Solar Cycle Driven Ocean Temperature Variations

What Slow Fourier Transforms can tell us.

Guest essay by Stan Robertson, Ph.D., P.E.

On May 3, 2014, an article on WUWT by Willis Eschenbach entitled, The Slow Fourier Transform (SFT) was posted. As he noted, the amplitude of the Slow Fourier Transform components are in the same units as the fitted data, intervals of arbitrary length and irregular data can be used and periodicities rather than frequencies are automatically extracted. In addition to rediscovering a very useful mathematical tool, Willis went on to show that there were apparently no variations of temperature associated with solar cycle variations for several long term temperature records. Now my normal inclination would be to say that if Willis didn’t find any there probably aren’t many to be found. But, on the other hand, as I showed in an October 10, 2013 WUWT article entitled The Sun Does It: Now Go Figure Out How!, it does not take much of a temperature variation to represent a very significant solar contribution to ocean surface temperatures and heat content.

Several researchers, including Nir Shaviv (2008), Roy Spencer (see http://www.drroyspencer.com/2010/06/low-climate-sensitivity-estimated-from-the-11-year-cycle-in-total-solar-irradiance/) and Zhou & Tung (2010) have found that ocean surface temperatures oscillate with an amplitude of about 0.04 – 0.05 oC during a solar cycle. Using 150 years of sea surface temperature data, Zhou & Tung found 0.085 oC warming for each watt/m2 of increase of TSI over a solar cycle.

In my previous article, I showed that the changes of Total Solar Irradiance (TSI) over a solar cyle were too small, by at least a factor of 3.6, to cause temperature oscillations with an amplitude of 0.04 C. Since the variations of temperature considered were clearly associated with solar cycles, it seemed to me that the sun does something more to change ocean surface temperatures than just vary its TSI. But the whole idea would fall apart if there really are no significant variations of ocean temperature correlated with solar cycles. That motivated me to look in places where Willis had not and, in particular, to look at shorter and more recent temperature records that might be both more accurate and with better distribution over the ocean surfaces.

 

I downloaded the HADSST3 global sea surface temperature raw data (http://woodfortrees.org/plot/hadsst3gl ) and took a look at the data since 1954. This covers 60 years of data and about five and one half solar cycles. To get an idea of what sort of noise would be in these data, I fitted the sea surface temperatures to a cubic polynomial just to get rid of most of the systematic variations. The figure below shows a plot of the residuals for the last 60 years.

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Figure 1 HADSST3GL residuals for the last 60 years
If we are looking for variations of about 0.04 C amplitude over the 5.5 solar cycles in the time period shown, then with apparently random variations of about 0.3 C amplitude in the record, the signal to noise ratio would be about 0.04 / 0.3 = 0.13. This would be a signal a long way down in the noise. So the question is, can we extract such a signal with a Slow Fourier Transform? To answer this question, I adopted Willis’ lovely SFT technique. I generated some test monthly data for a 60 year interval consisting of sine waves with a 10 year period plus monthly random noise in the range of +/-0.5 C. The slow FT results for waves with amplitude of 0.15 C, 0.1 C and 0.05 C would have signal to noise ratios of 0.3, 0.2 and 0.1, respectively. The results are shown in Figure 2.

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Figure 2. Slow FT for test sine waves with 10 year period for a sixty year interval; 6 cycles.

As one might expect, the random variations would have both short period and long period apparent periodicities as shown in Figure 2. At a signal to noise ratio of 0.2 (blue line), or larger, the signal buried in the noise can be nicely extracted by the Slow FT. At a signal to noise ratio of 0.1, and none of the other curves to aid the eye, you might just have to believe that there might be a signal with a 10 year period. It is hardly bigger than the spurious noise peaks. Of course, there are much more sophisticated signal extraction processes than the Slow Fourier Transform. From comments that I have seen here on WUWT, there are some sharp readers around who could surely teach us some lessons. It might be expecting too much to see such a small signal in the noisy sea surface temperature data with an SFT method. But it is worth noting that in each of the test cases, the Slow FT peaks at 10 yr are smaller than the amplitudes that generated the test data by about ten to twenty percent with worse results at lower signal to noise ratios.

Since it is pretty clear that we will be looking for a small signal in a lot of noise, we probably ought to see where to look. A slow FT of the SIDC sunspot numbers for the years since 1954 shows a peak at 10.8 years as shown in Figure 3.

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Figure 3. Slow FT for SIDC sunspot numbers 1954 – 2014

Now let’s have a look at the Slow FT for the sea surface temperature data. The average was subtracted to help suppress spurious long periods, but no smoothing was applied.

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Figure 4 Slow FT for HADSST3gl sea surface temperatures

I leave it to the readers to decide whether or not there is a solar cycle signal in the HADSST3gl sea surface temperature record. Considering that the slow FT tends to understate the actual signal amplitude at low signal to noise ratios, I think that this might be a credible detection of a solar cycle driven temperature variation at a 10.4 year period with a signal to noise ratio of at least 0.065 C/ 0.3 C = 0.22.

For the remainder of this essay, I would like to extend and recapitulate some of my previous findings. The prevailing view in climate science is that the sun has contributed very little, if anything, to the warming of the last century. Finding that ocean temperatures are affected during solar cycles to a much larger degree than can be explained by the small changes of solar irradiance that reach the sea surfaces is a huge challenge to the prevailing view, but it rests on some bedrock physics. A detailed accounting for energy exchanges, including thermal energies is as fundamental as it gets.

I was able to account for the long term secular trends of both the sea surface temperature changes AND the ocean heat content since 1965 with a linearly increasing rate of surface heating. This involved numerically solving some heat transfer equations, including the absorption of solar energy, but it provided a simple, two parameter simultaneous fit to the sea surface temperature record AND the ocean heat content record. The two parameters found were a rate of increase of surface heat input of 0.31 watt/m2 per decade and an average thermal diffusivity of the upper oceans of 1 cm2/s. A fairly good fit to both trends was obtained as shown in Figure 5.

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Figure 5. Measured and Calculated Sea Surface Temperature and Ocean Heat Content

A good fit was obtainable only for very narrow ranges of parameters. If the thermal diffusivity is taken to be too large, too much heat would be calculated for the ocean depths and surface temperatures would rise too little as the heat moves on to greater depths. If too small, the reverse occurs. If the input heating rate is too large, both rise too rapidly and if too small, both rise too little. The point of this exercise was to obtain a thermal diffusivity that could then be used to tell us how much surface temperature change could be produced by the changes of solar irradiance that occur during solar cycles. The answer is that the small variations of solar irradiance that reach the sea surfaces are far too small to produce temperature oscillations of even 0.04 C amplitude, much less the 0.065 watt/m2 amplitude suggested by Figure 4.

By the same computer program that I had used for my previous WUWT article, I have found that the amplitude of oscillating heat flux entering the ocean that would be required to produce surface temperature oscillations with the Figure 4 amplitude of 0.065 C would be 0.47 watt/m2 for thermal diffusivity of 1 cm2/s. How does this compare to the oscillating flux of solar radiation that reaches the sea surface? Let’s have a look at the solar irradiance changes over solar cycles. Figure 6 shows that TSI varies approximately sinusoidally over recent solar cycles with an amplitude of about 0.5 watt/m2 . (Thanks to Leif Svalgaard for TSI data.)

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Figure 6 TSI variations for a few recent solar cyles.

As explained in my previous WUWT post, about 70% of one fourth of this amplitude, or 0.0875 watt/m2 enters the troposphere averaged over the earth area and day-night cycles. About

(160 watt/m2 /1365 watt/m^2) X 0.5 watt/m^2 = 0.0586 Watt/m2 is absorbed at the surface at wavelengths below 2 micron. About half the difference between the 0.0875 and 0.0586 watt/m2 reaches the surface at longer wavelengths and after scattering in the atmosphere. This give a solar TSI amplitude of 0.073 watt/m2 that is absorbed at the sea surface. This is about 6.4 times smaller than the 0.47 watt/m2 amplitude needed to drive surface temperature oscillations of 0.065 C. This result is in better agreement with the larger factors of 5 – 7 found by Shaviv (2008) ( see http://www.sciencebits.com/files/articles/CalorimeterFinal.pdf)

It is of some interest that my results were obtained without assuming any particular depth of an ocean mixing layer. For a thermal diffusivity of 1 cm2/s, the contribution to thermal gradients that vary with the solar cycle below the first ten meters would be much less than 0.001 C/m anyway. I saw no need to introduce a mixing zone with zero gradients and an arbitrary depth boundary.

This leaves us with a clear result that the TSI variations during solar cycles are not the direct drivers of the associated ocean temperature oscillations. Something else that varies with the solar cycles affects the amount of heat flux that penetrates the ocean surfaces. In my opinion, the most likely candidate would be cyclical variations of global cloud cover, but the mechanism that would control it is presently a research topic. Whatever the mechanism of the larger heating variations, it seems quite possible that it might be capable of producing long term secular trends under the control of the sun in addition to variations over solar cycles.

To examine this point, go back to the result shown in Figure 5. The heat flux required to account for the trends of increasing sea surface temperature and ocean heat content had to increase by 0.31 watt/m2/decade. Could this be due to greenhouse gases? CO2 is supposed to produce heating at a rate of about 3.7 watt/m2 per doubling period of its concentration. With concentration increasing at a rate of about 5% per decade, the doubling time would be about 14 decades. Since the heating effect is a logarithmic function of concentration, this would produce a linear heating at a rate of 3.7/14 = 0.26 watt/m2 per decade. This is certainly in the right ballpark to be part of the explanation of the apparent surface heating of the last few decades, however, when we recall that sulfate aerosols with negating effects would partially counter the CO2, it seems to me unlikely that CO2 is the entire explanation. Considering the similar period of rapid warming in the first half of the last century and the presently expanding and embarrassing pause of temperature increases, it seems to me that there is ample room for a significant solar contribution to the longer term warming periods. So I still think that the sun does a lot of it and I would still like to know how. Climate scientists would be well advised to spend some time trying to find out.

210 thoughts on “Solar Cycle Driven Ocean Temperature Variations

  1. In my previous article, I showed that the changes of Total Solar Irradiance (TSI) over a solar cyle were too small, by at least a factor of 3.6, to cause temperature oscillations with an amplitude of 0.04 C.

    The standard formula for this is dT/T = (dTSI/TSI)/4, which with an amplitude [=half from min to max] of 0.05% in dTSI/TSI gives dT/T = 0.0125% [of T=288K] = 0.036 C , so the variation of TSI is just what is needed.

  2. Leif Svalgaard says:
    July 26, 2014 at 6:40 am
    . . . The standard formula for this is dT/T = (dTSI/TSI)/4, which with an amplitude [=half from min to max] of 0.05% in dTSI/TSI gives dT/T = 0.0125% [of T=299K] = 0.036 C , so the variation of TSI is just what is needed.
    ——————————————–
    Sorry Leif, the TSI variations are at the top of the atmosphere and that is where T must be taken as well. It is a different matter down at sea level where most of the heat enters the oceans as solar UV/Vis. Your calculation would only apply to a blackbody absorber with zero heat capacity. Your simple radiation balance is not applicable there and apparently you still don’t understand the concept of thermal inertia.
    Stan Robertson (bones)

  3. Finally! Someone intelligently calculates [] energy required in order to compare what is being delivered when examining possible cause and effect speculations. Thank you. The rest of your offering will be digested after breakfast and another cup of coffee.

  4. oops, need to delete a word to correct a sentence, “…intelligently calculates energy required…”

  5. “Your simple radiation balance is not applicable there and apparently you still don’t understand the concept of thermal inertia. ”
    Stan Robertson (bones)

  6. “Something else that varies with the solar cycles affects the amount of heat flux that penetrates the ocean surfaces. In my opinion, the most likely candidate would be cyclical variations of global cloud cover, but the mechanism that would control it is presently a research topic”

    and:

    “So I still think that the sun does a lot of it and I would still like to know how. Climate scientists would be well advised to spend some time trying to find out.”

    Already done:

    http://www.newclimatemodel.com/new-climate-model/

    Solar effects alter global cloudiness by changing the gradient of tropopause height between equator and poles which results in latitudinal climate zone shifting with consequential changes in the length of the lines of air mass mixing.

    One doesn’t even need to involve cosmic rays as per Svensmark.

  7. I see the value of q being shown as W/m2/10 years. What is this?? the units of q should be W/m2. What is the 10 years about? Is it the average value over 10 year periods? If so point that out.

  8. bones says:
    July 26, 2014 at 7:08 am
    Sorry Leif, the TSI variations are at the top of the atmosphere and that is where T must be taken as well.
    You can be as sorry as you like, my calculation stands.

  9. Leonard Weinstein says:
    July 26, 2014 at 7:30 am

    I see the value of q being shown as W/m2/10 years. What is this?? the units of q should be W/m2. What is the 10 years about? Is it the average value over 10 year periods? If so point that out.
    —————————————————————
    Leonard, you need to read my previous article for context. The rate of increase of surface heating in W/m^2/decade was what was needed to account for the measured increases of ocean surface temperatures and ocean heat content since 1965. That is different from the cyclical variation of heat inputs in W/m^2 over a single solar cycle of 10 to11 years.

  10. The top of the atmosphere translates to 0.073 watt/m2 under clear sky conditions. Naturally that means that all of it would enter in and be absorbed into the oceans under those conditions. Can we consider longwave infrared back radiation from CO2 adding to that figure? Probably trivially. So what would vary this figure considerably? Clouds and water surface conditions down to the depth of visible penetration around the equatorial band. If the wind is dead calm, the waters layer up with warm on the top and water starts to evaporate leading to clouds, so now we have even less watts. If the sea surface is chopped up we have fairly clear skies but we might have cloudy water leading to less penetration. It is a conundrum.

    However, over very long time spans we might have a convincing argument related to a building imbalance (as in more heat going in than going out) leading to long noisy cycles of warmth. But that imbalance begins to go the other way eventually. Leading to some very cold years, decades, and even longer before once again we climb back out of a cold spell. The oceans certainly have the capacity to absorb more heat than they give out (brrrr). The opposite is true as well. If conditions lead to evaporation of that heat, it could lead to long periods of warmth before the tank is empty. And the inertia of such a large volume can be calculated to be hundreds of years long.

  11. Leif Svalgaard says:
    July 26, 2014 at 7:34 am

    bones says:
    July 26, 2014 at 7:08 am
    Sorry Leif, the TSI variations are at the top of the atmosphere and that is where T must be taken as well.
    You can be as sorry as you like, my calculation stands.
    —————————————————–
    And it still stands as inapplicable to the ocean heating problem. If you have nothing new to add to this discussion, why don’t we agree refer the reader back to the comments below my previous article. Those were detailed enough for all to see our discussion of these issues at that time.

  12. Pamela Gray says:
    July 26, 2014 at 7:38 am

    The top of the atmosphere translates to 0.073 watt/m2 under clear sky conditions. Naturally that means that all of it would enter in and be absorbed into the oceans under those conditions. . . .
    …..The opposite is true as well. If conditions lead to evaporation of that heat, it could lead to long periods of warmth before the tank is empty. And the inertia of such a large volume can be calculated to be hundreds of years long.
    —————————————————————————
    Well written. I agree.

  13. bones says:
    July 26, 2014 at 7:39 am
    And it still stands as inapplicable to the ocean heating problem.
    In any case the observed variation is just as calculated from the radiation balance, so no extraneous considerations need be applied, but I’ll agree that you cannot be persuaded to see your error, so will let is stand there.

  14. Ocean heat data is an important topic in this discussion. Satellite data samples only the ocean’s skin. Therefore you may get the wrong impression that heat was “added” from above when in reality it was already there but just shifted to the surface. Previous to satellite data, surface heat was actually not surface heat but below surface heat. So be cautious in your use of data that leads you to conclude supposed added heat. That may not be the case.

    http://podaac.jpl.nasa.gov/SeaSurfaceTemperature

  15. What the co2 driven global warming advocates don’t discuss is that if the ocean has started eating global warming since the trade winds changed during the negative phase of the ocean’s ~60 year multi-decadal cycles, they also emitted excess energy during their positive phase from 1975-2005. The implication is that the oceans are capable of storing energy on long timescales, and releasing it on long timescales too. And they store a lot of energy. The top two metres alone contain as much energy as the entire atmosphere above.

    We know that the oceans keep the air temperature up over night as the release some of the energy the Sun poured into them during the day. We also know that there is a lag of a couple of months between the longest day of the year and the peak in surface air temperatures near coasts. This is thermal inertia and heat capacity at work. On longer timescales, we have recently confirmed that runs of El Nino events which release a lot of energy from the oceans are initiated on the falling side of the solar cycle, never on the upswing.

