I few months ago, I had a paper accepted in the Journal of Geophysical Research. Since its repercussions are particularly interesting for the general public, I decided to write about it. I would have written earlier, but as
I wrote before, I have been quite busy. I now have time, sitting in my hotel in Lijiang (Yunnan, China).
A scene in Lijiang near my hotel, where most of this post was written. More pics here.
A calorimeter is a device which measures the amount of heat given off in a chemical or physical reaction. It turns out that one can use the Earth's oceans as one giant calorimeter to measure the amount of heat Earth absorbs and reemits every solar cycle. Two questions probably pop in your mind,
a) Why is this interesting? and,
b) How do you do so?
Let me answer.
One of the raging debates in the climate community relates to the question of whether there is any mechanism amplifying solar activity. That is, are the solar synchronized climatic variations that we see (e.g., take a look at fig. 1
here) due to changes of just the solar irradiance, or, are they due to some effect which amplifies the solar-climate link. In particular, is there an amplification of some non-thermal component of the sun? (e.g., UV, solar magnetic field, solar wind or others which have much larger variations than the 0.1% variations of the solar irradiance). This question has interesting repercussions to the question of global warming, which is why the debate is so fierce.
If only solar irradiance is the cause of the solar-related climate variations, it would imply that the small solar variations cause large temperature variations on Earth, and therefore that Earth has a very sensitive climate. If on the other hand there is some amplification mechanism, it would imply that solar variations induce much larger variations in the radiative budget, and that the observed temperature variations can therefore be explained with a smaller climate sensitivity.
Since global warming alarmists want a large sensitivity, they adamantly fight any evidence which shows that there might be an amplification mechanism. Clearly, a larger climate sensitivity would imply that the same CO
2 increase over the 21
st century would cause a larger temperature increase, that is, allow for a more frightening scenario, more need for climate research and climate action, and more need for research money for them. (I am being overly cynical here, but it some cases it is not far from the truth). Others don't even need research money, don't really care about the science (and certainly don't understand it), but make money from riding the wave anyway (e.g., a former vice president, without naming names).
On the other end of the spectrum, politically driven skeptics want to burn fossil fuels relentlessly. A real global warming problem would force them to change their plans. Therefore, any argument which would imply a small climate sensitivity and a lower predicted 21
st century temperature increase is favored by them. Just like their opponents, they do so without actually understanding the science.
I of course, don't get money from oil companies. In fact, I am not a republican (hey, I am even the head of a workers union). I care about the environment (I grew up in a solar house) and think there are a dozen good reasons why we should burn less fossil fuels, but as you will see below, global warming is not one of them. In fact, I am driven by something strange... the quest for the knowledge!
With this intro, you can realize why answering the solar amplification question is very important (besides being a genuinely interesting scientific question), and why answering it (either way) would make some people really annoyed.
So, what do the oceans tell us?
Over the 11 or so year solar cycle, solar irradiance changes by typically 0.1%. i.e., about 1 W/m
2 relative to the solar constant of 1360 W/m
2. Once one averages for the whole surface of earth (i.e., divide by 4) and takes away the reflected component (i.e., times 1 minus the albedo), it comes out to be about 0.17 W/m
2 variations relative to the 240 W/m
2. Thus, if only solar irradiance variations are present, Earth's sensitivity has to be pretty high to explain the solar-climate correlations (see the collapsed box below).
However, if solar activity is amplified by some mechanism (such as hypersensitivity to UV, or indirectly through sensitivity to cosmic ray flux variations), then in principle, a lower climate sensitivity can explain the solar-climate links, but it would mean that a much larger heat flux is entering and leaving the system every solar cycle.
Now, is there a direct record which measures the heat flux going into the climate system? The answer is that over the 11-year solar cycle, a large fraction of the flux entering the climate system goes into the oceans. However, because of the high heat capacity of the oceans, this heat content doesn't change the ocean temperature by much. And as a consequence, the oceans can be used as a "calorimeter" to measure the solar radiative forcing. Of course, the full calculation has to include the "calorimetric efficiency" and the fact that the oceans do change their temperature a little (such that some of the heat is radiated away, thereby reducing the calorimetric efficiency).
It turns out that there are three different types of data sets from which the ocean heat content can derived. The first data is is that of direct measurements using buoys. The second is the ocean surface temperature, while the third is that of the tide gauge record which reveals the thermal expansion of the oceans. Each one of the data sets has different advantages and disadvantages.
