Basil Copeland and Anthony Watts
Image from NASA GSFC
Many WUWT readers will remember that last year we presented evidence of what we thought was a “solar imprint” in globally averaged temperature trends. Not surprisingly, given the strong interest and passion in the subject of climate change and global warming, our results were greeted with both praise and scorn. Some problems were pointed out in our original assessment, and other possible interpretations of the data were suggested. Some WUWT readers have wondered whether we would ever follow up on this.
We have been quietly working on this, and having learned much since our initial effort, are as persuaded as ever that the basic premise of our original presentation remains valid. We have tried out some new techniques, and have posted some preliminary trials on WUWT in the past few months, here, and here.
However, questions remain. Since a lot of bright and capable people read WUWT, rather than wait until we thought we had all the answers, we have decided to present an update and let readers weigh in on where we are at with all of this. We have, in fact, drafted a paper that we might at some point submit for peer review, when we are more comfortable with some of the more speculative aspects of the matter. What follows is taken from that draft, with some modification for presentation here.
For those that prefer to read this in printed form, a PDF of this essay is available for download here
Introduction
Evidence of decadal and bidecadal variations in climate are common in nature. Classic examples of the latter include the 20 year oscillation in January temperature in the Eastern United States and Canada reported by Mock and Hibler [1], and the bidecadal rhythm of drought in the Western High Plains, Mitchell, Stockton, and Meko [2], and Cook, Meko, and Stockton [3]. Other examples include a bidecadal (and pentadecadal) oscillation in the Aleutian Low, Minobe [4]; rainfall and the levels of Lake Victoria, East Africa, Stager et al. [5]; and evidence from tree rings along the Russian Arctic, Raspopov, Dergachev, Kolstrom [6], and the Chilean coast, Rigozo et al. [7].
Evidence of decadal or bidecadal oscillations in temperature data, however, especially upon a global scale, has proven to be more elusive and controversial. Folland [8] found a spectral peak at 23 years in a 335 year record of central England temperatures, and Newell et al. [9] found a 21.8 year peak in marine air temperature. Brunetti, Mageuri, Nanni [10] have reported evidence of a bidecadal signal in Central European mean alpine temperatures. But the first to report bidecadal oscillations – of 21 and 16 years – in globally averaged temperature were Ghil and Vautard [11]. Their results were challenged by Eisner and Tsonis [12], but were later taken up and extended by Keeling and Whorf [13, 14].
No less unsettled is the issue of attribution. Currie [15], examining U.S. temperature records, reported spectral peaks of 10.4 and 18.8 years, attributing the first to the solar cycle, and the latter to the lunar nodal cycle. In the debate over the bidecadal drought cycle of the Western High Plains, Mitchell, Stockton, and Meko [2] concluded that the bidecadal signal was a solar phenomenon, not a lunar one. Bell [16, 17] and Stockton, Mitchell, Meko [18] attributed the bidecadal drought cycle to a combined solar and lunar influence, as did Cook, Meko, and Stockton [3]. Keeling and Whorf [13], working with globally averaged temperature data, reported strong spectral peaks at 9.3, 15.2, and 21.7 years. Eschewing a simpler combination of solar and lunar influences, they proposed a complex mechanism of lunar tidal influences to explain the evidence [14].
The past decade has seen only sporadic interest in the question of whether decadal and bidecadal variations in climate have a solar or lunar attribution, or some combination of the two. Cerveny and Shaffer [19] and Treloar [20] report evidence of tidal influences on the southern oscillation and sea surface temperatures; Yndestad [21, 22] and McKinnell and Crawford [23] attribute climate oscillations in the Arctic and North Pacific to the 18.6 year lunar nodal cycle. But interest in discerning an anthropogenic influence on climate has largely eclipsed the study of natural climate variability, at least on a global scale. There continue to be numerous reports of decadal or bidecadal oscillations in a variety of climate metrics on local and regional scales, variously attributed to solar and or lunar periods [3-7, 10, 19-27], but little has been done to advance the state of knowledge of lunar or solar periodic cycles on globally averaged temperature trends since the final decade of the 20th Century.
Besides the shift in interest to discerning an anthropogenic influence on global climate, the lack of agreement on any kind of basic physical mechanism for a solar role in climate oscillations, combined with the apparent lack of consistency in the relation between solar cycles and terrestrial temperature trends perhaps has made this an uninviting area of research. The difficulty of attributing temperature change to solar influence has been thoroughly surveyed by Hoyt and Schatten [28]. In particular, there are numerous reports of sign reversals in the relationship between temperature and solar activity in the early 20th century, particularly after 1920 [28, pp 115-117]. More recently, Georgieva, Kirov, and Bianchi [29] surveyed comprehensively the evidence for sign reversal in the relationship between solar and terrestrial temperatures, and suggested that these sign reversals are related to a long term secular solar cycle with solar hemispheric asymmetry driving the sign reversals. Specifically, they argue that there is a double Gleissberg cycle in which during one half of the cycle the Southern solar hemisphere is more active, while during the other half of the cycle the Northern solar hemisphere is more active. They argue that this solar hemispheric asymmetry is correlated with long term terrestrial climate variations in atmospheric circulation patterns, with zonal circulation patterns dominating in the 19th and early 20th century, and meridional circulation patterns dominating thereafter (see also [30] and [31]).
In our research, we pick up where Keeling and Whorf [13, 14] leave off, insofar as documenting decadal and bidecadal oscillations in globally averaged temperature trends is concerned, but revert to the explanation proposed by Bell [16] and others [3, 18], that these are likely the result of a combined lunisolar influence, and not simply the result of lunar nodal and tidal influences. We show that decadal and bidecadal oscillations in globally averaged temperature show patterns of alternating weak and strong warming rates, and that these underwent a phase change around 1920. Prior to that time, the lunar influence dominates, while after that time the solar influence dominates. While these show signs of being correlated with the broad secular variation in atmospheric circulation patterns over time, the persistent influence of the lunar nodal cycle, even when the solar cycle dominates the warming rate cycles, implicates oceanic influences on secular trends in terrestrial climate. Moreover, while analyzing the behavior of the secular solar cycle over the limited time frame for which we have reasonably reliable instrumental data for measuring globally averaged temperature should proceed with caution, if the patterns documented here persist, we may be on the cusp of a downward trend in the secular solar cycle in which solar activity will be lower than what has been experienced during the last four double sunspot cycles. These findings could influence our expectations for the future regarding climate change and the issue of anthropogenic versus natural variability in attributing climate change.