    So we can go a stretch further and combine what we know. When solar activity falls, energy comes out of the ocean, not just over the period of the decline of a single 11 year solar cycle, but if the Sun stays low in activity terms, for many years. An integration of the sunspot number shows us that the ocean heat content rose all the way from 1934 to 2003. This is the real cause of ‘global warming’. A lot of excess energy is still retained in the upper ocean. We can expect the effect of a couple of low solar cycles to be softened by a proportion of that excess heat returning to space via the atmosphere warming it on the way.

    In developing my understanding of the Earth’s systems, I developed a couple of very simple models to help me fathom the way the surface temperature stays fairly constant as the solar cycles wax and wane. Back in 2009, by analysing the data, I found that the global average sea surface temperature, the SST, stays fairly constant when the Sun is averaging around 40 sunspots per month. By calculating the running total departing from this figure in a simple integration I found that combined with the ~60 oceanic cycles (also solar influenced), I could reproduce the temperature history of the last 150 years quite accurately. By adding in a nominal forcing for co2 (or an allowance for the infamous ‘adjustments’ to the data), I was able to get a match to monthly data which has a Pearson R^2 value of 0.9.

    Rog’s take which I agree with.

  16. The ocean’s role in the heat discharge/recharge/location factor needs to be considered (I added the word “location” to the function set because that is beginning to reveal itself as an important component in measuring oceanic heat). For that piece of your thesis I would rely on Bob Tisdale’s data explanations and oceanic processes, which are well supported in the literature and is beginning to receive notice by scientists such as Judith Curry.

    We are fortunate to have the offerings of Anth*** Watts’ surface station investigations and Bob Tisdale’s explanations of ocean temperature measurements and processes.

  17. It is very clear that IR radiation has no effect on OHC or surface water temperatures and that Visible Light and UV light have major effects on OHC and Surface Water temperatures.

    Therefore AGW has nothing to do with ocean heat content and ocean surface temperatures while the sun has everything to do with it.
    OHC has just been responding to the extreme strong solar conditions 1934-2003 which have leveled off post 2005. OHC will follow.

    IR penetration of surface ocean .1mm visible light /long UV light tens of meters. Seems pretty clear according to the data.

  18. Firstly for FT part, in looking a spectral analysis of SST , basin by basin, I found some odd changes were introduced by the Hadley processing around the decadal scale. Here is one example:

    The probably lunar periodicity of 9.04 years gets attenuated and somewhat shifted ( this probably corresponding to Scaffeta’s 9.1+/-0.1 and recent BEST european land temps ) .

    I don’t know which is “correct” but until someone at Hadley does some QA on the effects of their magic on the frequency spectrum, I’ll stick with ICOADS, at least for post WWII period.

    Sulphates seem to be in the news this week, and perhaps about time. However, the cause of the reduction in aerosols and the “brightening” does not seem to be due to our efforts with emission regulations:

    http://climategrog.wordpress.com/?attachment_id=902

    The otherwise calm stratosphere shows very clearly that the drop temperautre ( and in opacity ) was and after effect of the major eruptions. 0.5K apparently permanent drop in TLS after each event. The initial warming is due to extra blocking of solar and is well understood, However, the later cooling is usually attributed to GHG blocking upward LWIR.

    This is a result of the usual “linear trend” mentality dominant in climatology. If we draw a straight line through it we could possibly make such an erroneous attribution, yet here it is clear that there is no ‘linear trend’ but two events causing a drop.

    The most obvious explanation being that the processes that flush out volcanic aerosols also remove a lot of anthopogenic pollution aerosols.

    What gets blocked in stratosphere does not make it into the lower climate system, and vice versa. So the effect on the troposphere will be the inverse of this: initial cooling followed by a permanent warming shift.

    The ironic flip side is that despite the “volcanic winter” concept that has been drummed into popular culture ( and climate orthodoxy ) since the 1970s, the long term effect of ( at least the last two ) major eruptions has been a _warming_ ‘forcing’ on the troposphere.

  19. There is plenty to be cautious about when using the SST data set you chose. The errors in the raw data and attempts to reduce them are significant. I loved the part about the shuffled decks. Made me laugh out loud! I know this form of data entry quite well and have spent many hours removing chads before putting the punched cards into the machine that “read” the cards and translated that information onto very floppy indeed large square disks.

    http://www.metoffice.gov.uk/hadobs/hadsst3/description.html

  20. An active solar cycle causes the stratosphere to warm and expand as the ozone layer becomes more active. It is at least plausible to me that this change in the temperature profile of the atmosphere results in a condition in some ways similar to a temperature inversion which would suppress convection and result in warming over and above that attributable to TSI alone. Another way of looking at it is that the change in temperature profile raises the effective emissions height and this in turn raises surface temperatures.

  21. As the article in above post says past history shows us that (PROLONGED) minimum solar conditions have always corresponded with lower global surface temperatures. Data does not lie.

    I am still waiting for someone to produce data that shows this fact not to be true.

  22. Pamela Gray says:
    July 26, 2014 at 7:55 am

    Ocean heat data is an important topic in this discussion. Satellite data samples only the ocean’s skin. Therefore you may get the wrong impression that heat was “added” from above when in reality it was already there but just shifted to the surface. Previous to satellite data, surface heat was actually not surface heat but below surface heat. So be cautious in your use of data that leads you to conclude supposed added heat. That may not be the case.

    http://podaac.jpl.nasa.gov/SeaSurfaceTemperature

    ————————————————————-
    You raise a very important point, but it is the variation with the solar cycle that lets us determine that there is a larger variable flux. If the long term variations that I used to determine an average thermal diffusivity were produced in part by deeper ocean convection, that would produce error in my calculations. But there are other ways of determining diffusivities, including by direct measurement, that give me some confidence in the number I obtained. I don’t think that 1 cm^2/s is likely to be in error by as much as a factor of two.

  23. http://climategrog.wordpress.com/?attachment_id=981

    Applying a simple relaxation response to SSN ( as a general proxy of solar variabilty ) does seem to match most of the interdecadal changes in SST.

    The ~decadal variation seems to be more likely of lunar origin than solar. This explains why SSN seems to sometime being phase but then drifts out, finally being in anti-phase before drifting back.

    There is a notable divergence to the relaxation curve starting just before 1990. Which brings us back the aerosol changes:

    http://climategrog.wordpress.com/?attachment_id=902

  24. Firstly for FT part, in looking a spectral analysis of SST , basin by basin, I found some odd changes were introduced by the Hadley processing around the decadal scale. Here is one example:

    The probably lunar periodicity of 9.04 years gets attenuated and somewhat shifted ( this probably corresponding to Scaffeta’s 9.1+/-0.1 and recent BEST european land temps ) .

    I don’t know which is “correct” but until someone at Hadley does some QA on the effects of their magic on the frequency spectrum, I’ll stick with ICOADS, at least for post WWII period.

    Sulphates seem to be in the news this week, and perhaps about time. However, the cause of the reduction in aerosols and the “brightening” does not seem to be due to our efforts with emission regulations:

    http://climategrog.wordpress.com/?attachment_id=902

    The otherwise calm stratosphere shows very clearly that the drop temperautre ( and in opacity ) was and after effect of the major eruptions. 0.5K apparently permanent drop in TLS after each event. The initial warming is due to extra blocking of solar and is well understood, However, the later cooling is usually attributed to GHG blocking upward LWIR.

    This is a result of the usual “linear trend” mentality dominant in climatology. If we draw a straight line through it we could possibly make such an erroneous attribution, yet here it is clear that there is no ‘linear trend’ but two events causing a drop.

    The most obvious explanation being that the processes that flush out volcanic aerosols also remove a lot of anthopogenic pollution aerosols.

    What gets blocked in stratosphere does not make it into the lower climate system, and vice versa. So the effect on the troposphere will be the inverse of this: initial cooling followed by a permanent warming shift.

    The ironic flip side is that despite the “volcanic winter” concept that has been drummed into popular culture ( and climate orthodoxy ) since the 1970s, the long term effect of ( at least the last two ) major eruptions has been a _warming_ ‘forcing’ on the troposphere.

  25. http://climategrog.wordpress.com/?attachment_id=981

    Applying a simple relaxation response to SSN ( as a general proxy of solar variabilty ) does seem to match most of the interdecadal changes in SST.

    The ~decadal variation seems to be more likely of lunar origin than solar. This explains why SSN seems to sometime being phase but then drifts out, finally being in anti-phase before drifting back.

    There is a notable divergence to the relaxation curve starting just before 1990. Which brings us back the aerosol changes:

    http://climategrog.wordpress.com/?attachment_id=902

  26. The venerable punch care.

    http://en.wikipedia.org/wiki/Keypunch

    Notice the 8″ floppy disk. It’s equally floppy case was square on the outside.

    http://en.wikipedia.org/wiki/Floppy_disk

    Those were the days. At the old Portland VA hospital where most of my early work was done, the only room that was air conditioned was the computer room in the basement. Fortunately the audiology test lab was also in the basement. The poor vets suffered in the unvented heat in the various wards.

  27. You state the “average” was subtracted from your SST data set. What kind of averaging calculation did you use and how was it subtracted from the data set? Glad to see you did not use a box car smoothing function. However, I would not use one on the SSN either. Why? You destroy any abilities to at least start to determine cause and effect.

    We have had this discussion before.

  28. I calculated the change in SW entering the troposphere after Mt. Pinatubo settled to be 1.8 W;m2 in the tropics ( 20S-20N ).

    http://climategrog.wordpress.com/?attachment_id=955

    Inferring from the TLS plot, a similar magnitude effect from El Chichon, makes a change of 3.6 W/m2.

    The ERBE data was less continuous outside the tropics and I have not done the same calculation. I would expect a notable difference in climate response outside the tropics.

    Once averaged over 24h and the rest of the surface, this figure looks sufficient to account for most of the late 20th c warming.

  29. Pamela Gray says:
    July 26, 2014 at 8:45 am

    You state the “average” was subtracted from your SST data set. What kind of averaging calculation did you use and how was it subtracted from the data set? Glad to see you did not use a box car smoothing function. However, I would not use one on the SSN either. Why? You destroy any abilities to at least start to determine cause and effect.

    We have had this discussion before.
    —————————————————————-
    I just obtained an overall arithmetic average of SST for the 60 year period and subtracted that off month by month. I deliberately did not use any apodizing function even though that would suppress the side lobes. I just wanted something comparable to what Willis had done. In addition, there are so few cycles in this short record that apodizing might suppress a lot of the signal being sought. In the case of the 400 yr record that Willis analyzed, apodization would definitely help in revealing any signals present. Some graphs of the effects to be expected can be found here:

    http://www.shimadzu.com/an/ftir/support/tips/letter15/apodization.html

  30. The SST scaling indicates a change of approximately 0.1 K after each event, compared to 0.5K drop in TLS.

    0.2K in two decades is 1K/century. This could account for just about all the late 20th c. warming that was causing all the panic and also explains the lack of warming since.

    The additional SW input was showing no sign of reverting by the end of the ERBE data circa 2000, but the increase in SST seems to have equilibrated about five years after the postive forcing change around 1995.

  31. Bones: ” In addition, there are so few cycles in this short record that apodizing might suppress a lot of the signal being sought.”

    I would tend to use dT/dt to remove the trend and an extended cosine window (apodiser) fn. that if flat for 80% and a cosine taper at the 10% on each end.

  32. Would it also be accurate to say that Figure 1 casts some doubt on the idea that there is a recent history heat buildup? The clipping of the high end looks at a casual glance to be saying that there is limiting mechanism in play… whether it be the length of the year or the hand of God is not addressed but the max level is very uniform.

  33. We have had contributors noting that TSI into the tropical ocean varies too little to be responsible for causing warm spells such as the MWP and the recent late 20th century warming. We have also had it pointed out that cloud production by the tropical ocean provides negative feedback that “caps” its temperature. It has also been noted that ocean circulation transports water warmed in the tropics poleward where it is cooled by various heat loss processes.

    It has also been noted that solar UV output varies much more over the solar cycle than TSI, and that this variance greatly affects the temperature of the upper atmosphere via the ozone layer.
    At http://science.nasa.gov/science-news/science-at-nasa/2010/15jul_thermosphere/ it is noted that:

    “When carbon dioxide gets into the thermosphere, it acts as a coolant, shedding heat via infrared radiation. It is widely-known that CO2 levels have been increasing in Earth’s atmosphere. Extra CO2 in the thermosphere could have magnified the cooling action of solar minimum.”

    It appears that the sun’s warming effect upon the tropical oceans is very steady, but that its warming effect upon the polar atmosphere varies greatly. During periods of lesser solar activity the polar atmosphere cools, allowing greater loss of heat from the polar oceans. Increased cooling results in lower ocean temperatures. Increased CO2 in the upper atmosphere contributes to the atmosphere’s cooling effect upon polar oceans during lowered solar activity.

    The long term effect would be that warm periods are not the result of increased solar activity, but that cool periods such as the LIA and Dark Age cool period result from lapses in solar UV (and solar wind) production.

    SR

  34. Jim Hodgen says:
    July 26, 2014 at 9:16 am

    Would it also be accurate to say that Figure 1 casts some doubt on the idea that there is a recent history heat buildup? The clipping of the high end looks at a casual glance to be saying that there is limiting mechanism in play… whether it be the length of the year or the hand of God is not addressed but the max level is very uniform.
    ——————————————————————————-
    Figure 1 is just showing what is left after subtracting off a wiggly cubic. The full, unaltered data set can be viewed at the woodfortrees link that I provided. Temperatures were tending to level off in thise century and also the heat content in Figure 5 was doing the same.

  35. Pamela Gray says:
    July 26, 2014 at 7:55 am
    ….

    http://podaac.jpl.nasa.gov/SeaSurfaceTemperature

    ………….
    “The first automated method of gathering sst was by measuring water flowing through the input ports of ocean faring ships. While this method obtained a significant quantity of useful SST data there were some shortcomings. The depth of the input ports of different ships can vary greatly from ship to ship. In a stratified ocean these different depths can have different temperatures. This method also resulted in rigorous sampling along major shipping routes but a dearth of information about the vast majority of the world’s oceans.”
    ///////////////////////////

    I have studied many hundreds of thousands, quite possibly millions of entries in ship’s logs (and weather routing agencies) regarding weather and sea state (including ocean temperature).

    I have repeatably made this point that ship’s do not measure SST. The depth at which a ship draws water (from which the temperature is ascertained) varies greatly on the size, design and configuration of the vessel, as well as to whether it is sailing in ballast, fully laden or somewhere in between. Additionally, it will depend upon how the vessel is trimmed (usally trimmed to the stern but this could be 75cms to 3 m, or more). Even during the course of the voyage, the draft of the ship will alter (and hence the depth at which sea water is drawn) because of the consumption of stores (particularly bunkers from the double bottom), and possibly due to inherent changes in the cargo that is being carried (some cargos will tend to dry, some will evaporate light fractions). It is a constantly changing goal post.

    For the main part, vessel will typically draw water from a depth of 2 to 17 metres, perhaps somewhere between 4 to 10 metres being most common. That is a very big range.

    Further, ships are commercial assets and there may be commercial pressures that may encourage less than accurate record keeping. Weather conditions (including swell and current) may be exagerated to conceal a problem with the vessel’s performance.

    Sea water temperature may be under stated or overstated. For example, a vessel’s engine may have a cooling problem, so inlet water temerature may be recorded slightly high. A vessel may be trading in tropical waters and her antifouling coating is suspect, again higher temperatures may be recorded so as to expallain the build up of marine growth and bottom fouling.

    On the other hand, a vessel may be carrying a heated cargo. A heated cargo requires bunkers to be consumed for heating the cargo at some stage of the voyage. These cargoes are loaded ‘hot’ allowed to cool during the voyage (but not to fall below a certain minimum temperature), and then heated in preperation for discharge. It may be advantageous for the ship to under record sea temperatures so that it appears that the cargo is cooling quicker than it really is and therefore requires heating earlier and for longer, for which service the ship owner gets paid. So if sea water tempertaure is recorded on the low side, the ship owner may be able to claim for several days of bunker heating to the cargo which was not in fact carried out, since the warm ambient water through which the vessel was sailing kept the cargo warmer for longer.

    If you look at vessels plying the same route, say 50 nautical miles apart, the declared sea temperatures can be quite different. Some of this might be due to natural variation, particularly the extent of currents, some might be due to the differences in design and trimming of the two vessels, but some of the differences may be due to commercial influence.

    Now of course, I am not suggesting that every shipowner engages in such practice. Of course they do not, but commercial influence is a fact of life when quite substantial sums of money are involved.

    The nub of it is that the SST derived from ship’s should be deemed to carry extensive margins of error, and that prior to ARGO there is no reliable data on ocean temperatures.

