The Missing ~ 11-Year Signal

Guest Post by Willis Eschenbach

Dr. Nir Shaviv and others strongly believe that there is an ~ 11-year solar signal visible in the sea level height data. I don’t think such a signal is visible. So I decided to look for it another way, one I’d not seen used before.

One of the more sensitive signal analysis tools in our arsenal is the Fourier transform. If we have a complex signal, like say the sunspot signal, Fourier analysis allows us to see just how strong the different frequencies are that make up the signal. To start with, Figure 1 shows the sunspot record.

Monthly Sunspots 1749 2015Figure 1. New SILSO monthly sunspot record.

As you can see, there is a clear cyclical signal. However, the cycles vary in length. A Fourier periodogram reveals the strength of the various underlying signals:

fourier periodogram monthly sunspotsFigure 2. Fourier periodogram of the data shown in Figure 1. Shortest period shown is four years, as there are no strong cycles with shorter periods.

As you can see, most of the power is in the 11-year and nearby cycles. There is cycle strength out to twelve years or so. There is also a second smaller group of cycles with a period of ten years, of about half the strength of the 11-year cycle.

Now, if there is actually a solar cycle in the sea level height as Dr. Shaviv believes, then it should peak somewhere around 11 years. To look for such a cycle, I decided to look at the sea level records from the tidal stations of the world. These are available from the Permanent Service for the Mean Sea Level. For your convenience in investigating the question, I’ve collated them as an Excel worksheet here.

I like to have an absolute minimum of three cycles of data to use for my longest term analysis. So I started by selecting all of the tide station datasets that have sixty years or more of data, to allow me to look at cycles up to about twenty years. There were 199 such records. Here are some sample periodograms of four of these longest tide records.

fourier periodograms four longestFigure 3. Four periodograms of long-term tidal records. Shortest period shown is four months. The scale on the left is the range (maximum minus minimum) of the fitted cycle as a percentage of the range of the underlying tide data.

The largest period in the tidal records, as we might expect, is a one-year cycle. There is also a smaller cycle visible at half a year (six months). However, as you can see, there is no readily apparent strong 11-year cycle, although Swinoujscie (top right) has a small hint of an 11-year cycle … or it may be a random fluctuation.

Now, the averaging of tidal data has some large problems. The different locations have widely varying tidal amplitudes, so the large swings tend to swamp the averages. As a result, I decided to average the periodograms rather than averaging the data. Since all of the periodograms are expressed in scaled units as percentages of the range of their individual underlying datasets, they are directly comparable. And since the random variations would average out, I figured that averaging them should reveal even small signals. Figure 4 shows the 199-periodogram average:

average fourier periodograms 199 long tide dataFigure 4. Average of the periodograms of the 199 long-term tidal station records. Note that the error bars are not the error of the mean, which is much narrower. Instead, they reflect the spread of the underlying individual results.

As with the four individual periodograms, the average clearly shows the one-year and the six-month cycles. And as expected, the averaging of so much data allows us to see even very small cycles. I note, for example, a cycle of a bit more than three and a half years. I’ve noticed this same signal before in other natural datasets, and I’ve never discovered its origin.

There is also a similar-sized small peak visible at about six and a quarter years, also of unknown origin.

But the purported ~ 11-year solar-related cycle? Nowhere to be seen. Not a hint, not a twitch.

Conclusion? If there is any ~ 11-year signal in the sea level height, it is so small as to be lost in the noise.

That was a main problem that I had with Dr. Shaviv’s study. He stated that there appeared to be a cycle in the short satellite sea level height data, and he claimed it was a solar cycle … but for me that’s backwards. For me, the starting point for investigation has to be noticing some verified unexplained anomaly in the actual observational records. First we have to find something unusual, then we can speculate as to its causes and consequences. For example, just what is the odd 3+ year cycle in Figure 4? Now that we know that cycle is real, we can speculate and investigate its origins.

So for me, until there is evidence of an actual ~11 year cycle in the sea level height, any speculation as to the possible solar nature of said unobserved cycle is wildly premature.

And that’s the story of the missing ~ 11-year cycle.

w.

For Clarity: If you disagree with someone, please quote the exact words that you object to. This allows us all to understand the exact nature of what you don’t agree with.

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251 thoughts on “The Missing ~ 11-Year Signal

  1. One of the more prevalent features of those trying to sell you something, or indeed those engaged in ideological thinking, and it applies to climate change right down to the core of the IPCCS terms of reference is to slip in an unproven assumption unnoticed as part of what purports to be a discussions about something else.

    The IPCC itself has terms of reference that can be couched very simply – to examine the magnitude and effects of human induced climate change.

    Never to examine whether there actually is any human induced climate change.

    This appears to be the same – to look at subset of a problem that slipped in as an a priori assumption.

    ‘How bad is the 11 year cyclic influence of the sun on sea levels’ does not allow one to comment on whether there actually is such an influence. In fact the way the question is phrased is designed to move the discussion away and on from that question.

      • Most prosecuting attorneys prefer “when did you stop beating your wife?”

        I do agree with Leo to some degree,but I think Willis question is a fair one because, in this case, he’s looking to find evidence relative to another person’s working hypothesis, not stating the fundamental research question.

      • Well, the IPCC also appears to have borrowed from another legal saw: “When the facts are on your side, pound the facts; when the Law is on your side, pound the Law; and when neither the facts nor the Law are on your side, pound the table!”

        The IPCC and it’s zombies seem to have the “pound the table” bit down…

    • Shaviv is a sceptic regarding AGW. However, he’s also an astrophysicist and, as such, more or less is constrained to be a theorist first if he wants any other physicists to pay attention. Despite the clear logic of arguing that empirical evidence should take precedence, as Willis does, many scientists will disregard empirical evidence in favor of a theory when there is a conflict. They then look for “evidence” of the theory in the data and astonishingly, they often find it. A theory is an explanation, while a conflict with data is a problem. The nice thing about theories is that they “predict” things, which one can then obtain a grant to go look for. The Higgs boson is a first rate example of this. Consider the cost of the LHC.

  2. Looking for 11 year signal in climate events is a waste of time, since it is based on the sunspot numbers which have no polarity. Polar fields, north and south hemisphere sunspot polarity are all 22 year periodic events.
    Sun has 22 year periodicity, full stop.
    22 year periodicity can be found all over place, global, land and ocean temperature, the Earth’s core magnetic field, tectonics etc.

    • Vukcevic,

      Looking for 11 year signal in climate events is a waste of time, since it is based on the sunspot numbers which have no polarity.

      I totally agree. The solution is to restore the missing 22 year Hale cycle to the sunspot record. The missing low frequency polarity signal can be added to the sunspot count by simply listing all even number cycle sunspots as positive sunspot numbers and turning all odd number sunspot cycle counts into negative sunspot numbers.

      • Hi Mr. Mulholland
        Further problem is that the most of climate data analysed are presented either as annual or monthly sequence of numbers. Sun doesn’t work on 30/31 or 365 days, its effect is directed at the Earth with a peak influence at around 27-28 days depending where in the sunspot cycle sun happen to be (latitude dependant differential rotation)
        http://www.vukcevic.talktalk.net/LFC7.htm
        This would make a year about 13 ‘solar months’ long, not 12, originally it was 10, then 11 followed by the current 12 (blame the Roman emperors). Yes I know, I could be accused of astrology; no solar rotation has nothing to do with 13 signs of zodiac!

      • And the 13 months of the Lunar cycle.

        And some trivia for you. Manetho, the 3rd century BC Greco-Egyptian historian said the Egyptians originally counted Lunar years (ie: Lunar months) instead of Solar years. This resulted in human lives that were 900 or so years long, as is to been in the early biblical record.

      • Given that the moon’s gravitational effect on tides is I think 5 times greater than the suns (because it is much closer), I would have expected a lunar component as well. There are a variety of lunar cycles which I think repeat every 18.6 years.

    • Assigning a sign to the sunspot number is meaningless and just introduces a spurious 22-yr cycle. Take random data between 0 and 1 assigned to each month for 341 years. Invert the sign for every 11 years (132 months), run the spectral analysis and, presto, behold the beautiful 22-yr cycle peak.
      And, in addition, the polar fields change sign at solar maximum, not at minimum

      • Leif,
        So there is a 90 degree phase difference between the magnetic signal of the 22 year Hale cycle and my spurious reconfiguration of the sunspot count data?

      • No, it is more complicated than that:
        The polar fields and the solar wind change at solar maximum, but the sunspot polarities in each hemisphere change at solar minimum, and at any given time the sunspot number is made up of spots in both hemispheres with opposite polarities, so no net change. This whole idea of assigning a sign to the total sunspot number which is made up of [approximately] equal number of spots in the two hemispheres with opposite polarities is meaningless.

      • There is nothing odd about 90 degree phase difference, it is found in all oscillating systems, from pendulum and electric circuits to the N. Atlantic (AMO- Arctic atmospheric pressure)

      • That they claim so does not make it so. There is a difference between a mathematical description and actual physics. A physical harmonic oscillator is a system that, when displaced from its equilibrium position, experiences a restoring force, F, proportional to the displacement. What would that force be? We know of no such force.

      • Hi Mr. Sable
        If you are referring to my spectral graphs, the analysis is not result of the fast Fourier transform (FFT). Analysis is done by a method developed for analysing audio signals, based on correlation coefficients employing 90 degree phase shifts. Each data set although only had 131 samples, it is extended with zero front and back symmetrical padding to 2000 elements in total (standard I used elsewhere).

      • Analysis is done by a method developed for analysing audio signals, based on correlation coefficients employing 90 degree phase shifts.

        Paper? Source code?

        You are going to have edge effects with zero padding, and the edge effects depend on how far the signal is away from zero at the edge. Have you verified for edge effects? In general those sudden changes produce a sync signal in the frequency domain…

        Peter

      • Mr Sable
        Thank you for your comments, I am well aware of the edge effects and windowing procedure, but for short data series as in this case, windowing would have significant reduction effect on the mid range (as 22 year is) periodicities. I prefer to keep original data as it is and ignore as a noise anything that falls below 6db of the peak component.
        If you are up to challenge, I would like you to suggest data series (available on line) of the similar length to the above, than both of us do spectral analysis and compare the results.
        I am looking forward to your reply

      • Hmm…. No response from Mr. Sable; as it often happens many commentators are quick to criticise others but nowhere to be seen when challenged to come up with goods themselves.

      • No response from Mr. Sable; as it often happens many commentators are quick to criticise others but nowhere to be seen when challenged to come up with goods themselves.

        It’s the nature of this forum, you can’t easily track responses especially on old topics.

        If you are up to challenge, I would like you to suggest data series (available on line) of the similar length to the above, than both of us do spectral analysis and compare the results.

        Sure, why not. Why not the actual data above? Why are you unwilling to publish your source code and data?

        but for short data series as in this case, windowing would have significant reduction effect on the mid range (as 22 year is) periodicities. I prefer to keep original data as it is and ignore as a noise anything that falls below 6db of the peak component.

        If you have for example a ramp function, the “noise” of the edge effects is huge, and pretty much takes over the analysis. Your 6db won’t help you. Since you don’t show the time-domain series of this data, I don’t know if there’s a ramp function. There certainly is for temperature, it is going up…

        There are other methods than windowing. You can (1) reflect the signal in time and thus make it pseudo periodic (an option for some matlab filter implemetations but not AFAICT FFT), (2) work on the difference of the signal, (3), remove any DC component of the signal (detrending).

        I’ve only got a window implementation done, it’ll take time to implement the other two. Which did you do?

        I’m working on a “low frequency analysis” toolbox, which is necessary because all the defaults in R, Matlab, Octave, etc. are exactly wrong for this. (the defaults are okay for mid-frequency analysis).

        Peter

      • Oh look, no response from Mr Vukcevic. However I assume he’s just not reading this thread anymore because it’s hard to read old threads.

        In response to this challenge:

        If you are up to challenge, I would like you to suggest data series (available on line) of the similar length to the above, than both of us do spectral analysis and compare the results.

        Here it is. Code that figures out what the resolution of period analysis is given the length of the data.

        The simple answer is: It is very error prone to resolve any two periods whose differences in samples/period are less than two samples part across the length of the data. This seems to correspond well with the Nyquist criterion.

        For example, if you are looking at 314 years of sunspot data, if you were to notice a peak at 41.5 years, this peak might actually be the result of peaks of multiple periods between 37 years and 48 years. It could be a single component at 41.5 years, but you can’t tell. Note that for 37 years there’s 8.5 samples/year and for 48 years there’s 6.5 samples a year.

        In general I wouldn’t trust any periodogram that attempted to show periods of the length of the data divided by 5. The errorbars get extremely large above 5. For example with 314 years of sunspot data, 314/5 = 63 years. Note that the actual range of combinations of periods that could result in this signal is from 52 years to 79 years. Pretty large error bars.

        Here’s two graphs that you should test your analysis code against. The first tests the resolution of the process using sine waves that are very close together (2 samples/period close), and the second shows analysis of sunspot data with an overlay of sine waves created at the size and period of peaks found in the sunspot data. I’ve taken the liberty of putting errorbars based on +/-1 sample/period from the observed peaks.

        This should all run in octave and probably matlab. Source code here (any files with “-” in them are scilab and should be ignored):

        https://www.dropbox.com/sh/xsu1mr76bqhlgz1/AABJTKn4Pj96YVjTyfbkhA_ba?dl=0

        And in particular these two files of code and the file of period resolution data I created that you can import into your tool of choice:

        https://www.dropbox.com/s/5tk2rjdl8ki6je0/vallowfrequencyanalysis.m?dl=0

        https://www.dropbox.com/s/d46k0v71jiw563m/testlowfreqanalysis.m?dl=0

        https://www.dropbox.com/s/92yulrwkswvhq2k/test-sin-res.csv?dl=0

        best regards,

        Peter

  3. While I think it unlikely that there is a detectable relationship between sunspots and sea level, I’m not sure this is how you would detect one if it did exist.

    The effect of solar via clouds is always going to be slight – even if it exists. It would be like looking for a candle flame when said candle is standing in front of a floodlight. Not surprising that orbital characteristics dominate. Allowing for argument that solar has an effect, then we might expect c.11 year variations in the rate of rise in sea level, i.e. accelerations of the overall trend, not of the sea level itself.

  4. Twentieth century sea level: An enigma, A Paradox, Another example of the cult of CAGW’s shenanigans.

    Willis,
    You cannot find a correlation between ocean level rise and solar changes as the majority of the ocean level rise is due to seagate manipulation of the ocean level satellite data. Tidal gages, the earth’s rotational speed changes, and mass balance and maximum possible thermal expansion support the assertion that the ocean level is rising at 0.5 mm/yr to 1.2 mm/yr, not 3.2 mm/yr. 3.2 mm/yr is impossible based on mass balance and thermal expansion.