In our original presentation, we utilized Hodrick-Prescott smoothing to reveal decadal and bidecadal temperature oscillations in globally averaged temperature trends. While originally developed in the field of economics to separate business cycles from long term secular trends in economic growth, the technique is applicable to the time series analysis of temperature data in reverse, by filtering out short term climate oscillations, isolating longer term variations in temperature.
For the mathematically inclined, here is what the HP filter equation looks like, courtesy of the Mathworks
The Hodrick-Prescott filter separates a time series yt into a trend component Tt and a cyclical component Ct such that yt = Tt + Ct. It is equivalent to a cubic spline smoother, with the smoothed portion in Tt.
The objective function for the filter has the form
where m is the number of samples and λ is the smoothing parameter. The programming problem is to minimize the objective over all T1, …, Tm. The first sum minimizes the difference between the time series and its trend component (which is its cyclical component). The second sum minimizes the second-order difference of the trend component (which is analogous to minimization of the second derivative of the trend component).
For those with an electrical engineering background, you could think of it much like a bandpass filter, which also has uses in meteorology:
Outside of electronics and signal processing, one example of the use of band-pass filters is in the atmospheric sciences. It is common to band-pass filter recent meteorological data with a period range of, for example, 3 to 10 days, so that only cyclones remain as fluctuations in the data fields.
(Note: For those that wish to try out the HP filter on data themselves, a freeware Excel plugin exists for it which you can download here)
When applied to globally averaged temperature, the HP filter works to extract the longer term trend from variations in temperature that are of short term duration. It is somewhat like a filter that filters out “noise,” but in this case the short term cyclical variations in the data are not noise, but are themselves oscillations of a shorter term that may have a basis in physical processes.
This approach reveals alternating cycles of weak and strong warming rates with decadal and bidecadal frequency. We confirm the validity of the technique using a continuous wavelet transform. Then, using MTM spectrum analysis, we analyze further the frequency of these oscillations in global temperature data. Using sinusoidal model analysis we show that the frequencies obtained using HP smoothing are equivalent to what are obtained using MTM spectrum analysis. In other words, the HP smoothing technique is simply another way of extracting the same spectral density information obtained using more conventional spectrum analysis, while leaving it in the time domain. This allows us to compare the secular pattern of temperature cycles with solar and lunar maxima, yielding results that are not obvious from spectral analysis alone.
Using the Hodrick-Prescott Filter to Reveal Oscillations in Globally Averaged Temperature
We use the open source econometric regression software gretl (GNU Regression, Econometrics, and Time Series) [34] to derive an HP filtered time series for the HadCRUT3 Monthly Global Temperature Anomaly, 1850:01 through 2008:11 [35].
Figure 1 is representative output in gretl for a series filtered with HP smoothing (λ of 129,000). In the top panel is the original series (in gray), with the resulting smoothed trend (in red). In the bottom panel is the cyclical component. In econometric analysis, attention usually focuses on the cyclical component. Our focus, though, is on the trend component in the upper panel, and in particular the first differences of the trend component. The first differences of a trend indicate rate of change.
By taking the first differences of the smoothed trend in Figure 1, we obtain the series (in blue) shown in Figure 2, plotted against the background of the original data (gray), and the smoothed trend (red).
What does this reveal? At first glance, we see an alternating pattern of decadal and bidecadal oscillations in the rate of warming, with a curious exception circa 1920-1930. We will return to this later. Concentrating for now on the general pattern, these oscillations in the rate of warming are representations, in the time domain, of spectral frequencies in the temperature data, with high frequency oscillations filtered out by the HP smoothing.
As evidence of this, Figure 3 presents the result of two Morelet continuous wavelet transforms, the first (in the upper panel) of the unfiltered HadCRUT3 monthly time series, and the second (in the lower panel) of results obtained with HP smoothing.
The wavelet transforms below a frequency of ~7 years (26.4 ≈ 84 months) are visually identical; the HP filter is simply acting as a low pass filter, filtering out oscillations with frequencies above ~7 years, while preserving the decadal and bidecadal oscillations of interest here. In the next section, we investigate these oscillations in further detail, supplementing our results from HP filtering with MTM spectrum analysis, and a sinusoidal model fit.
Frequency Analysis
Figure 4 is an MTM spectrum analysis of the unfiltered HadCRUT3 monthly global temperature analysis.
A feature of MTM spectrum analysis is that it distinguishes signals that are described as “harmonic” from those that are merely “quasi-oscillatory.” In MTM spectrum analysis a harmonic is a more clearly repeatable signal that passes a stronger statistical test of its repeatability. Quasi-oscillatory signals are statistically significant, in the sense of rising above the background noise level, but are not as consistently repeating as the harmonic signals.
The distinction between harmonic and quasi-oscillatory signals is well illustrated in Figure 4 by the two cycles that interest us the most – a “quasi-oscillatory” cycle with a peak at 8.98 years, and a “harmonic” signal centered at 21.33 years. Also shown are a harmonic, and a quasi-oscillatory cycle, of shorter frequencies, possibly ENSO related. The harmonic at 21.33 years in Figure 4 encompasses a range from 18.96 to 24.38 years, and the quasi-oscillatory signal that peaks at 8.93 years has sidebands above the 99% significance level that range from 8.53 to 10.04 years. These signals are consistent with spectra identified by Keeling and Whorf [13,14].
Figure 5 is an MTM spectrum analysis of the HP smoothed first differences.
