Usoskin Et Al. Discover A New Class of Sunspots

Guest Post by Willis Eschenbach

There’s a new post up by Usoskin et al. entitled “Evidence for distinct modes of solar activity”. To their credit, they’ve archived their data, it’s available here.

Figure 1 shows their reconstructed decadal averages of sunspot numbers for the last three thousand years, from their paper:

usoskin figure 2Figure 1. The results of Usoskin et al.

Their claim is that when the decadal average sunspot numbers are less than 21, this is a distinct “mode” of solar activity … and that when the decadal average sunspot numbers are greater than 67, that is also a separate “mode” of solar activity.

Now, being a suspicious fellow myself, I figured I’d take a look at their numbers … along with the decadal averages of Hoyt and Schatten. That data is available here.

I got my first surprise when I plotted up their results …

Figure 2 shows their results, using their data.

decadal sunspot numbers usoskinFigure 2. Sunspot numbers from the data provided by Usoskin et al.

The surprising part to me was the claim by Usoskin et al. that in the decade centered on 1445, there were minus three (-3) sunspots on average … and there might have been as few as minus ten sunspots. Like I said, Usoskin et al. seem to have discovered the sunspot equivalent of antimatter, the “anti-sunspot” … however, they must have wanted to hide their light under a bushel, as they’ve conveniently excluded the anti-sunspots from what they show in Figure 1 …

The next surprise involved why they chose the numbers 21 and 67 for the breaks between the claimed solar “modes”. Here’s the basis on which they’ve done it.

usoskin Figure 3Figure 3. The histogram of their reconstructed sunspot numbers. ORIGINAL CAPTION: Fig. 3. A) Probability density function (PDF) of the reconstructed decadal sunspot numbers as derived from the same 106 series as in Fig. 2 (gray-filled curve). The blue curve shows the best-fit bi-Gaussian curve (individual Gaussians with mean/σ being 44/23 and 12.5/18 are shown as dashed blue curves). Also shown in red is the PDF of the historically observed decadal group sunspot numbers (Hoyt & Schatten 1998) (using bins of width ΔS = 10).

The caption to their Figure 3 also says:

Vertical dashed lines indicate an approximate separation of the three modes and correspond to ±1σ from the main peak, viz. S = 21 and 67.

Now, any histogram has the “main peak” at the value of the “mode”, which is the most common value of the data. Their Figure 3 shows the a mode of 44, and a standard deviation “sigma” of 23. Unfortunately, their data shows nothing of the sort. Their data has a mode of 47, and a standard deviation of 16.8, call it 17. That means that if we go one sigma on either side of the mode, as they have done, we get 30 for the low threshold, more than they did … and we get 64 for the high threshold, not 67 as they claim.

So that was the second surprise. I couldn’t come close to reproducing their calculations. But that wouldn’t have mattered, because I must admit that I truly don’t understand the logic of using a threshold of a one-sigma variation above and below not the mean, not the median, but the mode of the data … that one makes no sense at all.

Next, in the right part of Figure 1 they show a squashed-up tiny version of their comparison of their results with the results of Hoyt and Schatten … the Hoyt-Schatten data has its own problems, but let’s at least take a look at the difference between the two. Figure 4 shows the two datasets during the period of overlap, 1615-1945:

comparison usoskin and hoyt sunspotsFigure 4. Decadal averages of sunspots, according to Hoyt-Schatten, and also according to Usoskin et al.

Don’t know about you, but I find that result pretty pathetic. In a number of decades, the difference between the two approaches 100% … and the results don’t get better as they get more modern as you’d expect. Instead, at the recent end the Hoyt-Schatten data, which at that point is based on good observations, shows about twice the number of sunspots shown by the Usoskin reconstruction. Like I said … not good.

Finally, and most importantly, I suspect that at least some of what we see in Figure 3 above is simply a spurious interference pattern between the length of the sunspot cycles (9 to 13 years) and their averaging period of ten years. Hang on, let me see if my suspicions are true …

OK, back again. I was right, here are the results. What I’ve done is picked a typical 12-year sunspot cycle from the Hoyt-Schatten data. Then I replicated it over and over starting in 1600. So I have perfectly cyclical data, with an average value of 42.

But once we do the decadal averaging? … well, Figure 5 shows that result:

pseudo sunspot dataFigure 5. The effect of decadal averaging on 12-year pseudo-sunspot cycles. Upper panel (blue) shows pseudo-sunspot counts, lower panel (red) shows decadal averaging of the upper panel data.

Note the decadal averages of the upper panel data, which are shown in red in the lower panel … bearing in mind that the underlying data are perfectly cyclical, you can see that none of the variations in the decadal averages are real. Instead, the sixty-year swings in the red line are entirely spurious cycles that do not exist in the data, but are generated solely by the fact that the 10-year average is close to the 12-year sunspot cycle … and the Usoskin analysis is based entirely on such decadal averages.

