Evidence of a Significant Solar Imprint in Annual Globally Averaged Temperature Trends – Part 1

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

NOTE: This essay represents a collaboration over a period of a week via email between myself and Basil Copeland. Basil did the statistical heavy lifting and the majority of writing, while I provided suggestions, reviews, some ideas, editing, and of course this forum. Basil deserves all our thanks for his labor. This is part one of a two part series.  -Anthony


Evidence of a Significant Solar Imprint in Annual Globally Averaged Temperature TrendsBy Basil Copeland and Anthony Watts

It is very unlikely that the 20th-century warming can be explained by natural causes. The late 20th century has been unusually warm.

So begins the IPCC AR4 WG1 response to Frequently Asked Question 9.2 (Can the Warming of the 20th Century be Explained by Natural Variability?).  Chapter 3 of the WG1 report begins:

Global mean surface temperatures have risen by 0.74°C ± 0.18°C when estimated by a linear trend over the last 100 years (1906-2005). The rate of warming over the last 50 years is almost double that over the last 100 years (0.13°C ± 0.03°C vs. 0.07°C ± 0.02°C per decade).

Was the warming of the late 20th century really that unusual?  In recent posts Anthony has noted the substantial anecdotal evidence for a period of unusual warming in the earlier half of the 20th century.  The representation by the IPCC of global trends over the past 100 years seems almost designed to hide the fact that during the early decades of the 20th century, well before the recent acceleration in anthropogenic CO2 emissions beginning in the middle of the 20th century, global temperature increased at rates comparable to the rate of increase at the end of the 20th century.

I recently began looking at the longer term globally averaged temperature series to see what they show with respect to how late 20th century warming compared to warming earlier in the 20th century.  In what follows, I’m presenting just part of the current research I’m currently undertaking.  At times, I may overlook details or a context, or skip some things, for the sake of brevity.  For example, I’m looking at two long-term series of globally averaged annual temperature trends, HadCRUTv3 and GHCN-ERSSTv2.  Most of what I present here will be based on HadCRUTv3, though the principal findings will hold true for GHCN-ERSSTv2.

I began by smoothing the data with a Hodrick-Prescott (HP) filter with lambda=100.  (More on the value of lambda later.) The results are presented in Figure 1.

essifigure1

Figure 1 – click for a larger image

The figure shows the actual data time series, a cyclical pattern in the data that is removed by the HP filter, and a smoothed long term low frequency trend that results from filtering out the short term higher frequency cyclical component. Hodrick-Prescott is designed to distinguish short term cyclical activity from longer term processes.

For those with an electrical engineering background, you could think of it much like a bandpass filter which also has uses in meteorology:

Outside of electronics and signal processing, one example of the use of band-pass filters is in the atmospheric sciences. It is common to band-pass filter recent meteorological data with a period range of, for example, 3 to 10 days, so that only cyclones remain as fluctuations in the data fields.

(Note: For those that wish to try out the HP filter, a freeware Excel plugin exists for it which you can download here)

When applied to globally averaged temperature, it works to extract the longer term trend from variations in temperature that are of short term duration.  It is somewhat like a filter that filters out “noise,” but in this case the short term cyclical variations in the data are not noise, but are themselves oscillations of a shorter term that may have a basis in physical processes.

For example, in Figure 1, in the cyclical component shown at the bottom of the figure, we can clearly see evidence of the 1998 Super El Niño.  While not the current focus, I believe that analysis of the cyclical component may show significant correlations with known shorter term oscillations in globally averaged temperature, and that this may be a fruitful area for further research on the usefulness of Hodrick-Prescott filtering for the study of global or regional variations in temperature.

My original interest was in comparing rates of change between the smoothed series during the 1920’s and 1930’s with the rates of change during the 1980’s and 1990’s.  Without getting into details (ask questions in comments if you have them), using HadCRUTv3 the rate of change during the early part of the 20th century was almost identical to the rate of change at the end of the century. Could there be some sense in which the warming at the end of the 20th century was a repeat of the pattern seen in the earlier part of the century?  Since the rate of increase in greenhouse gas emissions was much lower in the earlier part of the century, what could possibly explain why temperatures increased for so long during that period at a rate comparable to that experienced during the recent warming?

As I examined the data in more detail, I was surprised by what I found.  When working with a smoothed but non-linear “trend” like that shown in Figure 1, we compute the first differences of the series to calculate the average rate of change over any given period of time.  A priori, there was no reason to anticipate a particular pattern in time (or “secular pattern”) to the differenced series.  But I found one, and it was immediately obvious that I was looking at a secular pattern that had peaks closely matching the 22 year Hale solar cycle.  The resulting pattern in the first differences is presented in Figure 2, with annotations showing how the peaks in the pattern correspond to peaks in the 22 year Hale cycle.

