Guest Post by Willis Eschenbach
I hear a lot of folks give the following explanation for the vagaries of the climate, viz:
And in fact, when I first started looking at the climate I thought the very same thing. How could it not be the sun, I reasoned, since obviously that’s what heats the planet.
Unfortunately, the dang facts got in the way again …
Chief among the dang facts is that despite looking in a whole lot of places, I never could find any trace of the 11-year sunspot cycle in any climate records. And believe me, I’ve looked.
You see, I reasoned that no matter whether the mechanism making the sun-climate connection were direct variations in the brightness of the sun, or variations in magnetic fields, or variations in UV, or variations in cosmic rays, or variations in the solar wind, they all run in synchronicity with the sunspots. So no matter the mechanism, it would have a visible ~11-year heartbeat.
I’ve looked for that 11-year rhythm every place I could think of—surface temperature records, sea level records, lake level records, wheat price records, tropospheric temperature records, river flow records. Eventually, I wrote up some of these findings, and I invited readers to point out some record, any record, in which the ~ 11-year sunspot cycle could be seen.
Nothing.
However, I’m a patient man, and to this day, I continue to look for the 11-year cycle. You can’t prove a negative … but you can amass evidence. My latest foray is into the world of atmospheric pressure. I figured that the atmospheric pressure might be more sensitive to variations in something like say the solar wind than the temperature would be.
Let me start, however, by taking a look at the elusive creature at the heart of this quest, the ~11-year sunspot cycle. Here is the periodogram of that cycle, so that we know what kind of signature we’re looking for:
Figure 1. Periodogram, showing the strengths of the various-length cycles in the SIDC sunspot data. In order to be able to compare disparate datasets, the values of the cycles are expressed as a percentage of the total range of the underlying data.
As you’d expect, the main peak is at around 11 years. However, the sunspot cycles are not regular, so we also have smaller peaks at nearby cycle lengths. Figure 2 shows an expanded view of the central part of Figure 1, showing only the range from seven to twenty-five years:
Figure 2. The same periodogram as in Figure 1, but showing only the 7 – 25 year range.
Now, there is a temptation to see the central figure as some kind of regular amplitude-modulated signal, with side-lobes. However, that’s not what’s happening here. There is no regular signal. Instead of there being a regular cycle, the length of the sunspot cycle varies widely, from about nine to about 15 years, with most of them in the 10-12 year range. The periodogram is merely showing that variation in cycle length.
In any case, that’s what we’re looking for—some kind of strong signal, with its peak value in the range of about 10-12 years.
As I mentioned above, when I started looking at the climate, like many people I thought “It’s the sun, stupid”, but I had found no data to back that up. So what did I find in my latest search? Well, sweet Fannie Adams, as our cousins across the pond say … here are my results:
Figure 3. Periodograms of four long-term atmospheric pressure records from around the globe.
There are some interesting features of these records.
First, there is a very strong annual cycle. I expected annual cycles, but not ones that large. These cycles are 30% to 60% of the total range of the data. I assume they result in large part from the prevalence of low-pressure areas associated with storms in the local wintertime, combined with some effect from the variations in temperature. I also note that as expected, Tahiti, being nearest to the equator and with little in the way of either temperature variations or low-pressure storms, has the smallest one-year cycle.
Other than semi-annual and annual cycles, however, there is very little power in the other cycle lengths. Figure 4 shows the expanded version of the same data, from seven to twenty-five years. Note the change in scale.
Figure 4. Periodograms of four long-term atmospheric pressure records from around the globe.
First, note that unlike the size of the annual cycle, which is half the total swing in pressures, none of these cycles have more than about 4% of the total swing of the atmospheric pressure. These are tiny cycles.
Next, generally there is more power in the ~ 9-year and the ~ 13-14 year ranges than there is in the ~ 11-year cycles.
So … once again, I end up back where I started. I still haven’t found any climate datasets that show any traces of the 11-year sunspot cycles. They may be there in the pressure data, to be sure, it is impossible to prove a negative, I can’t say they’re not there … but if so, they are hiding way, way down in the weeds.
