Guest Post by Willis Eschenbach
I was pointed to a 2010 post by Dr. Roy Spencer over at his always interesting blog. In it, he says that he can show a relationship between total solar irradiance (TSI) and the HadCRUT3 global surface temperature anomalies. TSI is the strength of the sun’s energy at a specified distance from the sun (average earth distance). What Dr. Roy has done is to “composite” the variations in TSI. This means to stack them one on top of another … and here is where I ran into trouble.
I couldn’t figure out how he split up the TSI data to stack them, because the cycles have different lengths. So how would you make an 11-year composite stack when the cycles are longer and shorter than that? And unfortunately, the comments are closed. Yes, I know I could write and ask Dr. Roy, he’s a good guy and would answer me, but that’s sooo 20th century … this illustrates the importance of publishing your code along with your analysis. His analysis may indeed be 100% correct—but I can’t confirm that because I can’t figure out exactly how he did it.
Since I couldn’t confirm Dr. Roy’s interesting approach, I figured I’d take an independent look at the data to see for myself if there is a visible ~ 11 year solar signal in the various temperature records. I started by investigating the cycle in the solar variations themselves. The TSI data is here. Figure 1 shows the variations in TSI since 1880
Figure 1. Monthly reconstructed total solar irradiance in watts per square metre (W/m2). As with many such datasets this one has its detractors and adherents. I use it because Dr. Roy used it, and he used it for the same reason, because the study he was investigating used it. For the purposes of my analysis the differences between this and other variations are minimal. See the underlying Lean study (GRL 2000) for details. Note also that this is very similar to the sunspot cycle, from which it was reconstructed.
If I’m looking for a correlation with a periodic signal like the ~ 11-year variations in TSI, I often use what is called a “periodicity analysis“. While this is somewhat similar to a Fourier analysis, it has some advantages in certain situations, including this one.
One of the advantages of periodicity analysis is that the resolution is the same as the resolution of the data. If you have monthly data, you get monthly results. Another advantage is that periodicity analysis doesn’t decompose a signal into sine waves. It decomposes a signal into waves with the actual shape of the wave of that length in that particular dataset. Let me start with the periodicity analysis of the TSI, shown in Figure 2.
Figure 2. Periodicity analysis of the Lean total solar irradiance (TSI) data, looking at all cycles with periods from 2 months to 18 years. As mentioned above, there is a datapoint for every month-by-month length of cycle.
As you can see, there is a large peak in the data, showing the preponderance of the ~ 11 year cycle lengths. It has the greatest value at 127 months (10 years 7 month).However, the peak is quite broad, reflecting the variable nature of the length of the underlying sunspot cycles.
As I mentioned, with periodicity analysis we can look at the actual 127 month cycle. Note that this is most definitely NOT a sine wave. The build-up and decay of the sunspots/TSI occur at different speeds. Figure 3 shows the main cycle in the TSI data:
Figure 3. This is the shape of the main cycle for TSI, with a length of 10 years 7 months.
Let me stop here and make a comment. The average cyclical swing in TSI over the period of record is 0.6 W/m2. Note that to calculate the equivalent 24/7 average insolation on the earth’s surface you need to divide the W/m2 values by 4. This means that Dr. Roy and others are looking for a temperature signal from a fluctuation in downwelling solar of .15 W/m2 over a decade … and the signal-to-noise ratio on that is frankly depressing. This is the reason for all of the interest in “amplifying” mechanisms such as cosmic ray variations, since the change in TSI itself is too small to do much of anything.
There are some other interesting aspects to Figure 3. As has long been observed, the increase in TSI is faster than the decrease. This leads to the peak occurring early in the cycle. In addition we can see the somewhat flat-topped nature of the cycle, with a shoulder in the red curve occurring a few years after the peak.
Looking back to Figure 2, there is a secondary peak at 147 months (12 years 3 months). Here’s what that longer cycle looks:
Figure 4. The shape of the 147-month cycle (12 years 3 months) in the Lean TSI data
Here we can see an advantage of the periodicity analysis. We can investigate the difference between the average shapes of the 10+ and the 12+ year cycles. The longer cycles are not just stretched versions of the shorter cycles. Instead, they are double-peaked and have a fairly flat section at the bottom of the cycle.
Now, while that is interesting, my main point in doing the periodicity analysis is this—anything which is driven by variations in TSI will be expected to show a clear periodicity peak at around ten years seven months.
