Guest Post by Willis Eschenbach
I thought I was done with sunspots … but as the well-known climate scientist Michael Corleone once remarked, “Just when I thought I was out … they pull me back in”. In this case Marcel Crok, the well-known Dutch climate writer, asked me if I’d seen the paper from Nir Shaviv called “Using the Oceans as a Calorimeter to Quantify the Solar Radiative Forcing”, available here. Dr. Shaviv’s paper claims that both the ocean heat content and the ocean sea surface temperature (SST) vary in step with the ~11 year solar cycle. Although it’s not clear what “we” means when he uses it, he says: 
“We find that the total radiative forcing associated with solar cycles variations is about 5 to 7 times larger than just those associated with the TSI variations, thus implying the necessary existence of an amplification mechanism, though without pointing to which one.” Since the ocean heat content data is both spotty and incomplete, I looked to see if the much more extensive SST data actually showed signs of the claimed solar-related variation.
To start with, here’s what Shaviv2008 says about the treatment of the data:
Before deriving the global heat flux from the observed ocean heat content, it is worth while to study in more detail the different data sets we used, and in particular, to better understand their limitations. Since we wish to compare them to each other, we begin by creating comparable data sets, with the same resolution and time range. Thus, we down sample higher resolution data into one year bins and truncate all data sets to the range of 1955 to 2003.
I assume the 1955 start of their data is because the ocean heat content data starts in 1955. Their study uses the HadISST dataset, the “Ice and Sea Surface Temperature” data, so I went to the marvelous KNMI site and got that data to compare to the sunspot data. Here are the untruncated versions of the SIDC sunspot and the HadISST sea surface temperature data.
Figure 1. Sunspot numbers (upper panel) and sea surface temperatures (lower panel).
So … is there a solar component to the SST data? Well, looking at Figure 1, for starters we can say that if there is a solar component to SST, it’s pretty small. How small? Well, for that we need the math. I often start with a cross-correlation. A cross-correlation looks not only at how well correlated two datasets might be. It also shows how well correlated the two datasets are with a lag between the two. Figure 2 shows the cross-correlation between the sunspots and the SST:
Figure 2. Cross-correlation, sunspots and sea surface temperatures. Note that they are not significant at any lag, and that’s without accounting for autocorrelation.
So … I’m not seeing anything significant in the cross-correlation over full overlap of the two datasets, which is the period 1870-2013. However, they haven’t used the full dataset, only the part from 1955 to 2003. That’s only 49 years … and right then I start getting nervous. Remember, we’re looking for an 11-year cycle. So results from that particular half-century of data only represent three complete solar cycles, and that’s skinny … but in any case, here’s cross-correlation on the truncated datasets 1955-2003:
Figure 3. Cross-correlation, truncated sunspots and sea surface temperatures 1955-2003. Note that while they are larger than for the full dataset, they are still not significant at any lag, and that’s without accounting for autocorrelation.
Well, I can see how if all you looked at was the shortened datasets you might believe that there is a correlation between SST and sunspots. Figure 3 at least shows a positive correlation with no lag, one which is almost statistically significant if you ignore autocorrelation.
But remember, in the cross-correlation of the complete dataset shown back in Figure 2, the no-lag correlation is … well … zero. The apparent correlation shown in the half-century dataset disappears entirely when we look at the full 140-year dataset.
This highlights a huge recurring problem with analyzing natural datasets and looking for regular cycles. Regular cycles which are apparently real appear, last for a half century or even a century, and then disappear for a century …
Now, in Shaviv2008, the author suggests a way around this conundrum, viz:
Another way of visualizing the results, is to fold the data over the 11-year solar cycle and average. This reduces the relative contribution of sources uncorrelated with the solar activity as they will tend to average out (whether they are real or noise).
In support of this claim, he shows the following figure:
Figure 4. This shows Figure 5 from the Shaviv2008 paper. Of interest to this post is the top panel, showing the ostensible variation in the averaged cycles.
Now, I’ve used this technique myself. However, if I were to do it, I wouldn’t do it the way he has. He has aligned the solar minimum at time t=0, and then averaged the data for the 11 years after that. If I were doing it, I think I’d align them at the peak, and then take the averages for say six years on either side of the peak.
But in any case, rather than do it my way, I figured I’d see if I could emulate his results. Unfortunately, I ran into some issues right away when I started to do the actual calculations. Here’s the first issue:
Figure 5. The data used in Shaviv2008 to show the putative sunspot-SST relationship.
I’m sure you can see the problem. Because the dataset is so short (n = 49 years), there are only four solar minima—1964, 1976, 1986, and 1996. And since the truncated data ends in 2003, that means that we only have three complete solar cycles during the period.