Besides the obvious correspondence in the peaks of the first differences in the smoothed series to peaks of the 22 year Hale solar cycle, there is a kind of “sinus rhythm” in the pattern that appears to correspond, roughly, to three Hale cycles, or 66 years.  Beginning in 1876/1870, the rate of change begins a long decline from a peak of about +0.011 (since these are annual rates of change, a decadal equivalent would be 10 times this, or +0.11C/decade) into negative territory where it bottoms out about -0.013, before reversing and climbing back to the next peak in 1896/1893.  A similar sinusoidal pattern, descending down into negative annual rates of change before climbing back to the next peak, is evident from 1896/1893 to 1914/1917.  Then the pattern breaks, and in the third Hale cycle of the triplet, the trough between the 1914/1917 peak and the 1936/1937 peak is very shallow, with annual rates of change never falling below +0.012, let alone into the negative territory seen after the previous two peaks.  This same basic pattern is repeated for the next three cycles: two sinusoidal cycles that descend into negative territory, followed by a third cycle with a shallow trough and rates of change that never descend below +0.012.  The shallow troughs of the cycles from 1914/1917 to 1936/1937, and 1979/1979 to 1997/2000, correspond to the rapid warming of the 1920’s and 1930’s, and then again to the rapid warming of the 1980’s and 1990’s.

While not as well known as the 22 year Hale cycle, or the 11 year Schwabe cycle, there is support in the climate science literature for something on the order of a 66 year climate cycle.  Schlesinger and Ramankutty (1994) found evidence of a 65-70 year climate cycle in a number of temperature records, which they attributed to a 50-88 year cycle in the NAO.  Interestingly, they sought to infer from this that these oscillations were obscuring the effect of AGW.  But that probably misconstrues the significance of the mid 20th century cooling phase.  In any case, the evidence for a climate cycle on the order of 65-70 years extends well into the past.  Kerr (2000) links the AMO to paleoclimate proxies indicating a periodicity on the order of 70 years.  What I think they may be missing is that this longer term cycle shows evidence of being modulated by bidecadal rhythms.  When the AMO is filtered using HP filtering, it shows major peaks in 1926 and 1997, a period of 71 years.  But there are smaller peaks at 1951 and 1979, indicating that shorter periods of 25, 28, and 18 years, or roughly bidecadal oscillations.  There is a growing body of literature pointing to bidecadal periodicity in climate records that point to a solar origin.  See, for instance, Rasporov, et al, (2004).  A 65-70 year climate cycle may simply be a terrestrial driven harmonic of bidecadal rhythms that are solar in origin.

In terms of the underlying rates of change, the warming of the late 20th century appears to be no more “unusual” than the warming during the 1920’s and 1930’s.  Both appear to have their origin in a solar cycle phenomenon in which the sinusoidal pattern in the underlying smoothed trend is modulated so that annual rates of change remain strongly positive for the duration of the third cycle, with the source of this third cycle modulation perhaps related to long term trends in oceanic oscillations.  It is purely speculative, of course, but if this 66 year pattern (3 Hale cycles) repeats itself, we should see a long descent into negative territory where the underlying smoothed trend has a negative rate of change, i.e. a period of cooling like that experienced in the late 1800’s and then again midway through the 20th century.

essifigure2

Figure 2 – click for a larger image

Figure 2 uses a default value of lambda (the parameter that determines how much smoothing results from Hodrick-Prescott filtering) that is 100 times the square of the data frequency, which for annual data would be 100.  This is conventional, and is consistent with the lambda used for quarterly data in the seminal research on this technique by Hodrick and Prescott.  I’m aware, though, of arguments for using a much lower lambda, which would result in much less smoothing.

In Part 2, we will look at the effect of filtering with a lower value of lambda.  The results are interesting, and surprising.

Part 2 is now online here

NEW An update to this has been made here:

evidence of a lunisolar influence on decadal and bidecadal oscillations in globally averaged temperature trends

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anomdebus
March 26, 2008 2:50 pm

You state:

it shows major peaks in 1926 and 1997

and

But there are smaller peaks at 1951 and 1979,

yet the graph in figure 2 does not show a peaks at 1926 and 1951, but 1936/1937 and 1958/1957
Could you clear this up, please?
Thanks

Basil
Editor
March 26, 2008 3:06 pm

anomdebus,
That statement is in reference to the AMO, not temperature. We didn’t present a chart showing those numbers. In the section you are reading from, we are comparing what we’ve found with what others have found indicating a long ~66 year climate cycle.
Does that clear it up?
Basil

anomdebus
March 26, 2008 3:21 pm

Basil,
Yes that does, thank you. I think I was letting my primate pattern making skills override my reading skills. 🙂
Thanks again.

