by Judith Curry
David Hagen wrote on the Dempster thread:
Empirical evidence for a celestial origin of the climate oscillations and its implications
Abstract. We investigate whether or not the decadal and multi-decadal climate oscillations have an astronomical origin. Several global surface temperature records since 1850 and records deduced from the orbits of the planets present very similar power spectra. Eleven frequencies with period between 5 and 100 years closely correspond in the two records. Among them, large climate oscillations with peak-to-trough amplitude of about 0.1 and 0.251C, and periods of about 20 and 60 years, respectively, are synchronized to the orbital periods of Jupiter and Saturn. Schwabe and Hale solar cycles are also visible in the temperature records. A 9.1-year cycle is synchronized to the Moon’s orbital cycles. A phenomenological model based on these astronomical cycles can be used to well reconstruct the temperature oscillations since 1850 and to make partial forecasts for the 21st century. It is found that at least 60% of the global warming observed since 1970 has been induced by the combined effect of the above natural climate oscillations. The partial forecast indicates that climate may stabilize or cool until 2030–2040. Possible physical mechanisms are qualitatively discussed with an emphasis on the phenomenon of collective synchronization of coupled oscillators.
Journal of Atmospheric and Solar-Terrestrial Physics 72 (2010) 951–970
Link to full version of the paper is [here].
Some text from the Conclusion:
Herein, we have found empirical evidences that the climate oscillations within the secular scale are very likely driven by astronomical cycles, too. Cycles with periods of 10–11, 12, 15, 20–22, 30 and 60 years are present in all major surface temperature records since 1850, and can be easily linked to the orbits of Jupiter and Saturn. The 11 and 22-year cycles are the well- known Schwabe and Hale solar cycles. Other faster cycles with periods between 5 and 10 years are in common between the temperature records and the astronomical cycles. Long-term lunar cycles induce a 9.1-year cycle in the temperature records and probably other cycles, including an 18.6-year cycle in some regions (McKinnell and Crawford, 2007). A quasi-60 year cycle has been found in numerous multi-secular climatic records, and it is even present in the traditional Chinese, Tibetan and Tamil calendars, which are arranged in major 60-year cycles.
The physical mechanisms that would explain this result are still unknown. Perhaps the four jovian planets modulate solar activity via gravitational and magnetic forces that cause tidal and angular momentum stresses on the Sun and its heliosphere. Then, a varying Sun modulates climate, which amplifies the effects of the solar input through several feedback mechanisms. This phenomenon is mostly regulated by Jupiter and Saturn, plus some important contribution from Neptune and Uranus, which modulate a bi-secular cycle with their 172 year synodic period. This interpretation is supported by the fact that the 11-year solar cycles and the solar flare occurrence appear synchronized to the tides generated on the Sun by Venus, Earth and Jupiter (Hung, 2007). Moreover, a 60-year cycle and other planetary cycles have been found in millennial solar records (Ogurtsov et al., 2002) and in the number of middle latitude auroras (Komitov, 2009).
Alternatively, the planets are directly influencing the Earth’s climate by modulating the orbital parameters of the Earth–Moon system and of the Earth. Orbital parameters can modulate the Earth’s angular momentum via gravitational tides and magnetic forces. Then, these orbital oscillations are amplified by the climate system through synchronization of its natural oscillators. This interpretation is supported by the fact that the temperature records contain a clear 9.1-year cycle, which is associated to some long-term lunar tidal cycles. However, the climatic influence of the Moon may be more subtle because several planetary cycles are also found in the Earth–Moon system.
The astronomical forcings may be modulating the length of the day (LOD). LOD presents a 60-year cycle that anticipates the 60-year temperature cycle (Klyashtorin, 2001; Klyashtorin and Lyubushin, 2007; Klyashtorin et al., 2009; Mazzarella, 2007, 2008; Sidorenkov and Wilson, 2009). A LOD change can drive the ocean oscillations by exerting some pressure on the ocean floor and by modifying the Coriolis’ forces. In particular, the large ocean oscillations such as the AMO and PDO oscillations are likely driven by astronomical oscillations.
From Scafetta’s comments on the Dempster thread:
The paper show that astronomical cycles match the temperature cycles with a probability of 96% and above, while current general circulation models such as the Giss ModelE would reproduce the same temperature cycles with a probability of just 16%.
Is the theory that I have proposed scientifically valid? Probably yes, because it is shown to be able to reproduce the global surface data patterns and has a chance to properly forecast climate oscillations much better than the Giss ModelE, for example. Thus, my theory matches the main requirement of the scientific method. The theory suggests that about 60% of the warming observed since 1970 is due to natural cycles, while the IPCC using GCMs claims that 100% of the post 1970 warming is anthropogenic. My theory reconstruct a cooling or momentarily temperature rest since 2002 as observed in the data, which the IPCC GCMs have all projected a significant warming which is not seen in the data, etc.
