Warming in Last 50 Years Predicted by Natural Climate Cycles
by Roy W. Spencer, Ph. D.
One of the main conclusions of the 2007 IPCC report was that the warming over the last 50 years was most likely due to anthropogenic pollution, especially increasing atmospheric CO2 from fossil fuel burning.
But a minority of climate researchers have maintained that some — or even most — of that warming could have been due to natural causes. For instance, the Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) are natural modes of climate variability which have similar time scales to warming and cooling periods during the 20th Century. Also, El Nino — which is known to cause global-average warmth — has been more frequent in the last 30 years or so; the Southern Oscillation Index (SOI) is a measure of El Nino and La Nina activity.
A simple way to examine the possibility that these climate cycles might be involved in the warming over the last 50 years in to do a statistical comparison of the yearly temperature variations versus the PDO, AMO, and SOI yearly values. But of course, correlation does not prove causation.
So, what if we use the statistics BEFORE the last 50 years to come up with a model of temperature variability, and then see if that statistical model can “predict” the strong warming over the most recent 50 year period? That would be much more convincing because, if the relationship between temperature and these 3 climate indicies for the first half of the 20th Century just happened to be accidental, we sure wouldn’t expect it to accidentally predict the strong warming which has occurred in the second half of the 20th Century, would we?
Temperature, or Temperature Change Rate?
This kind of statistical comparison is usually performed with temperature. But there is greater physical justification for using the temperature change rate, instead of temperature. This is because if natural climate cycles are correlated to the time rate of change of temperature, that means they represent heating or cooling influences, such as changes in global cloud cover (albedo).
Such a relationship, shown in the plot below, would provide a causal link of these natural cycles as forcing mechanisms for temperature change, since the peak forcing then precedes the peak temperature.
Predicting Northern Hemispheric Warming Since 1960
Since most of the recent warming has occurred over the Northern Hemisphere, I chose to use the CRUTem3 yearly record of Northern Hemispheric temperature variations for the period 1900 through 2009. From this record I computed the yearly change rates in temperature. I then linearly regressed these 1-year temperature change rates against the yearly average values of the PDO, AMO, and SOI.
I used the period from 1900 through 1960 for “training” to derive this statistical relationship, then applied it to the period 1961 through 2009 to see how well it predicted the yearly temperature change rates for that 50 year period. Then, to get the model-predicted temperatures, I simply added up the temperature change rates over time.
The result of this exercise in shown in the following plot.
What is rather amazing is that the rate of observed warming of the Northern Hemisphere since the 1970’s matches that which the PDO, AMO, and SOI together predict, based upon those natural cycles’ PREVIOUS relationships to the temperature change rate (prior to 1960).
Again I want to emphasize that my use of the temperature change rate, rather than temperature, as the predicted variable is based upon the expectation that these natural modes of climate variability represent forcing mechanisms — I believe through changes in cloud cover — which then cause a lagged temperature response.
This is powerful evidence that most of the warming that the IPCC has attributed to human activities over the last 50 years could simply be due to natural, internal variability in the climate system. If true, this would also mean that (1) the climate system is much less sensitive to the CO2 content of the atmosphere than the IPCC claims, and (2) future warming from greenhouse gas emissions will be small.
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I get such a kick out of the IPCC and our own EPA. Both acknowledge that water vapor is the most important greenhouse gas. But they both spend all their energies looking for global warming caused by the inferior greenhouse gases CO2, CH4, N2O and exotic CFCs. If water vapor is so important, why don’t they spend more time anlyzing it? After all, of the 15 million or so substances known to man, one – and only one – substance exists at all times in the climate system in the solid, liquid and gaseous state. That substance is water. It is time for scientists to give water (vapor) the respect it deserves not only as the ideal transporter of energy between oceans and air, and equator and poles, but as supreme ruler of the greenhouse gas kingdom.
Dear Bart and feet2thefire,
Thank you for your comments. It is an interesting discussion (apart from the occasional, albeit minor, flame war).
Bart quoted me as saying: “However, I think the weakness in this post is the idea that decadal oscillations in climate properties are potentially drivers of climate warming over time.”
And then replied: Are you considering constructive and destructive interference effects?
He later added: What he has shown is that the phasing of these natural cycles is such that they constructively interfere in recent times to produce at least a substantial portion of our current warming cycle. What we see in our limited field of view as a secular trend is, in fact, merely an isolated segment of a complex oscillation.
Yes, I did consider that as a possibility: that the PDO, AMO, and SOI result in a complex oscillation, with various combinations constructive or destructive interactions among them. This would mean, as you point out, that the 100 years of data is probably not quite long enough to show the full cycle of their complex interactions.
