Basil Copeland and I also found linkages between surface temperature and solar cycles in two articles we published in the last year. We were roundly criticized and ridiculed by warmists mainly due to a statistical error in the first essay, but the base premise remained and the second essay was improved due to that error. I’m pleased to see that NCAR has found other solar to earth linkages, such as this one in ENSO. This is exciting news, but by no means a complete solution to the climate puzzle. There is much more to be learned about this. This is but one connector of the hydra-like patch cable that Dr. Jack Eddy imagined – Anthony
Scientists find link between solar cycle and global climate similar to El Nino/La Nina. Credit: NCAR
Establishing a key link between the solar cycle and global climate, research led by scientists at the National Science Foundation (NSF)-funded National Center for Atmospheric Research (NCAR) in Boulder, Colo., shows that maximum solar activity and its aftermath have impacts on Earth that resemble La Niña and El Niño events in the tropical Pacific Ocean.
The research may pave the way toward predictions of temperature and precipitation patterns at certain times during the approximately 11-year solar cycle.
“These results are striking in that they point to a scientifically feasible series of events that link the 11-year solar cycle with ENSO, the tropical Pacific phenomenon that so strongly influences climate variability around the world,” says Jay Fein, program director in NSF’s Division of Atmospheric Sciences. “The next step is to confirm or dispute these intriguing model results with observational data analyses and targeted new observations.”
The total energy reaching Earth from the sun varies by only 0.1 percent across the solar cycle. Scientists have sought for decades to link these ups and downs to natural weather and climate variations and distinguish their subtle effects from the larger pattern of human-caused global warming.
Building on previous work, the NCAR researchers used computer models of global climate and more than a century of ocean temperature to answer longstanding questions about the connection between solar activity and global climate.
The research, published this month in a paper in the Journal of Climate, was funded by NSF, NCAR’s sponsor, and by the U.S. Department of Energy.
“We have fleshed out the effects of a new mechanism to understand what happens in the tropical Pacific when there is a maximum of solar activity,” says NCAR scientist Gerald Meehl, the paper’s lead author. “When the sun’s output peaks, it has far-ranging and often subtle impacts on tropical precipitation and on weather systems around much of the world.”
The new paper, along with an earlier one by Meehl and colleagues, shows that as the Sun reaches maximum activity, it heats cloud-free parts of the Pacific Ocean enough to increase evaporation, intensify tropical rainfall and the trade winds, and cool the eastern tropical Pacific.
The result of this chain of events is similar to a La Niña event, although the cooling of about 1-2 degrees Fahrenheit is focused further east and is only about half as strong as for a typical La Niña.
Over the following year or two, the La Niña-like pattern triggered by the solar maximum tends to evolve into an El Niño-like pattern, as slow-moving currents replace the cool water over the eastern tropical Pacific with warmer-than-usual water.
Again, the ocean response is only about half as strong as with El Niño.
True La Niña and El Niño events are associated with changes in the temperatures of surface waters of the eastern Pacific Ocean. They can affect weather patterns worldwide.
The paper does not analyze the weather impacts of the solar-driven events. But Meehl and his co-author, Julie Arblaster of both NCAR and the Australian Bureau of Meteorology, found that the solar-driven La Niña tends to cause relatively warm and dry conditions across parts of western North America.
More research will be needed to determine the additional impacts of these events on weather across the world.
“Building on our understanding of the solar cycle, we may be able to connect its influences with weather probabilities in a way that can feed into longer-term predictions, a decade at a time,” Meehl says.
Scientists have known for years that long-term solar variations affect certain weather patterns, including droughts and regional temperatures.
But establishing a physical connection between the decadal solar cycle and global climate patterns has proven elusive.
One reason is that only in recent years have computer models been able to realistically simulate the processes associated with tropical Pacific warming and cooling associated with El Niño and La Niña.
With those models now in hand, scientists can reproduce the last century’s solar behavior and see how it affects the Pacific.
To tease out these sometimes subtle connections between the sun and Earth, Meehl and his colleagues analyzed sea surface temperatures from 1890 to 2006. They then used two computer models based at NCAR to simulate the response of the oceans to changes in solar output.
