NEW An update to this has been made here:
Part II
By Basil Copeland and Anthony Watts
In Part I, we presented evidence of a noticeable periodicity in globally averaged temperatures when filtered with Hodrick-Prescott smoothing. Using a default value of lambda of 100, we saw a bidecadal pattern in the rate of change in the smoothed temperature series that appears closely related to 22 year Hale solar cycles. There was also evidence of a longer climate cycle of ~66 years, or three Hale solar cycles, corresponding to slightly higher peaks of cycles 11 to 17 and 17 to 23 shown in Figure 4B. But how much of this is attributable to value of lambda (λ). Here is where lambda (λ) is used in the Hodrick-Prescott filter equation:
The first term of the equation is the sum of the squared deviations dt = yt − τt which penalizes the cyclical component. The second term is a multiple λ of the sum of the squares of the trend component’s second differences. This second term penalizes variations in the growth rate of the trend component. The larger the value of λ, the higher is the penalty.
For the layman reader, this equation is much like a tunable bandpass filter used in radio communications, where lambda (λ) is the tuning knob used to determine the what band of frequencies are passed and which are excluded. The low frequency component of the HadCRUT surface data (the multidecadal trend) looks almost like a DC signal with a complex AC wave superimposed on it. Tuning the waves with a period we wish to see is the basis for use of this filter in this excercise.
Given an appropriately chosen, positive value of λ, the low frequency trend component will minimize. This can be seen in Figure 2 presented in part I, where the value of lambda was set to 100.
Figure 2 – click for a larger image
A lower value of lambda would result in much less smoothing. To test the sensitivity of the findings reported in Part I, we refiltered with a lambda of 7. The results are shown in Figures 3 and 4.
Figure 3 – click for a larger image
As expected, the smoothed trend line, represented by the blue line in the upper panel of Figure 3, is no longer as smooth as the trend in the upper panel of Figure 1 from Part I. And when we look at the first differences of the less smoothed trend line, shown in Figure 4, they too are no longer as smooth as in Figure 2 from Part I. Nevertheless, in Figure 4, the correlation to the 22 year Hale cycle peaks is still there, and we can now see the 11 year Schwabe cycle as well.
Figure 4 – click for a larger image
The strong degree of correspondence between the solar cycle peaks and the peak rate of change in the smoothed temperature trend from HadCRUT surface temperature data is seen in Figure 5.
Figure 5 – click for a larger image
The pattern in Figure 4, while not as eye-catching, perhaps, as the pattern in Figure 2 is still quite revealing. There is a notable tendency for amplitude of the peak rate of change to alternate between even and odd numbered solar cycles, being higher with the odd numbered solar cycles, and lower in even numbered cycles. This is consistent with a known feature of the Hale cycle in which the 22 year cycle is composed of alternating 11 year phases, referred to as parallel and antiparallel phases, with transitions occurring near solar peaks.
Even cycles lead to an open heliosphere where GCR reaches the earth more easily. Mavromichalaki, et. al. (1997), and Orgutsov, et al. (2003) contend that during solar cycles with positive polarity, the GCR flux is doubled. This strongly implicates Galactic Cosmic Ray (GCR) flux in modulating global temperature trends. The lower peak amplitudes for even solar cycles and the higher peak amplitudes for odd solar cycles shown in Figure 4 appears to directly confirm the kind of influence on terrestrial climate postulated by Svensmark in Influence of Cosmic Rays on Earth’s Climate (1998)From the pattern indicated in Figure 4, the implication is that the “warming” of the late 20th century was not so much warming as it was less cooling than in each preceding solar cycle, perhaps relating to the rise in geomagnetic activity.
It is thus notable that at the end of the chart, the rate of change after the peak associated with solar cycle 23 is already in the negative range, and is below the troughs of the preceding two solar cycles. Again, it is purely speculative at this point, but the implication is that the underlying rate of change in globally averaged temperature trends is moderating, and that the core rate of change has turned negative.It is important to understand that the smoothed series, and the implied rates of change from the first differences, in figures 2 and 4, even if they could be projected, are not indications of what the global temperature trend will be.
There is a cyclical component to the change in global temperature that will impose itself over the underlying trend. The cyclical component is probably dominated by terrestrial dynamics, while the smoothed series seems to be evidence of a solar connection. So it is possible for the underlying trend to be declining, or even negative, while actual global temperature increases because of positive cyclical factors. But by design, there is no trend in the cyclical component, so that over time, if the trends indicated in Figures 2 and 4 hold, global warming will moderate, and we may be entering a phase of global cooling.
Some are probably wondering which view of the historical correspondence between globally averaged temperatures and solar cycles is the “correct” one: Figure 2 or 4?
Such a question misconstrues the role of lambda in filtering the data. Here lambda is somewhat like the magnification factor “X” in a telescope or microscope. A low lambda (less smoothing) allows us to “focus in” on the data, and see something we might miss with a high lambda (more smoothing). A high lambda, precisely because it filters out more, is like a macroscopic view which by filtering out lower level patterns in the data, reveals larger, longer lived processes more clearly. Both approaches yield valuable insights. In Figure 2, we don’t see the influence of the Schwabe cycle, just the Hale cycle. In Figure 4, were it not for what we see in Figure 2, we’d probably miss some similarities between solar cycles 15, 16, and 17 and solar cycles 21, 22, and 23.In either case, we are seeing strong evidence of a solar imprint in the globally averaged temperature trend, when filtered to remove short term periodicities, and then differenced to reveal secular trends in the rate of change in the underlying long term tend in globally averaged temperatures.
At one level we see clear evidence of bidecadal oscillations associated with the Hale cycle, and which appear to corroborate the role of GCR’s in modulating terrestrial climate. At the other, in figure 4B, we see a longer periodicity on the order of 60 to 70 years, correspondingly closely to three bidecadal oscillations. If this longer pattern holds, we have just come out of the peak of the longer cycle, and can expect globally average temperature trends to moderate, and increased likelihood of a cooling phase similar that experienced during the mid 20th century.
In Lockwood and Fröhlich 2007 they state: “Our results show that the observed rapid rise in global mean temperatures seen after 1985 cannot be ascribed to solar variability, whichever of the mechanisms is invoked and no matter how much the solar variation is amplified.” . Yet, as Figure 5 demonstrates, there is a strong correlation between the solar cycle peaks and the peak rate of change in the smoothed surface temperature trend.
The periodicity revealed in the data, along with the strong correlation of solar cycles to HadCRUT surface data, suggests that the rapid increase in globally averaged temperatures in the second half of 20th century was not unusual, but part of a ~66 year climate cycle that has a long history of influencing terrestrial climate. While the longer cycle itself may be strongly influenced by long term oceanic oscillations, it is ultimately related to bidecadal oscillations that have an origin in impact of solar activity on terrestrial climate.
We are continuing to look at different methods of demonstrating a correlation. Please watch for future posts on the subject.
NEW An update to this has been made here:
References:
Demetrescu, C., and V. Dobrica (2008), Signature of Hale and Gleissberg solar cycles in the geomagnetic activity, Journal of Geophysical Research, 113, A02103, doi:10.1029/2007JA012570.
Hadley Climate Research Unit Temperature (HadCRUT) monthly averaged global temperature data set (description of columns here)
J. Javaraiah, Indian Institute of Astrophysics, 22 Year Periodicity in the Solar Differential Rotation, Journal of Astrophysics and Astronomy. (2000) 21, 167-170
Katsakina, et al., On periodicities in long term climatic variations near 68° N, 30° E, Advances in Geoscience, August 7, 2007
Kim, Hyeongwoo, Auburn University, “Hodrick-Prescott Filter” March 12, 2004
M. Lockwood and C. Fröhlich, Recent oppositely directed trends in solar climate forcings and the global mean surface air temperature, Proceedings of the Royal Society of Astronomy doi:10.1098/rspa.2007.1880; 2007, 10th July
Mavromichalaki, et. al. 1997 Simulated effects at neutron monitor energies: evidence for a 22-year cosmic-ray variation, Astronomy and Astrophysics. 330, 764-772 (1998)
from Chile (AD 1587–1994)
, Planetary and Space Science 55 (2007) 158–164Svensmark, Henrik, Danish Metorological Institute, Influence of Cosmic Rays on Earth’s Climate, Physical Review Letters 15th Oct. 98
Wikipedia, Hodrick-Prescott Filter January 20, 2008
Can someone check for an approximate 19 or 20 month periodicity in the 12-month-running mean for the period from start of 2000 to end of 2007 for the Hadley data at http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt
I’m runing Gnumeric on linux at home, so Excel plugins don’t do me much good. I do notice that if I switch to a 19 or 20 month running mean (boxcar?) the sawtooth pattern (as seen in the 12-month running mean) disappears. So I assume I’m seeing a 19 or 20 month periodicity. I do know of one natural cycle that takes approximately that long, but I’d hold my nose when quoting it, unless I had damn good backup.
I’ve uploaded a spreadsheet, with a lot of tabs, at http://clients.teksavvy.com/~walterdnes/temperatures.zip to show what I mean. The zipped file is approx 1 and a quarter megs. Read the README tab for documentation. I’ve saved as Excel 2007 format, so most everybody should be able to handle it.
Thanks so much for your work on this project. These results are astonishing. I am no physicist, but I can certainly see that this should put to rest any doubts about the solar connection. I remember a simpler time when the sun was acknowledged as a force in weather. Warm was good and the chilling cold was the killer. The world of science has been turned upside down. Thanks again for your work in helping to right some terrible wrongs.
Mike Bryant
So, a conclusion of your analysis above would be that it’s important to look a short time scales versus the long time-scales that climate modelers have used (which they emphasize when skeptics bring up the effects of the sun on climate). In other words, the climate modelers have misinterpreted the effects of multiple short-time events as one long-time effect that they attribute to man-made warming caused by CO2. Thus, the fundamental difference in explaining the recent warm-up between the skeptics and climate modelers is essentially one of time scales (i.e., climatge modelers don’t recogonize the impact of the sun in the short term and as a result they are implementing a long-term model that is fundamentally flawed when compared against reality). As a result, too much weight is given to CO2 in their models. People only model what they know. If people don’t understand how the sun impacts the climate, it’s not going to be reflected in their models.
Nice work gentlemen. I notice in Fig. 4 that when the HADCRUT peak preceeds the peak solar cycle, it seems to indicate warming.
It seems pretty conclusive and well referenced. Any chance of seeing this published in a Journal any time soon?
Anthony: Yes we hope to. I had a number of qualified people including a published climatologist, solar scientist, a statistician, and a certified consulting meteorologist (among others) look at this beforehand. We’ll see what new insight the comments bring.
Well I unfortunately, have non of those credentials, I believe I am the ONLY one who has noticed fig 1, is the Batman Logo!
http://www.globalposterindo.com/images/katalog/g080-batman-logo.jpg
So There!
Why didn’t you include plots of solar cycles along with the temperature data?
REPLY: Fugure 5 shows correlation between peak rate of change in the sunspot numbers and peak rate of change in the HadCRUT surface temp data. But, I’ll see if we can create an additional graph to post. Thank you for the suggestion.
I’ve asked (leif) today if he would be interested in commenting on these results at climateaudit (solar thread)
REPLY: Thanks
Very nice work Anthony and Basil.
Now all of us flat earther’s and moon landing denier’s have more work to support our story.
From figure 2 it looks like the non-cyclic temperature increase from 1880 to 2000 is 0.15C, which I assume is the AGW forcing.
Bravo,
You have found a way to pull out of the temperature data, components of specific periodicity. Furthermore, you showed that there is a component whose rate of change is in sync with and proportional to a well known solar cycle.
Can you take the numerical analysis further?
How many degrees of warming would this component, by itself, give us?
Can you use this technique to decompose the magnitude of warming /
cooling by periodicity?