The basic shape of the spectrum is unchanged, but it is now well above the background noise level because of the HP filtering. Attention is drawn in Figure 5 to four oscillatory modes or cycles because they correspond to the four strongest cycles derived from using the PAST (PAleontological STatistics) software [36] to fit a sinusoidal model to the HP smoothed first differences.
Shown in Figure 6, the sinusoidal fit results in periods of 20.68, 9.22, 15.07 and 54.56 years, in that order of significance. These periodicities fall within the ranges of the spectra obtained using MTM spectrum analysis, and yield a sinusoidal model with an R2 of 0.60.
Discussion
The first differences of the HP smoothed temperature series, shown in Figure 2 and Figure 6, show a pattern of alternating decadal and bidecadal oscillations in globally averaged temperature. From the sinusoidal model fit, these cycles have average frequencies of 20.68 and 9.22 years, results that are consistent with the MTM spectrum analysis, and with spectra in the results published by Keeling and Whorf [13, 14]. But to what can we attribute these persistent periodicities?
A bidecadal frequency of 20.68 years is too short to be attributed solely to the double sunspot cycle, and too long to be attributed solely to the 18.6 year lunar nodal cycle. There is indeed evidence of a spectral peak at ~15 years, which Keeling and Whorf combined with their evidence of a 21.7 year cycle to argue for attributing the oscillations entirely to the 18.6 year lunar nodal cycle.
But our evidence indicates that the ~15 year spectrum is much weaker, is not harmonic, and probably derives from the anomalous behavior of the spectra circa 1920-1930, something Keeling and Whorf could not appreciate with evidence only from the frequency domain. Especially in light of the evidence presented below, and because the bidecadal signal is harmonic, and readily discernible in the time domain representation of Figure 2 and Figure 6, we believe that a better attribution is the beat cycle explanation proposed by Bell [16], i.e. a cycle representing the combined influence of the 22 year double sunspot cycle and the 18.6 year lunar nodal cycle.
As for the decadal signal of 9.22 years, this is too short to be likely attributable to the 11 year solar cycle, but is very close to half the 18.6 year lunar nodal cycle, and thus may well be attributable to the lunar nodal cycle. Together, the pattern of alternating weak and strong warming cycles shown in Figure 2 and Figure 6 suggest a complex pattern of interaction between the double sunspot cycle and the lunar nodal cycle.
This complex pattern of interaction between the double sunspot cycle and lunar nodal maxima in relation to the alternating pattern of decadal and bidecadal warming rates is demonstrated further in Figure 6 with indicia plotted to indicate solar and lunar maxima. Since circa 1920, the strong warming rate cycles have tended to correlate with solar maxima associated with odd numbered solar cycles, and the weak warming rate cycles with lunar maxima.
Prior to 1920, the strong warming rate cycles tend to correlate with the lunar nodal cycle, with the weak warming rate cycles associated with even numbered solar cycles. The sinusoidal model fit begins to break down prior to 1870. Whether this is a reflection of the poorer quality of data prior to 1880, or indications of an earlier phase shift, we cannot say, though the timing would be roughly correct for the latter. But the anomalous pattern circa 1920, when viewed against the shift from strong warming rate cycles dominated by the lunar nodal cycle, to strong warming rate cycles dominated by the double sunspot cycle, has the appearance of a disturbance associated with what clearly seems to be a phase shift
These results agree with the evidence mustered by Hoyt and Schatten [28] and Georgieva, Kirov, and Bianchi [29] for a phase shift circa 1920 in the relationship between solar activity and terrestrial temperatures. However, we can suggest, here, that the supposed negative correlation between solar activity and terrestrial temperatures prior to 1920 rests on a misconstrued understanding of the data. As can be seen in Figure 6, the relationship between the change in the warming rate and solar activity is still positive, i.e. the warming rate is peaking near the peaks of solar cycles 10, 12, and 14, but at a much reduced level, indicative of the lower level of solar activity during the period. Indeed, for much of solar cycle 12, and all of solar cycle 14, the “warming” rate is negative, but the change in the warming rate is still following the level of solar activity, becoming less negative as solar activity increases, and more negative as solar activity decreases. Still, there is a strong suggestion in Figure 6 of a phase shift circa 1920 in which the relationship between solar activity and terrestrial temperatures changes dramatically before and after the shift. Before the shift, the lunar period dominates, and the solar period is much weaker. After the shift, the solar period dominates, and the lunar period becomes subordinate.
Speculating
To this point, we believe that we are on relatively solid ground in describing what the data show, and the likelihood of a lunisolar influence on global temperatures on decadal and bidecadal timescales. What follows now is more speculative. To what can we attribute the apparent phase shift circa 1920, evident not just in our findings, but as reported by Hoyt and Schatten [28] and Georgieva, Kirov, and Bianchi [29]? While the period of data is too short to do more than speculate, the periods before and after the phase shift appear to be roughly equivalent in length to the Gleissberg cycle.
Since 1920, we’ve had four double sunspot cycles with strong warming rates ending in odd numbered cycles. Prior to 1920, while the results are less certain at the beginning of the data period, there is a reasonable interpretation of the data in which we see four bidecadal periods dominated by the influence of the lunar cycle. These differences may be attributable to the broad swings in atmospheric “circulation epochs” discussed by Georgeiva, et al. [30], characterized either predominantly by zonal circulation, or meridional circulation. With respect to the period of time shown in Figure 6, zonal circulation prevailed prior to 1920, and since then meridional circulation has dominated. These “circulation epochs” may have persistent influence on the relative roles of solar and lunar influence in warming rate cycles.