    Further, it appears that when the latest adjustments were made to the ocean temperature data (HADSST3), they applied a decreasing temperature adjustment (you see this also with the land records, old data is adjusted downwards) because they considered there was a warming bias in the temperatures recorded by ships (an assumption based upon the premise that water is being heated by the pipework – which is false given the speed of flow of water through the engine), whereas the old data from ship’s temp records should be adjusted upwards to reflect the fact that ships are sampling not SST but rather ocean temperature at 4 to 10 metre depth below SST(as i say the range at which sampling is made is much wider). The warming bias caused by the water being heated in the inlet mainifold is an order of maginitude less than the cooling bias caused by the fact that the sea water is being drawn at depth and is not SST.

    Data on ocean temps should be viewed with extreme caution. Prior to ARGO there is no good quality data. There are ssues with ARGO, apart from its short duration and sparce coverage, namely that when it came on stream, a correction was made to remove buoys which were showing ocean cooling (see http://earthobservatory.nasa.gov/Features/OceanCooling/page1.php ), and no studies have been carried out to ascertain whether there may be an inherent in built temperature due to the free floating natuire of the buoys that drift with the currents, which currents themselves have their own temperature profiles.

    PS. Perhaps, I should just mention that a ship’s engine does not circulate water like a car through the radiator, but instead continuously draws fresh ocean water and dumps that water as soon as it has passsed through the engine. The volume of water passing through a ship’s engine is quite substantial due to the size of the machinery, and therefore is not significantly heated by the short period of time it spends in the inlet manifold.
    .

  36. A few suggestions that might bear fruit (wish I had time to do this myself):

    1. If there are possible peaks in more than one dataset, or if a dataset can be split into 2 or more portions, then are the phases of the Fourier amplitudes consistent with each other, subject of course to noise perturbations? They would have to be to enable a claim to be made for a solar signal.
    2. The varying lengths of the solar cycles suggests the use of resampling the data to get a consistent number of samples in each cycle, prior to doing a Fourier transform. Problem though is the likely delay(s) between TSI and temp, so maybe worth doing the resampling with a large set of delays and seeing which one works best. Maybe the delay could be estimated first by cross correlation.

  37. I think the missing link could be duration of heating (or cooling) over several solar cycles.

    I think of the solar cycles as periods of magnetic field turmoil causing structural turbulence on the solar surface allowing higher energy emissions as measured by TSI. These have a small heating effect on earth as well as higher UV related reactions such as ozone formation.

    I think the effect of one cycle gets lost within the background noise. However, when we get periods of low activity and thus low TSI across several cycles, this represents many decades without the regular pulse of increased radiation. We have seen such periods associated with cooling in the past.

    I strongly suspect that the latter half of the last century consisted not just high SSN and high TSI, but also an increase in the length of time the earth was receiving increased radiation.

    If we regard the solar cycle as a pulse of warming radiation then the frequency, shape and amplitude are all important since collectively they define the amount of heating during a multidecadal period.

    I assume that the effect of this heating on the oceans is the key factor and this is consistent with these timescales. So we are talking about the extra heat transferred to the oceans during a period of say 100 years with high TSI and lots of cycles compared with 100 years of low TSI and much fewer cycles. I suspect the difference could be significant.

  38. Just to add that if the mechanism involves a build up in which duration of heating is important then the higher temperatures would be expected to peak at the end of the heating period. This could be after a number of active cycles, so there would be a time lag.

  39. bones says:
    July 26, 2014 at 8:32 am
    ////////////////////
    Bones

    The point that Pamela makes (and upon which I expanded) is that prior to ARGO, there is no reliable data on SST.

    Prior to about 1975, data was predominantly collected by buckets. but these were of differing design (some better insulated than others), and there was an unknown time factor that it took for the bucket to be drawn from the top of the ocean and pulled up on board and the a measurement taken etc. HADSST2 had the well known bucket adjustment which was supposed to compensate for that.

    Post about 1975, the data has been predominantly collected by commercial ships, but these ships do not sample SST, but rather sample ocean temperature at a depth of between 4 to 10 metres below SST!!

    HADSST3 has made an adjustment to the latter data, because it assumes that the ship’s data has a warming bias. It assumed that the sea water was being heated slighly by the pipework from the hull aperture through to the water inlet manifold where the temperature sensor is situated. However, the volume of water throughput is large, and there is in practice very little time for the water to be so heated. The adjustment failed to take account of the material fact which is that the water being measured is not SST, but is water drawn from depth (say somewhere between 4 to 10 metres below SST). This latter fact more than offsets any warming bias in the ship’s data. Ship’s data under records SST because the water is drawn at depth; it should be seen as having a cool bias.

    I would not wish to average all the ships out but may be the average depth at which ocean water is drawn is 5 or 6 metres. Water at that depth, is considerably cooler than SST.

    The amount by which the water is cooler because of the depth at which it is drawn, far exceeds the slight warming caused by measuring temperature with sensors at the inlet water manifold. Accordingly, HADSST should have made an adjustment to increase temperature post about 1975 to reflect that the water sampled was water drawn at depth and therefore cooler than SST. However, the adjustment was the very opposite. Far from correcting an error/bias, they have created a bigger one (in the wrong direction).

    Your study is handicapped by the fact that there is no reliable good quality data on SST.

    When you are looking for changes measured in hundredths or even tenths of a degree, it is an impossible task when the errors in the procedures adopted in sampling the temperatures is so great.

    You can never splice different proxy sets together. The old bucket set is one set of data; the improved insulated bucket set, another set of data; the data from commercial ships’ a third different set of data; and finally ARGO a fourth different set of data. None of this data can be spliced to make one composite data set extending for some 60 years or so.

    You could base your study on the commercial ship period, say 1975 to say 2003, but then you would not be looking at SST since this data does not sample SST.

    You could base your study on the ARGO period (say 2003 to date). This does collect data on SST, but the duration of the data set is short. Further, it got off to a bad start as noted in my comment above.

    The bucket method is so fundamentally flawed for detail work, that I would not wish to go near it, but of course, you could have used that data sets.

    In summary, the data is hopeless, there are very wide error bands.

    ,

  40. richard verney says:
    July 26, 2014 at 10:13 am

    bones says:
    July 26, 2014 at 8:32 am
    ////////////////////
    Bones

    The point that Pamela makes (and upon which I expanded) is that prior to ARGO, there is no reliable data on SST. . . .
    ———————-
    I have to agree, however, my purposes here were very limited. First,I merely wanted to show that the SFT method could detect small signals and in comments I have noted that that can be improved upon in ways that might pull them out of the centuries long records that Willis examined. Secondly, I did not want the implication that there was no excess heating to stand unremarked. Shaviv and others have published peer reviewed works that have been ignored for too long.

  41. The arguments associated with Figure 5 (Ocean Heat Content 0-700 m) are weak because the data for OHC prior to 2003 are themselves weak, noisy, undersampled, and biased in their sampling.

    There is an excellent post by Tisdale, ARGO-Era NODC Ocean Heat Content Data (0-700 Meters) Through December 2010(WUWT March 25, 2011), particularly the Animation 1, location of XBT temperature profiles for 250-500m 1979-2003. This animation makes clear that these temperature profiles are so heavily weighted to the submarine patrol areas of the north Pacific and North Atlantic that the southern hemisphere is woefully undersampled.

    The entire anomaly of Figure 5 for the 0-700 m column is about 10*10^22 Joules = 100 ZJ. It takes 27.5 ZJ to raise the 0-2000m water column 0.01 deg C So it takes about 10 ZJ to raise the 0-700 m water column 0.01 deg C. Therefore, the 100 ZJ change in the 0-700 meter column in Figure 5 amount to about 0.10 deg C. With the temperature profiles of the southern hemisphere oceans so undersampled in the pre-ARGO era, I cannot believe we know the temperature anomaly of the worlds 0-700 m oceans an accuracy of less than 0.10 deg C. The error bars pre-ALACE, pre 1992 are larger than the signal.

    So I think in Figure 5, you are searching for parameters to fit what someone else’s theory of what the OHC should be rather that what was accurately measured.

  42. Stephen Rasey says:
    July 26, 2014 at 10:32 am

    The arguments associated with Figure 5 (Ocean Heat Content 0-700 m) are weak because the data for OHC prior to 2003 are themselves weak, noisy, undersampled, and biased in their sampling.

    There is an excellent post by Tisdale, ARGO-Era NODC Ocean Heat Content Data (0-700 Meters) Through December 2010(WUWT March 25, 2011), particularly the Animation 1, location of XBT temperature profiles for 250-500m 1979-2003. This animation makes clear that these temperature profiles are so heavily weighted to the submarine patrol areas of the north Pacific and North Atlantic that the southern hemisphere is woefully undersampled. . . .

    The entire anomaly of Figure 5 for the 0-700 m column is about 10*10^22 Joules = 100 ZJ. It takes 27.5 ZJ to raise the 0-2000m water column 0.01 deg C So it takes about 10 ZJ to raise the 0-700 m water column 0.01 deg C. Therefore, the 100 ZJ change in the 0-700 meter column in Figure 5 amount to about 0.10 deg C. With the temperature profiles of the southern hemisphere oceans so undersampled in the pre-ARGO era, I cannot believe we know the temperature anomaly of the worlds 0-700 m oceans an accuracy of less than 0.10 deg C. The error bars pre-ALACE, pre 1992 are larger than the signal.

    So I think in Figure 5, you are searching for parameters to fit what someone else’s theory of what the OHC should be rather that what was accurately measured.
    ——————————————————————————
    That may be so, but if the temperature and heat data have been inappropriately biased upward, the price that has to be paid is that they have to find a plausible heat source to cause it. Inadequate TSI variation creates a conundrum for the warmistas that makes me smile.

  43. Bones

    Further to my two comments above.

    See http://en.wikipedia.org/wiki/Ocean_temperature#mediaviewer/File:MODIS_and_AIRS_SST_comp_fig2.i.jpg

    This is a typical profile of ocean temperature over depth. Fig (a) is the day time profile, fig (b) the night time profile. In fig (b) one can see the dinurnal response to ocean overturning.

    This profile is typical, but in practice the profile varies from ocean to ocean, no doubt due to a combination of factors such as salinity, cleanliness/pollution, the prevalence of acquatic organisms, the amount of solar received, prevailing currents etc.

    You will note that during the day there is little change in ocean temperature between 1mm and about 4m. But at a depth below 4 metres, ocean temperatures begin to fall rapidly. Of course, ships are sampling ocean temps from water drawn below 4 metres, so they are drawing water from this problem zone.

    But at night, the profile is very very different. You will note that temperatures fall off rapidly as from 1mm below SST.

    So a different correction needs to be made between day and night, to take account of the diurnal ocean overtunring.

    There is aso a further problem thrown into the mix, and that is that the distribution of tonnage does not remain unfirom from year to year. Shipping responds to market conditions. Markets fluctuate and this has an impact on the volume and distribution of ships plying international trade. In one period ships of Panamax design may be favoured, in another it will be Handymax, in another Afromax. You will no doublt be familiar with the trend towards containerisation and how container ships have developed significantly over the years.

    This means that you cannot have an average for the draft of international tonnage since the type of tonnage and its distribution will vary over say 5 year periods. The average draft of ships plying trade 15 years ago, will be different to the average draft of ships plying trade 10 years ago etc. So any adjustment required to reflect that ships sample ocean temps at depths will need to constantly be adjusted as shipping evolves year to year.

    The margins of error in this data set are really very substantial.

    It is the achiles heel of claimate science, that all data sets have issues, and are not fit for purpose. The data sets are constantly being over extrapolated and no one is objective enough to set out the true error bands which are significantly wide on all data sets.

    I applaud your efforts, but you really are handicapped by the data sets from which you are working.

  44. Just a couple of further thoughts on the idea I proposed at 10:02 above.

    I’ve been using SSN as a proxy for TSI because it goes back further and though detection capability will have improved it doesn’t have all the complications of TSI measurement. I suppose I could have used radio flux but that only goes back to 1947. Based on a very crude assessment, the duration of SSN values of 75 and above have been higher during the period 1950-2000 that at any other time since SSN measurements started in 1750.

    The second thought is that the modulation of GCRs by the solar wind is a potential albedo control mechanism as proposed by Svensmark. This albedo effect must also be enhanced by its duration and is therefore the combined effect of several solar cycles will affect the outcome.

    The bottom line of my proposal is that multiple solar cycles of one extreme or the other show up in our climate record. Individual and mixed activity cycles are not noticed.

  45. If I were an alarmist running a ‘model’, trying to ‘associate’ a short term warming observation with a tiny increase of CO2 in the atmosphere, I would have to use positive feedback with a magnitude of about 80. No problem…who objects to this and with what data? However, if I were trying to associate observed variation in TSI with variation of temperature signals on Earth, I might only have to use a positive feedback of about 4…but oh, the objections.

    If I were to use the dT/T = 0.0125% argument I could not show the Earth’s atmosphere expanding enough to knock down satellites. Darn the empirical data.

    Does not the Earths atmosphere expand during a solar maximum? Is the atmosphere not somewhat decentralized during a solar maximum? What is the variation of the decentralization? What is the variation in clarity of the atmosphere as the solar wind varies?

    Seems that the real answer lies in the spectral variation and linkage with atmospheric physics. If I were to focus only on just TSI, it seems like I might be eligible to earn the ‘hobgoblin of little minds’ award.

  46. CORRECTION

    Further to my post at 10:56 am

    In the cited plot, Fig (a) is night time profile, Fig (b) is daytime profile.

    Fig (b) shows the daytime response to the absorption of solar at depth. There is a rapid drop off in temperature as from about 60cm depth. Unfortunately, since this is a profile, there is no scale on the plots, and thus change in absolute values is accordingly not readily apparent.

  47. Schoedinger’s cat: “I strongly suspect that the latter half of the last century consisted not just high SSN and high TSI, but also an increase in the length of time the earth was receiving increased radiation.”

    The logical response to that is the cumulative sum. However, if there is a warming effect there will feedbacks that tend to cause SST to fall back once the deviation ceases. This may most simply be characterised as a relaxation to equilibrium response which leads to an exponential decay.

    The result of such a response can be found by convolution with a suitable decay time constant.

    The result is what I posted above. Apparently know one seemed to get the significance.

    http://climategrog.wordpress.com/?attachment_id=981

  48. Schrodinger’s Cat, you say in your proposal that subtle trends only show up after a long period of time, but one individual strong difference does not show up. How is that possible?

  49. “””””…..bones says:

    July 26, 2014 at 7:08 am

    Leif Svalgaard says:
    July 26, 2014 at 6:40 am
    . . . The standard formula for this is dT/T = (dTSI/TSI)/4, which with an amplitude [=half from min to max] of 0.05% in dTSI/TSI gives dT/T = 0.0125% [of T=299K] = 0.036 C , so the variation of TSI is just what is needed.
    ——————————————–
    Sorry Leif, the TSI variations are at the top of the atmosphere and that is where T must be taken as well…….””””””

    Seems to me that Leif’s calculation is simply the small delta version of the Stefan-Boltzmann 4th power calculation, that presumes black body circumstances. And BB radiation laws tell us that the BB limit is the worst case.

    So I don’t know what your gripe with Leif’s number is.

    SB gives the worst case expectation, in the absence of positive or negative feedback interferences.

    The fact that the global Temperature seems to NOT reflect even that small a TSI signal, suggests that a substantial negative feedback is at work.

    Your claim that it matters where you take the signal, might be quite true. That simply confirms that other processes besides S-B are in play.

    Dr. S’s calculation and figure are correct.

    I don’t know why this is a problem; that this or that disturbance (TSI variation, or CO2 abundance changes or whatever), are occurring; but are not being manifested in climate changes.

    Negative feedback cares not a jot, what the source of a perturbational disturbance is. Feedback (negative) fixes anything and everything; from Aerosols to Zspots, including TSI.

  50. “This could be after a number of active cycles, so there would be a time lag.”

    There is , as I showed in the lagged-correlation plot.
    Removing the circa 10y ripple the long term correlation would peak at around 15y.

  51. richard verney says:
    July 26, 2014 at 10:13 am

    bones says:
    July 26, 2014 at 8:32 am

    I took a detailed look at Hadley SST “corrections” over at Judith Curry’s a year or two back.

    http://judithcurry.com/2012/03/15/on-the-adjustments-to-the-hadsst3-data-set-2

    That covers many of the points raised here. It also compared the FFT of earlier and later SST and how the “bias correction” messed with frequency spectrum. A point I have also linked to here concerning the 9y lunar peak.

  52. richard verney says:
    July 26, 2014 at 9:28 am

    Now of course, I am not suggesting that every shipowner engages in such practice. Of course they do not, but commercial influence is a fact of life when quite substantial sums of money are involved.

    I was on a Naval Nuke ‘Nam era. Gun decking the numbers if the watch stander was careless was not unknown. And it was covered up by all concerned.

  53. The volume of water passing through a ship’s engine is quite substantial due to the size of the machinery, and therefore is not significantly heated by the short period of time it spends in the inlet manifold.