AGW is supposed to create a small but monotonically increasing component superimposed on all the other, wildly changing, components of temperature change. Can you use this technique to isolate such an aperiodic signal and determine its magnitude?
Can you take the science further?
You have isolated an effect and shown it is compatible with prior work on CGR based influences on temperature.
Can you develop a model for how this effect would work?
Is there some component of our atmospheric system that somebody has shown behaves like this model?
Can you use this model to bring to light features of this component?
Stepping back out into more generic issues, can this technique, coupled with a good model, be used to pull out generic features of the system or of the driving influences? Say time constants of various thermal reservoirs?
Have you thought about what it means when you look at a smoothed rate of change of a smoothed global average?
Anyways, my questions are meant to urge you to take this further, if possible.
thanks for sharing your work.
The Impact of Different TSI Time Lags on Average TSI?
The following is a graph of TSI data, where a second duplicate column of TSI data (Lean et al & ACRIM) has been lagged five years after the first, to simulate the difference in response times of land and oceans. The bold red line is their average.
http://tinypic.com/fullsize.php?pic=9bg48o&s=3&capwidth=false
The results mimic the global temperature record well.
http://tinypic.com/fullsize.php?pic=kdtqat&s=3&capwidth=false
To reproduce, simply copy the same annual TSI data onto two spreadsheet columns and shift one down five years. Then average the two. It’ll be interesting to see what happens when the two data sets are proportioned for the differences in land and ocean area, and when the lag average is created with monthly data, and when PMOD data is used in place of ACRIM. I’ll let you know.
What I thought was the best correlation of the whole thing: that downward spike in the latter half of the 20th century is at 1976, which is close enough to the Great Pacific Climate Shift and the change in the AMO to be significant.
Regards,
Bob Tisdale
Anthony, being an electrical engineer in RF and communications this makes perfect sense to me after you guys doing the math. I think the “CO2 Climate scientists” at RC will be smarting after this one.
Outstanding job!
REPLY: Actually I think they’ll either ignore it at RC or make a joke of it. They are clearly entrenched in “no solar correlations”. -Anthony
This is incredible information and a credit to both of you for pulling it all together. Someday soon (hopefully) I’ll be asking permission to post it on the svensmarkeffect.com website once I finish the design and get it up and running.
I just can’t imagine how many hours you guys put into this… any guesses on your part?
Jack Koenig, Editor
The Mysterious Climate Project
http://www.climateclinic.com
Frank,
The connection between temperature and the solar cycle is complex, and non linear. There’s a connection, but it is not one that is easily presented visually. The solar cycle itself is a complex phenomenon to depict in a plot. What, exactly, is the “solar cycle” and how do you plot it? Sure, we could plot the sunspot cycle, but that’s not the connection we think we are seeing here, except in a very indirect way. The plot in Figure 4 correlates strongly with the timing of the solar cycle peak, as measured by sunspots, but not necessarily with the number of sunspots. But sunspots may be merely a proximate cause, and their number not a good indication of all that is taking place.
Figure 4 very strongly points to something that has to do with magnetic pole reversal. There is a very pronounced difference in the shape of GCR flux between odd and even numbered solar cycles. During even numbered solar cycles, it it peaks sharply. During odd numbered solar cycles, the “peak” is flatter, but longer in duration. If this is influencing earth’s climate through cloud cover formation, the effect is probably gradual and non linear. It probably causes the “core” trend in earth’s temperature to accelerate and decelerate with lagged influence. If all of this could be easily shown in a graph, it would have been done long before now.
Look at what we’re doing this way, if you can. There are lots of studies showing 22 year periodicities in climate proxies such as tree rings, drought indexes, etc. These implicate a solar climate connection even if they do not result in a plot against SSN’s. We’re seeing the same thing here, but with a twist. First, we’re seeing it in the instrumental record, which has only been rarely reported, that I can find, and second we’re seeing it in a way that is consistent with variations in GCR flux. It gives us some ideas on where to go next, in trying to establish a stronger statistical link. But the complexity of the relationships involved doesn’t reduce to something that can be easily plotted on a graph.
Basil
It’s very pleasing (though unsurprising) that Basil and Anthony’s remarkable analysis finds such a clear 22-year signal. That distinguishes the the climatic role of cosmic ray modulation by the Sun from the effects of the 11-year cycle in other solar mechanisms such irradiance.
Research on cosmic rays and climate has moved on a very long way since the rather elderly reference to Svensmark 1998. For a review article from last year see:
Henrik Svensmark, ‘Cosmoclimatology: a new theory emerges’, Astronomy and Geophysics, Royal Astronomical Society, London, Vol. 48, Issue 1, 2007
And Basil and Anthony’s rate-of-change analysis applied to Lockwood and Fröhlich provides valuable reinforcement to: :
Henrik Svensmark and Eigil Friis-Christensen, ‘Reply to Lockwood and Fröhlich – The Persistent Role of the Sun in Climate Forcing’, Danish National Space Center Scientific Report, 3/2007, September 2007
Downloadable from http://spacecenter.dk/publications/scientific-report-series/
As for the remark about possible global cooling — in an updated 2008 edition of our plain-language book The Chilling Stars (newly out with Totem in the USA, and Icon in the UK and Canada) Svensmark and I comment that we’ve been advising our friends to enjoy the global warming while it lasts.
Basil and Anthony,
Thanks for putting this in language that an old Navy radio operator can understand. It will be interesting to see how the scientific community responds to this work.
Steve Keohane,
I haven’t looked at them all, but it certainly looks like that for cycle 23, where our rate of temperature change peaks in 1997, but the solar cycle, as measured by SSN’s, peaks in 2000. This may have to do with the way the GCR flux varies between odd and even numbered solar cycles.
Basil
Can you use this filtering method to determine how many independent cycles/harmonics are contributing to the overall temperature record?
I asked a PHD Economics Univ of (Name withheld to protect the innocent) to comment on the use of the filter and his response was:
Which leaves me to ask is there another filter to use to confirm results? Just trying to forestall any criticisms.
The analysis is interesting but can’t be used as evidence of causality between solar activity and temperature increase. Temperature increase manifests itself as a trend in the original data. By differentiating the temperature you are reducing the trend contribution to a constant value.
For example, if:
T=a*t+b+cyclic_component
then:
dT/dt=a+d(cyclic_component)/dt
By differentiation, the trend component (a*t+b) was reduced to a constant. So the cycles in figure 4 are independent of the existence of a trend. They come from d(cyclic_component)/dt. The only information in figure reminiscent of the trend is a constant value that is being added to the cyclic component.
ok, there has got to be an enterprising graduate student who will take this on as their thesis.
If I didn’t like not starving, i’d be back in graduate school doing this.
As I said before this most definately needs to be published.
B, that vitriol is like a cat hissing; it’s scared.
============================
oh, i also see a correlation too, but I’d love to know the exact mechanism and how it all interacts.
Very interesting gentlemen. I can’t imagine the hate-mail Anthony is culling out of the comments section.
REPLY: The hate mail is nonexistant thus far. But having said that, I’m sure some will come any second now. -Anthony
JM,
Doesn’t what you are saying — about differencing reducing the trend component to a constant — apply only if the trend is linear? What if its non linear? What you see in the smoothed series — the blue lines in either figures 1 or 3, are not linear trends. They undulate, and differencing reveals a non random pattern of change in the rate of change. E.g., I’m questioning whether the “a*t” part of your question specifies the correct functional relationship, and that the resulting conclusion that dT/dt reduces to the constant “a” (plus the change in a cyclic component, but that’s already been removed from the data)). In effect, what you see plotted in Figures 2 and 4 are the “a’s” of your equation, and they are anything but constant.
As for causation, that’s always been the rub for studies which show 22 periodicities in climate metrics. When 22 year periodicities are found in tree rings, what does it prove? Many will say it shows a “connection” between solar activity and climate, but lacking an explanation of the actual physical basis for the connection, others will say that more is needed before claiming that the correlation proves causation.
That’s where the differing amplitude of the differenced “trend” between even and odd numbered solar cycles we are seeing here may prove important. Why would the signal be weaker in even numbered solar cycles than in odd numbered solar cycles? Well, there is a theory about that, having to do with the role solar magnetic pole reversals modulate cosmic ray flux. If you haven’t already, read Mavromichalaki, et al. Incidentally, I just now noted that Anthony has a difference Mavromichalaki, et al. paper than what I intended. The one I had in mind to cite is this one:
http://articles.adsabs.harvard.edu/cgi-bin/nph-iarticle_query?1996Ap%26SS.246….7M&defaultprint=YES&filetype=.pdf
I hope that link comes out when this gets posted. A full cite would be
Mavromichalaki H, Belehaki A, Rafios X, et al. Hale-cycle effects in cosmic-ray intensity during the last four cycles ASTROPHYS SPACE SCI 246 (1): 7-14 1997.
Another useful read as to why 22 year periodicities may infer something about the physical mechanism involved is this one:
http://www.atmos-chem-phys-discuss.net/6/10811/2006/acpd-6-10811-2006-print.pdf
Basil
Please could you include a plot of the 22year cycle (HadCRUT3 alone would be sufficient) filtered with lambda=100 and the 11 year cycle fltered with lambda=7 on the same graph for comparison?
Oh, and the Mauna Loa CO2 series might be interesting too!
REPLY: Actually you can do those yourself and easily. There is an HP filter plugin for Excel available here:
http://www.web-reg.de/hp_addin.html
terry,
“oh, i also see a correlation too, but I’d love to know the exact mechanism and how it all interacts.”
See the two references in my reply to JM. In the first, pay close attention to how cosmic ray flux is modulated between even and odd solar cycles, and the role magnetic pole reversal plays. The lower amplitude we are seeing in the even numbered solar cycles, compared to the odd numbered solar cycles, fits this model of solar activity very well.
Basil
JM,
You are correct if the trend is modeled with a linear function. But once it is modeled with another function it will still be present to some degree in the first derivative. In fact, if the trend is modeled using an exponential function (e.g. – a hockey stick), then the trend will still be present in the derivative.
thank you, Basil for your reply. I am looking forward to seeing many others actually take an open minded look at this. I think you’ll have better luck with the graduate students then you would with the entrenched “senior-level” climatologists.
CoRev,
Hodrick-Prescott works like a high pass filter. Other smoothing techniques, such as the binomial filter used by HadCRUT to smooth the long term temperature trend. are low pass filters. In the latter, the trend is forced upon the data, and the residuals are treated as the cyclical component. In Hodrick-Prescott, the data is not so much smoothed, as de-trended, with the “smoothed” series being the residual, just the opposite. In economics, the interest is in the de-trended part. Here, we’re finding something in the “residual trend” after the stronger, shorter cycles have been removed, allowing longer term cycles to emerge. Because we are looking at the smoothed series, and that over a long time frame, I don’t think that the traditional concerns your source mentions apply.
But if someone can suggest another filter that works similarly to HP, and if they wish to see if it confirms what we’re seeing, then by all means, we’re open to that kind of exploration.
Actually, what we’re seeing here has, in some degree, already been found, using spectral analysis. See, for instance:
http://scholar.google.com/scholar?hl=en&lr=&safe=off&q=brunetti+%22study+of+the+solar+signal%22&btnG=Search
So, in a sense, the connection has already been found. We’re just seeing it in a different temperature record, using a different technique, that happens to show a variation between odd and even solar cycles that may well relate to current thinking about how solar activity would impact earth’s climate.
BTW, I could find no reference to those Brunetti papers in IPCC AR4 WG1, Chapter 3, which is where I would have expected them to be discussed. There’s reference to related research by Brunetti et al on precipitation, but not to the work on solar signals in the instrumental record. It sure looks like a case of special pleading on IPCC’s part.
Basil
Basil, and Anthony: A veritable tour d’ force, congratulations. I agree with J.B., McG. and others, this is significant.