But wait … it gets worse. Sunspot cycles vary in length, so the error caused by the decadal averaging will not be constant (and thus removable) as in the analysis above. Instead, decadal averaging will lead to a wildly varying spurious signal, which will not be regular as in Figure 5 … but which will be just as bogus.

In particular, using a histogram on such decadally averaged data will lead to very incorrect conclusions. For example, in the pseudo-sunspot data above, here is the histogram of the decadal averages shown in red.

histogram pseudo sunspot dataFigure 6. Histogram of the decadal average data shown Figure 5 above.

Hmmm … Figure 6 shows a peak on the right, with secondary smaller peak on the left … does this remind you of Figure 3? Shall we now declare, as Usoskin et al. did, and with equal justification, that the pseudo-sunspot data has two “modes”?

CONCLUSIONS:

In no particular order …

1. The Usoskin et al. reconstruction gives us a new class of sunspots, the famous “anti-spots”. Like the square root of minus one, these are hard to observe in the wild … but Usoskin et al. have managed to do it.

2. Despite their claims, the correlation of their proxy-based results with observations is not very good, and is particularly bad in recent times. Their proxies often give results that are in error by ~ 100%, but not always in the same direction. Sometimes they are twice the observations … sometimes they are half the observations. Not impressive at all.

3. They have set their thresholds based on a bizarre combination of the mode and the standard deviation, a procedure I’ve never seen used.

4. They provided no justification for these thresholds other than their histogram, and in fact, you could do the same with any dataset and declare (with as little justification) that it has “modes”.

5. As I’ve shown above, the shape of the histogram (which is the basis of all of their claims) is highly influenced by the interaction between the length(s) of the sunspot cycle and the decadal averaging.

As a result of all of those problems, I’m sorry to say that their claims about the sun having “modes” simply do not stand up to close examination. They may be correct, anything’s possible … but their analysis doesn’t even come near to establishing that claim of distinct solar “modes”.

Regards to all,

w.

THE USUAL: If you disagree with me or someone else, please quote the exact words that you disagree with. That way, we can all understand just what it is that you object to.

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Latitude
February 22, 2014 3:42 pm

Figure 1 shows their reconstructed decadal averages of sunspot numbers for the last three thousand years…..
serious question?……how is that possible?

February 22, 2014 4:38 pm

Latitude said:
February 22, 2014 at 3:42 pm
Figure 1 shows their reconstructed decadal averages of sunspot numbers for the last three thousand years…..
serious question?……how is that possible?
—————-
Tree rings.
/joke

Jeff in Calgary
February 22, 2014 4:47 pm

Would be interesting to see what would happen if they used averaging of each individual cycle. (does that make sense?)

david moon
February 22, 2014 4:50 pm

Is a “decadal average” done like this:
average of 1900 through 1909
average of 1901 through 1910
average of 1902 through 1911, etc
or
average of 1900 through 1909
average of 1910 through 1919, etc

February 22, 2014 4:55 pm

Is there any sunspot/solar activity data vs warm/cold periods over extended periods that can be viewed, so the Sun’s activity and periods such as Roman, Medieval and 20thC Warm periods and and Cold periods such as during Maunder Minimum can be seen, such that a climate cycle can be postulated? Intrigued as to whether this correlation has any traction or any modelling?

jorgekafkazar
February 22, 2014 4:58 pm

“In a number of decades, the difference between the two approaches 100% …”
This is astrophysics, not astronomy. Astrophysicists are happy just to get the decimal in the right place. A sporadic deviation of only 100% is the same as nailing it, in astrophysics.

Clay Marley
February 22, 2014 5:03 pm

This reminds me of the Parana River study where they tried to use an 11 year running average to smooth out the sunspot cycles. Resulted in similar problems in distorting the signal. Then they tried to correlate that with stream flow.
Smoothing over cyclic behavior that varies in period requires something like a LOESS model, over say 20 years or so in this case. IMHO. I’d like to hear Willis’ thoughts on how to handle this kind of data though.

Lew Skannen
February 22, 2014 5:04 pm

Scientists archiving data and making it publicly available without a legal battle?
I can’t see that trend catching on.

Editor
February 22, 2014 5:06 pm

If they’re going to do sunspot averages, would it not make more sense to use average-over-a-cycle, rather than average-over-a-decade? I could see the possibility of sunspots being different over cycles, but that remains to be proven. However, average-over-a-decade looks entirely arbitrary.

February 22, 2014 5:08 pm

Looks to me like they got the same screeching racket (noise) that you get when you use an A to D converter record the digital data and then convert it back into an analog signal using a sample rate very close to the sampled frequency.

ShrNfr
February 22, 2014 5:08 pm

As a complex non-linear system, I would entertain suggestions of strange attractors seriously. The paper might not have found any, but I would not dismiss the possibility out of hand either.

February 22, 2014 5:32 pm

___ i ___
-1_ 0 _+1
___-i ___
The square root of minus 1 is a poor way to illustrate the spurious nature of this data manipulation method, we see perpendicular lines all over the place, and squaring a negative number is simply a type of rotation.

