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“
w., I don’t remember, did you look at CERES SW outgoing radiation and solar activity/cycle?
Also, I would expect that ocean circulation patterns would dominate the SST and that increased SW in the ocean may very localized. Perhaps it would be good to look at solar activity between el Nino events.
Konrad: “Results were published at Talkshop. My point about publishing results is this – one persons results carry far less weight than other persons replicating experiments. ”
I first came across your name on TS, I recall similar vaporous claims with no numbers. If the “proof” is over there, I must have missed it, please link. So far there’s nothing to “replicate”. One person’s _results_ have far more weight than one person’s ” I can assure you”.
Greg Goodman says:
June 8, 2014 at 6:04 pm
——————————–
Greg, here is the link to the first version I ran. There are complete instructions for others to replicate –
http://tallbloke.wordpress.com/2011/08/25/konrad-empirical-test-of-ocean-cooling-and-back-radiation-theory/
While this is a simple experiment just reflecting IR back to cooling samples, it suffers from the fact that backscattered IR is dropping as the water cools. This is why I show the build for the later versions as they use a constant IR source and results are more exaggerated.
There really is nothing special about such experiments. They are just the IR version of the old hair dryer trick –
Q. How do you heat a plastic tub of water with a hair dryer?
A. Point the hair dryer at the side of the tub, not the water surface.
DWLWIR combined with an average wind speed of Beaufort scale 4 is like trying to heat the oceans with a hair dryer.
The question you should be asking is not “have I run the experiments?” But – “if DWLWIR is not slowing the cooling rate of the oceans, what is keeping them warmer than the -18C predicted by SB equations?” The experiments to answer this are far more fun. Ever imagined you could run a steam engine off a flat plate solar collector with no concentration?
How large?
The math: “W’s” ego larger than any sun spot energy release from 1 billion years ago to now.
The solution: Do the work on the data out in the sun to better understand the power factor.
A thin skin may be the real problem.
“Greg, here is the link to the first version I ran. ”
Well that took some effort, but thanks. I’ve plotted it up, I’ll give it some reflection.
Dr. Shaviv,
I grant that your analysis is correct and there is correlation between solar cycle and SST and land temperatures. You quoted a peak to peak variation of 0.08 to 0.1 C between solar maximum and minimum. But isn’t the annual variation can be three times bigger than this? 0.1 C change in 11 years looks like noise. Whatever is causing a bigger variation in just one year can certainly cause a smaller variation in 11 years.
11 years is to the
sun is .000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
to the 100,000,00 million/th power.
Heck the sun may have had a divorce 1/2 that time ago.
May be calling an atty just now to cut the child support.
We being the child.
Greg Goodman says:
June 8, 2014 at 8:08 pm
——————————-
If you build the second variant with a constant strong IR source, there is a way to get water to heat via LWIR. The trick is to start with water that is very cold, so little evaporative cooling is occurring.
A good comparison test is to replace the water samples with matt black aluminium blocks. While not directly comparable as aluminium has a far lower specific heat capacity than water, the response to LWIR is distinct. According to climate models the oceans should be responding to DWLWIR as a “near blackbody” similar to the aluminium blocks. This is clearly not the case. All climate models show DWLWIR warming the oceans by ~33C above their theoretical blackbody temp. Something is very wrong with this picture.
ralfellis says:
June 8, 2014 at 5:10 am
Assuredly yes to both questions. Also, the “folding” technique reveals the variable sunspot cycle, no problem.
w.
Donald Morton says:
June 8, 2014 at 5:22 am
Actually, since I can’t find the ~11 year solar cycle in the 10Be data, I’m not at all convinced that 10Be is a “good proxy”, I mean, how good can it be if it can’t detect the 11-year cycle? See Cosmic Rays, Sunspots, and Beryllium for a full discussion.
w.
mobihci says:
June 8, 2014 at 9:00 am
mobihci, like many of the children infesting the internet, you seem to be incapable of reading. I said quite clearly:
Of course, the hordes of interchangeable arrogant anonymous popup internet jerkwagons like yourself always think you are above such common politeness.