While the role of variation in solar irradiation over the length of a solar cycle on the broad secular rise in global temperature is disputed, we are presenting here evidence primarily of a more subtle repeated oscillation in the rate of change in temperature, not its absolute level. As shown in Figure 2 and Figure 6, the rate of change oscillates between bounded positive and negative values (with the exception circa 1920 duly noted). Variations in solar irradiance over the course of the solar cycle are a reasonable candidate for the source of this variation in warming rate cycle. As WUWT’s “resident solar physicist”, Leif Svalgaard, has pointed out, variations in TSI over a normal solar cycle can only account for about 0.07°C of total variation over the course of a solar cycle. The range of change in warming rates shown in Figure 2 and Figure 6 are at most only about one-tenth of this, or about ~0.006°C to ~0.008°C. If anything, we should be curious why the variation is so small. We attribute this to the averaging of regional and hemispheric variations in the globally averaged data. On a regional basis, analysis [not presented here] shows much larger variation, but still within the range of 0.07°C that might plausibly be attributed to the variation in TSI over the course of a solar cycle.
So variations in solar irradiance over the course of the solar cycle are a reasonable candidate for the source of this variation in warming rate cycle. At the same time, the lunar nodal cycle may be further modulating this natural cycle in the rate of change in global temperatures. As to the degree of modulation, that may be influenced by atmospheric circulation patterns. With zonal circulation, the solar influence is moderated and the lunar influence dominates the modulation of the warming rate cycles. With meridional circulation, the solar influence is stronger, and the warming rate cycles are dominated by the solar influence.
At this writing, we are in the transition from solar cycle 23 to 24, a transition that has taken longer than expected, and longer than the transitions typical of solar cycles 16 through 23. Indeed, the transition is more typical of the transitions of solar cycles 10 through 15. If the patterns observed in Figure 6 are not happenstance, we may be seeing an end to the strong solar activity of solar cycles 16-23, and a reversion to the weaker levels of activity associated with solar cycles 10-15. If that occurs, then we should see a breakdown in the correlation between warming rate cycles and solar cycles at bidecadal frequencies, and a reversion to a dominant correlation between temperature oscillations and the lunar nodal cycle.
Interestingly, there was a lunar nodal maximum in 2006 not closely associated with the timing of decadal or bidecadal oscillations in globally averaged temperature. This could be an indication of a breakdown in the pattern similar to what we see in the 1920’s, i.e. the noise associated with a phase shift in the weaker warming rate cycles will occur at times of the solar maximum, and the stronger warming rate cycles will occur at times of lunar nodal maximum.
Repeating, there appear to be parallels between our findings and the argument of Georgieva et al. [29] of a relationship between terrestrial climate and solar hemispheric asymmetry on the scale of a double Gleissberg cycle. Solar cycles 16-23, associated as we have seen with increased solar activity, and strong correlations with the strong terrestrial warming rate cycles of bidecadal frequency, represent 8 solar cycles, a period of time associated with a Gleissberg cycle.
While the existence of Gleissberg length cycles is hardly challenged, their exact length and timing is subject to a debate we will not entertain here at any length. Javariah [37] on the basis of the disputed 179 year cycle of Jose [38] believes that a descending phase of a Gleissberg cycle is already underway, and will end with the end of a double Hale cycle comprising solar cycles 22-25.
While it is true that solar activity, as measured by SSN, is already on the decline, we would include the double Hale cycle 20-23 in the recent peak of solar activity, and not necessarily expect to see the bottom of the current decline in solar activity that quickly.
The issue here can perhaps be framed with respect to Figure 7 below:
Assuming we are on the cusp of a downward trend in solar activity that began circa 1990 according to Javariah, and will decline, say, to a level comparable to the trough seen in the early 1900’s, will it be a sharp decline, like that seen at the beginning of the 19th Century, or a more moderate decline like that seen at the beginning of the 20th Century? A naïve extrapolation might be to replicate the more gradual decline seen during the latter half of the 19th Century, suggesting a gradual decline in solar activity through solar cycle 31, i.e. for most of the 21st Century. And based on the prospect of a phase shift in the pattern of decadal and bidecadal warming rate cycles, the bidecadal cycle would come to be dominated by the influence of the lunar nodal cycle, and the influence of the solar cycle would be diminished, leading at least to a reduction in the rate of global warming, if not an era of global cooling.
This is a prospect worthy of more investigation.
Finally, while we readily concede that multidecadal projections are at best little more than gross speculation, in Figure 6 we have carried the sinusoidal model fit out to 2030, and in Figure 8 we use the sinusoidal model of rate changes to project temperature
anomalies through 2030. Assuming a simple projection of the sinusoidal model of rate changes persists through 2030, there would be little or no significant change in global temperature anomalies for the next two decades.
Looking carefully at the sinusoidal model, what we are seeing projected for 2010-2020 are a return to conditions similar to what the model shows for circa 1850-1860, with the period 1853-2020 representing a complete composite cycle of the four combined periods of oscillation. That is, 1853 is the first point at which the sinusoidal model is crossing the x-axis, and at 2020 the model again crossing the x-axis and beginning to repeat a ~167 year cycle. In terms of solar cycle history, that corresponds to a return to conditions similar to solar cycles 10-15, with another phase shift reversing the phase shift of ~1920. If these broad, long term secular swings in solar activity and global atmospheric conditions and temperature anomalies are not random, but reflect solar-terrestrial dynamics that play out over multidecadal and even centennial time-scales, then the early 21st Century may yield a respite from the global warming of the late 20th Century.
Conclusion
There is substantial and statistically significant evidence for decadal and bidecadal oscillations in globally averaged temperature trends. Sinusoidal model analysis of the first differences of the HP smoothed HadCRUT3 time series reveals strong periodicities at 248.2 and 110.7 months, periodicities confirmed as well with MTM spectrum analysis.
Analyzing these periodicities in the time domain with the first differences of the HP smoothed HadCRUT3 time series reveals a pattern of correlation between strong warming rate cycles and the double sunspot cycle for the past four double sunspot cycles. Prior to that, with a phase shift circa 1920, the strong warming rate cycles were dominated by the timing of the lunar nodal cycle.
We suggest that this reversal may be related to a weaker epoch of solar activity prior to 1920, and that we may on the cusp of another phase shift associated with a resumption of such weakened solar activity.
