Guest post by James Padgett
Many of you are aware that the concept of continental drift, proposed by Alfred Wegener, was widely ridiculed by his contemporaries. This reaction was in spite of the very clear visual evidence that the continents could be fit together like a giant puzzle.
I think this is where we are in climate science today. There is an obvious answer that many experts cannot see even though a young child would understand when presented with the evidence.
Our current crop of experts cannot see simple solutions. Their science is esoteric and alchemical. It is so complex, so easy to misunderstand, that, like the ancient Greek mystery religions, there is a public dogma and then there are the internal mysteries only the initiated are given access to.
And then there are the heretics who challenge their declared truths.
That isn’t to say that many climatologists aren’t smart. On the contrary, they can be very smart, but that doesn’t preclude them from being very wrong on both collective and individual levels.
One of the most brilliant men alive in the last century, John von Neumann, believed that by the 1960’s our knowledge of atmospheric fluid dynamics would be so great, and our computer simulations so precise, that we’d be able to control the weather by making small changes to the system.
It is true that the climate models used today do a very good job with fluid dynamics, but despite that understanding we can neither predict nor control the weather (and the climate) to the degree he imagined.
An incredible genius, he made a mistake. He didn’t understand the fundamental chaos that made his vision impossible.
In regard to the climate, I hope my simple vision is closer to reality than the excuse-filled spaghetti hypothesis that currently brandishes the self-given title of “settled science.”
My proposal, that climate is primarily driven by solar and oceanic influences, is probably believed by more than a few skeptics, but hopefully I can make a compelling case for it that both small children and climate scientists can understand. To that end I’ll take a quick look at the temperature record from 1900 until the present. I will explain the case for the oceanic/solar model and articulate the excuses given by the anthropogenic camp for the decades that inconveniently do not line up with the hypothesis of carbon dioxide being the primary driver of climate change.
1900-1944:
This period is largely warming. What could possibly be the cause of that?
The sun seems to be the obvious answer. It is so obvious in fact that even most mainstream climatologists admit its influence in these years. Some also say there is an anthropogenic effect in there, somewhere, and they could be right, but it certainly isn’t obvious.
And while the Atlantic is in its cool phase over the earlier part of this period, the largest ocean, the Pacific, is warm,especially in the last couple decades, but when it turns into its cool phase….
1945-1976:
We get 30 years of cooling in the surface station record.
According to proponents of the anthropogenic model, the unprecedented increase in carbon dioxide following World War II was not only masked, but overpowered by sulfate emissions. That is an interesting excuse, but this cooling period exactly matches the cool phase of the Pacific Decadal Oscillation (PDO).
So much so that when it goes into its warm phase in…
1977-1998:
We get 20 more years of warming:
which is kicked up a notch towards the end as the Atlantic goes into its warm phase:
That leaves us with the final period from…
1999-Present:
After the super El Nino of 1998 temperatures have largely flat-lined and perhaps even dropped slightly. Both the Atlantic and Pacific are in their warm phases and the sun remains at the “high” levels following the recovery from the Little Ice Age, but the Pacific seems to be wobbling cooler and cooler as it shifts back into its cool phase.
True we are the “warmest decade on record,” but we are also the only decade on record with both oceans in their warm phases in a time of relatively high solar activity. The only comparable time would be during and around the 1930’s and early 1940’s, around the time of the Dust Bowl, and the sun wasn’t as active back then – and that’s assuming the records are an accurate reflection of global temperatures back then.
So how do climate scientists explain this lack of warming for over a decade? Ah, well they blame the sulfates again – a classic excuse, while others say that the heat has teleported deep into the oceans. I say teleported because there is no record of the journey of that missing heat into those unmeasured depths from the well-measured depths it would normally have had to travel through in order to get to that abyss.
Of course, others say this time period is simply not statistically significant, but the only period of heating we can’t directly trace to the sun, the time from 1977-1998, a mere twenty year period, is certainly statistically significant in some minds.
To that I only have one question for them:
Are you smarter than a 5th grader?
Cheers,
James Padgett
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It’ll be interesting to see if the statement changes over the coming decade:
“
1011121314….etc….years isn’t a significant period to characterize the global temperature…..blah…blah….blah….”So how come can it be the case that 16 years of data can yield a statistically relevant result whereas 15 and 17 years of the same data set cannot?
Because 15 years of data does not contain enough positive (for want of a better word) data to support the hypothesis. With the addition of a 16th year there is enough positive data. But the 17th year contains enough negative data that the data from all 17 years doesn’t have enough positive data (relative to negative data).
