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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Deanster
Are you not “calling the kettle black“?
Lets have some civility here. Try some positive criticism rather than ad hominem attacks.
Spencer’s key insight is showing that natural causes with three quantitative measures (PDO, AMO, SOI) can accurately model future temperatures given future measures of those parameters – independently of CO2 concentrations. Spencer’s model has precisely shown “skill with regards to predicting future climate.” That in itself is a sea change in modeling compared to IPCC’s “90% probability” of anthropogenic caused warming.
Don Easterbrook has taken a similar approach and predicted sawtooth global temperatures over the next century based on 60 year PDO cycles. His method could then be applied to modeling Spencer’s three indices to give future projections. Spencer’s derivative model gives a major physical cause to temperature change, not just correlation. His tuning over the first data range to predict over the second range is sound methodology.
Lucia at the Blackboard is quantifying global temperature distributions and their statistical agreement/departure from the IPCC projections.
That methodology can be applied to Easterbrook’s and Spencer’s models.
Future work can then identify the causes of the very complex chaotic phenomena of ocean and atmospheric variations. Lack of that understanding does not negate Spencer’s discoveries of causation by natural fluid phenomena.
So what constructive comments or competitive models can you provide?
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?
It has been done already, and by the UN !:
ftp://ftp.fao.org/docrep/fao/005/y2787e/y2787e08.pdf
I’ve done a lot of these kind of correlations and have all this data. I think there might be an issue with how the methodology was implemented.
For example, in 2009, the SOI Index was -0.12 (CPC index), the Nino 3.4 Index was 0.471, the AMO index was 0.073, the PDO Index was -0.613. The combination of those indices or an accumulation cannot explain NH Land temperatures at +0.805C in 2009.
They have all cycled upward since 1975 and can explain part of the change since that time but they wouldn’t be able to explain the 1.0C or so of increase.
If we are beginning a Dalton or Maunder like minimum we should not worry about any past model made global warming, but how to handle the next world and not modelled deep cooling.
I am happy to have attended the same high school (SAHS) and university (LSSU) though not at the same time as Dr. Spencer.
I’d like to see the graphics with uncertainty bars so as to understand a bit more on how close the CRU and the project lay against each other. Statistical data on the model would be nice whenever the results are offered. I’d also like to see the model training period end in 1940 so as to avoid any argument that it reflects anthropomorphic forcings associated with CO2 increases.
The author of the published paper by FAO is:
Klyashtorin, L.B.
Climate change and long-term fluctuations of commercial catches: the possibility of
forecasting.
FAO Fisheries Technical Paper. No. 410. Rome, FAO. 2001. 86p.
ftp://ftp.fao.org/docrep/fao/005/y2787e/y2787e00.pdf
Nice photo but aren’t the apparent diameters of the Moon and Sun approximately equal when viewed from the Earth?
During the so-called “training period”, the model performs very poorly, reproducing neither the interannual variability or the overall pattern of temperature change seen in the observations. The real world saw the northern hemisphere temperature anomaly vary from as low as -0.7°C to as high as about 0.3°C. The model varies only from -0.2°C to +0.2°C. In addition, the model anomalies are lower in 1920-1935 than in 1900-1920. This is the opposite of what happened in the observations.
Given that the model performs so badly during its so-called “training period”, I see no value in any extrapolation to different periods of time.
Thanks, Roy Spencer, for this enlightening article. I have no doubts about the natural origin of climate change and it is the main argument that I managed in my conference on Climate Change and Biodiversity the last June 2nd. Among the pertinent scientific presentations on the physics of climate, I demonstrated how climate changes have favored the expansion of biodiversity, far from damaging or contracting it.
I think before we can even contemplate any prediction of the future we must have a very solid understanding of the past, clearly the contribution of the satellites has been vital to expanding our knowledge and allowed us to measure many parameters which we had no means of even a rough estimate prior to 1979.
With regard to the top 700 meters of ocean the Argo float buoys were not fully deployed until 2004 thus our understanding of the ocean currents is still in its infancy. The effect of the extremely complex and ever changing gravitation forces within our solar system have been credited with effecting the ocean currents I look forward to more research being done in this area.
Dr. Spencer has once again given us an excellent evaluation and novel approach based on sea surface data and I too was hoping there would be some predictions but then realized this would be premature. Nowhere near as premature as the predictions issued by the IPCC in the 80’s but then the IPCC is a political body and UAH one of the finest scientific establishments in the world and political bodies are famous for delivering wild unsubstantiated propaganda to back up their hidden agendas.
@David Halliday
In both cases – anti or pro – the proportion of believers to skeptics is irrelevant.
Science is not a matter of consensus, which is the realm of politics. Science is the realm of what is logically connected to what is already known, what is testable and thereby is falsifiable.