This leads directly to a second problem, which is the size of the uncertainty of the results of the “folded” data. With only three full cycles to analyze, the uncertainty gets quite large. Here are the three folded datasets, along with the mean and the 95% confidence interval on the mean.
Figure 6. Sea surface temperatures from three full solar cycles, “folded” over the 11-year solar cycle as described in Shaviv2008
Now, when I’m looking for a repetitive cycle, I look at the 95% confidence interval of the mean. If the 95%CI includes the zero line, it means the variation is not significant. The problem in Figure 6, of course, is the fact that there are only three cycles in the dataset. As a result, the 95%CI goes “from the floor to the ceiling”, as the saying goes, and the results are not significant in the slightest.
So why does the Shaviv2008 result shown in Figure 4 look so convincing? Well … it’s because he’s only showing one standard error as the uncertainty in his results, when what is relevant is the 95%CI. If he showed the 95%CI, it would be obvious that the results are not significant.
However, none of that matters. Why not? Well, because the claimed effect disappears when we use the full SST and sunspot datasets. Their common period goes from 1870 through 2013, so there are many more cycles to average. Figure 7 shows the same type of “folded” analysis, except this time for the full period 1870-2013:
Figure 7. Sea surface temperatures from all solar cycles from 1870-2013, “folded” over the 11-year solar cycle as described in Shaviv2008
Here, we see the same thing that was revealed by the cross-correlation. The apparent cycle that seemed to be present in the most recent half-century of the data, the apparent cycle that is shown in Shaviv2008, that cycle disappears entirely when we look at the full dataset. And despite having a much narrower 95%CI because we have more data, once again there is no statistically significant departure from zero. At no time do we see anything unexplainable or unusual at all
And so once again, I find that the claims of a connection between the sun and climate evaporate when they are examined closely.
Let me be clear about what I am saying and not saying here. I am NOT saying that the sun doesn’t affect the climate.
What I am saying is that I still haven’t found any convincing sign of the ~11-year sunspot cycle in any climate dataset, nor has anyone pointed out such a dataset. And without that, it’s very hard to believe that even smaller secular variations in solar strength can have a significant effect on the climate.
So, for what I hope will be the final time, let me put out the challenge once again. Where is the climate dataset that shows the ~11-year sunspot/magnetism/cosmic rays/solar wind cycle? Shaviv echoes many others when he claims that there is some unknown amplification mechanism that makes the effects “about 5 to 7 times larger than just those associated with the TSI variations” … however, I’m not seeing it. So where can we find this mystery ~11-year cycle?
Please use whatever kind of analysis you prefer to demonstrate the putative 11-year cycle—”folded” analysis as above, cross-correlation, wavelet analysis, whatever.
Regards,
w.
My Usual Request: If you disagree with someone, myself included, please QUOTE THE EXACT WORDS YOU DISAGREE WITH. This prevents many flavors of misunderstanding, and lets us all see just what it is that you think is incorrect.
Subject: This post is about the quest for the 11-year solar cycle. It is not about your pet theory about 19.8 year Jupiter/Saturn synoptic cycles. If you wish to write about them, this is not the place. Take it to Tallbloke’s Talkshop, they enjoy discussing those kinds of cycles. Here, I’m looking for the 11-year sunspot cycles in weather data, so let me ask you kindly to restrict your comments to subjects involving those cycles.
Data and Code: I’ve put the sunspot and HadISST annual data online, along with the R computer code, in a single zipped folder called “Shaviv Folder.zip“
Speaking of the global ocean’s deep layer, thermocline and mixing layer, it would be interesting to speculate that the mixing layer is the thing expanding up, not the deep layer. If that is the case, the rising sea level would all be due to a warming of the mixing layer since at least the LIA. If the thermocline level, measured from the perpendicular ocean bottom to the thermocline, averaged out to be at the same level, but the mixing layer on top of it is rising, the case would be nearly open and shut that sea level is not rising due to more water being added to the oceans, but to heat expansion in the mixing layer. If that is the case, projected sea level rise, which is currently considered to be anthropogenically related to added water due to melting land ice and ground water extraction, would necessarily have to change to a metric based on LIA-related, if not the last glacial period, heat rise expanding the mixing layer and little else.
Of the issue related to melting land ice, a good deal of that melting ice goes into the ground, potentially offsetting any increased ground water extraction. So that part of the equation can possibly be ignored under the anthropogenic hypothesis.
How to stop complete analytic foolishness that ensues from simplistic
presumptions?
A good starting point should be the recognition that the m-lagged sample
cross-correlation function
ccf(m) = cov(x,y;m)/(sigx*sigy)
does NOT have the same straightforward meaning that it does in ordinary
linear regression of time-invariant data. The power spectra of the
data-series comes into play via their effect upon the normalization
sigx*sigy, which is independent of inter-relationship, while the covariance
is not! In fact, it expresses in the lag-domain the average time-varying
characteristics ONLY of variously related signal components, which may be
in entirely different frequency ranges. Proper interpretation
of the sample ccf thus requires complete SPECTRAL knowledge of both data
series.