    There are four fundamental problems with ocean sea level.
    1. Sea level rise is a fundamental pillar to push AGW madness in the climate wars. When the Envisat satellite data shows the sea level is falling, the solution is to just change the data without explanation. (See Seagate link below.)

    2. The sea level rise prior to the recent fall cannot be explained based on mass balance and/or thermal expansion. Something caused the oceans to expand. The something is now reversing. This is a real paradox. The warmists do not include a breakdown of the estimated physical reasons for the 3.2 mm/year sea level ‘rise’ as that would force them to acknowledge a sea level rise of 3.2 mm/year that is physically impossible, if sea level rise forcing is limited to more water in the ocean (mass balance) and thermal expansion.

    3. The sea level increase does not track planetary temperature. It is too smooth.

    the historic rise started too early, has too linear a trend, and is too large.

    4. The sea level increase does not track ice sheet volume. Greenland ice sheet mass has now started to increase. The increase for this year was 200 Gt.

    http://joannenova.com.au/2012/05/man-made-sea-level-rises-are-due-to-global-adjustments/
    Man-made sea-level rises are due to global adjustments

    ftp://falcon.grdl.noaa.gov/pub/bob/2004nature.pdf

    Mass and volume contributions to twentieth-century global sea level rise
    The rate of twentieth-century global sea level rise and its causes are the subjects of intense controversy1–7. Most direct estimates from tide gauges give 1.5–2.0 mm/yr, whereas indirect estimates based on the two processes responsible for global sea level rise, namely mass and volume change, fall far below this range. Estimates of the volume increase due to ocean warming give a rate of about 0.5mmyr21 (ref. 8) and the rate due to mass increase, primarily from the melting of continental ice, is thought to be even smaller. Therefore, either the tide gauge estimates are too high, as has been suggested recently6, or one (or both) of the mass and volume estimates is too low.

    http://www.pnas.org/content/99/10/6550.full.pdf

    Twentieth century sea level: An enigma
    The Intergovernmental Panel on Climate Change attributes about 6 cm/century to melting and other eustatic processes, leaving a residual of 12 cm of 20th century rise to be accounted for. The Levitus compilation has virtually foreclosed the attribution of the residual rise to ocean warming (notwithstanding our ignorance of the abyssal and Southern Oceans): the historic rise started too early, has too linear a trend, and is too large. Melting of polar ice sheets at the upper limit of the Intergovernmental Panel on Climate Change estimates could close the gap, but severe limits are imposed by the observed perturbations in Earth rotation. Among possible resolutions of the enigma are: a substantial reduction from traditional estimates (including ours) of 1.5–2 mm/y global sea level rise; a substantial increase in the estimates of 20th century ocean heat storage; and a substantial change in the interpretation of the astronomic record.

    Envisat’s satellite failure
    http://www.esa.int/Our_Activities/Observing_the_Earth/Envisat/ESA_declares_end_of_mission_for_Envisat
    https://wattsupwiththat.com/2012/04/12/envisats-satellite-failure-launches-mysteries/

    Current Surface Mass Budget of the Greenland Ice Sheet (Note the increase of 200 Gt this year)

    http://beta.dmi.dk/en/groenland/maalinger/greenland-ice-sheet-surface-mass-budget/

    Seagate
    http://www.21stcenturysciencetech.com/Articles_2011/Winter-2010/Morner.pdf

    The mean of all the 159 NOAA sites gives a rate of 0.5 mm/year to 0.6 mm/year (Burton 2010). A better approach, however, is to exclude those sites that represent uplifted and subsided areas (Figure 4). This leaves 68 sites of reasonable stability (still with the possibility of an exaggeration of the rate of change, as discussed above). These sites give a present rate of sea level rise in the order of 1.0 (± 1.0) mm/year. This is far below the rates given by satellite altimetry, and the smell of a “sea-levelgate” gets stronger.

    When the satellite altimetry group realized that the 1997 rise was an ENSO signal, and they extended the trend up to 2003, they seemed to have faced a problem: There was no sea level rise visible, and therefore a “reinterpretation” needed to be undertaken. (This was orally confirmed at the Global Warming meeting held by the Russian Academy of Science in Moscow in 2005, which I attended). Exactly what was done remains unclear, as the satellite altimetry groups do not specify the additional “corrections” they now infer. In 2003, the satellite altimetry record (Aviso 2003) suddenly took a new tilt—away from the quite horizontal record of 1992-2000, seen in Figures 5 and 6—of 2.3 (±0.1) mm/year (Figure 7).

    As reported above regarding such adjustments, an IPCC member told me that “We had to do so, otherwise it would not be any trend,” and this seems exactly to be the case. This means that we are facing a very grave, if not to say, unethical, “sea-level-gate.” Therefore, the actual “instrumental record” of satellite altimetry (Figure 10) gives a sea level rise around 0.0 mm/year. This fits the observational facts much better, and we seem to reach a coherent picture of no, or, at most, a minor (in the order of 0.5 mm/yr), sea level rise over the last 50 years.

  5. I know it’s a bit boring & deja vu. I still remember that marvelous BBC2 Horizon programme 35/40 years ago which was all about the Sun & Sunspots, as we then knew the science of the day. It may have been coincidence, but they drew examples of things like the rise of Beatlemania & the rise of skirt hemlines, with rises & falls of Sunspot numbers, & much else! As an engineer I am no supersticious chump, but I still have a quiet hunch that the big shiney ball thingymabob in the sky, that possesses 99.9% of the mass of the Solar System, has more of an influence upon this little planet than most people like to think. Human beings are fallible creatures & the brain can be influenced by many things if it’s not aware! Could it be that a rise in Solar activity over the past few years will match the rise in greenalism, followed by a decline in greenalism following the decline in Solar activity through cycles 24, 25, & 26 +? May be, may be not, who knows? Perhaps I’ll ask Big Al when he’s finished counting his $squillions!

    • This engineer tends to agree and notes that cyclical mechanisms tend to manifest on a spinning planet with an orbiting moon and lots of surface fluid all orbiting that dirty great star with a set of other planets and various other interplanetary detritus especially when we know there are sun spot cycles and solar polarity cycles and who knows what other cyclical phenomena in evidence.

    • Well! Next you’ll be saying that because water vapour is 95% of the greenhouse gases then it’s more important than CO2. Heretic!

  6. Willis,
    It’s inconceivable that there should be no correlation at all between sea level rise and the solar cycle. But, clearly, the effect will be tiny: 11 or 22 years is a very short period and the oceans are vast.
    You probably need to look at the global average rather than individual records. And, because the effect will be very small, you need a more precise measure: the rate of change, rather than the actual level.

    Holgate published a graph showing the rate of change for the 20th century. Steve McIntyre commented on the graph:
    “… The maxima and minima of the solar cycles seem to match the fluctuations in sea level rise rather uncannily. While the resemblance is impressionistic (I don’t have a digital version of Holgate’s series), offhand, I can’t think of any two climate series with better decadal matching. I think that this resemblance is pretty obvious….”
    http://climateaudit.org/2007/02/11/holgate-on-sea-level/

    Here the two records are plotted together by David Archibald:
    https://wattsupwiththat.com/2009/04/07/archibald-on-sea-level-rise-and-solar-cycles/

    I know you claimed to disprove this correlation. Your proof relied on a very low R2 value. But R2 is very limited because it assumes a linear relationship. A low R2 could simply mean that the correlation is complex and non-linear, which is almost certainly the case.

    I’ve run a few hundred random graphs and none showed a correlation remotely as good as this.

    So, here’s a suggestion: why not run a periodogram on Holgate’s rate of rise data? I would guess it would show a pretty strong peak around 11 years.
    Chris

    • “You probably need to look at the global average rather than individual records. And, because the effect will be very small, you need a more precise measure: the rate of change, rather than the actual level.”

      If you’re trying to tease out a small signal from hopelessly noisy data, that would be a good way to do it if you don’t mind fooling yourself. (1) Taking averages involves loss of information, and (2) derivatives are less precise, not more precise than raw numbers.

  7. The one year “period” and its sub harmonic at two years is a spurious signal known as an alias. It is (most likely) caused by the sampling of the signal at intervals close to a day or half a day.

    • “The one year “period” and its sub harmonic at two years”

      Ed, Willis calls out signals at one year, and half year periods. sub-harmonic at two? typo?
      And how would day or half day sampling cause an alias at 365 days?

  8. The simple Fourier transform is not ideal for something with a variable period, it may be better first to resample the data so that all cycles are exactly 11 “years” long (1 “year” = 1/11th of the period between successive cycles).

    This is the classic problem of detection of a weak signal in background noise. In sonar systems one chops up the data into a sequence of segments and looks for the signal in each segment, an operator would only make a visual detection on several segments with a consistent signal.

    There are umpteen high performance (and therefore very complicated) algorithms for this kind of thing, but one needs either very expert knowledge or blind faith to put any trust in them, so I’d stick to the sonar operator method, must see a persistent signal in a sliding sub-window of data.

    • climanrecon August 19, 2015 at 3:41 am

      The simple Fourier transform is not ideal for something with a variable period, it may be better first to resample the data so that all cycles are exactly 11 “years” long (1 “year” = 1/11th of the period between successive cycles).

      The Fourier transform finds the solar signal clearly and evidently. Why would it not find the effect of the solar signal?

      w.

  9. I have one suggestion as to why the 11-year signal is not visible. In Dr. Shaviv’s paper his equation (2) represents the solar term as cosine function with amplitude of “a”. Later down in the paper he reports that their model uses a value of 2.5mm for “a”. In other words, the total amount of sea level change attributable to solar (according to Dr. Shaviv’s paper) is only +-2.5mm.

    Now, I am a little confused as to the vertical axis in your plots as they are in percentages of the total range, not mm. If I interpreted the data in your spreadsheet correctly, this range is typically somwhere in the neighborhood of 500mm peak to peak. Dr. Shaviv’s model says there is a 5mm peak-to-peak solar signal in there. If I’ve got your vertical axis wrong then please correct me.

    I suspect that perhaps there is not enough accuracy in the tidal data (and/or too much measurement noise) to be able to see the signal, even if it is there. Can you check the vertical axis of some of your plots in mm to see if a 2.5mm signal would be above the noise level at 11 years?

    I’m not that knowledgable about tides versus mean sea level…but there also might additional “noise” in tidal data because these are measurements made only along coastlines whereas the satellite data is (I presume) not.

  10. Thank you Willis. After reading through your Kerfuffle with Dr Shaviv, I’d considered doing a Fourier Analysis on the sea level data, but since I haven’t done one for 30 years, I think it might have taken me six weeks to collect and learn a tool set. You’ve saved me that.

    A few comments — none of which should affect your conclusions at all:

    1. Sunspot creation seems to act like a relaxation oscillator. Relaxation oscillators often aren’t that great at timekeeping. So I find it a bit unnerving that your eleven year peak is so narrow. I suspect, but couldn’t prove, that that is an artifact of your analytic approach.

    2. As vukcevic points out, there probably should be a substantial second harmonic peak in the sunspots around 22 years. Not there. Not that I know much about sunspots.

    3. Your reasons for using tidal gauge are good ones, but you should be aware of the limitations of tidal gauges.

    a. Their coverage is lousy — only at land-sea boundaries and mostly in the Northern temperate zone.

    b. They are affected by seasonal wind, water temperature, air-pressure, and in some cases nearby river flows. That’s probably the one year signal you find.

    c. Most, maybe all. are subject to local tectonic forces that are probably comparable to or possibly larger than sea level rise. We possibly won’t have that sorted out for many decades. Mostly these forces are probably either constant or have timeframes of centuries or longer. Shouldn’t affect your analysis I think

    4. If I understand Dr Shaviv’s work (and mostly I don’t) he’s talking about the rate of change in sea level, not the sea level itself. I suppose it’s conceivable that there is a signal in the change (dh for lack of a less loaded term) that is somehow washed out of h which is what you are (I think) examining.

    Anyway, Another nice paper.

    P.S. If clarity of explanation is a valid criterion you beat Dr Shaviv by orders of magnitude. His exposition reminds me of a 1970s computer wizard who was noted for his complex verbiage. That guy once wrote an abominable 300 word paragraph that probably said, “Sometimes you have to use big words because small words won’t do”

    • I would have said:
      Sometimes you have to use big words because diminutive words won’t do.

      Apologies to the ancient website milk.com (if it still exists)
      Before I read milk.com my vocabulary was small, now it’s big.

  11. Willis,
    Your approach here is practically guaranteed not to find any evidence of solar cycles in the data if such cycles exist. Your approach only demonstrates that the amplitude of seasonal tidal variation is far larger than interannual variation – something I think we could have guessed without the benefit of any analysis.

    If you really wish to look at the evidence for or against a periodic interannual component in MSL with periodicity similar to solar cycle length, then you have to eliminate the obscuring effect of the seasonal variation; otherwise you are wasting your time. The easiest way to do this is to convert your monthly tide gauge data into annual differences for the same month e.g the February value is replaced by the change in February value from the previous year. This will deseasonalise the data and differentiate the data, while retaining the original periodicity of any oscillatory components. You can then carry out a Fourier analysis on the resulting series to find the dominant interannual periodicities.

    You should then find clear evidence for quasi 11-year cycles in the data.
    Paul

    • You should then find clear evidence for quasi 11-year cycles in the data.

      I would have thought the same thing but there is still (at best) a very weak solar signal in the short-term data. Shaviv, et al., reported:

      …at least 70% of the variance in the annually smoothed detrended altimetry data can be explained as the combined effect of both the solar forcing and the El Nino–Southern Oscillation (ENSO).

      But their attributions to ENSO and other non-solar cycle influences suggest an even smaller component directly attributable to solar forcing.

      We find that the peak to peak radiative forcing associated with the solar cycle is 1.33 ± 0.34 W/m2, contributing a 4.4 ± 0.8 mm variation. The slow eustatic component (describing, for example, the cryosphere and large bodies of surface water) has a somewhat smaller peak to peak amplitude of 2.4 ± 0.6 mm. Its phase implies that warming the oceans increases the ocean water loss rate. Additional much smaller terms include a steric feedback term and a fast eustatic term. The ENSO contributes a peak to
      peak variation of 5.5 ± 0.8 mm, predominantly through a direct effect on the MSL and significantly less so
      indirectly through variations in the radiative forcing.

      http://sealevel.colorado.edu/content/2015rel3-global-mean-sea-level-time-series-seasonal-signals-retained

      http://sealevel.colorado.edu/content/2015rel3-global-mean-sea-level-time-series-seasonal-signals-removed

    • Paul_K August 19, 2015 at 4:07 am

      Willis,
      Your approach here is practically guaranteed not to find any evidence of solar cycles in the data if such cycles exist. Your approach only demonstrates that the amplitude of seasonal tidal variation is far larger than interannual variation – something I think we could have guessed without the benefit of any analysis.