Let’s see… statistical significance… Seems I remember something about that from all those stat classes I took. Ok, here’s one on “Statistical Signficance” that gives what I believe to be an easily understood example and might very well be used to determine the answer to this 10 year vs. 20 year question: http://www.statpac.com/surveys/statistical-significance.htm
Then we have WIkipedia weighing in on the subject here (which I also like because it ties Type 1 and Type II errors into the testing framework regarding the probability of rejecitng or accepting the null hypothesis): http://en.wikipedia.org/wiki/Statistical_significance
And since three references should be sufficient, here’s a third I find very informative: http://www.csulb.edu/~msaintg/ppa696/696stsig.htm
Based on the relative sample sizes (for number of data points is the critical factor in determining whether the differences are statistically significant) one simply needs to compare temperature data for the last 10 years with the prior 10 years; if the difference in the two are statistically significance then yes, you can say there’s been a difference in the last 10 years vs the prior 10.
I’ve not crunched the numbers, but it would be an interesting exercise for someone with the time and tools to do so. (It pretty much depends on the signal to noise ratio of the two groups of data sets.) It would be interesting to do that on daily datasets and on those averaged weekly, monthly, quarterly, and so on, although obviously no test for statistically significant difference can be made if we have averaged down to just two data points–the most recent decade and the one just prior. At some point there are insufficient data points to say the diffence is statistically significant but the averaging would certainly lower the signal to noise ratio.
Even my 5th grader understands this article. She now has to educate her science teacher who repeatedly shows DVDs by Bill Ney the Science Guy.
you need to extend the sunspot data to 2011 in the first figure.
Katharine Hayhoe tells us climate started in 1965.
http://notalotofpeopleknowthat.wordpress.com/2011/10/12/questions-for-katharine/
Now, for those who want to know what the research says about why a period greater than 17 years is required to see the anthropogenic signal through short-term fluctuations, see:
http://www.agu.org/pubs/crossref/pip/2011JD016263.shtml
The only quibble with this paper I might have is that it really didn’t consider longer-term solar cycle fluctuations such as we might see during a Dalton or Maunder minimum, which would push that period even longer of course. But, as a general rule, greater than 17 years is the minimum to see the anthropogenic signal, and so anyone pointing to a shorter period as proof the anthropogenic signal is not there simply is misguided or intentionally trying to deceive.
the fact the changes in world economic growth (GDP), particularly though the 2007-2010 great recession, are poorly correlated with global CO2 and methane emmissions is very damning for AAGW: Because even if AGW is true, the normal measures would fail to stop it (energy consumption declined sharply due to the great recession).
Nice article.
… alchemical;
… teleported;
… public dogma and internal mysteries.
Good descriptions.
————-
Statistical significance is based on random chance. To be able to determine significance, we must determine how the climate can change randomly, how much it can change by by chance.
To be able to do that, we have to determine how the climate changes “without” chance, what other forces drive the climate. To be able to do that, we have to determine what those other forces actually are. Then we have to determine how much those other drivers can also change by chance themselves.
The climate goes up and it goes down. We can’t figure it out and we don’t know what all the drivers are. We do know that chance and the other drivers not included in a climate model can overwhelm the greenhouse forcings in the climate models for a long period of time because none of them have been right since the first ones were run 29 years ago.
Bob Tisdale and others point out that long period ocean current cycles cause variations that can last up to decades or longer. These long period cycles are on top of long period variations of solar variation (which may be from a combination of absolute insolation variation, spectral variation with more UV, or effect on clouds via cosmic radiation). This variation in atmosphere temperature drivers is on top of the ocean’s lag and chaotic behavior of such a complex system as Earth’s biosphere, glacial content, aerosols, etc. Finding a simple correlation on one or two of these parameters that holds all the time is too simplistic. However, it appears that main ocean cycle and solar activity is a far better source of correlation that simplistic use of CO2. Just don’t try to take such correlation too far.
Bill Illis says:
“To be able to determine significance, we must determine how the climate can change randomly, how much it can change by by chance.”
—–
This is muddled thinking at it’s worst. The climate does not change by chance.
The answer to the headline question is the same as the answer to ‘Why does it take three women with PMS to change a light bulb? Because it does OK
Richard Lawson.
I was claiming nothing more than that climatologists “include the sun’s influence in their analyses”. I was asking James Padgett if he was claiming that climatologists were not, in their analyses, accounting for the sun’s output.