Among the many misconceptions that novices make in viewing sample ccfs is
that low correlation at zero-lag indicates little relationship between
series. That is true ONLY IF there are no time-lags involved. But
physical systems often display phase-lag between excitation and response!
With 90 degrees systematic lag, the ccf at zero lag is zero for purely
sinusoidal forcing. The analytic fact that the ccf maximum then occurrs at
a quarter-cycle lag in that simple case leads to another egregious
misconception: that the ccf maximum indicates some physically meaningful lag
relationship in the general case with continuous power densities. Only if
one data series is shifted wholesale by a constant to produce the second
series can such a conclusion hold.
To obviate such pitfalls, competent analysis of signal relationships relies
upon cross-spectral methods . Defined by the Wiener-Kintchine theorem
as the F. transform of the covariance function, the cross-spectrum is
complex-valued. Its real part is the co-spectrum C(f), obtained by the
cosine transform; its imaginary part is the negative of the
quadrature-spectrum Q(f), obtained by the sine transform. The crucial
information about signal relationships in the general case that
cross-spectrum analysis provides for each frequency-band is the squared
coherence:
R^2 = (C^2 + Q^2)/(Sx*Sy)
where the S denote the power spectra of the individual data series. The
confidence intervals for this vital metric–a spectral analog of simple
R^2–have been tabulated by Amos & Koopmans for various degrees of freedom
of spectral estimation. The relative phase between coherent signal
components in the same frequency band is given by:
phi = arctan (-Q/C)
Obtaining valid sample estimates of these quantities is nowhere near as
simple as merely utilizing the complex FFT coefficients of the ccf out to
lags of half the data length. It does require, however, the ccf values far
beyond what has been shown here in Figures 2 and 3. Cross-correlating SSN data with red noise simulations might obtain spurious max values comparable to what is seen there, but it could never obtain the 99% confidence in coherence levels shown by competent cross-spectrum analysis.
The highly significant coherence in a narrow band between SSN and SST can scarcely be revealed by the simplistic methods used in this post. If they were used in other contexts where detection of weak signals is vital, we would have no cell-phone communications, nor Dolby noise reduction, and enemy submarines with ballistic missiles (truly bad SSNs) would lurk totally undetected in our coastal waters.
Willis Eschenbach says:
June 12, 2014 at 11:48 pm
Why are you so studiously ignoring the many citations that mention the ~11 year cycle right in the title of the papers?
If there is garbage and rubbish being strewn around this comment section, clearly it’s from your direction. Along with shamefully dodging the valuable material and hiding behind ad hominems.
1sky1 says:
June 14, 2014 at 2:21 pm
I know you were punning, but a nuclear powered ballistic missile sub or “boomer” in the USN (“bomber” in the Royal Navy) is an SSBN. SSN is an attack sub (“fighter” in the RN).
As a Navy Reserve MD, I’m familiar both with designations and with the remarkably high CO2 levels on subs.
Catherine Ronconi says:
June 14, 2014 at 2:58 pm
Why are you so studiously ignoring what I said to you when you asked that question last time? To remind you, it was:
w.
Willis Eschenbach says:
June 14, 2014 at 10:00 pm
Pick any one you want. Your request for specific selections from among the many offered was already answered. Pick any of these. But to support your unfounded assertion that there is no evidence of an 11 year cycle, you’ll need to examine all of the studies that have found it.
Why do you expect everyone else to do your literature searches for you? Instead of attacking us for “piling up garbage”, why don’t you do what real science paper writers do & conduct an exhaustive literature search before making baseless assertions?
This is what got you in trouble with Roy Spencer and causes you to claim to have discovered phenomena already well known to real scientists. Your published “paper” violated one of the key rules for scientific article writing so well summarized on this blog by Pamela Gray, ie a review of literature. You must know that that is standard practice, since in your “paper” you state that you’re not following the usual rules.
Are you too lazy to conduct thorough searches, or afraid of what you’ll find? Or are you cutting corners in hopes of trying now to have a scientific career late in life? Real scientists have classes to teach and other demands on their time, so you can’t plead that your work keeps you from doing an adequate review before making baseless assertions. If it’s your illness, I’m sorry, but you should not make bold claims without any basis, which by the nature of your assertion requires that you look at every study you can find before so asserting.
The citations reproduced here are just a few of the many papers you need to read and analyze before you can even begin to claim there is so 11 year signal in climatological observations. It’s against the scientific method to assert a claim, then expect everyone else to do your research for you.
