Adjusting Temperatures for the ENSO and the AMO

“There appears to be some room to look at a solar influence but this would be quite small.”
I am no expert, but I suspect the oceans are being driven by the solar influence. It is becoming increasingly clear that the oceans are running the climate show on this planet.

There is also a chicken/egg question of warmer water outgassing or at the least not absorbing as much CO2. When oceans warm they take in less CO2 and when soils warm, they produce more CO2 due to increased rates of biological decomposition of organic matter. A recent (in the past week) paper figures that soils produce 10x more CO2 than all human activities combined. While a few degrees doesn’t make much difference in tropical regions, it can make a HUGE difference in temperate regions where a degree or two in local temperature might mean the difference between “frozen” and active biological decomposition. Also, a warmer year will result in a longer period above freezing and just a couple of weeks of additional time is again more than 10x human caused emissions over those two weeks. So an extra frost-free week could be equal to 10 weeks of additional human emissions from natural sources.
So CO2 may still not be a cause and is still quite likely to be a result of warming.

For a approach, fitting the Pacific Decadal Oscillation and CO2 to temperature trends, see: Roy W. Spencer’s model, Global Warming as a Natural Response to Cloud Changes Associated with the Pacific Decadal Oscillation (PDO)

The “PDO-only” (dashed) curve indeed mimics the main features of the behavior of global mean temperatures during the 20th Century — including two-thirds of the warming trend. If I include transient CO2 forcing with the PDO-forced cloud changes (solid line labeled PDO+CO2), then the fit to observed temperatures is even closer.
It is important to point out that, in this exercise, the PDO itself is not an index of temperature; it is an index of radiative forcing which drives the time rate of change of temperature.

Would Bill Illis’ fit above improve by using a combination of PDO, ENSO and AMO with ln(CO2)? Or are PDO, ENSO and AMO sufficiently interrelated as to not be independent?
Can the effects of the Urban Heat Island effect be quantitatively separated from CO2 forcing on temperature trends?

IT would also be helpful if Bill added original sources for the data (as URLs to the ENSO version and AMO version as used, for example.)

To Steve
Here is the AMO data which is updated monthly a few days after month end.
http://www.cdc.noaa.gov/Correlation/amon.us.long.data
Here is the Nino 3.4 anomaly from Trenbeth from 1871 to 2007.
ftp://ftp.cgd.ucar.edu/pub/CAS/TNI_N34/Nino34.1871.2007.txt
And here is Nino 3.4 data updated from 2007 on.
http://www.cpc.ncep.noaa.gov:80/data/indices/sstoi.indices

Great detective work Bill. Now we await the pitbull (Gavin) to see if he takes a bite!

Still can’t get spreadsheets with zip file. Lots of #VALUEs (using Excel 2007).
Only get this on the link – no way to download anything.
“ndex of ftp://ftp.cgd.ucar.edu/pub/CAS/TNI_N34/Nino34.1871.2007.txt/
Up to higher level directory
Name Size Last Modified”
Anthony:
Have you read this:
http://earthobservatory.nasa.gov/Newsroom/view.php?id=35952
On reading seems like NASA gobbly-gook and makes statements like this:
“With new observations, the scientists confirmed experimentally what existing climate models had anticipated theoretically” and
“Because the new precise observations agree with existing assessments of water vapor’s impact, researchers are more confident than ever in model predictions that Earth’s leading greenhouse gas will contribute to a temperature rise of a few degrees by the end of the century.” What’s a “few”?
What’s your take on this “News”?

Still having problems with zip file. Getting lots of #VALUE.
Also problems with ftp://ftp.cgd.ucar.edu/pub/CAS/TNI_N34/Nino34.1871.2007.txt
Can’t seem to download anything.
Anthony:
Have you read this:
http://earthobservatory.nasa.gov/Newsroom/view.php?id=35952
Any comments?

To Steve Hempell.
Regarding the water vapour study by Dessler – I read the paper and the results are not exactly as indicated in the news releases. The study examined the change in water vapour from DJF 2007 to DJF of 2008 when the La Nina (and the AMO) reduced temperatures by 0.4C.
The study found there was a 1.5% (percentage points) decline in relative humidity in the very lower levels of the troposphere and a 1.5% increase in relative humidity in the upper layers of the troposphere. The middle layers were constant.
Given there is more water vapour in the lower levels of the atmosphere, the study really found that there was a decline in overall relative humidity when global warming theory suggests it should stay more-or-less stable.
To be fair, the models do produce results which are similar to this as temperatures go up (but not when they go down as happened between 2007 and 2008.)

It makes me uncomfortable to look at the graph Hadley Plus Constant Versus Nino and AMO Model Only and see a hybrid of actual data and modeled data going back in time. Plotting anything that comes out of a computer on a chronologic baseline from the past is an inherently unsettling strategy, one that to my eyes appears to have been heavily influenced by AGWers’ love of GCMs.
The word “warming” on the graph, again, appears to have the ring of authority, as though there were only a single possible explanation for the divergence. That would appear to my eyes to be an argument, rather than a fact. Could the length of solar cycles have anything to do with temperatures? Could the intensity of solar cycles have anything to do with the rising temperatures? Could the PDO be at play here? Could, as someone else pointed asked, energy in the deep ocean that got there hundreds, or thousands, of years ago have raised atmospheric temperatures in the 20th century?

Okay, I see partions of two oceans discussed here… many more to go.

I wish I could remember who said that the climate is the continuation of the oceans by other means.
=======================================

kim: Von Cloudswitz

Bill Ellis: You wrote, “one just needs to examine the up and down of temperatures in the 1997-98 El Nino, for example, to see there is no accumulating impact.”
Take a closer look. Note the step change in the pre-and post-1997 global temperature trends that should be attributable to the 97/98 El Nino in the:
RSS MSU Data:
http://i34.tinypic.com/o9j0v5.jpg
GISS Data:
http://i35.tinypic.com/2ajs8ib.jpg
NCDC Data:
http://i36.tinypic.com/2ijhvdw.jpg
UAH MSU Data:
http://i36.tinypic.com/14scl08.jpg
and the HADCRUT Data:
http://i36.tinypic.com/1emam9.jpg
Or looking at data sets of smaller areas, notice the remarkable step changes in the Mediterranean Sea SST after the 97/98 El Nino:
http://i33.tinypic.com/6rpjzm.jpg
and the Gulf of Mexico SST:
http://i33.tinypic.com/2hyexwj.jpg
and the Atlantic Ocean SST:
http://i35.tinypic.com/9fmneo.jpg
and the western Pacific Ocean SST:
http://i34.tinypic.com/10pr9cm.jpg
Arctic temperatures shifted, too:
http://i38.tinypic.com/2cpx63c.jpg
Note the differences in response of the east and west Pacific Ocean SSTs (divided at 180deg longitude) to the 97/98 El Nino:
http://i34.tinypic.com/5tx6qg.jpg
Note also the differences in the responses of the Indian Ocean to significant El Nino events:
http://i38.tinypic.com/iejmtk.jpg
versus La Nina events:
http://i33.tinypic.com/15ofb41.jpg
I discussed the above in the following posts:
http://bobtisdale.blogspot.com/2008/08/did-9798-el-nino-cause-step-change-in.html
http://bobtisdale.blogspot.com/2008/07/hurricane-breeding-grounds.html
http://bobtisdale.blogspot.com/2008/10/atlantic-indian-and-pacific-ocean-ssts.html
http://bobtisdale.blogspot.com/2008/11/another-look-at-saw-tooth-trends-in.html
Bill: I don’t have the background that would allow me to delve into the data further and pull out an accumulating impact of ENSO. But maybe someone else reading this thread does. The fact that a running total of the Trenberth NINO3.4 SST anomaly data mimics the global temperature anomaly curve hints that there is an accumulation.
Regards.

Kim,
The oceans should be regarded as a continuation of the atmosphere as regards maintenance of global temperature and being so much more substantial the oceans are by far the greater part of the mechanism.

kim (23:30:28) : I wish I could remember who said…
“Climate is the continuation of the oceans by other means”
http://navalwarchangesclimate.wordpress.com/
That’s one link, kim. It seems to be all over the web.

Bill Illis:
Thankyou for this cogent analysis. I have one comment on your method and its effect on your conclusion.
I understand your article to say your analytical method has the following steps.
1.
The effect on temperature of AMO and ENSO within the time series is calculated by simple regression (this is possible because AMO and ENSO exhibit several cycles within the temporal range of the data set).
2.
The temperature effect of AMO and ENSO is deleted from the time series to reveal a residual temperature trend in the time series.
3.
The residual trend is assumed to be an effect of changed atmospheric carbon dioxide concentration over the temporal range of the data set.
4.
The assumption in step 3 is used to calculate the climate sensitivity to changing atmospheric carbon dioxide concentration.
This may be correct, but the assumption in step 3 is the logical fallacy of ‘argument from ignorance’. The assumption amounts to, “The cause of the residual trend is not known so it must be changing atmospheric carbon dioxide concentration”. (If this ‘logical fallacy’ is not clear then consider, “The cause of crop failures is not known so it must be witches”.)
Of course, the residual trend may be a result of changing atmospheric carbon dioxide concentration.
However, the assumption in step 3 does not concur with the implicit assumption of steps 1 and 2 that natural cycles are affecting the temperature trend.
Other natural cycles may also be affecting the trend, and the method is not applicable to cycles with lower frequency than the time series. Such a very low frequency oscillation does seem to exist. There is an apparent ~900 year oscillation that caused the Roman Warm Period (RWP), then the Dark Age Cool Period (DACP), then the Medieval Warm Period (MWP), then the Little Ice Age (LIA), and the present warm period (PWP).
There is no known cause of this apparent low frequency oscillation: some people suggest it could be solar influence, but it could be the chaotic climate system seeking its attractor(s), and it could be … . However, there is no known cause of the AMO and ENSO, either.
Therefore, the implicit assumption of your steps 1 and 2 suggests that the residual trend determined by your steps 1 and 2 could be recovery from the LIA that is similar to the recovery from the DACP to the MWP.
Indeed, since the method adopted the implicit assumption of your steps 1 and 2, consistency suggests that all the observed rise of global temperature in the twentieth century is recovery from the LIA that is similar to the recovery from the DACP to the MWP.
Hence, the calculated climate sensitivity to changing atmospheric carbon dioxide concentration obtained by your method should be assumed to be a maximum value until this possibility of recovery from the LIA is assessed.
I hope these thoughts are helpful.
Again, thankyou for your superb work that I trust will soon be published.
Richard

I also am having problems opening the excel files. Excel tries to repair (unsucessfully) the annual model, and I get a “cannot be accessed” error on the monthly.
Excellent analysis. I look forward to delving deeper over the holiday.

