Guest Post by Willis Eschenbach
There’s a new study entitled “Global warming preceded by increasing carbon dioxide concentrations during the last deglaciation”, Shakun et al. (paywalled, hereinafter Shakun2012). The paper claims to show that in the warming since the last ice age, CO2 leads temperature. Anthony wrote about it in his post “A new paper in Nature suggests CO2 leads temperature, but has some serious problems“. The press release says (emphasis mine):
A new study, funded by the National Science Foundation and published in the journal Nature, identifies this relationship and provides compelling evidence that rising CO2 caused much of the global warming.
Lead author Jeremy Shakun, who conducted much of the research as a doctoral student at Oregon State University, said the key to understanding the role of CO2 is to reconstruct globally averaged temperature changes during the end of the last Ice Age, which contrasts with previous efforts that only compared local temperatures in Antarctica to carbon dioxide levels.
“Carbon dioxide has been suspected as an important factor in ending the last Ice Age, but its exact role has always been unclear because rising temperatures reflected in Antarctic ice cores came before rising levels of CO2,” said Shakun, who is a National Oceanic and Atmospheric Administration (NOAA) Post-doctoral Fellow at Harvard University and Columbia University.
“But if you reconstruct temperatures on a global scale – and not just examine Antarctic temperatures – it becomes apparent that the CO2 change slightly preceded much of the global warming, and this means the global greenhouse effect had an important role in driving up global temperatures and bringing the planet out of the last Ice Age,” Shakun added.
The good news about the paper is that they have provided the temperature records (Excel spreadsheet) for the 80 proxies used in the study. My compliments to them.
Me being a suspicious fellow, however, I figured “trust but verify”, so I plotted up the temperature records that they used. I always begin with the original data, without any additions or distractions. Figure 1 shows the data that they used.
Figure 1. Records and types of proxies used in the Shakun2012 study
As you can see, some of the ice core records are down where we’d expect them to be, well below zero. Those are the GRIP and NGRIP records from Greenland. But there are some oddities about these proxies.
One problem that is immediately obvious is the timing. The peaks for the previous interglacial period (the Eemian, about 130,000 BC) don’t line up. That may not be much of a problem, though, because the paper is about the warming from the most recent ice age.
One oddity is that there are ice core records that are right around freezing (0°C). In addition, there are pollen records around freezing as well. This shows that we actually have a mix of anomaly records and actual temperature records. This is not a problem, just an oddity.
Next, let’s take a look at the location of the proxies. Figure 2 is from their paper:
Figure 2. Location of the proxies used in the Shakun2012 study.
This looks good, it looks like there may be passable coverage. So let’s look at the last glacial transition, we’ll look at the time since 26,000 BC.
Figure 3. Same data as in Figure 1, but showing the warming from the last ice age.
Here, you can see the Antarctic ice core records (yellow and green lines near 0°C) mentioned above that are shown as variations, with the modern value taken to be 0°C.
Some other observations. Greenland (yellow temperatures at bottom) seems to be an outlier in terms of change in temperature. The Antarctic ice cores and all of the rest of the records show much less warming since the ice age.
In order to compare these eighty proxies to each other, what we need to do is to “standardize” them. This means to first subtract the mean (average) of each proxy from the individual values. Then each of the individual values is divided by the standard deviation of the entire record for that proxy. The result will vary between about -3 and 3. Standardizing preserves the shape and timing of the data, it just makes all the proxies have a mean of 0 and a standard deviation of 1.
Next comes the part that the authors of these multi-proxy studies seem to have generally ignored. This is to look at each and every one of these proxy records and think about what they seem to mean. I’ll look at them sixteen at a time. Figure 3 shows the first sixteen of the Shakun2012 proxies.
Figure 4. Proxies from the Shakur2012 study. All of these cover the period from 26,000 BC to 1980 AD. Vertical dashed lines show the minimum (light blue) and maximum (dark red) values for the each proxy. Minimum and maximum times rounded to nearest 100 years. Colors as shown in Figure 1. Click for larger version.
NOTES BY NUMBER
1, 2: These are the Greenland ice cores. They show a warming of 32 and 27 degrees respectively, which is much more than any other proxy. Warming begins earlier than 20,000 BC.
4: The warmest date is at 1200 AD.
6: Warmest date is 1000 AD. Warming doesn’t start until 12,600 BC.
9: Maximum warmth is at 14,600 BC.
15: Very unusual shape, 11° warming.
Figure 5. Same as Figure 4, proxies from the Shakur2012 study. All of these cover the period from 26,000 BC to 1980 AD. Vertical dashed lines show the minimum (light blue) and maximum (dark red) values for the each proxy. Minimum and maximum times rounded to nearest 100 years. Click for larger version.
19: Warming doesn’t start until 10,800 BC
21: Maximum warmth precedes maximum cold.