No doubt peer-review can offer some editor-friendly improvements, but my intuitive feel is that it is ready for such an endeavor.
I asked nicely, I thought – I can’t post the plots here, they would strengthen your argument considerably, please, would you do it?
REPLY: Hi Chris, You did ask nicely, and I’m sorry if you thought the response was some sort of a brush-off, because that was not the intent. I just thought you and other readers might like to be engaged in the process a bit. We’ll have follow ups to this one where that and more can be posted. -Anthony
This may have to do with the way the GCR flux varies between odd and even numbered solar cycles.
Basil
Ah I see, it is like the flux between odd and even numbered Star Trek films. Now I get it.
j/k, nice work guys.
smart people man.
Many thanks, Anthony (& Basil)
Bob B / Anthony
Being entrenched does not bear any scientific fruit, now does it?
Just goes to show that the RC folks have no clue about how science works.
Leif Svalgaard points out alternating shapes to the peaks of solar activity, sharper alternating with rounder. Is there a connection?
=================================
Nice work and very interesting analysis, though I certainly don’t know anything about data filtering and smoothing… Looking at your data in Figure 5, it is pretty astounding that you see almost no lag between peak solar cylce date and peak temperature date. Your correlation results seem to refute Scafetta and West’s (2007) hypothesis that there is an internal lag associated with changes in solar activity due to heat sinks in the earth system. Their response times are from 6-12 years, which would make sense to me. Any ideas why this might/might not be true? My guess would have been that the terrestrial realm might respond faster to insolation changes, but HadCRUT is both sea surface temperatures and terrestrial measurements, so that doesn’t seem to hold up.
I’m sure you know this, but some journals state that publishing on the internet is prior publication and disqualifies a paper for publication in their journal. I hope you don’t have problems with this, and I assume you have had some journals in mind that might not care either way.
Reference:
Scafetta, N., and B. J. West (2007), Phenomenological reconstructions of the solar signature in the Northern Hemisphere surface temperature records since 1600, J. Geophys. Res., 112, D24S03, doi:10.1029/2007JD008437.
Basil/Anthony,
I’m running to keep up here, but I think I’ve replicated your results using pure Fourier analysis with the (growing like Topsy!) C++ toolset I mentioned earlier.
Here is the raw HADCRUT3VGL monthly data with a low-pass filter which removes everything above the 15’th harmonic in frequency space – i.e., everything shorter than (150/15 = 10) years:
http://www.woodfortrees.org/graphs/hadcrut3.fourier-lp-15.png
and here is the first derivative of that graph:
http://www.woodfortrees.org/graphs/hadcrut3.fourier-lp-15-d.png
Basically the process is:
– DFT the raw data into frequency space
– Remove everything above the 15th harmonic (keeping 0..14 and (N-15)..(N-1))
– IDFT back to time space
– (Second graph): Take first derivative
That’s it. There is no other smoothing or filtering.
Please ignore the end-effects; that is an artefact of the DFT/IDFT process which I’m still trying to figure out. I’d hate someone to use this as evidence of massive cooling in the past decade! Nevertheless, the main part of the graph indicates the same 11 and 22-year cycles. Oh, and the time axis is in months from 1850 (haven’t corrected that back from the IDFT yet).
Sorry this is a bit messy – there will be a proper interactive way of driving this at http://www.woodfortrees.org (as in, “seeing the…”) Real Soon Now.
Hope this helps!
Paul
REPLY: Thanks Paul, Nice to see an alternate method replicate it. Thanks for doing that. The first derivative graph you posted matches ours in pattern pretty well, but has one less peak. It also appears to be a bit more smoothed. Do you think that missing peak is related to the end effects you mentioned or maybe one of the smaller peaks, like 18, got smoothed out? -Anthony
Basil, thanks for the response. Would the Baxter-King high band pass filter, just replicate the same effort? I am not a scientist/mathematician so am clueless?
Unless you guys say no, I will put Part II up at my clearinghouse site. I already have the first referenced, but not written an article, as of yet. I am assuming that since it is here it is public.
REPLY: It Is public, feel free to link to it or post excerpts. I’d ask that the graphs not be copied to secondary webservers though. -Anthony
Basil,
I agree that demonstrating the exact physical link between temperature and the sun will prove difficult.
With regard to the apparent connection between solar magnetic field polarity and temperature, and the connection to cosmic ray flux which you eluded too; has anyone tried examining the physical interaction of the cosmic ray flux direction with the solar and terrestrial magnetic field? It seems apparent to me that the solar and terrestrial fields sum to increase or decrease the deflection of cosmic rays dependent upon the polarity of the solar magnetic field.
To elaborate on my inquiry of graphing the local dT/dt max and solar cycle max together to demonstrate correlation, I believe the key feature will be to find which solar parameter is linked to temperature change. From my previous paragraph, this link could be the solar magnetic field intensity, and/or some linear combination of other parameters.
It’s probably that whatever the link, it’s going to be highly convolved, because if it is obvious, you would think it would have already been discovered. Although, to be an important discovery you don’t necessarily have to hit the homerun, which would be a deterministic relationship capable of prediction, which is what the AGW focus on at their peril; it could just be a step in that direction and be critical to enhancing our understanding the solar-climate connection.
Anthony or Basil, is it possible to get a hold of tabularized data for Fig3b and Fig4?
Much appreciated
I wanted to give a kudos on temperature analysis in the derivative domain. A lot of people seem resistant, because they think that differentiating a noisy signal is always wrong.
But the important thing here is the extraction of meaningful features.
The errors in the surface temp series will occur as thermometers are moved, as site quality changes, or as stations are closed down. These changes are acyclic, and tend to dominate a signal over time.
By filtering out this “noise”, you get to see a whole new set of information encoded into the temp record. This is exactly what signal processing is for.
My signal processing is decent, but my statistics is rusty. Can anyone estimate the chances that this is just coincidence? It doesn’t look like it to me, but I have been fooled before.
Bravo,
Nice job Basil/Watts. Nothing that will not be derided by most groups that are entrenched in one way or another, but still it is a nice piece of work. I look forward to more on this subject.
Anthony
Why don’t you send your work to Bob Hodrick at Columbia? he is a good guy and not a brain-dead liberal. This is a topic that according to the alarmists is a threat to our very existence. It would be a good application of the skills that Hodrick has.
Maybe he could be paired up with someone like Lubos Motl or Svensmark to publish a study.
Anthony,
I think peak 18 disappeared from low-pass(15) because it’s very close to peak 19, so got suppressed by my right-on-the-edge filter. Moving the filter up to harmonic 18 generates this:
[Damn, wrong button: Please combine these if you can!]
http://www.woodfortrees.org/graphs/hadcrut3.fourier-lp-18-d.png
OK, here’s another interesting Fourier example… This is a band-pass filter between harmonic 5 and 25 – in other words, selecting cycles roughly between 6 and 32 years long:
http://www.woodfortrees.org/graphs/hadcrut3.fourier-bp-5-25.png
Note this is not differentiated. This simple shows the raw data with the long-term (more than 32 year) trend and the short term (less than 6-year) noise removed.
I’m now going to put this on a Web page where you can select filters to your hearts’ content… watch this space!
What I want to know now is, what was different about the 1930’s, solar wise?
Paul
Oh, great. just when we’ve got this neato cool 60-year PDO cycle that correlates, and now THIS?!
Curse you, Red Baron!
In your figure 5, regression, you ignore peaks at halfway between 15-16 and 16-17 from the temp record, that are not on a solar cycle.
Also my intuition is that the sort of plot that you show here in figure 5 is not proper use of X-Y regressions.
One more, and then I’ll shut up and code the interactive version so you can all play. This is a band-pass from harmonic 2 through 5. We’re in the deep sub-bass now:
http://www.woodfortrees.org/graphs/hadcrut3.fourier-bp-2-5.png
66 year cycles, anyone? And feel the volume: 0.3K+ peak-to-peak. God is clearly a drum-n-bass fan.
Basil/Anthony,
If you look at the RSS and the magnetic field map of the world you will see that the anomalies almost match the field lines. Why is this important. Because the suns magnetic field and CME’s effect the Earths magnetic field. They also change the atmosphere and may inhibit cloud production. This is also seen in the LOD variations that maybe cause by jerks in the geomagnetism. This may correlate with your solar cycle variations. Don’t want to go too much into it but it is very interesting. Very nice work on part II.
http://www.remss.com/msu/msu_data_monthly.html?channel=tmt
http://geomag.usgs.gov/charts/ig00f.pdf
http://www-istp.gsfc.nasa.gov/istp/nicky/cme-chase.html
LOD comparision to temperature.
http://sait.oat.ts.astro.it/MSAIt760405/PDF/2005MmSAI..76..957D.pdf
The Geomagnetic jerk in 2003 maybe the signal that the cooling has started.
http://spacecenter.dk/~nio/papers/SV_SHA.pdf
Interesting.
I did something similar: Using an Accurate Global Temperature Index to Diagnose Global Climate Change.
REPLY: To all readers here, this some sort of early April fools joke as he labels it “humor”.
Wonderful piece of work and I look forward to seeing it in journal form. I am particularly interested in the 66 year cycle it highlights due to the importance that the 60-70y Interdecadal Pacific Oscillation (or Pacific Decadal Oscillation for those in the Northern Hemisphere) has on weather and oceanic processes for us in the Southwest Pacific Ocean.
Your results are essentially the same as I get with Wavelet analysis, but a whole lot easier for my students to understand.
What is needed is to correlate the total solar flux with the temperature. Why is it such a stretch for scientists to realize that the sun heats the earth? Anyone who’s ever gone out on a sunny day can realize this. The energy output of the sun varies over time. Almost all stars have some luminosity variations. As was pointed out in another comment, sunspot cycles do not necessarily correlate with luminosity. With all the solar observatories in orbit, you’d think somebody was keeping track of solar luminosity. Get the data and plot a graph. It should be just obvious.
Nigel et al … witness the current situation with world rice supplies.
Highly disturbing and attributable to this winter and spring’s abnormal cold, especially in the eastern half of Asia. Although having written that, I report that this AM in Northern California there were freezing conditions, especially inland. Especially in areas of the Sacramento Valley where short grain hinode is grown.
Here is a question for you astrophysicists:
If this graph is indicates a GCR – temperature link, could we predict a hemisphere specific signal?
Ie, the earth is tilted so that one hemisphere has greater average exposure to the galactic core. If that is seeding clouds and changing the temperature, would we expect to see one hemisphere change temperature more than the other?
Hi Eric,
GCR’s come from all directions. Only changes if you get Super Nova’s and hope one of them isn’t real close and pointing at you. Gamma Ray Burst (GRB).
Hi
Oooops Erik. Sorry
Great work, guys, and the cleanest, most collegial comment thread I think I’ve ever seen. My tiny brain can’t figure the math, but I get the gist. And I have a couple of old communications receivers…
We need a label for watts goin’ on here (Puns again? (Ed). Sorry, mate…)
Open Source Science?
REPLY: “the cleanest, most collegial comment thread I think I’ve ever seen.” Thanks for that complement. On some other blogs, particularly with the ones run by phantom operators, vitriol, taunting, and general boorish behaviours is a way of life. I’ve never understood it, except to think that “anonymity breeds contempt”, because there is no repercussion for such behaviour. – Anthony
Thanks Jim.
Thanks Jim, I found the Geomagnetic Jerk 2003 paper to be intriguing, because it touched on something I had discussed with Basil prior to this 2 part series being published, and that is Spherical Harmonics. I see these as being key to understanding the magnetic field changes emanating from the sun. They may also help explain the 66 year period we see. I ran the idea by a solar physicist at the national solar observatory, and he was intrigued as well. More on this later, but here is an interactive tool that can be played around with.