No matter what scientific facts are presented to challenge the AGW ideology it is impossible for scientists to sway public opinion on this issue because the issue is political. It is very easy for high profile people who quote a scientific consensus that is supported by sophisticated computer models to convince the general public of anything that they want.
Even though the computer models have never yielded a single result that matches observations, any criticism of the models is met with some sort of complex justification that is beyond the comprehension of the general public so it is readily accepted by the masses and those questioning the validity of the models are vilified by the promoters of the AGW agenda as skeptics and deniers who are in the pockets of big oil.
The sole support for AGW is the climate models, and the sole support for the climate models with respect to CO2 is the forcing parameter. There is no actual physical rational for the forcing parameter, because it was simply contrived from the assumption that observed warming of 0.6°C was due entirely to a 100ppmv increase in atmospheric CO2 concentration. There was never any verification of this parameter either by theory or observation. There is no justification for this parameter based on the physical properties of CO2, because the molecular configuration of the CO2 molecule precludes any significant effect from CO2 beyond a concentration of 300ppmv, and the current concentration is 386ppmv.
There is no justification for this parameter based on observation because the observed notch in the spectrum created by CO2 is virtually identical for both the Earth and Mars and Mars has over 9 times the physical concentration of CO2 in its atmosphere than the Earth has in its atmosphere.
Even the reference temperature value for the parameter is faulty because the maximum temperature increase possibly attributable to human CO2 emissions is 0.1°C per century; not the 0.6°C that is used in the forcing parameter.
The climate models use a forcing parameter based on the equation:
CO2 rf = f * ln([CO2]/[CO2]prein)/ln(2)
where f= rf for CO2 doubling
In further documentation according to the IPCC, the “Radiative Forcing” ÄF, in watts per square meter, due to additional carbon dioxide in the atmosphere, can be calculated from the formula:
ÄF = 5.35 ln C/Co
The value 5.35 in this equation and the term [CO2]prein in the generalized equation demonstrate that the forcing parameter is based on the 100ppmv increase from the preindustrial value of 280ppmv and the 0.6°C of measured temperature over the time period that this 100ppmv increase occurred.
Further documentation in the IPCC reports states that the forcing of each watt/m2 raises the global temperature by 0.75°C + 0.25°C.
The Nimbus 4 satellite measured the thermal radiation spectrum of the Earth in 1970, when the CO2 concentration was 325ppmv as measured at Mauna Loa.
Mars has an atmosphere that is 95% CO2 with virtually zero water vapour and the remaining 5% of the atmosphere is comprised of O2 N2 and Ar, so CO2 is essentially the only “greenhouse gas”.
The atmosphere on Mars is so thin that the 950,000ppmv concentration of CO2 only represents about 9 times more actual CO2 than is in the Earth’s atmosphere in absolute terms.
Recent measurements of the thermal radiation spectrum from Mars should show a spectral notch from CO2 that represents an increase in forcing representing the 9 times difference in CO2 according to the equation:
ÄF = 5.35 ln C/Co
Considering that this formula gives a forcing value of 3.708watts/m2 for just a doubling of CO2, this value of 11.755watts/m2 for a 9-fold difference should be readily visible on the two measured spectra.
The spectral notch is virtually identical on both the 1970 Earth spectra with a 325ppmv and the Mars spectra from at least 9 times the concentration indicating that there is virtually no effect increases in CO2 beyond 325ppmv.
This clearly falsifies the equation and the numerical values used to determine the forcing parameter of the climate models that support the AGW hypothesis.
In addition to this physical evidence of an invalid assumption forming the basis for the forcing parameter, there is a blatantly obvious error in the actual values used in determining the magnitude of the forcing parameter. The temperature record shows that the global temperature has been increasing naturally at a rate of about 0.5°C/century since the Little Ice Age. The forcing parameter is based on the full measured 0.6°C/century without subtracting the natural warming of 0.5°C/century giving a forcing parameter that is 6 times larger than can be attributed to the measured increase in CO2.
Far less obvious, but the major fatal flaw of the forcing parameter is that it is based on an observation of temperature and CO2 concentration without taking into account the actual physical properties of CO2 and its limited effect on thermal radiation as defined by quantum physics.
As you are aware, certain gases can be caused to rotate and vibrate by thermal radiation. The rotation mode is relatively independent of wavelength but the vibration mode is limited to specific resonant wavelength bands. The rotation mode results from the interaction between the thermal energy and the dipole moment of the gas molecule. The carbon dioxide molecule is formed from two oxygen atoms equidistant from a central carbon atom and all three atoms are in a perfectly straight line. This configuration and symmetry eliminates any dipole moment, limiting the CO2 molecule to vibration modes only.
There is only a single vibration mode of CO2 that resonates within the thermal spectrum radiated by the Earth (and Mars). This bend vibration resonates with a band of energy centred on a wavelength of 14.77microns (wavenumber 677cm-1) and the width of this band is quite narrow as depicted on the spectra from Earth and Mars.
It only takes a minute amount of CO2 to fully “capture” the energy at the resonant wavelength, and additional CO2 progressively captures energy that is further and further from the peak wavelength. At the 280ppmv CO2 preindustrial level used as reference in the forcing parameter, about 95% of the energy bandwidth that could possibly be captured by CO2 has already been captured. There is only 5% of this limited energy available within the confines of this potential “capture” band left to be captured.
The greenhouse effect from CO2 is generally stated as 3°C, so an additional 100ppmv above the 280ppmv level is only capable of generating a maximum 5% increase or 0.15°C. The forcing parameter is based on a full 0.6°C which is four times the 0.15°C absolute physical limit of warming from CO2.
Furthermore if this 0.15°C increase has used up the full 5% of the remaining possible energy as the concentration reached 380ppmv, there is zero warming possible from further increases in CO2.
This is why the CO2 notch is virtually identical in the two spectra; the CO2 band was virtually saturated at the 325ppmv concentration level, so even nine times more CO2 has almost no appreciable effect.
Norm K.

Bill Illis: Sometimes a change of perspective is needed. Your analysis also doesn’t account for the disparity between the magnitude and frequency of El Nino events and those of La Nina events. This can readily be seen by smoothing NINO3.4 data. I used a 7-year filter for the following graph. (Actually an 85-month filter for the monthly NINO3.4 and Global Temperature anomaly data.)
http://i38.tinypic.com/2v9ay69.jpg
Other notes about the graph: Since the source of your data (Trenberth and Stepaniak) remark in the accompanying paper that the NINO3.4 data is questionable prior to the opening of the Panama Canal, 1914, I deleted the data before 1915. I also prepared this graph for an upcoming post that I haven’t gotten around to writing up, which is why it ends in 2005.
Note that the NINO3.4 data is predominantly positive from 1918 to 1944 and from 1977 to 2005 (periods when global temperatures rose) and that the NINO3.4 data is predominantly negative from 1943 to 1959 and from 1970 to 1977 (periods when global temperatures for the most part declined). There are some exceptions, but, in whole, it holds true. During the positive NINO3.4 period of 1959 to 1970, global temperatures started to rise but were suppressed by volcanic aerosols.
Regards.

John W:
I hope this posting will clarify what I meant by my comment, and I apologise if my use of an imperfect illustration caused confusion.
To begin, I want it to be very clear that I think Illis has provided a good, useful and important analysis which warrants publication.
My witches illustration was intended to aid understanding, and it was not intended as direct analogy. However, your comment brings attention to quality of data. (The records show that the number of detected witches did increase at the time when witchfinders were appointed. But it is not clear how many witches were detected and how many witchfinders existed.)
I stress that I think Illis has provided a superb analysis, but the quality of any analysed data should always be questioned because GIGO applies to all analyses.
Also, your comment concerning “driving the bus” illustrates the importance of ascribed causality. Which was causal; did increase to the number of detected witches induce increase to the number of witchfinders, or did increase to the number of witchfinders induce increase to the number of detected witches?
In the context of the analysis Illis provides, ascribed causality has great importance. Which is causal; did increase to atmospheric carbon dioxide concentration cause increase to the residual temperature trend, or did rising temperature cause increase to the atmospheric carbon dioxide concentration, or were the temperature and carbon dioxide changes caused by some other effect(s)?
My comment was intended to explain the importance of ascribed causality on the analysis Illis provides.
I am an extreme sceptic on matters of man-made global climate change. I do not know the cause(s) of the recent rise in atmospheric carbon dioxide concentration, and I do not know what – if any – effect that rise is having on global climate. But I want to find out.
The absence of any empirical evidence for anthropogenic (i.e. man-made) global warming (AGW) leads advocates of AGW to rely on the logical fallacy of ‘argument from ignorance’ and outputs of computer models.
History is replete with examples of politicians being guided by advisors who used the ‘argument from ignorance’ fallacy to justify their advice. The advisors have always presented an appealing case based on accepted theory, and they have always ignored – or rejected – alternative possible explanations for the effects which they have asserted as justification for their advice.
In ancient times such advisors said, “We do not know what causes lightening to strike so it must be the actions of Gods and people should make sacrifices to appease those Gods.” And, as my illustration said, in the Middle Ages such advisors said, “We do not know what causes crops to fail so it must be witches and we must eliminate the witches.”
Now, advocates of AGW say, “We do not know what causes global climate change so it must be emissions from human activity and we must eliminate those emissions.” Of course, they phrase it slightly differently: they say that they cannot match historical climate change with known climate mechanisms unless an anthropogenic effect is included. But this “anthropogenic effect” is an assumption with no more empirical evidence to support its existence than the empirical evidence for ancient Gods and witches.
My comments tried to say that the final part of Illis’s analysis adopts the same ‘logical fallacy’ that is used by AGW advocates. It is an assumption – not a fact – that increased atmospheric carbon dioxide is the cause of the residual temperature trend his analysis reveals. Indeed, his demonstration that natural oscillations cause some of the temperature trend adds credence to the possibility that other observed natural oscillations may also be significantly contributing to the trend.
But, as I also said, increased atmospheric carbon dioxide may be the cause of the residual temperature trend Illis’s analysis reveals.
I hope what I intended to say is now clear.
Richard

two rapid comments on the reply just above:
“the computer models have never yielded a single result that matches observations”
This looks to me like a very strong statement. Too bad it is completely false… In particular when you think many models biuld their internal set parameters based on reproducing observations over the last century.
“There is only a single vibration mode of CO2 that resonates within the thermal spectrum radiated by the Earth. This bend vibration resonates with a band of energy centred on a wavelength of 14.77microns (wavenumber 677cm-1)”
again, a very convincing argument, except that it is obviously incorrect:
http://www.globalwarmingart.com/images/thumb/4/4e/Atmospheric_Absorption_Bands.png/700px-Atmospheric_Absorption_Bands.png
There is more than just one asymetric vibration mode in CO2.

