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.

clip_image002

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.

clip_image004

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.

clip_image006

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.

clip_image008

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.

clip_image010

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.)

clip_image012

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.

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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.

[of T=299K]
[of T=288K], of course

kim

I think I’ve never heard so loud
The quiet message in a cloud.
=======================

bones

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)

Pamela Gray

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.

Pamela Gray

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

ren

“Your simple radiation balance is not applicable there and apparently you still don’t understand the concept of thermal inertia. ”
Stan Robertson (bones)
http://weather.unisys.com/surface/sst_anom.gif

Steve Keohane

Very interesting, thank you.

“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.

Leonard Weinstein

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.

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.

bones

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.

Pamela Gray

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.

bones

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.

bones

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.

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.

ren

Where is hiding warm in the oceans?
http://oi60.tinypic.com/2881uo5.jpg

Pamela Gray

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

ren

Where is the latent heat in the atmosphere?
http://www.ospo.noaa.gov/data/atmosphere/radbud/gs19_prd.gif

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.

Pamela Gray

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.

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.

Was there a WUWT post on previous to this enlightening study with an ICCC9 video on it and where did it go this morning?

My mistake

Greg Goomman

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:
http://climategrog.files.wordpress.com/2013/03/icoad_v_hadsst3_ddt_n_pac_chirp.png
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.

Pamela Gray

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

ren

Where had hidden hurricanes in the Atlantic?
http://oi62.tinypic.com/svti5w.jpg

pochas

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.

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.

bones

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.

Greg Goomman

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

Greg Goodman

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:
http://climategrog.files.wordpress.com/2013/03/icoad_v_hadsst3_ddt_n_pac_chirp.png
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.

Greg Goodman

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

Pamela Gray

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.

Pamela Gray

oops. “card” not care

Pamela Gray

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.

Greg Goodman

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.

bones

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

Greg Goodman

Here is an overlay of TLS ( inverted ) and SST for southern hemisphere.
http://climategrog.wordpress.com/?attachment_id=988
Having recognised the origin in the stratosphere changes, the same effect can be seen in SST, with temperature rise taking a few year adjust due to the thermal inertial of the oceans.

Greg Goodman

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.

Greg Goodman

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.

Jim Hodgen

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.

Steve Reddish

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

bones

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.
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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.

richard verney

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.”
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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.
.

MikeUK

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.

Schrodinger's Cat

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.

Schrodinger's Cat

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.

richard verney

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