Searching for harmonics, I found an interactive model that is geared towards atoms and molecules:
http://www.bpreid.com/applets/poasDemo.html
If you set I=6 and M=3 I think the packets correspond to a solar butterfly diagram of sunspot activity. Spheres are spheres, no matter what size. This interactive model simulates earth’s view of the sun. Now I could be totally wrong, and probably am, but to me the butterfly diagram looks like this spherical harmonic plotted as an earthside view. Positive real values are red, negative real values are blue, so look at how the polarity differs, then look at this SOLAR MAGNETIC butterfly diagram:
http://solarscience.msfc.nasa.gov/images/magbfly.jpg (look at the blue and yellow areas, it is like the interactive model viewed as a cylindrical projection)
The reason I choose I=6 is because it causes 4 distinct zones from pole to pole. This looks much like the way the sun puts out spots. High latitude spots for example, are said to correspond to the expected cycle 24. There are flow loops in the sun that aren’t that much different than what we see as Hadley circulation cells here on earth. Like on the interactive model I’ve presented, on earth we see separate bands of flow. Again, spheres are spheres.
[…] in Astronomy and Aerospace, Science, Science Education. trackback Here is an interesting analysis of solar min/max data. I can’t vouch for the kind of analysis that was performed. But it is […]
TCO,
The plot in Figure 5 is not a regression. There is a correlation coefficient shown, but we’re not doing any regressing. There may be a better way to “correlate” correspondence of the peaks, though, than to calculate a correlation coefficient between the years of the peaks. Any ideas?
The two peaks around solar cycle are certainly curious, and invite closer inspection at some point. They go away with higher order filtering.
Basil
Now, all that has to be done is to tie in the fluctuations in with PDO and AMO and you’ll have a gen-yu-wine Unified Theorem.
It’s all one piece. There must be some cause-and-effect . . .
Hmmm.
Re: Figure 5 corr = .9984…
What would be the corr of two random walk series using the same xy setup as in Figure 5?
Great post Basil and Anthony. It is a good thing I enjoy reading. I believe that there will be some real head scratching going on in some of the RC type blogs and some will just try to pass it off as crack pot work. It IS NOT.
Just as an aside Basil here in Alabama we have no problem correlating the effect of sun on temperature the theory is
1. 4:30am get flash light go out to the hickory tree in the yard read old Coke-a-cola thermomenter temp is 69.
2. Go back to bed and enter normal day.
3. 3:00pm go back out to the old hickory tree and insure the old Coke-a- cola thermomenter is in the shade and take reading. Temp is now 105.
4. Conclusion is that, “Yep the sun sure made it hot today”.
Makes one wonder what makes it so hard to under stand that the sun effects the surface temperature.
Don’t ya wish it were that simple?
Bill Derryberry
Anthony:
Once again, you were faster than me. I was going to send you that link with the butterfly diagram.
If you have advanced to this level of solar dynamics, then I no longer have any doubts about your scientific abilities.
WAY TO GO!
I have always looked at this as an exploration of our Sun, and how it is a variable star. You have done an outstanding job in presenting the data in a way that anyone can understand.
CO2 has increased from 0.000280 of the atmosphere to 0.000384 of the atmosphere or an increase of 0.0001.
Now when this change is compared to an increase from 1,362 watts/m2 (minimum value recorded) to 1368 w/m2 (maximum value recorded) in solar irradiance, the global warmers say this change has virtually no impact. But the change in CO2 has a huge impact.
I don’t know how a 0.4% change in solar energy (which is all the heat the Earth gets) can be less of an impact that a 0.01% change in the atmospheric composition.
Clearly it has to. And this analysis proves it in my mind.
Just think how much colder the height of the winter is compared to the maximum of the summer. My location has a swing of 50C in the average between these two numbers. While averaging over the entire planet is expected to balance out between the seasons, it is extremely clear that changes in solar energy must have a large impact on temperatures. 0.4% should have a large impact.
I just love a series where part 2 beats part 1 . . .
REPLY: always save the best for last.
Is it just me or does the cold happen faster than the warm period? This reminds me of freezing a turkey. Takes just hours. Thawing the damned thing takes forever. Is there something about warming up from a cold state that makes it happen slower than cooling down from a warm state?
Do we have more time (as in years) to gear up for warm periods? And just months to gear up for cold?
Check out Tamino’s last graph in his Part 3 thread.
=================================
I’ve heard Leif Svalgaard talk about the fact that TSI peaks alternate between round and sharp. Could this have something to do with the differing odd/even solar cycle contribution.
Well, the Earth does generate its own heat internally, molten core and all that.
It looks pretty much like you picked a filter that a) eliminated the large positive trend between 1900 and 2008 and b) eliminated any frequency whose period was less than 22 years as can be seen from the bottom pane in Fig 3.
Figure 5 is not very informative. Better would be to graph the difference between the solar peak and the HadCRUT peak in years. That one jiggles all over the place
Anthony: “detrending” was part of the process, much like removing a DC or an extremely low frequencey component that is near DC from a complex AC signal. Pretty standard stuff in electronic signal processing. It was applied over the entire signal, not just a section.
Thank you for your suggestions on figure 5.
Well, the Earth does generate its own heat internally, molten
core and all that.
I think the earth’s own heat is ~.08 w/m^2.
As a relative beginner when it comes to understanding the math behind these kinds of posts I’m trying to come to grips with what is graphed above. In laymans terms it appears that you plotted the HadCRUT values against the smoothed HadCRUT as a zero baseline (figure 3 graph 2), used a filter to get 23 (or so) rate of change peaks (fig 4) and then plotted the peaks on a graph along with solar cycles but with no variables.
To me it appears that you’ve shown that the “noise” of the original data vs the smoothed data is correlated to sunspot cycles but does that have any bearing on the absolute value of the trend line itself? In other words, if the noise on the trendline was a sawtooth with the peaks aligned with max sunspot and the mins at min sunspot but the slope of the trendline was 2C/century would that correlation have any meaning?
Thanks. I wasn’t sure how much. Just wanted to illustrate that the sun isn’t the only heat source, just the vastly dominant one.
Nice work Basil and Anthony. Very interesting and well written. FYI – I duplicated your work and then tried a Gaussian smoothing on the HadCRU data and got virtually the same result.
http://i32.tinypic.com/x27320.jpg
This was done with a Gaussian smoothing routine with sigma = 3. An Excel add-in with this and other functions is available from SRS1 Software. It is shareware with a free 30 day trial period.
http://www.srs1software.com
I didn’t think it was the case, but this would seem to strengthen the argument that the cycle seen in the plots is not an artifact of the HP filtering.
REPLY: Jeff, thanks for the work on this. -Anthony
Pamela –
Speaking as a chemistry Professor, a Turkey freezes at exactly the same rate as it thaws when done at the same temperature. I think that you are assuming that it “freezes” soon after being placed in the freezer when in actuality it takes the same time. At the freezing point, q = mL (where L = 80cal/g) and at this temperature it is a reversible process. That is – any small increase in heat can EXACTLY be subtracted. By the way – most chemical reactions are irreversible, but phase changes are not.
Sorry for the OT post, but wanted to correct this “myth” (like hot water will freezes sooner than cold water placed in a freezer).
reminder,
flux density,
one month ago 0067.4
today 0079.3
Evan’s comment about a 60-year PDO cycle popped a random thought into my mind, and I offer this only as a curve-ball for others to bat… If you had *two* cycles from different sources, one of 60 and one of 66 years, IIRC they would ‘beat’ with a wavelength of LCM(60,66) = 660 years. The exact beat frequency is very sensitive to the exact periods of the two inputs (musicians, think about tuning a guitar).
Then consider the rough dates of the Medieval Warm Period, Little Ice Age and now…
Jeff C. good job. For me, the main/first complaint to answer was the use of a infrequently used filter in the climate environment.
I notice that the major ENSO events (1876-78, 1891, 1925-26, 1982-83, and 1997-98) have all occurred when the temperature Trends in Figure 2 are at, or very near, an upper peak.
Is it false to deduce that:
a) Because major ENSOs occurred near peak temp trends, see Fig 2
b) and temp trends correlate well with sunpost/solar cycles, as your paper indicates,
c) then El Ninos are mainly driven by sunspot/solar cycles?
We are always told that El Ninos cause global temps to increase, when if fact it’s probably the other way around. That is first the sunspots – then warming, and then the ENSO.
(Wikipedia says that the current cooling is caused by the current La Nina. How do we know its not the other way around?)
Anyone follow me?
The major ENSOs also line up well the sunspot cycles:
1876-78 – cycle 11
1891
Sorry – hit the wrong key!
1891 – cycle 13
ENSO 1925 – cycle16
ENSO 1980 – cycle 21
ENSO 1998 – cycle 23
I mean just recently a report came out saying the ocean temps have cooled a little over the last 5 years. Could this have led to the current El Nina?
Can I ask my question now? How do we use filtering to find the low stuff? I know how it is done for brainwaves. I would love to have a look at the minimums across the span: length, solar flares during minimums, last one out/first one in overlap, etc.
And one more question: I have noticed that solar flares seem to have a non-linear drop in amplitude, sort of like a switch that turns on and off when the sunspot gets to a certain size or overall number. Could this be a better predictive measure of solar effects on temperature, especially during the upswing and downturn? If the ramping up or down amplitudes leads temperature change, wouldn’t that be a possible strong case for cause-effect? Can we plot solar flare magnitude compared to temperature change? Does that data exist? The number of sunspots may have only a mild to moderate correlation to flares being produced. It seems logical to me that the heat of the flare (and all the stuff it ejects) is more important than the fact that it is counted.
Precisely, Pierre.
===========
Alan, we had three sunspots, now going away, and the flux is dropping. It is not unexpected to see last gasp last cycle sunspots. Flux will not rise consistently until we see new cycle sunspots with regularity, and surely not until they outnumber old cycle spots. Minimum may not be here, yet. Cherry Pie is delicious, though.
===========================================
Bill Illis – greenhouse gases take up a small % volume of the atmosphere, but they do lots of warming work. Most of the atmosphere is insensitive to IR. Look at any overview of the greenhouse effect (not GW per se, but just the basic effect) and you’ll see that at any given moment the Earth’s surface receives more warmth from the atmosphere’s backradiation than directly from the sun. Sounds strange, but true.
Certainly true at night, Ian. Some of what you call ‘back radiation’ started at the sun and directly warmed the atmosphere. It is not really back radiation.
=======================================
While my knowledge of the relevant maths is not sufficient to enable me to keep up with the article, it does seem to make sense. But on a different aspect of pattern recognition and cycles, last night, I was using an analytical device which has the most incredible way of recognising various cyclic events in a long data string. From a single varying voltage, my ears and brain were able to distinguish the various instruments playing in a symphony orchestra. If the temperature record, unsmoothed and unfiltered could be applied to an analogue converter of some sort to produce a voltage, then this could be played as a short track. Due to the woefully limited amount of data, you would probably only get a two or three second output, but it would be interesting to see whether the brain can “hear” different patterns, or “instruments”. Silly thought, but…who knows, you might just hear something, then again, you might just get a burst of noise, which might also give some insight into a lack of patterns.
Kim said:
and it heated the land and water. The stored heat is given back after the Sun drops. Mitigated by clouds to slow the heat radiation back into space. That Ole cloud effect, don’cha know.
Of course CO2 has its own impact, but…?
kim, yes, of course almost all of it came from the sun originally. And greenhouse gasses delay its return to space, warming the planet surface. Averaged over the planet, the surface is warmed more by the atmosphere than by _direct_ sunlight. Check any basic description/depiction of the greenhouse effect to confirm.
My point to Bill Illis was to avoid being misled by the scaling differences between TSI (normally expressed with a number over 1000) and CO2 concentration (expressed as a part per million), or to compare their change rates directly. (This is leaving aside the problems of comparing to the top-of-atmosphere TSI figure.) Bill, I was suggesting that your comparison doesn’t capture the extent to which IR, originally from the sun’s energy, is kept around by greenhouse gasses.