Here are some of the studies previously cited here & so studiously ignored by you:
1) Rigozo et al. (2002) detected an 11-year cycle in tree-ring width data from Brazil over the period 1837-1996; and Black et al. (1999) reported finding a 12.5- to 13-year signal of climatic variability in the North Atlantic Ocean over the past 825 years. Additionally, Dean et al. (2002) found an approximate 10-year cycle in a lake sediment core obtained from Elk Lake, Minnesota, USA, covering the past 1500 years. Both Rigozo et al. and Dean et al. implicate the sun as the likely source of the approximately 11-year periodicity noted in their records. Black et al. are less enthusiastic about this possibility, but they feel the sun is responsible for driving centennial-scale climate oscillations in their record.
2) In an analysis of tree-ring chronologies from northeastern Mongolia, Pederson et al. (2001) report “possible evidence for solar influences” on the regional hydrologic cycle. For the period 1651-1995, they reconstructed annual precipitation and streamflow histories for this region, which upon subjection to spectral analysis revealed significant periodicities of 12 and 20-24 years that are believed to be solar-induced.
3) Neff et al. (2001) also provide evidence for a solar-induced influence on the hydrologic cycle. For the period 9,600-6,100 years before present, they investigated the relationship between a 14C tree-ring record and a proxy record of monsoon rainfall intensity inferred from calcite ð18O data obtained from a stalagmite in northern Oman. Their investigation revealed an “extremely strong” correlation between the two data sets; and spectral analyses revealed statistically significant decadal and multi-decadal periodicities of 10.4, 26 and 89 years for the 14C tree-ring record, and 87 years for the ð18O record.
4) Chile, 2005:
http://www.clim-past-discuss.net/1/121/2005/cpd-1-121-2005-print.pdf
Abstract
Spectral and wavelet analysis were performed on a tree ring width time series obtained
from a 2500 yr old cypress tree (Fitzroya cupressoides) from Costa del Osorno, Chile.
The periods for analysis were selected at 95% confidence level. Both periodicities
characteristic 5 of solar activity and climatic variations were found in this tree ring width
series. The 11 and 22 years solar cycle periods were present in tree ring data with a
confidence level above 98%. This indicates the solar modulation of climatic variations
is being recorded by the tree ring grown. However wavelet analysis shows that these
are present only sparsely. Short-term variations, between 2–5 years, are also present
10 in tree ring data, and are shown by wavelet maps to be a more permanent characteristic.
This time scale is a signature of ENSO events. Long-term variations, above 200
years, are also present in tree ring data. The spectral analysis performed in this work
shows that this species has the ability to record solar-ENSO variations that seems to be
affecting the local environment of tree growth, and also that this region was influenced
15 by ENSO events at least in the past 2500 yr interval covered by this study.
5) Chile, 2007:
http://faculty.fgcu.edu/twimberley/EnviroPol/EnviroPhilo/AD.pdf
Abstract
Tree growth rings represent an important natural record of past climate variations and solar activity effects registered on them. We
performed in this study a wavelet analysis of tree ring samples of Pilgerodendron cupressoides species, from Glaciar Pio XI (Lat: 491120S;
741550W; Alt: 25 m), Chile. We obtained an average chronology of about 400 years from these trees. The 11-yr solar cycle was present
during the whole period in tree ring data, being more intense during Maunder minimum (1645–1715). The short-term periods, around
2–7 yr, that were found are more likely associated with ENSO effects. Further, we found significant periods around 52 and 80–100 yr.
These periodicities are coincident with the fourth harmonic (52 yr) of the Suess cycle (208 yr) and Gleissberg (80–100 yr) solar cycles.
Therefore, the present analysis shows evidence of solar activity effect/modulation on climatic conditions that affect tree ring growth.
Although we cannot say with the present analysis if this effect is on local, regional or global climate, these results add evidence to an
important role of solar activity over terrestrial climate over the past 400 yr.
1sky1 says:
June 14, 2014 at 2:21 pm
Actually, a good starting point to ending “analytic foolishness” would be your worked example using Nir Shaviv’s data. Nir Shaviv has provided his worked example. I’ve provided mine, using the same data.
And once again, you’re all mouth, nothing but theory and no results. You might be 100% correct, 1sky1, you seem like a smart guy. But claiming you are correct hardly demonstrates it. So far, you’ve talked the talk, but you’ve never walked the walk.
Here we have a clear example. Shaviv claims that there is a significant correlation between sunspots and SSTs. I say no. I’ve posted up the sunspot and the SST data.
So what does your whiz-bang method say, 1sky1? Are they significantly correlated or not? Mumbling about theory doesn’t cut it, my friend. It’s time for a worked example.
Or not, your choice. I’ve heard plenty of hilarious reasons from you as to why you never produce any actual results, but I doubt that you’ve run out of excuses yet …
w.