However, I’m not aware that these three are, individually, predictable oscillations. Are they now, in anything other than a crude sense? Also, I don’t believe that Dr. Spencer made that claim. From my reading he merely showed that these oscillations – when and in what combination they occur – can predict the global anomalies. I may be misreading, though.
I tend to agree with feet2thefire, in that the sun is the ultimate cause of these various oscillations. However, if a pattern of some sort can be established, that would be wonderful. Perhaps, then, the PDO, AMO, and SOI can serve as proxies for the changing cycles of the sun … sunspots, radiance, and wobbles in the Earth’s orbit?
Bart, you mentioned elsewhere that these oscillations are predictable. Can you expand on that? I’ve seen predictions, based on solar forcings, that the next 20 years or so will be somewhat of a cooling trend. Can these oscillations be used to predict the next 5, 10, or 20 years? I would be interested to see that.
Cheers,
-Ted
Re: phlogiston
Are you suggesting clouds & optical extinction have no effect on insolation received by oceans? (You edited out my [time-saving] shortcut: “is basically”.)
More here: http://www.sfu.ca/~plv/SAOT_SO_R.png
[ definitions here: http://www.sfu.ca/~plv/VolcanoStratosphereSLAM.htm – see June 11 update]
If we had more time, we could split hairs further (and probably learn that we do not disagree). Thanks for the note.
Paul Vaughan says:
June 11, 2010 at 4:25 am
My message was somewhat terse since it was written from a mobile phone – thus the editing. Well no of course the ocean heat input from the surface is a huge factor. Its just that I dont think its the only factor – the oceans are deep and big enough to be able to introduce some cyclical changes in heat delivery to the surface and thus “climate”, perhaps as a delayed reaction to patterns of earlier surface heat input.
Willie Soon the astrophysicist from Harvard has done some research where he finds a solar signature in climate patterns over the last century or two (nothing original there) but further, he finds a correlation between temporal patterns of solar input at the Arctic and high latitudes in the Northern Hemisphere, and tropical Atlantic ocean heat and SST patterns a decade or so later. I only read a short interview of his on this and dont have an article to cite. It would be nice if Willie were to post and discuss this here. I like the idea of solar entrainment of ocean cycles. With the considerable work you and others (e.g. tallbloke) have done on analysis of many potential astrophysical periodic climate forcing processes, perhaps you could shed some light on this.
Very interesting post (and website). What I like about Dr Spencer’ s work is that he brings novel ideas in offering additional explanations for the warming of the 20th century. He is a pioneer in trying to force the climatologist community to think outside the AGW paradigm. Of course, as in all pioneering work, there are still lots of questions which still have to be answered concerning the exact mechanisms by which the PDO, AMO and SOI would lead to more cloud cover on a multi-decadal cycle for example. Or what the possible role of increasing/decreasing water vapour content in increasing/decreasing the radiative forcing with multi-decadal oscillations ? Also, the source of the heat for the multi-decadal oscillations has to be determined. The role of the CO2 radiative forcing (with and without feedbacks) also has to be taken into account. Perhaps the measurement of the distribution of the temperatures, salinity and velocities fields in the oceans will allow an estimate of the heat flux coming from the surface of the ocean relative to that coming from the ocean depths. These measurements could allow climatologists to determine the role of the solar and radiative forcings on the increase in heat content of the late 20th century relative to that of the deep ocean circulation.
Bart,
In science, you are not supposed to throw out data without a d&mn good reason, ESPECIALLY NOT the data that has the highest degree of correlation. Dr. Spencer doesn’t give us a compelling reason why he throws out CO2.
As Tom points out, regressions should be done with all available independent variables, but Dr. Spencer picks only 3. If you pick any combination of 3 variables out of the available ones, you will find dozens of regressions with some degree of fit, but the objective is to pick the BEST fit, and that requires including CO2 in the mix.
I have found that a more complete global temperature model (from regressing 14 variables, including SOI and PDO) requires in order of importance, CO2, AMO, El Nino (a proxy for PDO and SOI), sunspot counts (a proxy for total solar insolation and cosmic rays), and the Arctic Oscillation(? go figure), and still 18% of variation is uncorrelated. There are lesser degrees of correlation with other variables as well, but the “confidence level” is less than 95% for them, and sometimes “collinearity” with the above variables bumps them out. (Example: Sunspots AND cosmic rays don’t appear in regression models simultaneously because they are highly correlated with each other, and for the most part one represents the other. Volcanic effects SHOULD correlate, but the confidence level is < 95%.)
Bottom line: Dr. Spencer is "cherry picking" his variables, throwing out the best one.