      If you really wish to look at the evidence for or against a periodic interannual component in MSL with periodicity similar to solar cycle length, then you have to eliminate the obscuring effect of the seasonal variation; otherwise you are wasting your time. The easiest way to do this is to convert your monthly tide gauge data into annual differences for the same month e.g the February value is replaced by the change in February value from the previous year. This will deseasonalise the data and differentiate the data, while retaining the original periodicity of any oscillatory components. You can then carry out a Fourier analysis on the resulting series to find the dominant interannual periodicities.

      You should then find clear evidence for quasi 11-year cycles in the data.
      Paul

      Thanks, Paul. I don’t believe for a minute that interannual variability obscures an 11 year signal. That makes no sense at all. In any case, I gave you the dang data in a most accessible spreadsheet form. Do the math, establish your case with actual calculations, come back when your idea has some observational support and we’ll talk.

      w.

      • You are correct Willis.

        However noise and accuracy issues in tide gauge data can obscure this signal quite easily. I said it above and repeat here again — I don’t think that tide gauge data is of sufficient quality to be able to see such a small signal (+-2.5mm).

        I’m not taking sides on whether this signal is really there or not, I’m just saying that tide gauge data will not reveal the signal (if it is there) due noise and quality issues.

        For example see here:

        Hanan, John. The Difficulties in Using Tide Gauges to Monitor Long-Term Sea Level Change
        International Federation of Surveyors, Article of the Month, July 2010.

        (I was able to view this paper on Research Gate web site)

        In essence what I think you have done is proven what is perhaps an unstated premise of Dr. Shaviv’s paper — that this signal was not visible prior to having satellite altimetry data. And again, I am not taking a position on whether the signal is either there or not.

      • wxobserver,

        The whole point of Fourier analysis is that things like noise often operate at different frequencies than the signal you are looking for. There almost certainly IS noise associated with Tide Gauge data (and any other kind of sea level data) But, that noise is almost certainly not running at a frequency of 11 years. So, even though the noise might obscure the signal in the observed data, it won’t obscure it in the Fourier transform. Again, that’s the whole point of doing a frequency analysis like this.

  12. Willis writes “So for me, until there is evidence of an actual ~11 year cycle in the sea level height, any speculation as to the possible solar nature of said unobserved cycle is wildly premature.”

    I’m pretty sure that Dr Shaviv was never looking at solar activity vs sea level height. He was looking at solar activity vs the rate of change of sea level height. Two entirely different things…

    • Tim, he regressed his “harmonic solar component” (a sine wave) directly against the sea level, not against the change in sea level. Look at his equation 1. Clearly he is looking at sea level height.

      w.

      • It doesn’t look like that to me. His equation is the differential of sea level as a function of time. Besides I think he explicitly mentioned it in his initial reply to you.

    • Re: change vs rate of change

      If the signal contains sin(x) as Shaviv claims, then the derivative of the signal will contain sin(x)+pi/2 (aka “cos(x)”). You’ll get the same sinusoid, just shifted to the right 90 degrees.

      • And you’ll see it if its the only signal that applies, but if there are other drivers of sea level then it’ll be lost. We know there are other drivers of sea level…

  13. “First we have to find something unusual, then we can speculate as to its causes and consequences.”

    Makes sense.

    So, what are the known consequences of that 11 year solar cycle?

  14. Willis: Do you have access to the the actual satellite data that Dr. Shaviv used in his analysis? Why should you expect that looking at tidal data, presumably on data on the continental shelf, would give the same results as measurements taken over the entire globe? Also, it would appear that you have not included tidal measurements from the southern hemisphere where there is much more ocean than land.
    BTW what is the accuracy of the satellite data when it come to measuring sea level?

    • Walt D. August 19, 2015 at 5:00 am

      Willis: Do you have access to the the actual satellite data that Dr. Shaviv used in his analysis?

      Thanks, Walt. I just spent the last couple of posts discussing the actual satellite data. It is too short for Fourier analysis of an 11-year cycle, as it is barely over two solar cycles long.

      Why should you expect that looking at tidal data, presumably on data on the continental shelf, would give the same results as measurements taken over the entire globe?

      Because the global signals can’t contain the signal unless at least some of the tidal gauges contain the signal.

      Also, it would appear that you have not included tidal measurements from the southern hemisphere where there is much more ocean than land.

      I’ve used all datasets in the PSMSL data with records longer than 60 years.

      BTW what is the accuracy of the satellite data when it come to measuring sea level?

      Over what period and what area?

      w.

    • According to NASA’s discussion of the JASON-2 mission,:

      …​high-precision ocean altimetry measures the distance between a satellite and the ocean surface to within a few centimeters.

      http://www.nasa.gov/mission_pages/ostm/overview/index.html#.VdS_aUukPwI

      And further:

      The Poseidon-3 radar altimeter, provided by Centre National d’Etudes Spatiales (CNES), is the mission’s main instrument. It accurately measures the distance between the satellite and the mean sea surface. Derived from the Poseidon-2 altimeter on Jason-1, it emits pulses at two frequencies (13.6 and 5.3 gigahertz) to the ocean surface and analyzes very precisely the time it takes for the signals to return.

      The Advanced Microwave Radiometer (AMR), provided by NASA, is an advanced version of the microwave radiometer that flew on Jason-1. It measures radiation from Earth’s surface at three frequencies (18, 21 and 37 gigahertz) to determine the amount of water vapor present in the atmosphere. This water vapor affects the accuracy of altimeter measurements by delaying the time it takes for the altimeter’s signals to make their round trip to the ocean surface and back.

      The Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS), provided by CNES, determines the satellite’s precise position in orbit to within a few centimeters, information that is critical in interpreting altimetry data. It works by receiving signals in two frequencies from a ground network of 60 beacons all over the globe. The relative motion of the satellite generates a shift in signal frequency, called the Doppler shift, which is measured to determine the satellite’s velocity and position.

      The Laser Retroreflector Array (LRA), provided by NASA, is an array of mirrors that allow the satellite to be tracked with centimeter accuracy by 40 satellite laser ranging stations on the ground. By analyzing the round-trip time of the laser beam, the satellite’s precise position in orbit can be determined. It is an exact copy of the LRA on Jason-1.

      http://www.nasa.gov/mission_pages/ostm/spacecraft/index.html

    • BTW what is the accuracy of the satellite data when it come to measuring sea level?

      According to NASA’s discussion of the JASON-2 mission, the best satellites can do is get within a few centimeters. Beyond that, it is adjusted by application of various corrections and assumptions:

      …​high-precision ocean altimetry measures the distance between a satellite and the ocean surface to within a few centimeters.

      http://www.nasa.gov/mission_pages/ostm/overview/index.html#.VdS_aUukPwI

      And further:

      The Poseidon-3 radar altimeter, provided by Centre National d’Etudes Spatiales (CNES), is the mission’s main instrument. It accurately measures the distance between the satellite and the mean sea surface. Derived from the Poseidon-2 altimeter on Jason-1, it emits pulses at two frequencies (13.6 and 5.3 gigahertz) to the ocean surface and analyzes very precisely the time it takes for the signals to return.

      The Advanced Microwave Radiometer (AMR), provided by NASA, is an advanced version of the microwave radiometer that flew on Jason-1. It measures radiation from Earth’s surface at three frequencies (18, 21 and 37 gigahertz) to determine the amount of water vapor present in the atmosphere. This water vapor affects the accuracy of altimeter measurements by delaying the time it takes for the altimeter’s signals to make their round trip to the ocean surface and back.

      The Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS), provided by CNES, determines the satellite’s precise position in orbit to within a few centimeters, information that is critical in interpreting altimetry data. It works by receiving signals in two frequencies from a ground network of 60 beacons all over the globe. The relative motion of the satellite generates a shift in signal frequency, called the Doppler shift, which is measured to determine the satellite’s velocity and position.

      The Laser Retroreflector Array (LRA), provided by NASA, is an array of mirrors that allow the satellite to be tracked with centimeter accuracy by 40 satellite laser ranging stations on the ground. By analyzing the round-trip time of the laser beam, the satellite’s precise position in orbit can be determined. It is an exact copy of the LRA on Jason-1.

      http://www.nasa.gov/mission_pages/ostm/spacecraft/index.html

  15. I thought Shaviv said you need to look at the first differential of the height data. It should show up in both if it were to exist but it might be worth the exercise.

    • Two things. First, if it exists in the first differential, it exists in the signal. Second, Shaviv regressed his sine wave against sea level height, not against the first differential. See his Equation 1 for confirmation.

      w.

      • Willis –

        I see that Dr. Nir Shaviv commented on your post “My Thanks, Apologies, and Reply to Dr. Nir Shaviv” on August 17, 2015 at 2:10 PM. Based on some of your comments here, it seems that maybe you missed his response.

        I’d be interested on your reaction and rebuttal of his argument.

        Thanks

        Dan

      • DanMet’al August 19, 2015 at 12:09 pm

        Willis –

        I see that Dr. Nir Shaviv commented on your post “My Thanks, Apologies, and Reply to Dr. Nir Shaviv” on August 17, 2015 at 2:10 PM. Based on some of your comments here, it seems that maybe you missed his response.

        I’d be interested on your reaction and rebuttal of his argument.

        Thanks Dan. I read it, and I thought about it, and I decided to let it go. I understand what he is saying about using the integral to do the harmonic analysis. And he’s right, using a sine wave does simplify the analysis, because the integral of sin is – cos, and the integral of cos is sin. But all you get are answers about sine waves. You can’t use the integral of the sunspot data the way you can the integral of the sine wave. The integral of the sunspot data is NOT a simply 90° lead/lag as it is with the sin/cos.

        And fitting a 12.6 year sine wave to a 23-year dataset doesn’t even pass the laugh test, especially as part of a six-parameter model.

        For these and other reasons, I decided that we’re just too far apart on this question for further discussion to be profitable. Instead I’ve been looking to see if his purported cycle is real using averaged periodograms. I can’t find any sign of it.

        Regards,

        w.

  16. The issue raised by Willis is very interesting but there is no chance to show a correlation between the sunspot number and the sea level measured near the coastlines. To my knowledge, the only place where the correlation is possible is where baroclinic waves resonate with solar cycles. Where the resonance occurs the cross-wavelet analysis of sea surface height reveals two antinodes in opposite phase, as occurs in the North Atlantic for the 8-year period Rossby wave. Off the Cape Hatteras, the Gulf Stream leaves the eastern North American coast around 35°N. At the westernmost antinode facing east, along the subtropical gyre, the sea level oscillates on few centimeters (http://climatorealist.neowordpress.fr/
    ).
    For periods between half a year and eight years, the forcing of these gyral waves is induced from the sequence of warm and cold waters conveyed by western boundary currents, and causes the oscillation of the thermocline of the gyre (the surface height anomaly is -0.0025 times the amplitude of variation of the thermocline depth). But these gigantic gyral waves also have the ability to tune with the long-period solar cycles of one to up to several centuries, as well as Milankovitch cycles that affect the occurrence of glacial and interglacial periods, throughout tens of thousands of years, while filtering out the effects of the best known, the 11-year solar cycle: the gyral waves resonate at 1, 4, 8, 64, 128,… year periods (11 yrs is too far from those natural periods, despite the large bandwidth of the 11-yr period cycle).
    So, two good reasons not to see correlation with the 11-year cycle, the location of measurements and the selected solar cycle.

    • Jean-Louis Pinault August 19, 2015 at 5:43 am

      The issue raised by Willis is very interesting but there is no chance to show a correlation between the sunspot number and the sea level measured near the coastlines. To my knowledge, the only place where the correlation is possible is where baroclinic waves resonate with solar cycles.

      Somehow, you know the only secret place on earth where a solar cycle would be visible in the ocean … and you know this how?

      w.

      • Willis,
        Solar cycles should be visible at the antinodes of quasi-stationnary baroclinic waves, i.e. along the subtropical gyres where the western boundary currents leave the coasts, inducing sea surface height (SSH) anomalies. Unfortunately, SSH series are not long enough to show such SSH oscillations. However, SST anomalies may be highlighted since SSH anomalies result from the thermocline oscillation: the deeper the thermocline, the higher the positive SST anomaly, and the shallower the thermocline, the lower the negative SST anomaly. The 128-yr SST anomaly forced from the Gleissberg cycle can be evidenced in the Northen Atlantic, from long SST series (http://climatorealist.neowordpress.fr/). The 11-yr period cycle is not perceptible but the 8-yr period cycle inherited from the tropical oceans is strong.

      • Willis Eschenbach August 19, 2015 at 9:31 am Edit

        Jean-Louis Pinault August 19, 2015 at 5:43 am

        The issue raised by Willis is very interesting but there is no chance to show a correlation between the sunspot number and the sea level measured near the coastlines. To my knowledge, the only place where the correlation is possible is where baroclinic waves resonate with solar cycles.

        Somehow, you know the only secret place on earth where a solar cycle would be visible in the ocean … and you know this how?

        w.

        Jean-Louis Pinault August 19, 2015 at 10:23 am

        Willis,
        Solar cycles should be visible at the antinodes of quasi-stationnary baroclinic waves, i.e. along the subtropical gyres where the western boundary currents leave the coasts, inducing sea surface height (SSH) anomalies. Unfortunately, SSH series are not long enough to show such SSH oscillations.

        Merci, Jean-Louis. So your claim is that you know the only secret place on earth where the solar cycle would be visible, but you don’t have the data to demonstrate that with actual observations …

        Pass.

        w.

    • “The lunar month should be an extremely powerful signal in your analysis, so where is it?”

      Interesting pointt, however, PSMSL data seems to be monthly (or annual) averages with daily/ monthly tidal fluctuations therefore averaged out. And in any case, Willis cut of his analysis on the low side at 4 months.

    • John A August 19, 2015 at 5:55 am

      Willis,

      the lunar month should be an extremely powerful signal in your analysis, so where is it?

      It’s monthly data … so a monthly signal is too short for much meaningful analysis. In addition it’s immaterial to this discussion, so I’ve started the analysis at four months.

      w.

      • Oh,it should not be confused gravitational waves and baroclinic waves. I think that Willis is looking for baroclinic waves (which store or restore heat) resulting from forcing from the variation in solar irradiance.

  17. Hi Willis,

    I just wanted to make sure of a few things regarding your analysis.

    1) For your analysis, does it matter that the data has underlying trends? I ask this as someone is not near well-enough versed in Fourier analyses. From what little I do know, I’m guessing it doesn’t effect anything, but I wanted to have this verified by someone who knows the nuts and bolts of this type of analysis.