Now that’s a good post. Keep ’em coming!
0.4°C more warming with a doubling of CO2 – hardly catastrophic. Certainly does not warrant expensive mitigation programs demanded by many.
“…adjustments of old temperature records by GISS and the Hadley Centre and others have artificially increased the temperature trend… ”
Now why doesn’t that surprise me? I’m curious how the other side will respond to this.

I just returned from a climate change conference in Amsterdam organised by the Royal Geological and Mining Society of the Netherlands on the 20th of November http://www.kngmg.nl/
Two speakers: Prof Jurg Beer (physicist) of Zurich and Prof Kees de Jager of Utrecht University and founder and first director of the Utrecht Space Research Laboratory showed some remarkable correlations between temperature variations and solar activity over the last 400 years or so. They concluded that no anthropogenic signature could be detected. They purely concentrated on the statistical significance of the observations. Yet they realized that the changes in solar forcing are not enough to cause the temperature fluctuations, but they didn’t want to speculate about the possible causes. Obviously some other mechanism must explain the amplified effect on temperature. They knew about Svensmark et al but didn’t want to comment on it as they felt not qualified to do so, but they were eagerly awaiting the outcome of the forthcoming CERN experiments.
If ENSO and AMO are also correlating with the past temperature fluctuations, I can only conclude that the sun ( via clouds? ) is responsible for the frequency and strength of the various oceanic oscillations.
De Jager’s paper has just appeared in the September issue (Volume 87, no 3) of the Netherlands Journal of Geosciences.

Anthony, still having problems opening the excel sheets, even in zip format. Says they are corrupted.
REPLY: I tried a download from another machine that I didn’t write the post from and had the same result. I’ll see if I can figure out this nuance. – Anthony

Chris S. (06:44:32)
Whose reconstruction of solar activity did your speakers use? Where’s Leif to comment on this latest?
========================================

re: web based research collaboration. Scientists need to feed their families too. Who will fund such an effort? Scientists don’t make a product that you can buy at Walmart. What funding sources could be accessed for such an endeavor that does not have, or can set aside, a vested interest in the outcome? And how long would they be willing to fund before answers are forthcoming?

Bill Illis, one last thing. With respect to your statement and graph about the NINO3.4 anomaly data trend or lack thereof, there is a significant difference between the Trenberth NINO3.4 SST anomaly data (The ultimate source is HADSST) and the Smith and Reynolds (ERSST.v2) version. Here’s a comparative graph of the monthly data:
http://i36.tinypic.com/2s76q02.jpg
Here’s a graph of the difference with a linear trend line:
http://i37.tinypic.com/2q33dcz.jpg
That trend is substantial and the dip in the early 20th century is consistent with the ERSST.v2 version of the Pacific Ocean. I don’t think the Trenberth (HADSST) NINO3.4 data has been detrended, though it looks like it might have been, because the difference also shows up in the annual NINO3.4 SST data of the two data sets:
http://i33.tinypic.com/orl1tc.jpg
And the difference in the annual SST data:
http://i38.tinypic.com/20zw7bb.jpg
I discussed it here:
http://bobtisdale.blogspot.com/2008/11/nino34-data-comparison-hadsst-and.html
Who knows, maybe the guys at the Hadley Centre didn’t like the pesty SST dip in the early 20th century, so they smoothed it out. Stranger things have happened.
Regards

Thank you, Bill Illis, for this very nice post.
May I, nevertheless, ask the following questions:
1) the weight of ENSO is considerably less than that of AMO (0.06 or +/- 0.2 Celsius variation vs 0.5-0.7 or +/- 0.3-0.4 C variation).
ENSO represents tropical pacific, while AMO represents northern atlantic – not including tropical atlantic. The total area of pacific ocean is approx. 180 million km2, thereof tropical/subtropical area approx. 90 million km2. The atlantic ocean has 80 million km2, thereof the AMO area is approx. 30 million km2. The ratio is 3:1 while the weight factors ENSO vs AMO have roughly 1:2.
Why do you not use pacific decadal oscillation instead of AMO? PDO represents the total pacific, with, maybe, too little weight for the tropical pacific, which then would be compensated by ENSO.
2) The logarithmic dependence on CO2 concentration. Could it be replaced by just a linear dependence on time, without spoiling the agreement? After all, it can be claimed according to IPCC that 1/3 of the global warming arises from solar influence, which to a very first approximation has been linear in time (probably no longer).
3) The Hadcrut global data CO2 logarithmic prefactor of 2.73 yield 0.1 C per decade warming (since 1958), while the RSS global data give a CO2 logarithmic prefactor of 1(or 0.046 C/decade, since 1978). The difference to some extend seems to arise from the heavier weight of the last decade in the RSS analysis, but mainly may arise from inadequate land surface data (see UHI etc discussion a few days ago). Do you share this view?
A logarithmic ansatz for the CO2 dependence ignores any negative feedback due to enhanced latent heat transport at higher temperatures (the Lindzen argument).

Pamela Gray (07:14:29) :
“Scientists need to feed their families too. Who will fund such an effort?”
That is why I made the Linux analogy – built collaboratively by a community of intensely interested individuals – with nothing more than sweat equity. I assume Bill Illis did not get paid for his little research work – yet he has put together a potentially very interesting piece of science. Anthony puts this blog together, which furthers the science and doesn’t get paid. This is not unrealistic to think that it could work. We clearly have a large group of technically competent people out here with the skills & the knowledge to address many of these problems. Just as with Linux, one person didn’t write the whole OS, the community did it together. Same could apply here – those who have the skills to contribute can contribute as they are able. As a side benefit, no one could say it is an effort funded by an agenda – no grant money funding the AGW’s, no “big oil” money (as the AGW’s like to think the “skeptics” are funded by) – just people motivated by finding the truth.

Have you, or anyone, attempted to apply a Fourier transform to either the raw data or the residual error data?
“Eyeballing” residual frequencies in a graph like that is fraught with observation errors. If there are regularities in the data, a Fourier transform will exhibit spikes at various frequencies, and you can then go looking for things that happen on those time scales.
Regards,
Ric

Pamela Gray wrote: “re: web based research collaboration. Scientists need to feed their families too. Who will fund such an effort? Scientists don’t make a product that you can buy at Walmart. What funding sources could be accessed for such an endeavor that does not have, or can set aside, a vested interest in the outcome? And how long would they be willing to fund before answers are forthcoming?”
Of course the funding has to be from “proper” sources, otherwise the results are suspect for some unknown reason.

Kim,
De Jager considered both the equatorial and the polar activities. The latter is, apparently, often neglected.
He referred to the “smoothed maximum sunspot numbers; a proxy for the maximum toroidal field strength over the centuries” and the “smoothed values of the geomagnetic aa index at sunspot minimum; a proxy for the maximum poloidal field strength” (Duhai& De Jager, 2008). Since 1000 AD they named the following minima: Oort, Wolf, Sporer, Maunder and the Dalton.
By the way, they predict the next solar cycle, #24 to have a maximum strength of 68 +/-17 sunspots to be reached in 2014.

Title:
The Solar Dynamo and Its Phase Transitions during the Last Millennium
in: Solar Physics, Volume 250, Issue 1, pp.1-15.
Duhau, S.; de Jager, C.

To the posters who are suggesting trying other series etc., that is why I have done this. Just to show that it can be done. Like I wrote, it could certainly be improved on.
When we get the spreadsheets up and running, they are set-up so that one could try just about any other variation. All the charts etc. are in there as well.
I really did this so we could actually start adjusting for these things rather than just noting “if you adjust for …”
That and it was clear to me that increased temperature trend of the 1980s, 1990s and 2000s was in part just a reflection of the ENSO and AMO and was not global warming. realclimate even has a GISS temp chart up right now showing temps going straight up like it will reach the moon. This analysis method says the GISS trend per decade since 1979 is only 0.058C per decade far, far less than 0.2C per decade it is projected to be.
http://i463.photobucket.com/albums/qq360/Bill-illis/GISS1979Warming.png?t=1227720573

Great post, Bill, and some great comments, too. I agree with some others that a natural warming since the LIA could explain the gradual increase in temperatures; it doesn’t have to be CO2-related. We know there are some very long-term cycles at play. The current lull in solar cycle 24 will probably help us understand the effects of the sun better. I’m buying more long-johns.

To Phil,
Thanks, but isn’t the formula really (I can’t do the symbols).
— Change in T x–>y = C Ln(CO2x) – 26.9 – [C ln(CO2y) – 26.9]
— the constants cancel each out when you are talking about a change in T so they are not represented but the proper formula would still include them.

One interesting thing about Jan Jannsens analysis compared to this one is that it only uses 3 variables to create the fit which I think is pretty much as good as Jan’s. Jan … do you agree? Jan,for example modelled volcanoes direct whereas this analysis suggests AMO/ANSO is directly impacted by Volcanoes so ” we dont need it”
If this analysis is right C02 is overplayed as a climate influence, and I for one agree.
We are left with the open question of what mechanism drives AMO and ENSO. Well perhaps volcanoes are part of the answer but CO2 driving global warming isn’t. I haven’t found anything in the literature which suggests a plausible cause of OMO/ENSO variation – its a natural cycle – i.e we don’t know.
Anybody seen a plausible explanation?
This and Jan’s model do make predictions on temperature but we will have to wait a long time to test them

Bill Illis, a very interesting piece of work. However, what is missing to my eye is a comparison of your use of CO2 to represent the trend, and just using a straight line to represent the trend.
To make the case that CO2 is involved, you need to show that the fit using CO2 plus ENSO 3.4 plus AMO is significantly better than the corresponding fit using a linear trend plus ENSO 3.4 plus AMO.
My best to you,
w.