Not only that, he is "cherry picking" his time span, from 1900 to 1960. I compared a regression of AMO, PDO and SOI over 1900-1960 with one covering 1900-2009. The shorter regression fits pretty well with HadCrut temperature, but the longer time span shows that a predictive factor for long-term temperature increase has been left out. (I propose that this is because the long term warming signal is much smaller over 1900-1960 than 1900-2009, and it gets "covered" by the larger "natural variation" "noise".) He SAYS he is doing it so he can use his model to "predict" the future, but I suspect he does it because he has to to get the answer he wants. To be frank, I suspect he has also cherry-picked his temperature data set (Northern hemisphere instead of global temp) and his methodology (taking the temperature derivative and then reintegrating it on the other side instead of just directly using temperature). If you do enough data manipulation, you will often find some way to force what you want out of it.
In contrast with his method, when I take the 1900-1960 AMO/PDO/SOI vs. Global temp model to "predict" 1961-2009, I find that the prediction deviates from actual temperature more and more with each passing year. The increasing trend line from 1961-2009 is not reproduced by the model. However, when I model 1900-1960 AMO/PDO/SOI/ CO2 vs Global temp, that predicts the 1961-2009 "future temperature" very well. I find that the 60-year model DOESN'T produce the same result.
I disagree about the "elephant in the room". I think it is CO2. I have some friends who simply refuse to accept it. They will walk all around it and steadfastly avoid it and have an open mind about anything else, but vigorously protest that they don’t see the elephant. WRT CO2, their minds are closed off. One of these friends, let’s call him “B”, I’ve found is ignorant of some pretty basic aspects of AGW theory and results, but he steadfastly refuses to read any AGW publications or web sites. He doesn’t even want to consider it. I suspect that 20 years from now as CO2 and temperature still continue to rise, “B” and “F” will continue to attribute it to ABC – anything but CO2.
Have YOU bothered to crack open any part of the IPCC report? Not even the summary document? How can you understand if you don’t look at both sides of the argument? I myself have been (temporarily) persuaded of some things by skeptic web sites only to find that when I look up the same topics on AGW sites, I realize I’ve been swayed by rhetoric and glitzy presentation and not science. You can’t claim to have an open mind if you don’t look at both sides.
phlogiston-
“there is a little-known quantum effect in very deep water”
We are SO needing a reference for that. I admit a skepticism for people throwing around “quantum” claims for this and that.
However, your back of envelope calculation seems reasonable.
KevinUK
Thanks, and sorry. Statistical models are more accessible to the wanna-be armchair scientist. GCMs are beyond my time and capability. For that, I have to take the word of research papers.
Tom,
Thanks for the statistical pointers. I will have to look into that. I’m not a statistician and I’m still learning how to use JMP after switching from MiniTab, and the collinearity indicator I’m accustomed to using isn’t in there.
Back to Kevin,
Let’s not overlook something else that is very important in the IPCC’s models – their forecast for population growth, economic growth (especially in developing nations), and the fuel mix. Without the explosive growth in CO2 emissions due to rapid population growth and geometric economic growth in large-population developing nations, forecasts for temperature increases would be much more subdued. Those inputs themselves are speculative.
For example, a recent report suggests that birth rates are falling faster than predicted in many nations.
From rising commodity prices we can clearly see that this rapid economic growth is putting enormous pressure on industrial resources. Who is to say that commodity prices won’t go so high that they put the brakes on growth.
Their fuel mix forecasts a shift toward cheap and CO2-intensive coal in the worst case as oil and gas become more pricey.
Also wages are beginning to increase rapidly in parts of China. This, too, may very well slow down growth to well below the IPCC’s worst case forecasts.
According to IPCC’s models, the rate of temperature increase doesn’t REALLY take off until about 2040, and a major reason is the multiplicative effect of these three growth factors: population, economic growth, and increasing carbon intensity per megaJoule of energy.
Charles S. Opalek-
The issue with water vapor is that it is highly dependent on temperature. If temp goes down, water vapor decreases within days. If temp goes up, water vapor will increase within days or weeks through evaporation off the oceans. There’s relatively much water vapor in the tropics, much less in deserts, and orders of magnitude less at the poles in winter. Water vapor’s concentration is a feedback on temperature, and so is its greenhouse effect. It magnifies the effect of things that change temperature, but it can’t independently change temperature itself. It is a “slave” to temperature.
CO2, CH4 and N2O are much more independent. Their net removal rate from the atmosphere occurs on a much longer time scale. That is why they get more attention as “GHGs”.
As you say, water vapor must be included in climate models and research. It is one reason for the “climate sensitivity” estimates of 2-4C per doubling of CO2. It is not CO2 that directly causes a 2-4C increase. It increases temperature only a little bit, but the higher temperature also increases water vapor, which in turn increases temperature even more (along with other factors). A similar water-induced sensitivity effect also magnifies changes in insolation, etc.