They found that, as the sun’s output reaches a peak, the small amount of extra sunshine over several years causes a slight increase in local atmospheric heating, especially across parts of the tropical and subtropical Pacific where Sun-blocking clouds are normally scarce.
That small amount of extra heat leads to more evaporation, producing extra water vapor. In turn, the moisture is carried by trade winds to the normally rainy areas of the western tropical Pacific, fueling heavier rains.
As this climatic loop intensifies, the trade winds strengthen. That keeps the eastern Pacific even cooler and drier than usual, producing La Niña-like conditions.
Although this Pacific pattern is produced by the solar maximum, the authors found that its switch to an El Niño-like state is likely triggered by the same kind of processes that normally lead from La Niña to El Niño.
The transition starts when the changes of the strength of the trade winds produce slow-moving off-equatorial pulses known as Rossby waves in the upper ocean, which take about a year to travel back west across the Pacific.
The energy then reflects from the western boundary of the tropical Pacific and ricochets eastward along the equator, deepening the upper layer of water and warming the ocean surface.
As a result, the Pacific experiences an El Niño-like event about two years after solar maximum. The event settles down after about a year, and the system returns to a neutral state.
“El Niño and La Niña seem to have their own separate mechanisms,” says Meehl, “but the solar maximum can come along and tilt the probabilities toward a weak La Niña. If the system was heading toward a La Niña anyway,” he adds, “it would presumably be a larger one.”
Source: National Science Foundation (news : web)
h/t to Leif Svalgaard
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Paul Vaughan (20:49:13) :
Leif Svalgaard (18:50:08) “Other people seem to have difficulty finding the ‘phase reversal’…”
This is pure distortion.
Show me the phase reversal in these plots then!
Chandler period filtered out:
http://img339.imageshack.us/img339/1050/chandlerwobbleyear.jpg
Year period filtered out:
http://img119.imageshack.us/img119/4125/chandlerwobblechandler.jpg
PS I am not impressed with you ability to communicate with other human beings in a civilised fashion.
Paul Vaughan (20:49:13) :
This exchange is terminated. Do not address me in future.
On another thread you suggested that all CO2 readings were false. I tested the theory with one station looking at weekly data and comparing to hourly. Basically I found an approx. 1 week delay in the houly data. There was nothing to show that the CO2 data was truly invalid as you suggested.
I have now checked out you (and your references) assertion that the wobble has a 180 phase shift in the 30’s. It is not present. I have checked another of your plots comparing wobble and rainfall. I cannot obtain the graph of wobble that you did.
Wavelet transforms are taking analysis away from the measured figures made on a 18.25 day schedule (this must mean the data is interpolated already) and adding in a mathematical interpolation between further analysis and reality. Chandler wobble may be a good candidate for this (it is unlikely (but not impossible) that the wobble sinusoid will vary wildly from a pure sinusoid. But this is only an assumption.
Here is what the real data looks like.
http://img265.imageshack.us/img265/1466/chandlerunfiltered.jpg
Difficult to see with all the “noise” – which of course may be signal – but still no phase change!
bill (02:50:10) “On another thread you suggested that all CO2 readings were false.”
This is not true. You have misunderstood (or worse).
I alerted people to the fact that rigid annual structure has been artificially imposed on some monthly CO2 time series and suggested that people use the NOAA time series.
Anyone with the necessary background will easily turn up the same results.
I pointed out the note at the bottom of the CDIAC “data” webpages alerting people of the adjustments. It appears you have not bothered to verify this.
The CDIAC “data” are actually statistics. There is a difference between data & statistics — statistics are summaries of data – i.e. based on calculations made from data.
bill (02:50:10) “[…] references) assertion that the wobble has a 180 phase shift in the 30’s. It is not present.”
You are claiming Jan Vondrak (Vice President International Astronomical Union), a leading authority on the Chandler wobble (& EOP more generally), is wrong about something really simple. It’s child’s play to show the phase reversal (if you know how).
I can spend a bit more time on this if you really want to make a solid effort to understand (something you never did when I patiently sacrificed my time addressing your questions about the CO2 ‘data’).