There’s a lot of interesting stuff here. I am glad that Norm Kalmanovitch dropped in with some information on CO2 IR activity.
One thing I see constantly in papers, without anybody ever justifying the mechanism, is the claim that the warming due to CO2 is a logarithmic function. This then leads to talk of a “climate sensitivity” parameter being the mean global temperature rise due to a doubling of CO2.
But if you get into the details of infrared absorption by CO2 following the notes that Norm left us up above; I don’t see any justification for the assumption of a logarithmic relationship between CO2 concentration in the atmosphere and the temperature rise (mean globally).
Now I don’t doubt that you can take some sets of data, and curve fit them to a logarithmic currve. Everybody knows you can hide all kinds of pestilence by simply plotting data on a log-log plot. The ability to curve fit data, and calculate correlation coefficients between sets of data doesn’t prove that there is any cause and effect relationship whatsoever.
You wouldn’t believe the total mayhem that scientists have wreaked by simply messing around with numbers, in the belief that you couldn’t possibly closely match real data to the results of just messing around with numbers.
Well if you believe that, you need to review the history of the “Fine Structure Constant” which has the value e^2 / 2 h c e0 where e is the electron charge; h is Planck’s constant; c is the velocity of light, a e0 (epsilon zero) is the permittivity of free space, and is approximately 1/137. The 1/137 form is intimately linked to that sordid history. The first chapter of the great fine structure constant scandal involved Sir Arthur Eddington who one proved that alpha (TFSC) was EXACTLY 1/136; but when nature didn’t comly with his thesis, and the measured value became much closer to 1/137, the good Professor Eddington thereupon proved that alpha was indeed EXACTLY 1/137. Well it isn’t, it’s about 1/ 137.0359895 and has been measured so accurately that it was used as a method for measuring the velocity of light (which IS now specified as an EXACT number (2.99792458E8 m/s) ).
Dear deluded Professor Eddington, became known as Professor Adding one !
Well that was only the first episode of the FSC scandal. In the mid 60s someone derived the 1/FSC number as the fourth root of (pi to some low integer power times the product of about four other low integer numbers raised to low integer powers). I’ll let you university types search the literature for the paper. It computed 1/FSC to within 65% of the standard deviation of the very best experimental measured value of 1/FSC which is 8 significant digits. And the paper included ZERO input from the physical real world universe; it was a purely mathematical calculation. But of course it had to be correct because everybody knows you can’t get the right answer just by mucking around with numbers. The lack of observational data input phased nobody in the science community who embraced this nonsense; well for about a month. That’s how long it took some computer geek to do a search for all numbers that were of the same form; 4th root of the products of low integers to low integer powers and pi to a low integer power.
The geek turned up about a dozen numbers that were equal to 1/FSC within the standard deviation of the best experimental measurments; and one of those numbers was actually within about 30% of the standard deviation; twice as accurate as the original paper. A more sophisticated mathematician developed a multidimensional sphere thesis where the radius of the sphere was the 1/FSC number and a thin shell that was =/- one standard deviation fromt hat radius contained a number of lattice points thatw ere solutions to the set of integers in the puzzle. So he computed the complete set of answers that fit the prescription; the result of doing nothing more than mucking around with numbers that was accepted as correct because it so accurately fitted the observed data.
So watch out what you go for, just because some fancy manipulations fit your data; particularly noisy like data that can hide real errors from the predictions.
One can model the optical transmission of absorptive of materials as a logarithmic function. If a certain thickness transmits 10% of a given spectrum, twice the thickness will transmit 1%, and so on; BUT such materials absorb the radiation and convert it entirely to thermal energy.
Not so with water vapor or CO2 or any other GHG. Some absorption processes may convert some of the energy to heat energy; but mostly the absorbed IR photon is simply re-emitted, perhaps with a frequency shift due to Doppler effects, or even Heisenberg uncertainty. Subsequent re-absorption by other GHG molecules, may face totally diffrent results due to temperature and pressure changes in between successive absorption-re-emission events. The likelihood that such processes follow any simple logarithmic function is rather remote, and the possibility that the global mean surface temperature change due to such porocesses also follows a logarithmic function; even more so.
I know all the books and papers say it’s logarithmic; how many of them derive the specific logarithmic function based on the molecular spectroscopy physics ?

John Philip says … “the GHG forcing does not act instantaneously or even on an annual timescale -”
What is the physical/physics basis for saying the GHG forcing does not act instantaneously or certainly within a year. We are talking about photons of light here. Where is the energy going?
and “… there is a lag in the climate response which means that there is estimated to be around 0.6C warming in the pipeline”
I noted the theory is now the deep oceans are absorbing some of the increase and it might them take us longer to reach the doubling temperature. How long then? Because I think global warming researchers have a duty to tell us that now. Does the temperature reach the doubling level 35 years, 75 years or 100s of years after CO2 reaches the doubling plateau?
The points about the construction of the indices is well-taken. Where can we find the raw data before it is detrended?

“That is why I made the Linux analogy – built collaboratively by a community of intensely interested individuals – with nothing more than sweat equity. I assume Bill Illis did not get paid for his little research work – yet he has put together a potentially very interesting piece of science.”
Things like that generally get started by someone who is curious and wanting to see if they can make something themselves. That was how Linux got started when Linus Torvalds sat down to play with his 386 and decided out of simple curiosity if he could make an unix-like OS. Others got interested and began adding pieces so initially it was sort of a “stone soup” effort.
But then things changed and in a very important way. To give an example, we used Linux at work. We made some changes to some programs to better support our particular environment. Over time as the “upstream” versions of these programs were released, we would have to fit our changes into the new code release. Sometimes it was easy, other times it was more difficult depending on what changed in that upstream release. One day I saw someone asking about a feature on a mailing list for one of these programs and it was a feature we had actually implemented in our environment. I made a decision to provide our changes to the software developer as a “contribution” and they were adopted and incorporated into the standard package. We never had to experience that pain of patching our changes into the code after that. The “upstream” maintainer adopted the maintenance of those changes and a lot of other people benefited from the new features we added. But overall the motivation was self-interest. It was to our benefit to have someone else maintain that code and offload the job of having to merge our changes with every new code release.
So while things often get started out of curiosity, and people will often take an interest in almost a “hobby” sense, what really gets something rolling is when it actually becomes useful in a “real world” sense. And while people will sometimes gift some work out of the goodness of their hearts, often the biggest returns are from people in whose interest it is to get their changes into the broader code base than to have to hack at it every time something changes. It becomes more efficient to open the source than to keep it closed.
Same with projects here. People whose livelihood depends on accurate weather data might find it in their interest to help with the surface stations project or to share what information they have more generally. A firm in the agricultural industry, for example, might make better long term decisions if they knew that growing seasons were actually shortening or flat and not lengthening. If there is no warming, then making economic decisions based on the assumption that growing seasons will get longer in the future can cost someone a fortune. And if I am selling something and if I have the right information, nobody is going to buy it unless they also have the right information so it pays both parties (it is in their self-interest) to get accurate information out there so the producer provided the right thing and the market demands the right thing.
What is going on now with our government data is practically criminal in the economic sense. Because of politically-based bias, real economic damage is potentially being done. I am all for “open source” science models.

To Phil,
okay now I see what you are saying.
I was modeling the ln(280ppm or 285ppm) to be at -0.4C rather than Zero.
This whole model is based on the anomaly (from the baseline) so it crosses Zero when the particular temperature series baseline anomaly passes Zero. Now each series has a slightly different baseline and when you are comparing series you have to match up the baselines but I wanted ln(280ppm) to be at -0.4C.

Bill – Thermal inertia of the climate system is pretty uncontroversial, see for example this
write up of a paper by Meehl et al which
quantifies the relative rates of sea level rise and global temperature increase that we are already committed to in the 21st century. Even if no more greenhouse gases were added to the atmosphere, globally averaged surface air temperatures would rise about a half degree Celsius (one degree Fahrenheit) and global sea levels would rise another 11 centimeters (4 inches) from thermal expansion alone by 2100.
“Many people don’t realize we are committed right now to a significant amount of global warming and sea level rise because of the greenhouse gases we have already put into the atmosphere,” says lead author Gerald Meehl. “Even if we stabilize greenhouse gas concentrations, the climate will continue to warm, and there will be proportionately even more sea level rise. The longer we wait, the more climate change we are committed to in the future.”
So the ‘physics’ explanation is that the heat largely goes into the oceans which take years to decades to warm in response, 70% of the surface is ocean and it takes around a decade for the surface layer to mix with the deep ocean …
The paper concludes with a cogent statement by Meehl: “With the ongoing increase in concentrations of GHGs [greenhouse gases], every day we commit to more climate change in the future. When and how we stabilize concentrations will dictate, on the time scale of a century or so, how much more warming we will experience. But we are already committed to ongoing large sea level rise, even if concentrations of GHGs could be stabilized.”
…
The inevitability of the climate changes described in the study is the result of thermal inertia, mainly from the oceans, and the long lifetime of carbon dioxide and other greenhouse gases in the atmosphere. Thermal inertia refers to the process by which water heats and cools more slowly than air because it is denser than air.
There is a discussion of the length of time to equilibrium in
this paper [may need a free subscription to access].
The AMO data before de-linear-trending is here … http://www.cdc.noaa.gov/Correlation/amon.us.long.mean.data
but see the caveats on the NOAA page linked earlier. Hope this helps.

Fine lines and CO2 absorbtion spectra
As I recollect A photon reacts to a CO2 molecule by changing its excitation state, either by changing the vibration mode of the atoms or by raising an electron’s energy going round one of the atoms to a higher level. I think IR absorbtion is in the latter category. Anyway there a a very large number of possible vibration modes and it requires different amounts of energy to move from one to the other. Each possible mode change creates an absorbtion line so there are lots of them

Great analysis, Bill. Just one question. given that the temperature response to increased CO2 is logarithmic, why do we only see a warming signal post 1970 or so? One would expect a greater warming signal early in the rise of CO2, rather than later. Or am I missing something?

One other quick question; if we are already committed to gross sea level rise and temperature rise because of GHG already emitted, and the ML data certainly shows that CO2 keeps on going up unabated despite everybody’s Kyoto committments; then why has the earth been cooling for the last ten years? We should have had about 1/10 of the ten degrees or so predicted for the year 2100 in temperature rise, instead we have had a very sizeable temperature fall; so much for the effect of thermal lag times.
Some people may buy Meeh’s thesis (I do agree there are thermal lags) but why would the temperature go the wrong way, when the “forcing” continues to climb in the same direction.
As to the multiple fine lines in the CO2 IR spectrum; I’m familiar with the so-called symmetrical stretch mode which is not IR active, and the asymmetrical stretch mode which is IR active around 4 microns or so, and the degenerate bending mode which I believe is the 14.77 or 15 micron mode that everyone talks about (haven’t been able to get a definitive value for what wavelength that is.
But anything involving elecron levels in the atoms; as distinct from molecular vibrations, would seem to involve much higher photon energies than required for the molecular effects, so one would expect them to be visible light or shorter wavelengths.
Since CO2 is a linear molecule with no dipole moment, it would not be too active in rotation about the molecular axis, and other rotation modes say about the carbon atom and other axes, would seem to be much longer wavelengths.
But i’m eager to learn, so if someone can explain the energy level foundation for the many fine lines in the IR spectrum of CO2 I’m all ears.