The ocean heat content, is a direct measurement of the energy stored in the oceans. However, it requires extended 3D data, the holes in which contributed systematic errors. The sea surface temperature is only time dependent 2D data, but it requires solving for the heat diffusion into the oceans, which of course has its uncertainties (primarily the vertical turbulent diffusion coefficient). Last, because ocean basins equilibrate over relatively short periods, the tide gauge record is inherently integrative. However, it has several systematic uncertainties, for example, a non-neligible contribution from glacial meting (which on the decadal time scale is still secondary).
Nevertheless, the beautiful thing is that within the errors in the data sets (and estimate for the systematics), all three sets give consistently the same answer, that a large heat flux periodically enters and leaves the oceans with the solar cycle, and this heat flux is about 6 to 8 times larger than can be expected from changes in the solar irradiance only. This implies that an amplification mechanism necessarily exists. Interestingly, the size is consistent with what would be expected from the observed low altitude cloud cover variations.
Here are some figures from the paper:
fig. 1: Sea Surface Temperature anomaly, Sea Level Rate, Net Oceanic Heat Flux,
the TSI anomaly and Cosmic Ray flux variations. In the top panel are the inverted
Haleakala/Huancayo neutron monitor data (heavy line, dominated by cosmic rays with a
primary rigidity cutoff of 12.9 GeV), and the TSI anomaly (TSI - 1366 W/m
2 , thin line,
and based on Lean [2000]). The next panel depicts the net oceanic heat flux, averaged
over all the oceans (thin line) and the more complete average heat flux in the Atlantic region (Lon 80°W
to 30°E, thick line), based on Ishii et al. [2006]. The next two panels plot the SLR and
SST anomaly. The thin lines are the two variables with their linear trends removed. In
the thick lines, the ENSO component is removed as well (such that the cross-correlation
with the ENSO signal will vanish).
fig 2: Sea Level vs. Solar Activity. Sea level change rate over the 20th century
is based on 24 tide gauges previously chosen by Douglas [1997] for the stringent criteria
they satisfy (solid line, with 1-σ statistical error range denoted with the shaded region). The rates
are compared with the total solar irradiance variations Lean [2000] (dashed line, with
the secular trends removed). Note that unlike other calculations of the sea level change rate, this analysis
was done by first differentiating individual station data and then adding the different stations. This
can give rise to spurious long term trends (which are not important here), but ensure that there
are no spurious jumps from gaps in station data. The data is then 1-2-1 averaged to remove annual noise.
Note also that before 1920 or after 1995, there are about 10 stations or less such that the uncertainties increase.
fig 3: Summary of the “calorimetric” measurements and expectations for the
average global radiative forcing F
global. Each of the 3 measurements suffers from different
limitations. The ocean heat content (OHC) is the most direct measurement but it suffers
from completeness and noise in the data. The heat flux obtained from the sea surface
temperature (SST) variations depends on the modeling of the heat diffusion into the
ocean, here the diffusion coefficient is the main source of error. As for the sea level
based flux, the largest uncertainty is due to the ratio between the thermal contribution
and the total sea level variations. The solid error bars are the global radiative forcing
obtained while assuming that similar forcing variations occur over oceans and land. The
dotted error bars assume that the radiative forcing variations are only over the oceans.
These measurements should be compared with two different expectations. The TSI is the
expected flux if solar variability manifests itself only as a variable solar constant. The
“Low Clouds+TSI” point is the expected oceanic flux based on the observed low altitude
cloud cover variations, which appear to vary in sync with the solar cycle (while assuming
several approximations). Evidently, the TSI cannot explain the observed flux going into
the ocean. An amplification mechanism, such as that of CRF modulation of the low altitude cloud cover is required.
So what does it mean?
First, it means that the IPCC cannot ignore anymore the fact that the sun has a large climatic effect on climate. Of course, there was plenty of evidence before, so I don't expect this result to make any difference!
Second, given the consistency between the energy going into the oceans and the estimated forcing by the solar cycle synchronized cloud cover variations, it is unlikely that the solar forcing is not associated with the cloud cover variation.
Note that the most reasonable explanation to the cloud variations is that of the cosmic ray cloud link. By now there are many independent lines of evidence showing its existence (e.g., for a not so recent summary take a look
here). That is, the cloud cover variations are controlled by an external lever, which itself is affected by solar activity.