    2) One of the points raised by Dr Shaviv, if I understand his criticism of you properly, was that the signal should be present in the rate of sea level change, not necessarily in sea level itself. Would it be possible to extend your analysis into a rate of change? I still don’t expect there to be an 11-year signal, but it’s one of those things that you don’t know until you try.

    3) You mentioned that you limited your analysis to data sets of sufficient length, which I agree is the proper way to do it. I was just wondering if there might be some spurious signals when the data is not subject to such a limitation, and that this might be why some people are misled into thinking a real signal exists.

    • Jimmy August 19, 2015 at 6:53 am

      Hi Willis,

      I just wanted to make sure of a few things regarding your analysis.

      1) For your analysis, does it matter that the data has underlying trends? I ask this as someone is not near well-enough versed in Fourier analyses. From what little I do know, I’m guessing it doesn’t effect anything, but I wanted to have this verified by someone who knows the nuts and bolts of this type of analysis.

      I’ve detrended all of the sea level data before Fourier analysis, as is the usual practice.

      2) One of the points raised by Dr Shaviv, if I understand his criticism of you properly, was that the signal should be present in the rate of sea level change, not necessarily in sea level itself. Would it be possible to extend your analysis into a rate of change? I still don’t expect there to be an 11-year signal, but it’s one of those things that you don’t know until you try.

      If it exists in the derivative it exists in the signal, because the signal is nothing but the cumulative sum of the derivative. Also, Dr. Shaviv did NOT regress his sine wave against the differential. He regressed it against sea level himself, meaning that he expects to see the signal in the sea level.

      3) You mentioned that you limited your analysis to data sets of sufficient length, which I agree is the proper way to do it. I was just wondering if there might be some spurious signals when the data is not subject to such a limitation, and that this might be why some people are misled into thinking a real signal exists.

      Spurious signals in sea level are a huge problem, and in fact you need more than three cycles to have confidence in your data.

      w.

      • Thanks for the reply, Willis. You said “If it exists in the derivative it exists in the signal, because the signal is nothing but the cumulative sum of the derivative.” I’m having a little bit of trouble wrapping my head around this, which I think is because I lack a sufficient enough understanding of the fourier analysis. Do you have any good links for educating myself about it?

  18. Swinoujscie is a site on the Baltic Sea coast, where Oder enters the sea. The Baltic Sea is quite isolated from the oceans. There is none or little sign of tides there. On the other hand, the capricious flow of Oder is likely to affect what happens there. So using Swinoujscie data in this context is not a good idea.

    Land mounted tide gauges are generally quite inaccurate and, of course, local, also loaded with systematic errors. The satellite data, on the other hand, is truly global, telling us something about the behavior of the global ocean on our planet, also offering better and uniform accuracy of instruments used.

    Solar cycles are driven by various mechanisms, internal and external ones. Interactions with Jupiter and Saturn show there. Observe that Jupiter’s year is about 11.86 earth years long. Saturn’s year is about 30 earth years long. Correspondingly, we see “11-year” (it’s not exactly 11, you see) and “60-year” oscillations in solar activity. The earth ocean may very well respond thermally to solar activity and dynamically to Jupiter’s and Saturn’s pulls. The question is how accurate we would have to be, to observe this.

    • Gus August 19, 2015 at 7:08 am

      Swinoujscie is a site on the Baltic Sea coast, where Oder enters the sea. The Baltic Sea is quite isolated from the oceans. There is none or little sign of tides there. On the other hand, the capricious flow of Oder is likely to affect what happens there. So using Swinoujscie data in this context is not a good idea.

      Thanks, Gus. No, what is not a good idea rejecting datasets because you think they don’t contain the signal. Before analysis you don’t know whether the solar signal is present in Swinoujscie, nor do I. Rejecting datasets based on your prejudices is not science.

      Land mounted tide gauges are generally quite inaccurate and, of course, local, also loaded with systematic errors.

      That’s not true at all. You just made that up. A tidal gauge with a stilling well is very accurate. And they are not “loaded with systematic errors”, you made that up too. They typically contain a spurious trend because of continental uplift/subsidence. But over the short time in question (centuries) these are linear in nature, and thus are removed when the data is detrended prior to analysis.

      Look, the data is sensitive and accurate enough to show us the tiny ~3.75 year cycle of unknown origin. Why would it not show us an 11-year cycle?

      The satellite data, on the other hand, is truly global, telling us something about the behavior of the global ocean on our planet, also offering better and uniform accuracy of instruments used.

      Yes, and if we had 60 years of it for Fourier analysis I’d use it in a heartbeat, with the usual caveats … but we only have about 23 years of satellite data, far too short.

      w.

      • “>> A tidal gauge with a stilling well is very accurate. And they are not “loaded with systematic errors”, you made that up too. They typically contain a spurious trend because of continental uplift/subsidence. <<"

        This ground movement is exactly what I'm referring to calling it "systematic error," because this is what it is. The other systematic error is the sinking (under its own weight) and thermal stretching of the gauge itself. I am not making any of it up. And, of course, there is also the locality problem. We know, from satellite observations, that the ocean does not behave uniformly, even when all ground movements are taken into account and subtracted from observations. We know, for example, that the ocean level rise rate is different in the southern hemisphere than in the north, or different in the Indian Ocean from what is observed in the Pacific. In the Pacific itself, there is a bulge in a part of the ocean that accounts for all ocean level rise, other parts of it subsiding.

        And I see in your reply that you know of these problems and value, as I do, satellite measurements. So, we are not in disagreement here.

        But you despair that we only have 23 years of satellite data, so you seek to use gauge data where satellite data is not available. I just don't trust old gauge data to any degree at all, when we're talking about global ocean level rise and other global ocean dynamics features, some expressed in terms of (1.7 +/- 0.6)mm/year. I don't see how you can make this kind of measurement, with this level of accuracy using gauges that you only have in a handful of points around the ocean's periphery and none at all in the middle of it. Satellite data, perhaps. Even here there are doubts about the error range and they are being discussed in the literature.

        My preference is to admit that we don't have trustworthy, global data for more than 23 years back, so we can't say anything "trustworthy and global" on the subject. I agree that to extract an 11-year signal from a 23-year sequence is "stretching" credibility. We need at least a century of satellite observations, not only regarding this particular issue, but everything else claimed to be "global."

        Sun spots, incidentally, are not a good measure of solar activity. There are better, more precise measures, such as 14C, 10Be and 18O production.

      • Sun spots, incidentally, are not a good measure of solar activity. There are better, more precise measures, such as 14C, 10Be and 18O production.
        Actually not. The deposition of these radionuclide proxies are influenced by, among other things, climate itself. See e.g. http://arxiv.org/ftp/arxiv/papers/1003/1003.4989.pdf and http://arxiv.org/ftp/arxiv/papers/1004/1004.2675.pdf
        “We have compared the yearly production rates of 10 18 Be by cosmic rays in the Earths polar atmosphere over the last 50-70 years with 10Be measurements from two separate ice cores in Greenland. These ice cores provide measurements of the annual 10Be concentration and 10Be flux levels during this time. The scatter in the ice core yearly data vs. the production data is larger than the average solar 11 year production variations that are being measured. The cross correlation coefficients between the yearly 10Be production and the ice core 10Be measurements for this time period are less than 0.4 in all comparisons between ice core data and 10Be production, including 10Be concentrations, 10Be fluxes and in comparing the two separate ice core measurements. In fact, the cross correlation between the two ice core measurements, which should be measuring the same source, is the lowest of all, only ~0.2. These values for the correlation coefficient are all indicative of a “poor” correlation. The regression line slopes for the best fit lines between the 10Be production and the 10Be measurements used in the cross correlation analysis are all in the range 0.4-0.6. This is a particular problem for historical projections of solar activity based on ice core measurements which assume a 1:1 correspondence.
        We have made other tests of the correspondence between the 10Be predictions and the ice core measurements which lead to the same conclusion, namely that other influences on the ice core measurements, as large as or larger than the production changes themselves, are occurring. These influences could be climatic or instrumentally based. We suggest new ice core measurements that might help in defining more clearly what these influences are and-if possible to correct for them”

  19. The data you’re using is composed of calendar monthly averages of some sort (the exact derivation of which we don’t know, calendar months are not equal). Your blunt instrument is picking out the interference pattern of 12 mashed up calendar monthly data points with something we know full well has a lunar dominant frequency.

    This illustrates well the “Fallacy of Fourier”. It can often be used to indicate a suspicion for further investigation but never, ever to prove a negative. Usually it doesn’t work at all when the dominant real time base is close but not equal to the sample rate. All you end up with are spurious interference harmonics.

    Sure enough, you’ve picked up the annual seasonal cycle, an expected subharmonic and bugger all else. Isn’t numerology wonderful stuff, hours of fun and frolics :-)

    • AJB August 19, 2015 at 7:24 am

      The data you’re using is composed of calendar monthly averages of some sort (the exact derivation of which we don’t know, calendar months are not equal). Your blunt instrument is picking out the interference pattern of 12 mashed up calendar monthly data points with something we know full well has a lunar dominant frequency.

      And yet the Fourier analysis has no problem picking out the sunspot signal, which also has the exact same “12 mashed up calendar monthly data points” … if as you claim the months are a problem with the sea level data, why are they no problem with the solar data?

      This illustrates well the “Fallacy of Fourier”. It can often be used to indicate a suspicion for further investigation but never, ever to prove a negative. Usually it doesn’t work at all when the dominant real time base is close but not equal to the sample rate. All you end up with are spurious interference harmonics.

      The “Fallacy of Fourier”? Is that a thing? Google finds exactly two entries for that, so I fear you’re just dressing up your own prejudices by wrapping them in quotes and pretending that they are widely shared.

      As to whether Fourier analysis can “prove a negative”, nothing can prove a negative. Which is why my conclusion was:

      If there is any ~ 11-year signal in the sea level height, it is so small as to be lost in the noise.

      Note that I was very careful to not say that the signal doesn’t exist, because we can’t prove that.

      w.

  20. Unless I am doing something wrong the SH SST shows a decent blip at around 11 years. I wouldn’t expect a large spectral anomaly associated with the 11 year solar cycle in of Earths climate metrics because TSI only deviates by 1 Watt over the 11 year cycle, but nonetheless it is there, whereas the 1 year cycle is associated with Earths axial tilt and the eccentricity of Earths orbit which causes a change in TSI of almost 100 watts over the course of a year.

    http://www.woodfortrees.org/plot/hadsst3sh/from:1900/fourier/magnitude/normalise/to:100/plot/sidc-ssn/from:1900/fourier/magnitude/normalise/to:100

  21. It’s been may years since I needed to do much Fourier analysis, although my lens design software can use FFT for computing MTFs and the like, or it can do full Fraunhoffer integration as well.

    So just what is the result of doing Fourier transforms on finite length data series.

    Not that I’m suggesting that artifacts introduced due to finite time data series are hiding Willis’s nemesis.

    He seems to be doing a good job of not finding an 11 year itch.

    But I was wondering if ANY of his mystery peaks might be simply mathematical artifacts of the transform of a finite length data series.

    I know that when I do MTFs either by direct integration or FFT, I get all kinds of rubbish pops up out of nowhere if I don’t put in a lot of data.

    g

    • George,

      I use the FFT for a great many things in Seismic Data processing and analysis. Each seismic trace has an average of 2000 samples sampled at 4 milliseconds which has a nyquist of 125 Hz.. The general rule of thumb is that anything stronger than 20 DB down is resolvable with an FFT in the seismic world. For instance the analog to digital converters in seismic acquisition as well as the geophones themselves often pick up 60 hz. power line interference that shows up on an FFT power spectrum of each trace even though you cannot see any visual evidence of the 60 cycle sine wave when visually inspecting a plot of each seismic trace. In other words it is a very robust algorithm that is used for deconvolution, filtering, spectral balancing and signal to noise improvement, in my experience. The use of a hanning or other type of taper applied to the leading and trailing samples of a finite signal can dramatically cut down on the aliasing and edge effects.

      • It would seeem to me that the best place to look would be to isolate the Steric component and look for the signal there… remove amounts added by melting ice, remove ENSO effects ..(maybe your 3 and 7 year bumps) and you look at Steric component

        That really amounts to looking at the increase due to warming…

        The crazy thing in my mind is to look at sea level at all since the 11year effect will be buffered.

        If the 11 year cycle doesnt show up in Tmax… well everything after that is just a wild goose chase

      • Steven Mosher August 19, 2015 at 11:05 am

        It would seeem to me that the best place to look would be to isolate the Steric component and look for the signal there… remove amounts added by melting ice, remove ENSO effects ..(maybe your 3 and 7 year bumps) and you look at Steric component

        That really amounts to looking at the increase due to warming…

        The crazy thing in my mind is to look at sea level at all since the 11year effect will be buffered.

        If the 11 year cycle doesnt show up in Tmax… well everything after that is just a wild goose chase

        Thanks, Mosh. I agree that looking in the ocean is the wrong place, for no other reason than the amount of noise and thermal buffering.

        w.

  22. The difference seems obvious to me. Willis, you’re using tidal gauge data, while Dr. Shaviv is using the flawed satellite altimetry data which has been adjusted to “prove” the scary accelerated 3 to 3-1/2 mm/yr rate of rise, so sea-level rise rate can be pointed at as one more calamitous result of AGW. There are two problems I see with Dr. Shaviv’s use of the satellite data – 1) the possibly intentionally introduced warming bias not supported by tidal gauge data, and 2) the short duration of the satellite record being insufficient to show clear trends or cycles.

    It is not inconceivable that the 11-ish year cyclical signal Dr. Shaviv noticed in the satellite data was inadvertently introduced by the algorithms used to produce the more-rapid-than-reality rate of rise. I have no evidence of that, of course, but Occam’s Razor… if the data are flawed to begin with (rate of rise 1-1/2 – 2 mm/yr faster than reality) can perceived cycles in that data be trusted?

    • Or maybe the satellites have noise problems that correlate with sunspots? They are sitting outside the atmosphere with all that radiation coming down on them, it wouldn’t surprise me.

  23. I want you all to imagine the following.

    Imagine that C02 cycled like sunspots do.
    Imagine someone argued that this cycle must show up in the sea level data. It just MUST!
    Imagine you just read Willis’s Post, showing no such thing.

    1, How many of you would scream “falsified”
    2. How many of you would say ” no wait, look here, willis, no wait do this first, twist this thing for me willis’
    in other words how many of you would go excuse hunting

    does that excuse hunting remind you of excuse hunting you see to explain the pause.

