Guest Post by Willis Eschenbach
I hear a lot of folks give the following explanation for the vagaries of the climate, viz:
It’s the sun, stupid.
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.
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“What I don’t believe is that it’s an amplitude-modulated carrier wave with two sidelobes.”
Well lsvalgaard seems convinced it is a sign of modulation and says there is theoretical basis for such a modulation ( beyond what is suggested by the power spectrum ).
“I said there is no regular signal in the sunspots, Greg, because there isn’t one. The cycle lengths vary, with no apparent pattern. Where is your regular signal?”
Your software fits regular signals. The major components ARE regular signals yet you say ” there is no regular signal in the sunspots,”
Sure the “length” of the dips in the time series is variable because your can’t even properly define when a cycle starts or ends and there’s a lot of minor periodicites (noise or otherwise) then can push both troughs and peaks back and forth.
The whole point of spectral analysis is to untangle that visual mess of the time series and see whether there is any structure to it. You did that, you demonstrate it’s there yet for some reason don’t “believe” that it’s there.
Seems odd to me.
Willis;
Here is some more food for thought.
http://www.climate4you.com/images/CloudCoverAllLevel%20AndWaterColumnSince1983.gif
One of the aspects noted is the shift of mid level clouds as the lower 1.2um band interacts with water in the mid troposphere. You will not the shift and increase of these clouds much higher in the atmosphere which reflects much more heat than lower level clouds.
I am trying to find a good spectral analysis over time to show the shift in solar output within bands.
“The cycle lengths vary, with no apparent pattern.”
Is that your sticking point? It’s apparent that there’s a rough cycle. A bit more a bit less but it does not run off even over hundreds of years.
The reason for spectral techniques is help analyse that which is not always “apparent” or to determine whether some that ‘appears’ to be happening really is , and it’s not the mind seeing faces in the the clouds.
In fact if you try to model SSN it’s not cos ( 130years ) * cos ( 11 years ) it’s more like abs( cos ( 130years ) * cos ( 22 years ) ). When you FFT that or SFT that it has to fit twice the frequency.
You spoke last time about doing SFT with other functions. I think this would be a good subject for such a test. I may give it a try tomorrow but I’ve done enough for one day.
In fact I will because there’s a lot of this climate data that seems to be abs(cos) rather than purely harmonic. Now I have the code, I’ll try hacking it about at bit.
I think at least 3 people have mentioned some form of the suggestion that the earth may be a low-pass filter. This was the only response I saw to that idea:
Willis Eschenbach says:
May 24, 2014 at 4:20 pm
…..
Thanks, Mick, but I’m not buying that explanation at all. The earth’s temperature swings on the order of 6°C peak to peak over the course of a year. Why would it not respond over an 11-year period?
…..
This does not convince me that the earth-as-a-low-pass-filter explanation is wrong. A much higher amplitude signal could get through a low-pass filter, even if its frequency is higher. Low-pass does not mean it stops all higher frequency signals regardless of amplitude. It attenuates the signal, but if the signal has a high enough amplitude, it can get through.
The feasibility of the solar theory can be defended (I think) by saying that the 11 year cycle has a low enough amplitude, and a high enough frequency, to be completely filtered. The very long term solar cycle (involving the Maunder Minimum) has a much lower frequency (and also has a much higher amplitude, by the way), so the effect is not filtered. Again, the yearly seasonal signal referred to has the highest frequency, but has such a high amplitude that it gets through anyway, in this way of thinking.
I’ll say it again. Watch Dr. Miyohara. Cosmic Ray 22-year cycle: at 9.5 min in. Relative Humidity in Japan and Cosmic Rays, 1620-1760 AD, at 19:21 min. Strong correlation. She’s not chopped liver.
rbs – Thx for the Pustilnik et al link. Excellent.
Greg Goodman – I agree with you (and M Simon, Matthew R Marler, et al) re the unknown. Ascribing things to causes not known (aka “we don’t know”) is at the core of science. The alternative is ascribing things to the wrong causes or to invented causes.
richardscourtney : “The oceans CAUSE the “1 year cycle in temperature”. “. It’s so blindingly obvious, why didn’t I see it like that before? Thanks.