Incidentally, talking about the oceans, Arthur C. Clarke made once a very cute observation:
“How inappropriate to call this planet earth when it is quite clearly Ocean!”
References:
1) Nir J. Shaviv (2008); Using the oceans as a calorimeter to
quantify the solar radiative forcing, J. Geophys. Res., 113, A11101,
doi:10.1029/2007JA012989.
Local Copy.
Comments (27)
I think I've never heard so loud
The quiet message in a cloud.
===================
Shaviv
Good to see such clear correlation of evidence from several different tracks.
May I refer you to Niche Modeling March 23, 2009
Global Temperature Change and Geomagnetic Field Intensity
This provides very obvious spatial correlation to support your calorimeter paper. Spatially correlating the magnetic field with temperature change should strongly support your position.
This is beautiful work, the best science, such high, clear correlations without any areas of serious doubt. Thank you. I'd like to second Alan Cheetham's correlation of global temp to geomagnetic field, and add yet another factor - the widening gap between levels of CO2 produced at/near the North Pole and South Pole. This widening gap can be used to support Northern Hemisphere fossil fuel CO2 production, but it can equally support the global temperature anomalies, with CO2 being driven out of a warming ocean.
Dr Shaviv
There is great interest in the Watts Up With That reposting of your thread here. However, a serious question has arisen from solar expert Leif Svalgaard, who disputes your sea level figures. His sources are (Leif Svalgaard 12:57:33, 15 April @ WUWT): for the tidal gauges: http://www.cmar.csiro.au/sealevel/sl_data_cmar.html Church & White, GRL, 33, L01602, 2006; for the satellite data: http://sealevel.colorado.edu/results.php . His graph is http://www.leif.org/research/Sea-Level-Change.png . Perhaps you would care to join the discussion there to answer Dr Svalgaard; we would all be interested, for the sake of good science!
Solar physicist Leif Svalgaard state that you have tortured the data you used for your paper figure 2. Find his critics at
http://wattsupwiththat.com/2009/04/15/the-oceans-as-a-calorimeter/#comments
on 15.04.2009 at 9:48
Moreover Lean 2000 is an obsolete reconstrunction.
Would you provide an answer? Thank you.
Yes, I pulled finger nails until the data said "I give up, I give up!"
o.k., now seriously.
In order to get the cleanest data I used the 24 tide gauges chosen by Douglas 1997 for different stringent criteria (e.g., in geologically stable locations, long records, consistent with other gauges nearby, etc). I used someone else's tide gauges so that I could not be accused of cherry picking.
Secondly, because I am not interested in long term trends, but I am interested in short term derivatives, I treated the data differently than what other people do. Instead of averaging the station heights and then differentiating, I first differentiated the data for each station and then added the derivatives. The reason is that this way I avoid getting spurious jumps from the start or end of individual station data. Because it can give rise to spurious long term trends and because I don't care about long term trends, I simply removed any linear trend from the data.
In the graph from 1870 that Lief Svalgaard points to, one cannot see the 11-year signal because the latter only amounts to a few cm amplitude (3.5 mm/yr!). It obviously drowns in the annual noise or the long term trends in Leif's particular graph. Note that at least over the past 50 years, Holgate sees consistently the same 11-year variations in the data (e.g., referenced here). Of course, because he uses a lot of lower quality stations (177) and/or is not careful to first differentiate and then add the tidal gauge data, he sees somewhat different variations before 1950, than what I find. (Of course, this is not a problem because he does not care about 11-year variations). Anyway, did Holgate torture his data too?
Oh, and the fact that Lean 2000 is used for the TSI is totally meaningless. The correlation with any signal synchronized with the 11-year solar cycle would give the same result. Note that I removed any long term trends from the tide data and from the solar proxies (whether TSI or cosmic rays).
Thanks Shaviv, I was pretty sure you'd have an answer. It's appreciated.
My new book: "It's The Sun, Not Your SUV" at www.itsthesunnotyoursuv.com proves that your ocean heat-sink measurement technique is also a proof that it is the sun that has caused most of the temperature changes since 1880. GHG may at best have a minor influence in temperature changes. However, with such large natural forces from the sun and secondary forces of ocean currents, volcanic dust, and ocean's heat-sink it is difficult to demonstrate a clear case that GHG have an impact upon temperature close to the levels indicated in the IPCC reports.