Pamela Gray says:
June 13, 2014 at 11:05 am
——————————–
Thank you for the link to that paper, there was much of interest. While it was a modelling paper, the proposed effect of ocean chlorophyll changes seems plausible.
You ask – “So why did these clearly well-informed scientists endeavor such a task using the visible lightband and ignore UVa, which you seem to think is such a big deal?”
The answer is simple, they were looking at simply the changes in ocean circulation and heat content due to changes in the depth to which radiation penetrates in the oceans. Funny thing. This is exactly the type of mechanism I am talking about.
You claim these are “clearly well-informed scientists”. I concur. They are very, well informed.
While they do not use the correct engineering terms “selective surface” or “selective coating”, they do know that the oceans are not responding to incident radiation as a “near blackbody”, and the depth at which radiation is thermalized in the oceans is very important. Note this statement from the paper starting –
“As a first step, most models assume that all of the solar irradiance is absorbed at the surface in the same way that latent and sensible heat are passed across the air-sea interface. In an effort to provide a more realistic…”
They are correct in that the oceans are not a “near blackbody” they are a selective surface. So what is a selective surface? Willis always says “do the maths”. I always say “do the empirical experiment”. Maths is not physics. Maths can be used model physics, but it can also be used to model non-physical mechanisms, a chronic problem in climastrology.
Here is a simple empirical experiment entitled “Shredded Lukewarm Turkey in Boltzmannic Vinegar” –
http://oi61.tinypic.com/or5rv9.jpg
The experiment is simple, both acrylic blocks have equal IR emissivity and equal ability to absorb UV & SW. The only difference between the blocks is the depth of UV/SW absorption. For dramatic results expose the blocks to full sun for 3 hours. The average temperature of block A will be around 20C higher than block B. The base temperature of block A will be around 40C higher than block B.
If exposed to intermittent SW even the surface temp of block A will exceed that of block B.
The depth of SW/UV absorption in a transparent material with a slow rate of internal non-radiative transport and an IR emissivity <1 is critical to determining the resultant temperature of such a “selective surface” exposed to intermittent UV/SW radiation.
Because of convective circulation, turbidity and surface roughness, the oceans are far more complex than this. However, below the diurnal over turning layer, the oceans will act in a manner analogous to the simple selective surface experiment. Here the effects from variation in UV/SW radiation can be cumulative.
At 10 w/m2 at 50m depth it is plausible that UV variation between solar cycles could cause a tiny accumulation of 0.8C in 150 years.
Pamela Gray says:
June 13, 2014 at 11:43 am
———————————
It has been estimated that while the rate may have decreased recently, sea levels have been rising at around 300mm per century. In 150 years since the LIA, this would be around 450mm. If this were from melting land ice it would represent a layer over 1m deep over the total land surface of the planet. This does not seem plausible.
However ocean warming due to incident LWIR is not possible for water that is free to evaporatively cool. Therefore variation in atmospheric radiative gas concentration is also not a plausible mechanism for sea level rise.
Mechanisms that may be plausible are –
– UV/SW variation between solar cycles accumulating in the oceans.
– Variation in ocean turbidity (biological or mineral)
– Variation in cloud cover.
– Volcanic activity.
Catherine Ronconi said June 14, 2014 at 2:58 pm, replying to Willis, in part:
“…Why are you so studiously ignoring the many citations that mention the ~11 year cycle right in the title of the papers?…”
First, I quite honestly don’t know where the “many citations that mention the ~11 year cycle right in the title of the papers” are. Please direct me – I MIGHT well have missed the links. All I found above that had a mention of an 11-year cycle is Hood et al. The abstract suggests a finding in some part of the N. Pacific, but not in the Arctic! I can’t see the full paper which is paywalled. (I miss the days in academia when the papers just loaded and we never thought about restricted access.) In any event, exactly where are the “many citations” particularly as they might relate to sea-surface temperature and not rainfall over land (like the Tibetan Plateau – a well-known sea), or something like that.
But if there are really “many citations”, than a reader here might well expect a dozen or so could be easily listed, or a link compiling listings to many papers could be posted. Where are they? Please give Willis and the rest of us some consideration and list a few items, or better, “many” of them.
I have no doubt there is a 11-year (very approximately) solar cycle for SOME things. Two at least. One of these is the SSN on the sun itself, obvious enough. As for the earth itself, I am personally familiar with only one thing – traffic on the 10 meter ham-radio band, which peaks with the sunspots. I doubt 10-meter ham-gabbing is related to sea surface temperatures. I thought it had to do with ions at the top of the atmosphere. It does correlate well with the Maunder Minimum though – there was no 10-meter ham traffic for that entire 70 years!
Bernie Hutchins says:
June 15, 2014 at 9:51 am
As a ham myself (H44WE), that comment had me spilling my morning coffee on the keyboard. My thanks, and a happy Fathers Day morning to you all.
w.