Tom
February 22, 2014 5:49 pm

February 22, 2014 at 4:58 pm
“This is astrophysics, not astronomy. Astrophysicists are happy just to get the decimal in the right place. A sporadic deviation of only 100% is the same as nailing it, in astrophysics”.
So, by your logic, all space launches could have had been 10 times heavier, or lighter. F=ma=10ma. You then imply the equivalence of a deviation of an order of magnitude with doubling, or halving.
You could be a taxpayer-funded climastrologist with those error bars, deserving public ridicule. It seems to me that you have crossed that line by a factor of between 2 and 10.

Editor
February 22, 2014 6:01 pm

Willis: It’s my understanding that the Hoyt & Schatten sunspot numbers were created to explain the warming up through the 1950s and that one of the authors no longer agrees with that reconstruction. I guess we’ll have to wait for Leif to confirm my memory of that reconstruction.
Regards

February 22, 2014 6:06 pm

Like the square root of minus one, these are hard to observe in the wild
Useful for ‘book-keeping’ and making the math work out right; a method of indicating phase quadrature in equations, in the math. I doubt you will ever really observe “i” (or “j” as the sparkies like to denote it) per se, in nature (outside of using a network or phase-gain analyzer) … again, quadrature “I” operations work well to describe stored, rather I should say, transitive or ‘reactive’ energy (as when stored in the mag field of an inductor or in in/between/ the plates of capacitor or in the near field of an antenna (essentially an L/C ckt)) in a non-DC, non-static (AC-excited or dynamic WRT to time) circuits, yes …
.

February 22, 2014 6:16 pm

Bob Tisdale says:
February 22, 2014 at 6:01 pm
Willis: It’s my understanding that the Hoyt & Schatten sunspot numbers were created to explain the warming up through the 1950s and that one of the authors no longer agrees with that reconstruction. I guess we’ll have to wait for Leif to confirm my memory of that reconstruction.
Your memory is correct. Schatten now longer believes that the Group Sunspot Number is correct [more correctly: that my analysis and re-evaluation is correct]. All values before ~1885 are about 50% too low. When you graft such a series to the end of the 14C data you create an automatic ‘sunspot hockey stick’. More details about the SSN here: http://www.leif.org/research/CEAB-Cliver-et-al-2013.pdf
The whole Usoskin article is not science, but advocacy, as Usoskin is peddling the ‘solar activity since 1960 has been the highest in several thousand year’ [he used to say 12,000 years]. This, of course, explains Global Warming. Some here may agree with his analysis just because they have a similar bias, regardless of what the science says. Perhaps [hopefully] Ilya will show up here to defend his ‘work’.

timetochooseagain
February 22, 2014 6:47 pm

@lsvalgaard-Could we calibrate the data Usoskin used against more accurate sunspot data…or is the use of it as a proxy tenuous?

Jean Parisot
February 22, 2014 6:48 pm

Why are we averaging relatively sparse data sets that can be visualized with today’s technology?

bushbunny
February 22, 2014 7:01 pm

Jean I am no scientist but understand something of archaeological and palaeoanthropological researches. I can not rationalize where they got the data from for 3,000 years ago. It appears to be that this could be a case of corrupting the data to prove the hypothesis, I could be wrong. It goes on all the time in universities and academia. They have to publish to prove they are doing something with the funds and grants they get, bugger the factual credibility contained.

February 22, 2014 7:04 pm

Thank you
Paul

bushbunny
February 22, 2014 7:05 pm

As far as statistics are concerned, what is the point of the research, to prove or not prove. If I was to do some research into say ‘domestic violence’ and only took say a100 case histories to prove my point. Say in one town only, was or could this represent truly the condition in other towns. You can fudge statistics. There are so many variables involved in climate change and weather patterns, what suits one region might not be relevant to another.

Lance Wallace
February 22, 2014 7:32 pm

Tom says:
February 22, 2014 at 5:49 pm
In defense of JorgeKafkazar’s statement, I too was trained in astrophysics, and our general mantra was that “1=10”–that is, if we could estimate the energy of a blue giant as exp(55+-1) ergs we were happy. Tom, it’s engineers who operate the space program, and we should all be happy that astrophysicists don’t.
By the way, I no longer remember the energy of blue giants (it was 40 years ago!) so don’t hold me to the “55”–it’s the principle of the thing.

JBirks
February 22, 2014 7:34 pm

“Some here may agree with his analysis just because they have a similar bias, regardless of what the science says.”
———————————
That’s a provocative statement. Possibly true for some, I don’t know. From a purely strategic standpoint, one could argue that Usoskin’s data tricks are less egregious than the Team’s (at least he archives it), and a flawed rival to CAGW is better than none at all. There comes a time when the science becomes so politicised that “the science” of it becomes secondary to “winning.” The more I look, the more I wonder how many people really care what the science is, or would even know if they saw it.
I am not arguing for an abdication of scientific responsibility. By all means, let’s get the science right. But is that even possible in an environment where the scientists themselves are going rogue to promote their own causes?

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