    You want to find a solar signal. Sea level is the last place you would look, Tmax would probably be the first place to look

    • Steven Mosher August 19, 2015 at 8:32 am

      You want to find a solar signal. Sea level is the last place you would look, Tmax would probably be the first place to look

      We’re nothing if not a full service website. Here, to the same scale as Figure 4 above, is the periodogram of the Berkeley Earth Maximum Temperature …

      w.

      • Thank You willis.

        My sense of things is that if the 11 year cycle ( a small increase in wattage ) would show up ANYWHERE
        it would show up FIRST in TMAX as TMAX is directly related to incoming energy.
        Having Not found it there, the temptation is to go on a snipe hunt. Of course we cant stop snipe hunts…

  24. Willis I am with you on the 11 year sunspot no real climate correlation connection as I show clearly in what I have to say below ,but that is by no means to suggest there is not a solar /climate connection.

    My argument with you is not over the 11 year so called sunspot cycle climate connection but extreme prolonged periods of solar minimum activity versus the climate.

    Willis here is my argument as to why you fail to connect the solar/climate dots in any convincing way although you do leave the door opened.

    A quote from Willis, which is excellent.


    Any natural regulatory system has bounds on the variations it can control, and there are events that could alter or destroy the regulation.

    Second quote from Willis which is excellent.


    “Willis- The sun has no effect whatsoever on climate you are correct I apologize also to L svaalgard

    Willis says below that
    Eliza, I have never said that, nor anything even remotely resembling that. Those are YOUR WORDS, not mine.

    I have to apologize to Willis for not listening to him carefully enough because if one really listens to what he is saying he is opened to solar, while also saying there are events that can destroy or alter the natural regulatory system of the climate.

    So I have a starting point with Willis , which at one time I thought I did not have.

    Another point we agree on is if the sun varies enough it will have an impact on the climate. Everyone submits to this ,the disagreement however, is not if solar variation will change the climate but does the sun vary enough to accomplish this?

    This leads to my argument with Willis , which is the so called 11 year sunspot normal cycle is not where one is going to be able to find solar/climate connections, because the EXTREMES in solar activity are not strong enough in degree of magnitude or long enough in duration of time to have a climate effect. In addition the 11 year cycle going from weak to strong sunspot activity cancels the climate effect it may have before any significant impact could come about.

    In other words thresholds can not be reached in the climate system due to these 11 year variations in solar activity. This is the wrong place to look if one wants to find a solar climate connection.

    The place to look is when the sun enters an extreme period of prolonged minimum solar quiet and when one looks at these periods the data does show a climate/solar correlation to one degree or another.
    The problem is there are other factors superimposed upon even this extreme solar variability which although keeps the lower global average temperature trend in place there are periods of rising temperatures within the overall lower temperature trend.

    Why ? Because within any global temperature trend initiated by solar variability one has to take into account the following factors;

    1. all solar minimum differ as was the case recently with the 1996 solar minimum versus the 2008-2010 solar lull, which effects the climate in a different manner..

    2. the stage of where earth is in respect to Milankovitch Cycles is either going to work in concert or against the current trend the solar variability is exerting upon the climate. Right now I would say Milankovitch Cycles are on balance acting in concert with minimum prolonged solar activity.

    3. the geo magnetic field can enhance given solar activity effects or diminish given solar activity effects upon the climate. A weaker field compounding given solar effects.

    4. land /ocean arrangements and elevations. Right now acting in concert with reduced solar activity very favorable for cooling.

    5. the ice dynamic/snow cover which when at a critical stage can enhance or diminish the solar impacts. Right now not that favorable.

    6. the rogue terrestrial event such as a super volcanic eruption or the rogue extra terrestrial event such as an impact could turn things upside down in the climate system.

    7. this being very important which is the elusive thresholds which I think are out there but I do not know what degree of solar extremes are needed to bring them about, but there must be solar extremes that will bring them about. This is also probably tied into the initial state of the climate , for example point 5, which is to say just how far is the climate system of the earth from that inter –glacial/glacial threshold at the time the prolonged minimum solar conditions commence, which I think go a long way in the climatic effect the given solar variability will have upon the climate. .

    8. the normal earth intrinsic climate factors which superimpose themselves upon the big general climatic trend regardless if they are associated directly with given solar activity or not.

    9. Lunar input- which could possibly enhance or diminish given solar activity.

    My best guess based on the historical climatic record is the solar extremes needed to have a clear climatic impact and not one that is obscured have to be slightly less then quote so called normal 11 year sunspot minimums but more importantly the duration of time has to be longer.

    Once this is in when combined with the points in the above the climate result should come about, with the exception if point 6 were to take place.

    Possible important (some) secondary effects due to solar activity which in turn can moderate the climate.

    cosmic ray change moderates cloud coverage.

    ozone changes moderates atmospheric circulation

    geological activity moderation.

  25. As far as the thermo regulator you have suggested again that works to keep the tropics regulated within a range as dictated by the overall climatic regime the earth is in.

    Your regulator however can not does not stop the climate from going from one regime to another as the historical climatic record shows and in no way does it give a semi cyclicality to the climate.

    What gives a cyclicality to the climate is most likely extra- terrestrial beats ranging from Milankovitch Cycles to Solar Variability to the Geo Magnetic Field Strength to Land/Ocean Arrangements .

    Your thermo regulator at best keep the earth range bound but the range is to large to stop the earth from going from a glacial state to an inter- glacial state which for practical terms makes the climate of the earth unstable.

  26. Averaging the solar cycle doesn’t even fit solar cycle data.

    Actual solar peak years:

    2000, 1989, 1979, 1968, 1958, 1947, 1937, 1928, 1917, 1906, 1894, 1883

    11 year cycle

    2000, 1989, 1978, 1967, 1956, 1945, 1934, 1923, 1912, 1901, 1890, 1879

    Why wouldn’t you just compare actual sunspots for a given year to sea level rise for a given year to see if there was a coloration?

  27. Willis is approaching this in a way which is meaningless which is the 11 year sunspot cycle is not the climate game changer . This is not the argument , the argument is does the sun vary enough when it reaches prolonged minimum conditions when combined with other factors result in the climate of the earth going from one regime to another regime.

  28. Willis is concentrating on the small detailed picture rather then looking at the big far reaching picture.

    Frankly his commentary about the value of Nir Shaviv work is meaningless ,and it does not really matter if you agree with Dr. Shaviv , or not.

    This is at best a distraction to the real issue which is does a prolonged minimum solar event when taken in totality with other items that influence the climate of the earth as I have pointed in my earlier post result in a significant climate change or not?

    This is the central issue.

    • Salvatore, since the topic of the article is Willis’ analysis of Dr. Shaviv’s study finding a correlation between sea level and the 11-ish year solar cycle, it’s your commentary that’s distracting, in my opinion.

      Not everything on WUWT has to be about significant climate change, or about the big picture. There are plenty of articles posted on those topics, but this one is not, and from what I understand, Anthony’s site here is not all about that big picture of what has significant impact on climate change – it’s about whatever interests Anthony.

  29. Salvatore, wouldn’t that properly be, “Dr. Shaviv is approaching this in a way which is meaningless …” if the 11 year cycle is irrelevant? It looks to me as though Willis is looking for a signal in the tidal gauge data to see if he can find what Dr. Shaviv claims is present in sea level data – a roughly 11 year cycle which correlates with the solar cycles. He’s not (from my reading) trying to prove that the 11 year cycle is a climate game changer.

  30. It’s time for the more learned to explain to this layman why there is such a fixation on the 11 year solar signal. I fully understand that the AVERAGE solar cycle length is 11 years however that is simply the AVERAGE length. The actual lengths vary from 9.0 to 13.7 years. So the question I have is how can one expect to find an 11 year signal in a cycle length of 9, 9.7 or 9.8 years? If you look at the period from Dec 1913 to Oct 1964, cycles 15 – 19, the cycle lengths were 10.0, 10.1, 10.4, 10.2, 10.5 years. Again I ask how can an 11 year signal be expected to found in this period? Just want to know.

    • Again I ask how can an 11 year signal be expected to found in this period?
      Because such a [strong] signal is actually found. Here is another cut at it. Showing the FFT of the area of the solar disk covered by sunspots:

      As you can see there is a strong 11-year peak [and no 22-year peak].

      • Thank you. So if the sunspots show such a strong signal at 11 years, why do the cycles vary so much in length?

      • As you can see there is a strong 11-year peak [and no 22-year peak.””

        Wow, there you go freaking me out again. Why is that??

        But not why I am here today.

        Thank you for sharing your knowledge and information with us Dr. S.
        Just want to share back at you some good info from the Interstellar Magnetic Fields researchers….

        ON THE ROTATION OF THE MAGNETIC FIELD ACROSS THE HELIOPAUSE
        M. Opher and J. F. Drake 2013 ApJ 778 L26

        …The solar magnetic field strongly affects the drapping of the interstellar magnetic field (B ISM) around the HP. B ISM twists as it approaches the HP and acquires a strong T component (East-West). The strong increase in the T component occurs where the interstellar flow stagnates in front of the HP. At this same location the N component BN is significantly reduced. Above and below, the neighboring B ISM lines also twist into the T direction. This behavior occurs for a wide range of orientations of B ISM.
        The angle δ = asin (BN /B) is small (around 10°-20°), as seen in the observations. Only after some significant distance outside the HP is the direction of the interstellar field distinguishably different from that of the Parker spiral….
        http://iopscience.iop.org/2041-8205/778/2/L26?rel=sem&relno=2

        Interstellar magnetic fields: from Galactic scales to the edge of the heliosphere
        Katia Ferri`ere
        IRAP, Universit´e de Toulouse,
        13th Annual International Astrophysics Conference: Voyager, IBEX, and the Interstellar Medium Journal of Physics: Conference Series 577 (2015)

        pg. 9…The conclusions here are similar to those reached in Section 3.1, namely, the ISMF orientation in the close vicinity of the Sun departs significantly from that observed in the large-scale ISM beyond 500 pc of the Sun. The former must be associated with discrete features within the Local Bubble – possibly with the G-cloud that lies just outside the Local Cloud in the general
        direction of the Galactic center [44]. [44] interpreted their derived ISMF orientation, together with the direction of the interstellar flow past the heliosphere, as evidence that the local ISM is an expanding fragment of the S1 shell of the Loop I superbubble….

        pg. 10… The only in-situ measurements of ISMFs were made by Voyager 1, which is now believed to have crossed the heliopause into the very local ISM [49]. Ever since August 25, 2012, when the spacecraft was at 122 AU of the Sun, it has been measuring ISMFs [50]. For the first month after August 25, 2012, the average magnetic field strength was B = (4.4 ± 0.1) μG and the average
        magnetic field direction had azimuthal angle B = 287±1 and
        elevation angle B = 14±2 in RTN coordinates [51]. This field direction is close to the Parker spiral direction, P = 270 and P = 0. Since then, the field strength has been smoothly varying in the range (3.8 − 5.9) μG,
        and the field direction has been increasingly deviating from the Parker spiral [50]. TheVoyager 1 measurements are consistent with the very local ISMF draping around the heliosphere and being twisted toward the Parker spiral [52].

        Very cool figure on pg.6
        Figure 4. All-sky map in Galactic coordinates (with the Galactic center in the middle) of the rotation measures of ‘ 42 000 extragalactic radio point sources from the NVSS ( > −40) and S-PASS ( < 0) surveys.
        Positive (negative) rotation measures, which correspond to a magnetic field pointing on average toward (away from) the observer, are plotted in blue (red).
        http://iopscience.iop.org/1742-6596/577/1/012008/pdf/1742-6596_577_1_012008.pdf

        March 3, 2015
        NASA-Funded Study Finds Two Solar Wind Jets in the Heliosphere

        ..“If there were no interstellar flow, then the magnetic fields around the sun would shape the solar wind into two jets pointing straight north and south,” said Drake.

        “The magnetic fields contract around these jets, shooting the solar wind out like squishing a tube of toothpaste.”

        In the presence of the interstellar flow, these jets are bowed backwards, creating a crescent shape, as seen from the side of the sun. The jets erode in the presence of the strong interstellar flow, leading to two attenuated, short tails. This leads to a much shorter heliosphere of only about 250 times the distance between Earth and the sun, or about 23 billion miles..
        https://www.nasa.gov/content/goddard/two-solar-wind-jets-found-in-the-heliosphere

      • Dr. S., with respect to solar hemispheric preference to sunspots production , how long will one hemisphere dominate, before switching to the other hemisphere dominating? What about polarity in this hemispheric dominance?

        What is the polarity of the ISMF that is denting the nose of the heliosphere creating that big dent and ribbon of Energetic ‘neutral’ Atoms (ENA)?

        How does the IBEX seen ribbon of charged particles, change and evolve over solar cycle? position/extent

        Is it the same polarity ISMF that is squeezing the solar polar fields and bending them backwards? (sounds like magnetic reconnection)

      • Does the pos/neg polarity changes in ISMF occur around approx. 100 year periods? Are there active boundaries?
        done

  31. Willis
    Re: “If there is any ~ 11-year signal in the sea level height, it is so small as to be lost in the noise.”

    See Scafetta 2013 Fig. 3. Periodogram of New York City.
    While Scafetta “highlights a dominant quasi 60 year oscillation”, this periodogram also shows substantial evidence for an 11-12 year oscillation. Note Scafetta’s use of the “Maximum Overlap Discrete Wavelet Transform (MODWT)”
    Scafetta, N. Common errors in analyzing sea level accelerations, solar trends and temperature records. Pattern Recognition in Physics 1, 37-58, doi:
    10.5194/prp-1-37-2013, 2013

    I demonstrate that: (1) multidecadal natural oscillations (e.g. the quasi 60 yr Multidecadal Atlantic Oscillation (AMO), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO)) need to be taken into account for properly quantifying anomalous background accelerations in tide gauge records such as in New York City;

    Note further discussion by Benestand and then Scafetta:
    Benestad, R.E.: Comment on “Discussions on common errors in analyzing sea level accelerations, solar trends and global warming” by Scafetta (2013), Pattern Recogn. Phys., 1, 91–92, doi:10.5194/prp-1-91-2013, 2013. http://dx.doi.org/10.5194/prp-1-91-2013

    Reply to Benestad’s comment on “Discussions on common errors in analyzing sea level accelerations, solar trends and global warming” by Scafetta (2013)
    ———————
    PS Note the dominant ~ 60 year sea level oscillation
    Scafetta, N. Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes. Climate Dynamics July 2014, Volume 43, Issue 1-2, pp 175-192
    , – See more at: http://notrickszone.com/2013/04/23/duke-scientist-on-sea-level-rise-patterns-in-tide-gauge-records-mostly-driven-by-natural-oscillations/#sthash.Mj2EXJmo.dpuf

    Mazzarella A. and N. Scafetta, 2012. Evidences for a ~60-year North Atlantic Oscillation since 1700 and its meaning for global climate change Theoretical Applied Climatology 107, 599-609. DOI: 10.1007/s00704-011-0499-4

    Parker, A. Reply to “Comment on “Sea-level trend analysis for coastal management” by A. Parker, M. Saad Saleem, M. Lawson” Ocean & Coastal Management 87 (2014) 116e118

    • David L. Hagen August 19, 2015 at 9:35 am Edit

      Willis
      Re:

      “If there is any ~ 11-year signal in the sea level height, it is so small as to be lost in the noise.”