As to whether the goal of this thread is to determine whether there is an eleven year cycle evident in the record, I have asked repeatedly for you or anyone to come up with such a cycle. No one has done so to date. Instead, like yourself, they want to cover up their pathetic failure to do what they often claim is a simple task by attacking me.
As to whether or not finding such a cycle “really is not a simple task”, Nir Shaviv and many others claim that it really IS a simple task. So you’ll have to take that question up with Nir and others who make such a claim …
Unfortunately, when I try their own methods on their own data as I did with Nir’s methods and data, the results quickly evaporate. So perhaps the task is more difficult than they claim. Me, I’ve made no claim that it should be easy OR hard. What I have said is that after several centuries of looking and only finding the most elusive hints of an 11-year solar cycle in the data, we can say that if such a cycle exists, it is buried way down in the weeds.
Now, if you want to arise from your moribund okole and contribute to the thread by finding such a cycle, please do so. However, sitting around and whimpering that you don’t like me and my results is just pathetic. It’s hard for folks to watch a grown man acting as childishly as you are. Lead, follow, or get out of the way, but whining about how you don’t like me is useless.
Regards,
w.
Greg Goodman says:
June 8, 2014 at 12:55 pm
I appreciate your asking, but if you don’t know the answer to that question, it’s clear you are far beyond my poor powers to assist you.
w.
If the suns traveling at a speed of 750,000 kmph on its path around the galaxy and the sun gets out in front like when we see an eclipse hear on earth and we have a strong energy exchange like a full moon here on Earth . Does the earths induce a space quake? http://www.everythingselectric.com/forum/index.php?topic=245.0
Mistake in my post should say “when the earth gets out in front “
Greg Goodman “I think all that answers some of Mike Jonas’ points too.“. It looks like it might, I’ll have to think about it a bit more. Thanks anyway.
Greg: The slope affects the correlation. If you want to know where the max correlation happens and what it’s value is, why would I want to distort both datasets by removing a spurious linear trend from both before doing CC?
Willis: “I appreciate your asking, but if you don’t know the answer to that question, it’s clear you are far beyond my poor powers to assist you.”
Is that an elaborate of saying ” I don’t know, so I’ll pretend to be superior and walk away”? That is a response worthy of 1sky1. Surprising, you’re normally so good at telling everyone how they should be doing things.
How are you getting on with the significance question? I thought you just needed to number of data points to plug into an R function call. For the central region N=1700 for both datasets, what do you get for your 95% test ?
Willis,
I compared SIDC yearly to your SSN data in zip linked to in post and to “Total Solar irradiance TSI and Heliospheric Magnetic Field Strength HMF B Reconstructions” (since AD 1700) from Leif’s site.
Leif has the +20% correction applied pre-1945, you used pre-1947. Almost meaningless difference.
The SIDC (now WDC-SILSO) page says of the data (click “Info” at above link):
Offhand I don’t see you using the pre-1749 annual data in your previous few posts, so why include it in your file, especially without the caveat?
There is also a strange difference in Leif’s file, which may be related to old-style programming. When comparing in the 1749 to 1945 or ’47 range, SIDC times 1.2 then rounded to 2 decimal places yields exactly your numbers.
But starting in 1849, Leif usually varies by some multiple of 0.12, the differences range from +0.36 to -0.48. As 0.12 comes from rounding 1/8 (round to the even #), it’s like someone was saving file space by using only 3 bits (or 1 digit) to store the decimal portion as eighths.
From what I have seen in science of using arcane file and record formats that need to be read by a proprietary Fortran program, I wouldn’t be surprised.
Konrad says:
June 8, 2014 at 7:09 pm
Greg Goodman says:
June 8, 2014 at 6:04 pm
——————————–
“…The question you should be asking is not “have I run the experiments?” But – “if DWLWIR is not slowing the cooling rate of the oceans, what is keeping them warmer than the -18C predicted by SB equations?” The experiments to answer this are far more fun. Ever imagined you could run a steam engine off a flat plate solar collector with no concentration?”