Paul’s comments caused me to look at fig 5 again. Did anyone notice that the sunspot is a straight line, but the surface data seems to show a very slight wave pattern ahead, then behind.
Note also that the pattern drifts a little after 1980. Could thissomehow be a reflection of exaggerated ground readings due to site violation?
Speaking of greenhouses, I have come across two observations that make one ponder
1) A garden green house ( or a closed car) does not work by trapping the heat because of the insulating and back radiation properties of the glass (or metal). It heats up because there are no convection currents within the green house( car). It is the enclosure that drives the heat up with respect to the outside temperatures. It is a misnomer to call the atmospheric effect “greenhouse” as there is plenty of convection in the atmosphere.
2) In http://arxiv.org/PS_cache/arxiv/pdf/0707/0707.1161v3.pdf the position is taken by Gerhard Gerlich and Ralf D. Tscheuschner that :
“The atmospheric greenhouse effect, an idea that authors trace back to the traditional works of Fourier 1824, Tyndall 1861, and Arrhenius 1896, and which is still supported in global climatology, essentially describes a fictitious mechanism, in which a planetary atmosphere acts as a heat pump driven by an environment that is radiatively interacting with but radiatively equilibrated to the atmospheric system. According to the second law
of thermodynamics such a planetary machine can never exist.”
It is a rambling paper, but this second of law thermodynamics would be serious trouble for the atmospheric greenhouse model . It is true that heat cannot be transfered from a lower temperature reservoir to a higher temperature reservoir ( the Clausius statement of the second law of thermodynamics) without work being done somehow. ( think of air conditioners ). As the temperature in the upper atmosphere ( outside a plane at 30000 feet) is lower than the temperature near the surface, what is doing the work?
Has anybody seen any discussion /have a link of the atmospheric greenhouse effect as a thermodynamic engine ,other than the above linked note which says it is a perpetual motion machine of the second kind?
Water vapour is by far the most important greenhouse gas, followed by the first 40 ppm of CO2, then by the next 80 ppm, then the next 160 and so on. The few ppms that we are now adding to the atmosphere are very minor in the overall greenhouse effect. The greenhouse effect of CO2 decays logarithmically as concentrations increase. Too many people falsely believe that it is a linear function. It is not.
Greenhouse gases do lots of warming work? Yes.
A few more ppms of CO2? No. They are insignificant!
Apparently, David Hathaway of NASA is becoming impatient and they are going to send a manned expedition, including Hathaway, to the Sun to see what is going on. In order to save costs and construction time, they are planning to make the trip at night so they won’t have to worry about the heat. It is hoped that they can get all their measuring devices planted and be far enough away from the sun before daybreak.
To Ian, yes I understood all that.
The impact of GHGs is often expressed in Watts/m2 as well which is variously quoted for a doubling of CO2 at 4.2 w/m2 (and we are only halfway there now.)
Changes in solar irradiance (divided by 4 for the Earth as a sphere and the lowest measured to the highest measured) have been as much as the current GHG forcings of approximately 2 W/m2.
How come solar has no impact while GHGs account for so much warming.
I also note that the 1878 temperatures (an El Nino year) from Hadley are virtually the same as today’s numbers (despite the 1878 temps being adjusted downward by Hadley.) Does that signal no warming for 130 years?
This is worth a reading, is clear and concise, good plots:
http://www.warwickhughes.com/agri/Solar_Arch_NY_Mar2_08.pdf
“Solar Cycle 24: Implications for the United States
David Archibald
International Conference on Climate Change”
“We have to be thankful to the anthropogenic global warming proponents for one thing. If it weren’t for them and their voodoo science, climate science wouldn’t have attracted the attention of non-climate scientists, and we would be sleepwalking into the rather disruptive cooling that is coming next decade. We have a few years to prepare for that in terms of agricultural production.”
As anna v. points out ‘back-radiative’ warming of the surface is nonsensical. CA had a AGW ‘radiative budget’ flow chart a couple of months back around the time Curry (GATech?) was posting.
The back-radiation AGW specifies approaches 25% of the original energy reaching the ground. This is impossible. There can be no net flow of heat between bodies at the same temperature, let alone a transfer from the cooler to the warmer.
The UAH MSU data demonstrates that the equatorial high troposphere is not warming.
In addition, the surface emissivity is more than two orders of magnitude greater than atmospheric CO2 and re-emits energy received faster than the CO2 can absorb.
The errors in the Greenhouse heuristic are legion and the G&T paper details the most basic of them well.
Pamela,
re: rate of rise versus rate of fall.
and
Drew
re: time constant of the ocean.
I have no idea if what you see is due to dynamics in the sun, or in the earth.
But, in my simpler world of cyclotron produced medical radioisotopes, the rate of change in amount of isotope is a function proportional to the beam current that hits the target minus the rate of decay times the amount of isotope created. Since the production rate goes to zero as the amount of isotope approaches saturation, it is not usually worth running for more than one half-life, and the rate of increase doesn’t change much from the rate of production.
So, for short term changes in my simple world the rate of rise is mostly based on the beam current and how it changes. But turn it off, and the rate of fall is solely due to the decay rate.
It may be possible that in the much more complex world and and the very complex sun and the ways they couple, that Anthony and Basil may have isolated a driver term and its coupling to a reservoir with a similar time scale , but are dealing with small perturbations from equilibrium instead of starting from absolute zero and trying to warm up the planet. Except, the the average temperature is a measurement of the atmosphere which is also driven by the sun TSI as gated by the GCR, amongst other effects, and the ocean time constant will be afunction of how it radiates, how it gives or takes heat from the atmosphere, and maybe many other things. But, if this math has filtered the data so that the rate of change seen in the atmosphere temperature is mostly due to the ocean and or the sun/gcr, and the rate of change in the ocean is mostly due to the sun/gcr and the coupling to the atmosphere, then for an initial perturbation from equilibrium the initial rate of rise in the atmosphere would have two components proportional to the sun/gcr driver term, and the rate of fall in the atmosphere would have a component based on the rate of fall in the ocean. (Sorry that sentance is so long.) So one could be seeing both time structure in the driver, and time structure inherent in the system.
I will leave it to others to come up with a real model and to see just what effect each part of the system has, which is what I tried to urge with my previous post. But it is worth remembering that a time constant much shorter than the time frame of changes in the driver will stay in equilibrium with changes in the driver, so one will see the longer time frame of the driver in that system. And a time constant much longer than the changes in the driver will not have enough time to react and the system will seem unperturbed by the changes in the driver. And time constants nearly the same as that of the driver will be more complex, and harder to tell apart.
And Drew, the total change, (integrated rate of change), should show the time lag. The current in an RC circuit is the rate of change of charge in C. The voltage on C lags the rate of change of the current.
The link between this work and the PDO has been mentioned a few times. Of particular interest is Paul Clark’s comment of beating between solar forcing and the PDO. From an oceanographic perspective the PDO involves the circulation of thermosteric anomalies around the Pacific Ocean. These derive from atmospheric/solar effects when the parcels of water at at the surface – Precipitation/evaporation balance effects salinity, amount of shortwave radiation reaching the ocean effects temperature anomalies = density changes. Clearly the GCRs implicated here will influence the salinity & temperature anomalies through influencing clouds.
The anomaly then circulates subsurface (ventilated thermocline theory) until it returns to the surface 50-70 years later. If the return is sufficiently in phase with solar cycles then the anomaly will be amplified, and if it is out of phase it will be attenuated.
We’ve been playing with wavelets to looks at oceanographic and coastal atmospheric processes related to the PDO and ENSO. There is clear evidence for interaction between the two, but we also are seeing a longer period pattern in paleoindices that suggests that there is something going on akin to beating.
The problem has been figuring why it is happening. The work summarised here is therefore intriguing.
Anna, with respect to part a) you have that a bit wrong, greenhouses work because the barrier (glass or whatever) cuts off convective flow from inside to outside, so the inside heats to the point where radiation and conduction from the surface match the incoming from the sun. There is plenty of convection inside the greenhouse.
As to part b) if you want the math rich version about why G&T are wrong take a look at Arthur Smith’s comment on Arxiv
A less mathematical, but longer version can be found at Rabett Run, which, as long as it is is but a fraction of the original on dot.earth.
REPLY: “…greenhouses work because the barrier (glass or whatever) cuts off convective flow from inside to outside, so the inside heats to the point where radiation and conduction from the surface match the incoming from the sun.” That is essentially correct, the term, “Greenhouse”, when used to describe atmospheric effects, is a popular misnomer. Notice that most greenhouses have fans/vents, hinged glass panels, and airflow control systems to help regulate temperature. -Anthony
Also, most commercial greenhouses have a machine in the corner pumping out CO2 to keep the level above 1000ppm. This is not to warm the atmosphere in the greenhouse, but to feed the plants. When the level of CO2 drops below 150ppm, (which it will do by mid-morning if not replenished), the plants will stop growing and if it drops below 90ppm then photosynthesis stops.
How about Miscolczi’s objection?
============================
From the pattern indicated in Figure 4, the implication is that the “warming” of the late 20th century was not so much warming as it was less cooling than in each preceding solar cycle, perhaps relating to the rise in geomagnetic activity.
Rather than requiring readers to infer something about magnitude from the rate plot, why not point them to the trend plot in Fig. 3 from which it was derived? That tells you directly how much warming or cooling occurred.
I know very little about solar mechanics, or GCMs for that matter. But for what it’s worth, it does seem to me that you could be a bit more careful about implying things about the magnitude of potential effects from rate data — especially if it’s just peak rates. For example, I’m not sure it’s appropriate to imply anything about the magnitude of GCR flux as a temperature forcer based upon a measure of peak rate of change in temperature. If anything I would think that some kind of measure of the area under the curve for the period in question would be more appropriate — unless the fastest rate of change is more important than the overall magnitude of change. On that score, I can’t say. But if it is, I think your discussion could make that clearer. And also if it is, then more attention should be paid to a discussion of whether the measurement of those rates are appropriate.
And I still don’t understand why you picked the HP filter. It seems to me you’ve violated just about every theoretical assumption you could in that regard. But I’m not a good enough statistician to derive the filter’s response profiles on the one hand, and I sure as heck don’t know enough about solar dynamics on the other to mount a compelling argument. So I’m willing to take Paul Clark and other’s word on various other filtering results. And actually, I did spend some time putting the data through a variety of Butterworth and finite impulse response filters and was able to get similar results — assuming I was careful to pick the right cut-off frequencies and rolloff characteristics. I got some very pretty results, too! In fact, I got one that looked very similar to the graph in the Wikipedia article. Although I’m pretty sure the parameters I used made about as much sense as Jim B’s Batman logo, lol!
Sorry, still OT, but one more quick comment on greenhouses.
The place to see the earth’s ‘greenhouse effect’ at work is in a hot desert in summer.
Stand in the sun at 2pm and feel the heat pouring down on you. The temperature will be in the high 40s, maybe even 50 and the sweat will be pouring off you and quickly evaporating. Come back just before dawn and the temperature will be in the low single figures, maybe as low as zero. (You’ll also get a fantastic view of the stars.)
Move west along the same latitude until you cross the mountains and then stand in the sun at 2pm. The temperature will be in the high 30s or low 40s and the sweat will be pouring off you, but now it will not be evaporating. The glass from which you are drinking the cold beverage of you choice will seem to have developed a leak and be dripping on your leg. Come back just before dawn and the temperature will be in the high teens, maybe even low twenties and your glass will still be dripping.
The difference, of course, is the humidity, not the CO2 content of the atmosphere. Water vapour. THE greenhouse gas.
If, instead of spending millions, (billions?), on assesment reports, GIGO models and annual conferences in exotic locations, we had established a network of sensors measuring temperature, humidity and CO2 at hourly intervals, we would by now have maybe twenty years worth of empirical data to play with.