      See Scafetta 2013 Fig. 3. Periodogram of New York City.

      Dear heavens, anyone but Scafetta. He is a cyclomaniac who loves to use multi-parameter fitted models. In the paper you link to he says of his results:

      … the solar activity increase during the 20th century contributed at least about 50 % of the 0.8 ◦ C global warming observed during the 20th century instead of only 7–10 % (e.g.: IPCC, 2007; Benestad and Schmidt, 2009; Lean and Rind, 2009; Rohde et al., 2013). … [This] result was obtained by using solar, volcano, greenhouse gases and aerosol constructors to fit modern paleoclimatic temperature reconstructions (e.g.: Moberg et al., 2005; Mann et al., 2008; Christiansen and Ljungqvist, 2012) since the Medieval Warm Period, which show a large millennial cycle that is well correlated to the millennial solar cycle (e.g.: Kirkby, 2007; Scafetta and West, 2007; Scafetta, 2012c).

      Seriously? He says he is fitting “solar, volcano, greenhouse gases and aerosol constructors” to things like the 2008 paleo temperature reconstruction by Michael Mann he can show that solar is The Winnah!, and you believe his conclusions? See my post “Kill It With Fire” for a discussion of just how bad Mann2008 is.

      And what is a “constructor” when it’s at home? Scafetta seems to use the term to mean “independent variable”, but that’s not clear.

      And the model? Well, Scafetta’s as bad as Shaviv’s. This time around, Scafetta uses things like a five-parameter linear model where the variables are the ENSO signal, the solar signal, the volcano signal, a trend, and an offset. It is a bog-simple straight linear model. Will it fit the data? Given five tunable parameters, and a variable (ENSO) which is a part of what you are trying to predict, it would be shocking if Scafetta couldn’t fit the temperature data … so?

      Not only that, but in the past Scafetta has used the magical power of tunable parameters to fit things like the cycles of Jupiter and such to the temperature … and those astronomical based models fit the temperature just as well as the new whiz-bang volcano-solar-ENSO models. If one model is right the other must be wrong, but Scafetta has argued passionately for both …

      People don’t seem to get it. FITTING THE TEMPERATURE RECORD WITH A MULTI-PARAMETER LINEAR MODEL IS TRIVIAL! Give me ten parameters like some of Scafetta’s models, and three datasets of most any type, and I’ll make the climate elephant wave his trunk … but so what? Scafetta has fit half a dozen models so far to the temperature record, using wildly disparate variables, and all of them fit the temperature record with reasonably good fidelity … so? All that proves is that if Scafetta has N different models purporting to explain temperatures using different variables, a minimum of N-1 of the models must be wrong …

      Seriiously, SO WHAT! Fitting multi-parameter models to the historical climate record is meaningless child’s play.

      Pass.

      w.

      • Willis
        You can do better than that -(ad hominem genetic and red herring).
        I explicitly pointed to: Scafetta 2013 Fig. 3. Periodogram of New York City. See also Fig. 2b which looks to similarly show about 27 cycles at about 11 years over 300 years. Those are two explicit frequency analysis methods that both appear to show ~ 11 year oscillation in sea level (which should stand on their own on an analysis basis separate from the rest of the argument.)
        The question is why you found no ~ 11 year signal with your method while Scafetta did with his method.
        David

        PS Scafetta’s “empirical model” still appears to be predicting temperatures better than the IPCC’s from 2011.

      • It still amuses me that people think that reproducing the Global temperature index is some great feat.

        At a minimum a model of temperature should be tested by.

        1. Its ability to get SAT correct globally
        2. its ability to get SST correct globally
        3. Its ability to get each hemisphere correct (SAT and SST)
        4. Its ability to get TTL correct.

        not just the global temmperature index.

      • David L. Hagen August 19, 2015 at 5:21 pm

        You can do better than that -(ad hominem genetic and red herring).

        It appears you weren’t around for the previous go-rounds with Scafetta. He’s a piece of work. See:

        Loehle and Scafetta calculate 0.66°C/century for AGW
        Guest post by Craig Loehle and Nicolas Scafetta
        Human Effect on Climate Clearly Detected
        (but is 0.66 deg C/100yr since ~1950!)
        Loehle, C. and N. Scafetta. 2011. Climate Change Attribution Using Empirical Decomposition of Historical Time Series. Open Atmospheric Science Journal 5:74-86.

        Riding a Pseudocycle 2011-07-30
        Loehle and Scafetta recently posted a piece on decomposing the HadCRUT3 temperature record into a couple of component cycles plus a trend. I disagreed with their analysis on a variety of grounds. In the process, I was reminded of work I had done a few years ago using what is…

        Congenital Cyclomania Redux 2013-07-23
        Well, I wasn’t going to mention this paper, but it seems to be getting some play in the blogosphere. Our friend Nicola Scafetta is back again, this time with a paper called “Solar and planetary oscillation control on climate change: hind-cast, forecast and a comparison with the CMIP5 GCMs”. He’s…

        You go on to say:

        The question is why you found no ~ 11 year signal with your method while Scafetta did with his method.

        Who knows? Scafetta is well known for refusing to show his source code despite repeated requests. As a result, nobody but Scafetta knows most of that kind of stuff.

        In any case, if you look closely there’s a much larger problem. The length of the New York tide dataset is 119 years. As I’ve said, to have any faith in a cyclical analysis you need a minimum of three cycles, and I much prefer four. That means four cycles of about thirty years, or maybe three cycles of 40 years if I was really desperate … but that’s all the further I’d trust it, and I’d doubt the 40 year cycles.

        He shows cycles out to 100 freakin’ years, in a 119 year dataset … and there are not eve two cycles for his claimed 60 year cycle. Those are both jokes.

        It gets worse. He claims the cycles are 150 to 300 mm in height … but the standard deviation of the detrended NYC monthly tide dataset is only about 80 mm, and the annual swings are maybe 150-250 mm. There’s no 300-mm 60-year cycle in the data, that’s easy to disprove, just take a look at the data.

        You can follow Scafetta all you want. Me, I’ll pass until you can show me his claimed 60-year 300-mm cycle in the NYC tide data. You’re welcome to start down that rabbit-hole and listen to the mad hatter, up to you … it’s not for me.

        w.

  32. That you are fixated on your untenable view is no argument in favor of that view. Lots of people claim stuff that is false, you included.

    Leif says in the above.

    My response.

    Again this is your opinion which does not make it correct or in the majority.

    I am glad you voice your opinions but that is all they are opinions.

    • Voicing opinions is very different from discussing science, and it is good that you acknowledge that. And we have now heard enough of your opinion. Come back when you have changed it.

  33. Climate data cannot show how the sun varies a lot during prolonged periods of no variation

    Leif says which is totally false when one looks at the recent solar lull 2008-2010 versus the solar activity of the last half of the last century. I see plenty of variability.

    • What you see is that during that ‘lull’ as you call it, global temperatures have been high compared to the average over ‘the last half of the last century’. That we can agree on.

      • Again you not understand the climate system when you make those kind of statements.

        Again you do not listen to what I have said about how it works, you have paid no attention for if you have you would have known I expected no climate reaction from that solar lull.

      • Yet you drag out the lull to show just the opposite. And you are correct that I don’t listen to your explanation about ‘how it works’, because your utterances make no sense.

  34. The purpose of the lull being dragged out as you say is to show the sun has variability not to show a climate connection because the necessary criteria I called for was not all met during that lull.

    • At every sunspot minimum, sunspots almost go away and solar activity relaxes to the same state. A good indicator of solar activity is the F10.7 microwave flux. There is that flux back to 1840:

      As you can see, at every minimum the flux [and thus solar activity] is the same. No variability during lulls.

  35. Am probably stating the obvious here – but observations of sunspots are directly ‘on’ the sun – and can clearly be counted, noted, etc, and seemingly display an 11 year cycle. Great! We can further suggest that said cycle may imply cyclic changes in activity and the energy giving (out) properties the sun has, yes? Now – the sun chucks out these mega-amounts of energy in roughly all directions, yes? (lets ignore the odd solar flares for the moment!) How much of the given outflow of energy actually reaches the earth? Answer – not much. So then, Gaia decides to tinker with the tiny bit of sun’s overall actually arriving energy further, via cloud cover, stored ocean heat, etc, etc, etc This introduces lags, enhancements, reductions, etc, etc. So, how does anyone realistically expect to find a signal comparable to the observed ‘on the sun’ sunspots?, Even if we said the earth receives 0.1% of the suns energy then clearly, the range of variation we might see would only be 1000th of the observed ‘on-sun’ solar sunspots (assuming a direct spot/energy/activity correlation actually exists). Whichever way you look at it – earthbound detections of variations in solar energy are likely to be very small compared to the directly observed (sunspot) data and masked by the ‘other’ noise of the whole earth climate system. i.e. the observed sunspot data is unlikely to be directly comparable in scale and size to any ‘recorded on earth’ data given the likely noise in the system and small ‘sampling’ (of the actual emitted energy) involved. Needle and haystack may be a more sensible way of looking at it?

    • So, how does anyone realistically expect to find a signal comparable to the observed ‘on the sun’ sunspots?
      But that is precisely what the ‘sun nuts’ are claiming to find. We hear things like “solar activity accounts for 70% of observed climate variation”. So you would wholeheartedly agree that such utterings are nonsense.

      • Not really Leif. It is entirely logical to consider that any variations in incoming energy from the sun will affect climate. Even a tiny percentage point variation will affect the climate over a long enough timescale. The trouble is we do not have enough measurements of such variation – and solar spot counting just doesn’t cut it! Those constantly trying to link to 11 year cycles are the ones making the error in my opinion, as they are comparing melons to amoebas (scalewise!).. I do believe that it is realistic to explain past climate variation via long term solar variation (such as the YD and MM) because these can be seen over multi-decades and even century timescales. It is more likely that solar activity changed during these periods, given that there are not other earth based phenomena likely to have such an impact – even big volcanoes only last a year or two. Hence, (unless there have been some mega-catastrophes not recorded?) we must logically conclude that something external caused these clearly evident (and recorded) climate variations. Ignoring astronomical and any weirdo alien type stuff leads us to solar variation as the most likely culprit… which then leads us to ‘suspect’ that such variation is still ongoing and possible, yes? Yes, the 70% claim may be unrealistic, but on a cumulative effect basis, can this be completely dismissed?

      • but on a cumulative effect basis, can this be completely dismissed
        As solar activity is cyclical, effects will also be cyclical and not cumulative.
        There is no doubt that the sun has influence, the question is how much, and it seems clear [at least to me] that the answer is ‘not much’, otherwise there would not be continuing strife about this as the evidence would be clear [and it is not].

      • Exact, solar activity is the main driver of climate variability. But this occurs through the oceans. In other words, baroclinic waves are resonantly forced by solar cycles, then SST anomalies promote cyclones or anticyclones at mid-latitudes, depending on the sign of the SST anomalies. Unfortunetely, the 11-yr cycle does not resonate.
        JL

      • :”There is no doubt that the sun has influence, the question is how much, and it seems clear [at least to me] that the answer is ‘not much’, otherwise there would not be continuing strife about this as the evidence would be clear [and it is not].”

        Yup. If it was “the sun stupid” the evidence would be clear.

      • Jean-Louis Pinault August 19, 2015 at 10:58 am

        Sure, but the 128 yr period cycle resonates.

        lsvalgaard August 19, 2015 at 10:59 am

        Evidence?

        Jean-Louis Pinault August 19, 2015 at 11:06 am

        Wavelet analysis of SST in the Northern Pacific (http://climatorealist.neowordpress.fr/).

        Thanks, Jean-Louis. To do any analysis of a Fourier or other periodic type on natural data, you need to have an absolute minimum of three cycles worth of data, and I prefer to have at least four. You can verify this by taking a long natural dataset, dividing it in half, and doing a Fourier analysis on the whole as well as the two halves. They will often be very different, with apparent cycles that are clear and strong in one half of the data but which disappear in the second half.

        This is an oddity of the climate—apparent cycles will appear, and last for a while, even for three or four cycles, and then simply fade away and die. So you need to be most suspicious of conclusions about long-period cycles.

        As a result, I’d reject out of hand any claimed analysis of a 128 year cycle based on sea surface temperatures. We don’t have good data for SSTs for 128 years, much less for three times that long.

        w.

      • As an evidence of solar interaction with baroclinic waves, the wavelet analysis of SST in the 48-96 yr band, to highlight 64-yr period SST anomalies:

        Those anomalies are harmonics of the 128-yr cycle that is resonantly forced by the Gleissberg solar cycle.
        The wavelet analysis does not obey the same rules as the FFT. Only a part of the series is used.
        Now the 128-yr period SST anomalies:

        In the North Atlantic SST series seems to be reliable over one century and half.
        JL

      • Those anomalies are harmonics of the 128-yr cycle that is resonantly forced by the Gleissberg solar cycle
        First of all, your cycles are generally artifacts generated by band-pass filtering. Second, Even if similar periods were found, there is no evidence that they are causally related.

      • SST anomalies within the relevant bands are not artifact, which could be questionable for the 128-yr cycle, not for the 64-yr cycle: precautions were taken to check the evolution of the amplitude and phase of the SST anomalies when shifting the window required for the wavelet analysis, along the period of observation.
        The causal relationship between the 64-yr and 128-yr period SST anomalies is largely beyond the scope of this discussion intended to highlight oceanic areas where the Sea Surface Height (SSH) oscillates. I would prefer to refocus the debate on its goal by adding a video highlighting this time SSH anomalies within the 6-12 yr band.

        On the left, in the North Atlantic, are shown the surface height anomalies induced by the 8-year period gyral Rossby wave, red anomalies indicating the lowering of the thermocline, blue anomalies its rising: SSH anomalies range between -0.16 and 0.16 meters.
        These antinodes are always associated with a modulated geostrophic current at the node of the quasi-stationary wave, as shown at right, red anomalies indicating that the modulated current flows eastward, blue anomalies westward: the modulated component of the Surface Current Velocity (SCV) range between -0.08 and 0.08 m/s.

        JL

  36. The question is the variability extreme enough and long enough in duration to impact the climate?

    However to access the impact the other 9 points I posted earlier have to be taken into consideration.