Which of course leads to the obvious question … why no sign of the 11-year solar cycles?
I hold that this shows that the temperature of the system is relatively insensitive to changes in forcing. This, of course, is rank heresy to the current scientific climate paradigm, which holds that ceteris paribus, changes in temperature are a linear function of changes in forcing. I disagree. I say that the temperature of the planet is set by a dynamic thermoregulatory system composed of emergent phenomena that only appear when the surface gets hotter than a certain temperature threshold. These emergent phenomena maintain the temperature of the globe within narrow bounds (e.g. ± 0.3°C over the 20th Century), despite changes in volcanoes, despite changes in aerosols, despite changes in GHGs, despite changes in forcing of all kinds. The regulatory system responds to temperature, not to forcing.
And I say that because of the existence of these thermoregulatory systems, the 11-year variations in the sun’s UV and magnetism and brightness, as well as the volcanic variations and other forcing variations … well, they make little difference.
As a result, once again, I open the Quest for the Holy 11-Year Grail to others. I invite those that believe that “It’s the sun, stupid” to show us the terrestrial climate record that has any sign of being correlated with the 11-year sunspot cycles. I’ve looked. Lots of folks have looked … where is that record? I encourage you to employ whatever methods you want to use to expose the connection—cross-correlation, wavelet analysis, spectrum analysis, fourier analysis, the world is your lobster. Report back your findings, I’d like to put this question to bed.
It’s a lovely Saturday in spring, what could be finer? Gotta get outside and study me some sunshine. I wish you all many such days.
w.
For Clarity: If you disagree with someone, please quote their exact words that you disagree with. It avoids all kinds of pernicious misunderstandings, because it lets us all know exactly where you think they went off the rails.
Why The 11-year Cycle?: Because it is the biggest cycle, and we know all of the other cycles (magnetism, TSI, solar wind) move in synchronicity with the sunspots. As a result, if you want to claim that the climate is responding to say a slow, smaller 100-year cycle in the sunspot data, then by the same token it must be responding more strongly to the larger 11-cycle in the sunspot data, and so the effect should be visible there.
The Subject Of This Post: Please do not mistake this quest for the elusive 11-year cycle in climate datasets as an opportunity for you to propound your favorite theory about approximately 43-year pseudo-cycles due to the opposition of Uranus. If you can’t show me a climate dataset containing an 11-year cycle, your hypothesis is totally off-topic for this post. I encourage you to write it up and send it to Anthony, he may publish it, or to Tallbloke, he might also. I encourage everyone to get their ideas out there. Here on this thread, though, I’m looking for the 11-year cycle sunspot cycle in any terrestrial climate records.
The Common Cycles in Figures 3 and 4: Obviously, the four records in Figs. 3 & 4 have a common one-year cycle. As an indication of the sensitivity of the method that I’m using, consider the two other peaks which are common to all four of the records. These are the six-month cycle, and the 9-year cycle. It is well known that the moon raises tides in the atmosphere just as it does in the ocean. The 9-year periodicity is not uncommon in tidal datasets, and the same is true about the 6-month periodicity. I would say that we’re looking at the signature of the atmospheric tides in those cycle lengths.
Variable-Length Cycles, AKA “Pseudocycles” or “Approximate Cycles”: Some commenters in the past have asserted that my method, which I’ve nicknamed “Slow Fourier Analysis” but which actually seems to be a variant of what might be called direct spectrum analysis, is incapable of detecting variable-length cycles. They talk about a cycle say around sixty years that changes period over time.
However, the sunspot cycle is also quite variable in length … and despite that my method not only picks up the most common cycle length, it shows the strength of the sunspot cycles at the other cycle lengths as well.
A Couple of my Previous Searches for the 11-Year Sunspot Cycle:
Looking at four long-term temperature records here.
A previous look at four more long-term temperature records.