Bill Illis: The following link is to a google spreadsheet with the ERSST.v2 version of NINO3.4 SST and SST anomaly data. It’s the monthly data fresh out of NOAA’s NOMADS system from January 1854 to October 2008. I tried to replace the Trenberth data with it, but ran into the following problem.
I entered annualized ERSST.v2 NINO3.4 data into the Annual Temperature Anomaly Model, starting at 1871, at column C, row 44. It created a host of #VALUE errors. I thought the difference in climatology (The ERSST.v2 base years are 1971 to 2000) was putting the data was out of a working range for the model, so I recalculated the anomalies based on the same base years as the Trenberth NINO3.4 data (1950-1979). That didn’t help.
http://spreadsheets.google.com/pub?key=p4p8emYTQFThxsDz4aQ05NA
Please try the ERSST.v2 data and see if it works for you.
Regards

George E. Smith (14:57:31):
See the animation on:
http://www.atmosphere.mpg.de/enid/1__Oxidants___Observation/-_observation_spectroscopy_l6.html
I have the same questions.
Perhaps, I need to understand the interaction
H2O + CO2> H2CO3
in the atmosphere.

To Bob Tisdale,
I got your ERSST.v2 data in and working. I have to say google docs does do a mess of things so we probably shouldn’t use it again until they get the bugs out.
On the good side, this data certainly works and produces a greater coefficient for the Nino 3.4 region (lagging it by 3 months seemed to work better again). The warming signal against CO2 also drops to about 1.65C per doubling.
On the downside, the r^2 falls from 0.783 to 0.745 and the errors are a little larger and/or show more consistently above or consistently below characteristics.
But it does not look bad at all. This dataset more consistently catches the spikes for example. Here are the two charts you would want to see.
http://img265.imageshack.us/img265/3814/btisdalehadcrut3oe1.png
http://img383.imageshack.us/img383/4695/btisdalewarmingqg8.png

Bill. This link
http://www.sciencemag.org/cgi/ijlink?linkType=ABST&journalCode=sci&resid=229/4716/857
Should get you to the Hansen(1985) paper without the need for a paid subscription. His results are summarised in the 2005 paper referenced earlier:
The lag in the climate response to a forcing is a sensitive function of equilibrium climate sensitivity, varying approximately as the square of the sensitivity (1), and it depends on the rate of heat exchange between the ocean’s surface mixed layer and the deeper ocean (2–4). The lag could be as short as a decade, if climate sensitivity is as small as 0.25°C per W/m2 of forcing, but it is a century or longer if climate sensitivity is 1°C per W/m2 or larger (1, 3). Evidence from Earth’s history (3–6) and climate models (7) suggests that climate sensitivity is 0.75° ± 0.25°C per W/m2, implying that 25 to 50 years are needed for Earth’s surface temperature to reach 60% of its equilibrium response (1).
http://www.sciencemag.org/cgi/content/full/308/5727/1431
I note he published a temperature forecast just a few years later which did not include any ocean absorption that we can tell of since his Scenario B forecast temps are about twice as high as they are currently.
Not so. Hansen’s scenarios were based on an early version of the NASA climate model, of course this includes the physics of ocean heat takeup. What is your source for the claim that Scenario B is currently a 100% overestimate?
The temperature trend since 1979 indicates we can never reach the 3.25C doubling level no matter how much the oceans absorbs or how much lag time there is. It would take a thousand years.
The trend in the UAH data, which shows the least warming of the various global datasets, is approx 0.17C/decade, so a linear extrapolation takes just 200 years to reach a highly dangerous 3.4C increase. In fact the warming is more likely to be exponential, due to thermal inertia and the impact of positive feedbacks, notably absent from this analysis. One example of a positive feedback: as the Arctic ice melts, the reduced albedo raises the local temperature and causes melting of the permafrosts, releasing trapped carbon. The Arctic permafrost contains twice as much carbon as the entire global atmosphere. See these recent papers
http://www.cgd.ucar.edu/ccr/dlawren/publications/lawrence.grl.submit.2008.pdf
http://www.bioone.org/perlserv/?request=get-document&doi=10.1641%2FB580807&ct=1
Moving on,
Richard Courtney: Please explain how liquid water absorbs heat but does not warm until some time later. My understanding is that – in the absence of latent heat exchange – any warming would be instantaneous.
Tell me Richard, last time you made coffee, when you switched on your kettle, applying a positive energy transfer, did the water boil
(a) Instantaneously, or
(b) A few minutes later ?
Now imagine your kettle is ocean-sized and the energy flux is measured in a few W/m2. Are you seriously arguing that a such huge body of water will warm ‘instantaneously’?
George Smith why has the earth been cooling for the last ten years? We should have had about 1/10 of the ten degrees or so predicted for the year 2100 in temperature rise, instead we have had a very sizeable temperature fall; so much for the effect of thermal lag times.
George – which of the four major global temperature indices shows a ‘sizeable temperature fall’ over the last 120 months please? Here’s the data:
http://tinyurl.com/563bmc
They all appear to show an increase. Please explain.

Bill: Thanks for the update. I forgot to note earlier that the output of your model appears to generate a global temperature anomaly curve that comes much closer to the instrument data than at least one high-priced GCM. It will remain nameless so not to start a battle on this thread.
Question: At what cell did you paste in the ERSST NINO data and did you use the revised NINO data starting at Jan 1871? I want to make sure I’m looking at the same spreadsheet that you are when I include it.
Thanks again.

Smokey – the figure I gave is a simple linear fit to all the available UAH data,from Spencer and Christy, so there can really be no question of cherry picking. Your graph OTOH is a highly dubious polynomial fit widely condemned as misleading on this, of all, websites.

Don Keiler had asked earlier if there was any change in the rate of warming over time.
The changes are actually very hard to decifer.
My model based on ln (CO2) shows a gradual increase over time (not dissimilar to the very slightly exponential growth in Co2 levels) to where it is 0.15C per decade in the 2000s.
However, the actual observation data (after adjusting for the ENSO and the AMO) shows much more variation.
There is a very slight cooling trend from about 1890 to 1915. In the 1920s, warming jumps to about 0.2C per decade, then it falls to 0. From 1933 to 1945, it jumps to about 0.25C per decade and then falls rapidly to a negative value of -0.2C per decade from 1946 to 1955. From 1955 to 1975, warming is about 0.1C per decade. But from 1975 on, there is a gradual deceleration in the warming rate so that is very close to 0.0C per decade right now.
Complicated.
There is obviously more going on here than the model shows.

To John Philip
The UAH unadjusted temperature trend is just 0.13C per decade (not 0.17C).
The UAH data adjusted for the ENSO and the AMO produces a warming trend of just 0.03C per decade which is probably a little low but would produce no warming to worry about at all.

Phil. (19:44:42)
It seems that each instant after heat was applied the temperature rose. Looks pretty instantaneous to me.
====================================

To Phil and John Philip
Note we are talking about deep ocean temperatures here versus the sea surface (since the sea surface temps are already captured in the global temperature series.)
The data does show there is some warming in the deep oceans. There is a 0.1C increase in some latitudes (about 30% of the oceans) down to 1,000 metres and about 0.05C in some latitudes (about 15% of the oceans) down to 2,000 metres. So it appears there is, indeed, some warming of the deep oceans.
During the ice ages when surface temps fell by 5C, the deep oceans appear to have decreased in temp from their current 3C to about 0C. So the deep oceans are affected by the surface temps.
Water, however, is one of strangest chemicals around. When it solidifies as ice, it gets less dense and floats. Warmer water, however, rises to the top and colder water sinks to the bottom. If it freezes, it rises to the surface. Hence, any change in the surface sea temps takes a long, long time to influence the oceans at deeper levels. The very cold water stays at the bottom, the warmer water rises to the surface.
It almost takes a complete circulation of the oceans to make much difference at all, which can be a thousand years or more. The lag between surface temps and CO2 in the ice ages indicates we could expect 800 years for the deep ocean to be really influenced by the surface.
My issue with this is that global warmers refuse to say how much lag there is. None of Hansen’s papers that I could find (including the one linked to by John Philips) say anything about it.
More importantly, in a physical sense, the deep ocean absorption just means that more mass needs to be heated up by the increased greenhouse effect provided by increased CO2. We don’t warm to +3.25C, we only get to +1.85C and then an equilibrium is established. The deep oceans will continue to absorb energy from the surface continuously and it will start cooling again if that energy doesn’t continue rising. Once we get to a doubled CO2 level (and let’s say we stay there) there is no more warming to come once the deep oceans catch up.
That is my perspective on it. And I firmly believe the warmers need to be clear about this for once.

Bill – you’re right 0.13C/decade for UAH since 1979 is correct, I was confusing UAH with the RSS analysis, apologies for the confusion. However taking the regression analysis as published and extrapolating it forward suffers from these flaws:-
– It ignores the thermal inertia of the climate system, assuming that all the forcing applied is reflected in the temperature rise already observed. This is not the case, it is uncontroversial that the heat stored in the ocean will continue to cause a rise in surface temperatures for several decades.
– It uses detrended data for the AMO regression but (nearly) raw data for the ENSO regression. The analysis should be repeated using the same source data for both oscillations, the incorrect statement that the AMO data shows no trend should be addressed.
– It does not handle feedbacks correctly, more sophisticated models find that as water vapour increases (to choose just the most significant single feedback), the resulting greenhouse warming increases exponentially, acting to offset the logarithmic declining effetcs of additional CO2.
The question of the size of the lag between a radiative imbalance and the corresponding temperature increase does not have a simple single answer – some feedbacks, for example the disintegration of large ice sheets, operate on a scale of centuries, the IPCC’s figures for a doubling of CO2 use a definition of climate sensitivity that includes ‘fast’ feedbacks only, sometimes called the Charney sensitivity which assumes that the land surface, ice sheets and atmospheric composition stay the same.. See Chapter 10 of AR4 WG1.
Richard, later on in our thought experiment the kettle is switched off. The temperature as measured some distance from the heat source continues to rise for some time as the heat is distributed through the body of water. Same thing, but on a planetary scale.

“Would you please explain why you claim a sizeable cooling?”
That’s all only a play with the starting point. I just did the same with the last 80 months and here we go with a sizable cooling:
http://www.woodfortrees.org/plot/hadcrut3vgl/last:80/plot/hadcrut3vgl/last:80/trend/plot/gistemp/last:80/plot/gistemp/last:80/trend/plot/uah/last:80/plot/uah/last:80/trend/plot/rss/last:80/plot/rss/last:80/trend

Phil (22:58:19) That’s an excellent explication of a nice nuance. This is why the Jason measure of sea level are so important. Since Argos buoys only go down about two miles, if Trenberth’s ‘extra heat’ is being stored deep in the oceans, there should still be thermal expansion of volume of the oceans.
I particularly worry about the halt in the reported Jason data stream until very lately, and the attempt to jigger the Argos readings of the last four years back to warming. The evidence that the oceans are cooling is truly of more import than the recent atmosphere cooling.
===============================================

Earlier John Philips had linked to the unadjusted untrended AMO data. I have put this data into the model now. It is exactly the same data I used before except it has very slight trend in it, about 0.002C per year or about 0.02C per decade GW impact potential.
It produces some interesting results.
The coefficient for the AMO goes back up to 0.75 as we has seen in other times. The r^2 falls somewhat to 0.74 but the F-statistic jumps to by far the highest number I have seen at 738.
More importantly the warming residual left over falls to the infamous 1.24C per doubling (which the actually physics calculations say the number should be.) Interesting.
It also allows one to see better some of the changing over time warming signals I was seeing before. There is certainly a peak then fall-off starting in the late 1970s for example and other variations at other times.
Here is the Warming modeled chart.
http://img73.imageshack.us/img73/4331/hadwarmusinguntramorr6.png
I will have to think about if it is valid to use an AMO index which has a slight trend in it. The point about this regression method is to remove the natural variation from the climate. if the AMO is rising due to warming, then it can’t really be used for this purpose (although the untrended data could be). Other studies have shown that the AMO is a natural climate cycle that even has longer cycles lasting hundreds of years.
Any thoughts?