So let me continue by looking at the periodicity analysis of the HadCRUT4 temperature data. We have that temperature data in monthly form back to 1880. Figure 5 shows the periodicity analysis for the global average temperature:
Figure 5. Periodicity analysis, HadCRUT4 global mean surface air temperatures.
Bad news … there’s no peak at the 127 month period (10 year 7 month, heavy dashed red line) of the variation in solar irradiance. In fact, there’s very little in the way of significant periods at all, except one small peak at about 44 months … go figure.
Next, I thought maybe there would be a signal in the Berkeley Earth land temperature data. The land should be more responsive than the globe, because of the huge heat capacity of the ocean. However, here’s the periodicity analysis of the Berkeley Earth data.
Figure 6. Periodicity analysis, Berkeley Earth global land surface air temperatures. As above, heavy and light red lines show main and secondary TSI periods.
There’s no more of a signal there than there was in the HadCRUT4 data, and in fact they are very similar. Not only do we not see the 10 year 7 month TSI signal or something like it. There is no real cycle of any power at any frequency.
Well, how about the satellite temperatures? Back to the computer … hang on … OK, here’s the periodicity analysis of the global UAH MSU T2LT lower tropospheric temperatures:
Figure 7. Periodicity analysis, MSU satellite global lower troposphere temperature data, 1979-2013.
Now, at first glance it looks like there is a peak at about 10 years 7 months as in the TSI. However, there’s an oddity of the periodicity analysis. In addition to showing the cycles, periodicity analysis shows the harmonics of the cycles. In this example, it shows the fundamental cycle with a period of 44 months (3 years 8 months). Then it shows the first harmonic (two cycles) of a 44-month cycle as an 88 month cycle. It is lower and broader than the fundamental. It also shows the second harmonic, in this case with a period of 3 * 44 =132 months, and once again this third peak is lower and broader than the second peak. We can confirm the 132 month cycle shown above is an overtone composed of three 44-month cycles by taking a look at the actual shape of the 132 month cycle in the MSU data:
Figure 8. 132 month cycle in the MSU satellite global lower troposphere temperature data.
This pattern, of a series of three decreasing peaks, is diagnostic of a second overtone (three periods) in a periodicity analysis. As you can see, it is composed of three 44-month cycles of diminishing size.
So the 132-month peak in the T2LT lower troposphere temperature periodicity analysis is just an overtone of the 44 month cycle, and once again, I can’t find any signal at 10 years 7 months or anything like it. It does make me curious about the nature of the 44-month cycle in the lower tropospheric temperature … particularly since you can see the same 44-month cycle (at a much lower level) in the HadCRUT4 data. However, it’s not visible in the Berkeley Earth data … go figure. But I digress …
I’m sure you can see the problem in all of this. I’m just not finding anything at 10 years 7 months or anything like that in either surface or satellite lower troposphere temperatures.
I make no claims of exhausting the possibilities by using just these three analyses, of the HadCRUT4, the Berkeley Earth, and the UAH MSU T2LT temperatures. Instead, I use them to make a simple point.
If there is an approximately 11 year solar signal in the temperature records, it is so small that it does not rise above the noise.
My best wishes to everyone,
w.
PERIODICITY THEORY: The underlying IEEE Transactions paper “Periodicity Transforms” is here.
DATA: As listed in the text
CODE: All the code necessary for this is in a zipped folder here. At least, I think it’s all there …
USUAL REQUEST: If you disagree with something I said, and yes, hard as it is to believe it’s been known to happen … if so, please quote the exact words you disagree with. That way, everyone can understand your point of reference and your objections.
@Willis Eschenbach “The average cyclical swing in TSI over the period of record is 0.6 W/m2. Note that to calculate the equivalent 24/7 average insolation on the earth’s surface you need to divide the W/m2 values by 4. This means that Dr. Roy and others are looking for a temperature signal from a fluctuation in downwelling solar of .15 W/m2 over a decade … and the signal-to-noise ratio on that is frankly depressing. This is the reason for all of the interest in “amplifying” mechanisms such as cosmic ray variations, since the change in TSI itself is too small to do much of anything.”
What do you mean by a downwelling of 0.15 W/m2 over a decade? 0.15 W/m2 multiplied by a decade is a hell of a lot – so maybe you mean something else?
