As we look at attribution of global warming to various physical mechanisms, one of the puzzling observations we can make is that many researchers place too much emphasis on a single cause. This is especially true of the research from those that have skeptical views of GHG-caused warming.  For instance, Scafetta is convinced that the orbital forces are the key, and may also prove to be the cause of any long-term trends we are seeing — yet he makes a concerted effort to downplay the effects of the CO2 control knob, giving the CO2 TCR a very low value.  That is OK if he is truly being skeptical but not so good if he wants to retain objectivity.

From a previous post, we added Scafetta’s orbital cyclic parameters to the CSALT model. These include orbital parameters that are lunar as well as solar and planetary.  If we look at the periods that control lunar tides — the 18.613 year period and the 8.848 period  — CSALT generates an amplitude and phase that lines up remarkably well with the diurnal tidal analysis of R.Ray at NASA Goddard [1], whose work has been referenced by skeptic Clive Best  here [2] .  See Figure 1 below:

Fig 1: The top panel shows the CSALT extracted 18.6-year diurnal tidal period amplitude (right axis) along with the temperature phasing. The left axis shows the yearly averaged actual tidal amplitude from R.Ray[1], which is completely in-phase with the temperature factor.  The middle panel shows a higher resolution look at the tidal amplitudes over a shorter time interval.  Both the 18.6 year and a faint 8.85/2 year extracted temperature signal are in phase and of comparable relative amplitudes as the data.  The bottom panel shows the semidiurnal amplitude with a 8.85/2 temperature signal which has a different sign than the diurnal signal.

This is likely not a coincidental effect, as to line up a phase that accurately via a random contributing factor has a low probability.

The mechanism behind the temperature oscillations is likely an ocean-driven transfer of heat across the Earth as suggested  by Best [2]. He says that “The magnitude of this effect is difficult to estimate. However let’s assume that it is capable of producing a 0.05 degree C global oscillation .”  CSALT extracts a value of approximately 0.07 C peak-to-peak in diurnal oscillation, comparing favorably to Best’s estimated value.

In characterizing the diurnal tide oscillations in Figure 1, the maximum yearly extent in tides is exactly opposite in phase to the 18.6-year temperature factor. This make sense if we think of a tidal pull as a decompression of the atmosphere. Much as the expansion of the tides is due to a pull of the water toward the moon, the atmosphere will do the same.  Due to the ideal gas law a reduction in gravitational pressure will appear as a decrease in temperature.  This is likely a small effect though and other explanations are likely at work, such as due to ocean mixing. This is what Best is likely inferring as the ocean-driven transfer of heat.

The CSALT model has attracted criticism because of the number of parameters it includes. It is true that adding periodic components will improve the fit of a pseudo-cyclical signal, as that is the basis of Fourier analysis of waveforms — any waveform is decomposed as a set of periodic signals and given enough of these components with the right phase and amplitude, one can reconstruct any waveform.

However, these periodic components are not random or arbitrarily selected. They come from our understanding of cyclic energy that is applied to and dissipated by the earth.   The lunar tidal forces with its precise diurnal frequency of 18.613 years and semidiurnal frequency of 8.848 years is well documented.

Consider the following Figures 2 and 3.  Figure 2 shows how the correlation coefficient decreases as each of the cyclic periods is perturbed away from the nominally define orbital set value.  Where the values are harmonics, these are scaled in unison as they do not have twice the degrees of freedom as independent values would.   Note that the sharpness of these peak values against a 10% perturbation shows how sensitive they are to these values.

Fig 2:  Factors governing the correlation are sensitive to the precise period chosen. A variance of +/- 10% will knock the overall R value down.

Next, Figure 3 treats the entire orbital set with a uniform scale factor on the fundamental periods. In other words, each period is lengthened or shortened in unison.  Note, again, how the nominal periods, picked not arbitrarily but due to years of mathematical orbital modeling and observational data, show a sharp peak which appears tuned to the periods.  Also, the side-lobes indicate that the relative scaling of the periods is important as these will resonate as they cross synchronized peaks in the temperature record.

Fig. 3: Treating all the cyclic periods with a common scaling demonstrates the sharpness of the nominally chosen fundamental periods.  Not adding the orbital set generates the baseline value for R.

The bottom-line is that each one of these factors appears to be a subtle but real contributing factor to the global temperature signal.  Each one of these increases the correlation as it asymptotically approaches a value of unity. Skeptics such as Scafetta want to hit a home-run with a one-size-fits-all explanation to climate change, but the reality is much more subtly mundane, with the CO2 control knob obviously governing the upward trend.

Fig. 4 : Latest CSALT model agreement demonstrating the high R value achieved by including the orbital cyclic components.

 Related Posts

• CSALT references

References