Kate Forney – re the flaws in Willis’ argument: OK, maybe Charles Nelson didn’t spell any out and was unnecessarily abusive, but there is a significant flaw in Willis’ argument. First, please note that when he says “despite looking in a whole lot of places, I never could find any trace of the 11-year sunspot cycle in any climate records “, or just about anything else for that matter, he speaks nothing but the truth. But the flaw is that he is only looking for a reasonably regular or linear type of effect. There are many reasons to suppose that the effect would not be like that, and several commenters here have given examples of observations that suggest that the effect does indeed exist. The final flaw is that these are being dismissed using arguments based on the regular/linear type of logic. For example, he dismisses one graph saying “Any graph missing the middle third of the data provides no “evidence” of any kind. Now I heartily agree that a graph missing its middle third is very dubious, and in a simple linear world it should be summarily dismissed, but in a complex coupled non-linear world it just might (no more than that) be providing a valuable clue.
Willis writes:
Whether sunspot numbers were declining post 1960 is not what matters. The average level of solar activity from the 1920’s through the end of the Twentieth Century was somewhere between high and very high. If solar magnetic activity does drive global temperature then what matters is the level of activity, not whether it is rising or falling.
Many prominent climatologists make this fallacious argument that late 20th century warming cannot have been due to the sun because solar activity was not rising over this period. Collecting examples has been one of my hobby horses. Two years ago I sent the authors of these quotes an email, suggesting that they must be assuming that by the late 1970s (the beginning of the warming that occurred during the second half of the 20th century) ocean temperatures had already equilibrated to whatever forcing effect the high level of solar activity was having. Otherwise warming would continue until equilibrium had been reached.
Of course none of them had mentioned any assumption about ocean equilibration in their analyses (as Willis does not). I was giving them an out. Their claim that warming would be caused by the change in the level of the forcing rather than by the level of the forcing is blatantly unscientific, but if they were making an unspoken assumption that the oceans equilibrate rapidly to a change in forcing then we could talk about THAT.
Yes, replied Lockwood and Solanki and several others, they WERE assuming rapid ocean equilibration (which does not stand up to the least bit of scrutiny).
As others have pointed out, there isn’t an 11 year cycle, there is a range from 9 to 15 or so. But more than that, IIRC, few of the cycles are actually AT 11 years, with the stronger nodes being both below and above that point. ( For some reason, 9.5 and 12 ish come to mind… but it’s been a long time since I saw that write up and don’t have a link at hand)
So you look for an 11 year period in data known not to have an actual 11 year period. Once again “averaging” strikes it’s fatal blow… (Averaging is used to hide things. Sometimes that is useful, like hiding noise to see the base note, but often it just hides and obscures truth. Sometimes it brings to the front something that isn’t real and doesn’t exist. Like the average person being a semi-hermaphrodite… ALWAYS be wary of anything that uses averages…)
Not just Hershel, but also Jevons found a crop price solar cycle link. Jevons went through large volumes of data from the British Empire, including a load of data from India (IIRC), but he looked at actual match to solar cycles, not to a mythical average period.
I know you love your new periodogram toy / tool, and it can be very useful for a lot of things; but do recognize that it is “exactly wrong” for looking for evidence of a VARIABLE length oscillation impact. Line up the peak or bottom of a cycle with the other variable. Wiggle match. Then you can start looking for what statistical / math tool to QA check your vision.
Ah, found a reference (it’s just doing simple math on the actual sunspot data so anyone can check it):
http://personal.inet.fi/tiede/tilmari/sunspots.html#twotypes (Timo Niroma )
That your priodogram finds an 11 year peak makes it immediately suspect. An analysis ought to find a peak at a bit under 12 years ( 11.85 ) and a touch over 10 years ( 10.25 ) but not AT 11 or 11.1 years. That your Fig. 2 finds a peak at 11 years, higher than the ones at about 10 and about 12, implies the technique “has issues”…
To then not find a fictional 11 year cycle in other data is not much of a surprise when the real mode is a wandering range of period lengths with nodes at about 10 and 12 but tending to avoid the 11 year average.