Those points about the interplay between sun, atmosphere, ocean surface and ocean depths are critical to the whole issue.
I have heard it said that the ocean height continues to rise despite the ocean surfaces cooling and so the global system is still warming even though SST and atmosphere seem to be cooling.
My explanation would be that when the ocean oscillations are negative then less heat energy is being released to the atmosphere but solar input to the oceans continues so that there is an increase of energy in the oceans despite a cooling of atmosphere, land and so climate. During such periods solar energy gets tucked away in the depths and is denied to the atmosphere so that energy radiates to space faster than it is replenished by energy released from the oceans.
Conversely a period of positive oscillations causing atmospheric warming would normally involve enough release of energy from the oceans to warm the atmosphere but reduce the total energy in the system. That should result in a fall in ocean height and normally would.
However it appears that even during the 25 year warming spell from 1975 to 2000 there was nevertheless a slow increase in ocean height which appears to falsify the above BUT at the same time there was a so called grand solar maximum. Thus it is possible that the energy in the system continued to increase during the warming spell despite a full set of positive ocean oscillations. All that is needed for that to happen is for the historically high solar input (not necessarily reflected solely by TSI) to be putting more into the system than the positive oscillations are releasing.
Any consideration of multidecadal movements of energy between ocean surfaces and depths and variable and intermittent releases of that energy to the atmosphere is currently missing from the whole debate but in my view it is critical.
Combine those energy flows with solar changes over several cycles and I suspect that all the changes we have observed so far will be fully explained without involving CO2 at all.

John S says:

And the surface temperature control in actual climate is provided by moist convection adjusting the vertical lapse rate in the atmosphere, not by the marginal radiative effect of trace gas concentrations.

This brings to mind something I cannot understand with respect to AGW claims about the marginal effect of CO2.
That is, what mechanism do they propose will actually cause thermal runaway as CO2 levels increase?
They seem to hint that increasing CO2 will cause more of the outgoing LWR to be absorbed, thus heating up the atmosphere, and then? Causing more water to be evaporated and thus heating up the atmosphere more?
However, for that to occur, the extra heat/energy in the atmosphere has to be transferred to water, ie the oceans. But this would depend very much on timing, since hot air rises, and only the small portion in contact with the sea can transfer that energy by conduction. Of course, radiative transfer could also occur, but that would depend on the mean free path at the frequencies involved, and the probability that a molecule of CO2 transfers its energy to another molecule in the atmosphere before it radiates that extra energy away.
So, it would seem to me that the effect of an increase in CO2 would be to increase the convection effect that John S refers to, although only marginally.

To John Philip,
Regarding the proper log formulas, I am really modeling all the GHGs here (using CO2 as a proxy for all of the them.) And I am modeling Temperature response.
The 5.35 ln (CO2/CO2o) is the formula for the “Forcing” of CO2 only (and there is a bunch of other formulas for the other GHGs and other forcings such as aerosols as well). In the most recent IPCC, the coefficient for CO2 was changed from 5.35 to 5.0.
With the 5.0 or 5.35 formula, one then gets a 3.45 Watts/m^2 impact from the CO2 forcing only which when multiplied by 0.75C /w/m^2 estimated temperature response to a forcing results in 2.6C per doubling of CO2 only.
When you add up all the forcings from all the GHGs and other feedbacks – the estimated forcing per doubling is 4.33 w/m^2 * 0.75C /w/m^2 = 3.25C per doubling.
In effect I am just regressing to find out how much forcing change there has really been to date (assuming forcings result in 0.75C per watt per metre although it really doesn’t matter what the number is). In effect, I am skipping all these steps and just regressing for the actual temperature response.
The warming models are really based on (using the anomaly C basis rather than Kelvin):
— 4.7 * ln(280) – 26.9 = -0.42C
— 4.7 * ln(560) – 26.9 = +2.84C
and the change is +3.25C per doubling
The regression returns
— 2.7 * ln(280) – 15.8 = -0.42C
— 2.7 * ln(560) – 15.8 = +1.44C
and the change is +1.85C per doubling
I was hoping I wouldn’t have to get into this discussion because it is very messy. I fell for this trap too a couple of times when I was designing it (as Anthony Watts can attest to). There are a lot of coincidences in these numbers.
And perhaps the modelers, in trying to nail down every little impact in “forcings” which may be based on calculations that are not correct to start with (where did the 5.35 come from anyway) , they have lost a little perspective on what they are trying to do which is model a Temperature response. Is the climate actually responding in “Temperatures C” rather than in “minute forcings in watts per metre squared”, the way it is supposed to.
I got quite a few “Watts” into that post.

Tom Vonk says:

The Planck’s distribution of the excited vibrationnal levels of CO2 demands that the proportion of excited levels stays CONSTANT for a given temperature .
Consequence is that CO2 simply must radiate away what it absorbs because else we have no more LTE .

Bear with me here as I am trying to understand this, and may have to go away and read a physics text book.
However, what says that the temperature must stay CONSTANT? When the atmosphere, via CO2 increases, absorbs more energy, wouldn’t its temperature shift upwards and reach a different LTE point?

To Basil,
I did do the RSS tropics and the RSS northern hemisphere. (There is a nice fit to the Tropics).
http://img151.imageshack.us/img151/1222/rsstropicslz2.png
http://i463.photobucket.com/albums/qq360/Bill-illis/RSSNorthHemisphere.png
The warming in the Tropics for RSS is about 0.045C per decade which is basically the same as the global number. The Northern Hemisphere is higher at about 0.07C per decade.
I, as well, have not seen a very good explanation for why the temperature in the northern hemisphere is rising faster.
One little explanation might be that the AMO has been cycling upward since 1975. The reconstruction shows the AMO is much more important in the northern hemisphere than it is for the global temp series or for the Tropics. In the Tropics, the ENSO becomes dominant and the ENSO doesn’t really have long cycles of consistently up or down – just a lot of short sharp swings.
And thanks for the link to the regional Hadcrut3 data series. I have not used these specific breakdowns yet and will try them out.

Moderator:
Sorry, I clicked on the wrong page before I submitted this. I reposted on the correct page. Please remove the above comment as it is not on topic here.
REPLY: It’s the holiday, not to worry – Anthony

I trust the Moderator will not post this if it is straying too far from the important point of Bill Illis’s analysis, but it concerns the natures of ‘evidence’ and ‘modelling’ (the analysis is a model).
Phillip Bratby says:
“The quote from the Hansen 1985 paper includes “Evidence from Earth’s history (3–6) and climate models“. Since when have climate models been able to produce evidence? I always thought evidence came from measurements, not from predictions!”
I agree. One my peer review comments for the IPCC AR4 (which it is not surprising was ignored) said the following:
Page 2-47 Chapter 2 Section 2.6.3 Line 46
Delete the phrase, “and a physical model” because it is a falsehood.
Evidence says what it says, and construction of a physical model is irrelevant to that in any real science.
The authors of this draft Report seem to have an extreme prejudice in favour of models (some parts of the Report seem to assert that climate obeys what the models say; e.g. Page 2-47 Chapter 2 Section 2.6.3 Lines 33 and 34), and this phrase that needs deletion is an example of the prejudice.
Evidence is the result of empirical observation of reality.
Hypotheses are ideas based on the evidence.
Theories are hypotheses that have repeatedly been tested by comparison with evidence and have withstood all the tests.
Models are representations of the hypotheses and theories.
Outputs of the models can be used as evidence only when the output data is demonstrated to accurately represent reality.
If a model output disagrees with the available evidence then this indicates fault in the model, and this indication remains true until the evidence is shown to be wrong.
This draft Report repeatedly demonstrates that its authors do not understand these matters. So, I provide the following analogy to help them. If they can comprehend the analogy then they may achieve graduate standard in their science practice.
A scientist discovers a new species.
1.
He/she names it (e.g. he/she calls it a gazelle) and describes it (e.g. a gazelle has a leg in each corner).
2.
He/she observes that gazelles leap. (n.b. the muscles, ligaments etc. that enable gazelles to leap are not known, do not need to be discovered, and do not need to be modelled to observe that gazelles leap. The observation is evidence.)
3.
Gazelles are observed to always leap when a predator is near. (This observation is also evidence.)
4.
From (3) it can be deduced that gazelles leap in response to the presence of a predator.
5.
n.b. The gazelle’s internal body structure and central nervous system do not need to be studied, known or modelled for the conclusion in (4) that “gazelles leap when a predator is near” to be valid. Indeed, study of a gazelle’s internal body structure and central nervous system may never reveal that, and such a model may take decades to construct following achievement of the conclusion from the evidence.
Richard

Okay, here is the problem with the reconstruction and why it doesn’t work really, really well.
The Southern Hemisphere temps (as linked to by Basil) are not matched up by the ENSO or AMO indices. I tried the Antarctic oscillation linked to by evanjones and this gets one closer but it is still off by quite a bit.
Does anyone know of a good Southern Ocean Index to try?
The Southern Oscillation Index is more related to the El Nino and La Nina phenomenon rather than southern ocean temps as the name would indicate so that one doesn’t work – in fact the ENSO is negatively correlated with southern hemisphere temps which is a little strange I guess except when one considers that the ENSO develops out of the ocean circulations from the southern oceans sometimes and, in fact, lags the southern ocean temps versus leading global temperatures as it does. A little counter-intuitive but nonetheless.
Here is the problem.
http://img122.imageshack.us/img122/7797/shtempanomalybq1.png
Any ideas for a southern ocean index which matches this?
And Richard, I agree with you completely. Empirical evidence is king and should always overrule any theory. It is the basis for science and medicine and the reason why civilization has advanced in recent centuries. I don’t know why theory overrules evidence in the global warming field however.