March 26, 2008 3:52 pm

Thanks for your very fine work. You have been putting a lot of work into finding the truth, and the lies, and all of us appreciate it.
On catholicfundamentalism.com there are frequent references to Global Warming, not because it’s real, but because those who tell lies for money, position, and power are condemning their souls to perdition.
There is a spiritual component to this, and we can’t forget to pray for those who lack the strength or morals to seek the truth.

Jim Arndt
March 26, 2008 4:03 pm

Hi,
Basil what TSI source are you using? Hopefully not Hoyt. I think there are many current TSI sources available but Hoyt seems not to fit the current trend. Very nice piece of work though. I have also found that there might be a link to magnetism meaning that the earths magnetic field concentrates the PDE which breaks up the cloud forming nuclei when the TSI peaks. See the RSS map and magnetic field map. Very interesting and still very much work in progress.
http://www-atlas.usgs.gov/articles/geology/a_geomag.html#one
http://www.remss.com/msu/msu_data_monthly.html?channel=tlt

Editor
March 26, 2008 4:21 pm

Basil, Anthony:
This is a great piece of work. I had just started playing around with taking the first derivative of smoothed time series, but had not explored filtered series as of yet. This will send me into whole other directions. But I want to see part II first!

Gary Gulrud
March 26, 2008 4:25 pm

Rico:
“indicate that your assumption that solar irradiance is coupled with temperature through a single mechanism (which is what the assumption of a single trend requires)…
i.e., how good it actually was at distinguishing the short-term “noise” from the actual trend.”
I don’t believe this analysis is at all cogent. If the purpose were to look at the incoming TSI and the PDO/AMO (or other/additional oscillations), as a TSI history, in a component analysis with the end being to create a polynomial fit, it would, but that is not here entertained. Indeed, a differential equation seems a better goal altogether than the one you envision.
Pattern recognition appears to be the sole objective here.
REPLY: “Pattern recognition appears to be the sole objective here”
That’s the best description one could make for what this is about. Find the pattern present first, detailed analysis comes later. – Anthony

Andrew
March 26, 2008 4:31 pm

Fascinating! You are skilled at what you do, guys! I’m currently revisting older work on solar right now. This new finding supports what I have generally found based on that work. Can’t wait for the conclusion!

Pamela Gray
March 26, 2008 4:42 pm

Maybe I can shed some light on finding cycles within what appears to be steady state noise. In my research, synaptic brain response to auditory signals as measured by electrode pickup on the scalp can only be found by filtering out the background static noise of the brain. Our brains fire all the time in a fairly random and steady state when we are just chillin, as in not thinking or listening to anything (that’s how we know we are not brain-dead). This noise can be mathematically reduced (filtered out) to a narrow band of “zero” and even smoothed out to near zero (in simple terms adding negatives and subtracting positives so that random becomes zero), leaving space above and below for patterned or cyclic responses, if they occur. Now we add a series of clicks or pips to the ears, and presto: out comes a series of waves (measured electrical synaptic jolts) that can be measured for slope, peak amplitude, and time, as well as corresponded to the major synaptic junctions of the auditory neural pathway. We can even determine the frequency of the tone pip that was sent down the pathway. Higher frequencies result in earlier wave peaks, lower frequencies result in later wave peaks. Until filtering was used, the very small but PATTERNED auditory neural pathway responses hid behind a veil of random static noise. You just never know what you will find when you filter out random stuff. Gold miners used basically the same principal by filtering and washing out dirt to get to the nuggets.

Raven
March 26, 2008 4:50 pm

Bill Illis (13:33:12) : says:
“Now that the global warming community has bullied Judith Lean into reconstructing her solar reconstructions at least three times now and the latest numbers show hardly any solar variation whatsoever, it is clear that the global warming community is going to re-write every historical record there is until only CO2 matters.”
There are good scientific reasons for the change that have nothing to do with climate science. In fact, the new solar data actually problems for the warmers because now they cannot argue that the LIA and MWP were caused by changes in the sun that are not occurring today. IOW – warmers cannot argue that CO2 is the only plausible explaination for the warming today if they don’t know why warming occurred in the past.

