the true anthropogenic component be identified.  We choose 1942 and 2008 as the peaks in this cycle to show a net warming of 0.45±0.2 C. CO2 levels rose by 70 ppm between those two dates. This is then used to derive from observations a value for  TCR = 1.5 ± 0.1 C.

About Clive Best

PhD High Energy Physics Worked at CERN, Rutherford Lab, JET, JRC, OSVision
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10 Responses to Natural versus Anthropogenic

  1. A C Osborn says:

    The only problem with the analysis is the fact that the Temperature record used is Fabricated.
    I would like to see the same thing done with the Raw data.

    • Clive Best says:

      Yes. There is indeed the possibility that the station data have been “homogenised” either consciously or most likely sub-consciously. Unfortunately the raw station data from CRU is not available. I think Phil Jones says he lost them !

      So all we can do is to use their data and show that at worst warming is “very likely” to be less than 2C by 2100. So if we haven’t all died from Ebola or food riots by then, at least global warming won’t be much of a big problem. A warmer climate in the UK would probably be of economic benefit.

  2. Ian says:

    I saw this comment on Climate Etc, Atlantic versus Pacific versus AGW where I see you also commented.

    “Paul S | August 28, 2014 at 10:22 am | Reply

    A priori, it could potentially be an interesting point, but doesn’t really have anything to do with Judith’s critique or Gavin’s critique of Judith’s critique.

    As to the error bars, consider the reason for the variance in GHG and OA temperature response. Probably the biggest is sensitivity, but sensitivity would apply nearly equally for cooling and warming anthropogenic factors. That means a model with high-end GHG response (about 1.3ºC according to Figure 10.5) is also likely to have a high-end OA response (about -0.6ºC). The net total is 0.7ºC. Does that make more sense for you?”

    Do you have any thoughts on the error bar comments?

    • Clive Best says:


      No I fail to understand the point about error bars. If models have a net GHG forcing error of 0.4 C and a similar error for aerosols, then how can the sum of these two effects have a much smaller error ? Am I massing something ? Paul S seems to be arguing that just because aerosols have a cooling effect they cancel out the errors on GHG warming effect. He is saying they are correlated I think.

      So he is saying that if models are too sensitive then they will also increase the negative aerosol cooling ! However, aerosols values are inherently very uncertain, whereas we know precisely what the CO2, CH4 levels are.

      • Ian says:

        Looking at the error bars, it seems that Paul S’s position may be the official position, although I’ve not seen this explanation detailed anywhere in the IPCC documentation. Maybe I need to look more closely.

        The error values seem to have been effectively vector summed (?!). Based on the pure subtraction, this suggests the correlation is 100%. Surely there are other errors in the calculation/measurement of the effect of aerosols other than model sensitivity, no?

        Thanks anyway.

  3. Ian says:

    I had a look at the Real Climate site and you’d commented on a thread there last year.
    Gavin responded on the error bar issue in this way.

    gavin says: 14 Oct 2013 at 1:01 PM
    “Just for completeness, and to preempt any confusion, this post from Paul Matthews, is a typical example of what happens when people are so convinced by their prior beliefs that they stop paying attention to what is actually being done. Specifically, Matthews is confusing the estimates of radiative forcing since 1750 with a completely separate calculation of the best fits to the response for 1951-2010. Even if the time periods were commensurate, it still wouldn’t be correct because (as explained above), the attribution statements are based on fingerprint matching of the anthropogenic pattern in toto, not the somewhat overlapping patterns for GHGs and aerosols independently. Here is a simply example of how it works. Let’s say that models predict that the response to greenhouse gases is A+b and to aerosols is -(A+c). The “A” part is a common response to both, while the ‘b’ and ‘c’ components are smaller in magnitude and reflect the specific details of the physics and response. The aerosol pattern is negative (i.e. cooling). The total response is expected to be roughly X*(A+b)-Y*(A+c) (i.e. some factor X for the GHGs and some factor Y for the aerosols). This is equivalent to (X-Y)*A + some smaller terms. Thus if the real world pattern is d*A + e (again with ‘e’ being smaller in magnitude), an attribution study will conclude that (X-Y) ~= d. Now since ‘b’ and ‘c’ and ‘e’ are relatively small, the errors in determining X and Y independently are higher. This is completely different to the situation where you try and determine X and Y from the bottom up without going via the fingerprints (A+b or A+c) or observations (A+d) at all. – See more at:

    So the fingerprinting is more accurate than the current measurements, and so accurate that an overall Anthropogenic contribution can be stated to circa +/- 0.1C over a 60 year period.

    I find it hard to square that with the current pause in surface and troposphere temperatures and the comparison to the model predictions

    Why does this seem so similar to the financial models of 2008? Very bright people making extremely accurate calculations based on insufficient knowledge of both initial conditions, assumptions and underlying controlling dynamics.

    Hey ho.

    • Clive Best says:

      Gavin does a similar trick when he dismisses Judith Curry’s 50-50 attribution claim. He first says that the time range is different (1951-2010) (1970-2010) so therefore the opponent has made a stupid mistake and all conclusions drawn are therefore wrong.

      Now above he also claims that Anthropogenic actually means GHG + Aerosols. So apart from some minor terms Aerosols = -const*GHG . That really is the same as saying

      ANT = GHG – fudge factor*GHG

      ANT = (1- (fudge factor))*GHG = all observed warming

      Fudge Factor is the year by year tuning needed to make CMIP5 hindcasts agree with temperature data.

      You can’t win against Gavin’s logic !

  4. tallbloke says:

    This post makes the assumption that the 60yr oceanic cycle is the only natural cycle affecting the surface temperature. However there is abundant evidence for a ~1000yr natural cycle too. GHGs didn’t start increasing in 1700AD to any appreciable extent according to the ice core data the warmists like to use, so we have to assume natural causes for the ‘recovery from the Little Ice Age’.

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