Bernie Hutchins says:
June 15, 2014 at 9:51 am
I don’t know how you MIGHT have missed the many references to 11 year cycles cited above. I found them easily. See prior comment for A FEW of them. Or use the FIND function & search for “11”.
Catherine Ronconi said June 15, 2014 at 1:17 pm:
“….I don’t know how you MIGHT have missed the many references to 11 year cycles cited above. I found them easily. See prior comment for A FEW of them. Or use the FIND function & search for “11″. …..”
Search for ’11”. That’s very funny! I don’t suppose you tried to use a FIND on “11” before suggesting it to me. I tried that last night on this post and there were well over 400 instances then, 484 when I tried it just now. Not much help. It was a joke – right?
Onward. Let’s try your first suggestion: Rigozo et al. (2002)” which is not much of a lead! A bit of searching goes through a CO2-Science site and onward to Advances in Space Research and finally the paper title “Solar variability effects studied by tree-ring data wavelet analysis” complete with an invitation to lighten my wallet by $35.95 if I would like to actually see it. (The title apparently is not one of your “many” with 11 years right in the title. It does have the redeeming virtue of NOT adding another “11” to the FIND total!) Nor is there an 11 in the free abstract.
Enough wild geese for me.
Bernie Hutchins says:
June 15, 2014 at 4:32 pm
I did and found lots of abstracts and titles quoted with references to a 10 to 12 year cycle, mostly 11.
Catherine Ronconi says:
June 15, 2014 at 1:14 pm
Thanks, Catherine. What exactly do you think that I’ve been doing? To date I’ve investigated tree ring records, tropospheric temperature records, tidal records, SST records, surface temperature records, sea level records, rainfall records, river flow records, and likely some others I’ve forgotten.
Since I haven’t been able to find a single example that stood up to examination, and I won’t live long enough to investigate them all, I asked people to point to the study that they thought would hold up. That way, I figured that the people holding the view would tell me about the study that really was good, that was solidly constructed and analyzed, that would stand up to examination.
Instead, you and others took it as an invitation to pile every crappy paper you could find on me, even some papers that (like the Black paper you cite below) specifically state that they are NOT about the 11-year sunspot cycle. Not what I expected.
I expected that the champions of the idea that the sun affects the climate would seize the chance to show me, and the world, that there is a study that actually will stand up to close examination … foolish me. Foolish me.
So I’ve been trying to get across to you and others that yes, I know that there are literally dozens and dozens of studies out their making the claim that they’ve found the elusive 11-year cycle. So what? After the climate “consensus” debacle, are you seriously claiming that a bunch of papers that all agree with each other are therefore right?
What I’d like is to cut through the fog, and ask the adherents of the “It’s The Sun, Stupid” point of view tell me what they see as the rock solid evidence, the real study.
Instead, you say it’s my job and try to bury me under random garbage, and insult me in the process. Well, OK … but if you guys that believe in the theory won’t tell me where the good solid study is to be found, I’ll continue to say that I haven’t found it …
(Please note that I have been clear from the first. I have emphasized that I was NOT saying that the sun has no effect on the climate. What I WAS saying was that to date, I’ve not found a single climate dataset that shows a statistically significant ~11-year solar signal.)
Dear heavens, are you really that dense? CITE OR QUOTE YOUR ASSERTIONS! Which “paper” are you babbling about without identifying? I’ve written about 500 posts and now you think I can read your mind?
Also, what got Roy Spencer in trouble is that he didn’t bother to read what I’d written before making his accusations. Fortunately, the internet never forgets, so I was able to clearly show that he (and now you as well) were just slinging mud.
Do your homework, Catherine, your dislike of me is affecting your judgement. Roy was simply wrong in his claim that I had not cited Ramanathan, and he was simply wrong that Ramanathan’s hypothesis was the same as mine. I had cited Ramanathan, and the two hypotheses are totally dissimilar. Lucky for me, it’s all there in black and white.
My dear, I have looked at every serious study of the sunspot cycle that I’ve found. I’ve skipped what I see as the garbage. In the process, as near as I can tell, I have not only read but analyzed and falsified more important papers on the subject than anyone that I know of. I have shown that there is no 80-year Gleissberg cycle. I’ve shown that the Christensen-Lassen papers don’t hold water. I’ve shown that Nir Shaviv’s SST results are not statistically significant. I’ve shown that the ever-cited Parana River study was a joke. I’ve even dug out and looked at Herschel’s original claims about wheat prices and sunspots. I’ve analyzed a variety of climate datasets on my own, and dug deeply into the claims of others. Not only that, I’ve taken the time to write all of those studies up for jerks like you to jeer at and for serious folks to read and discuss and add to, plus I have posted the hundreds and hundreds of lines of computer code that lazy old me wrote and debugged plus the data to allow replication, plus I’ve answered inane comments such as yours by the hundreds and hundreds … and I also have a day job building houses.