How are you estimating the period in this plot?
http://img339.imageshack.us/img339/8189/chandlerwobbleaveragepe.jpg
What you have done here?
http://img265.imageshack.us/img265/1466/chandlerunfiltered.jpg
bill (21:23:55) “PS I am not impressed with you ability to communicate with other human beings in a civilised fashion.”
Bold-faced obfuscation meets rejection. It’s simple – and it’s practical.
Reply: Ok everybody tone it down and I have to add the obligatory I don’t care who started it. ~ charles the moderator.
Paul Vaughan (12:56:58) :
bill (21:23:55) “PS I am not impressed with you ability to communicate with other human beings in a civilised fashion.”
Toned down: “by a show of hands, who out there disagrees with ‘bill’?
CO2
“The monthly values have been adjusted to the 15th of each month.” i.e. interpolated between actual measurement days. Not sure why it is done but it should not invalidate data. (hourly data compared to monthly data bears this out.
http://img13.imageshack.us/img13/2339/co2barrowhourvsmonthobs.jpg
The NOAA series is slightly different but not significantly so.
The wobble data is also not actual readings – taking readings 10/20 times per year at exact intervals may now be possible but is very unlikely to have been done in 1800s. Is this data therefore invalid?
Paul Vaughan (12:51:52) :
You are claiming Jan Vondrak … a leading authority on the Chandler wobble (& EOP more generally), is wrong about something really simple. It’s child’s play to show the phase reversal (if you know how).
Name and status do not matter to me. The data I obtained from your reference is shown in the many plots I have shown:
Yearly frequency removed:
http://img119.imageshack.us/img119/4125/chandlerwobblechandler.jpg
Chandler periods removed:
http://img339.imageshack.us/img339/1050/chandlerwobbleyear.jpg
There is no phase reversal shown. So obviously :
1. the data is wrong
2. or I am not displaying the phase Vondrak is measuring
3. or Excel is faulty
4. or The bandpass filter I am using is faulty (a possibility)
5. or Vondrak is wrong
6 or ????
The plot of chandler period (with no annual freq) does show the phase dropping to 15 deg at one of the low amplitude points but this quickly recovers to 90deg when amplitude is restored
(the low amplitude is caused by the two chandler periods shown in the FFT beating together giving a 82 year period (1.17 and 1.19 very APPROX)
How are you estimating the period in this plot?
http://img339.imageshack.us/img339/8189/chandlerwobbleaveragepe.jpg
This was done on zero crossings of y displacement then averaged over a 10 year period to try to get to your period vs rain plot:
http://www.sfu.ca/~plv/ChandlerPeriodAgassizBC,CanadaPrecipitationTimePlot.PNG
I have since changed the plotting to use positive peak to positive peak of y for time (this should be more defined than zero crossing)
and phase measured from
+ve peak y to +ve peak of x
-ve peak y to -ve peak of x
What you have done here?
http://img265.imageshack.us/img265/1466/chandlerunfiltered.jpg
This is the wobble with no filering of high frequency (short period) noise. bandpass filer bandwith is 0.05 to 250 years. It shows 1924 to 1929 noisy signal but the phase of x vs y is the same on entry to this period as on exit from it. The phase during the 1924 -1929 period may be grossly different but at 1923 and 1937 the phase is similar (or at 360 deg).
I can spend a bit more time on this if you really want to make a solid effort to understand (something you never did when I patiently sacrificed my time addressing your questions about the CO2 ‘data’).
You refused to state point blank the problem with the co2 data. I compared monthly and hourly co2 data to try to see what thew problem was:
http://img13.imageshack.us/img13/2339/co2barrowhourvsmonthobs.jpg
This showed no problem.
If you were to state what phase I am supposed to see with respect to what I will look.
There is no point continuing with the cryptic suggestions as my time is as important as yours. and I have no software for wavelet analysis.
Hello bill,
In order to diagnose the source of the misunderstandings, this may have to go back & forth a bit.
I have no doubt that these 2 matters can be sorted out to your satisfaction if you make a solid, patient effort to follow what I have written & what I write.
Let’s slow things down to whatever pace is necessary.
–
CO2
Please provide links to the exact webpages (plural) from which you are getting your data in this plot:
http://img13.imageshack.us/img13/2339/co2barrowhourvsmonthobs.jpg
Thank you.