Atmospheric Pressure and Sunspot Data:
Tahiti to 1950 and Tahiti 1951 on (note different units)
Darwin to 1950 and Darwin 1951 on (note different units)
Sunspots These are from SIDC. Note that per advice from Leif Svalgaard, in the work I did above the pre-1947 values have been increased by 20% to adjust for the change in counting methods. It does not affect this analysis, you can use either one.
For ease of downloading, I’ve also made up a CSV file containing all of the above data, called Long Term Atmospheric Pressure.csv
And for R users, I’ve saved all 5 data files in R format as “Long Pressure Datasets.tab”
Code: Man, I hate this part … hang on … let me clean it up a bit … OK, I just whacked out piles of useless stuff and ran it in an empty workspace and it seemed to fly. You need two things, a file called madras pressure.R and my Slow Fourier Transform Functions.R. Let me know what doesn’t work.
If we are still looking here’s another:
Interactions between externally forced climate signals from sunspot peaks and the internally generated Pacific Decadal and North Atlantic Oscillations
Loon & Meehl 2014
When the Pacific Decadal Oscillation is in phase with the 11 year sunspot cycle, there are positive sea level pressure (SLP) anomalies in the Gulf of Alaska, nearly no anomalous zonal SLP gradient across the equatorial Pacific, and a mix of small positive and negative sea surface temperature (SST) anomalies there. When the two indices are out of phase, positive SLP anomalies extend farther south in the Gulf of Alaska and west into eastern Russia, with a strengthened anomalous zonal equatorial Pacific SLP gradient and larger magnitude and more extensive negative SST anomalies along the equatorial Pacific. In the North Atlantic, when the North Atlantic Oscillation (NAO) is in phase with the sunspot peaks, there is an intensified positive NAO SLP pattern. When the NAO is out of phase with the peaks, there is the opposite pattern (negative NAO). The relationships are physically consistent with previously identified processes and mechanisms and point the way to further research.
lsvalgaard says:
May 29, 2014 at 8:16 am
Check out Figure 4 of: “Holocene Forcing of the Indian Monsoon Recorded in a Stalagmite from Southern Oman”
Cheers, 🙂
Shawnhet says:
May 29, 2014 at 9:12 am
Check out Figure 4 of: “Holocene Forcing of the Indian Monsoon Recorded in a Stalagmite from Southern Oman”
1st: that is not global
2nd: dating and temperature proxies are uncertain
3rd: the gullible will believe anything.
lsvalgaard says:
May 29, 2014 at 9:40 am
1st: It refers to one of the most important features of global circulation patterns,
2nd: And the paper deals with how to analyze these uncertain records
3rd: No one has to believe anything. If you have a better interpretation, go ahead and publish it. Until you do, I’ll stick with the published stuff.
Willis Eschenbach says:
May 27, 2014 at 1:54 pm
Greg, after work last night I took a closer look at this. You plot the “first difference” of the Tahiti sea level pressure, d(SLP)/dt, and you get this.

I’ve tried the same thing, and I get this:
You sure that you are plotting the derivative d(SLP)/dt? I get nothing like what you get. I also don’t get your result for the cross-correlation of the sunspot number (SSN) with d(SSN).
I’m in mystery here …
w.
PS—Since correlation goes from -1 to 1, plotting on any other scale to make your results look more significant is heinous chartsmanship …
Shawnhet says:
May 29, 2014 at 9:48 am
I’ll stick with the published stuff.
Here is some published stuff: http://www.leif.org/EOS/Is-there-Evidence-for-Solar-Forcing.pdf
“Numerous authors have considered the apparently self-evident hypothesis that since the sun is the fundamental driving force for the earth’s climate, there should be clear links between the main climate patterns and the main index of solar variability. However, rigorous testing of causative links between sunspots and climate indices finds no links on time scales up to about 15 years. Solar driving of climate must be present at timescales relevant to glacial-interglacial cycles and most-likely at shorter scales as well, but solar and climate proxies that meet length and resolution criteria necessary to prove the hypothesis are yet to be adequately tested.”