    The heating is strictly from the delta P (pressure) and flow and some pipe friction. But both of those numbers are small. Heat transfer from the ship’s interior is minimal given flow rates even at slow cruising speeds. Ship power required goes up as the cube of the speed through the water. And the flow goes up at the about same rate for the cooling water in order to keep the delta T across the condenser as low as possible. Condenser temperature makes a huge difference in steam powered efficiency.

  54. I might also mention that some years back Climate Audit looked at SST measurements and covered a lot of the same caveats discussed here.

  55. Pamela Gray says:
    July 26, 2014 at 10:54 am

    The increase in Ocean heat has been calculated to be measurable but not significant. See the following post Judith Curry likes as well. How does this increase compare to the present thesis being considered here?

    http://motls.blogspot.com/2013/09/ocean-heat-content-relentless-but.html

    ————————————————————-
    I used the Levitus et al. data as posted on the NOAA web site. My best fit to the heat content data yielded about 16% more calculated heat absorbed than Lubos obtained. The way Lubos calculated the temperature change involved an integration of the temperature gradient over the depth which he never completed in detail. Nevertheless, he computed an average rate of required heating that he said was less than 0.5 watt/m^2. I started at zero in 1965 and ramped it up linearly for 45 years. My average rate would be 0.69 watt/m^2. Because of differences in the way our calculations were done, I don’t think that the results are completely comparable. When all is said and done, my calculations matched both the heat content changes to 700 meters and the surface temperatures. I might go back and average the temperature changes over the 700 meters, but I would guess that I would get a smaller mean increase because the temperature changes are much larger at the surface than at greater depths where most of the mass is located.

  56. Pamela Gray says:
    July 26, 2014 at 7:38 am
    However, over very long time spans we might have a convincing argument related to a building imbalance (as in more heat going in than going out) leading to long noisy cycles of warmth.
    =========================================================================
    Pamela, I had noticed when looking at one of Dr Svalgaard,s solar charts that there is a distinct change in the length of time at solar minimum. In regards to that I had similar thoughts to what you express above. The chart shows the last minimum as having a 4+/- year period. The prior 6 minima have a period at minimum of 2+/- years. The 6 minima prior to that all have 4 +/- years at minimum. The chart starts in 1875. I would love to see that chart extended back a few more cycles to see if the minimum reverts back to 2+/- years. Cycle 17 is the pivot point between 4+/- and 2 +/- years. Is this two iterations of a 6 cycle pattern? Cycle 17 is the first above average cycle, which is then followed by the 2 strongest cycles on the 139 year chart. My first impression 6 years ago when I first looked at the ssn charts available was “why wouldn’t that be considered as the main component of the current warming?”. I made comments to that effect at newsvine. My next thought was “look at how the solar cycles appear to fit with the Pacific Northwest 9 year flood pattern. A pattern which shifted in the mid 1970s and now ranges around 11+ years, to almost 12 years. That set the hook and I have been wriggling at the end of the line ever since.

    Anyhow, my original thought on the difference of a solar minimum spending less time at minimum was “would that lead to an additional accumulation in the energy budget of Earth, and thus the warming which the records show?”. Is the reversion back to a 4+/- base in the last minimum the reason that we now see a slight cooling?

  57. A terrific chart on data coverage for Ocean Heat Content from
    Judith Curry, Ocean Heat Content Uncertainties, Jan. 21, 2014.

    http://curryja.files.wordpress.com/2014/01/presentation6.jpg?w=1500&h=1158

    Note the 0-700 meter curve shows. 20% global coverage in 1990, 40-30% from 1995-2003, and then rises to 70% with the advent of Argo.

    Further note the definition of “coverage”: At least one temperature reading in each 1 x 1 deg bin per year, like measuring January, April, July, or October makes no difference when looking of 0.01 deg C changes to the world’s oceans. I think the source is Levitus 2012.

  58. My speculation is that Earth’s own atmospheric variations undergoing oscillations that put more or less clouds in the sky over long periods of time determines heat build up or loss from the greatest store of all, the oceans in the equatorial band, and in particular the Pacific equatorial band. Solar variations at sea surface would be completely buried in the much more noisy and oscillating intrinsic factors that let in or keep out solar heating.

  59. M Simon says:
    I might also mention that some years back Climate Audit looked at SST measurements and covered a lot of the same caveats discussed here.

    ===
    That was in relation to HadSST2 which was based on Folland’s folly: a 0.5 deg drop inserted in 1946. McIntyre was heavily critical of this kludge and it seems to have been heeded to some extent.

    HadSST3 came out with a whole new raft of “corrections” in a jolly array of 100 permutations and the median of the 100 frigs which is what is usually taken to be “HadSST3″

    This new version basically phased the same 0.5 C in over about 25 years so this it did not look so obviously wrong. The excuse being Folland was “right for the wrong reason”. In order to achieve the nice smooth slide in they ignored the ships records of what was engine-room intake or buckets and allocated their bucket and ERI bias “corrections” on a random basis to acheive what they considered to be the “correct” proportion of ERI vs buckets in each grid cell for a particular year.

    ie. they ignored the written record and made it up as they saw fit.

    I discussed all this in detail in the post at Curry’s blog, that I linked above.

  60. george e. smith says:
    July 26, 2014 at 11:39 am

    . . . .Seems to me that Leif’s calculation is simply the small delta version of the Stefan-Boltzmann 4th power calculation, that presumes black body circumstances. And BB radiation laws tell us that the BB limit is the worst case. So I don’t know what your gripe with Leif’s number is.
    ————————————————–
    While Leif’s calculations are exact, they would apply only at the unit optical depth height in the atmosphere from which outgoing infrared exits at about 255 K and not at the sea surface. And only then if nothing more than average TSI plus its small variations over the solar cycle were passing on down to sea level.

    Consider a planet in a solar system with a rock solid constant TSI, but unfortunately, the planet’s atmosphere is infested with invisible cloud weevils that cyclically eat holes in the cloud cover. If the holes are large enough they can be detected by the variations of sea surface temperatures that they cause. The holes periodically let more of the steady TSI reach the surface. Using orbiting satellites to look for incoming TSI variations would yield nothing in this case. Either surface temperature measurements or satellite measurements of outgoing thermal infrared should show cyclical oscillations even though incoming TSI at the top of the atmosphere shows none.

    Since earth shows such surface temperature oscillations, Leif needs some outgoing IR observations to prove that we do not have cloud weevils. Saying that they don’t exist on the basis of an inapplicable calculation is not good enough.

  61. M Simon , you talk of “gun decking” whatever that means, and making the data up if no one was watching. What do you think is the likelihood of an engine-room reading being logged as bucket and vice-versa?

  62. Pamela Gray says: July 26, 2014 at 11:39 am

    Schrodinger’s Cat, you say in your proposal that subtle trends only show up after a long period of time, but one individual strong difference does not show up. How is that possible?

    I’m saying that one or two very active cycles may not show up but a whole string of them do. Think of each very active cycle as a heating pulse. A string of them would cause heating.

    When the solar activity is low, the heating pulses are very weak with a longer gap between peaks. Also, they allow GCRs and more albedo. A string of them causes cooling.

  63. Bart says:
    July 26, 2014 at 11:50 am

    Some info on the “SFT“.
    ———————————-
    Thank you!

  64. Typical low-pass filters affect earlier data as well as later data which can be acceptable but is not physically possible

    A relaxation response, as a weighted integral, has low pass properties but also introduces a lag as can be seen here compared to low-pass and lagged SSN.

    http://climategrog.wordpress.com/?attachment_id=998

    I think this possibly what David Evans’ has picked and incorrectly interpreted as “notch-delay”. Finding a notch filter in nature is not easy. IMO he in misinterpreting his FT and is really seeing the presence of low-pass filtering, not a notch filter. The lag he is then having to invent to align the data is the lag that is created by a relaxation response.

    The above plot shows a 20y relaxation is quite similar to an 11y low-pass with an 11y lag.

    It is unlikely that the system can be accurately modelled with a single time constant response due to multiple ocean depths and other surface effects, each with a different response time. Some faster feedbacks are likely to be further attenuating the 11y periods.

    However, for such a simplistic model it seems to catch general form of SST.

    Here I show that tropical SST is very insensitive to changes in radiative forcing , this also means there will be little 11y signal visible. The cumulative effect may be mainly from SW component that penetrates deeper and bypasses the surface feedback mechanisms like evaporation and convection.

    http://climategrog.wordpress.com/?attachment_id=884

  65. Schrodinger’s Cat says:
    July 26, 2014 at 1:14 pm
    Think of each very active cycle as a heating pulse. A string of them would cause heating.
    ========================================================================
    My thoughts have been similar in that regard.

  66. No need to torture data to extract solar input.
    I used NOAA global Land&Ocean data (see the other thread) and calculated its spectrum.
    It is clear that the 11 years Sunspot cycle isn’t there, but the Hale cycle shows as the most prominent .
    But before the ‘mechanism’ questions comes up,
    Miss Gray, I forgot to bring my homework notebook, but it does say something about interaction between the Arctic summer atmospheric pressure and the Himalayan monsoons.

  67. Thanks for a very interesting analysis, Dr. Stan. I just took a look at the dataset in question, and I fear I can’t reproduce your results. I find no significant signal of the type that you show. Here is my result:

    I suspect the problem may be that you have subtracted a cubic polynomial from the data, which is a technique fraught with problems. If not, I’m not sure what you did … my analysis shows, for example that there is a 5-year cycle nearly as large as the 9-year cycle, and a 3.8 year cycle that is larger than the nine year cycle. In addition, your graph is much smoother and less detailed than mine. Again, I’m not sure why.

    As a test, I ran a cross-correlation between sea surface temperature and sunspot numbers for the same period. Here’s that result:

    Lag is in years, with positive lag meaning SST lags sunspots. Unless you believe that somehow the warming from the excess sunlight during the stronger half of the sunspot cycles is magically delayed between ten and twelve years, I’m not seeing anything there but random results. It’s a recurring problem with looking at something with a strong signal such as the sunspot data—you get an ~11-year cycle with almost any random red noise dataset you choose to compare it against.

    Next, as a further check on the results, I looked at the period 1900-1950. There is no strong cycle of anything around 11 years in that earlier HadSST3 data, but there is a cycle at 14 years, which is obviously not solar driven, and no cycle at 9 years as in my results above … and the cross correlation is no better (although different) from the one shown above.

    Overall, I’d say you are looking at artifacts, but I’m willing to be convinced otherwise …

    Finally, the HadSST3 data is the average of 100 realizations of a computer model of the sea surface temperatures using slightly different assumptions. Such a procedure always makes me a bit nervous, particularly when the cycles are quite small. Details on the realizations are here.

    Best regards, and thanks again for the work. I do love to see someone run the numbers themselves.

    w.

  68. So Willis, are you connecting with the internet on the ship or are you still landlocked?

  69. My bad. I forgot you are attending a physicians’ conference related to emergency stuff.

  70. bones says:
    July 26, 2014 at 1:15 pm

    Bart says:
    July 26, 2014 at 11:50 am

    Some info on the “SFT“.
    ———————————-
    Thank you!

    See “The Slow Fourier Transform“. In a subsequent post, tamino identified what I’d done as:

    tamino says:
    May 26, 2014 at 7:57 pm

    The method you describe is very clever. It’s also known (in the astronomical literature at least) as the Date-Compensated Discrete Fourier Transform, or DCDFT (Ferraz-Mello, S. 1981, Astron. J., 86, 619). It’s related to the more popular (but in my opinion less effective) Lomb-Scargle modified periodogram (Scargle, J. 1982, Astrophys. J., 263, 835). You have also chosen to plot the *amplitude* spectrum rather than the *power* spectrum, a habit which is uncommon but certainly valid.

    and I see no reason to doubt him.

    It’s a great technique, because it ignores missing data and can accept totally non-regular data.

    I’ve previously posted the R code for the functions, it’s here.

    w.

  71. Pamela Gray says:
    July 26, 2014 at 1:57 pm

    My bad. I forgot you are attending a physicians’ conference related to emergency stuff.

    Indeed, I’m in Knoxville, Tennessee.

    w.

  72. The period 1950-2000 had a series of cycles which were high in SSN and highest in the duration of SSN>75 compared with all SSN cycles that were logged since 1750. The average SSN over that period was about 52.

    It is probably fair to use SSN as a proxy for TSI since the turbulence caused by the magnetic field generates the higher energy radiation.

    Long periods of low solar activity are associated with cooling, as you know. All I am claiming is that the solar effect on climate is multi-cycle and therefore multi-decadal and related to cumulative heating or the lack of it. A mixture does not register apart from possibly a small net effect.

  73. Willis Eschenbach says:
    July 26, 2014 at 1:51 pm

    Thanks for a very interesting analysis, Dr. Stan. I just took a look at the dataset in question, and I fear I can’t reproduce your results. I find no significant signal of the type that you show. Here is my result:

    I suspect the problem may be that you have subtracted a cubic polynomial from the data, which is a technique fraught with problems. If not, I’m not sure what you did … my analysis shows, for example that there is a 5-year cycle nearly as large as the 9-year cycle, and a 3.8 year cycle that is larger than the nine year cycle. In addition, your graph is much smoother and less detailed than mine. Again, I’m not sure why.
    —————————————————–
    Willis, I just computed an arithmetic average SST from the monthly data, then subtracted it from the monthly values. I did not fit the residuals from the cubic fit. I only looked at the cubic fit residuals to get an idea of the size of the random variations. I suspect that the reason that my graph looks different might be that my least squares fits to sine curves with arbitrary phase were done for 0.2 year period increments. In addition, I did not use a log scale for periods on the graph. What I did was least squares fits to monthly data that I downloaded from woodfortrees.
    sst = avg + A sin(2 pi t/P) + B cos(2 pi t/P)
    and took the amplitude to be sqrt(A*A + B*B)
    I used the entire data interval from Jan 1954 – May 2014 for each tested period, P, and I have just reported what I got. I agree that there is a significant 5 year cycle. It showed up clearly a while back when I tried to use Roy Spencer’s technique to look for a signal for the last four solar cycles.

    It would not surprise me to find a delayed correlation such as the one found by Solheim et al., in which temperature trends correlated with solar activity and length of solar cycle delayed by a cycle period. On that basis, they predicted cooling for Norway during solar cycle 24 due to the short cycle 23.

    It may be that I am finding artifacts. I will examine this point in some future calculations with your SFT. It is a pretty neat tool. I will probably use some 3 year averaging to suppress short period noise and some apodization to suppress side lobes and see just how small s/n ratios can still yield valid detections. Will also look at some of the long temperature records. It beats being outdoors in the heat here.

  74. Thanks for the links, Greg. I was thinking of using something more like a gaussian filter. Having taught optics many times, I am well aware of ways that the sinc function can bite you.

  75. “It would not surprise me to find a delayed correlation such as the one found by Solheim et al., in which temperature trends correlated with solar activity and length of solar cycle delayed by a cycle period. On that basis, they predicted cooling for Norway during solar cycle 24 due to the short cycle 23.”

    This kind of approach always seems rather contrived to me and success rather intermittent. Perhaps they are picking up a real effect of which the length is an indicator.

    The minimum point is the cross-over between the tail of the last cycle and the rise of the new one. If the new ( current ) cycle is weak, it will take longer to pick up and the min date will be later.

    I have already posted the lag-correlation showing about one cycle lag and proposed an obvious relaxation response as being the cause of the lag.

  76. Greg Goodman says:
    July 26, 2014 at 3:12 pm

    . . . You may find some useful alternatives here, as well as a script to calculate a relaxation response.

    http://climategrog.wordpress.com/category/scripts/

    ————————————–
    Right on! An awk script! I used to use awk a lot and I still have a functional DOS version. I may be the last dinosaur, but I will take good tools where I can find them. Thanks.

  77. I rather thought I’d debunked the SFT by running a simple sine wave through it and noticing sidelobes and other anomalies. Please just use a transform that’s been tested and validated for nearly a century – the discrete fourier transform, or its optimized version, the FFT.

    http://wattsupwiththat.com/2014/05/26/well-color-me-gobsmacked/

    Any signal transform should have:

    (1) sine waves run through it
    (2) Impulse function run through it
    (3) step function run through it
    (4) white noise run through it.

    And verify the results are in agreement with the well-known spectral properites of those types of signals.

    The SFT does not produce the expected output for a sine wave. This invalidates most of the analysis above.

    Notes:

    which comes from a file designed to be read by Willis’s SFT code:

    https://www.dropbox.com/s/ieglk36hnxa430f/test-sin.csv

    Source code: https://www.dropbox.com/sh/5wh9dbja6x37nfa/AADhfZFr6JXWF2vCDAj407Hoa

  78. “…they predicted cooling for Norway during solar cycle 24 due to the short cycle 23.”

    If there is a long term solar effect, it should have been dropping since before 1990 according to the relaxation idea but has been propped up by the volcanic effect. However, that current cycle is so weak ( as picked up by the late minimum ) that I think it’s going to start biting soon, Unless AGW saves us.