This should help me localize the source of the misunderstanding. (My impression is that you are investigating something different from what I was commenting about.)
–
Polar Motion
bill (19:47:20) “Name and status do not matter to me.”
Name & status don’t guarantee scientific wins — I (& most here at WUWT I suspect) will whole-heartedly agree.
The more important part was:
“[…] is wrong about something really simple. It’s child’s play to show the phase reversal (if you know how).”
This is no exaggeration.
You need only 2 very simple things to demonstrate the phase reversal:
1) a stationary wave with a period of ~6.4 years.
2) a moving-estimate of the polar motion group-wave (envelope) period as a function of time.
I’ll assume you can handle #1.
There are many ways to obtain #2 (some of them dead-simple).
Suggestion:
Think of x & y as a 2-dimensional vector (instead of as 2 separate time series).
The task is not to compare the phase of x with the phase of y. Please acknowledge that you have understood this before we proceed. Thank you.
Also, before spending time doing a bunch of calculations (that may be heading down a path unrelated to the one we are trying to discuss here), please tell me one or 2 (or 3) ways you might like to go about pursuing item#2. (This will help me assess whether you are focused on the correct task. Thank you bill.)
Regards,
Paul.
bill (19:47:20) “You refused to state point blank the problem with the co2 data. “
I must object to this statement because it is false.
–
bill (19:47:20)
“I have no software for wavelet analysis.”
Do you have Excel?
That’s what I use.
I only resort to using SPlus (& SPSS, depending on the task) when I need higher-quality graphics.
Example of SPlus color-contour plot:
http://www.sfu.ca/~plv/ccLR1CRF.PNG
[featured: time-integrated cross-correlation of Log2(SunspotNumber+1) with cosmic ray flux]
Examples of Excel color-contour plots:
http://www.sfu.ca/~plv/1930sHarmonicPhaseDifference.PNG
http://www.sfu.ca/~plv/SunspotCyclePeriod.PNG
There are some substantial software-design problems with Excel-color-contour-plot-menus, but I’ve found solutions (&/or viable work-arounds) for all of them — feel welcome to enquire if you encounter obstacles.
Cheers,
Paul.
bill,
Here is some information about wavelet analysis and its use for tidal analysis and Chandler Wobble influence:
http://www.geo.uni-jena.de/geophysik/environ/pres_wg06/HU.ppt
bill,
A very useful reference work by Gross and Vondrak:
http://www.leif.org/EOS/1999GL900422.pdf
Of course, no hint of a phase shift.
bill,
And the famous Gross paper form 2000 explaining the excitation of the wobble: http://www.leif.org/EOS/2000GL011450.pdf
The last sentence in a publication is often telling:
“The wide distribution of these atmospheric and oceanic angular momentum estimates by the IERS Special Bureaus for the Atmosphere and Oceans enables the type of interdisciplinary research whose results are reported here.”
Keep in mind the Nasa PR machine (especially when results that leave new questions are publicized as final answers to age-old mysteries).
Keep in mind that SBA & SBO would like to survive & flourish.
Suggested:
Read papers by other authors that give a different treatment (bearing in mind the concept of shared-variance).
And this is telling:
In reviewing Gross’ work (including his 2007 overview in Treatise on Geophysics), pay scrutinizing attention to his treatment of r^2.
bill, I think you will find this a very distracting tangent [if you pursue it now] (but a very interesting one when you have time).
For now, I suggest wrapping up our misunderstanding expeditiously. It has nothing to do with Gross’ 2000 findings (which are limited by the short length of the employed series) and you can manage a basic conceptual understanding without learning wavelet methods – (that can come later, on your own time).
You need only 2 very simple things to demonstrate the phase reversal:
1) a stationary wave with a period of ~6.4 years.
2) a moving-estimate of the polar motion group-wave (envelope) period as a function of time.
Paul Vaughan.