28. Maximum doesn’t occur until 400 BC.
30. Maximum doesn’t occur until 1400 AD.
31. Maximum doesn’t occur until 2400 BC.
32. Maximum doesn’t occur until 1500 AD.
Figure 6. Same as Figure 4. Click for larger version.
34: Maximum at 1600 AD
35: Maximum at 14,000 BC
36: Strange shape, constant warming until the present.
42. Maximum not until 400 AD.
44: Warming until the end of the record in 8200 BC.
Figure 7. Same as Figure 4. Click for larger version.
50: Maximum not until 1100 AD.
51: Constant rise beginning to end.
52: Large drop and rise after maximum warmth.
53: Rises beginning to end.
54: Rises beginning to end.
58: Maximum not until 1300 AD.
59: Maximum not until 1600 AD.
60: Large rise in 1100-1200
Figure 8. Same as Figure 4. Click for larger version.
67: Warming starts at 25,900 BC.
68: Warming only one tenth of a degree
76: Warming occurs almost instantaneously
Discussion
The variety in the shapes of these graphs is quite surprising. Yes, they’re all vaguely alike … but that’s about all.
The main curiosity about these, other than the wide variety of amounts of warming, is the different timing of the warming. In some proxies it starts in 25,000 BC, in others it starts in 15,000 BC. Sometimes the warming peaks as early as 14,000 BC, and sometimes around 5,000 BC or later. Sometimes the warming continues right up to the present.
The problem becomes evident when we plot all of these 80 standardized proxies together. Figure 9 shows all of the standardized temperature traces.
Figure 9. All 80 temperature proxies from Shakun2012. Colors as shown in Figure 1.
Now, there’s plenty of things of interest in there. It’s clear that there is warming since the last ice age. The median value for the warming is 4.3°C, although the range is quite wide.
But if you want to make the claim that CO2 precedes the warming?
I fear that this set of proxies is perfectly useless for that. How on earth could you claim anything about the timing of the warming from this group of proxies? It’s all over the map.
Final Conclusion
The reviewers should have taken the time to plot the proxies … but then, the authors should have taken the time to plot the proxies.
w.
[UPDATE] A hat tip to Jostein, who pointed in the comments to the Shakun Nature paper being available here.
[UPDATE] Some folks wanted to see the CO2 data they used on the same timescale. Other folks said the colors in Figure 9 were misleading, since ice cores were printed on top, obscuring others below. We’re a full-service website, so here’s both in one:
Figure 10. All proxies, along with CO2 record used in Shakun2012.
My best to all,
w.
I decided to take a look at the various proxies by proxy type. There are ten different kinds of proxies.
Figure 11. Proxies averaged by type.
A few notes, in no particular order. The ice core records are similar, but the timing is different.
Foram assemblages seem to be useless. The same is true of the Tex86 proxies.
Pollen has a consistent signal, but the warming doesn’t start until about 10,000 BC.
MBT/CBT perfectly exemplifies the problems with this approach. Which one are we supposed to believe? Which one is it that is lagging the CO2?
Finally, the Mg/Ca and the UK’37 proxies kinda sorta have the same shape, but no uniformity at all regarding the timing of the rise.
Let me close with a black-and-white version of the above chart. This allows you to see where the denser areas are located.
Figure 12. Proxies by type. Blue line shows CO2 data as used in the study.
Note the difference in the underlying shapes of the different types of proxies, and the differences in their timing with respect to the rise of CO2.
Next, note that the CO2 record they are using is from Antarctica. That is the reason for the good fit with the single “ice core ∂18O and dD” proxy (left graph, second row) and the “ice core dD” (center graph, second row). Both of those are Antarctic records as well.
Also, as you can see, even within each proxy type there is no unanimity regarding the timing of either the onset or the end of the warming from the last ice age.
CO2 is the blue line … so was the warming before or after the blue line?
w.
[UPDATE]—The discussion continues at Shakun Redux: Master tricksed us! I told you he was tricksy!
Without reading the whole lot, sorry, priorities, but there is another mega problem comparing dates of records. They are often not independent. A lot of dating happens by fitting curves, compared to other proxies, wiggle matching.
Apart from that. maybe proxies aren’t that good either. See this little essay about Siberia during the Last Glacial Maximum:
http://dl.dropbox.com/u/22026080/Last%20Glacial%20Maximum%20in%20Siberia.doc
Excellent work, CO2 driving temperature is a ridiculous idea, it makes more sense that energy input drives the processes of the rise and fall of CO2 whether or not if it’s recorded as an ice proxy. It’s a Crank science Fail. Good man Willis.
aaron says:
April 6, 2012 at 12:10 pm
Good questions. From the paper
Next, you ask:
Quite similar, but with less annual swing.