Regardless of such lack of evidence, solar enthusiasts continue to believe in their conviction, you are seemingly no different.
You gotta love it….Little Ice Age…The Big chill is on H2 (History Channel #2) just watched them say “There is questions as to what caused the start of the LIA ,BUT, there is little doubt what caused the coldest period…the Maunder Minimum, less sunspots, less solar radiation,and global cooling because of…THE SUN !!! ” Several scientist stand up on TV and confirm this! So, the ‘science is not settled’. Not saying they are right, just pointing out this is no different than saying man is responsible for GW. No one really knows for sure … YET…except that man is not responsible for GW, and soon, we will know what causes GW and GC.
From lsvalgaard on May 29, 2014 at 12:10 pm:
Be glad they aren’t explaining how the sunspot cycle is masked from the data due to the added variations from the epicycles. And how as Mars is not yet ascendant over Jupiter while Venus is in retrograde this shall bring peace to Syria while granting you increased virility.
Leif,
If you want to say I am gullible for believing a particular paper, you may want to provide evidence that that paper is somehow flawed. You would not want to provide evidence relating only to yearly and decadal trends and completely ignore the idea that the dynamics may be different and/or easier to see over longer timeframes.
On it’s face, the paper I provided is evidence of a solar effect and you have provided no plausible argument against its conclusions. Maybe you have one, but just because some other guys didn’t find a relationship looking at different data over the short term doesn’t mean that there is anything wrong with the paper I referenced.
Shawnhet says:
May 29, 2014 at 12:50 pm
On it’s face, the paper I provided is evidence of a solar effect and you have provided no plausible argument against its conclusions.
There are hundreds of such papers, all with their own flaws. One believes what fits one’s world-view or agenda. The published paper I provided argues that there is no strong evidence for solar forcing [as Willis also found]. Show where it goes wrong. My point is that just because a paper is ‘published’ does not lend it automatic credence [as you seem to imply].
lsvalgaard says:
May 29, 2014 at 12:55 pm
I already showed you were it is less that ideal. Your paper deals with too short a timeframe to plausibly address all the effects that can affect the climate. How long does it take for the oceans to equilibrate to a change in forcing? A lot more than 15 years that’s for sure.
It is entirely possible that there is nothing wrong with the paper you reference *and* that there is nothing wrong with the paper *I* reference. It is entirely possible (and frankly plausible) for us to be unable to detect short term changes caused by the sun but not if those effects persist for longer time periods. In that context, do you have any substantive critique of my paper?
I am honestly interested but to me it appears that you simply reflexively dismissed my paper without even reading it.
lsvalgaard says:
May 28, 2014 at 9:53 pm
I was referring, apparently too obscurely, to the seeming correspondence or lack thereof between climatic phenomena & changes in geomagnetism.
Well I wish someone had told me that any paper showing a solar cycle influence must be flawed before I started digging through my references. On a positive note it did let me find several dead links and forced me to do a little organizing so it wasn’t a complete waste of time.
LT says:
May 27, 2014 at 1:25 pm
LT says:
May 28, 2014 at 1:31 pm
Actually, LT, the 11-12 year peak is the fifth strongest peak. In order they are 7.8, 2.4, 1.6, 2.9, and 11.3 years.

Next, as I pointed out in my RSS analysis, we have only 32 years of data for the datasets you’ve chosen. That means we can’t even diagnose a 12-year cycle. I mean you can plot it, but you’re getting into the very sketchy realm. I doubt very much if the 11-year cycle is statistically significant.
Finally, you’ve shown no evidence of a “5 – 9 [year] ENSO” cycle, and I have no idea if there is one. I’ve never looked at the periodogram of the El Nino. Hang on … OK, here’s the periodogram of the Oceanic Nino Index (ONI):
As you can see, while there is a 3.75 and a 5 year cycle, there is no “5 – 9” year cycle. As a result, your explanation of the 7.8 year peak fails completely.
w.