By searching for records where the humidty was the same and the CO2 was higher we could look at the slope of the night time temperature drop, as well as the maximum and minimum temperatures, and maybe find some experimental evidence for the effects of CO2. Anthony and the Steves would have loads of numbers to play with from known sites with known conditions, and if we’d spent a bit more on solar observations, the sun – climate link could have been teased out.
Experiments and reliable data? Nah, it’ll never catch on. Playing with supercomputers and having conferences is the way to do science.
Anna:
Re Gerhard Gerlich and Ralf D. Tscheuschner – Eli provided you with a link to Arthur Smith’s excellent paper refuting much of G&T. Admittedly, however, he doesn’t directly discuss the 2nd law issue.
So, to discuss that: Basically, the deal is that the greenhouse theory does not require the flow of energy from the upper atmosphere to the surface. The greenhouse gases in the atmosphere just reduce the amount of energy that escapes from the surface back into space. You can come up with radiative problems simple enough to give in a first-year physics course that demonstrate the same sort of effect. In fact, if I were a professor (rather than an industrial physicist), I would definitely give my students such a problem on a problem set or exam that would allow them to show that G&T are wrong!
Here is a sample problem that does this: A blackbody sphere S is held at a constant temperature T_S. Then put a blackbody spherical shell A around it. All of this in otherwise empty space. It is easy to calculate the temperature of the shell A due to the balance between the radiation it receives from S and what it radiates back out into empty space. If you then surround this shell A by another blackbody shell B, it is only slightly more difficult to calculate the temperature of both A and B. You will find that B (“the upper atmosphere” in this analogy) has a lower temperature than A (“the earth” in this analogy) and yet A has a higher temperature than it had in the absence of B!
Moral of the story: Conservation Laws (like the Laws of Thermodynamics) are very powerful tools but, like any powerful tool, they can also easily be misapplied.
NOTE: Over on the “Tamino” blog, there’s an application of “Rayleigh’s R” to Figure 5 demonstrating a result different from ours. We are currently looking into the application of Rayleigh’s R distribution to this issue.
Basil and I have discussed it and we agree, it is interesting and challenging at the same time. A central issue is how to correctly identify the peak of the solar cycle, and we are looking at that more closely.
There has been replication of the SSN to HadCRUT surface data link by at least three people, using different methods, including FFT, plus more traditional filters. We are currently exploring those replications along with additional statistical tests and correlations.
Rico,
Regarding filter selection, as several of us have demonstrated, very similar results can be obtained using a variety of filters. As you correctly point out, the selection of the high frequency cut-off is important as there seem to be numerous high-frequency waveforms modulated on the carrier that tend to mask the 22 year cycle if not removed.
Assuming the application of the filter is causing a spurious 22 year cycle to emerge, doesn’t it strike you as odd that this spurious signal happens to be in phase with the solar cycle? Not only that, there are actually two 22 year cycles, 180 degrees out of phase, of different amplitude. The larger amplitude 22 year cycle is in phase with the odd numbered solar cycles, the smaller amplitude 22 year cycle is in phase with the even numbered solar cycles. And , of course, the odd/even solar cycles have opposite polarity (i.e. are out of phase). That is an awful lot of coincidences for a spurious signal.
I don’t think anyone is saying this disproves AGW, just that there seems to be an interesting pattern in the temperature data related to the solar cycle. In fact, the need to plot the derivative of the filtered response to see the pattern would tend to argue against this relationship being the dominant trend in the data. Something else must be causing a significant portion of the positive linear slope over time or the pattern would be visible immediately after filtering without needing to plot dT/dt. That something else could be non-climactic (UHI, data adjustments, equipment changes, etc.) or it could be real (a longer unknown solar periodicity, PDO/AMO, Co2, etc.). Time will tell.
@Pierre Gosselin (aka AGWscoffer)
Re: ENSO and Solar Activity
Before his death in 2004, Dr Theodor Landscheidt made some uncanny predictions of El Nino and La Nina events (2-4 years in advance) based on predictions of solar activity.
The post Anthony refers to is here:
http://tamino.wordpress.com/2008/04/01/how-not-to-analyze-data-part-3/
I’m having trouble with figure 5. Obviously that the graph shows a roughly linear climbing line is of no interest – ascending numbers do that (wouldn’t an entirely different kind of graph be better at showing any correlation or lack there of without the misleading ascent). But aren’t solar cycles 11 year events or there abouts – and then, on the scale you’ve drawn (20 year intervals on the vertical axis), wouldn’t anything other than very closely or consistently aligned plots (the plot for your cycle 11 is in the wrong place by the way) result be needed to even begin to show any kind of correlating trend between the figures at all? As it is, (with even a cursory examination) it would seem as though peaks are variously hit and miss and quite random.
Infact, I’m surprised how uncorrelated the data appears to be.
RE: Jay, we recognize that we need to do a better job with figure 5. We are taking a new approach.
Kim, the Hungarian problem is mostly in assumption g) which simply is not true.
Anthony,
May I offer a hypothesis why the differential in Figure 4 doesn’t peak singularly for cycle 16. Until I give the answer, please be patient by following my line of thought. I have hunch that the influence of the solar cycle on earth’s climate is confounded with the amount of particulate matter (pm) in the stratosphere. I got this idea by looking at Atmoz’s pre-April Fool’s post where he showed the temperature series of the stratosphere and the troposphere. It shows that the stratosphere has cooled significantly in the last 30 years that, in my opinion, are due to less ash from volcanic eruptions and from less pm emitted by countries around the world, particularly the Former Soviet Union and China (the latter due to modernizaton). In other words, when pm reaches the stratosphere due to volcanism and man-made pollution, it heats the stratosphere (by absorption of energy) while at the same time cools the troposphere by shielding the sun. Now that I got your attention, look at the years where cycle 16 occurs – The Great Depression! A drop in worldwide industrial output (and pm pollution) coincided with the peak of cycle 16 to produce the highest temperatures in NA for the 20th century. Also, to answer a prior question regarding why the troughs in Figure 4 are rising for the past 4 cycles, it may be simply that the stratosphere has been progressively getting cleaner.
REPLY: Chris, this makes a lot of sense. Especially since the last total lunar eclipse was said to be “odd looking” due to the atmosphere being so clean.
See this article on the Feb 20th 2008 lunar eclipse:
http://environment.newscientist.com/channel/earth/climate-change/dn13376-lunar-eclipse-may-shed-light-on-climate-change.html
We have something similar in 1998, most of Pinatubo’s dust had settled by then, we had and El Nino, and a solar max coming on.
[snip]
Phil, I’m happy to post your comment, but please try again, perhaps with a “collegial” approach. Thank you for your consideration.
http://rabett.blogspot.com/
As for 1) you are right, I have expressed myself badly. Though “plenty of convection” in the garden greenhouse is true only while it starts heating up (no convection in a hot closed car).
Thank you for the references. I will look into them.
Joel Shore (16:55:44) : My last excursion into thermodynamic problems was back in 1959, I have to open textbooks from back then. I have though the clear summary in my head that thermodynamic laws are valid in all large scale systems. It is only in the microcosm that contradictions may arise, and those are resolved by statistical mechanics.
Now in your example with S, A and B, I have not done the problem, but assuming you are correct, work must be done to keep S into the steady temperature, no? , since it is radiating heat off. I am looking for that “work” in the system “surface heat reservoir”-“troposphere reservoir”, i.e. consistency with the laws of thermodynamics ( which I am sure nature obeys).
Kevin B (16:20:28) :
I am not disputing that H2O mainly is keeping our temperatures temperate, I just would want to see the right thermodynamic framework. Finding it might explain some data, for example why the upper troposphere is not heating up as the IPCC CO2 greenhouse signature demands.
Tony Edwards’ idea of using the best wave recognition system available, our ears, is quite brilliant! My interest in Fourier transforms on this data comes from some work in audio synthesis many years back, and I was joking about God playing sub-bass, but I hadn’t thought of taking it to the obvious conclusion… There’s something deeply romantic about listening to the Earth’s heartbeat (well, one of them, anyway).
But to return to practicalities: If we output the 1900-odd HADCRUT3 samples we’re using at 44.1KHz (CD sampling rate), it would only last about 43ms, so we’d have to loop it, but that’s probably OK as long as we detrend it so the ends match, to avoid a spike at 23Hz. The 11-year cycle would then show up as a 334Hz signal – somewhere around E4 (E above middle C), right where the human ear works best.
I’ll see what I can do…
REPLY: Why not use a lower sampling rate …if doesn’t matter to the data as long as all data is sampled equally. Music of the spheres.
An FFT of your Fig 4:
http://i25.tinypic.com/2884h00.jpg
REPLY: Thanks Bob. Could you elaborate a bit on how you reached this?
‘Also, most commercial greenhouses have a machine in the corner pumping out CO2 to keep the level above 1000ppm. This is not to warm the atmosphere in the greenhouse, but to feed the plants. When the level of CO2 drops below 150ppm, (which it will do by mid-morning if not replenished), the plants will stop growing and if it drops below 90ppm then photosynthesis stops.’~ Kevin B
Kevin, my wife is assistant grower at a local greenhouse (‘Assistant’ meaning, she does All the thinking and most of the work), and she knows whereof you speak!
It is also interesting how quickly a greenhouse can cool off when clouds or the energy screens are in effect. Even in the summer, it can get Cold inside.
Bravo Anthony and Basil!
You have shown a clear correlation between years in two consecutive time series. That’s fabulous! I hope you will publish this soon, hopefully in Nature or Science!
Keep up the good work, guys!
REPLY: Thanks but we need to rework figure 5. The correlation comes out different under other types of analysis.
I believe that correlation is a strong indicator of cause and effect but it is a poor indicator of which case is true. Leading indicators of later events are better for this purpose, especially if the correlation follows a mathematical predictive formula. In my brain research, I was able to say that the peaks I was looking at were mathematically connected to the onset of the pip tone and were frequency specific. I knew how fast these signals traveled from the earphone to the major synaptic junctions because I knew how fast signals traveled along the neural pathway from one junction to the next. Sure enough, all five peaks I found (peaks three through five were known, peaks one and two had not been measured yet or at least reported to have been measured in the literature) were predicted to be exactly in that spot along the time axis based on the onset of the pip and the mathematical calculation of where they should be.
What parts of these smoothed data strings show potential for that kind of predictive relationship between solar events and temperature change? It would seem to me that solar events would predict later temperature change in some kind of mathematical time lag.
Should we be looking at peaks, troughs or slopes for predictive value (thus cause and effect theory that passes the smell test)?
Anthony, I had asked for tabular data for your figure 4 on an earlier post. But I instead took by hand 1 Yr data points off your graph and used the EXCEL Fourier analysis tool.
REPLY: Check your email.
Anthony: Unless you use a ridiculously low sampling rate you are going to have to loop anyway, and it’ll move the decadal cycles out of musical frequencies. Using CD rate is (a) highly convenient for simple generation and (b) has a good auditory rationale (Nyquist = 22Khz, limit of human hearing)
I too would love to know how Bob B gets his great spectrum plot; clearest evidence yet, I’d say… Bob, did you replicate Basils/Anthony’s algorithm from scratch or somehow reverse engineer it from the graph? Then how did you get this plot from the raw FFT? It’s something I’ve been struggling with myself…
Mickeys – this is a model of how not to debate with people constructively. It relieves or indulges one’s feelings, but it does not help or convince them, and this should be the aim of debate. To put matters which one understands better in terms which the other party can both understand and accept. Anything else is self indulgent and counterproductive,
Bob B: Oh, I just noticed you asking for the raw data earlier – that explains it. But I’m still interested to know how you derive the wavelength plot from the raw FFT frequency domain output. I’ve been struggling with the fact that there aren’t enough harmonics to get that level of precision in the wavelength domain – e.g. harmonic 7 of 158 years is a wavelength of 22.5 years, harmonic 8 is 19.75. How do you interpolate the values for 20 and 21 years? Did you vastly pad the data first to get closer harmonics, and then sort the magnitudes into annual buckets?