    If there is not some clear cooling in the next 5 years, I may well be convinced that there is significant AGW.

  79. “Right on! An awk script! I used to use awk a lot and I still have a functional DOS version. I may be the last dinosaur, but I will take good tools where I can find them. Thanks.”

    Second last ;)

    There’s a gaussian in there too. The Lanczos has a nice short transition band but has rather a long kernel so you loose quite a bit at each end. If that is not a problem its a very good filter.

  80. Peter Sable:

    In what way is that unexpected? What does FFT produce on that same sample?

  81. Cross-correlation of tropical and ex-tropical Indian Ocean shows similar 9.3y ( anti-phase ) and 22y in-phase, with weaker ~11y. Similarly very strong 3.8y.

    http://climategrog.wordpress.com/?attachment_id=779

    Most SST records seem to show ~9y lunar being stronger than the 11y solar, and comparable to 22y solar. Failing to acknowledge the significant lunar signal has been the cause of many problems for those trying to detect 11y solar.

  82. Schrodinger’s Cat says:
    July 26, 2014 at 10:02 am

    “I think the missing link could be duration of heating (or cooling) over several solar cycles.”

    That idea is the basis for my solar model, based on HADSST3, where solar input vs HadSST3 reveals the idea you presented, as you explained well too. You and everyone else talking about this, the author of this post, many others, are converging on the truth. As SC24 goes by with more and more low SSN days, when the solar “mini-max peak” is finally over and we’re really into a long solar min, the OHC will give it up and SSTs will drop, as HadSST3 depicts every solar cycle min, and we will bear witness together as it happens again. This time the warmists will have nowhere to hide, nowhere to run, no way out except to abandon their ship of foolishness.

    I really appreciate Stan Robertson for going to such great lengths to prove this relationship exists.

  83. JoNova territorial hissy fit yet?

    One guy added NOTCH.

    Weirdo.

    Wiggle matching is the sound of waves on a beach. Everything just fits!

    Yeah, man, just look at that sky.

  84. vukcevic says:
    July 26, 2014 at 1:43 pm
    ============================================
    Nice chart, thanks for sharing. I should have ended my last comment with ” will the next 5 solar minimums all have a larger ‘footprint’ at minimum? Meaning will we have 5 solar cycles worth of cooler climate? Then there is that potential for the extra ingredient of a deeper than normal minimum coming from the right conjunction of events, ie…solar down, oceans cool, and polar changes as main contributors.

  85. Paul Homewood is right. You need to start before 1998 or after 2000 to avoid the Nino/Nina whipsaw. Anything in between in a cherrypick. (Anthony is using a pro-warming cherrypick startpoint.)

  86. Thanks Stan and all for a terrific symposium on the subject. This thread reads like roundtable give and take with exchanges of thoughts and criticisms – cooperative offerings of data files, codes, tweaks and alternatives to analytical approaches in a polite gathering of deeply knowledgeable proponents . Even Willis shows up on cue to contribute. I’ve known for a long time Pamela is smart, but I’m impressed with the dimensions of her knowledge and ideas on this gritty specialized subject (my fondness for redheads has nothing to do with this opinion!). This is how science would be taught in a perfect world. A classy piece of work this thread.

  87. Thanks for the kind words Gary. Weather and climate is my lifelong hobby and I am such a nerd about it. But I am not nearly as schooled as other professional and amateur informative scientists who contribute posts and comments here at WUWT. The honor goes to them as I am only a grasshopper. I have spent pleasurable hours and hours learning a great deal from the likes of Anth***, Willis, Bob Tisdale, and Leif.

  88. Several researchers, including Nir Shaviv (2008), Roy Spencer (see http://www.drroyspencer.com/2010/06/low-climate-sensitivity-estimated-from-the-11-year-cycle-in-total-solar-irradiance/) and Zhou & Tung (2010) have found that ocean surface temperatures oscillate with an amplitude of about 0.04 – 0.05 oC during a solar cycle.

    As seen in Roy Spencer’s article, his first graph “Estimating Climate Sensitivity from the Solar Cycle in Total Solar Irradiance” lists as source a Judith Lean TSI reconstruction. In the text this is described as using the TSI variations from a Tung & Camp paper he was referred to, href=”http://www.amath.washington.edu/research/articles/Tung/journals/solar-jgr.pdf” rel=”nofollow”>Solar-Cycle Warming at the Earth’s Surface and an Observational Determination of Climate Sensitivity. They credit Judith Lean for providing her UV and TSI reconstructions, references list Lean et al 1995 “Reconstruction of Solar Irradiance since 1610 – Implications for Climate-Change” and two 2005 papers, a Lean and a Lean et al.

    The Lean TSI reconstructions are discredited and not to be used, even Lean agrees they are wrong, which includes Lean 2000 and a Lean and Wang 2005 version. A major part of the reasons is href=”http://wattsupwiththat.com/2014/06/28/a-cool-question-answered/#comment-1672049″ rel=”nofollow”&gt. There is also an issue about adding in a “background” based on the sunspot cycle, which is an error.

    Since Tung was using Lean in the Tung & Camp paper which Spencer referenced, and it is likely Lean was also used in Zhou & Tung 2010 (I will likely be corrected if wrong), that’s 2/3 of the cited previous “evidence” of such a small signal already effectively blown away.

    Ah good, Nir Shaviv 2008 is available href=”http://onlinelibrary.wiley.com/doi/10.1029/2007JA012989/abstract” rel=”nofollow”free open access and complete. And what is that in the References… It’s Lean 2000!

    You need better examples of researchers who have found this tiny solar signal, who are not sharing the same flaws. I cannot now see any of those you cited as acceptable, thus your evidence that others have found as you are claiming is insufficient, and perhaps actually non-existent.

    [Request you check links. .mod]

  89. “It would not surprise me to find a delayed correlation such as the one found by Solheim et al., in which temperature trends correlated with solar activity and length of solar cycle delayed by a cycle period. On that basis, they predicted cooling for Norway during solar cycle 24 due to the short cycle 23.”
    ” Correlations with time lag
    As a background for the investigation of possible relations between SCL and temperature in sunspot periods, we determined the correlation between SCL and temperature for variable lags of an 11-year time window. We calculated 11 year running mean temperatures for the selected datasets, and correlated this with the SCL with lags from 0 to 13 years, calculated from the middle time for each solar cycle. The starting point could also have been chosen as the year of solar maximum or the end year of the sunspot cycle. However, we selected the middle time, since this gave the possibility to check correlations with the same sunspot cycle (lag=0).”

    http://www.sciencedirect.com/science/article/pii/S1364682612000417

  90. Oh noes! In my last comment I screwed up my formatting of the OP quote while killing the auto-URL WP function to stay under the 3-URL-max no-moderation limit! Whatever shall I do?

    Stop trying to do it like others and just blockquote a large chunk and preface with a “From the article:” note, next time and afterwards, which I know works. I should be old enough to know to go with functional over fancy and/or following questionable practices, italics-only quoting can get messy and make it hard to keep track. Doofus!

    [Well, they’re there someplace, but I can’t figure them out. 8<) .mod]

  91. From Schrodinger’s Cat on July 26, 2014 at 2:03 pm:

    The period 1950-2000 had a series of cycles which were high in SSN and highest in the duration of SSN>75 compared with all SSN cycles that were logged since 1750. The average SSN over that period was about 52.

    You need to hang around Leif Svalgaard’s site and check out the work on the new sunspot number:

    http://leif.org/research/

    Basically, the Group Sunspot Number is crap, and the pre-1947 (or 1945) International (aka SIDC) SSN were too low, there is no Modern Grand Maximum. You can see the effect on the popular “Leif’s best guess TSI reconstruction” graph:

    As the 1950-2000 period was in reality not noticeably different from previous times in SSN and TSI, you should not look to the Sun as a driver of increased global warmth during that period.

  92. “In addition to the relation between solar cycle length and the amplitude of the next Rmax, it is reasonable to expect a time lag for the locations investigated, since heat from the Sun, amplified by various mechanisms, is stored in the ocean mainly near the Equator, and transported into the North Atlantic by the Gulf Stream to the coasts of Northern Europe. An example of time lags along the Norwegian coast is an advective delay between the Faroe-Shetland Channel and the Barents Sea of about 2 years determined from sea temperature measurements (Yndestad et al., 2008).”

    http://www.sciencedirect.com/science/article/pii/S1364682612000417

  93. Found in kadaka (KD Knoebel) on July 26, 2014 at 11:17 pm, a previous comment of mine:

    [Request you check links. .mod]

    and also found in my July 26, 2014 at 11:35 pm comment:

    [Well, they’re there someplace, but I can’t figure them out. 8<) .mod]

    Ack!! What did you do to my 11:17pm post, it’s a mess!

    I was ready at 11:35 to leave it like it was, but for what you have done…

    Here is the fixed version, what should have been at 11:17pm, formatting fixed, just needed some open/close tags flipped in first paragraph:

    Several researchers, including Nir Shaviv (2008), Roy Spencer (see http://www.drroyspencer.com/2010/06/low-climate-sensitivity-estimated-from-the-11-year-cycle-in-total-solar-irradiance/) and Zhou & Tung (2010) have found that ocean surface temperatures oscillate with an amplitude of about 0.04 – 0.05 oC during a solar cycle.

    As seen in Roy Spencer’s article, his first graph “Estimating Climate Sensitivity from the Solar Cycle in Total Solar Irradiance” lists as source a Judith Lean TSI reconstruction. In the text this is described as using the TSI variations from a Tung & Camp paper he was referred to, Solar-Cycle Warming at the Earth’s Surface and an Observational Determination of Climate Sensitivity. They credit Judith Lean for providing her UV and TSI reconstructions, references list Lean et al 1995 “Reconstruction of Solar Irradiance since 1610 – Implications for Climate-Change” and two 2005 papers, a Lean and a Lean et al.

    The Lean TSI reconstructions are discredited and not to be used, even Lean agrees they are wrong, which includes Lean 2000 and a Lean and Wang 2005 version. A major part of the reasons is here. There is also an issue about adding in a “background” based on the sunspot cycle, which is an error.

    Since Tung was using Lean in the Tung & Camp paper which Spencer referenced, and it is likely Lean was also used in Zhou & Tung 2010 (I will likely be corrected if wrong), that’s 2/3 of the cited previous “evidence” of such a small signal already effectively blown away.

    Ah good, Nir Shaviv 2008 is available free open access and complete. And what is that in the References… It’s Lean 2000!

    You need better examples of researchers who have found this tiny solar signal, who are not sharing the same flaws. I cannot now see any of those you cited as acceptable, thus your evidence that others have found as you are claiming is insufficient, and perhaps actually non-existent.

  94. kadaka (KD Knoebel) says:
    July 27, 2014 at 1:02 am

    Basically, the Group Sunspot Number is crap, and the pre-1947 (or 1945) International (aka SIDC) SSN were too low, there is no Modern Grand Maximum. You can see the effect on the popular “Leif’s best guess TSI reconstruction” graph:

    As the 1950-2000 period was in reality not noticeably different from previous times in SSN and TSI, you should not look to the Sun as a driver of increased global warmth during that period.

    Unfortunately most reading this blog will ignore your comment. Funnily enough, if you’d posted a similar comment on a warmist blog they would also have ignored it because the CAGW crowd rely on the Lean reconstruction in order to explain the early 20th century warming.

  95. For the n-th time, you can not use the last decades for this type of analysis because volcanic activity was almost in phase with solar.

  96. This article demonstrates how little we know. The question you pose and your suspicion that solar radiation plays a larger role than generally accepted has an intuitive feel for me, but then my intuition is often wrong. From what I can tell, the physics of radiation do seem to be poorly incorporated into climate models. As many visiting the WUWT may not have a radiation physics background, perhaps you could do a little basic education based on following. Going back to the basics always helps me.
    1) Available Energy > the TSI provides us with a measure of the incoming energy, but does not tell us how that energy is deposited (absorbed) or distributed in the environment.
    2) TSI measurement techniques/equipment > the question I have had for a long time is – are we measuring all of the available incoming energy and incorporating it in the TSI? The electromagnetic spectrum (EMS) is not the only source of available incoming energy, notably high energy particles being another source. Are EMS wavelengths shorter than 10E-12 measured and how so? We get a lot of those high energy photons and the energy transfer mechanisms are complex with the energy often going into the disruption of a nucleus that does not necessarily compute to eventual heat or radiation transfer. I have gathered that the entire EMS is measured with the TSI, but could use a confirmation of this. My root question is – are we missing something in our measurement of the TSI? I have a lot of faith in guys like Leif, but I still have in me a little of the Missouri “Show Me” and could use some reassurance on this topic.
    3) Energy transfer > this is where I suspect we have the least knowledge due to the complexity of trying to figure out all the possible routes of energy depositions and energy conservation that eventually lead to what we call heat or lack thereof. We can readily observe the outcome with our thermometers and calorimeters. However different routes of energy deposition at specific wavelengths or particle energies could have an impact on the eventual outcome of greater, or lesser, molecular excitation. I wonder how much work we have put into this arena of study. As you noted, cloud cover and aerosols (just to name a couple things) will impact the energy transfer especially with re-radiated EMS that could be lost to space. These factors greatly complicate the whole energy conservation thing.
    It takes a pretty big jar of hubris to think we have even the slightest clue yet.

  97. bones & Pamela Gray
    .”….inertia….. calculated over hundreds of years long.”

    Thinking in these very long term ways has to be the key to unraveling this huge mystery of our climate. I could never understand why any solar change would have to show up in an immediate change of global temperatures. There have to be lag upon lag upon lag of unknown variables of unknown dimensions over unknown time scales.
    Puzzles for the coming century. I love your very long term thinking.

  98. Changes to the sunspot record doesn’t make the kind of difference to solar analyses that some here are claiming, and definitely doesn’t change the fact that the sun causes warming and cooling cycles.

    kadaka (KD Knoebel) says:
    July 27, 2014 at 1:02 am

    “As the 1950-2000 period was in reality not noticeably different from previous times in SSN and TSI, you should not look to the Sun as a driver of increased global warmth during that period.”

    The sunspot record from 1950-2000 included most of the highest solar cycle activity levels ever observed and recorded. The comment qouted here ignores both the direct solar heating influence from those higher than average cycles, and also the heat storage and lagged release from the same solar influence during the period.

    The bias on display here: “you should not look to the Sun”, is holding up progress.

  99. Bob Weber says:
    July 27, 2014 at 5:53 am

    The sunspot record from 1950-2000 included most of the highest solar cycle activity levels ever observed and recorded. The comment qouted here ignores both the direct solar heating influence from those higher than average cycles, and also the heat storage and lagged release from the same solar influence during the period.

    Bob, I have looked for the 11-year cycle in a whole host of datasets, without success.

    I have also noted that during both the Maunder and Dalton minima, the temperatures started rising well BEFORE the succeeding increase in sunspots/TSI. This casts great doubt on the sun being the cause of the temperature drop.

    Now, people have explained away the first finding by saying (as you do) that it has to do with the lags in the system.

    However, that makes the situation with the Dalton and Maunder minima worse, not better. If there is such a lag, the drops in temperature should occur well AFTER the drop in sunspots/TSI … but they don’t …

    Regards,

    w.

    PS—You say:

    The bias on display here: “you should not look to the Sun”, is holding up progress.

    My friend, I have “looked to the sun” more than just about anyone I know … the problem is not lack of looking.

    The problem is, I haven’t found any evidence to support the claim that minor variations in TSI have an effect on the climate, and much evidence that there is no such effect.

  100. sleepingbear dunes says:
    July 27, 2014 at 5:50 am
    ” I could never understand why any solar change would have to show up in an immediate change of global temperatures. ”
    ————————————————————————————————————————-
    Changes in insolation show up very quickly in temperatures. Think of the difference between winter and summer temps as latitude increases. However at the equator, the temperature difference is negligible. So clearly it is insolation that rules not tiny differences is TSI.

  101. “However, that makes the situation with the Dalton and Maunder minima worse, not better. If there is such a lag, the drops in temperature should occur well AFTER the drop in sunspots/TSI ”

    Not if the ocean cycles are dominant.

    One could well envisage that a positive ocean phase started warming the air before solar activity began to recover at the end of the Maunder and Dalton.

    Likewise a negative ocean phase would start cooling the air before a drop in solar activity

    Sometimes the oceans are in phase with solar activity and sometimes out of phase with it.

  102. It is clear that “warming” is shifted north of the equator.

    Oceans are defending themselves, but until the.

  103. All you folks who claim a large role in global temperatures for the variations in the sun’s strength over the sunspot cycle, here’s a graph for you:

    What most people don’t realize is that out of the ~1360 W/m2 of total solar irradiance, the variation of the sun’s strength over a typical sunspot cycle is ± 0.5 W/m2. This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!!!