Ted,
The AMO appears to have roughly an 80 year cycle, but I am not aware that it is predictable.
After rising since the 1970s, it appears to have flattened out again (since about 2000), which may continue for 10-20 years before it begins the downward phase of its cycle. But as you say, 100 yrs data is not enough on which to base a prediction for an 80-year cycle. We might as well be predicting stock prices.
(When I say “flattened out”, I mean its long term moving average. In reality, it jumps up and down quite a bit in the short term.)
This is a little off topic, but it relates to solar forcing.
In a recent paper, paleoclimatic data shows that the tropical monsoon cycle responds very reliably to the ups and downs of Milankovitch insolation forcing on one of the shorter time scales (either 23kyr 65N forcing swings or the 41kyr obliquity cycle, I forget which),
but the ice sheets and sea level and global temperature do not respond directly to those insolation forcings. (Otherwise we might not have a 100kyr ice age cycle.)
The point – the sun isn’t “everything”.
Jbar says:
June 12, 2010 at 8:02 am
“It increases temperature only a little bit, but the higher temperature also increases water vapor, which in turn increases temperature even more (along with other factors).”
Only, it doesn’t, because the formation of clouds dominates, and the overall feedback is negative, as Spencer, Lindzen, and others have shown.
Jbar says:
June 12, 2010 at 7:09 am
“In science, you are not supposed to throw out data without a d&mn good reason, ESPECIALLY NOT the data that has the highest degree of correlation. Dr. Spencer doesn’t give us a compelling reason why he throws out CO2. “
I’m curious, do you think that by pushing your definition of “science” in the preamble, you thereby assume a position of authority by claiming its past successes as your own? Of, maybe you are trying to fool yourself into believing that you are on the side of almighty Science? I got news for you sport: you ain’t foolin’ nobody else.
In any case, you are wrong, wrong, wrong, wrong, wrong. It is sufficient for Spencer to show that another model which does not include CO2 fits the data.
“Have YOU bothered to crack open any part of the IPCC report? Not even the summary document?”
I’ve looked at it in depth. It is a shockingly shoddy document, and the summary for policymakers is pure propaganda.
Jbar says:
June 12, 2010 at 7:20 am
phlogiston-
“there is a little-known quantum effect in very deep water”
We are SO needing a reference for that. I admit a skepticism for people throwing around “quantum” claims for this and that.
However, your back of envelope calculation seems reasonable.
The “quantum” effect was indeed pure bullshit, a light-hearted fabrication – thus the “not” at the end. [Phlogiston et al., J Pure Pseudoscience 1 (1): 1-20, 2010]. The sort of thing that “Daedalus”used to write at the end of New Scientist and Nature.
I’m looking forward to another post about what’s happening to OHC. For my back of envelope calculation I assumed 5% of the ocean (upper200m) with 12C, 95% (200-4000m) with 3C. I ignored the atmosphere, this is equivalent to only the top 7m or so of the ocean. The world’s shallow seas probably increase the proportion of surface water and thus make my 0.4C figure an underestimate, so perhaps something between 0.5-1 degree might more accurate.
Phlogiston,
I guess I missed the “not”. Like your moniker BTW.
Tom,
You made a comment that in my regression of Hadcrut temperature with AMO, PDO, SOI and CO2, you thought that there was a collinearity problem with CO2.
Well, THANKS to your note, I finally got off my kiester and figured out how to turn on the VIF (variance inflation factor) display in JMP. (Wasn’t easy. Unhelpful “help” feature.) The VIF values are all under 1.1, which indicates that none of the independent variables are collinear.
Also the “correlation of estimates” does not indicate any strong correlation between independent variables.
Bart,
I think the statisticians in my company would not agree with you at all. I think that they are more likely to agree with Tom who said that you should include as many variables as you can when trying to understand something as complex as climate. I’ve tried it with up to 14 variables, and CO2 always came out on top. I think Dr. Spencer picked only his 3 variables because it gave him the result he wanted.
It is obvious that if you DON’T want to find out if something is strongly correlated with temperature, you simply don’t look for it. You leave it out of your correlation altogether, just like Dr. Spencer did.
In pointing out that throwing out whatever data you want without a d&mn good reason is strictly verboten in science, “you thereby assume a position of authority”
I’m just pointing out one of the many things that science graduate students have beaten into them during their “rites of passage”.
“I’ve looked at [the IPCC report] in depth. It is a shockingly shoddy document, and the summary for policymakers is pure propaganda.”
Ummm, Bart. Aren’t you assuming a position of authority???
“you are wrong, wrong, wrong, wrong, wrong”
Ummm, Bart. Aren’t you assuming a position of authority???