If so, this may result in a reduction in the rate of global warming, and possibly a period of global cooling, further complicating the effort to attribute recent global warming to anthropogenic sources.
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[37] Javariah, J. Sun’s retrograde motion and violation of even-odd cycle rule in sunspot activity. 2005; 362(4): 1311-1318.
[38] Jose, P. Sun’s motion and sunspots. Astronics Journal. 1965; 70: 193-200.
Erl Happ (10:12:29) :
Summarise in one paragraph
Slashing away the fluff here is what remains:
As temperature falls in the tropical stratosphere, more ozone drifts down into the lower stratosphere and upper troposphere, warming occurs, ice cloud density is affected and the sea warms in response to enhanced solar radiation.
I didn’t see any reference to mechanisms or physics in the rest. If you can find any, add it to the above and we’ll go from there.
Today I have time only for the briefest of clarifications, rather than a debate.
To oms: There’s no disagreement here on the potential for momentum transfer by wave groups to mass flows generated by other mechanisms. Indeed, the nonlinear effect of what is widely termed “radiation stress” in gravity wave studies is the generation of a “wave drift” in the direction of propagation, wherein the particle wave orbit is no longer closed. Flotsam carried onto a beach by breaking waves provides the most commonly observed strong example. With non-breaking waves the effect is very much weaker. What disagreement there is stems from your assumption that it was I that was positing the notion of this being a primary heat transfer mechanism. That dubiuos honor belongs to someone else.
To Leif: Radiation stress refers to the “wave drift” of gravity waves, not to thermal radiation (see above). Air carrying heat and moisture aloft is usually called moist convection, rather than upward wave propagation.
To Basil: I don’t wish to discourage you from investigating the periodic lunar nodes, but the evidence so far is virtually nonexistent, the mere coincidence of the presumed fourth harmonic found at 4.5 years notwithstanding. Two suggestions come to mind. 1) Truncate the temperature record to match the nearest integer mutiple of the lunar mode cycle and perform a bare bones DFT analysis to see what harmonics really stand out. 2) Look for relationships between temperature and sunspot records at the lowest frequencies (below the Hale) that seem to modulate the latter. That’s where spectrum analysis shows the most power in the temperature record.
John S. (12:16:18) :
To Leif: Radiation stress refers to the “wave drift” of gravity waves, not to thermal radiation (see above).
A good example of different jargon. To ‘radiate’ can, of course, also just mean to propagate in a certain direction. It is, in such interdisciplinary discussions, so important to stay away from narrow ‘lingoism’. Admittedly, that is hard at times.
How easily subtopics get muddled on a blog!
Re: Leif Svalgaard (11:46:47) :
I brought up the example as a reply to bill (08:30:07) to illustrate how a tuned oscillator (electrical or otherwise) can be excited at its first subharmonic frequency. The behavior only depends on the fact of modulating a parameter in the differential equation for the oscillator.
In the solar cycle example, there is no need for the 22 y subharmonic to be created on the Sun. If the 11-yr cycle affects the earth through some arbitrary mechanism, then at least in principle the black box 11-yr oscillator can be excited at second order at a 22-yr period.
On the other hand, if the 11-yr cycle has no detectable effect on the earth system, then we probably shouldn’t be looking too hard for its 22-yr subharmonic.
John S. (12:16:18) :
I also assumed you were referring to the Reynolds stresses. The “primary heat transfer mechanism” argument seems to be a misunderstanding or confusion with someone else (although your Stokes drift example CAN lead to some interesting fluxes).
Leif Svalgaard (13:14:59) :
Agreed. We also have to navigate the ‘lingoscape’ in citations keeping in mind the fields in which they were published!
oms:
OK I give in. I can in no way use a simulator to generate subharmonics! Tried modulating the capacitance of a tuned circuit at 2x its fundamental. Tried introducing energy via diode etc, etc. but no fundamental build up.
a free cct simulator:
http://www.linear.com/designtools/software/ltspice.jsp
Jim Powell (19:45:12) “Leif, the man has a doctorate in his field and does an extensive mathematical analysis. Chill out.” / Leif Svalgaard (20:26:12) “Whom are you referring to?”
I believe Jim was referring to Harald Yndestad.
– –
Pamela Gray (07:10:06) “Leif, thank you thank you for the link on the QBO. I downloaded the paper and will be reading it […] “
Pamela, can you clarify which link (of the many links Leif has provided) impressed you so much?
Was it this one? …
M. Ern and P. Preusse (2009). Wave fluxes of equatorial Kelvin waves and QBO zonal wind forcing derived from SABER and ECMWF temperature space-time spectra. Atmospheric Chemistry and Physics Discussions 9, 5623-5677.
http://www.atmos-chem-phys-discuss.net/9/5623/2009/acpd-9-5623-2009.pdf
http://www.atmos-chem-phys-discuss.net/9/5623/2009/acpd-9-5623-2009-print.pdf
– –
Erl Happ (09:23:55) “At http://en.wikipedia.org/wiki/File:Mslp-jja-djf.png
you will see global maps of sea level pressure. Would you care to speculate why pressure is so much lower in the high latitude Southern Ocean and Antarctica than it is in the Arctic or over Siberia?
Do I see part of the answer in a link provided by Leif? …
Timothy E. Dowling (2008). Music of the stratospheres. Nature 453, 163-164.
http://www.nature.com/nature/journal/v453/n7192/full/453163a.html
http://www.nature.com/nature/journal/v453/n7192/pdf/453163a.pdf
“[…] semiannual oscillation (SAO) […] Earth’s SAO is driven by the different response to surface heating between the ice of Antarctica and the surrounding ocean […] The influence of the QBO and SAO on Earth’s weather cannot be overstated. They modulate seasonal activity, […], the strength of the polar vortex, the mixing of atmospheric trace species, […]. Because the portfolio of eastward waves is distinct from that of westward waves, the eastward and westward phases of the QBO are different. The big news is that this asymmetrical, long-period response has now been observed in the stratospheres of three planets.” / “Fifteen-year oscillations in Saturn’s equatorial stratosphere bear a striking resemblance to the shorter-term oscillations seen on Earth and Jupiter — akin to notes played on a cello, a violin and a viola.”