We have accurate readings of TSI from only 26th March 2003. I thought I’d check the data myself. The difference between TSI received from 26/05/2003 to 26/01/2004 and from 4/08/2008 to 6/04/2009, a period of 245 days, is 102 W/m2 or 25.5 W/m2 over the surface of the Earth. That is the Earth received about 1.48×10^16 Watts more during the former period than the latter.
Does this show up in the temperature charts. I think it does. What more of a “signal” do you want?
http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_March_2014_v5.png
I got hung up staring at figure 4, since I was earlier looking at a graph of the temperature patterns over the last several ice age stadials. Figure 4 looks like a compressed 110,000 year record of stepped cooling to a low point, with sudden warming of the interstadials. Does the sun employ the same cycle pattern on multiple time scales? I’m beginning to suspect changes in the earth’s orbit aren’t the sole cause of ice ages.
Steven Mosher says:
April 11, 2014 at 11:11 am
“Do you really conclude that the sun does not have a big influence on our climate? Riddle me this: What is the most influential source of energy that warms our planet?”
1. the sun supplies all the energy.
2. the variations in that power are small.
3. these variations do not influence the CLIMATE
4. climate is the long term average of weather.
There are exceptions. when we look over really long periods you will find evidence that orbital changes do influence the climate and that the faint young sun does as well.
But to the actual point. The changes from 1850 to today are not solar driven
A) the variations are small relative to the changes
B) there is no coherence between the TSI record and the temperature ( which is just PART OF the climate)
C) If you want to identify the cause of the change in temperature, you need to look at something else.
what is not a cause.
1. natural variation. natural variation doesnt explain natural variation.
2. ocean cycles. ocean cycles describe patterns in data they do not ’cause’
a good candidate for study?
well the intuition that the sun is the main cause is good one. the sun supplies the power received.
does anything else cause forcing or change forcing or modulate forcing.
yes: the atmosphere and what it is made of
++++++++++
I asked: “Do you really conclude that the sun does not have a big influence on our climate?”
And you said it supplies all the energy. That’s not completely, true, it supplies most of the energy. But let’s just say it’s 100%. You’re saying that something that supplies all of the energy to our planet does not have a big influence on our planet. And then conclude – and only changes in our atmosphere are responsible.
Of course we would agree the sun affects our climate since it supplies all the energy. And of course changes in atmosphere affect our climate.
I also submit that there is good knowledge of our atmosphere being changed by changes in the sun. This is why your original statement was taken to task.
Richard says:
April 11, 2014 at 9:22 pm
Sorry for the confusion, Richard. Curiously, my writing is never as clear to others as it is to me … go figure.
In any case, I didn’t say “a downwelling of 0.15 W/m2 over a decade”. I said a fluctuation in downwelling solar of .15 W/m2 over a decade, meaning that the sun goes up and down by that much over a period of ten years. It doesn’t mean a constant forcing of 0.15 W/m2 as you seem to think.
w.
Richard says:
April 11, 2014 at 9:22 pm
It’s possible that you are looking at something different. It is true that the planet moves closer to and further from the sun, and this changes the instantaneous sun strength (although not by as much as you claim).
However, that doesn’t make sense, because you have compared 245 day of solar data from May to January on one hand to 245 days of data from August to April. So I haven’t a clue why you got that result.
But since (as appears to be your habit) you haven’t provided a link to your data, I’m afraid I can’t comment on it.
In any case, the TSI data that is normally cited and used is standardized so all of it reflects the strength of the sun at a constant fixed distance from the sun. That way, the data only contains the variations in the solar strength itself, and doesn’t contain the changes due to the elliptical orbit of the earth around the sun.
w.
You have to see that cosmic radiation is concentrated in the middle and high widths, causing changes in the ozone, in accordance with the geomagnetic field. If the magnetic activity of the sun falls, the radiation flux will significantly increase in these areas.
http://terra2.spacenvironment.net/~raps_ops/current_files/rtimg/dose.15km.png
http://www.cpc.ncep.noaa.gov/products/intraseasonal/temp50anim.gif
Willis,
“I looked at whether TSI or anything else that varies in sync with the sunspot cycle is affecting temperature … and so far, the answer is a resounding “No”.