    Now, it is theoretically possible that there is some amplification factor. Let’s be insanely generous and say that the variation is amplified by a factor of 10 … this still only gives us a variation of ± 0.4%, a minuscule four-tenths of a percent.

    I find it highly unlikely that such a variation will make the slightest difference to the global temperature, whether in the short or the long run.

    Finally, in the last half billion years the strength of the sun (using standard physics and the knowledge of stellar evolution) is estimated to have increased by 5%. IF the sun ruled the temperature we should have seen an increase in global temperature over that time of 5%, or about 15°C (27°F). Obviously, there is no sign of this in the geological record.

    And it gets worse if we think that there is some mysterious amplification factor of ten regarding the solar strength … because then we should have seen an increase of about 150°C over that time, and that’s a joke.

    w.

  104. Willis Eschenbach It will not help. Now we begin to feel the effects of the solar impulse 2006.

  105. Stephen Wilde says:
    July 27, 2014 at 7:24 am

    “However, that makes the situation with the Dalton and Maunder minima worse, not better. If there is such a lag, the drops in temperature should occur well AFTER the drop in sunspots/TSI ”

    Not if the ocean cycles are dominant.

    The claim being made here has nothing to do with ocean cycles.

    One could well envisage that a positive ocean phase started warming the air before solar activity began to recover at the end of the Maunder and Dalton.

    One could well envisage that the temperature is driven by the variations in tree cover in China … I fear that postulating some unsubstantiated possibility does not advance the discussion.

    Likewise a negative ocean phase would start cooling the air before a drop in solar activity

    Sometimes the oceans are in phase with solar activity and sometimes out of phase with it.

    So your claim is not that the sun is ruling things, but that some vague unspecified “ocean cycles” are in charge … if so, what is driving the ocean cycles? You’ve ruled out the sun driving the “ocean cycles” by pointing out that they are not in phase with each other.

    The sun drives the daily cycles, and the annual cycles, and it is never true that sometimes the daily or annual temperatures are “in phase with solar activity and sometimes out of phase with it”. That’s what “driving” implies, that when sun goes up the temperature goes up and vice versa. If ocean cycles wander in and out of phase with the sun, that is prima facie evidence that one is NOT driving the other.

    w.

  106. By staring long enough at a waveform of noise, and with intense calculation, one can recover the Rorschach signal in said noise.

  107. My advice would. Solar activity is the weakest since 100 years. It is now a place for observation, because is going curiously.

  108. I’ve had a bit of experience with noise and vibration control in the automotive industry. One must be careful not to simply compare the frequency content of a suspected input to that of an output to decide if the former is driving the latter. Unless a given dynamic system is being excited much below any of its inherent resonances, one would not expect the spectra to match. A given dynamic system will have its own frequency response function (FRF) to a given coupled input. In other words, if the spectrum of the coupled input was perfectly flat, the output response of the system will still be curvy and wiggly. The more degrees-of-freedom of the system, the more complex the curve shape will be. A single degree-of-freedom system, say, a single mass suspended by a spring, will have a single resonant frequency, which in the case of a mass on a spring is the square root of the spring stiffness k over the mass m. This simple single-degree-of-freedom FRF looks like the static response at frequencies far below the resonance, then climb to a peak (of infinity if there were absolutely no damping) at resonance, then starts falling again after the resonant point. It crosses back to the static response amplitude when the input frequency = 1.414 times the resonance, so any input at a frequency lower than this is amplified . At frequencies higher than this, the response starts dropping towards an asymptote of zero at infinite frequency. This is the range of attenuation.

    Of course in reality, the only place where such perfect one-degree-of-freedom systems exist is in text books. The FRF of any real dynamic system will have a series on resonances and anti-resonances.

    If you have an output, and you don’t know what the input is, I believe you’re better off looking at the coherence function between suspected input signals and the known output. Unfortunately, in my experiences, we essentially always knew what the input was, and we used machines to calculate coherence (which require multiple averaged response measurement), so I am not able to describe well the mathematics of such.

  109. Ren, you linked to a Rossby Wave being propagated up into the stratosphere. Rossby waves are an instrinsic part of our atmosphere and demonstrate how Earth’s own climate and weather systems break into the stratosphere. These waves are often mistaken by solar enthusiasts as evidence of a top down solar mechanism. That is false. They have been clearly shown to be a bottom up phenomenon.

    http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCIQFjAA&url=http%3A%2F%2Fwww.rsmas.miami.edu%2Fusers%2Fisavelyev%2FGFD-2%2FRossby%2520waves.pdf&ei=uB_VU62BIdekyASwh4GYBA&usg=AFQjCNHAo23UtJpVqMnJkjI3Tr0adfenvA&bvm=bv.71778758,d.aWw

  110. ren says:
    July 27, 2014 at 7:43 am

    Willis Eschenbach It will not help.

    Ren, I was going to skip this as I do virtually all of your comments, but I thought I could assist you in gaining some traction by pointing out that far too many of your comments are incomprehensible or wildly off topic.

    For example the comment quoted above. What is the “It” that will not help? Science? The PDO? Praying for rain? Solar variations? Your sentence contains no meaning.

    As a result, I generally can’t figure out what you might possibly be talking about, I am unwilling to guess, and I don’t have time to screw around with the back-and-forth of trying to extract your meaning from you.

    Here is another example:

    ren says:
    July 27, 2014 at 8:20 am

    What will be the extent of ice cover in April 2015?

    http://oi62.tinypic.com/55jx40.jpg

    What on earth is the point of this question? Are you looking for estimates? There are several blogs where people guess the future ice maxima or minima, but April? The maximum is usually in March, why April?

    And in support of your curious question, you’ve posted an (uncited) image that appears to be from Cryosphere Today, no text, no citation, no reason given. That’s as useful to your question as a picture of a kitten, all you’ve done is irritate the reader by wasting our time.

    And what does this have to do with putative solar cycle driven variations in temperature?

    If you want people to comment on your ideas, the ideas need to be on point, on topic, clearly explained, and referenced or cited to something other than a random graphic with no provenance.

    Just saying, if you want traction, your current methods are not assisting you in the slightest.

    All the best,

    w.

  111. Pamela Gray says:

    July 26, 2014 at 9:43 pm

    Thanks for the kind words Gary. Weather and climate is my lifelong hobby and I am such a nerd about it. But I am not nearly as schooled as other professional and amateur informative scientists who contribute posts and comments here at WUWT. The honor goes to them as I am only a grasshopper. I have spent pleasurable hours and hours learning a great deal from the likes of Anth***, Willis, Bob Tisdale, and Leif.
    ===================
    As long as it doesn’t go to your red-head, it’s all good :)

  112. Willis Eschenbach says:
    July 27, 2014 at 7:39 am

    “This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!!!”

    Poor argument. Plot similarly the global mean temperature on a Kelvin scale to see that the effect we are looking for is of tiny proportion as well, about +/- 0.2K in the ~60 year variation out of 300K.

    Willis Eschenbach says:
    July 27, 2014 at 7:51 am

    “You’ve ruled out the sun driving the “ocean cycles” by pointing out that they are not in phase with each other.”

    Non sequitur. In a system with lag, there is always as phase difference between input and output for periods shorter than the lag.

  113. Willis Eschenbach
    I show phenomena which science knows very little. Tell me why the lack of hurricanes in the Atlantic? What is “suddenly” happen?

  114. Pamela Gray says: “The top of the atmosphere translates to 0.073 watt/m2 under clear sky conditions. However, over very long time spans we might have a convincing argument related to a building imbalance (as in more heat going in than going out) leading to long noisy cycles of warmth. But that imbalance begins to go the other way eventually. Leading to some very cold years, decades, and even longer before once again we climb back out of a cold spell. The oceans certainly have the capacity to absorb more heat than they give out (brrrr). ”

    I think there is amble evidence already of what is the “noise” in the system. That is changes in the PDO, AMO, NAO, AO and etc. These cycles are not synchronized – which tends to introduce noise in the system. I think it is likely that these “oscillations” are caused by heat imbalances that happen over time.

    I agree with many others who think solar output such as TSI vary over time and get amplified in various ways such that they have more of an impact that the energy alone will explain. Thus there are observations such as the one by the current essayist Stan Robertson who wrote above, “I think that this might be a credible detection of a solar cycle driven temperature variation at a 10.4 year period with a signal to noise ratio of at least 0.065 C/ 0.3 C = 0.22.”

    Then in periods like the Maunder Minimum of around 1645 to 1710 or so, there is the theory that TSI gets to a “minimum” and stays flat during that period instead of continuing to dip. But is this what stars do? Is there a minimum – and then even as activity of the star declines, TSI stays flat? Observations from other stars don’t seem to be sufficient to answer this question (at least from what I could find). Some astronomers have been trying to determine how much the output of stars varies over time. However, the observations do suggest that there are similar stars to ours that probably vary more than the amount of variation that humans have thus far been able to measure. But the amount we have thus far been able to measure probably means little given that humans have had instruments capable of determining TSI only a relatively short time.

    In a nutshell, then, I think changes in solar output including TSI have an impact on the earth’s climate. Variations in TSI are likely amplified through various means (i.e, changes in cloud cover). The other major input to changes in temperature are the various “oscillations” such as PDO, AMO, AO, NAO and etc. The oscillations vary over decades and multiple decades causing changes in energy absorbed and released from the oceans – thus having an impact on surface temperature and locations of winds, clouds and etc. They probably are modulated by heat imbalances that build up in ocean basins over time. The “oscillations” might also be influenced by solar changes – if solar output changes, this will impact how much heat builds up and where it builds up in the oceans.

  115. FWIW, I Googled “ren comment bot” and discovered “Ren” was a handle used on the hackaday-dot-com site.

    How are scientists like rabbits? They like to replicate.

  116. kadaka, that makes sense. Artificial sentence structure. Changes in sentence syntax that appear to be automatic. Posting quotes without comment. Indeed we might have a “bot” in the belfry.

  117. Willis mentions the extraordinary stability of temperature over aeons as a reason for not accepting a significant solar influence on climate.

    The answer is that although the sun alters global cloudiness and thus the proportion of solar energy entering the oceans the subsequent shifts in the climate zones are the negative system response which keeps outgoing radiation equal to incoming radiation.

    For a water planet the adjustment mechanism even works if the top of atmosphere insolation changes as a result of a large change in solar power such as that since the early faint sun.

    It is the weight of the atmosphere on the ocean surface that determines the amount of energy that the oceans can retain from whatever incoming radiation arrives from the sun by setting the amount of energy required to achieve the phase changes of water.

    The oceans then determine air temperatures.

  118. bones says:
    July 26, 2014 at 7:08 am

    Leif Svalgaard says:
    July 26, 2014 at 6:40 am

    Stan, one example of how little change it takes in TSI to create clouds and rain is evident in the phenomenon of two rainy seasons in Tanzania/southern Kenya caused by the transit of the sun back and forth over the equator. The apparent transit angle is ~12 degrees on each side of the equator, however the rains are initiated before the extremes are reached – “long rains” starting in March-April and short rains in October-November. Therefore at ~5 degrees N and S would appear to be enough to initiate this. TSI on a square metre 5 degrees N or S is ~cos 5*TSI at the equator, i.e. is 0.99619 of the insolation at the equator. I believe this direct observation would present a measure of how sensitive “weather” is to small fluctuations in TSI.

  119. Willis said:

    “If ocean cycles wander in and out of phase with the sun, that is prima facie evidence that one is NOT driving the other.”

    A logical non sequitur.

    The sun determines global cloudiness which then affects the proportion of TOA insolation that gets into the oceans.

    Internal system variability sets up cyclical movements within the oceans and there is no reason why that internal variability need be synchronous with the initial solar variations given the thermal inertia of the oceans, possible lunar influence and separate interactions between the individual ocean basins.

    Furthermore, as per Willis’s own Thermostat Hypothesis it is the variable ocean/atmosphere response that eventually negates the initial solar effects on global cloudiness.

    Less clouds skews ENSO towards more El Ninos compared to La Ninas and El Ninos are a cooling effect for the system overall even if the middle latitudes get a little warmer from more poleward zonal jets whilst the energy flows through the air more quickly on its way from the oceans to space.
    The circulation changes in air and oceans are a therefore a negative system response to the initial solar induced changes in cloudiness.

    Climate changes as observed so far (within the interglacial) seem not to involve significant changes in global temperature, merely changes in the distribution of available energy with the largest effects in middle latitudes as the climate zones shift to and fro latitudinally.

    Even during Ice Ages there seem to be similar climate shifts on an approxomate 1000 to 1500 year time scale but they don’t cause Ice Ages to begin or end so solar variability causing cloudiness changes would appear to fit the bill both within Ice Ages and Interglacials.

  120. Willis, try looking at this, http://climate4you.com/images/SunspotsMonthlySIDC%20and%20HadSST3%20GlobalMonthlyTempSince1960%20WithSunspotPeriodNumber.gif

    In 1965, ’76, ’86, ’96, and ’08 there were solar minimums. Look up at the SST graph, and see the temp dips that correspond to the minimums. Yes, that’s wiggle-matching, but we are comparing real observations. Can you see the El Nino’s and La Nina’s in the SST graph? The SST anomalies in ’65 and ’76 show a clear negative temperature change during the solar minimums. There’s much more information in this graph than is apparent. I am not sure why you’re not picking up those temp drops at the solar minimums in your statistical work.

    Most of the graphs from other datasets as seen here: http://climate4you.com/ (scroll down the page…) show the same temp drop features at the solar min marks. The point is, temps drop when solar activity drops off, the amount of the drop is dependent on the energetic strength of the particular cycle and lagged accumulated oceanic heat release that had built-up over many cycles.

    At this point, because I really have other things to do today instead of spending all day on the comment section here, I’m going to return to this topic again in a week or two after finishing up my presentation on solar warming/cooling, where great attention will be given to how it happens. After which, Willis, I will welcome your point of view on the statistical aspects of my model, realizing many are dubious of solar-driven warming/cooling, including yourself.

    There are lags in the system, and your stats work could help find the lag(s). David Stockwell determined a 2.75 year lag. Did anyone read David Stockwell’s papers on solar supersensitivity and accumulated sunspot anomaly? His stuff is here: http://landshape.org/enm/solar-supersensitivity-a-new-theory/ , papers here http://vixra.org/abs/1108.0004 and here http://vixra.org/abs/1108.0020 .

    Just so you know, ren’s native language is not english….he does the best he can – he’s a smart guy who studies UV, cosmic arays, and the stratosphere. I just wish he was easier to understand!

  121. Pamela Gray: “Indeed we might have a “bot” in the belfry.” Nice play on words. Ironic, too, since rén (人) means “person.”

  122. Gary Pearse says:
    July 27, 2014 at 11:41 am

    bones says:
    July 26, 2014 at 7:08 am

    Leif Svalgaard says:
    July 26, 2014 at 6:40 am

    Stan, one example of how little change it takes in TSI to create clouds and rain is evident in the phenomenon of two rainy seasons in Tanzania/southern Kenya caused by the transit of the sun back and forth over the equator. The apparent transit angle is ~12 degrees on each side of the equator, however the rains are initiated before the extremes are reached – “long rains” starting in March-April and short rains in October-November. Therefore at ~5 degrees N and S would appear to be enough to initiate this. TSI on a square metre 5 degrees N or S is ~cos 5*TSI at the equator, i.e. is 0.99619 of the insolation at the equator. I believe this direct observation would present a measure of how sensitive “weather” is to small fluctuations in TSI.

    Thanks, Gary. A couple comments on that. First, I find this:

    It is suggested the semi-arid/arid climate in East Africa and its bimodal precipitation annual cycle can be explained by the ventilation mechanism, in which the atmospheric convective stability over East Africa is controlled by the import of low MSE air from the relatively cool Indian Ocean off the coast. During the rainy seasons, however, the off-coast sea surface temperature (SST) increases (and is warmest during the long rains season) and consequently the air imported into East Africa becomes less stable. This analysis may be used to aid in understanding overestimates of the East African short rains commonly found in coupled models.

    Next, Kenya stretches from about 4°N to 4°S so it is directly on the equator.

    Next, the swing of the sun is from 23.5°N to 23.5°S, not “~12 degrees on each side of the equator”. This makes the difference from when it is over the equator to the furthest point south equal at the TOA to cos(23.5) = 0.91, or a difference of 28 W/m2 between extremes.

    Next, you’ve forgotten the variation in TSI caused by the varying distances from the sun. This increases the TSI when the sun is on one side of the Equator and decreases it when the sun is on the other side.

    From the CERES data, here is the TOA monthly insolation for the Equator:

    So while you may indeed be correct that the sun is causing the two rainy seasons, the annual variation in TSI in Kenya is about 50 W/m2 peak to peak, not the tiny amount you have calculated.

    w.

    PS—You say “however the rains are initiated before the extremes are reached”. In fact the rains start somewhere around the equinoxes (March & September), when the sun is directly over the equator.