Lazy? All that accusation does, Catherine, is prove to the lurkers that your judgement sucks begonias, and that you are willing to throw baseless mud.
I have not asked anyone, including you, to “do my research for me”. I’ve asked you to point out what you think are good studies SO THAT I COULD DO MY RESEARCH FOR ME, because if I wait for you or anyone out there to “do my research for me” I’ll wait forever. You do my research for me? Don’t make me laugh. Let us know when you analyze your first paper or dataset on the subject, I’m sure Anthony would consider publishing it if it’s good.
The problem is that there is so much crap out there on the subject that I couldn’t possibly analyze it all if I could live a hundred years. So I asked for assistance from adherents of the idea to identify the good stuff. Now, if you want to assist in that regard, fine, and if you don’t, piss off … but don’t try to claim I’m wrong for asking for assistance in shoveling out the Augean Stables. If the adherents of an idea can’t point to a valid study supporting the idea, that means something.
You go on to say:
This is exactly why I don’t look at every study. Black says the cycles are 12.5 to 13 years. Rigoso says 11 years. Dean says 10 years. Obviously, they can’t all be right … and Black even says it’s doubtful that his results are related to the sunspot cycle. Am I “studiously ignoring” Black? No, I’m paying attention to it, and as a result I know I don’t need to read it.
You see why I asked you not to just shovel this kind of garbage, but to look through them and pick the one you think will stand up?
Seriously, Catherine, look at it this way. I have offered, of my own generosity, to allow you to select one study for me to analyze. If you don’t want to take me up on that offer, fine.
But if you do, the offer still stands. Where is the study that you think proves the case? And if you don’t have such a study … why are you on my case?
In the meantime, I won’t hold my breath. While you are sitting around criticizing, lazy old me will just continue to analyze the studies that seem like they have a chance of not falling apart as soon as they are looked at in detail.
Regards,
w.
I wouldn’t have insulted you if you didn’t make it a practice to insult others so regularly, suffering as you do from delusions of competence.
The fact is that you have been too unstable to have had a normal career, so now are trying to feed your megalomania by ripping off the ideas of people who have devoted their lives to science. You haven’t changed since your mental problems surfaced in the Army.
Why do you want me to pick one study? How about you pick one of the many showed you that overtly in their title or abstract find a quasi-decadal signal?
If you insist on my picking one, then how about one of the two Chilean studies to the abstracts of which your attention has repeatedly been directed. Better yet all of them.
If you don’t have the time to review all the relevant literature, then how dare you make the easily demonstrated false claim that there is no signal? By its very nature, such a claim should only come after exhaustive analysis of at least dozens if not hundreds of papers. Instead, like so many other losers working out their anger on message boards and blogs, you aggressively state a position then tell the sane people to find exceptions to it for them. I’ve seen this pathological behavior over and over, which is one reason why I rarely comment or post, but find it more instructive to observe.
Catherine Ronconi said June 15, 2014 at 4:54 pm:
“I did and found lots of abstracts and titles quoted with references to a 10 to 12 year cycle, mostly 11.”
Sorry. You say “I did” but not what you did. I assume it must have been the FIND on “11” in this post that I was worried about? Is that right? Well I just went through all (now 492 occurrences) and found NO “abstracts and titles quoted with references to a 10 to 12 year cycle, mostly 11.” We MUST be doing something entirely different. I certainly could be missing something. Please help.
Hopefully it is not too much to ask that you do, as seems to be the tradition on WUWT and as a matter of common courtesy, a list the specific clickable links to perhaps two or three of these papers (at least one please). Others do this much and much much more. Please choose papers that can be downloaded in full without charge. Or if these can’t be found, please write up a brief summary of your own reading of the papers you cite, addressing the concerns that have been voiced on this posting.
My sincere thanks.
Bernie Hutchins says:
June 15, 2014 at 6:29 pm
How can you possibly have missed them when I recopied two of the abstracts previously linked here with “11 year cycles” in them in a comment to which you replied? But here for at least the third time are those two:
4) Chile, 2005:
http://www.clim-past-discuss.net/1/121/2005/cpd-1-121-2005-print.pdf
Abstract
Spectral and wavelet analysis were performed on a tree ring width time series obtained
from a 2500 yr old cypress tree (Fitzroya cupressoides) from Costa del Osorno, Chile.
The periods for analysis were selected at 95% confidence level. Both periodicities
characteristic 5 of solar activity and climatic variations were found in this tree ring width
series. The 11 and 22 years solar cycle periods were present in tree ring data with a
confidence level above 98%. This indicates the solar modulation of climatic variations
is being recorded by the tree ring grown. However wavelet analysis shows that these
are present only sparsely. Short-term variations, between 2–5 years, are also present
10 in tree ring data, and are shown by wavelet maps to be a more permanent characteristic.