I agree–as I said, I don’t think that the 11-year periodicity in itself is going to tell us much about the relationship between the sun and global temperature. It’s what happens DURING the 11-year cycles that is telling us something, i.e., the sunspot number is a symptom of what is happening with the sun’s magnetic field and that is the most important variable. The incidence of low sunspot numbers of the Wolf, Sporer, Maunder, Dalton, and 1880-1915 Minimums during cool periods gives us a clue that we should look for evidence of decreased solar magnetic fields at those times. The cool periods span more than one 11-yr cycle, typically up to three cycles of low sunspot numbers. The higher 10Be and 14C isotope production rates during these cycles tell us that the cosmic radiation flux was high and thus the solar magnetic field low. So the solar connection looks very real in the data, but it isn’t going to show up in 11-year periodicity itself. So I don’t think we need to wait for an 11-year periodicity connection to show up before looking at cause-and-effect relationships between the sun and global temperature. The real-time data speaks for itself.
Don
Don Easterbrook
The increase in GCR is just visible especially now, when we have peak activity at 24 cycle.
Don Easterbrook says:
April 11, 2014 at 11:12 pm
Don, you are making the claim that I discussed upthread. This is the claim that the system somehow is impervious to the large 11-year changes in sunspots / TSI / magnetism / whatever… but at the same time it is exquisitely sensitive to the much smaller slow secular variation and drift of sunspots / TSI / magnetism / whatever.
Now … if you can explain how that happens, you might be on to something. Me, I don’t see how that could possibly be the case.
Do you think, for example, that the seasonal changes in solar input could show up in the data, but NOT the daily changes in solar input? Could the system not change from the large solar day/night swing in input, but still change from season to season due to much smaller solar changes?
And if you think so, what physical process could possibly mask out the daily changes but allow in the much slower seasonal changes?
Because this is exactly what you are claiming, that the system somehow ignores the much larger changes in the 11-year solar cycle, but responds to half-century long changes in the same variable(s) that are a couple of orders of magnitude smaller?
Call me crazy, but I misdoubts that claim of yours …
w.
Willis I wonder whether it might be better to pick a single site that has a quality data set, and is not influenced by the UHI effect, and compare its maximum temperatures only, with the various solar measurements.
Ian Bryce says:
April 12, 2014 at 12:39 am
Thanks, Ian. Upthread I showed periodicity of the Armagh data, one of the world’s longest continuous temperature datasets. However, I was using the mean data, not the max. Hang on, I think I have the max data … … OK, dug it out, converted it to R. No difference from the previous analysis of the mean data. Here’s that previous result again:
Note that not only is there no sign of an 11-year cycle, there’s no large cycles at all. The periodicity analysis of both the min and max data is virtually identical to that.
Finally, I looked at the periodicity of the monthly temperature range. I did this because the study of Forbush events that someone linked to above used daily temperature range as a proxy for cloud cover. The thinking is that clouds warm the nights and cool the days, so more clouds would lead to a narrower temperature range.
However, the periodicity analysis of the monthly temperature range showed no ~ 11-year cycle … nor any other cycle for that matter. So now I’ve investigated three more datasets, and found no 11-year cycles.
Still waiting …
w.
I thought of something else: a periodicity that should have popped up in the temperature data sets but didn’t.
1) Since the data was monthly values, and
2) Since the sun warms first one half of the world during half of a year and then the other half of the world during the second half, and
3) Since the data was “land” measurement data, and
4) Since there is much more land mass above the equator than below, and
5) Since there are many more temperature measurements in the northern hemisphere than in the southern, . . . . . . .
well shouldn’t there have been a HUGE periodicity spike at 1/2 year when supposedly the sun was warming all of those northern hemisphere temperature guages?
Willis Eschenbach says:
April 11, 2014 at 10:59 pm
It’s possible that you are looking at something different. It is true that the planet moves closer to and further from the sun, and this changes the instantaneous sun strength (although not by as much as you claim).
However, that doesn’t make sense, because you have compared 245 day of solar data from May to January on one hand to 245 days of data from August to April. So I haven’t a clue why you got that result.
But since (as appears to be your habit) you haven’t provided a link to your data, I’m afraid I can’t comment on it.
This is the data Link. It’s from SOURCE. The reason why I didn’t cite it was because I presumed you knew about it. I have taken the daily data of TSI.
http://lasp.colorado.edu/home/sorce/data/tsi-data/#summary_table
It may not agree with any logic of yours but I have got the result because the data says so.