  123. Ren is fine… Ren Hoëk is rather adventurous and intelligent. As long as Stimpson J Cat (Stimpy) doesn’t show up, because that’s when Ren gets emotionally brittle. Then it WILL get very annoying. ;-)

  124. Bart says:
    July 27, 2014 at 9:38 am

    Willis Eschenbach says:
    July 27, 2014 at 7:39 am

    “This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!!!”

    Poor argument. Plot similarly the global mean temperature on a Kelvin scale to see that the effect we are looking for is of tiny proportion as well, about +/- 0.2K in the ~60 year variation out of 300K.

    First, I don’t understand the “60 year variation”, when the head post and my comment are both talking about 11 year cycles.

    Second, you appear to assume the temperature is varying linearly with radiation. A variation of ~ 1 W/m2 translates to a 0.25 W/m2 variation on a global 24/7 basis. This is further reduced by clouds to a change of about 0.17 W/m2 entering the system.

    Assuming no amplification or feedbacks other than the greenhouse effect, this would be a change of 0.05°C … like I said, inconsequentially small.

    Willis Eschenbach says:
    July 27, 2014 at 7:51 am

    “You’ve ruled out the sun driving the “ocean cycles” by pointing out that they are not in phase with each other.”

    Non sequitur. In a system with lag, there is always as phase difference between input and output for periods shorter than the lag.

    I don’t understand this. A lag only changes the phase, so you are correct that there is “always as phase difference between input and output” in a lagged system. However, what there generally is NOT is a response to a cyclical signal that goes in and out of phase with the driven signal, regardless of the period lengths.

    Consider, for example, the lag in the annual heating of the earth by the sun. It is about two months. Now, if we look at a period shorter than that lag, say a day … we do NOT see the daily cycle going randomly into and out of phase with the input.

    So I’m not clear at all on your claim.

    Thanks,

    w.

  125. Chasing dimensionless sunspot number is a waist of time. Sunspot cycles have a distinct magnetic polarity (opposite) on each of two solar hemispheres.
    Dr. S will say that they cancel each other, but that is not the case for the open solar magnetic flux impacting the Earth. .
    Two magnetic polarities are separated by the heliospheric current sheet (HCS), thus the Earth sees only one at any time.
    How much time the earth spends in each polarity is determined by the tilt angle of the HCS, which is considerably different between even and odd cycles.

    All Earth’s electrically conducting (from wires to ocean currents) and electrically charged (from clouds to ionosphere) systems differentiate between two solar magnetic polarities.
    For example when the Earth is swept by the HCS all geomagnetic stations record sharp magnetic spike of one or the other polarity depending on the direction of crossing.
    As a consequence, the 22 year cycle is present in both land and ocean temperatures. Here is the NOAA’s L&O temperature anomaly and its spec with the 22 year component the most prominent one.
    How does it work? That is much harder to answer; for a test we cannot turn it off, but according to (my) extrapolation there is a remote possibility that the sun just may do us a favour and switch it off for ~ 10-11 years (starting about 2020)

  126. There are such (apparently) contradictory assertions about the effect of solar activity on global or regional sea surface and land temperatures from eminent persons on this thread that I resorted to Googling “solar activity and climate change” .
    The first ref , from thousands , was the following from an international team led by a Gerard Bond from Columbia Univ in Science, Vol 294, 2130 etseq (Dec 2001). It looked at cooling of the north Atlantic and the extent of drift ice at times of low solar activity, during the Holocene , the last 12000 years , and found a positive correlation , but over a 1500 year cycle ie slow variation in solar output as evidenced by the formation of cosmogenic nuclides C14 and Be10.(free access PDF article). They seem to conclude that the Earth’s climate is indeed sensitive to small changes in solar output (UV/Vis radn. and solar wind) and that changes in the North Atlantic waters could have repercussions further afield (if I have understood it correctly).

    http://www.essc.psu.edu/essc_web/seminars/spring2006/Mar1/Bond%20et%20al%202001.pdf

    To follow up all relevant articles of this nature ( and some state the opposite) and resolve the differences of opinion seen in this thread would take one person a significant part of their lifetime, but if there could be, say, an International Team of Climate Scientists looking objectively at all causes of climate change and reporting back at , 1 – 2 year intervals, that would be such a help.
    A pipe dream alas.

  127. Willis Eschenbach says:
    July 27, 2014 at 12:48 pm

    “First, I don’t understand the “60 year variation”, when the head post and my comment are both talking about 11 year cycles.”

    So, you are looking for an even smaller effect. That merely reinforces the point.

    “However, what there generally is NOT is a response to a cyclical signal that goes in and out of phase with the driven signal, regardless of the period lengths.”

    For a linear system. Not all systems are linear.

    I’m not telling you, you are wrong. I am telling you, you are levying constraints on the allowable system response without acknowledging them.

  128. Willis Eschenbach says:
    July 26, 2014 at 1:51 pm

    Thanks for a very interesting analysis, Dr. Stan. I just took a look at the dataset in question, and I fear I can’t reproduce your results. I find no significant signal of the type that you show. Here is my result: . . .
    ————————————-
    Willis, the same program that pulled that .05 C sine wave out of the noise in my Figure 2 is the one that pulled a 10.4 year cycle out of the Jan 1954 – May 2014 Hadsst3gl data. I used 0.2 year steps of period, P, and least squares fitted
    sst – avg = A sin(2 pi t/P) + B cos(2 pi t/ P)
    where avg was the arithmetic average sst for the 60+ year record and t was time in months since Jan 1954. No smoothing, filtering or apodization applied; just the data from woodfortrees. I have rechecked that program and those calculations. I ran another trial with 0.1 year steps and the results overlay those of my Figure 4. I believe that my results are OK as I reported them. Please take a hard look at your program and try fitting the same data.

  129. Bart says:
    July 27, 2014 at 1:56 pm

    Willis Eschenbach says:
    July 27, 2014 at 12:48 pm

    “First, I don’t understand the “60 year variation”, when the head post and my comment are both talking about 11 year cycles.”

    So, you are looking for an even smaller effect. That merely reinforces the point.

    No, I’m looking for a larger effect. The swing in any given solar cycle is much larger than the swing over 60 years.

    “However, what there generally is NOT is a response to a cyclical signal that goes in and out of phase with the driven signal, regardless of the period lengths.”

    For a linear system. Not all systems are linear.

    Since the response to both the day/night solar variations and the annual solar variations is quite close to linear (including the S-B equation), you need evidence before you start asserting non-linearity.

    I’m not telling you, you are wrong. I am telling you, you are levying constraints on the allowable system response without acknowledging them.

    Bart, it is theoretically possible that the earth’s response to the sun is best described by a 4th degree polynomial with thresholds … but until someone can demonstrate that, I say that the Stefan-Boltzmann equation needs to be the default choice.

    Thanks as always for your comment,

    w.

  130. The UV changes during a solar cycle are very significant, even if the change in TSI is small. The UV will influence ozone production and other chemical reactions in the atmosphere.

    The magnetic field will change enormously with a positive peak followed by a negative peak. The solar wind will change throughout and the neutron count received on earth will peak out of phase with TSI. So a great deal of change takes place. I’m not convinced that we fully understand the full implications for our climate.

  131. Bob Weber says:
    July 27, 2014 at 11:59 am

    Willis, try looking at this, http://climate4you.com/images/SunspotsMonthlySIDC%20and%20HadSST3%20GlobalMonthlyTempSince1960%20WithSunspotPeriodNumber.gif

    In 1965, ’76, ’86, ’96, and ’08 there were solar minimums. Look up at the SST graph, and see the temp dips that correspond to the minimums. Yes, that’s wiggle-matching, but we are comparing real observations.

    Thanks, Bob, but you are not comparing the observations. You are comparing a centered, acausal smooth of the observations. I gave the graph of the cross-correlation function between the ACTUAL observations of HadSST3 and sunspots above. It is not statistically different from random chance.

    Just so you know, ren’s native language is not english….he does the best he can – he’s a smart guy who studies UV, cosmic arays, and the stratosphere. I just wish he was easier to understand!

    I figured that, but if he wants to get traction, he needs to up his game and stop posting uncited, unreferenced, unexplained links. I’ve gone fruitlessly to too many of his pointless graphics, and at this point I’ve given up.

    I looked at the David Stockwell links you sent, and it was totally unconvincing. I can only echo Greg Goodman’s comment, viz:

    Why is this study limited to 1950 onwards? Both temp and SSN go way back before that.

    It is also well known that the correlation of SSN and [temp] does not hold further back in 20th c. It then comes back into phase in late 19th c.

    Greg also raised a number of other very salient objections to the study.

    I have the same objection to the head post, as I spelled out above. Picking the 50 year time period when there is a weak correlation between SST and temps, a correlation which is nonexistent in the previous 50 years, is a cherry-picked deal-breaker for me. Color me completely unimpressed.

    w.

  132. Willis Eschenbach says:
    July 27, 2014 at 7:39 am

    All you folks who claim a large role in global temperatures for the variations in the sun’s strength over the sunspot cycle, here’s a graph for you: (skip)
    What most people don’t realize is that out of the ~1360 W/m2 of total solar irradiance, the variation of the sun’s strength over a typical sunspot cycle is ± 0.5 W/m2. This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!!!

    Now, it is theoretically possible that there is some amplification factor. Let’s be insanely generous and say that the variation is amplified by a factor of 10 … this still only gives us a variation of ± 0.4%, a minuscule four-tenths of a percent.

    I find it highly unlikely that such a variation will make the slightest difference to the global temperature, whether in the short or the long run.

    Finally, in the last half billion years the strength of the sun (using standard physics and the knowledge of stellar evolution) is estimated to have increased by 5%. IF the sun ruled the temperature we should have seen an increase in global temperature over that time of 5%, or about 15°C (27°F). Obviously, there is no sign of this in the geological record.

    And it gets worse if we think that there is some mysterious amplification factor of ten regarding the solar strength … because then we should have seen an increase of about 150°C over that time, and that’s a joke.

    w.
    —————————————————————
    Willis,
    It might seem to a lot of folks that a one part per 1360 variation of TSI over a solar cycle might be capable of producing a one part per 2800 variation of earth surface temperature, but I am not one of them. A sinusoidal oscillation of ocean temperatures with 0.04 C amplitude can’t be produced with the dinky part of that TSI variation that reaches the surface on average. That is basic calorimetry that I presented in my article of last October.

    So the only remaining question is whether or not such a temperature variation exists. In view of my Figure 4, I am inclined to think that it does. I didn’t make up the data of Hadsst3gl or even cherry pick it except to avoid an apparent pre-1954 glitch. (I wanted only recent cycles anyway.)

    If cyclically varying cloud cover is the source of a larger variation of solar flux at sea level, it would not necessarily scale up to produce 150 C temperature changes on a geologic time scale. Personal incredulity is not an argument against the mechanism. Leif Svalgaard is similarly incredulous but has never presented an argument that is capable of rejecting the cloud modulation mechanism. His argument fails for a planet with steady TSI (dTSI=0) and cyclical cloud variation (maybe associated with life cycles of cloud eating weevils?). His argument would say that dT = 0 if he opened a parasol and that would be true at the top of the atmosphere but not at sea level.

  133. lgl says:
    July 27, 2014 at 3:37 am

    For the n-th time, you can not use the last decades for this type of analysis because volcanic activity was almost in phase with solar.

    ———————————————————-
    Thank you! I will take a good look at this. If the SST variations are due to volcanoes then the solar amplification link is broken, but the temperature variations would still be quite real.

  134. “What most people don’t realize is that out of the ~1360 W/m2 of total solar irradiance, the variation of the sun’s strength over a typical sunspot cycle is ± 0.5 W/m2. This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!”

    Trace Watts

  135. There is something called the Ideal Gas Law which has THE formula for the temperature of any volume of atmospheric air and it specifically forbids there being an effect on temperature related to spectral response.

    The claim of a ‘green house gas’ effect is made by people who can’t explain how they don’t know that.

    “I talk a lot online” is not authority. Being able to calculate the temperature of a volume of atmospheric air correctly is authority.

    The people who can calculate correctly the temperature of a volume of air use the Law of Physics which forbids there being a class of gases which affect the temperature of atmospheric air

    based on their spectral relationship to light.

    It’s the end of that claim as soon as someone shows up with it and dares one of the believers in the green house gas effect believers to do some simple gas temperature calculations.

  136. Which is why believers in Green House Gas effect discuss anything but the actual calculation of the temperature of a volume of atmospheric air,

    and you never : not ever – see them do it or be around when any such calculation discussions go on.

    The Ideal Gas Law by specific application to all gases in atmospheric air, assigns one energy holding capacity;

    that energy holding capacity is *identical for CO2, and Methane, and Nitrogen, and Oxygen, Argon.*

    In real atmospheric temperature calculations done by real scientists who get repeatable instrument verified answers

    there is no such “green house gas” calculation, which is why the believers in it can’t ever provide a formula for it.

    It’s junk science which can not stand alonside the mathematical formula specifically forbidding it’s existence.

    The Ideal Gas Law’s assignment of energy capacity called the Gas Constant is the mathematical constant that specifically forbids any, and all the claims of temperature based on infrared or any other color light handling by gases.

    Go look it up. It’s a fie letter formula that can be thrown onto the desk with any believer of green house gas effect. Give him the instrumental measurements and tell hem to start calculating temperatures of volumes of atmospheric air.

    Tell him to show you his calculations allowing for spectral handling.

    He’ll have to find a reason to disrupt the situation because there is none.

  137. The optimal Fourier transform (OFT) might be considered a more sophisticated version of the slow Fourier transform. It finds sinusoids in artificial data exactly if the signal-to-noise ratio is low.

    The OFT fits the best ten sinusoids at once (that number is an adjustable parameter, but computation time goes up with it), not just one at once like the slow Fourier transform. It then takes those sinusoids away from the signal and repeats, to find the first 100 best sinusoids in the signal. The OFT is derived and explained at

    http://jonova.s3.amazonaws.com/cfa/optimal-fourier-transform.pdf

    The spreadsheet with all code and data is

    http://jonova.s3.amazonaws.com/cfa/climate.xlsm.

    See the “Transform Lab” sheet, recall HadSST3 or HadCrut4, and recall the cached OFT of each.

    The sea surface temperatures, HadSST3 from 1850 to 2013, shows only the following sinusoids near 11 years (with amplitude, phase, and period):
    10th biggest, 0.025 deg C, 95 deg, 12.65 years
    19th biggest, 0.022 deg C, 272 deg, 10.28 years
    66th biggest, 0.008 deg C, 71 deg, 11.95 years
    90th biggest, 0.006 deg C, 282 deg, 11.04 years
    So it shows a 11 year component of about 0.02C amplitude, even lower than the slow Fourier transform in Figure 4 above.

    Similar analysis is contained in the spreadsheet on all the major temperature and solar series, including the global mean surface air temperatures (HadCrtut4, UAH, etc).

    This observation led to the notch-delay solar theory, which is described at

    http://sciencespeak.com/climate-nd-solar.html.

  138. Chris Magnuson says:
    July 27, 2014 at 5:17 pm

    There is something called the Ideal Gas Law which has THE formula for the temperature of any volume of atmospheric air and it specifically forbids there being an effect on temperature related to spectral response. . . .
    Chris Magnuson says:
    July 27, 2014 at 5:37 pm

    Which is why believers in Green House Gas effect discuss anything but the actual calculation of the temperature of a volume of atmospheric air,

    . . . In real atmospheric temperature calculations done by real scientists who get repeatable instrument verified answers there is no such “green house gas” calculation, which is why the believers in it can’t ever provide a formula for it. . . .
    Leave a Reply
    ———————————————–
    Chris,
    Please take these comments elsewhere. I have spent a lifetime as a physicist and I can tell you that what you have written is simply wrong. Any infrared active molecules such as water vapor or carbon dioxide in air can certainly be heated with electromagnetic radiation. It is comments such as yours that the warmistas try to use to smear all honest skeptics.
    Stan Robertson

  139. David Evans says:
    July 27, 2014 at 6:01 pm

    The optimal Fourier transform (OFT) might be considered a more sophisticated version of the slow Fourier transform. It finds sinusoids in artificial data exactly if the signal-to-noise ratio is low. . . . .
    ————————————————-
    David, Thanks for the information. I will certainly check out the links. I am very curious just what OFT might reveal for Hadsst3gl since Jan 1954. The SlowFT for the whole 150 year period picks out peaks with amplitudes of about 0.035 C for 7.6, 9, and 11.2 year periods and peaks at about 0.05 C in about their 3rd harmonics at 22.4, 27, 32.6 years. I have no idea what that might be telling me. I suspect artifacts of merging segments into a long record.