Paul Vaughan (16:52:58) :
“Do I see part of the answer in a link provided by Leif? …”
Yes, no doubt about it at all. Especially: “they modulate seasonal activity, […], the strength of the polar vortex, the mixing of atmospheric trace species, ”
But the big issue is what initiates all this. Is it planetary waves driven by convectional and topographical influences and god knows what (all very mysterious), or is it the sun via change in irradiance and geomagnetic activity influencing the strength of the vortex and thereby the mixing of trace species that erode ozone…….the species that ‘cool the atmosphere’ to use Thayer’s terminology.
Observing the variation in high latitude temperature since 1948 I would say we are on a descent that began about 1983 and the cycle appears to be about 100 years in length. I don’t see internal variability modes as capable of producing that. It’s more likely related to the interplanetary magnetic field. In other words tropical warming episodes vary in strength over very long time scales.
Leif,
I did not avoid your suggestion as you can see. But there is a time lag introduced by the moderation process. Your request appeared as I posted a comment, and it appeared above the comment looking as if I had ignored the request. Not so, as you see.
The first phenomena that you choose to cut out as ‘fluff’ pertains to the connection between ozone concentration in the stratosphere and solar activity. This may suit you but not me. There is plenty of literature supporting this connection including this talk:http://physics.oulu.fi/toiminta/kollokviot/2008-04-10_rodger.pdf, this symposia:http://envisat.esa.int/workshops/envisatsymposium/sessions/15b.htm
This paper: http://nora.nerc.ac.uk/5936/1/Luetal_2006JD007864_JGR_NORA.pdf
Here: http://www.cosis.net/abstracts/COSPAR02/01724/COSPAR02-A-01724.pdf
and most recently supporting the notion that the influence is continuous and very influential in determining mass density and trace gas variations on all time scales at: http://www.agu.org/pubs/crossref/2008/2008GL035745.shtml The Implications are elaborated in a talk that appears here:http://www.aero.org/conferences/itmr/2009proceedings.html
Lots of fluff around the place.
I must confess to be learning as I go along and some of the stuff I write I would modify or eliminate today but here is my non peer reviewed point of view: http://climatechange1.wordpress.com/2009/04/05/solar-warming-solar-cooling/ and also: http://climatechange1.wordpress.com/2009/03/08/the-atmosphere-dancing-in-the-solar-wind-el-nino-shows-his-face/
There is also the question of how the variability that is observed relates to the direction of climate change in the recent past and what is to be expected. Cut it out and much of the purpose of the exercise disappears. Hardly fluff I would think.
I would regard the stuff that you retain as non controversial. The linkages can readily be supported by observation of atmospheric and sea surface temperature.
Here is an example from recent literature where others notice the terrestrial linkages observed: http://www.atmos-chem-phys-discuss.net/9/12141/2009/acpd-9-12141-2009.html
Unfortunately, the writers have the thing upside down. It is presented as a “teleconnection” of ENSO as if ENSO was the driver. The input driving the system is solar as the references cited above amply demonstrate. As long as the prevailing orthodoxy can maintain that ENSO is an internal oscillation of the climate system no progress will be made in understanding the sources of solar driven climate change. You are very much a part of that orthodoxy.
Your use of the word ‘fluff’ to describe elements of what I wrote provokes the following observation. “There are none so blind as those who will not see.”
Leif,
I did not avoid your suggestion as you can see. But there is a time lag introduced by the moderation process. Your request appeared as I posted a comment, and it appeared above the comment looking as if I had ignored the request. Not so, as you see.
The first phenomena that you choose to cut out as ‘fluff’ pertains to the connection between ozone concentration in the stratosphere and solar activity. This may suit you but not me. There is plenty of literature supporting this connection including this talk:http://physics.oulu.fi/toiminta/kollokviot/2008-04-10_rodger.pdf, this symposia:http://envisat.esa.int/workshops/envisatsymposium/sessions/15b.htm
This paper: http://nora.nerc.ac.uk/5936/1/Luetal_2006JD007864_JGR_NORA.pdf
Here: http://www.cosis.net/abstracts/COSPAR02/01724/COSPAR02-A-01724.pdf
and most recently supporting the notion that the influence is continuous and very influential in determining mass density variations on all time scales at: http://www.agu.org/pubs/crossref/2008/2008GL035745.shtml The Implications are further explained in a talk that appears here:http://www.aero.org/conferences/itmr/2009proceedings.html
I must confess to be learning as I go along and some of the stuff I write I would modify today but here is my point of view: http://climatechange1.wordpress.com/2009/04/05/solar-warming-solar-cooling/ and also: http://climatechange1.wordpress.com/2009/03/08/the-atmosphere-dancing-in-the-solar-wind-el-nino-shows-his-face/
There is also the question of how the variability that is observed relates to the direction of climate change to be expected. Cut it out and much of the purpose of the exercise disappears. Not fluff at all.
I would regard the stuff that you retain as non controversial. The linkages can readily be supported by observation of atmospheric and sea surface temperature.
Here is an example from recent literature where others notice the terrestrial linkages observed: http://www.atmos-chem-phys-discuss.net/9/12141/2009/acpd-9-12141-2009.html
Unfortunately, the writers have the thing upside down. It is presented as a “teleconnection” of ENSO as if ENSO was the driver. The input driving the system is solar as the references cited above amply demonstrate. As long as the prevailing orthodoxy can maintain that ENSO is an internal oscillation of the climate system no progress will be made in understanding the sources of solar driven climate change. You are very much a part of that orthodoxy.
Your use of the word ‘fluff’ to describe elements of what I wrote provokes the following observation that I see as fair under the circumstances: “There are none so blind as those who will not see.”