This time scale is a signature of ENSO events. Long-term variations, above 200
years, are also present in tree ring data. The spectral analysis performed in this work
shows that this species has the ability to record solar-ENSO variations that seems to be
affecting the local environment of tree growth, and also that this region was influenced
15 by ENSO events at least in the past 2500 yr interval covered by this study.
5) Chile, 2007:
http://faculty.fgcu.edu/twimberley/EnviroPol/EnviroPhilo/AD.pdf
Abstract
Tree growth rings represent an important natural record of past climate variations and solar activity effects registered on them. We
performed in this study a wavelet analysis of tree ring samples of Pilgerodendron cupressoides species, from Glaciar Pio XI (Lat: 491120S;
741550W; Alt: 25 m), Chile. We obtained an average chronology of about 400 years from these trees. The 11-yr solar cycle was present
during the whole period in tree ring data, being more intense during Maunder minimum (1645–1715). The short-term periods, around
2–7 yr, that were found are more likely associated with ENSO effects. Further, we found significant periods around 52 and 80–100 yr.
These periodicities are coincident with the fourth harmonic (52 yr) of the Suess cycle (208 yr) and Gleissberg (80–100 yr) solar cycles.
Therefore, the present analysis shows evidence of solar activity effect/modulation on climatic conditions that affect tree ring growth.
Although we cannot say with the present analysis if this effect is on local, regional or global climate, these results add evidence to an
important role of solar activity over terrestrial climate over the past 400 yr.
You’re sincerely welcome.
“I expected that the champions of the idea that the sun affects the climate would seize the chance to show me, and the world, that there is a study that actually will stand up to close examination … foolish me. Foolish me.”
Wait, I thought the thread was just about some elusive 11 year signal, and there was no claim that solar influence of climate could be dismissed if such a signal could not be found? Foolish me? No, I can see I’m not the only one who can see what this is really all about.
Catherine Ronconi on June 15, 2014 at 6:35 pm provided two links:
(1) We saw these much earlier and they were not yours – from Milodonharloni. Both are the same author. The first was based on “a tree”! The second says “trees” and that the data is from Rigozo et al (2006a), apparently in Trend Appl Sci Res, so we don’t know how many here – I guess two at least! Fig. 1 of this 2007 paper plots “Tree ring width” so I guess we are back to one tree. BS.
(2) I can not reply and ignore something else too. For the record: With regard to your attack on Willis, you have redefined uncouth beyond the pale.
Bernie Hutchins says:
June 15, 2014 at 7:28 pm
I never claimed that they were originally mine. Where did you get that idea? I referenced them. What is your major malfunction?
What in my comments about Willis was wrong? Have you not read his vicious ad hominem attacks on others & dismissal of others’ work as garbage? Maybe you missed the graphs he posted without citing sources, misleading readers that they were original with him, until their sources were cited by other commenters here?
But if you like so many here want to remain a fan boy of such a character, you’re welcome to him.
I was nuts ever to comment again on this blog populated by crackpots who give catastrophic man-made climate skepticism a bad name after leaving the last time.
Willis,
Have you seen this? It is germane to this post.
http://joannenova.com.au/2014/06/big-news-part-ii-for-the-first-time-a-mysterious-notch-filter-found-in-the-climate/
Catherine Ronconi says:
“I was nuts…”
I wouldn’t go that far, Catherine. But it’s pretty clear you have an unhealthy fixation on Willis, who has been unusually patient with you.
I suppose that will cause you to label me one of the “crackpots” here. That’s fine. I’ve taken sides. You brought it on yourself by playing the man and not the ball.
M Simon says:
June 15, 2014 at 8:44 pm
———————————-
It is indeed germane to this post as they are looking at why an 11 year solar signal will not be identifiable in temperature records.
If you read some of my responses to Pamela on this thread, you will note that I am describing a plausible physical mechanism (UV variation below the ocean thermocline) for solar influence on climate that would create long term signal but mask shorter single solar cycle signals.
Konrad.
June 15, 2014 at 9:57 pm
Thanks! I’ll have a look. The thread is so long I passed up reading it in favor of just posting that comment. I had read the original post when it came out. Which is how I knew where to leave the link.
Konrad,
As well as posting here I have sent Willis an e-mail. I have his addy based on having some mutual friends a very long time ago. I expect a post on this in a day or so.
M Simon says:
June 15, 2014 at 8:44 pm
Thanks, M. I have seen it, if you search down the comments you’ll see that I have replied there at Jo’s site.
w.
I also notified Mosh.
Willis,
Thanks! I’m just down to #14 or so in the thread. I’ll keep my eye out. BTW I’m an EE so I recognize the Bode Plot.