I’m clearly missing something obvious here…
Anthony writes: RE: Jay, we recognize that we need to do a better job with figure 5. We are taking a new approach.
Actually, I don’t think the problem is just with figure 5. If you take each of your Hadcru peaks from Fig. 4 and calculate the actual phase of the solar cycle, they’re more or less randomly distributed. There doesn’t seem to be any significant clustering around the peaks, when you analyze the actual numbers.
I’m afraid that a lot of the commentary in this thread is missing the point.
REPLY: We are going through different methodologies to evaluate more rigorously. If you have suggestions, feel free to pass them along.
Paul Clark, thank you for appreciating my suggestion. Further to it, what I had in mind was even simpler than you suggested and that was to use an ordinary amplifier system and feed in a voltage scaled to the monthly or yearly data, without smoothing or messing about with it, maybe using a digital to analogue converter. I figured that if looking for a 22 year then you would want to vary the signal at a rate which would produce, say a 22 hertz signal for the 22 year cycle, so, apply the voltage at a 22 year per second and you would get a song 6/7 seconds long. This might actually be long enough to provide hearable sounds. Maybe quicker would be better, but that would reduce the listening time. I’d try it if I had any gear like that, but those days are 40 years ago. I hope something comes of it.
Das lied von der erde?
You’ll have to eliminate noise from volcanoes. The oceanic oscillations may or may not be in phase with the solar cycles, and we have poor historical data about them, so how to treat them is problematical. I’m almost certain that if there is lag in the oceans, it may vary, further compounding your search for correlations. But I believe there is a survivor, lost in the fog, and it’ll be found, eventually, if there.
===============================================
Thinking further on the Rayleigh R and the angle of the SS cycle. 0 to pi is 0.382 of the cycle, pi to 2pi 0.618, on the average. The cycle is not a true sinoid. Each cycle calculation needs separate treatment.
I’m living apart from my library but I’ll wildly guess polar coordinates might be more convenient.
If Tamino (or his Svengali) got the significance criteria right, I’ll bet the method, competently applied, gives roughly confirming results to Basil’s simpler, original approach at a cost of multiplied doubts (the eyeball method).
Hi Gary,
Last night before your private email, I found a method that would evaluate each cycle separately. We are in sync. Thanks very much for the ideas.
“Thinking further on the Rayleigh R and the angle of the SS cycle. 0 to pi is 0.382 of the cycle, pi to 2pi 0.618, on the average. The cycle is not a true sinoid. Each cycle calculation needs separate treatment.
I’m living apart from my library but I’ll wildly guess polar coordinates might be more convenient.
If Tamino (or his Svengali) got the significance criteria right, I’ll bet the method, competently applied, gives roughly confirming results to Basil’s simpler, original approach at a cost of multiplied doubts (the eyeball method).”
No it won’t, it’s quite clear from Fig 5 that there is a considerable variation in phase shift between the points. For example look at the shift for the first 4 points (allowing for the error on series 11) it’s opposite to the shift on the last three! Proper analysis will show no correlation between the two series, hopefully you’ll post this comment this time.
Anthony – thanks for posting Tamino’s comment with the link to his analysis. He has done some interesting work, as you acknowledge in your comments regarding the shortcomings of figure 5. I appreciate your willingness to take the criticism seriously, even if it wasn’t offered in the most constructive fashion. Once this hurdle is cleared, I’m sure the filter selection question will again arise. I’ve done some work comparing the impulse response of numerous filtering methods and the effect on the data. Upon completion, I’ll forward it if you are interested.
REPLY: Yes by alll means I’d love to look at it.
I have been looking at solar flare data: numbers and magnitude on a monthly basis. Nice wave pattern to it. There are peaks, slopes and troughs with an overall decline since spring of 06. I have eye-balled noticed that when flares drop below “M” class, so does the temperature data. When flares have risen to “M” and “X” classes in the same month, so does the temperature. Since M and X class solar flares eject material at near light speed, the time it takes to reach earth’s upper atmosphere is quite short but can be calculated.
Based on the wave pattern I am seeing in just a year’s worth of data, I am wondering if this data has long-term cycles as in decadel or even bidecadel, ultra long-term cycles as in millenial, and short term cycles as in seasonal, that can be filtered to show these patterns.
I am also wondering if this data has a mathematical predictive nature to temperature fluctuations and change patterns. I like things I can measure in time from signal onset to effect. Maybe that is why I am seeing a possible pattern.
REPLY: I ahve no idea about flare data, I have not studied it at all – Anthony
re: flares
There was a spike to X class flares in Dec 06 and then a spike in global temp around Jan 07. There were M class flare spikes in Apr 06 and in July 06, and then there were two temp spikes around the same time (I am only eyeballing graphs, not data tables).
hmmmmm
In terms of a different analysis for Figure 5, I would just start with the time each temperature cycle and each solar cycle peaks and the difference between the two.
Tamino’s analysis is specifically chosen to appeal to his readers (as always). It is not designed to see if there is a real correlation between the two. it is designed to throw you off (as always.)
If the average difference is less than 2 years (preferably closer to less than 1 year), then you really have something.
Plot the average difference in time between the two maximums versus time. If it is a scattergram congregating around a zero difference over time (with very few outliers above +/-2 years) then you have something. If the scatter shows a trend over time (2 cycles above zero, then 2 cycles below zero) then you have another thing.
Add the solar and temperature minimum correlations to the mix and you really, really have something.
Note that there will be outliers caused by the ENSO given its large impact (unless the trade winds and Kelvin waves are also driven by the solar cycle which will result in even the ENSO outliers matching up.) Volcanoes wil also impact the outliers, specifically Tambora in 1815, Krakatoa in 1893, and possibly El Chichon in 1984 and Pinatuba in 1991.
Have you guys looked at the Scafetta and West paper on solar and climate correlation; they seem to think there is a match for very short periods, not just the Schwabe and Hale cycles; they have developed a methodology specifically to counter random and non-gaussian accusations like Tamino has thrown at you. The link is: http://www.fel.duke.edu/~scafetta/pdf/opinion0308.pdf
REPLY: Yes we are all over that paper, thanks
To all of you posting on this blog,a million thanks for what you do.I am a truck driver from Southern California with only a highschool education but lots of curiosity.As I watch all the lemmings run off into the nonexistant Global warming sea,I am astonished at their religious like zeal in ignoring the plain truth in front of them.My only wish is for a layman’s paper explaining all this so that I can better communicate the truth to all who will take five minutes and listen to reason.Again thank you so very much for all your effort.Sincerely,
Bob Kendall
REPLY: Thanks Bob, here is one I can recommend for you done by a friend, Warren Meyer.
http://www.climate-skeptic.com/2008/01/my-best-skeptic.html
Bob, this link also is worth reading for a simplified view of the controversy:
http://www.middlebury.net/op-ed/global-warming-01.html
re: the paper you are all over
Solar flare data in table format (including plottable format) can be had at http://www.ngdc.noaa.gov/stp/SOLAR/ftpsolarflares.html
Average global temperature data can be had at
http://www.data360.org/dsg.aspx?Data_Set_Group_Id=1655
I wonder if solar flares are like God pointing a big finger at the source and cause of Earth’s temperature fluctuations. God even has a neon sign called the Northern Lights advertising the damned thing.
By the way, that big spike in temperature in Jan of 07 was preceded by 4 HUGE flares (X class), all in Dec 06.
Anthony
re: the Duke paper you are all over
Solar flare data is VERY interesting. I assume you know where to find the plottable formatted data?
REPLY: We’ve only been concentrating on SSN’s Thanks for the suggestion and for the link in the prior post. It ended up in the spam filter due to the embedded URL’s
Cohenite:
What about Taminos post is “random and non-gaussian accusations”? Didn’t you understand it, or did it simply go against your belief even if it is mathematically rigid? The whole point is that it shred the correlation between solar cycles and temp. rise to pieces. And that was what this post was all about.
Having said that, I appreciate that Watts has acknowledged that they are off the mark and currently try to improve their methodology. I guess they have already stumbled across it, but if not, what about using wavelets? It accounts for frequency change in time, as do not Fourier analysis.
Sorry to be a pest, but I presume you guys are familiar with Tung and Camp’s model-independent approach to climate sensitivity to solar fluctuations; that being the case, how do you think this non-model approach marries with Miskolczi’s realistic atmospheric model? I first considered Miskolczi as a complement to CO2 saturation processes, but on reflection Miskolczi seems to add something to feedback chronology, which is an issue that Real Climate base their critique of Scafetta’s paper. In respect of climate relaxation times, Stephen Schwartz has taken a, in retrospect, self-evident approach to planetary climate equilibrium sensitivity as a means of isolating temperature rises due to increased CO2 forcing. Do you guys have an opinion on this?
Could you comment on the attached from the UK’s Daily Telegraph ?
It seems to be concentrating mostly on the Svensmark hypothesis but goes on to include some standard AGW stuff, the IPCC states that………
http://www.telegraph.co.uk/earth/main.jhtml?xml=/earth/2008/04/03/scisolar103.xml
Phil,
There is no pertinence to the term ‘phase shift’ in the present context, Basil and Anthony are measuring the departure in time at SSN max of DT/dt^2 = 0 at the positive extrema. In no way are they attempting to measure, in their present study, phase relations between the solar cycle and any terrestrial cycle.
Obviously that correlation might be estimated by any number of methods and interested observers are grateful Tamino passed on on one, Raleigh’s R, that, though difficult to implement accurately here, might be useful.
What interests me in the short run is a visual comparison of the solar cycle, PDO/AMO cycles, and ‘global temperature’, the last being the most problematic data set for what it might imply about the actual energy being delivered over the past 200 years, a Gleissberg cycle.
One should be careful to analyze for oneself and not depend too closely on gadflies like Hansen’s Bulldog; his enthusiasm outstrips his talent.
Onanym:
I think you might start a blog devoted to ‘Dadaism and the discipline of automatic writing’ and find more Tamino fans than encountered here.
Oh, my DT/dt^2 above is supposed to mean second derivative of global Temperature with respect to time.
Gary,
So the question goes to you as well; what in Taminos analysis is wrong in you opinion? Keep to the question, or don’t comment on my comments. At least stay close to polite.
With respect to automatic writing, count the number of comments here saying something along the lines “I don’t know much math, but this seems convincing to me”.
And the phase has everything to do with the present analysis since it’s correlating the timing of two oscillating signals.
And to be very picky: second derivative is normally written d^2T/dt^2. Being even more picky, DT/Dt (note big letters) is normally reserved for the substantial derivative.
Bill Illis:
If your scatter analysis comes out with clusters both before and after the timing of the temp, then you have no causality. I could of course be very wrong in that, if so, please explain why.
I am not of the Sun school. However, if you want to acertain the sun’s influence you have to figure a way of getting volcanic forcing ( at least) out of the record
volcanoes are basically shot noise. I think Tammy had a post on how to back their contribution out of the time series. So back out ( remove) the volcano jolts and then see what you have.
REPLY: They won’t just show up as “shots” or spikes in the temp record, more like the pulse followed by the right side trailing slope of a gaussian curve as particulates settle.
To Onanym, ideally the scatter would produce solar cycles which lead the temperature cycle by a short period of time. But the climate is also randomly variable and the sunspot solar cycle does not always equate directly with total solar energy received by the Earth so there is likely to be both positive and and negative lags in the two maximums.
Anthony,
The Institute of Physics has published a short paper this week that argues there is weak or no statistical confirmation of the link between cosmic ray ionization (due to reduced solar flux) and low-level cloud formation.