The *beliefs* of human beings have rarely, if ever, been included in these latter categories. Hence, science has a long history of the lone maverick being right (or at least less wrong) and the majority being wrong.
However, you were right to question Mr Spenser’s resort to that particular fallacy.
tallbloke says:
June 8, 2010 at 7:02 am
“Are we to take away the idea that the oceanic cycles are controlled by the sun and moon?? ”
Spencer says he is avoiding that by purpose.
Then you avoid the discussions you would otherwise would get on that matter. Why fog the discussion with that issue?
When more and more people realise that it behave like a closed loop, you can, as a different matter, discuss the external forces, if any.
Like Svensmarks theory on cloud formations. Or whatever mechanisms that is behind it. I think Shavivs curves on correlations between cosmic rays and temperature over 500 million years at least should be of some interest. Yes, surely correlation is not neccessarily causation, that is true. But it gives a reason for investigation.
Look at fig.2;
http://www.phys.huji.ac.il/~shaviv/Ice-ages/GSAToday.pdf
Steven H says:
June 8, 2010 at 8:36 am
Nice photo but aren’t the apparent diameters of the Moon and Sun approximately equal when viewed from the Earth?
Indeed, if the observer stands on the surface of the Earth. However, if the observer is out of the Earth, i.e. in the space, the virtual scene is of a Moon which is bigger than the Sun. This virtual scenery was beautifully expressed by the artiste on his canvas. 🙂
I beg your pardon….what warming are you talking about?
Coincident with the modern solar maximum … Weird.
Deanster says:
June 8, 2010 at 4:27 am
“So the question stands, are you working on ways to predict these cycles in terms of directions and magnitude of change? Also … “publish”!!!”
Deanster, if you read Specers book “The great climate blunder” you will get the full picture. You would then also know that Spencers paper is coming very soon.
There is no need to predict anything any further that a few years, since the sensitivity is so small, is there? All you need to know is whether you need to invest in winther-equipment or not for the next few years. ( Hint: Yes, you do )
And the mechanism that leads to an Ice Age, why predict that?
Its like predicting your own expiry-date.
Do you really want to know?
So, back to combat malaria!
Ted says June 7, 2010 at 10:01 pm:
Ted, these are not necessarily opposing arguments. The PDO, AMO and SOI are phenomena in themselves, driven essentially by the sun. They are only patterns of variability, not causes in and of themselves. They are intermediates in the whole process, where they APPEAR to cause weather/climate, but not initial causes themselves. They can’t and don’t exist except within the overall heating pattern that begins with the Sun.
In the first graph, indicies should be indices.
Dr. Spencer,
Various web sites define these indexes as:
[Note that air pressure is dependent upon, and therefore a proxy for, temperature.]
So what you’ve done is to correlate, um, temperature to temperature. And you found a close correlation! Well done!
Now kindly use this to predict future temperatures. Please extend your graph and your model to predict temperatures through the year 2060. Oh, wait, we have to wait until 2060 to do that, so that you have the temperature readings with which to predict the temperature readings.
Also, kindly explain the mechanism (other than hand waving, magic, and climate gremlins) that is actually causing the warming. You’ve described it. You’ve quantified it. You’ve “predicted” it based on a correlation to three temperature based indexes. But explain it. How does a planet with a relatively stable climate suddenly, dramatically warm?
Mark says:
June 7, 2010 at 11:18 pm
Could we please clarify once and for all whether models are useful or useless. Or are they only one or the other depending on whether we like what they say?
_____________________________________________________________________
Models are a tool and like any other tool they can be misused. Models however are NOT scientific facts and Dr. Spencer is not calling this “model” a fact.
It’s painfully obvious that this model is completely useless and wrong because:
1. It does not use the latest supercomputer technology.
2. It does not employ a mutated version of Principle Component Analysis.
3. It does not invert any of the input data series.
QED
The temperature differential of about 0.3*C is about what various calculation predict for the influence of increased pCO2 ….
***********
Sphaerica says:
June 8, 2010 at 9:54 am
Dr. Spencer,
Also, kindly explain the mechanism (other than hand waving, magic, and climate gremlins) that is actually causing the warming. You’ve described it. You’ve quantified it. You’ve “predicted” it based on a correlation to three temperature based indexes. But explain it. How does a planet with a relatively stable climate suddenly, dramatically warm?
**************
Can anyone explain why space is warped by gravity? Einstein’s equations only describe the shape of space in a gravitatinal field, not why it does it. It explains how the G.F. modifies time, but not why. Why is almost never addressed in science.
Gail Combs,
And whom, anywhere, any when, has ever said that models, or any specific model, is a fact? You made that up.
You either believe it is appropriate to use models in science, or you believe it is inappropriate. So don’t dodge the question. Which is it?