Your own question, with the Rumsfeldian litany of unknowns, is a strawman, as is Alan the Brit’s waffle. The fact remains that the sun’s output, and changes to such, are accounted for in climatological analyses, and certainly at the level of solar physics mentioned by James Padgett.
I simply asked, and I will ask again, if James Padgett is claiming that climatologists do not, in their analyses, account for the sun’s output. Of course, the obvious supplemetary question for James Padgett and others to answer, if they think that the first can be answered in the affirmative, is to indicate which analyses are deficient in accounting for solar output, where such deficiency occurs, and exactly what are these supposed deficiencies.
The rancorous responses above don’t actually address the point of my questioning.
Simple answer to the title’s question is that 20 years is longer that the basic solar cycle and 10 years is not.
I embrace the idea of creating a new climate model that focuses on the fundamentals such as sun, clouds and oceans. Dr Spencer has his own simple climate model that is quite good especially compared to the billion dollar IPCC models. We should use mostly the best data ARGO and satellites, because the length of training period is not necessarily better.
Nope.
Coal and oil are too valuable to burn. Much more practical to consider them raw materials for production.
Use Hydrogen plus nickel (see http://wattsupwiththat.com/2011/10/28/test-of-rossis-1-mw-e-cat-fusion-system-apparently-successful/
There are a few misconceptions above. First the number of points in an interval is irrelevant, only the length of the interval matters. I could set up equipment to measure temperature every microsecond but my 86 billion extra data points per day would make no difference. Second, even R Gates made this mistake, amplitude matters. If we get (for example) a 1C drop over the next (say) 5 years, that is statistically significant. Why? Because it’s unique in the record, no other 5 year periods have shown that magnitude of a drop. How significant? That part is tricky, there may only be a few dozen 5 year periods to compare against unless we overlap them in which case they are not independent samples.
In short, to determine significance, ask what your sample is, what samples you are comparing against (and how many), what those samples show compared to your sample. Is your sample unique compared to a large number of other samples? Then it is significant.
A fine article though I’d like to point out there is no such thing as “fundamental chaos” in nature. Choas Theory is a mathematical concept. Just because something appears chaotic doesn’t mean it is. One should never confuse mathematical models with reality. Chaos and Randomness are merely expressions of lack of knowledge. There is no theoretical reason that the underlying processes will not be discovered. Otherwise, the basic mission of Science is futile. If von Neumann made an error it was in underestimating the complexity of the problem possibly by several orders of magnitude.
10 years vs 20 years? When an entire earth climate cycle (glacial period–to–interglacial period–to start of glacial period) is 100K years this is a silly question. With a mere 100 years of highly biased unrepresentative surface temperatures and a few decades of satelite data there is simple no such thing as climate science. There is barely enough data for weather reporting-as daily demonstarted by the woefully inaccurate weather predictions makes clear. Climate scientist and meteorologist, get over yourselves! You are a pseudo-science like “social science”, “political science” and economics.
The premis of this article is ridiculous, bearing in mind that huge groups of people in ‘educated’ countries don’t believe that continental drift ever happened.
God made the planet in 6 days remember. There were no dinosaurs, despite the evidence, the president is not American, despite the evidence, the world is not warming, despite the evidence.
Bernard J:
At November 5, 2011 at 6:28 am you say;
“I simply asked, and I will ask again, if James Padgett is claiming that climatologists do not, in their analyses, account for the sun’s output.”
Clearly, you failed to understand the several answers you obtained. So, I will spell it out in simple language for you. The answer to yourt question is:
No, they do not: they only include a factor for solar irradiance which is only a small – and, in this case, a possibly insignificant – part of the sun’s output.
I hope you are now able to understand.
Richard
lemiere jacques says:
November 5, 2011 at 3:41 am
You must understand that if you want to convince scientists ( 5 grade) you must give a physical explanation such as heat transfert, forcing from coulds coverage modifications…so that you can quantify and be falsified…
Gravity, relativity, quantum mechanics, these are some of the greatest triumphs in modern physics. Where is the physical mechanism to explain them? What causes time to pass slower in a gravitational field? What is the speed of gravity? What is the physical mechanism underlying the uncertainty principle? How can these great theories have any value without there being a physical mechanism to explain them?
Science has one great power – and only one. True science can DEMONSTRATIVELY and REPEATEDLY and RELIABLY predict the future – with better odds than chance. That simple test is what sets science apart from everything else.
If a theory seeks to explain but has no predictive value, it is worthless as science, because there is no way to determine if it is true or false. Worse, it can do great harm. We end up blood-letting. Yet at the time the “experts” were convinced, the consensus opinion was that illness was caused by bad blood.