Al
March 26, 2008 6:04 pm

“IOW – warmers cannot argue that CO2 is the only plausible explaination for the warming today if they don’t know why warming occurred in the past.”
They used the history-erasing hockeystick to essentially eliminate all vaguely recent historical warming.

Deanster
March 26, 2008 6:29 pm

Basil .. Anthony …
I’ve seen this before!!!
When you mentioned a cycle of 65-70 years, Landscheidts Big Fingers immediately came to mind! I went back to John Daly’s site and re-read his article, and sure enough .. there it is.
“Cycles of big fingers have a mean length of 35.8 years (178.8 years [big hand] / 5 = 35.76 years [big fingers]). They are closely connected with solar activity. They coincide with maxima and minima in the Gleissberg cycle and open up the possibility of predicting these crucial phases many years ahead [62, 63]. As will be shown below, they also define the length of the 22.1-year magnetic cycle of sunspot activity (Hale cycle). ”
What was really interesting is the link between the 60-70 year cycle and an influence on the Hale Cycle. …. hmmmmmmm
I know some people think Landscheidt was a kook because he played with Astrology .. but I can’t help but wonder, why is it that I keep seeing other research unknowingly confirm what he did.

March 26, 2008 6:49 pm

I am inclined to suspect that the recent stabilization in global temperatures may well merely reflect the launch of the Aqua satellite, launched 2002.
What happens is that whenever the data looks unfavorable to anthropogenic global warming, people cast about until they find a possible source of error. If you look hard enough, you can always find a *possible* source of error. Then they pull an error term out of their asses, and “correct” the data till it is politically correct. Eventually someone gets around to making a measurement that is proof against this potential source of error. (Aqua’s orbit does not drift) “Corrections” of older data sources then rapidly converge to agree this new more error resistant source of data – but the old “corrections” continue to be applied to historical data.
Satellites directly measure global temperatures against an absolute standard. The last remaining source of wiggle room was orbit drift, and Aqua does not drift, so since 2002, and *only* since 2002, we have unchanging thermometer in the sky measuring the whole globe, except for the poles.

Bruce
March 26, 2008 7:13 pm

Actually, more sunshine has been reaching the earth since the early 1990’s.
“Variations in solar radiation incident at Earth’s surface profoundly affect the human and terrestrial environment. A decline in solar radiation at land surfaces has become apparent in many observational records up to 1990, a phenomenon known as global dimming. Newly available surface observations from 1990 to the present, primarily from the Northern Hemisphere, show that the dimming did not persist into the 1990s. Instead, a widespread brightening has been observed since the late 1980s. This reversal is reconcilable with changes in cloudiness and atmospheric transmission and may substantially affect surface climate, the hydrological cycle, glaciers, and ecosystems. ”
http://www.sciencemag.org/cgi/content/abstract/308/5723/847

Arnost
March 26, 2008 7:18 pm

Anthony / Basil
Just FYI, the authors of this paper did something similar with the Chinese temperature records and also found cycles of similar lengths. So there is some support out there…
http://www.crikey.com.au/Media/docs/Zhen-Shan–Xiuan-MeteorAtmosPhys-2007-d1227bc1-3183-456f-a935-69c263af1904.pdf
It did not pass unnoticed as WC had a brief look at it on Stoat, and by the looks of it, Lubos also had something on it:
http://scienceblogs.com/stoat/2007/08/multiscale_analysis_of_global.php
cheers
Arnost

Bruce
March 26, 2008 7:20 pm

By the way, there is a difference between TSI and solar radiation reaching the earth.
http://www.timesonline.co.uk/tol/news/uk/article696586.ece
Consider the UK in 2006:
http://www.metoffice.gov.uk/climate/uk/2006/sunshine.html
As much as 70% above normal in 2006.
Or, long term:
http://www.metoffice.gov.uk/climate/uk/about/UK_climate_trends.pdf
“Table 12 shows the percentage change in sunshine, based on a linear trend starting from 1929. It shows that the greatest and most significant changes occurred in the winter season, when there has been an increase in sunshine of about 20% for central and northern England.
Sunshine has also increased in these areas by about 10% in autumn, and by 8% over the year as a whole for eastern and NE England. These increases could be a result of the Clean Air Acts of 1956 onwards, which has led to a decrease in air pollution.”
Cleaning up of air pollution …