    That post made at 8:48 am Aug.19th.

    • Your argument is a bit circular: if the sun has not varied enough to influence the climate we should just wait long enough until it looks like it has. It is like if I claimed that I mentally can force a coin always to show heads when flipped and I claim that the coin will show 6 heads in a row, so just keep flipping until it does and my claim is validated.

      • No my argument is solar activity has to reach certain criteria before it can trigger a climate reaction in a significant way and until that criteria is reached do not expect much in the way of solar /climate connections.

      • Yep. The old clock test. Wait long enough and your prediction that it is 12:00 will come true. Setting up a bunch of solar parameters (that can easily just be reduced to one that reflects and drives all the other measures) and then waiting for average temperatures to perform to your expectations is not even low hanging fruit in proper scientific methods.

  37. IF there’s some correlation between temperature and the sunspot cycle, the only place I can imagine it would be seen is in deeper ocean temperatures where blue sunlight penetrates deeply and where it is that same blue light that varies most greatly with the sunspot cycle. Even then it might take decades of the sun’s penetrating blue rays to affect things enough so that a correlation would reveal itself.

    It’s too bad there isn’t more ARGO data.

    • Nonsense. There is absolutely no match between the energy required to variably heat such a massively large volume of water and the extrinsic solar energy available in “blue” light (I am guessing you mean UV light), above short term sub-surface intrinsic-driven temperature variations related to mixing, overturning, etc.

    • Come back in 30 years?
      A ‘lets see what happens’ must include a time horizon to be valid. How long must we wait? To be sure that we are not just seeing yet another random fluctuation. I would say 30 years would be convincing to take the effect seriously, but not, of course, to settle the question definitively [that might take a century or two and/or a quantitative and plausible physical mechanism]. I can make an analogy with solar activity and geomagnetic effects, where about a century was the time scale for understanding and acceptance to emerge.

      • No, I think baroclinic waves are resonantly forced by solar cycles, inducing up and down motions of the thermocline. So, the heat is hidden a few tens or hundreds of meters deep. The equations of motion of long baroclinic waves show that the thermocline is in quadrature relative to forcing.

      • And apparently that heat stays hidden for centuries or longer.
        There is good evidence that the Earth has liquid water and life 3000 million years ago, yet the Sun’s luminosity back then was only 70% of what it is today, so even such a MAJOR change did not make a great dent in the climate. Eventually, however, when the Sun swells up to engulf the Earth in 5000 million years time, the solar influence will be strongly felt. In the meantime, perhaps not so much.

      • No they don’t. http://www.leif.org/research/2006GL027817-Milankovich.pdf :
        “Basic physical arguments are used to show that, rather than focusing on the absolute global ice volume, it is much more informative to consider the time rate of change of global ice volume. This simple and dynamically-logical change in perspective is used to show that the available records support a direct, zero-lag, antiphased relationship between the rate of change of global ice volume and summertime insolation in the northern high latitudes.”

      • lsvalgaard: “Sun’s luminosity back then was only 70% of what it is today…”

        And the day was…what?..11, 12 hours long? I wonder what winds were like back then.

        Is there any evidence of past atmospheric pressures? I recall reading that pterodactyls needed a denser atmosphere to fly.

      • “Google…friend…Lots of speculation…”

        I searched before posting. I consider myself a pretty good searcher, but Dim Sun Paradox speculation seems focused on greenhouse gases.

        Wikipedia gives various possibilities, including tidal heating from a close moon. But no consideration of fast spin, which affects low latitude winds, Hadley cell circulation, and cloud formation.

        Earth’s climate is naturally perturbed.

      • I don’t know if he means delta h or differential h, but in any case his conclusion is absurd [the 70%] so I don’t worry too much what he thinks or how people interpret it. As they say “color me unimpressed”.

      • lsvalgaard:

        What I was hoping for.

        Perhaps tidal heating and vulcanism, faster spin of Earth and Sol, weaker magnetic field, stronger solar wind, higher UV luminosity, and greenhousey atmosphere were all required. Perhaps there’d be no life on Earth without the moon.

        The references, and your contributions generally, are much appreciated. Thanks for taking the time.

  38. A comparison between Solar Cycle 12 and the current Solar Cycle 24. Set against a comparison of winter temperatures during the two periods. Winter temperatures from the Central England Temperature set.

  39. I am slightly bemused as to why anyone would think there should be an 11-year solar signal in the sea level record.

    The oceans are a fixed volume of water in a basin of fixed dimensions (when taken over a single decade). While warming will effect sea levels, I see no hope of that happening over such a short time period of 11 years (actually, 5.5 years).

    In short, there is nothing to see here – move along. If they had investigated a centinial or millenial signla, it would have made more sense.

  40. lsvalgaard

    August 19, 2015 at 10:49 am

    but on a cumulative effect basis, can this be completely dismissed
    As solar activity is cyclical, effects will also be cyclical and not cumulative.

    No – I can’t accept that – you are implying that for every rise there should be a drop – however, as I mentioned, we see the sun activity ramping up and ramping down. If the first cycle is +2 and the next cycle is -1; then the cumulative effect is +1 and so on…..for all the reasons everyone knows, seeing this overall effect as measurable within the cycles may not be possible….but it doesn’t mean the cumulative effect (either up or down) is not present!

    • In the long run there is a drop for every rise, certainly [as we now know] that is the case every 11 years, every 100 years, and no trend the past 300 years, so there is no evidence for a cumulative effect.

      • Are you not accepting that Younger Dryas and Maunder Minimum are most LIKELY solar related? On the reasonable assumption that you accept they existed/occurred – how else are you going to explain them other than via a cumulative decline in solar input?
        Also, no trend for 300 years (based presumably only on observed SS numbers?) does not necessarily equate to no trend in incoming solar variation! Hence, I mentioned before that we simply do not have enough modern measurements of actual radiation to use. Old SS data is no more or less a proxy, the same as ice cores, etc. It is assumed to be correct (though still ‘corrected’ lol) and is assumed to ‘match’ current SS observations – which are ‘correlated’ to current solar measurements. That ‘assumed’ correlation may or may not be valid – hence the need for much more time/data.

      • Of course I do not. There is no evidence that they are solar-related. And all the other solar parameters we know off follow the sunspot number. You are, of course, allowed to pick and chose what you want to believe, but that does not count as evidence.

      • >>Leif
        >>There is no evidence that they (ice ages) are solar-related.

        Yes, you believe it is all Milakovitch cycles, as you have said previously.

        So how did we recover from the Younger Dryas, while solar NH insolation was DECREASING? And how did we stay locked in the ice age before last when NH insolation increased by 10%?

        Admit it, Leif, there are other factors at play here.

      • We have to go by the strong evidence we have. Other, unknown influences can be discussed when evidence and theory are developed to the point where they can be taken seriously. Just saying that they may be other things in the mix does not do anything for me, but apparently enthralls you beyond reason. So are we all different.

      • “In the long run there is a drop for every rise”

        But not over a constant timebase and the sunspot record is somewhat saw-toothed. Every Watt (a joule in a constant, precise time interval) counts.

      • >>Just saying that they may be other things in
        >>the mix does not do anything for me.

        But you are emphatically saying ‘its not the Sun’, when there is another unknown factor at play here. And you do not know if that factor is solar related or not. So you bald assertion is unjustified.

        R

      • No, I’m saying there is no evidence that it is the Sun. Very different thing. What people took as evidence [that solar activity has been steadily increasing] has turned out not be happening.

  41. There is a strong underlying assumption of seeing an ~11 yr cycle in the solar data and looking for an 11 year signal in other datasets, such as this sea level data or any other dataset which might be effected.

    There is an implicit assumption that the earth-ocean-atmoshphere system does not act as a filter on the input signal, or that the filter is spectrally white.

    I am sure any electrical engineers or geophysicists reading this get where I am coming from with this. We have an input signal that is being convolved with the earth-ocean-atmoshphere system to yield an output signal (such as the sea level curve in question). By assuming you should see a frequency spectra of the output signal that matches the input signal is to assume the frequency spectra of the earth-ocean-atmoshphere system is completely white.

    In geophysics , we never see the earth filters behave that way with seismic signals. I see no physical reason to believe the ocean-atmoshphere system would behave that way either, given the myriad of processes at work.

    Bottom line – until you know what the earth-ocean-atmoshphere filter response to incoming solar energy is, you can not prove or disprove solar inlfuence on climate via signal analysis.

    • Bottom line – until you know what the earth-ocean-atmosphere filter response to incoming solar energy is, you can not prove or disprove solar influence on climate via signal analysis.
      Tell that to all the sun-nuts who claim that they can. If you can’t see it, you cannot claim it.

    • “I am sure any electrical engineers or geophysicists reading this get where I am coming from with this. We have an input signal that is being convolved with the earth-ocean-atmoshphere system to yield an output signal (such as the sea level curve in question). By assuming you should see a frequency spectra of the output signal that matches the input signal is to assume the frequency spectra of the earth-ocean-atmoshphere system is completely white.”

      Precisely

  42. Just to further the last point, I could design a match filter such that when convolved with the input solar signal you would get the output sea level signal.

    But this would have no physical basis and be completely meaningless. Similarly, looking for 11 year signals in output data is meaningless unless you know what the earth-ocean-atmoshphere filter looks like.

    • Agreed, that there’s no physical basis to connect solar activity to sea level variations. But, I seriously doubt that any matched convolution filter could be designed that would convolve with the “input solar signal” to obtain a credible replica of the “output sea level signal.” You might design a filter whose output may have a very similar power spectrum as sea level, but by all indications the requisitely high cross-spectral coherence simply would NOT be there.

    • Not sure what you mean by “yield spectral information about the sea level change annual growth rate”. In any case the FT of the derivative of any of the tide stations is dead flat at periods longer than one year.

      Thanks for the question,

      w.

  43. Kev-in-Uk August 19, 2015 at 10:41 am

    Not really Leif. It is entirely logical to consider that any variations in incoming energy from the sun will affect climate. Even a tiny percentage point variation will affect the climate over a long enough timescale.

    The luminosity of the sun has increased by about 5% since the “Cambrian explosion” of life on the planet. If your theory were correct, then the earth should be significantly warmer now than it was when life began. But all of the evidence points the other way. Generally, we’re at the cool end of the last half billion years, and if your theory were true, we’d be at the warm end.

    The temperature of the earth is NOT a function of the forcing as the current climate paradigm asserts without proof. Instead, the planetary temperature is kept within fairly narrow bounds by thermoregulatory mechanisms. These mechanisms are temperature-threshold based, not forcing based, and so they are relatively immune to small changes in forcing, even when the change is maintained. When we get a bit more sun, we get a bit more clouds and thunderstorms, and the overall temperature doesn’t change.

    w.

    • Willis – not sure if that argument seems a little forced, excuse the pun, because obviously, as one part of the system shows a greater input (your luminosity) the output part (IR, albedo, etc) may also show a greater value – thereby ‘reducing’ the overall effect. e.g. taking the time lag considerations in account – in the same way as we assume we may be recovering from the LIA, the effect of that increased luminosity will take time to build and take time to disperse (back into space) after the supposed zenith of luminosity. Variations in the climate would be very difficult to ‘isolate’ or pin down within that likely large ‘laggy’ system. Even as a geologist, I take the palaeoclimate proxies with a sack of salt.

      Even in your last paragraph, you have dismissed the lag in the system as saying the overall temperature doesn’t change – but in reality – it did, even if only for a few hours (as per your thermal cloud regulatory theory) – you could not suspect that if you were historically looking back at max/min temp data – so how would you know or posit such a mechanism existed? (in the absence of a current observation of thunderstorms I mean)

      The cumulative effect of very minor changes will depend on the lag in the system and of course the climate regulatory systems you mention. That does not mean that they are not there — just we cant see or detect them within the noise of the system. In my opinion, even 300 years of SS data is not really a great indicator of solar activity if we consider that 1) old data may not be brilliant and/or directly comparable to modern data and 2) the sun may have changed a little since then anyway, and hence our modern observations/correlations need not necessarily be ‘correct’ when compared to old data. In the same way as I don’t fully accept the ice core temp proxies, because it is based on assumptions that modern temps and firn deposition can be directly ‘compared’ to past temps and firn deposition/compaction. It is a proxy, but has to be used with caution. I dunno, perhaps like C14 dating – it has to be given a wide range and heavily understated (likely or estimated) limits of accuracy.

      Ultimately, what do people make of the varying solar cycles? – i.e. the differences between ramp up and slow down of the various cycles (based on SS numbers) – is it right to use this as a sole definer of actual solar activity and ergo, the actual solar insolation onto/into the earth? I think we are too reliant on this premise. Like Mosh says about the temp data, its the best we have. But it’s limitations are well known. Why is SS data not treated with the same contempt or scepticism?

      regards
      Kev

  44. lsvalgaard

    August 19, 2015 at 11:22 am

    Of course I do not. There is no evidence that they are solar-related. And all the other solar parameters we know off follow the sunspot number. You are, of course, allowed to pick and chose what you want to believe, but that does not count as evidence

    Leif, with respect, – that is somewhat ironic. You seemingly ‘believe’ in no significant solar variation based ultimately on what amounts to historical SS data? Fine, but that does not count as (direct) evidence either, especially as we know full well that insolation does indeed vary! What about solar parameters we don’t know or understand (because we only have limited observations)? Obviously, you can pick and choose too!

    I’m not arguing one way or the other, per se – I am just pointing out that either extreme stance is not currently demonstrable – that solar is or isn’t a main driver. I simply find myself more within the LOGICAL deduction camp that, as the primary source of (almost) all energy on the planet, and more specifically ‘into’ the climate system (even via lagged systems such as oceans) – any variation in solar activity/energy/whatever – will most likely have a climatic effect. I don’t know how much, how long, or how significant, but it IS a logical derivation. The tendency to dismiss solar activity as minor, simply because we don’t yet understand it fully, or we have not yet been able to measure significant (or more accurately, what we ‘believe’ to be significant) changes is not really a viable stance in my humble opinion. Microscopic changes in things can and do indeed lead to much bigger effects – hence, looking at what is ultimately macroscopic indications (such as sunspots) is perhaps a little blinkered. I fully accept we have that data, and we should use it – but it is limited and this should be remembered at all times. Ditto for the surface temp record, etc – it is all rather limited in the big (and geologically time based) scheme of things.
    regards
    Kev

    • we know full well that insolation does indeed vary! What about solar parameters we don’t know or understand (because we only have limited observations)
      You are being a bit clever here going after a straw man. ‘Insolation’ usually has a meaning other than solar activity related [Milankovich, etc]. And about the things we don’t know we should keep silent as nothing meaningful can be said about them and they certainly cannot be taken as ‘evidence’. As a solar physicist I will state that we have a pretty good understanding [not compete – there is always more to learn – but pretty good] of the solar parameters we do know about.