And I might add its May to Jan 2003/4 and Aug to April 2008/9 Those were the periods of Max and Min Solar Irradiance
PS the computation actually comes to about 119 W/m2 (not 102) or 29.8 W/m2 on the Earth’s surface. And that’s a forcing of about 1.73×10^16 Watts over that period
SORCE even
Willis Eschenbach says:
April 11, 2014 at 10:59 pm
You might get a slightly different result as there are some days with 0 data. For these I have taken values in between the ends of the discontinuity.
Ok Willis
Close your eyes and you will not see it.
http://virakkraft.com/periodicity-sun-temp.png
http://www.leif.org/research/Scafetta-Report.pdf
Richard had said:
April 11, 2014 at 9:22 pm
I questioned that. How could TSI be different by 102 W/m2? And what was the source of his data? The answer:
I never, ever assume what someone used as a data source. I’ve been bitten too many times to guess what you have neglected to specify.
Richard, from your link, showing the SORCE data:
Now … you do see that the variations over the 11 year cycle are on the order of 0.5 to 1 W/m2? The range of the entire scale of the graph is only 3 W/m2.
So while you may claim that the difference between two 245-day periods is 102 W/m2 … I’m not seeing it in the data you used.
w.
lgl says:
April 12, 2014 at 1:48 am
That makes no sense at all. What you have shown in those graphs is simply the graph I showed, clumsily overlaid with a Fourier analysis of “synthetic data”. Now “synthetic data” seems like an oxymoron to me … and a Fourier analysis (FFT) of synthetic data seems perfectly transcendental, by which I mean totally disconnected from reality.
More to the point, I don’t understand what you think overlaying my graphs with the FFT of some random hunk of synthetic data means … but to me it means nothing. I asked for a TEMPERATURE DATASET containing some visible 11-year signal. Overlaying my graph with the FFT of “synthetic data” is nothing like what’s wanted and needed.
w.
Willis Eschenbach says:
April 12, 2014 at 3:24 am
Richard, from your link, showing the SORCE data:
Now … you do see that the variations over the 11 year cycle are on the order of 0.5 to 1 W/m2? The range of the entire scale of the graph is only 3 W/m2.
So while you may claim that the difference between two 245-day periods is 102 W/m2 … I’m not seeing it in the data you used.
Dear Willis,
Please assume what I have said is gospel. I know not a thing about Kopp or Krivovo or Ball or the IPCC AR5 or that graph, though its shown on the page. On the link I sent you there is the TSI data “Available TSI Data Summary Table/Data Access”. I have downloaded the Full Mission Download, Daily Data, which is in a text file. This gives the daily TSI values starting from 26/02/2003 and ending on 5/04/2014. I have converted that into an Excel file and made a graph of the TSI vs the dates. This gives me a clear picture of the TSI variation with time. There are many gaps in the data. I have filled those in with average values over the period.
As for my “claim” that the difference between two 245-day periods is 102 W/m2 (actually 119 W/m2 as I have later said), this “claim” has arisen by adding the TSI vaues of the two 245 day periods together and then subtracting them, which as you know Excel does for you in the blink of an eye. Those are actual values from the data.
Changes in the galactic radiation at both poles of the Earth are the same and depend on the magnetic activity of the Sun and latitude.
http://neutronm.bartol.udel.edu/realtime/southpole.html#levels
http://cosmicrays.oulu.fi/webform/query.cgi?startday=20&startmonth=10&startyear=2013&starttime=00%3A00&endday=06&endmonth=04&endyear=2014&endtime=00%3A00&resolution=Automatic+choice&picture=on
The only real measured data of TSI we have is from 26/02/2003 onwards. All other previous data are reconstructions, mainly from the Sunspot numbers I suspect, and no one really knows if they are true or not.
Richard says:
April 12, 2014 at 4:23 am
The only real measured data of TSI we have is from 26/02/2003 onwards. All other previous data are reconstructions, mainly from the Sunspot numbers I suspect, and no one really knows if they are true or not.
Not so. The real data starts in 1978.
lsvalgaard says:
April 12, 2014 at 4:31 am
Richard says:
April 12, 2014 at 4:23 am
The only real measured data of TSI we have is from 26/02/2003 onwards. All other previous data are reconstructions, mainly from the Sunspot numbers I suspect, and no one really knows if they are true or not.
Not so. The real data starts in 1978.
And where does that come from? Who measured it and how accurate is it? Where is the link to that data?