Please provide links to the exact webpages (plural) from which you are getting your data in this plot:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/brw/
http://cdiac.ornl.gov/ftp/trends/co2/barrsio.co2
OK 6.4 years ish is the beat frequency between the chandler wobble and the annual 365.2421897 day
However,there seem to be 2 chandler frequencies 1.15 and 1.19 years as shown in these two plots.
during the 30s the 1.15 slowly displaces the 1.19. I would therefore expect a phase change between the 6.4 fixed period (because that is what you have done) and the mixed chandler frequencies of 1.15+1.19.
however in physical terms all that happens is a slowing down of chandler period during the 30s. I was expecting a phase shift between x and y (i.e. reversal of direction).
Can you confirm that this is your “phase shift”
1.19ish period chandler wobble
http://img411.imageshack.us/img411/576/chandlerwobble119.jpg
1.15ish period chandler wobble
http://img151.imageshack.us/img151/5341/chandlerwobble115.jpg
Leif Thanks for those references!
It is interesting to note that the simple FFT so despised by Paul Vaughan, shows two distinct chandler frequencies. Using a bandpass filter pulls each frequency out of the mix 1 year, 1.15 years and 1.19 years. This seems to be an amazing band pass algorithm for excel. I will have to check it out on some other manufactured data and check for phase accuracy etc.
The same web site has a useful smoothing algorithm (hodrick prescott) which seems to produce a level of filering similar to a moving average with little phase/amplitude distortion compared to the moving average.
http://www.web-reg.de/
bill (10:48:59) “It is interesting to note that the simple FFT so despised by Paul Vaughan, shows two distinct chandler frequencies.
This suggests misunderstandings bill.
To probe them, I will ask 3 questions:
1) Do you think the 2 frequencies you mention are both continuously operating across the record?
2) How do you interpret the bulge around them (in your power spectrum plot)?
3) Have you ever used windowed-FFT?
– –
bill (07:37:27)
“however in physical terms all that happens is a slowing down of chandler period during the 30s.”
That’s part of it.
In order to see a phase reversal, one has to first decide, “relative to what?” If you look relative-to-a-stationary-wave, you will see (even without doing any calculations) that the polar motion group-wave (the envelope) is in ~anti-phase with a stationary wave with a period of ~6.4a before ~1931 and in-phase after (if you phase-align the latter part of the record).
This is equivalent to what Vondrak (& others) showed.
Figure 10 – top of top panel:
http://www.yspu.yar.ru/astronomy/lib/Rotation.pdf
It’s not complicated. I suppose if it is confusing (&/or has confused) people it might have something to do with the nature of the time series (2-dimensional vector with a beat-envelope – i.e. not the type of series (all) folks around these forums are normally used to handling – e.g. temperature time series, sunspot curves, etc.)
It is interesting to note that the (absolute) power falls during the ~20 year phase reversal interval. (This suggests other wavelet transforms – for example timescale-normalized. (The one I presented was time-normalized.)) …So at the time of the Chandler slow down / polar motion envelope phase-shift, the annual wobble played a (relatively) stronger role.
If you now go back through my earlier comments (in earlier threads) you will probably easily see why I took differences & used them to calculate a vector magnitude (makes things simpler). If you go through that exercise & plot the results on a grid with 6.4a (horizontal) spacing, the phase reversal is plain-as-day. [As I said upthread: I only (generally) bother with a wavelet transform if I can already envision that it will provide a concise summary of something I already see. However, unfortunately: Many of the academics I deal with dismiss the wavelet transforms on the grounds that they do not know enough about wavelet transforms to assess them. This certainly creates an “interesting” challenge.]
“slow down”
correction: “speed up”
(We are talking about frequencies & timescales in this exchange – & not always being careful.)
My emphasis added in bold:
“Values above are taken from a curve consisting of 4 harmonics plus a stiff spline and a linear gain factor, fit to monthly concentration values adjusted to represent 2400 hours on the 15th day of each month. Data used to derive this curve are shown in the accompanying graph. Units are parts per million by volume (ppmv) expressed in the 2003A SIO manometric mole fraction scale. The annual average” is the arithmetic mean of the twelve monthly values.”
http://cdiac.ornl.gov/ftp/trends/co2/barrsio.co2
This is the page you need to compare monthly values:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/brw/brw_01C0_mm.co2
Difference both series and study the annual structure comparatively (across years & series). I look forward to hearing what you find.
Also, you are looking at Barrow, Alaska, USA. Recall that I was looking at Alert, Nunavut, Canada when I found the problem.