Just catching up with all the discussions on this thread so I could easily have missed or misunderstood something but, with regards to the “ocean warming”
Richard Courtney writes
(c) The heating from AGW of the ocean is (i) mostly direct radiant IR input that is absorbed within the top few meters of the ocean,
Shouldn’t that be millimetres – or even fractions of mm. I was under the impression that IR only penetrated the top ‘skin’ of liquid water. I’ve seen Doug Hoyt demonstrate this using transmission formula with appropriate absorption coefficients for typical IR wavelengths.
This raises the question (for me at least) as to how increased GHGs warm the ocean. Some AGWers seem to be arguing that, rather than warming from the direct downward IR effect, increased GHGs actually slow the rate of ocean cooling.

I forgot the problems with the “arrow” symbols .
In the above collisional reaction it shoud read :
CO2* + N2 (-) CO2 + N2* where the “(” and “)” are left and right arrows .

There is a key assumption here, i.e.
The ENSO and the AMO are capable of explaining almost all of the natural variation in the climate. and
The coefficient for the Nino 3.4 region at 0.058 means it is capable of explaining changes in temps of as much as +/- 0.2C.
The coefficient for the AMO index at 0.51 to 0.75 indicates it is capable of explaining changes in temps of as much as +/- 0.3C to +/- 0.4C.
That is, the essay assumes that correlation demonstrates causality. This is a logical fallacy, without considering the underlying physics it is impossible to conclude whether the oscillations are driving the temperature or the oscillations are modified by the changing temperatures, As Trenberth and Hoar (2001) found
Both the recent trend for more ENSO events since 1976 and the prolonged 1990-1995 ENSO event are unexpected given the previous record, with a probability of occurrence about once in 2,000 years. This opens up the possibility that the ENSO changes may be partly caused by the observed increases in greenhouse gases.
If this is the case then simply subtracting the ENSO index from the observed temperatures will not give the ‘real’ residual global warming signal.
From an eyeball of the first chart it seems the good correlation starts to break down in the second half of the 20th century as GHG warming becomes dominant. The model attempts to plug this gap with a formula based on the multiple of the natural log of CO2 plus an arbitrary constant, which gives a reasonable match. The expected global warming from theory is given as:
When you add up all the forcings from all the GHGs and other feedbacks – the estimated forcing per doubling is 4.33 w/m^2 * 0.75C /w/m^2 = 3.25C per doubling.
In effect I am just regressing to find out how much forcing change there has really been to date (assuming forcings result in 0.75C per watt per metre although it really doesn’t matter what the number is). In effect, I am skipping all these steps and just regressing for the actual temperature response.
And this is expressed as the formula:
The warming models are really based on (using the anomaly C basis rather than Kelvin):
— 4.7 * ln(280) – 26.9 = -0.42C
— 4.7 * ln(560) – 26.9 = +2.84C
and the change is +3.25C per doubling
The regression returns
— 2.7 * ln(280) – 15.8 = -0.42C
— 2.7 * ln(560) – 15.8 = +1.44C
and the change is +1.85C per doubling
In other words the ‘regression’ simply uses lower values for the multiplier and constant.
This is not legitimate, the 0.75C/W/m2 figure is an expression of the climate sensitivity, that is the expected temperature rise produced by a given forcing. However the IPCC define climate sensitivity as
the equilibrium change in the annual mean global surface
temperature following a doubling of the atmospheric equivalent
carbon dioxide concentration.
The key point being that there is thermal inertia in the climate system and so the observed temperatures are only expected to match the modelled temperatures once equilibrium is reached (this is a convenient construct, in fact equilibrium is never reached, but it is a useful concept), Hansen et al (2005) finds :
Evidence from Earth’s history and climate models suggests that climate sensitivity is 0.75° ± 0.25°C per W/m2, implying that 25 to 50 years are needed for Earth’s surface temperature to reach 60% of its equilibrium response.
In other words in the half century following a change in forcing as the climate system is still responding, it is unsurprising that a simple logarithmic model with reduced coefficients gives a reasonable match to observed temperatures, but it is not valid simply to extrapolate this forward.
Some of the forcing goes to increasing the ocean heat content, this figure from the same paper shows how the models’ estimate of the increased OHC in the top 750m compare with observations. Any model that assumes all the extra forcing goes purely to increasing surface temperatures must explain the origin of this extra heat.
As explained above the statement …
As well, the AMO appears to be a natural climate cycle unrelated to global warming. is incorrect because the dataset chosen had already had the trend removed, the trend is described as
It is exactly the same data I used before except it has very slight trend in it, about 0.002C per year or about 0.02C per decade GW impact potential.
Actually slightly over 0.025C/ decade. Given that the data cover 15 decades, the difference over the dataset is approx 0.375C, equivalent to more than 50% of the 20th century warming. The fact that a change of this magnitude has an apparently minor impact on the model tells us something very interesting about its robustness.
Let us take a brief look at what the IPCC models which include the ocean physics and feedbacks actually projected for recent decades. The figures from the TAR are here. Taking Scenario A2 as a reasonable midrange choice and a good match to the actual forcings trajectory the temperatures were projected to increase by 0.35C from the baseline year of 1990 to 2010, a linear trend of 0.175C/decade. The actual trend in the monthly HADCrut dataset over the period since January 1990 to 3dp is 0.176C/decade.
Not bad.

Bill Illis:
You ask;
“But I’m really looking to pull the natural variation out of the total global temp anomaly so it appears I need something for the southern hemisphere.”
OK, I understand what you want and I cannot provide real help. However, there is a possibility that – I think – warrants mention if – as I hope – you publish your work.
I remind that I wrote above:
“Other natural cycles may also be affecting the trend, and the method is not applicable to cycles with lower frequency than the time series. Such a very low frequency oscillation does seem to exist. There is an apparent ~900 year oscillation that caused the Roman Warm Period (RWP), then the Dark Age Cool Period (DACP), then the Medieval Warm Period (MWP), then the Little Ice Age (LIA), and the present warm period (PWP). ”
And I later wrote above:
“Additionally, the water that went into deep ocean ~800 years ago is returning to the surface now. This could be affecting ocean surface layer pH, ocean surface layer temperature, and – therefore – atmospheric carbon dioxide concentration (mostly by the pH change). It could be expected to affect the magnitude of the residual trend detected in the analysis provided by Bill Illis. ”
In other words, there is an apparent natural cycle with too great a frequency to be analysed by your method that could be expected to provide warming which was stored in the oceans during the MWP and is now being returned to the atmosphere.
Indeed, this possibility is proclaimed by those who advocate “AGW in the pipeline”.
However, as I also said;
“The Second Law of Thermodynamics says that the atmospheric temperature rise induced by return to the surface of that AGW stored in deep ocean cannot be more than the temperature rise that put it into the ocean. Therefore, it threatens “our children’s children” (in ~800 years time) with no more AGW than we experienced in the twentieth century. And that warming is so small that we cannot discern it from natural variation.”
Therefore, this postulated ‘warming from the MWP’ cannot provide a temperature rise greater than the temperature rise from the Dark Age Cool Period (DACP) to the Medieval Warm Period (MWP). But, conservatively it could be assumed to have provided 0.2 deg.C to observed recent Southern Hemisphere temperature rise.
I repeat that I know this fails to answer your need, but I do think it merits at least a footnote in the publication I hope you will provide.
Richard

John Phillips says – “In other words the ‘regression’ simply uses lower values for the multiplier and constant (for the warming reconstruction). ”
No, I’m saying they ARE lower so far. Not simply uses, they are lower.
I can perhaps adjust the global warming model’s log formula to include a “Time” component which is missing so far as follows:
— 2.7 * ln(560) – 15.8 + (Another up to 1,000 years of additional not-really-well-defined-or-explained warming in the pipeline) = 3.25C
So far, the pipeline has some leaks in it.
—-
And I had read the paper you linked to earlier about the AMO when it was discussed on realclimate a week or so ago.
I note the abstract states the AMO is a natural climate cycle independent of global warming.
“The results imply the AMO is a genuine quasi-periodic cycle of internal climate variability persisting for many centuries, and is related to
variability in the oceanic thermohaline circulation (THC). This relationship suggests we can attempt to reconstruct past THC changes, and we infer an increase in THC strength over the last 25 years. Potential predictability
associated with the mode implies natural THC and AMO decreases over the next few decades independent of anthropogenic climate change.”
And they did forecast (so far correctly) that it would weaken in the next decades.

John Philip asserts:
“Actually, although IR only penetrates less than 1 mm an important part of the mechanism by which GHG forcing heats the ocean is IR absorbtion in the surface skin layer which reduces the temperature gradient across the layer, causing more of the heat from sunlight absorbion to be retained in the water below.”
Really? Prove it.
The assertion assumes little mixing of the ocean surface layer. Indeed, it assumes a “surface skin layer” that is “less than 1 mm” thick and is independent of the underlying water. But the entire surface layer is turbulent and it is very turbulent near the surface.
While the possibility of the assertion cannot be rejected, it is so implausible as to be worthy of rejection until supporting evidence is provided.
As a postscript, I add that I spent the first 3 years of this decade living on a boat in an attempt to quantify energy interactions at sea surface. My endeavour was defeated – so the project was a failure – by effects of surface ripples (n.b. ripples, not waves) that I do not think had been previously detected. Hence, having wasted those three years of my life, I am extremely sceptical of any simplistic assertions concerning energy interactions at sea surface.
Richard

Jeff Id, re feedbacks … published just last month, Dessler et al found …
Between 2003 and 2008, the global-average surface temperature of the Earth varied by 0.6
C. We analyze here the response of tropospheric water vapor to these variations. Height-resolved measurements of specific humidity (q) and relative humidity (RH) are obtained from NASA’s satelliteborne Atmospheric Infrared Sounder (AIRS). Over most of the troposphere, q increased with increasing global-average
surface temperature, although some regions showed the opposite response. RH increased in some regions and decreased in others, with the global average remaining nearly constant at most altitudes. The water-vapor feedback implied by these observations is strongly positive, with an average magnitude of lq = 2.04 W/m2/K, similar to that simulated by climate models. The magnitude is similar to that obtained if the atmosphere maintained constant RH everywhere
and concluded …
The existence of a strong and positive water-vapor feedback means that projected business-as-usual greenhouse gas emissions over the next century are virtually guaranteed to produce warming of several degrees Celsius. The only way that will not happen is if a strong, negative, and currently unknown feedback is discovered somewhere in our climate system.
(My bold).
cheers,
JP

For a discussion of the ‘ocean skin’ issue please see my article here:
http://co2sceptics.com/news.php?id=1645
I would add that natural swings in the power of the atmospheric greenhouse effect are likely to occur routinely as a result of natural changes in the total amount of water vapour in the atmosphere.
As the Earth warms for whatever natural reason the atmosphere will hold more water vapour and if it cools for whatever natural reason then the atmosphere will hold less water vapour.
Either way the natural water vapour variations will dwarf by orders of magnitude any changes in the power of the greenhouse effect that could be attributed to human CO2.
Furthermore those natural water vapour swings have never caused us to cross a tipping point so why should a tiny variation induced by any effect from human CO2 do so ?