From Dominic Manginell on May 29, 2014 at 12:15 pm:
Really? Wikipedia says about the LIA:
Down in the Causes: Solar Activity section it says:
So by the NASA definition of the period, it would be the Spörer Minimum that ushered in the LIA, which correlates with other definitions of the period.
As seen by the table and chart at link, the Spörer Minimum had a very wide trough, at 90 years overall. The Maunder Minimum in contrast was a ramp down and ramp up without significant dwelling at the bottom, and only 70 years total.
So Spörer starts the LIA, then Maunder lines up with the start of first particularly cold interval.
But then the short Dalton Minimum runs from 1790 to 1830, thus it didn’t even start until twenty years into the second particularly cold interval.
And the last particularly cold interval started twenty years after the end of the Dalton Minimum, thus the planet was getting colder despite the solar activity ramping up.
Thus the evidence shows solar influence is likely not the primary driver of these climate changes, but may have a contributory factor. Indeed, there are several candidates for being contributory factors. Further research is indicated.
And your fixation on the best-known Maunder Minimum is unseemly and unbecoming of an inquisitive mind, no further research indicated.
LT says:
May 28, 2014 at 3:25 pm
LT,
You should at least quote my words before accusing me of “dismissing evidence”.
QUOTE! MY! WORDS! THAT! YOU! DISAGREE WITH! I have never made the claim that “the Sunspot Cycle is the biggest cycle”.
Not according to those who say “It’s the sun, stupid!”
Ooooh, fatal mistake, LT. When a man starts telling me he’s right because of his extensive experience, I know I’ve won the debate …
Your claim that I “only discovered the FFT less than 60 days ago” is a pathetic attempt to deflect attention from the science.
More to the point, your claim is absolute BS. Here is a post of my from 2011 discussing the brilliant insights of old Joe Fourier, which were way old news to me then … sixty days, my aspidistras.
But that means nothing about my analysis—either it’s right, or it’s wrong. And not only is when I “discovered” Joe Fourier meaningless, I first started learning about Fourier in the 1970’s … so I’ll see your thirty years, and raise you to forty years. However, my forty and your thirty mean absolutely nothing here. Either our claims are right or they are not. For example, your claim that the 7.75 year peak in the RSS results is due to the El Nino periodicity is totally contradicted by the data … and all of your thirty years and my forty years makes no difference in the slightest to that fact.
I agree with you completely when you say “33 years of data is more than enough data for an 11 year cycle to show up on a power spectrum”.
But the question isn’t whether it shows up, lots of things “show up” … the question is whether we can trust it, whether it means anything or whether it is just part of the random fluctuations. My experience in climate science has shown me that three cycles is an absolute minimum, and even then you can get badly fooled. I’ve shown elsewhere that there are strong cycles in some climate datasets that last for a century or more, five or six cycles … and then just disappear for the next century. Go figure …
Regards,
w.
“There is only one CERTAINTY….NOTHING is Certain !” I am humbled by and admire all here. I see much hard work and dedication going on and we here that read this site are much better ‘educated’ cause of you ….Thank you!
steven says:
May 27, 2014 at 7:12 pm
Thanks, steven, but that study is paywalled. Dig up a copy and I’ll take a look, I’m not paying for unknown studies.
w.
PS—I note that they have looked at three geographical areas and lags up to 3 years, which means their results need to be significant at the p-value of 0.01 … and I strongly doubt they are. Looks like a data dredge to me …
steven says:
May 28, 2014 at 12:02 pm
Thanks, Steven. Any study that claims to be using “reanalysis data” should be looked at very, very carefully. “Reanalysis data” is climatespeak for “computer model results”. As such, you need to think about several things you wouldn’t need to think about if it were actually observations. Inter alia, these are:
1. How good is the model?
2. What model results are of interest (surface temps, atmospheric temps, pressures, etc.)?
3. What data is input to the model, in order to produce the results?
4. How much of the result you’re interested in is observation, and how much is imagination?
What a global reanalysis model does is to use the observations as constraints, and then figure out the unknown values (e.g. in gridcells where there are no observations) using all the information that we have.