The red band shows the approximate latitude of Mauna Loa, where the longest CO2 record is taken.
w.
Well done Willis. When I read in their paper about “… potential physical explanations for the correlations between temperature, CO2 concentration and AMOC variability in three transient simulations of the last deglaciation…” I started wondering about the purpose of all this verbiage. Climate simulations as far as I go have been losers and I certainly can’t check any of this stuff myself. After more unnecessary verbiage about “Uncertainty analysis” and “Robustnes of results” I realized it was meant to ease us into a belief that they have discovered something big: carbon dioxide did not follow but preceded end-Pleistocene warming. I never would have guessed it from their graphs. It is clear that this paper, as all others emanating from the climate establishment, takes it as a matter of faith that any observed warming is caused by the enhanced greenhouse effect of carbon dioxide and then attempts to prove it. There is just this one problem with their assumption: the chief greenhouse gas on earth is not carbon dioxide but water vapor. They both absorb outgoing infrared (long-wave) radiation and it is their combined absorption of radiant energy that causes the atmosphere to get warm. But now consider this: when we don’t change the amount of carbon dioxide in the air we have a stable climate. There are local temperature and humidity variations, to be sure, but long-term drift is absent. What guarantees this? To prevent a long term temperature drift the IR absorption by greenhouse gas concentration that determines IR transmittance of the atmosphere must respond to any such temperature drift. And water vapor is the only greenhouse gas that can easily do that. Starting from this qualitative picture Ferenc Miskolczi brought in radiation theory and showed that for a stable climate to exist the optical thickness of the atmosphere in the infrared had to have a value of 1.86 (15% transmittance). This transmittance is determined by the combined absorption of infrared radiation by all the greenhouse gases present, but the adjustment is maintained by water vapor, the only adjustable greenhouse gas in the lot. The blogosphere was hostile to the idea because it wiped out the sacrosanct Arrhenius law. But Miskolczi went on to test it using NOAA database of weather balloon observations that goes back to 1948. He found that the IR transmittance of the atmosphere had been constant for the previous 61 years as his theory predicted (E&E 21(4):243-262, 2010). During that same period of time the amount of carbon dioxide in air increased by 21.6 percent. This means that the addition of all this carbon dioxide to air had no effect whatsoever upon the absorption of IR by the atmosphere. And no absorption means no greenhouse effect, case closed. This is an empirical observation, not derived from any theory, and it overrides any theoretical calculations that do not agree with it. Specifically, it overrides any calculations based on climate models that use the greenhouse effect to predict warming. In accord with this, a close examination of the temperature history of the last 100 years reveals that there has been no greenhouse warming at all during this entire period. Starting with the twentieth century, the first part of the twentieth century warming started in 1910 and stopped in 1940. There was no corresponding increase of carbon dioxide at the beginning of this warming which means that according to the laws of physics it cannot be greenhouse warming. Bjørn Lomborg attributes this warming to solar influence and I agree with him. There was no warming in the fifties, sixties, and seventies while carbon dioxide relentlessly increased. There is no satisfactory explanation for this lack of warming, only various contorted excuses to explain it away. The true reason for this lack of warming is clear from Miskolczi’s work. There was no warming in the eighties and nineties either according to the satellite temperature measurements. There was only a short spurt of warming between 1998 and 2002 caused by the warm water that the super El Nino of 1998 had carried across the ocean. And there was no warming from that point on to the present while carbon dioxide just kept on going up on its merry way. And if you still think Arctic warming proves the existence of greenhouse warming think again: Arctic warming is not greenhouse warming either and is caused by Atlantic Ocean currents carrying warm Gulf Stream water into the Arctic (E&E 22(8):1067-1083, 2011). Taking all this history and Miskolczi’s theory into account the attempt of this Nature article to explain the end-Pleistocene warming as greenhouse warming is nothing more than hopelessly misguided global warming doctrine.
REPLY: Try learning about the revolutionary new feature: PARAGRAPHS
– Anthony
Willis Eschenbach says:
April 6, 2012 at 10:54 am
Steven Mosher says:
April 6, 2012 at 9:23 am
======================================
Willis, do not expect a reply from Mr Mosher. Pendantic hit and run comment, no engagement in a real consversation, as if he is above such petty dialogue, this is what I expect from him lately.
“Shakun all over!”
Great work Willis.
I came to the same conclusion several days ago and posted: “Shakun et al is highly improbable.”
http://wattsupwiththat.com/2012/04/04/a-new-paper-in-nature-suggests-co2-leads-temperature-but-has-some-serious-problems/#comment-945861
Mind you, I did not crunch the numbers.
Instead, I employed basic principles, namely the tried and trusted “Law of Warmist BS”:
“You can save yourselves a lot of time, and generally be correct, by simply assuming that EVERY SCARY PREDICTION the global warming alarmists express is FALSE.”