Paper here
REPLY: Thanks Peter, I was aware of it but had not hunted down the PDF just yet. I appreciate you providing it and saving that trouble. I’ve briefly scanned it, and I have a couple of problems with it and the author, Sloan.
1) In this is the paper’s conclusion:
On the surface it seems the time scales of the effects they looked at and what Svensmark proposes are vastly different. They are looking at Forbush decrease for the signatures, but they are short period events (hours/days) compared to the much longer GCR modulation by long period changes in the suns’s magnetism, which is said to be the driver.
It just seems disconnected. Maybe I’m missing something, but it seems to me that you can’t draw a conclusion about something that operates on timescales of years to short period events lasting hours or days.
2) In the interview Sloan gave to BBC he said:
Now I don’t know if he was misquoted or not, but particle bursts/CME’s (and resulting Forbush decrease) from the sun are an entirely different thing than GCR modulation by the suns magentic change over a long period.
Asked to comment, Svensmark said in the BBC article:
If Sloan was looking for correlation between charged partcle bursts instead of GCR’s I’d have to agree with Svensmark. We’ll see how it all shakes out. Maybe the BBC just did another crappy job of reporting a science interview and that’s not what he said at all, but it sure seems odd.
Here’s another paper that looks at the much larger view of GCR modulation:
http://www.griffith.edu.au/conference/ics2007/pdf/ICS176.pdf
Yes. Spike followed by a fall off. These events pin the negative
excursions. Not sure what that does. just an observation.
Onanym
“it shred(s) the correlation between soalr cycles and temp. rise to pieces.”
Bold words. My wife has the mathematical nouse in this household; she understood Tamino’s rebuttal; she didn’t like his George Clooney attitude, but that goes with the territory. I’m just a humble lawyer trying to make a killing from the carbon-trading gravy train before Joe Public realises he has been sold a pup and the whole thing goes belly-up.
Fourier can still be useful; Watts have concentrated on 2 cycles, Schwabe and Hale, with a nod at a 60-70 year periodicity; they have used Javaraiah’s work on the Hale cycle, but Javariah has also done a paper on a 17 year solar cycle; since the solar influence is variably constant, any analysis should cover all cycles, with a reasonable assumption being that climatic discrepancies that statistically fall outside those periods are the result of either lag or unknown cycles or combinations. The Watts’ analysis was brave but deficient in content perhaps.
I posted this also on the sunspot page. Take a look at this link:
http://www.griffith.edu.au/conference/ics2007/pdf/ICS176.pdf
This predicts that the next minimum period is imminent and may be as pronounced as either the Daulton or Maunder.
This is a totally different approach than the solar scientists have used to predict an unusually/unprecedented low level of activity in cylce 25 – but both forecasts are pointing to the same result.
Basil and Anthony great work. The results are astounding. As an electrical engineer I fully appreciate what you have done, it’s what we have been doing with signal analysis for years. A really ground breaking application of the technology.
Output the temperature with a DSP and do a Fourier transform analysis on the signal. Never know what you might find … If anyone has a copy of Mathematica, I believe it will do the work for you.
oops – didn’t realize that was previously posted. Sorry
Mosher’s comment re “shot” has to do with the incidence of the actual explosions themselves. That they happen irrespective of the sun or of AGW. Modelling the temp effect as a trailing off from the events is fine. But the attempted correction to Mosh’s point is off.
Basil (several posts back):
A. I’m not sure of the semantics. In any case, my sense is that correlation analysis and your choice of axes and such is off. I think this has been well pointed out to you by now by others with more description. I’m not a “jock”, but I could sense right away that there was a fundamental flaw in your method.
B. I don’t know a better method of comparing cyclicality. I have asked this question as well. I think you should research this in books and with experts. I’m sure that it is a type of problem that has been thought about and that there are some good methods and caveats on usage and stuff. Your work to date is obviously very preliminary and the comments on publishing, etc. were “off”. It’s fine to “doodle”. But at least appreciate that you are doodling when you do so. And then go and learn the basics of what techniques are needed to use on your particular problem. Do that before publishing or even before overly promoting your work. (BTW: you worry me a bit with some of your tone. You seem to be a bit pompous in language, etc. but not to really be a critical thinker. Please work on that.)
C. ‘the peaks are interesting but come out with higher level filtering’.
1. Well, in the filter you DID use, the peaks were there. So they should be included in figure 5.
2. Why the comment on filters in commentary, but not in the initial headpost (draft publication)? Do you appreciate that points like this should be raised as part of the publication itself?
3. It just scares me to hear things like use more filtering to remove peaks.
4. Doing numerical correlation analysis on smoothed data is a dangerous thing. One that we criticize AGWers for.
REPLY: TCO, using a better “wrapper” these days I see. Good on you!
I was kinda iffy on Tammy’s raleigh R. Ah well first off I liked the measure
but I was not so sure how a spatial measure did in the temporal domain. That’s not a criticism just a quizicism. It would be good to test if that method was robust in this kind of application. Open question.
The entire issue of “correlating” through whatever measure, the sunspot maximum with the surface temp dt, seems on reflection to be a snipe hunt of sorts.
Surface temps ( as collected by Jones and cru and hansen and crew) are noisy bits of the record. If you think that SSN correlates in some way to the HEAT of the planet, then look at SST. It’s a big old capacitor and all the high freq crap is filtered out.
Looking at hadcrude or gimptemp ( jokes intended) you are just introducing unnecessary noise.
Look at SST. a thought.
AW here is a thought.
Do a reconstruction.
Gary, you said: “There is no pertinence to the term ‘phase shift’ in the present context, Basil and Anthony are measuring the departure in time at SSN max of DT/dt^2 = 0 at the positive extrema.”
However the following quote shows that B & A are indeed trying to assert that the two curves are in phase.
“The strong degree of correspondence between the solar cycle peaks and the peak rate of change in the smoothed temperature trend from HadCRUT surface temperature data is seen in Figure 5.”
However the form of plot they used hides the actual lack of correlation between the timings of the peaks.
“One should be careful to analyze for oneself and not depend too closely on gadflies like Hansen’s Bulldog; his enthusiasm outstrips his talent.”
Some of us are able to think for ourselves Gary!
Phil and Mosher:
I’m at best a jack of all trades and master of none and am obliged to defer to those like Mosher who obviously work often in the area.
My abiding belief here is that stats are inappropriate (ICA excepted) for the determination and evaluation of causation, and I believe Phil, J, and Tammy are expecting Basil and AW to prove that to which they do not aspire, a correlation of cyclic phenomena tantamount to causation.
A couple of relevant observations of current practice:
MBH98 proposed to combine temperature proxies, e.g., the Bristlecone series, by means of PCA, to replace existing proxies with less precision, e.g., 10Be, and temperature data. The latter because the record was essentially NH only.
It would have been entirely plausible to do a PCA on the BC data, separating into factors (H20, C02, Temp), creating a polynomial fit and then doing phase analysis in a calibration of the resulting fit with the local temp.
This was not done or imagined. This despite the intent to recreate a reasonable facsimile of the temperature curve, a continous record!
Phase analysis wasn’t undertaken with the composite proxy! And some of the MBH98 supporters are here engaged.
Svalgaard and Cliver (2007?) have proposed correcting historic SSN data with Geomagnetic data. Neither are physical quantities, but statistics themselves. Indeed, SSN are discontinuous taking no value between 0 & 11.
The former are the direct result of torodial fields near the Suns surface, presumably bathed in the polodial field. The later are the effect at 93 million miles of the highly ‘twisted poloidal field’ of orginating some days earlier. In addition the Geomagnetic measure is highly effected by UV, a highly volatile factor.
It would have been perfectly plausible that the SSN and Geomagnetic data be evaluated for phase consistency since the object was to correct SSN data.
This was not done or imagined.
I’m not arguing against hypocrisy here. Basil and AW are measuring a feature of the data. Many of their critics are manifestly out of their depth in their analysis.
Just happened to have three annual mean temperature graphs of Mauritius, N. Colombia and Zinder, W. Africa from 1951 onwards; you would be surprised to see how closely the peaks and troughs match those on fig. 4!
Mosh, thanks for the suggestions.
Capacitor, indeed. I love capacitors. Especially those big honking 1 farad ones you can buy now.
aw the big issue with the gsmt record is the year to year noise. this will give you a very noisy estimate of dt. sst might be better, but check.
one way to think about it is this. if you had zero trend and noise with a 1 deg sig
your year to year delta can be huge. swinging from 1 sig down to one sig up would imply a rate of 2 times the 1 sig value.
Excellent work gentlemen! There is a wonderful elegance about using differentials. After all, weather and climates are not driven by absolutes but by differences, and it seems apropos that the sun’s relationship to our climate also be related in this manner.
Thanks again and Godspeed in getting this published!
[…] week, when Basil and I posted Part 2 of our series on seeing a solar imprint in the HadCRUT temperature record, it spawned a lot of interest, debate, replication, and criticisms. One of the criticisms from […]
Very good work.
Now if you can determine the extent of solar radiation on global mean temperatures you will be closer to testable predictions.
TCO:
“BTW: you worry me a bit with some of your tone. You seem to be a bit pompous in language, etc. but not to really be a critical thinker. Please work on that.”
Pot, kettle, … ?
I love following wherever the trail leads. I have no pre-conceived notion about warming other than the cancer scar on my lip. For that, I must admit, I have a bone to pick with the sun and its rays.
My first thought about global warming was the result of my skin heating up and burning (I am a redhead so I burn ALL THE FRIGGIN TIME) when the sun is shining bright. From there I naturally thought that when the sun was hot, I was hot. Therefore the temperature around me was hot. If the sun stayed hot with little time spent in slumber, I just figured that the temperature rise was due to a hot sun. However, if that were the case, we would have seen this simple relationship long ago and there would be no Al Gore movies.
Apparently this is not the case because we have Woody Al stiffly describing the devastating affects of the stuff we all breath out.
But at least I was given the opportunity to see peaks. . . .Then I started looking at valleys. From there I started looking at what the sun was doing during the valleys. Man, was I surprised. Here is what it is doing when it sleeps: It is NOT protecting us from some very damaging rays. Not only did I get a hole in my lip, but our blanket in the sky is being eaten alive by that seemingly quiet, passive sun. So I have come full circle. The scar on my lip can probably be blamed on solar MINIMUMS, not maximums. What else can we add to the rap sheet of the sun when it looks oh so peacefully quiet?
Hey Pamela, I’m sorry to read about your scar and I hope it goes okay for you (presumably it wasn’t malignant!). In your case, you could blame genetics as much as the sun ;).
It’s true this simple relationship hasn’t been seen before, more than likely because nobody bothered to look. But you know, apparently there is nothing new under the sun. So it goes.
[…] the reply from Svensmark Here’s another from Ken Gregory and here’s another from Anthony WattsObviously you won’t spend any time reporting on them, because life’s too short isn’t it […]
Frank Ravizza: Good post. I’m not much of a physicist, but when I took physics, we learned that moving a conductor in a magnetic field produced a current. The Earth’s core is a conductor, yes? Is there a pole-to-pole terrestrial dynamo current? If so, how large? And what part would the semi-conductive crust and the conductive oceans play in this?
Basil & Anthony: Interesting, but based on a friendly argument at SC24, I’m leery of H-P smoothing. I hope you find an appropriate [non-derivative-based] function set that will allow correlation, rather than peak matching.
Pamela Gray: My turkey cooling theory: Heat rises; cold doesn’t. A warm turkey in a cold box will set up a convection pattern with the hot turkey air rising and then being cooled and recycled back from bottom to top again. No such convection cell exists with a cold turkey in a 70°F room–the hot air will not come down from the ceiling and flow over the turkey. Makes sense?
Thanks for this insight,I appreciate the info
That ‘s quite a unequaled point of view, not ever really thought of that. Resplendent article .