Basil
Editor
March 26, 2008 7:42 pm

Jim Arndt,
This discussion took a wrong turn somewhere. We’re not looking at irradiance. There’s casual mention of it by Anthony in a general remark at the beginning of the discussion, but if that’s the source, it reads something into what Anthony said that I don’t think he meant. Some other commenters have gone off on their own tangent about irradiance and what the data is for it, and so forth, but we’re not going to infer anything about irradiance that I know of. In fact, in an early reply in the discussion I put a little 🙂 after a remark about infering a rather different physical basis for what we think our findings may be showing.
Rico,
We’ll explain more about lambda in Part II. But why do you ask about tau? What is your understanding of the role it plays in HP filtering?
I understand well what is required to pass peer review, and we’re only just getting started on this. I can see where this work needs to interact with some of the references you cite, but not others. And I have a long bibliography I’m compiling of numerous others. Which brings me back to “c” in your list of expectations for Part II. What sources might I have overlooked that show relationships between Hale cycles and temperature trends? Even if there are others, are you saying that corroborating work that may only advance the state of knowledge or understanding incrementally is a waste of time? Actually, based on what we’ll present in Part II, I think what we are doing goes beyond that, but I don’t really understand the basis for your skepticism.
Basil
REPLY: I never meant to imply irradiance was used in this essay. I used the term in talking about how I think the climate system can look much like an electrical circuit, with irradiance being part of that, voltage for example…and that all came from thinking about bandpass filters. I’m an amatuer radio operator so I tend to think along tose lines. – Anthony

Jim Arndt
March 26, 2008 8:11 pm

Hi,
Basil and Anthony, Thank you for making that clear. Many people use the Hoyt and it not in line with the current thinking in TSI reconstructions. Just wanted to make sure. Keep it up and I am waiting in earnest for part II.

Mike C
March 26, 2008 8:17 pm

Anthony,
Our friends at NCDC shut off the managing parties field again. They have also taken down the obstruction and exposure information.
REPLY: I’ll look into it.

March 26, 2008 8:25 pm

Related to the latest ice breakage horor story. A puzzle for number phobic environuts. According to
wikipedia
the Ross Ice Shelf moves 1.5 to 3 *meters* a day. Given that rate calculate amount of time it would take to reach New Zealand *if* there is no iceberg breakages.

Roger Carr
March 26, 2008 9:04 pm

Pamela Gray: “Then, in the non-absorbing part of the cycle, it stops soaking up CO2, leaving it to rise into the upper stratum of the atmosphere to get measured by alarmists.”
Beautiful line! m’am.

Jeff Alberts
March 26, 2008 9:20 pm

There are good scientific reasons for the change that have nothing to do with climate science. In fact, the new solar data actually problems for the warmers because now they cannot argue that the LIA and MWP were caused by changes in the sun that are not occurring today. IOW – warmers cannot argue that CO2 is the only plausible explaination for the warming today if they don’t know why warming occurred in the past.

You mean the LIA and MWP they say didn’t happen?

Bob B
March 27, 2008 2:36 am

Basil, the spectral analysis also shows the exact amplitude of each frequency component which you won;t get from a time domain analysis.
BTW I recently favor GaAs transistors

Rico
March 27, 2008 5:11 am

Basil (14:13:53): I do not follow you on this. Any single trend can be the result of multiple independent variables or influences.
It can, but it’s not a necessity. If nothing is known about the nature of the data it could just as easily be the opposite: multiple independent variables or influences could result in different trends. But by using an HP filter you are imposing the single trend assumption when in fact it might not be valid. In math speak, the HP algorithm assumes the signal upon which it is applied is composed of two distinct frequencies whose periodicities are “sufficiently distinguishable” from each other. The filter is highly dependent upon that assumption. That might be appropriate for economic data, but I doubt it’s appropriate for climate data. But if you think it is, then it seems like you should argue your case in some detail. Moreover, it appears to me the results could be highly dependent upon the value of lambda, which essentially serves as the cut-off frequency. In both those regards, I think you should read this paper if you haven’t already.
And perhaps the essential question is: how dependent are the conclusions you make after the second step in your analysis on the lambda value you use in the first step? If they aren’t, then it seems to me you will have to defend your use of a particular value on a technical level. And if you can’t, then I think it could be rightly argued that you are attempting to interpret artifact. But I’ll wait for what you say in Part 2.
As for your later question about the tau (19:42:02), I withdraw my statement. Upon first glimpse of the formula for the HP filter I misinterpreted its meaning. I think I have a better handle on it now. Regarding the question of corroboration, my point was just that you have to fit your results in with those of others that have attempted to analyze the same or similar phenomena. But it sounds like you have a good handle on that.

kim
March 27, 2008 5:31 am

Go see what Pete has in the latest Svalgaard thread.
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