Erl Happ (10:12:29) :
What I call ‘fluff’ starts out with this:
The solar wind and irradiance are jointly influential in changing the distribution of the mass of the atmosphere between the winter pole and the equator influencing the strength of the winter vortex, polar atmospheric temperature at all levels, the ozone content of the stratosphere and the height of the zone of ozone creation in the tropical stratosphere.
This is not a mechanism or physics, but a just a statement of what you believe and as such is fluff compared to the following statement that has some connection with a mechanism. Similarly for the stuff following that one statement.
erlhapp (19:03:47) :
As long as the prevailing orthodoxy can maintain that ENSO is an internal oscillation of the climate system no progress will be made in understanding the sources of solar driven climate change.
Perhaps there is no progress to be made if [or because] the sun is not a major driver in the first place. To overcome orthodoxy [also known as well documented and generally accepted knowledge by knowledgeable people as ‘science’] you need to have very strong and compelling arguments and evidence. If and when you have that, orthodox science changes on a dime [plate tectonics, dark energy, general relativity, quantum mechanics are examples of complete paradigm changes that only took a few years to play out]. If your arguments and evidence are weak or unphysical the idea will struggle for centuries without ‘progress’, as the solar/climate ‘connexion’ so clearly demonstrates.
bill (15:21:53) :
Hm that’s curious. How did you configure the circuit and how did you handle the modulation of the capacitor?
Thanks for the simulator link. I might give it a try too!
Leif Svalgaard (21:48:03) : …
No. Plate tectonics – and every other advance in fundemental science! – was rigorously, dogmatically, almost religiously opposed by conventional wisdom for decades. BY the very people sho dominated teh field.
The “change” – Looooong after he died! – came about ONLY when another “outside expert” was able to use NEW technology (undersea sonar surveys) to plot the ridges and slopes underwater. Conventional geologist were dragged kisking and screaming to the theory – definitely not “on a dime” in peer-reviewed literature.
Cite any fundamental change in science that happened from within the field, going all the way back to Tycho and Copernicus: The “experts” (by definition!) in each field have been proven wrong by the very nature of theat “fundamental change”. And no “inside expert” ever predicted nor promoted the changes that affected his or her own field .
At best, we can accept that the university-approach of plodding and conventional analysis paid by years of re-analysis of “conventional wisdom” validates (engineering-level approximations) of conventional theory.
Leif Svalgaard (21:48:03) :
In truth, what we are looking at is not fundamental theory yet, but a pattern. And potential – but very important – subtle data BEHIND and between the observed pattern.
For example, using your earlier example of continental drift, we have observed the coast lines of the Eastern US seaboard, Weste Europe, West Africa, and East side of south America. They “sort of” match – but we are looking at data that (may OR may not) reveal the underwater continental shelves (which DO closely match – but cannot say WHY the plates move nor HOW they “float” on a not-yet-discovered mantle.
We have not (yet) found equivilent traces of the Atlantic ridge, the near-continuous earthquakes there, spreading magma layers, and increasing deposits of underway dirt on ever-older layers of spreading seabed. WE DON’T KNOW WHAT TO LOOK FOR YET with respect to climate change over periods of centuries. (Over tens of centuries, orbit changes seem to dominate.) Sorry, but we cannot give you a 200 word summary – though I’d really like to! – just as he could not theorize the “why” of mantle and crustal movements in 1924. Nor of mountain and underwater canyon relationships. Yet.
But, please note that “something” is continuously twisting the PDO and other ocean-dominated oscillations every 35 some-odd years. There might be something INSIDE the sun’s circulating current and magnetic patterns doing it – where the sun changes the earth’s received radiation … something else happens over differing decal-long cycles and heat sinks -> something else changes the air and currents.
Don’t know yet.
Fundamentally, ALL of the climate reactions must go back to the original equations as you indicated above. Right now, no group of equations can explain the not-quite-random-but-not-regular cycles we are getting. The system is too large, too chaotic.
Or we must accept “…and (sometimes) miracles occur. And (sometimes) they don’t occur.” That method has also been used to explain everything in the past.
8<)
Robert A Cook PE (12:31:53) :
No. Plate tectonics – and every other advance in fundemental science! – was rigorously, dogmatically, almost religiously opposed by conventional wisdom for decades. […]
The “change” – Looooong after he died! – came about ONLY when another “outside expert” was able to use NEW technology (undersea sonar surveys) to plot the ridges and slopes underwater.
I’ll have to say ‘No’ to your ‘No’. What was opposed was ‘Continental Drift’ [which would still, rightly, be opposed today], namely the notion that the continents plow through the ocean floors. Once the correct notion, sea floor spreading, was found, conversion was swift. The same with all the other examples. There is, of course, some truths to the notion that progress happens because old scientists die.
“but we cannot give you a 200 word summary “
Except that I asked one of those who professes to KNOW, one that has the will ‘to see’.
In the end, we have to go by what we find, demonstrate, and therefore, in a sense, ‘know’, rather than hypothesizing that it could be this or that or whatnot, if we could only figure out how this or that or whatnot does what we so fervently want this or that or whatnot to do.
bill (15:21:53):
Spare yourself more frustration. Linear systems NEVER exhibit harmonic or subharmonic response, no matter how one sets up the paramters. Such response is the exclusive province of nonlinear systems, particularly those exhibiting chaotic behavior. The response of some chaotic systems can even be primarily subharmonic.
Looks like this thread is dead, aside from the interminable debate. Adios, amigos!
John S. (18:13:20) :
If his simulator is allowing him to modulate the capacitance in a time-dependent fashion, isn’t that different from a linear system?
John S. (18:13:20) :
Not dead John. The interminable debate helps to highlight the issues. For me, its back to the historical data, to trace the change in the parameters that influence atmospheric circulation, cloud cover and albedo. There is plenty to keep me busy in the historical record.
The present state of our understanding of ‘natural’ climate change is indicated by the lack of agreement in the models that predict ENSO events.
Some of these models reputedly take note of tropical stratospheric temperature. Some take note of the state of the polar vortexes. None, so far as I know attempt to incorporate planetary wave activity.