And therein lies a big problem problem for this particular study. You see, one of the things that the reanalysis models use as input is solar energy … so we are virtually guaranteed to find “solar influence” in the model outputs for gridcells with no observations. Remember that computer climate models are linear machines—their output is a simple lagged linear transformation of their input. So if they put solar in, they’ll get solar out.
The problem is compounded by choosing tropospheric temperatures, in that we have very little balloon data for temperatures over the oceans (and not a whole lot over the land). This means that pre-satellite, the model is making up 70% of the data or more …
Since when you put solar in you get solar out, we should not be surprised when Zhou and Tung find it. We should also not assume that has anything to do with the real world.
w.
Shawnhet says:
May 29, 2014 at 9:48 am
I’ll stick with the published stuff.
lsvalgaard says:
Here is some published stuff: http://www.leif.org/EOS/Is-there-Evidence-for-Solar-Forcing.pdf
interesting paper – i downloaded the pdf for further study – but clarify something for me – are they saying that they’ve proven a negative – something Willis has specifically denied doing
steven says:
May 29, 2014 at 8:39 am
“Another”? I haven’t seen the first one yet that actually shows a solar connection. I know there are lots of studies out there, but each one I look at evaporates … in any case, you go on to reference:
LINKS! PROVIDE LINKS! There’s not enough hours in the day for me to screw around with a string of bad studies. You want an answer, you provide the link.
w.
From Willis Eschenbach on May 29, 2014 at 2:33 pm:
Google-Fu applied:
Ms. Prof. Lesley Gray – much research connecting solar variability to climate responses
https://www2.physics.ox.ac.uk/contacts/people/grayl
Email link there. Request a copy?
However at the Wiley link it says:
Submitted, revised, published… and corrected five months later, over a year after first submission?
What value is a copy, especially a preprint, without knowing the correction?
Hey I might have some meat on a 2013 co-authored paper, GRL:
A mechanism for lagged North Atlantic climate response to solar variability.
Oh, it’s a model that fits output from climate models.
Just as well. This was given up by Google Scholar as the only available free download link. After a browser download fail, wget (which ABC news said is a powerful hacking tool favored by Snowden) has spent about 10 minutes continually retrying before finally surrendering, always saying “Read error at byte 90319/630864”.
Can hackers be putting out “free download” doctored PDF’s to ensnare all those rich but miserly scholars and scientists?
Willis, I don’t want an answer. I thought you did. I’m an ocean heat transport skeptic and it matters not the least to me if it is forced or just internal variation. If you were really looking for an answer you would have already found everything I linked. Google is your friend.
Regarding vanLoon and Meehl (2014) :
It is shown solar peak years as used by vanLoon and Meehl are associated with cold events of ENSO. Thus the composite study in this paper seems to me is nothing but ENSO -ve and PDO +ve for Fig 1e; whereas ENSO -ve and PDO -ve for Fig 1f. Hence for obvious reason there is no SST signature in tropics for 1e (cancelling each other) and very strong -ve SST in tropics for 1f (reinforce each other). Such observation can simply be attributed to cold ENSO rather than peak sun.
Regarding Fig 2: During cold ENSO, as we know more undisturbed polar vortex and hence more +ve NAO. Thus peak sun (cold ENSO phase) and +NAO will imply more positive NAO (hence more std dev). Whereas peak sun (cold ENSO which also imply more +ve NAO) and negative NAO will obviously reduce negative NAO (hence more std deviation).
Regarding Gray et al. (2014):
In the observation if different period is chosen the lag response is different. How can any mechanism related to sun can explain that ?
Willis, I have to say when I saw the results of you spectral analysis of the RSS and I saw the small peak near the 11 year cycle, I found it to be very intriguing and not easily dissmissed as noise, do you not think that is a possible signature of the 11 year cycle in the RSS data?