      • Leif – you are twisting my meaning I think. I was of course referring to the published variation in solar influx of allegedly around +/- 1.3 w/m2. Even as 0.1% of total solar, it is a significant amount. How much do we actually know about the interactions of solar wind, cosmic rays, geomagnetic effects (sun and earth), etc, etc? (I don’t know, but I bet its not everything !). I mean, as a physicist, you should know full well that there is stuff still to be confirmed/proved, we only just recently confirmed Higgs bloody Boson!
        Just as a for example – the Northern Lights are believed to be when solar wind particles are guided by the earths magnetic field and release their energy as light – this is why we see them. However, what is happening when we can’t see them? Do we deduce that there are no solar particles at that time? No, of course not – just the conditions are not the same to allow them to be ‘as’ visible, if at all. Should we therefore use the Northern Lights as a proxy for solar activity or the strength of the solar wind? or for the strength of the earths magnetic field, etc? Understanding the principle does not necessarily demonstrate the understanding of the whole picture or why we see/don’t see the interactions of the various components!
        I don’t really see there is much else to say, but thanks for the discussion.

      • Well, words are important. If you mean irradiance, say that. If you mean insolation, say that.
        As for the various effects you mention: we do know in some detail haw all that works. There are still further details to discover, but the basics is well-understood. You underestimate how MUCH we actually know.
        You ask:
        However, what is happening when we can’t see them?
        We wait until it is dark, then we can see them [all the time if you are in the right place – they never go away]

        Should we therefore use the Northern Lights as a proxy for solar activity or the strength of the solar wind?
        they would in fact be good proxies for those things, and have been used for that.

  45. The climate regulator you suggest Willis does not regulate climatic cycles all it does is keep the tropics in a more or less steady state.

    The real climatic regulators I will post next.

  46. Here is what regulates the climate , in a brief concise nutshell. This is what keeps it within a range bound to a degree.

    Land/Ocean Arrangements and Land Elevation.

    Milankovitch Cycles- where earth is in regard to these cycles.

    Solar Variability- primary and secondary effects..

    Geo Magnetic Intensity- which moderates solar activity.

    Initial State Of The Climate- how far the climate is from the glacial /inter-glacial threshold.

    Ice ,Snow, Cloud Cover Dynamic – which are tied to the above to one degree or another.

    Intrinsic Earth Bound Climatic Items- such as ENSO which refine the climate trends.

    Rogue Terrestrial Event- such as a Super Volcanic Eruption.

    Rogue Extra Terrestrial Event – such as an impact.

  47. What Willis fails to address is how his tropical regulator give the climate a semi cyclic beat. My climate regulators do.

    In addition the regulator he proposes from a practical stand point does not make the climate stable as far as humans are concerned unless one thinks a glacial versus an inter -glacial period is of no significance.

    This is what matters.

  48. The primary frequency in the solar sun spot time series is 11 years +/-. The FFT will easily pull out this signal. The primary frequency in the tidal records is 1 year. The FFT does a great job in showing this as well. It would make more sense to filter the tidal record to eliminate the 1 year and shorter cycles. Also show the tidal record time series (which was not done). Figure 1, sun spot time series, Figure 2, sun spot frequency spectrum, Figure 3 tidal record time series filtered to eliminate 1 year and shorter frequencies and Figure 4, tidal record spectrum. Then you can argue that the sun spot time series is dominated by the 11 year cycle and the tidal record is dominated by noise.

  49. Hi Willis,
    3.5 year period frequency is very simple. It is Lowest Common Multiplier of orbital length of Earth, Venus and Mars. If you look it is more like 3.7 year period. This is 1350 days. Venus year is 225 days, Mars year is 687 days. 1350 is exactly 6 Venus years, 3,7 Earth years and very close 2 Mars years.
    You simply found that each 3,7 year Venus and Mars are aligned for maximum impact on Earth tide.

  50. I thought Shaviv said that there was an 11 year cycle in the rate of change of sea level not in the sea level itself…. Willis graph shows why an 11 year harmonic is a good approx for solar though.

  51. A periodogram of the TOPEX and Jason data show an 11 year period in the sea level data.

    The University of Colorado Sea Level Research Group publishes monthly data for the Global Mean Sea Level. The data can be downloaded here. It is a combination of data from Jason-1, Jason-2 and TOPEX. It is the data that was used by Dr. Shaviv et al. in their paper.

    Unfortunately, the data file contains the date in decimal years format (e.g., “1993.0409”). I wrote a program to convert the decimal years to year-month-day format. The data is reported approximately every 10 days (but sometimes there are 20 days between data values), which means there are two or three data values per month. The periodogram works best if the time between measurements are all the same. So I wrote another program to average the values for each month. That way the data is in monthly format (available here; sorry its a Word document because WordPress will not let me load text files into my media library). I then used the following R-code to read the data, calculate the periodogram and plot the result, which is shown in Figure 1.


    sldat <- read.table( "c:/temp/sl_global_avg.txt", header = TRUE, row.names=1)
    slpgram <- spec.pgram( sldat, plot = FALSE)
    plot(slpgram, log="no", main="Sea Level\nRaw Periodogram",lty=1,col="black" )

    Figure 1. The periodogram for the TOPEX and Jason Sea Level data.

    The frequencies and periods of the five heighest peaks in Figure 1 are shown in Table 1. The period in months is obtained by taking the recipricol of the frequency. The period in years is obtained by dividing the period in months by 12 months/year. Figure 2 shows a close-up view of the first frequency peak at 0.00740 month-1.

    Frequency
    Period
    Period

    month-1
    months
    years

    0.00740
    135
    11

    0.0222
    45
    4

    0.0852
    11.7
    1

    0.167
    6
    0.5

    0.481
    2.1
    0.2

    Table 1. Frequencies and Periods

    Figure 2. A closeup view of the periodogram for the TOPEX and Jason Sea Level data with the frequency at 0.00740 month-1 marked by a vertical line.

    The data shows an unmistakable peak at a frequency of 0.00740 month-1. That is, the data shows an unmistakable peak at a period of 11 years, which is roughly the same as the solar cycle. Therefore, Dr. Shaviv and his collegues are justified in assuming a harmonic solar component in the seal level data.

    • In the case of stochastically varying signals, raw periodograms are not statistically CONSISTENT estimators of the power spectra, no matter how long the record. Furthermore, power spectrum peaks at nearly the same frequency are far from clear evidence of causal physical relationship between two signals They could readily be concomitant variables, physically dependent in some way upon an unknown third variable. What is absent in all claims of solar components in sea-level data is any demonstration of high cross-spectral coherence. Even with high coherence, we would meet only a necessary, but not sufficient, condition for acausal connection.

      • You are quite right. Just because an 11-year cycle appears in a data set does not mean that it must be related to the solar cycle. At absolute most, one can say only that it could be related to the solar cycle. Necessary, but not sufficient. But, it is still worth investigating.

      • Yes. After I was looking more at the periodogram, I would agree that the word “unmistakable” is much too strong. The 11-year period appears at the very edge of the chart, which means that the cycle just barely emerges from the data. So one should say only that there is a peak (without any adjectives), but it should be taken with a grain of salt. But is there in the data, and it is still worth investigating. And I would still say that Dr. Shaviv et al. were justified in their use of an harmonic solar component to try to tease out a fit to that 11 year cycle.

        I would expect though, that as more data comes in, it is more likely that the peak will grow rather than vanish. But then again maybe it will vanish.

      • nhill, I say again, three cycles is my absolute minimum length for periodograms of natural datasets, and I much prefer four cycles … and I’ve been fooled by five cycles.

        With a 22-year dataset, you have two cycles … useless for an 11-year signal. It’s one of the problems with Shaviv’s analysis.

        Grab a long dataset and run a periodogram on it, then divide it in have and do the same on the two halves. See what happens to the cycles longer than about a quarter of the data. Not pretty.

        w.

  52. The problem with using a small number of tide gauges is that what we’re trying to measure-indirectly by measuring the surface height) are changes in the ocean’s volume due to thermal expansion. To reliably do that, we need to measure the height across the entire ocean, because sea level can rise and fall in individual places relative to the “mean” height.

    It’s a shame the altimetry data only go back so far.

  53. If sunspots are the accellerator pedal then Shaviv hypothesises that there will be a signal in the sea level acceleration but Willis focused on a relationship between accellerator pedal position and the speedo reading – I can be doing 100 mph with my foot off the pedal or 10 mph with my foot flat to the floor. Looking at sea level seems like a fundamental error.

  54. Okay, I’m going to be a squeaky wheel on this one. Willis, I suspect there is a severe flaw in what you are doing here, you don’t seem to be aware of it and nobody else is paying any attention to it:

    There is far too much noise in the tidal data to be able to see the 11-year signal even if it were present.

    This is easy to prove and I’m working to get my data and graphs accesible (I will try to post links later today). Willis, you should be able to easily do this yourself too. All you have to do is add a fake 11-year signal to the tidal data and then see if the periodogram can find it. I’ve tried this experiment with data from several locations (e.g. Brest) and the results are similar with all of them.

    I have taken Willis’ published tidal data and added a 5.0mm peak-to-peak sine wave at various periods from 11 to 12 years and with various phase offsets (details below). You can see a change in the periodogram around 11-12 years, but it is so small compared to the noise that I don’t think anyone could reasonably say “there’s a signal there”.

    So, while this is a great discussion to have — especially the part about “where would or should one look for 11 year signals?”, I propose that Willis is working with data which cannot possibly show this signal — even if it is there. GIGO.

    I am sorry to be so adamant on this point but making un-warranted conclusions (there’s no signal there) from dodgy data (there’s too much noise) is just plain wrong.

    Details: Since the tidal data has a resolution of 1mm I have used this formula to create the fake signal:

    fake(t) = round(2.5mm * cos(omega * t + phase offset))

    omega is chosen to yield a period between 11 and 12 years. Then I added this fake signal to the raw tidal data before generating the periodogram.

    Willis, I do not know the exact details of your construction of the periodograms so I cannot duplicate your results exactly. I de-trended the data, offset to zero mean value and then applied a Hanning window before computing the discrete Fourier transform.

    Finally, I’m fallible too…if I made a mistake here then well, I made a mistake and you have my apologies in advance. However, I have checked my work several times through and cannot find any mistakes. If you find that I’ve made an error I can accept that too and won’t take it personally if you speak poorly of me!

    • Okay, here’s all of the tools and graph results that prove that a +-2.5mm 11-year signal in the tidal data is not easily detectable. The only thing I could not make available is the CSV version of Willis’ spreadsheet, but you can generate that easily by using “Save As…” in Excel to save a CSV format file.

      Scripts were run in Matlab but were tested in Freemat too.

      This example uses only a windowed periodogram and there are more advanced ways to do periodograms out there, so perhaps the signal might be detectable that way but certainly not as shown here.

      http://wxobserver.wordpress.com/2015/08/20/tidal-data-tools-and-results-archive/

      Please post any comments here as opposed to the blog linked above as it is not regularly checked for comments.

  55. It seems to me that low presence of a ~11-year cycle in Fourier analysis indicates that variations of solar activity don’t have much effect on sea level. Sea level variations are driven by temperature, via thermal expansion (and its inverse), and runoff/formation of accumulations of water (including ice) on land. This seems to indicate that climate sensitivity to solar variation is low.

    Otherwise, wxobserver is on-spot about noise exceeding signal.

    As for the distinct peaks: The 1-year peak seems to be from one or more annual cycles, such as annual variation of wind direction at a coastal tide gauge. The .5-year peak is the 2nd harmonic – which can come from the annual variation deviating from a sinusoid by having its annual high-point or its annual low-point deviating from a sinusoid in the direction of either going spiky or being limited/squashed/clipped.

  56. Willis,

    It seems quite sure that there is little 11-year solar signal in sea level, neither in temperatures.
    One question remains: does the water vapor/clouds/precipitation feedback remove these cycles in favor of an 11-year amplitude in the water cycle?
    There are indications for an 11-year cycle in river discharges mainly in the mid-latitudes: Mississippi catch area, Portugal, Po (Italy), Nile and in South Africa… Partly caused by shifts of the jet stream to the poles or equator during the solar cycle (at maximum: more UV – ozone – higher temperatures in the lower stratosphere – more temperature difference between equator and poles).

    I have the links, but a previous comment still is in moderation (I hope), because of too many links…

    As you have both datasets for precipitation and the solar cycle, maybe an idea for a follow-up article…

  57. Willis – I enjoy your posts. The theory that solar cycles influence cloud formation and our climate seems plausible to me. But, I agree with you about not expecting their periodicity to be directly reflected in sea-level measurements. I’m an electrical engineer, and cordially offer a few remarks.

    Because global sea-level changes in recent centuries are dominated by thermal expansion, they are driven primarily by changes in mean ocean temperature (averaged globally and over all depths). Because of their immense thermal capacity, it takes centuries to completely warm the oceans from the surface. Assuming roughly constant geothermal warming, recent changes in mean ocean temperature are largely the net result of the variable warming applied to the surface over the last several centuries. This is like a low-pass filter, smoothing out short-term (less than a century) variations in mean temperature.

    It’s like a pot of water on a gas stove. If the gas is rapidly turned on and off by a Morse code operator, a frog basking in the pot would only sense gradual delayed warming, with no way to know whether he was warmed by Shakespeare or a Michael Mann paper (although some might say Mann’s work should have a telltale stench).

    But, it’s always good to look at real data. The solar data certainly seems oscillatory, but if the period varies significantly, Fourier techniques would give a dull peak. An alternative would be to compute the correlation between the solar data and a composite sea-level time-series and see if there’s a meaningful peak. (I wouldn’t expect one.) If using Fourier methods, of course there are endless ways to do it, such as Welch’s method with various window and segmenting options, as others mentioned, but I don’t think that was really the problem here.

    The suggestion of looking at the derivative of sea level makes sense theoretically, but IMO wouldn’t help in practice because the 11 year signal and its derivative were both pretty thoroughly filtered away, and even if a trace remained, taking a derivative would amplify spurious noise.

    Clearly the bottom line is that there are much better places to look for solar cycle signatures.

  58. Milankovitch Cycle as I have said are a part of the big climate picture but fail to explain the 1470 year climatic cycle within the big picture and the countless abrupt climatic changes that have taken place on the order of the YD. The YD period not being unique in the historical climatic record.

    Other climatic items are in play to account for this which I have explained in may of my previous postings.

  59. Tidal data is nowhere near good enough to extract anything other than the 1 year signal. You need to use satellite altimetry data — properly corrected for ENSO — but alas you will need to wait a few more decades.

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