With Solar forces alone from 1880 to 1960, the books models can predict the changes in temperature from 1960 to 2009 within a few hundredths of a degree. The key charts are available at the website.
Please contact me through the website if you would like to receive more information
Best Regards,
John Zyrkowski, Author
"With Solar forces alone from 1880 to 1960, the books models can predict the changes in temperature from 1960 to 2009 within a few hundredths of a degree."
Oh really? Green house gasses have no heat trapping properties then :-)
Dear Dr. Nir Shaviv... Lean's reconstruction on TSI is not obsolete; it is just that she used several proxies and sunspots database for calculating the intensity of solar irradiance; 10Be and Ca-II, for example.
Dr. Svalgaard and other solar physicists are using sunspots only; this is the reason by which their reconstructions show an almost smooth baseline. I have compared Lean's and Svalgaard's databases against Bond's database on hematite stained grains and have found a clear correlation, so Lean's 2001 reconstruction on TSI, based on proxies and sunspots, is as valid as Svalgaard's TSI reconstruction, based on sunspots alone.
Sorry to come in rather late to this discussion but it's still just as relevant today.
I see two big errors in Svalgaard's rather dismissive comments on your work here, that seem to show his lack of understanding more than anything.
Firstly, he maintains that you should be comparing the differential of sea level with the diff of TSI rather than the TSI (though he does not say why he thinks that).
Since TSI (W/m2) is a power term it already contains 1/T dimension . You are clearly correct in what you do , he is so quick to critisise that he does not stop to thing it through. He just thinks both should be d/dt without looking at the nature of the properties used.
Secondly he says it does not matter in which order you do the differentiation and the averaging.
This is wrong. A running mean is basically a crude low-pass filter (with a fairly awful frequency response like sin(x)/x ). If you apply the filter before the the time derivative you are differentiating the filter response as well as the data.
What is required is the mean of the diff of the data.
So in doing the mean first he introduces a spurious term including the differential of the time response of the running mean filter.
It's a basic rule of data processing to do any smoothing (which is generally just for visual presentation) after calculating the properties you wish to examine, not before.
It's rather surprising that someone of his level does not appreciate dimensional analysis or basic data processing yet is so quick to be dismissive of others. The word hubris comes to mind.
Sadly this sort of thing seems to be very common, especially in climate science.
Unfortunately that WUWT thread is closed now but I thought it was worth noting here.
Thanks for the interesting content of this site. It's reassuring to find there are still people who understand what science means.
Try "Using the oceans as a calorimeter to quantify the volcanic radiative forcing" instead.
http://virakkraft.com/sealevel-VEI.jpg
It would have been interesting if there was actually a significant correlation. But even with your offset, there is poor correlation. Moreover, why would a VEI=3 or a VEI=6 eruption give you a comparable signal? VEI=6 is 1000 times more dust than VEI=3...
Not very good arguments.
"even with delay". It is well known that the climatic effect of large eruptions is delayed.
"there is poor correlation". Like 1900-1920 in your graphs, in counter phase?
"VEI=3 or a VEI=6 eruption comparable signal". (VEI>3 is VEI=4 and up but that's a detail) They are not comparable, that's why the offset is not constant over the whole span. Around 1900 and after 1960 there were many VEI5&6 eruptions bringing material to the stratophere, i.e longer delay. http://data.giss.nasa.gov/modelforce/strataer/index.html 1930 to 1960 they were mainly VEI4, i.e no delay. For simplicity I have done it like that here: http://virakkraft.com/sealevel-VEI-3.jpg (but the 70's were also VEI4s.) http://www.volcano.si.edu/world/largeeruptions.cfm
VEI > 3: O.k.... my mistake. But still, placing two eruptions with a factor 100 difference on the same footing is strange... How does the correlation look like if you look at the total volume of the eruptions (or even the log of it)?
Correlation: Although the time scales look similar, your signals don't really correlation. Look for example at the years with maximum N(VEI>3), then the sea level change rate can be either high or low:
1902 -3 mm/yr
1918 2
1932 5
1951 -4
1964 2
1975 0
1982 3
1992 0
(years are the volcano years.)
Following your suggestion, a high VEI should give a negative sea level change rate. I don't see anything consistent.