As previously indicated: There isn’t a problem if you are only interested in the undifferenced trend at super-annual timescales. (I want to make sure there are no misunderstandings.)
I will run the analysis for Barrow now (to make sure there are not further misunderstandings).
Feel welcome to ask any follow-up questions.
Re: bill (10:48:59)
I would be careful about the hazards of moving away from a boxcar kernel. My impression is that there are a lot of misunderstandings out there about moving-window time-integration (including smoothing). The “best” choice of kernel depends on the particular task. Boxcar kernels have some nice harmonic properties that few seem to appreciate (or even be aware of). It could be quite challenging to interpret time-integrated cross-correlation analyses based on kernels that introduce harmonic distortion.
Results of Barrow CO2‘ analysis (note the prime ‘ symbol, which indicates rate of change):
http://www.sfu.ca/~plv/BarrowNOAAprime.png
http://www.sfu.ca/~plv/BarrowCDIACprime.png
http://www.sfu.ca/~plv/BarrowNOAAprimeMinusCDIACprime.png
http://www.sfu.ca/~plv/BarrowCO2primeScatterplot.png
http://www.sfu.ca/~plv/BarrowCO2primeResiduals.png
Note the imposed annual structure for CDIAC. This is important for anyone modeling seasonal fluxes (such as ecosystem carbon modelers I know).
The results for Alert are even more dramatic (as has been discussed previously).
Paul Vaughan (12:03:35) :
I will ask 3 questions:
1) Do you think the 2 frequencies you mention are both continuously operating across the record?
The simple FFT obviously does not show this. I initially assumed that the peaks at 1.18 years were in reality just a bit of FM on the fundamental. However, the BP filter shows 2 discrete frequencies. Reducing the bw of the bp filter to just include the 1.15 year period shows an amplitude of 0.3 relative. the 1.19 year wobble shows an amplitude of 1.2 relative. The 365.25 period has an amplitude of 1.0 relative during the 1930s
The amplitudr of the 1.15 year wobble may be modulate with a 162 year wave.
2) How do you interpret the bulge around them (in your power spectrum plot)?
A with any plot like this more resolution could show individual frequencies however with the data available it shows as noise or perhaps occassional frequency excursions of the main wobbles (there are a few other discrete frequencies in this area.)
3) Have you ever used windowed-FFT?
The built in excel funcion does not have windowing function. However, I often have, as part ogf my work, used such functions on real-time FFTs on DSOs. I do understand that the window type will affect the shape of the spectrum (but not the frequency of the peaks).
In order to see a phase reversal, one has to first decide, “relative to what?” If you look relative-to-a-stationary-wave, you will see (even without doing any calculations) that the polar motion group-wave (the envelope) is in ~anti-phase with a stationary wave with a period of ~6.4a before ~1931 and in-phase after (if you phase-align the latter part of the record).
1. What is the physical manefestation of yourhyperthetical stationary wave vs group wave phase reversal?
2. If I chose 6 years then the phase is continuously changing. before and after the 30s the main wobble is 1.19 years during the 30s the main chandler wobble is 1.15 years. The chandler wobble beats with the 365.25 day annual wobble to create a 6.4y wave. It is obvious that the wave will be longer with 1.15 y (during the 1930s) and shorter (outside the 30s) This will cause a phase shift!
3.In one post to claim that artificial constraints have been applied to CO2 data from CDIAC on on other posts you impose an artificial FIXED period of 6.4 years to get your phase shift. This is inconsistent?
4. There are other frequencies that filtering picks up
~1.2years reasonably constant amplitude over the period of the data.
~1.225 years reasonably constant amplitude over the period of the data.
Missed the other high level wobble period and update on others
1.179 y period with an amplitude of 0.63 rel
1.192y period with an amplitude of 0.68 rel
1.0008y period with an amplitude of 0.601 rel
bill (19:43:50) “The chandler wobble beats with the 365.25 day annual wobble to create a 6.4y wave. It is obvious that the wave will be longer with 1.15 y (during the 1930s) and shorter (outside the 30s) This will cause a phase shift!”
The lights go on. Like I said: It’s simple.
Case closed.