Is the theory that I have proposed (the climate is regulated by astronomical cycles) already explained by means of other established theories such the fundamental laws of mechanics, thermodynamics, chemistry and so on? No, it isn’t. Does this mean that the proposed theory is not “scientific”? No, because, rigorously speaking, the scientific method does not require that a proposed theory must be explained by another theory. Future research may search for interconnections among scientific theories and consolidate or eventually debut a proposed theory.
Thus, I believe that the problem of physical uncertainty cannot be addressed by looking to some mysterious and magic statistical method. People simply need to apply the scientific method in the proper way. That is, if one does not understand yet the microphysics of a complex phenomenon (that is if analytical computer climate models are not satisfactory yet), he should look at the phenomenon as a whole and try to understand the information implicit in its dynamics by constructing and forecasting it first. The microphysics problem is addressed later.
From another message (not necessarily about this paper):
For example, once I had a sequence of data and I estimated its power spectrum. According to the usual statistical theories the amplitude of the spectrum peaks can be associated to a statistical confidence level. I found a set of peaks with an extremely low statistical confidence level and the statistical theory would imply that such peaks are indistinguishable from random noise, and therefore, not relevant. However, later I realized that those peaks had a clear dynamical meaning, thus it was not noise, but important signal.
The truth was that the statistical theory was based on axioms that did not agree with the dynamics of my physical signal.
So, statistics can be easily misapplied in natural science if one does not understand its framework. And this happens all the times.
George Taylor, former Oregon State climatologist writes:
Nicola Scafetta has published the most decisive indictment of GCM’s I’ve ever read in the Journal of Atmospheric and Solar-Terrestrial Physics. His analysis is purely phenomenological, but he claims that over half of the warming observed since 1975 can be tied to 20 and 60-year climate oscillations driven by the 12 and 30-year orbital periods of Jupiter and Saturn, through their gravitational influence on the Sun, which in turn modulates cosmic radiation.
If he’s correct, then all GCM’s are massively in error because they fail to show any of the observed oscillations.
There have been many articles over the years which indicated that there were 60-year cycles in the climate, but this is the first one I’ve seen which ties them to planetary orbits.
In the comments, Vukcevic writes:
Not much new there. In 2003 I wrote short article
analysing Jupiter-Saturn vs. solar activity resonance. Scafetta’s mechanism of magnetic resonance is not new either, as many of readers may recall long and tedious arguments I had with Dr. Svalgaard on the subject. I wrote about the J-S effect, but do not think climate change is a direct response to it.
None of these offer a convincing mechanism, hence we have to look to the field anew.
Solar system, as the name implies is a ‘system’ and most of ‘grand events’ are rooted in that system, that has been known for long time, but on its own it does not move let alone resolve the climate debate.
Dr. Scafetta has to come up with some ‘down to Earth’ data that can be directly applied to what is recorded during last 350 or so years, if he is to make any impact on the climate lobby, otherwise his work will be dismissed and consigned to the realm of astrology.
I haven’t seen any other substantive analyses of this paper, have I missed anything?
The key result IMO is power spectrum shown in Fig 3.
Fig. 3 shows the power spectrum (Ghil et al., 2002) of the global surface temperature (monthly sampled). Two methods are adopted: the maximum entropy method (1000 poles) and the multi-taper method against the null hypothesis of red noise with three confidence levels. The figure shows strong peaks at 9, 20 and 60 years with a 99% confidence against red noise background. The graph also shows a clear annual cycle and several other cycles with a 99% confidence. The harmonic signal Fisher (F) test gives a significance level larger than 99% and 95% for the 60 and 20 year cycles, respectively. The Blackman–Tukey correlogram produces a spectrum equivalent to that obtained with the maximum entropy method, but its peaks are less sharp and do not have a good resolution. In the following, the maximum entropy method is used because with a proper number of poles it better resolves the low frequency band of the spectrum and produces very sharp peaks (Priestly, 2001).
On the surface, this significance analysis (e.g. the results) doesn’t seem convincing, in particular the multi-taper analysis seems to be producing too many peaks with 99% confidence, especially given the short length of data record used?
The attribution of these peaks to astronomical cycles occurs based on the matching of the astronomical cycles to the spectral peaks, without any apparent physical mechanism relating them. The amplitude of the spectral peaks does not seem consistent with the likely subtle effects of astronomical forcing.
If there is some sort of amplifying feedback at work, is there any reason to think that the phase of the forcing would be reflected in the phase of the response in this complex nonlinear chaotic climate system?
How would one go about either falsifying Scafetta’s hypothesis, or garnering further support for it?