The human brain is no bigger today than it was then. We are still equally as likely to make mistakes.
From the viewpoint of a physician.
Statistics is the science of how numbers behave. Not many people really care about or understand statistics. They care about the subject they love (climatology, psychology, whatever), but don’t give a hoot about how numbers behave. They just plug their data into a formula without any understanding of what they are doing. Since nobody loves statistics, statisticians have a hard time convincing people to use their expertise in many types of studies, including tree rings. Only when the numbers look bad will they call in a statistician. Imagine spending years gathering data, getting accolades from your peers, and then having some statistician tell you that your data is garbage. You have wasted millions of dollars and years of your life.
Keep in mind that you never prove anything by statistics. You simple state the probability that a series of numbers or a set of groups of numbers occurred solely by random chance. Not really very sexy.
The 95% cut off is clearly artificial. And, almost never applied properly. Data dredging is a well know way to get the desired but wrong conclusion. If you try 20 different correlations with an outcome, one is bound to be statistically significant at the 5% level.
Especially for observational data, to get data free of bias is extremely hard. Investigators will cherry pick all the time to get the result they want. Even with laboratory testing, investigators will throw out data they deem “outliers.” If this were not so, we would not see so many medical science papers refuted by further studies. People also tend to report positive results and forget the negative results. Everybody has to make discoveries to get more grants.
So, ask any seasoned medical statistician ( I am not one of those.) about the climate data. They would just laugh.
Here is a simple elegant peer reviewed study which explains the temperature since records began very well.
http://people.iarc.uaf.edu/~sakasofu/pdf/two_natural_components_recent_climate_change.pdf
In a nutshell there is a 1/2 ° per CENTURY warming due to solar increase and feedbacks. This warming is real but of interest only to climate scientists.
On top of this there is a 60 year PDO cycle which explains the short term variation very well.
This warming and cooling doesn’t add any actual warming or cooling but it annoys the alarmists very well.
The pattern fits for 120 years but let’s just look at 1940 on.
1940 to 1978 — Cooling because PDO was negative [Aerosols aren’t needed to explain this ]
1978 to 1998 — Warming because the PDO was positive and there were more El Ninos than La Nina’s.
1998 to present Flat because El Nino’s equal La Nina’s
http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml
The cooling of 1940 to 1978 caused climate scientists to decry global cooling. The warming of 1978 to 1998 caused them to decry global warming.
As of 2005 the cycle has turned down.
Posted on November 5, 2011 by James Padgett
Guest post by James Padgett
“ … Of course, others say this time period is simply not statistically significant, but the only period of heating we can’t directly trace to the sun, the time from 1977-1998, a mere twenty year period, is certainly statistically significant in some minds.
Why is 20 years statistically significant when 10 years is not? “
Right, significance is a term from the discipline of statistic. In the science of physics time periods are not used, but frequencies f [f = 1/sec]. Time is not an observable in physics. A well used term in physics is a correlation coefficient. And it is useful to take a most great interval.
Because of the knowledge of a climate frequency of about ~ 1/900 years^-1 for the frequency of the “Warm time / Little Ice age”, and the knowledge of the warm phase in these centuries, a discussion of 20 or 10 years has no relevance in climate science.
The reconstructed global temperature spectra contain a lot of non sinusoidal oscillations with frequencies in the range of three to four orders of frequency. All that oscillations have a real heat source and a physical mechanism and a real geometry.
Of coarse the reconstructed global temperature proxies are neither precise in time nor in amplitude. And moreover it is not known for sure what the source of heat spikes are, next to the Sun.
This leads to a problem if a correlation coefficient is computed from a possible solar heat source and the reconstructed global temperature. On the other side it is not out of the question to verify terrestrial heat sources by using the method of the solar system heat dynamics.
Simple summation of solar tide functions from couples of six slow moving planets suggests that the main global temperature effect on Earth is controlled by the solar system:
http://volker-doormann.org/images/hadc_ghi6_1850.gif
The simulation can be updated adding the fast moving bodies inside Jupiter.
The tide frequency of ~ 1/900 years^-1 and its half frequency of ~1/1.8 ky^-1 is well known as ‘Bond event’. The climate amplitude of this non sinusoidal oscillation is about +- 2 °Cel. and this has more relevance as some tenth of 1° Cel. in 10 or 20 years.
V.
Once we realize we don’t know the answer, we can start looking for it. But as long as we’re zero-ed in on the CO2 boogey-man, we will probably never attempt to find out.