Most are currently predicting an El Nino event. The fact that none predicted the now receding La Nina we can forget for the moment. Are they right now? This is the puzzle.
erlhapp (20:39:42) “The interminable debate helps to highlight the issues.”
Agreed.
–
erlhapp (20:39:42) “For me, its back to the historical data, to trace the change in the parameters that influence atmospheric circulation, cloud cover and albedo.”
I’ll be interested to hear your insights in the days ahead.
Question:
Does anyone construct global dayside-nightside temperature-contrast time series?
–
erlhapp (20:39:42) “The present state of our understanding of ‘natural’ climate change is indicated by the lack of agreement in the models that predict ENSO events.”
Well-said.
erlhapp (20:39:42) :
Why wouldn’t a GCM, which includes both fluid flow and vorticity, automatically incorporate Rossby waves?
“The above from the source quoted. Nothing about photon count, dividing into IR, visible, UV, etc. Nothing about “TSI may be converted to ‘total energy’ assuming a spectral contribution of discrete wavelengths”. TSI simply measures the total radiation of all wavelengths. Who are you trying to fool this time?”
Sorry, Leif, I have not had time to return until now. The four sensors, the radiometers, are those assigned to the categories I noted as their site describes in the data sheets, e.g., sigma for the UV sensor is 12-24%.
Putting the principles into less technical English so that anyone can understand is a boon not an imprecision. Look up ‘irradiance’. Your “scientists'” use of ‘energy’ is an imprecise use of the term.
gary gulrud (23:51:05) :
Sorry, Leif, I have not had time to return until now. The four sensors, the radiometers, are those assigned to the categories I noted as their site describes in the data sheets, e.g., sigma for the UV sensor is 12-24%.
You must be looking at something else. Perhaps provide a link to what you think are the data sheets. The four radiometers measure the same thing and are multiple to provide redundancy and degradation measurements, and are not measuring different pieces of the spectrum.
Putting the principles into less technical English so that anyone can understand is a boon not an imprecision. Look up ‘irradiance’. Your “scientists’” use of ‘energy’ is an imprecise use of the term.
To refresh your memory of who used ‘energy’:
gary gulrud (10:41:24) :
TSI is measured via a photon count. TSI may be converted to ‘total energy’ assuming a spectral contribution of discrete wavelengths.
There is usually no confusion [unless deliberate] between power and energy [the latter simply power integrated in time over area]
oms (23:39:16) :
“Why wouldn’t a GCM, which includes both fluid flow and vorticity, automatically incorporate Rossby waves?”
Beyond my knowledge. I do know however that GCM’s can not predict ENSO events so if they do include waves its not helping them get the right answer.
Paul Vaughan (21:19:21) :
Does anyone construct global dayside-nightside temperature-contrast time series?
Paul, most of the data I see is aggregated to monthly values. I then calculate a running 12 month average so as to smooth out seasonal effects.
Daily data is hard to get and hourly data even harder, and the period only very recent. But airports have it. I imagine that you would have to compile it station by station. The NOAA is compiling data from round the world and doing an excellent job of making it available quite cheaply.
“I’ll be interested to hear your insights in the days ahead.”
What an invitation?
Sea surface temperature variation coincides with 200hPa temperature variation.
The main driver of 200hPa temperature change is ozone content.
When the pole warms the sea warms at 20-40° latitude in the summer hemisphere. It may also coincidentally warm near the equator but frequently the warming begins in the Pacific off Chile at 20-40°S and this leads Nino 1+2 and the entire equatorial region.
I imagine that 20hPa temperature reflects ozone content. Peaks in 20hPa temperature between 10°N and 10°S can be seen to order peaks in 200hPa temperature between 10° and 40° of the equator in both the north and the south with a slight lag in the northern hemisphere on about half the occasions. After 1990 and prior to 1960 there is a lag of up to a year in the peak of 200hPa temperature between the equator and 20° latitude due to the time it takes for water that is warmed between 20° and 40° to feed into the equatorial region but between 1960 and 1990 there is coincidence.
The rise in sea surface temperature after 1978 was much greater between 20-40°S than closer to the equator. Monitoring SST in the ENSO 3.4 region is a complete waste of time. The action is elsewhere.
20hPa temperature over the equator is currently approaching minimum. Over the last 20 years SST at 20°N to 20°S has peaked when 20hPa temperature over the equator reaches its minimum. So, on that basis, the current warming should be brief. However, a swift increase in solar irradiance and geomagnetic activity might reduce that lag. There is strong warming happening off California, the atmosphere is pretty well wrung out by the La Nina and the rise in temperature in mid year should be strong.
Here is a longer perspective. As the tropical ocean continues to cool 20hPa temperature over the equator will climb due to reduced transport of water vapour into the stratosphere and the gyrations in 20hPa temperature will increase in amplitude. That will give rise to greater variation in 200hPa and sea surface temperature. However, the ocean will cool like it did in the 1970’s with ever stronger cooling events. The tendency to extreme El Nino warming events will continue to diminish. Sea surface atmospheric pressure off Chile began to rise in 1978 as it did over Antarctica and after 1990 atmospheric pressure began to rise in the Arctic. There is no sign of those trends reversing.
If the solar influence that drives the the strength of the winter vortex and ultimately the ozone content of the stratosphere continues to weaken then the vortex will strengthen, the stratosphere will cool at mid to high latitudes and warm at low latitudes. Surface temperatures will fall at high latitudes as the supply of warm water from the tropics becomes less warm.
“You must be looking at something else.”
The SORCE site.
“To refresh your memory of who used ‘energy’”
nearly all photon energy incident on the detector is converted into heat
Obviously, if their TIM detector were responsible for their accuracy to six(or thereabouts) decimal places and TSI units were joules per area there would be no need but backward compatibility to offer Watts/m^2.
I can believe they accurately measure radiation pressure not energy. I’ve seen estimates for UV energy down 12%, and solar faculae are responsible for upper visible region as well. The description of function is not rigorous.