///////////////////////////////////////
Konrad
Personally, I consider it wrong to consider the temperature of the oceans to be about 18degC. In reality, the average temperature of the oceans is about 4 degC. I would suggest that when considering the so called Green House Effect, we should use a figure of 4 degC for the ocean temperature.
I would therefore rewrite your question (and I have previously posed this several times on other threads), why after approximately 4 billion years of Solar + DWLWIR are the oceans only 4 degC?
It is only by chance that we are presently seeing the SST at about 18 degC. In other planetary cycles, we would be seeing this as about 23 to 26 degC, or as 2 to 5 degC, and this not because of a huge difference in the amount of solar irradiance that is hitting planet Earth or in the amount of DWLWIR.
We would not experience ice ages, at least not in the way we have seen them, if the average temperature of the cocean was 18 degC. It is because the average temperage is so low (about 4 degC) that it comes back to bite..
From richard verney on June 9, 2014 at 3:13 am:
Gravity!
As I heard it explained, as water cools it will shrink in volume, but only until it reaches approximately 4°C for pure water, when it achieves maximum density. Colder than that, water will expand.
As gravity causes the water above to force the water below into the smallest possible volume, it forces the water below to be about 4°C, the temperature of the minimum volume. Thus the depths of the ocean are that temperature, down to where it rises from lithospheric heat.
This also makes claims of “missing heat” to be questionable. As gravity maintains the deep water temperatures at a fixed amount, it is very difficult to warm the ocean depths at all. If the heat cannot be absorbed, and as the lithosphere underneath is a source of heat, logically the ocean depths should reject the extra thermal energy and “bounce” it back upwards.
Willis, thank you very much for the two links. I spent a while digesting them, because they use different definitions of the surface layer and come to slightly different conclusions. But both seem to be in general agreement with my claim, that wind controls the surface temperature.
If you look at the PDF cartoon Figure 1 it shows a relatively constant surface temperature at night OR in STRONG WINDS. Their definition of strong winds is 12 knots, it is typical for me to see 15 knot winds for weeks. With no wind or very light winds the surface warms during the day.
Which is exactly what I am claiming, that the wind speed controls the surface temperature, but the two discussions help clarify the mechanisms and emphasized mixing and thermal inertia.
What I found extremely interesting in the PDF was the suggestion that
“The variability of near- surface temperature gradients can be large compared to the accuracies of SST needed for climate research (e.g. Ohring et al. 2005), and thus the effects of the thermal skin layer and diurnal heating must be taken into account when generating CDRs of SST. For this reasons, a SST foundation temperature is defined and suggested for use in climate applications.”
Their SST Foundation temperature is found below 10 Meters, below the diurnal and mixing layers and which incidentally is the same temperature as the surface temperature in strong winds. Who would have thought?
kadaka (KD Knoebel) says (June 9, 2014 at 4:05 am):
You form an interesting hypothesis that if plausible, would certainly call into question the whereabouts of the missing heat speculation. Lots of discussion points to consider. Do you have links? Or is this your own thought? Either way, I see a really good blog post in the making if you care to. I for one would readily peruse your expanded post.
Willis Eschenbach
We know when sun spots are big the release CME’s that can hit earth with lots of energy(even ice structure changing ones)
This may be a dumb question but is there a complete index that measures all the energy the sun releases and hits earth.
kadaka (KD Knoebel) says:
June 9, 2014 at 4:05 am
While that is true for pure water at atmospheric pressure, it is not true in the ocean depths. There, the water continues to contract until it freezes.
w.
Greg Goodman says:
June 9, 2014 at 1:36 am
Nope. It’s a simple fact. If you don’t understand why you would detrend a pair of ~150 year datasets when looking for an 11 year cycle, I’m quite sure I will have no success explaining it to you, particularly given your instant knee-jerk disagreement with almost anything I say. Ask your favorite statistician, Greg, because truly, I can’t help you.
Since your results are meaningless when looking for 11-year cycles (due to the fact that you did not detrend your data), there is no way to calculate their statistical significance.
w.