This is a great analysis. My only issue with it is the apparent assumption of no cross biases for unevaluated parameters.
For example, suggesting that the remaining trend may have some small, but basically minimal room for influence on the temps is a bit mesleading. It may well be true that there is little additional explanation in the temperature variations or trends in addition to what’s been looked at simply because ENSO and AMO are proxy measures for these otehr things, but that is different from suggesting a lack of solar influence. To the extent that the ENSO and AMO occur precisely from other influences means that they are really a proxy measure for something else. It would be similar to saying that age as an insurance rating parameter isn’t really the risk factor, but it is a proxy for experience.
This doesn’t necessarily change the analysis at all, but it may shift the question. Does the sun influence the El Nino and/or AMO cycle? And how much? Is the relative magnitude of El Nino affected by GHGs?
I am also curious as to why the PDO is not considered. Even with a good fit, I’m just uncomfortable with the assumption that global temps so easily boils down to three parameters. I personally suspect that some of the attribution currently given to GHGs in the analysis may even yet be overstated if other things were considered.
It may seem like I’m being too critical, I suppose. I don’t mean to be. All in all, I find it to be a very intriguing study.

Moderator – Fair enough, however FYI the first line of the article linked to and authored by Stephen Wilde states
Stephen Wilde has been a Fellow of the Royal Meteorological Society since 1968. however I counted half a dozen factual errors in the first few paras of the piece, which I thought odd for someone claiming to be a FRMetS.
The RMS lists those entitled to use the FRMetS title on its website
http://www.rmets.org/about/people/fellows.php
There is no Stephen Wilde listed. It also lists the requirements …
Becoming a Fellow normally requires a formal qualification (eg. a first degree in a science subject and/or post-graduate degree or an NVQ in a relevant discipline) and at least five years of professional experience within or directly related to meteorology. Exceptionally, long experience and performance at a high professional level, suitably attested by peer review, can replace the requirement for a formal academic or vocational qualification. MSc or PhD study in a relevant subject counts as one or two years experience respectively.
which contrasts with Mr Wilde’s profile which states he runs a Law firm and follows Meteorolgy in his spare time
http://co2sceptics.com/contributors.php
Now there may be some innocent explanation, misunderstanding or administrative error, but given the recent post about Karl’s phantom doctorate perhaps we could ask Mr Wilde to explain, as it appears to be a primae facie case of someone impersonating a meteorologist
😉
REPLY: My initial issue was with claims (or lack thereof) made in comments, however it appears that you aren’t the first one to notice this regarding articles outside of this blog.
See
http://petesplace-peter.blogspot.com/2008/05/myth-of-man-caused-global-warming.html
I agree that he is not on the list. But let’s hear why. Perhaps there is a valid explanation.
Mr. Wilde, what say you?

Tom Vonk says:

The Planck’s distribution of the energy levels has a very low sensibility to temperatures – around the room temperature only about 5 % of the CO2 molecules are excited . At lower temperatures even less .

Does this mean that at any one instant, only 5% of the CO2 molecules are able to heat the atmosphere by transferring energy to other species?

Hmmmm … a seems the RMS rules changed in 2003, the new stringent requirements were introduced, and Fellows elected before that date may continue to describe themselves as a such purely as a courtesy title but not use the formal FRMetS appellation as a sign of professional competence.
Still, most people are not aware of this distinction and would be bound to conclude that someone describing themselves as a Fellow of the RMS was indeed a FRMetS and a professional meterologist, rather than an enthusiastic amatuer.
Incidentally, the Code of Conduct for Fellows (FRMetS) states they must use the name of the Society only when duly authorised.

Mr Wilde – Thanks for clearing that up, as I said, it was quite possibly a misunderstanding – which turns out to be the case. Most people will find it a little odd that someone with no professional meteorological qualifications, publications or experience, and who is ineligible to use the title FRMetS can legitimately describe themselves as a Fellow of the Royal Meteorological Society, but I accept that this is indeed the case.
Anyway, this is drifting both off-topic and ad-hom, as it is meant as a ‘discussion piece’ I may add a few thoughts and corrections later if I get time, but probably not here. …
JP (B.Sc) 😉

After examining the AMO index issues more thoroughly, I have decided it is still valid to use the AMO index as a natural climate variable which is not related to global warming.
It is apparent the untrended index should be used, however, given the AGW community would not accept using the raw untrended data (given it does have a trend.)
Earlier in developing this model, I had downloaded a Long-Term AMO reconstruction by Stephen Gray et al which goes back to 1572. I decided not to use it since it is just annual data and has greater variability than the current AMO index method. There are a few inconsistencies in the time periods when the indices overlap but agree on the general up and down swings.
Here it is.
http://img510.imageshack.us/img510/1639/ltamoindexxr2.png
This reconstruction shows that the AMO appears to be a natural climate cycle that even has greater swings in temperatures in the past than the current index shows. Some of these swings match up with the climate changes we know about in history such as the onset of the Little Ice Age for example.
Here is what the Raw Untrended AMO Index looks like.
http://img357.imageshack.us/img357/900/trendedamoindexkq9.png
While it does have what seems to be a pretty rapid trend upward, some of this is just a result of the scale and the time period covered. The trend upward over the past 140 years would not be inconsistent with what is seen in the longer reconstruction.
The increase is only 0.024C per decade and, in terms of the regressed coefficient for the AMO, it would have just a 0.018C per decade GW impact (the models predict about 10 times as much).
Other studies conclude the AMO is a natural cycle, so therefore, I believe it can continue to be used.
Furthermore, it clearly impacts monthly temperatures so any reconstruction should use it. The untrended data does not contain a global warming signal. What may be a completely natural increase in the AMO over the past 140 years, can be left for the global warming residual.

I kept saying “Raw Untrended” in the above and that should say “Raw Trended”.

is not an accurate description of the process. The heating occurs as a result of solar irradiance penetrating the surface, the IR radiation reduces the temperature gradient at the surface layer slowing the release of that heat back to the atmosphere.
JP
what about the mixing? or if there’s no mixing – evaporation?
Though we’ve been talking about 1 mm penetration isn’t the true value more like 1/20 mm, i.e. ~99% is absorbed within 0.05mm.
I too find the AGW explanation for ocean warming (or lack of cooling) totally implausible – and certainly within the timeframe of decades.

To Sean
Underlying the ENSO and the AMO is the thermohaline ocean circulation.
The AMO is where the once warm ocean water sinks to the depths and becomes part of the deep ocean. The energy transfer between the ocean and the atmosphere as a result of this process creates the forcing/temperature change – sometimes warm, sometimes less warm.
The ENSO is not normally thought to be a node of the ocean circulation but has similar characteristics in that deeper and colder ocean water is sometimes brought to the surface when the Trade Winds are stronger than normal for an extended period of time. Colder water wells up and there again is an energy exchange. When the Trades slow down for an extended period of time, there is less up-welling and more surface heating from the Sun in the Nino region and again there is then a warm energy exchange rather than a cooling energy exchange.
Now if there were an ocean circulation index, we wouldn’t the two measures.

For those unconvinced about the existence of the ocean surface skin layer and its role in the increase in OHC here’s another blatent appeal to authority, NASA this time. It’s got figures and charts and references and everything …
Over the surface of the ocean, there frequently exists a very thin layer called the surface skin layer in remote sensing sciences (Schluessel et al., 1990) (Figure 2). The existence of the surface skin layer can be demonstrated both in theory (Hinzpeter, 1967, 1968) and in observations (Ewing and McAlister, 1960; Saunders, 1967; Clauss et al., 1970; Schluessel et al., 1990) by the need to regulate the long wave radiation and the sensible and latent turbulent heat fluxes across the sea surface. Above and below the thin skin layer, turbulent eddy fluxes enhance heat flux in the ocean and/or atmosphere across the interface. However, the eddy cannot transport heat across the ocean surface by itself. The heat balance in the skin layer must be accomplished by molecular processes, hence the thin skin layer. The actual thickness of the skin layer depends on the local energy flux of the molecular transports, which is usually less than 1 mm thick and can persist at wind speed up to 10 m/s. For stronger winds, the skin layer is destroyed by breaking waves. Observations indicate that the skin layer can re-establish itself within 10 to 12 seconds after the dissipation of the breaking waves (Ewing and McAlister, 1960; Clauss et al., 1970).

Richard Courtney: “4.From (3) it can be deduced that gazelles leap in response to the presence of a predator.”
What you are describing is induction, not deduction. In this instance you have argued from the particular to the general.
“Gazelles are observed to always leap when a predator is near” is a particular observation, or observations, that is, limited to a finite set.
“Gazelles leap in response to the presence of a predator” is a general conclusion. Therefore, the argument is inductive. A deductive argument would be:
– Gazelles leap in response to the presence of a predator
– This animal leaps in response to the presence of a predator
– This animal is a gazelle.
Scientific hypotheses/theories are deductive. A general case is stated, then particular observations/tests made for or against the general claim. These observations/tests are evidence. Climate models can act as evidence because they test the theory.

Brendan H says:

Climate models can act as evidence because they test the theory.

That would be the case if climate models faithfully implemented the theory, however, that would seem to be far from the case.
They contain, as far as I can tell, all sorts of ad-hoc forcings to get them to conform to the actual temperature record.
Who was it who said give me five parameters and I can model an elephant.

To evanjones,
I put the Indian Ocean SST index into the reconstruction and it certainly helps with the southern hemisphere reconstruction and it also helps with the overall global temp reconstruction.
Three problems, however. The data ends in 2004 and doesn’t seem to be updated anymore. Second, I tried other Indian Ocean Indices including the dipole and these other ones don’t provide an improved reconstruction. Thirdly, the Indian Ocean SST index covers the whole Indian Ocean and I don’t want to use indices that cover really large sections of the oceans – the complete ocean index would be the best reconstruction of course but then it would be like trying to reconstruct a dataset when you are already using 70% of the dataset as your independent variable. It is one of the reasons I used just the Nina 3.4 regions.
So, back to the drawing board again.
I’ve been thinking about the question Sean Houlihane asked and what is the underlying forcing (or let’s say rationale) with the ENSO and the AMO which makes them good choices to reconstruct climate variations.
And the answer really is that these two regions are the most active regions where the Oceans are exchanging energy (heat and cold) with the Atmosphere. There is far, far more energy being transferred back and forth in these two regions than any other …
… Except for the third big region which is the opposite of the AMO in the southern hemisphere and that is the downwelling region in the Weddell Sea off Antarctica.
http://upload.wikimedia.org/wikipedia/commons/4/4c/Thermohaline_Circulation_2.png
So this is the missing piece of the puzzle. No index for this region however. Any ideas by anyone? Bob Tisdale or David Smith still around?