    As Willis suggested, it may also be the case that all that I found in Figure 4 were artifacts of a similar nature. Or perhaps, as lgl said, there has been a coincidence of solar cycle periods and periodic volcanic eruptions. (That might be more credible than cloud eating weevils.) Honest efforts will eventually sort all of this out. In the meantime my previous calorimetry calculations make it crystal clear that TSI variations alone could only drive ocean temperature oscillations with an amplitude of about 0.01 C.

  140. I don’t think Chris Magnusen was denying that infra red active molecules can be heated by electromagnetic radiation.

    The point is that the operation of the Gas Laws ensures that densities change with such heating and the subsequent convection rearranges the positions of those heated molecules along the lapse rate slope so that there need be no change in surface temperature.

    Hence the fact of our well recognised and useful Standard Atmosphere.

  141. ren says:
    July 27, 2014 at 10:20 pm
    “Willis I speak only that the changes in ozone over the polar circles lead to strong cooling of the oceans. Therefore, there will be fewer hurricanes.”

    I agree with ren.

    More ozone in the stratosphere above the poles warms the stratosphere and pushes down tropopause height.

    That enables more frequent pulses of cold air towards the equator.

    Since the length of the lines of air mass mixing is increased thus causing more clouds along the more meridional jet stream tracks less solar energy gets into the oceans to drive hurricane formation.

    That proposition is consistent with Stan’s observations.

  142. Stan needs the Gas Laws to work as they do in order to achieve the global cloudiness changes referred to in his article.

    Only by expansion or contraction of the stratosphere relative to the troposphere differing at different latitudes can the necessary shifts in the climate zones be achieved and it is those shifts that cause cloudiness changes globally. Those changes are caused by top down solar effects.

    Willis needs the Gas Laws to work as they do in order to achieve the changes in emergent phenomena that enable his thermostat hypothesis to work.

    Only by differential expansion and contraction can density variations in the horizontal plane lead to the changes in convection that alter the timing and vigour of emergent phenomena locally and regionally. Those changes are caused by bottom up oceanic effects.

    Climate change is the result of the ever varying net interplay between the top down solar and bottom up oceanic effects.

  143. David Evans says:
    July 27, 2014 at 6:01 pm
    …………
    I use spectral analysis developed some years ago for electronic communication signals.
    Using NOAA annual data for the global temperatures (land & ocean) , I limited the spectrum components to one decimal point (on account of using annual not monthly data). Contribution of individual components in the sunspot cycle range is about half or less than one at the Hale cycle.

  144. ***
    kadaka (KD Knoebel) says:
    July 27, 2014 at 2:34 am

    You need better examples of researchers who have found this tiny solar signal, who are not sharing the same flaws. I cannot now see any of those you cited as acceptable, thus your evidence that others have found as you are claiming is insufficient, and perhaps actually non-existent.
    ***

    Yup. What you say has been said repeatedly & still hasn’t sunk in. Sigh….

  145. m2. This is a variation of ± 0.04%, FOUR-HUNDREDTHS OF A PERCENT!”m2.

    No the variation in solar is more then .04%. That is the crux of the problem this assumption based on no real long lasting data that the solar activity is much more constant then what it really is.

    In addition secondary effects are associated with solar variation which amplify solar effects themselves upon the climate.

  146. During the most recent solar lull 2008-2010 TSI was off by .15%.

    While the Maunder Minimum much longer and more severe then the recent short solar lull. Making it likely that TSI was off by amounts greater then .15% during the Maunder Minimum.

  147. What has taken place in year 2005 is a complete change from active to inactive solar activity.

    This change in my opinion will be more then enough to have another climatic impact just as is the case when one reviews historical climatic data.

    My challenge remains- Which is show me the data which shows a prolonged solar minimum period being associated with a rising temperature trend or a prolonged maximum solar period being associated with a falling temperature trend.

    I find no such data and the same result is going to happen as this decade proceeds.
    Already solar activity is falling off and we are no where near the bottom of the solar cycle 24-solar cycle 25 minimum.

    I think the data (especially post 2005/prior to 2005 ) supports the view that the sun can be quite variable and this variability can happen over a short period of time as is the case in the first decade of this current century.

    Expect climate implications if this prolonged solar minimum keeps advancing going forward.

  148. The problem with so many postings over this site is there is a lack of understanding of noise in the climate system, thresholds in the climate system ,lag times in the climate system and that the climate system is non linear and never in the same state.

    Therefore my point (which i have made many time previously) is DO NOT EXPECT an x change in the climate from given x changes in items that control the climate. This I have preached but with little fanfare.

    Why- look read below.

    The initial state of the global climate.
    a. how close or far away is the global climate to glacial conditions if in inter- glacial, or how close is the earth to inter- glacial conditions if in a glacial condition.
    b. climate was closer to the threshold level between glacial and inter- glacial 20,000 -10,000 years ago. This is why the climate was more unstable then. Example solar variability and all items would be able to pull the climate EASIER from one regime to another when the state of the climate was closer to the inter glacial/glacial dividing line, or threshold.

    The upshot being GIVEN solar variability IS NOT going to have the same given climatic impact.
    .
    . Solar variability and the associated primary and secondary effects. Lag times, degree of magnitude change and duration of those changes must be taken into account.

    Upshot being a given grand solar minimum period is not always going to have the same climatic impact.

    This is why solar/climate correlations are hard to come by UNLESS the state of solar activity goes from a very active state to a very prolonged quiet state which is what has happened during year 2005.

    So the nonsense that post Dalton no definitive solar /climate correlations exist just supports my notions of what I just expressed.

  149. Meanwhile, a quiet sun is correlated with a stronger jet stream pattern as noticed in northern hemisphere summers. So we are dealing with under-specified models in global temp debates and measures. Does a stronger jet stream pattern influence oceans and is there a measure of jet stream strength and southerly influence?

  150. ” Willis Eschenbach says:
    July 27, 2014 at 12:33 pm

    Gary Pearse says:
    July 27, 2014 at 11:41 am

    I stand corrected (on several things!). Thanks, Willis. About 30years ago I actually used the correct 23.5 degrees swing knowledge to design a sloped, passive two-by-four and stapled polyethylene sheet to the entire south wall of my farmhouse (maximized for mid January). My kids would step out the window with a card table and play chess or cards in their shirtsleeves on a sunny crisp February day.

  151. Gary Pearse says:
    July 28, 2014 at 8:57 am

    I stand corrected (on several things!). Thanks, Willis.

    You are a gentleman for saying so.

    About 30years ago I actually used the correct 23.5 degrees swing knowledge to design a sloped, passive two-by-four and stapled polyethylene sheet to the entire south wall of my farmhouse (maximized for mid January). My kids would step out the window with a card table and play chess or cards in their shirtsleeves on a sunny crisp February day.

    Nice!

    w.

  152. I just noticed this comment by Willis Eschenbach says:
    July 27, 2014 at 7:39 am
    “Finally, in the last half billion years the strength of the sun (using standard physics and the knowledge of stellar evolution) is estimated to have increased by 5%. IF the sun ruled the temperature we should have seen an increase in global temperature over that time of 5%, or about 15°C (27°F). Obviously, there is no sign of this in the geological record.”

    The actual composition – earth’s atmospheric pressure is not known for sure. However, it is known that during the Cretaceous, the atmosphere was quite a bit thicker. It is likely that over time, the earth loses a little bit of atmosphere each year. Over hundreds of millions of years, that adds up.

    Changes in thickness of the earth’s atmosphere obviously impact its thermal characteristics. Without knowing exactly how the atmosphere changed, it is not possible to make your analogy.

  153. The solar effect less talked about.
    The heliospheric atmosphere is still evolving during this new era of low solar activity. The region we call interplanetary space, Earth’s home.
    And the stats for today have some zeros. Doesn’t look like the Interplanetary Magnetic Field of the sun will be affecting Earth so much.
    But what about the Interstellar Magnetic Field reconnection with the Interplanetary magnetic field?

    http://www.spaceweather.com/

    Solar wind
    speed: 331.2 km/sec
    density: 0.6 protons/cm3
    explanation | more data
    Updated: Today at 0056 UT
    Interplanetary Mag. Field
    Btotal: 2.2 nT
    Bz: -0.0 nT
    explanation | more data
    Updated: Today at 0057 UT

  154. Carla says:
    July 29, 2014 at 6:19 pm
    But what about the Interstellar Magnetic Field reconnection with the Interplanetary magnetic field?
    As I have explained to you a hundred times, the solar wind is supersonic and no magnetic influence can travel upstream, so no influence is to be expected.

  155. Don’t ask me about the cloud ratio to cloudless days around these parts of Wisconsin. I’m a driver and I see clouds every day these days. Not always all day, but clouds are more plentiful. Now why would that be. ha go figure. And people are calling them Fall like clouds.
    Changes in the upwind crescent of the solar gravitiational focusing function?
    no no no

    Gee there’s Dr. S. better go back upthread and see what part of this could be nonsense.

  156. And you should see the lower height of the upwards daily water vapor and what it attaches too..

  157. Leif Svalgaard says:

    July 29, 2014 at 6:22 pm

    Carla says:
    July 29, 2014 at 6:19 pm
    But what about the Interstellar Magnetic Field reconnection with the Interplanetary magnetic field?
    As I have explained to you a hundred times, the solar wind is supersonic and no magnetic influence can travel upstream, so no influence is to be expected.
    ——————————————————————
    Except Dr. S. the distribution of outgoing solar wind isn’t what it used to be. The distribution isn’t the same when the heliospheric bubble is squashed…
    And the volume filling from CME’s is there either.

  158. Leif Svalgaard (replying to):
    July 29, 2014 at 6:22 pm

    Carla says:
    July 29, 2014 at 6:19 pm
    But what about the Interstellar Magnetic Field reconnection with the Interplanetary magnetic field?

    As I have explained to you a hundred times, the solar wind is supersonic and no magnetic influence can travel upstream, so no influence is to be expected.

    OK. Not really significant questions, but nevertheless, permit me to ask anyway, please:

    1. But a magnetic field “travels” at the speed of the crossing magnetic/electric fields in that charged stream, not at the physical speed of the charged particles within the beam. So, why could not a magnetic effect “travel upstream” in a physical beam [of] moving particles downstream?

    2. Could the particles within a physical beam ever travel “supersonic” downstream? That is, a physical effect (the sonic pressure difference we use to define sonic and supersonic) ever be supersonic? A different particle (or airplane or bullet or meteor) separately energized can and often does proceed through a physical medium (air, water, or ionized gas) faster than the speed of sound in a moving medium, but can a physical part of a beam made itself of particles ever be supersonic?

  159. Carla says:
    July 29, 2014 at 6:45 pm
    Gee there’s Dr. S. better go back upthread and see what part of this could be nonsense.
    Every little bit of it, Carla. The interstellar magnetic field cannot influence the interplanetary magnetic field in the inner solar system where Earth is.

  160. But good to see you drop by Dr. S. and do appreciate your presence on these solar matters.
    Had a question related to solar rotation and quiet portions in the rotation. But can’t remember it exactly right now..

  161. RACookPE1978 says:
    July 29, 2014 at 6:54 pm
    1. But a magnetic field “travels” at the speed of the crossing magnetic/electric fields in that charged stream, not at the physical speed of the charged particles within the beam. So, why could not a magnetic effect “travel upstream” in a physical beam [of] moving particles downstream?

    Magnetic changes move at the so-called Alfven speed. The solar wind [at Earth] moves outwards from the Sun at a speed ten times larger than the Alfven speed, so magnetic changes are just swept away ourwards.

  162. Leif Svalgaard says:

    July 29, 2014 at 6:55 pm

    Carla says:
    July 29, 2014 at 6:45 pm
    Gee there’s Dr. S. better go back upthread and see what part of this could be nonsense.
    Every little bit of it, Carla. The interstellar magnetic field cannot influence the interplanetary magnetic field in the inner solar system where Earth is.
    ————————————————————–
    Well then, what about the solar gravitational function and how do the two field couple..?

  163. Leif Svalgaard says:

    July 29, 2014 at 7:02 pm

    Carla says:
    July 29, 2014 at 7:00 pm
    Well then, what about the solar gravitational function and how do the two field couple..?
    Well, how about it?
    —————————————————–
    Accretion models, depicting different stellar magnetic field orientation and field strengths aren’t exactly clear as to the role of the Interstellar magnetic field. From what I have seen.

    The STEREO twins have observed the upwind crescent at 1 AU Dr. S. It is not under the rock anymore ya know.
    Is the data going to still be available from another source if the STEREO twins undergo..(what is it that was supposed to be going on with the STEREO twins?)

  164. Carla says:
    July 29, 2014 at 7:34 pm
    Accretion models, depicting different stellar magnetic field orientation and field
    The sun is not accreting anything significantly at this late stage of its life. When it was young and the solar wind was a thousand times stronger and accretion was millions of times stronger, there were connections, but not anymore. I think we have also gone over this many times.

  165. Let us see how low each solar parameter goes going forward as we head toward the minimum of solar cycl24 and the beginning of solar cycle 25. I expect extremely low values.

    My criteria will be met.

  166. It should not escape the casual reader here that the search for a tiny bit of solar connection larger than that already known is ironic. How so? Two reasons. First, the piece of the spectrum that varies a bit more than the whole thing (UV), is only a very small portion of the total solar frequency spectrum thus has far less energy in the total spectrum in terms of affect. Given that solar enthusiasts are talking only of the varying portion of UV that varies a bit more than average during prolonged minimums, we are discussing an even smaller amount of UV. Second, proponents often site unknown amplification factors that are intrinsic to Earth’s climate systems. They cling to these points like the cat on its last rope.

    Here is the irony. If these tiny tiny amounts of solar variation somehow (of unknown mechanism) control the largest processes on Earth that create weather and climate, how do they so dismissively disregard tiny CO2 increases (of known mechanism)? Are not both propositions preposterous in the face of such a large hard to move Earth?

  167. Pamela Gray: Here is the irony. If these tiny tiny amounts of solar variation somehow (of unknown mechanism) control the largest processes on Earth that create weather and climate, how do they so dismissively disregard tiny CO2 increases (of known mechanism)? Are not both propositions preposterous in the face of such a large hard to move Earth?

    The irony has been oft noted, and it is worth noting again, as you did. The evidence does not seem to me to support either a strong belief in or strong dismissal of either partially known mechanism, since so many “other things” of the phrase “other things being equal” are unknown, conjectural, etc.

    What makes the discussion interesting instead of vapid is the possibility that an effect that is small on the absolute scales may be large relative to the good or optimal range for agriculture, wildlife, ocean surface level (for humans) and so forth.

    Figure 4 of the main post would be enhanced if accompanied by some measure of what the procedure would produce in a time series with no signal at all (i.e., standard errors of the estimates, confidence bands from simulations without a signal, and so forth.) The message here seems to be: If the signal is present at all, it is for sure small. Why the author believes that the method necessarily underestimates the signal is not explained ( ” Considering that the slow FT tends to understate the actual signal amplitude at low signal to noise ratios,”); considering that this problem has been reworked, I’d expect that any presentation has resulted from a method that is biased towards overestimating the effect.

  168. Matthew R Marler says:
    July 31, 2014 at 11:33 am
    . . . .The message here seems to be: If the signal is present at all, it is for sure small. Why the author believes that the method necessarily underestimates the signal is not explained ( ” Considering that the slow FT tends to understate the actual signal amplitude at low signal to noise ratios,”); considering that this problem has been reworked, I’d expect that any presentation has resulted from a method that is biased towards overestimating the effect.
    ———————————————————-
    When the Slow FT method was used on test data with 10 year period and 1/10 signal to noise ratio, it barely revealed the signal and obtained a peak about 20% smaller than the amplitude of the test data. The underestimate was progressively less at higher signal/noise ratios.

  169. Like I said. trace Watts

    “Here is the irony. If these tiny tiny amounts of solar variation somehow (of unknown mechanism) control the largest processes on Earth that create weather and climate, how do they so dismissively disregard tiny CO2 increases (of known mechanism)? Are not both propositions preposterous in the face of such a large hard to move Earth?”

  170. The answer is the sun is the engine of earth’s climatic system therefore any change in it will change the climate of the earth through primary and secondary effects.

    The historical record of solar activity versus global temperatures shows this to be the case. The data shows that each time the sun enters a prolonged solar minimum period of activity the average temperature trend for the globe over that time is down and each time the sun enters a prolonged period of active activity the average temperature trend for the globe is up. Pretty clear cut.

    The same thing will be happening this time as this decade proceeds.

    Still there will be those as there are now in the face of the data that will still insist this just is not so.

    In the meantime I expect my climate forecast will be correct in general terms ,although specifics can’t be known.

    The climate forecast is the global temperature trend will be down and persistence in weather patterns will increase due to primary and secondary effects of prolonged low solar activity. This persistence in weather patterns much more prevalent post 2005 when solar activity diminished significantly.
    Which means expect deviations in precip/ temp. patterns both up/down but the overall temp. trend for the globe to be lower.

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