If the 11 year solar cycle has no influence on surface air temperatures, how and why is it included as a either a major forcing or basically a nonexistent forcing?
You can lead a horse to water, but you cannot make him/her drink. Belief trumps data. Every time. And slows any benefit -even stops benefit- that can be realized when presented with good solid data.
ducdorleans says:
May 25, 2014 at 2:43 am
Statistics is different from a (rock) solid theory? Who knew?
But on the off chance you are serious, since “a solid theory” and “statistics” are entirely different universes, yes, I’d agree they are quite different.
What either of those have to do with periodograms and the Quest for the 11-Year Signal is a mystery to me, though …
Duke, I’m just looking for a signal. I have no theory, since I have no signal. And I have no statistics, since I have no signal. I’m just looking, whether or not I’m proficient in R …
w.
Willis,
I would strongly recommend this paper by Nir Shaviv.
http://www.sciencebits.com/files/articles/CalorimeterFinal.pdf
As many others have said, the analysis presented here suffers from the fatal flaw of **assuming** the solar cycle is 11 years long, and then when not finding a link to climate indicators climate indicators **claiming** that there is no detectable correlation to the **solar cycle**. Since the actual solar cycle length is not fixed the conclusions do not logically follow from the analysis.
To effectively test the hypothesis presented here, one would need to test the relationship between the actual observed climate cycle length and any changes in those climate indicators. It bears making explicit but for a solar cycle that is 9 or 15 years long, there is no reason for the solar effect on climate in year eleven of that cycle to resemble *at all* year eleven in an eleven year cycle.
Cheers, 🙂
Mr. Eschenbach, you have the patience of a saint. Thanks for your consistently clear thinking.
Willis
Have a look at the following correlation between secular global mean temperature and sun spot count:
http://www.woodfortrees.org/plot/hadcrut4gl/mean:756/normalise/plot/sidc-ssn/mean:756/normalise/from:1880
What do you think?
E.M.Smith (May 25, 2014 at 8:28 pm) makes some very interesting observation concerning the “11 year” sunspot cycles being mainly ~10 years and ~12 years with little in the middle at ~11 years. Willis finds the data to be broadened but still largest at ~11 years. Smith correctly points out the often-seen evils of averaging, as an associated complication here.
As a signal processing engineer I look at everything as a filter! We use an analysis filter to examine the sunspot cycle. Distinguishing 10 years or 12 years from 11 years (about 10%) is already “moderate Q”. We can do a LOT better with electronic instruments on the lab bench, but for chaotic nature, it is not surprising that there is a blur. So the ~11 year sunspot cycle looks like an acceptable candidate for a quasi-periodic driving signal.
If we then say that this established potential “solar drive” in turn manifests itself in a manner that translates to effecting climate on Earth, we are looking at the Earth as a filter (a system at least) and postulating the drive as the input to that filter, and various climate parameters as multiple outputs (also the filter has multiple inputs). A Solar/Earth physicist may well calculate possible mechanisms and climatic responses to the driving signal. Willis claims no response is found.
What does a signal processing engineer make of a filter that is not responding. Well, it could be that someone forgot to connect the “input cable” (no mechanism). Or perhaps the experimenter forgot to turn up the gain of the signal generator (weak drive). Or of course the filter may responds to many frequency bands but have a relative notch (or be low-pass) at the frequency set by the drive. Finally, the detection instrument may be improperly set up. All of these things happen in the lab.
Smith then says “To then not find a fictional 11 year cycle in other data is not much of a surprise when the real mode is a wandering range of period lengths with nodes at about 10 and 12 but tending to avoid the 11 year average.”
I disagree. In the bench filter we check this by using the SAME instrument (like a scope) on the input and output. Willis does this – he doesn’t look for just 11 at the output. The engineer here suspects that the signal is weak, or the filter doesn’t like that (high) frequency very much.
Suspicious0bservers says:
May 25, 2014 at 3:58 am
Suspicious, it’s clever of you to claim, without the slightest attempt to support the claim, that “11 years is not long enough”.
Why not? And not long enough to do what? As someone pointed out upthread, when the eclipse occurred, the temperature dropped immediately and precipitously. Since temperature can change that fast, why is 11 years “not long enough” for a small temperature change? That makes no sense.