Of course, the comparison I did is quite meaningless. It just tells you that by eye you can see whatever you want. The best thing is to do a full comparison. If you send me your VEI data (to shaviv at phys dot huji dot ac dot il) then I can run it through the same statistical comparison I did with the solar data.
The numbers are here: http://virakkraft.com/volcano1880-2006.xls (there's also some sunspot data) but it will not be of much use for you. I did this very simple, treating the volcanism as on/off just counting the VEI>3 here: http://www.volcano.si.edu/world/largeeruptions.cfm
A proper analysis must deal with where; north/south/tropical, maybe time of year, explosivity (those reaching the stratosphere will have a more delayed effect), amount of debris, type of debris and probably more, so you see you will never get an accurate result. But it does not have to be that complicated. Maybe there's a threshold, some debris and the cloud formation is boosted (but more debris does not give even more clouds). Or maybe scattering of the sunlight is the key.
(pdf image converted to text with Adobe OCR)
POSSIBLE CORRELATION BETWEEN SOLAR AND VOLCANIC ACTIVITY IN
A LONG-TERM SCALE
2003ESASP.535..393S
Jaroslav StreStlk
Geophysical Institute AS CR, Bocni 11 1401, 141 31 Prague, Czech Republic, Email: xxx@XXX.xxx
Abstract:
Volcanic activity on the Earth is described by special
annual indices available since 1500. These indices have
been compared with annual sunspot numbers. Volcanic
activity displays no ll-yr periodicity. Using 2l-yr
running averages a striking similarity between these
two time series is clearly seen. Volcanic activity is
generally lower in periods of prolonged maxima of
solar activity and higher in periods of prolonged solar
minima. There is also a similarity between the spectra
of these two series in the long-period range. Main
peaks are located in the same periods in both series
(200-215 yr, 100-105 yr, 80-90 yr). The influence of
volcanic activity on the climate is indubitable. Annual
means of surface air temperature display similar longterm
periodicity as the volcanic activity.
Conclusions:
The narrow similarity between solar and volcanic
activity in the long-term scale suggests two quite
different possible consequences:
a. Solar activity governs the volcanic activity on the
Earth in long-term scale. Volcanic activity is
usually higher in periods of prolonged minima of
solar activity and vice versa. However, the
mechanism of this forcing is not known. Perhaps
geomagnetic activity mediates solar influences
(unfortunately, series of these data are too short). If
it will be confirnled in the future, then solar
influences on the climate could be considered as
being mediated by the volcanic activity, creating
a chain: solar activity - (geomagnetic activity) -
volcanic activity - climate changes. Direct solar
influence on climatic changes is, of course, not
excluded. But it is difficult to distinguish what part
of these changes is mediated by volcanic activity
and what part is direct solar influence. It would be
also necessary to explain why this chain does not
work in short-term scale.
b. The similarity of the long-term course of solar and
volcanic activity is accidental and is pronounced
only in the last few centuries. Then long-term
natural climatic changes would be caused only by
long-term changes of volcanic activity. The role of
solar activity would be in this case only apparent
due to the accidentally sin1ilar course of both
activities during the last five centuries.
Nevertheless, some small direct solar influence is
not excluded. In this case no similarity in shortterm
scale can be expected and it is not necessary to
look for an explanation why it is not observed. These two different conclusions mean that the
investigation of solar, volcanic and climatic changes
together in a considerably longer period (at least one
millenium) is very desirable.
aaron
I would expect two things. Most volcanic activity would happen during changes in flux, as that's when there would be most instability. I would expect a big lag. Second, I would expect a change in the nature of the particles emmitted by volcanos.
CRF would probably change the type of volcanic material emmitted at the end of a long period of high CRF. It might even be a dampening effect on a solar relationship in the short short as potential cloud condesation particles and other cooling particles form during a high CRF phase and are emmitted when we shift into a low CRF phase.
Long periods of high CRF probably change the nature of the particles emmitted from volcanos.
I'd try to look at much larger time scales.
aaron
Hey, Nir
I just stumbled on a couple of interesting posts about feedbacks and sensitivity.
http://wattsupwiththat.com/2009/03/30/lindzen-on-negative-climate-feedback/
http://wattsupwiththat.com/2009/03/29/dr-roy-spencer-on-publishing-and-climate-sensitivity/
I just wanted to see your opinion and to ask what it (if correct) does to your estimates about CRF being responsible for 2/3 of the warming?
Shaviv
May I recommend:
Alexander, WJR, Bailey, F., Bredenkamp, DB, van der Merwe, A., and Willemse, N. 2007 Linkages between solar activity, climate, predictability and water resource development. J. South African Institution Civil Engineering Vol. 49, July, pp 32-44 Paper 649. http://climaterealists.com/index.php?id=2643
They find better hydrological correlation to a double solar cycle of 20.8 years. (e.g. flipping alternate solar cycles.) It would be interesting if you see that difference as well.
Hi, Nir
Have you seen this paper
http://www.atmos-chem-phys.net/8/737...7373-2008.html
Nir
Would welcome your comparison of your results with those of Landscheidt on Mayaud's geomagnetic index aa, sunspot number and CO2 change rate. See:
Variations in CO2 Growth Rate Associated with Solar Activity Theodor Landscheidt
E.g. comparing your sea level variations Fig. 6 with the of change in CO2 Fig. 1 (originally from Keeling and Whorf, 2003)
Hi Prof. Shaviv,
For the past year I have followed with interest the unusual recent solar cycle (in)activity, along with your work and that of Svensmark, Soon, Sharma, Sherer, Solanski, Verma, Marusek, Sharma, Svalgaard, Harrison, Marsh and others, that have been so important for countering the anthropogenic global warming Lysenkoists.
I was just wondering, if you combined your three calorimeters into a single one using a Kalman filter, would you get a better picture? The resulting figure might make a useful addition to your paper.
As you have mentioned, there are plenty of good reasons to be more efficient with our use of fossil fuels, although carbon dioxide and anthropogenic global warming is not one of them. With the current Dalton-like dip in solar activity, the prospect of a significantly colder Northern Hemisphere in the near future is not pleasant, and not likely to reduce our use of fossil fuels.
Please keep shining the light on the science.
Thanks,
-Peter
Nir
Lucia Liljegrens statistical analysis at the Blackboard have shown that the IPCC models are in a bad shape. The inconsistency between observed and modelled temperature trends shows that the models are clearly getting something badly wrong. The present vulcanic lull and increasing levels of GHG's in the atmosphere have failed to result in the predicted rise in global temperatures in recent years.
If you are right about the influence of cosmic rays on climate you should be able to do better than the IPCC. I know you cannot make predictions about future global temperature as your most important independent variable is not (yet) predictable, but based on your research you should be able to specify a model of global temperature (even just a simple one) with much better "predictive" skill.
I would be interested to know what your prediction would be of the 20 year global temperature trend from 2009 to 2029 if solar activity should take another long slumber like during the Maunder Minimum.
Since the little ice-age was about 1deg cooler than today, then a new mounde-like minimum should cool the earth by that much (i.e., return to pre-1900 values). However, it would take a few decades for the oceans to loose all this excess heat. How long exactly? I don't know yet.
Thank you for your reply, Nir.
If cosmic ray-induced changes in low cloud cover over oceans is the explanation for your observations that ocean heat content varies in sync with solar activity, isn't Leif Svalgaard right that earth's albedo should follow the 11-year cycle too:
"the cosmic rays follow the 11-year cycle and the albedo should follow the same 11-year cycle if the variation of cosmic rays is the reason for the changing albedo [and hence temperature]."
Doesn't Enric Pallés albedo data contradict your theory about the role of cosmic rays?
Kind regards
Dr Shaviv.
I am a layman but am trying to absorb as much of the science as possible as I find the climate discussion very compelling.
I have greatly appreciated your blog items. They break down your technical papers (which I also look at) and make the subject more accessible to me. Thanks!
I have been following the CRF theory with great interest since clouds seem to be a big uncertainty factor in the IPCC theory at present. I would like to know what you have to say about this lecture which makes a point (at 42 min.) about the Laschamps anomaly at 40K years ago. The assertion is that since the magnetic field was flat for a long period and cosmic rays showed increased effect in that period, there should have been a decrease in temperature but wasn't.
http://www.agu.org/meetings/fm09/lectures/lecture_videos/A23A.shtml
The speaker, Dr Richard B Alley gives a very good paleoclimate history and also addresses CO2 lag to temperature with a good analogy to loan interest.
He makes it sound like this single anomaly relegates CRF to a 'fine tuning' knob, but I would very much like to hear your response.