All I can deduce from your rant is that you, like the other folks here, can’t find the 11-year cycles either. And like them, you have your excuse ready. You don’t provide a scrap of support for the excuse, but you pull it out anyhow.
w.
Matthew R Marler says:
May 25, 2014 at 7:07 pm
quoting RichardCourtney…
“The reason for the global seasonal temperature change is the different coverage of Northern hemisphere (NH) and Southern hemisphere (SH) by water (land is not as good a heat sink as water) so the seasonal variation is greater in the NH than the SH. This support’s Monckton’s claim of a great oceanic heat sink effect.”
Isn’t it *both* the differential sea surface area and the change in total insolation from perihelion to aphelion?
————————————————————————
Yes Mathew, but the affect on the atmosphere is the opposite of what one would expect. (More solar insolation in the SH summer = less atmospheric GAT)
Willis is looking for an small signal in a short (11 year) cycle against a background of many other climate factors, some instance, some which take centuries to manifest, some cyclical, some not, but in combination inherently chaotic. (A daunting task for any one climate factor, and I have yet to see any one factor that has a constant signal)
In theory a change in solar insolation from a weak cycle to a strong cycle should produce a steady graph if it had an effect on GAT. What happens annually should be a clue to Willis that the earths insolation to disparate ocean depth system does not work that way.
In the SH summer the earth receives almost 7% more insolation, (a huge increase dwarfing any CO2 affect) yet the GAT drops, it does not rise. A reasonable question to ask is does the earth, (land, ocean and atmosphere) gain or lose energy during the SH summer? More SH and total solar insolation,= less atmospheric GAT. For how long would this last if it did not change? Would the ocean continue to warm until they warmed the atmosphere? (Does this heat hide in the first 700′?) How long would that take? What is the ocean residence time of the major aspects of solar wavelength that change the most during solar cycles? Does the Sun have cycles within cycles, repetitive Maunder Minimums, and periods of repetitive strong cycles?
Regarding Alec Rawls says:
May 25, 2014 at 7:52 pm
=======================================
Thank you Alec. I think you once made the analogy of a large pot of water on a steady low burn. Turn the heat up from a long duration low to max for two minutes, then turn it back to medium high. It should shock no one that the water continues to heat after the flame is turned down to medium high. The ocean is a large pot indeed.
Only two things affect the energy content of a system in a radiative balance. Either a change in input, or a change in the residence time of energy within the system. (For this system we are talking about the land, the oceans and the atmosphere.)
Konrad says:
May 25, 2014 at 4:19 am
Konrad, I fear in among the 394 comments so far, I didn’t see it. So your nasty tone is unwarranted.
I don’t know why I should respond to such an unpleasant person, but let me see if I can find the comment and discover what th “effective emissivity” is that you are babbling about … hang on …
Well, now, isn’t that just peachy? In fact, this is the first mention of “effective emissivity” in the whole thread, and you’re busting me for not answering it earlier?
Run the “empirical experiment” to do what, exactly?
As I understand the question, Konrad, the situation is a sphere (the planet) inside a shell (the atmosphere), with radiation passing in both directions between the two. Since the reflectivity of both is quite low, the effective emissivity is very close to the theoretical blackbody cavity emissivity. As a result, there is only one emissivity value used in climate calculations. For water, it’s on the order of 0.96 or so. In fact, for most natural substances, it’s well about 0.90. As a result, it is usually assumed to be 1 for all but the most detailed calculations.
Or as Geiger put it in “The Climate Near The Ground”, my climate bible (first published in the 1950’s when people still measured things instead of using models, and now in the seventh edition):
Hope that helps …
Geiger and every other serious scientist I know of thinks that the oceans are a near blackbody for thermal infrared. Actual measurements show the oceans are a near blackbody for thermal infrared (Geiger quotes the measurements made by U. L. Gayevsky). So I fear that your claims will require more than your assertions to establish them …
w.
PS—Do you really think the insults help your scientific case?
rbs says:
May 25, 2014 at 4:52 am
Thanks, rbs. Unfortunately, they haven’t used sunspots. Instead they’ve used variations in 10Be. I’ve discussed the problems with 10Be before. In addition, their data is not available anywhere online that I can find, so I can’t analyze their results. However … they seem too good to be true, 100% correlation.
w.
From Girma on May 25, 2014 at 9:58 pm
I think you’ve adequately shown how too much smoothing ruins the data. A 63 year running mean, when you’re only using 133 years of SSN data?
First, I’m going to specify from:1850 and to:2014 to take full advantage of the HADCRUT4 data. And since it’s available, I’m going to also add in the Tropics (30°N-30°S) subset, as any solar effect should be most noticeable where sunlight has the greatest effect.
BAM, there it is! Will you LOOK at that Practically PERFECT match between tropics and sunspots!
Which indicates the problem. And as a side note, see how the ends are 31.5 years (half of 63) shorter than the range, indicating a true running mean, if there’s not enough data then there is no result.
Now I’ll repeat the same graph but with a more reasonable 5yr+1mo (61 mo) running mean. The month is there so there are whole months on each side of the particular month the mean is being generated for. Actually, I’ll put it on the same graph as what I graphed before, with an offset for clarity.
Whoops, there it is! Your beautiful curve-matching is shot. In broad strokes, you can see SSN following temperatures, until the late 1970’s (the Great Pacific Climate Shift?) where SSN goes down while Temperatures go up. And temperatures had a downward slope starting about 1940, while your over-smoothed curves arc up, up, up.
Smoothing spoils data. Use only enough for clarity, and avoid calculating from smoothed data. Minimal smoothing for presentation, crunch from as raw as you can.
Ah, the “very large (open) pot of pure water on an (conventional AC electric) stove with a conventional regulator (at atmospheric pressure and temperature in a closed room under standard conditions…..) These thermodynamic analogies get soooooooooooo cumbersome so fast …. 8<)
Aside: But, if I am looking for a 11 year cycle (but am I not wrong in assuming that 11 year cycle if the actual sunspot cycles are not ever actually at 11 but at 10.2 OR 11.8 as found above!), what would be the "symptom" of changing the amount of heat energy input with respect to measured temperature? Can you really assume that you know all of the physics involved closely enough to know what you are measuring?
If the water were not yet boiling, then "maybe" changing heat input would change the temperature. Depending n when I measured temperature, and whether the water was frozen or not when I turned on the stove. If I varied the electric current (as pointed out above) so fast that the "average" AC current at 60 Hz (or 50 in Europe) was no longer at 60 Hz, would it matter?
Consider if I was ramping that average AC current (while holding it constantly at 60 HZ) in an 11 minute up-and-down cycle, would I see any difference in temperature in a 5 gallon pot? No. Not if I were measuring either too slow or too fast with respect to the change in heat input.
And, I would see absolutely no change at in water temperature at all if the water were boiling: The temperature would stay at 100.0 C regardless of what I changed the current to nor how frequently I changed the current. (As long as current-in energy exceeded total heat losses. If heat losses exceeded heat input over time, the pot would cool, EVEN IF I INCREASED CURRENT!
Now, the rate of water removal during boiling would vary as i changed average current but that rate of water removal could not be measured by any thermometer! It would be slowed by lag times in all of the points, some quick, some slow as well. Further, if the water were boiling, and I DID want to see any effect from a change in oven current, I would need to measure water level at a rate fast enough to "catch" useful data. If that were done, I would need to remember that a faster boiling would create more bubbles, which (temporarily!) raises water level. Then, later on as water boils away, the faster boiling rate removes the water from the open pot. But what am I measuring when the actual pot water level goes down? The loss of bubbles from today's cooler energy input, or the loss of water from yesterday's faster boiling?
So, would I ever actually "measure" that relationship between varying the stove current and the final effect on water level and temperature?
Hoser says:
May 24, 2014 at 11:49 pm
Wow. 157 so far took the bait.
[??? .mod]
Sorry. I just found nothing really redeeming in more Willis foundering. I like Willis, I really do. Not kidding in any way. But there comes a point where it’s just watching grass grow. Now the grass can be interesting. It can be several shades of green, even some green we never really noticed before. But it’s grass. And it’s still growing.