Genesis of this new Law of (Human) Nature is outlined at:
http://wattsupwiththat.com/2012/02/28/the-gleick-tragedy/#more-57881
One problem with all the ice cores is that the CO2 data is very sporadic. You can see the ‘holes’ in Willis’ CO2 graph. I tried some time ago to get a handle on which came first by looking at the second derivatives, but failed because the CO2 data is sparse – far sparser than the temperature proxy data. I also found that it makes a huge difference where you start normalizing, because that can change the apparent zero, and if the normalized zeroes of the temperature and CO2 differ, then the leader will change position, and become the apparent follower!
@agfosterjr
‘
I bet you’re a bundle of laughs at parties 🙁
For me WUWT is an education. This is an excellent, painstaking and essential review. I suspect Shakun et al. is the kind of paper that the IPCC would be looking to include in its 5th Assessment Report. Perhaps now they won’t be able to.
Nice piece of work if the temperatures are plotted the right way. Always interested in factual evidence.
How science should be done!
One cannot conclude anything from these datasets. Besides Shakun used different proxies. Different proxies give different results as proven in piece above.
Conclusion: Proxydata are nothing more than an estimation of what happened. They tell you nothing about the actual temperatures or concentration levels of certain gases from a specific period in time.
A good example is this one on the Greenland Ice Core (GISP2):
http://hot-topic.co.nz/easterbrooks-wrong-again/
If you take a look at graph 4 and 5 it is obvious that the anomalous temperatures from the last 170 years are higher than what happened in the last 10.000 years. It is agreed that the MWP was as warm, warmer of slightly colder than 20th century temperatures.
And we can detect the MWP (1000 years ago) in graph 5. Also take a look at the discrepancy between actual temperature data and ice-core data in graph 5 as well.
According to Richard Alley ice-cores are the gold standard in proxies. Yeah…Right!
I see what you’re saying, which I think is that the spread in time of the proxy data appears to be too great to allow a determination of whether the temperature increase precedes or succeeds the increase in the CO2 data. But there are statistical techniques that allow a quantification of how likely it is that the increase in CO2 precedes the increase in the proxies, based on the these data. So I think it’s a bit harsh to state that these data are perfectly useless for this purpose.
“When I buy a jigsaw puzzle I digitally scan the pieces to produce a Cartesian coordinate readout for each on a mm scale. Then I make the necessary transformations to digitally compare the sides of each in all possible combinations, making fits accordingly. I find this saves much time over eyeballing it.
I bet you’re a bundle of laughs at parties :-(”
Any time I see a jigsaw puzzle on a table I take one non-edge piece, sneak it into my pocket when nobody is looking, and walk away.
Willis Eschenbach: Those are the years with the highest and lowest data points.
If you wrote that, I missed it.
I have a copy of the paper, and have had one since a day or so after it came out. What’s your point?
My first point was that you should submit this as a letter to the editor of Nature. It’s a chore you might not like to take up, but your post here makes a good point well: if there is evidence that CO2 increase preceded temperature increase, that evidence is hard to see. Only the abstract was posted, and until you wrote in response to me, I did not know you had the whole paper (though I did wonder how you had obtained the data without the whole paper.) Maybe “it goes without saying” that you would not critique a paper from its abstract, but I am a dunce and I never get what goes without saying properly. I expected that you’d link an unpaywalled copy of the paper if you had it.
Back to highest and lowest data points. Assuming for the sake of argument that all of the time series are measures of some underlying process (plus other stuff) what you want is something like the maximum and minimum of the underlying process, or the inflection points of the underlying process, or things like that. The maxima and minima of the individual records don’t give that. The data hint strongly (or shout loudly) that estimates of such quantities are likely to have large variances. My following comment, that your method should be compared to the method of the authors, omitted my guess that the original authors had even less than you presented relevant to their case. It was a response to Steven Mosher’s implied (or at least inferred by me) point that you had supplied a less reliable analysis than the authors, since he critiqued you but not them.
Oh. I see I ought to have read Anthony’s post on the paper first.
Excellent Willis.
I’ve read various claims that CO2 follows temperature, variously by 300 to 800 years. Are these claims equally questionable ?
There is certainly a very weak link in this paper when it claims that a 0.3degree change results in a sufficient outgassing of carbon dioxide from the Southern Ocean to ultimately increase CO2 by about 100ppm. That’s certainly an hypothesis that can be tested against solubility, but I don’t think that’s even necessary. If it were true, then the CO2 concentration in today’s atmosphere, after a SH warmup of about 0.5deg, would be rising much more rapidly than indicated by mere emissions, and the fractional increase in the atmosphere would be traceable to a decrease in the southern ocean.
The subsidiary hypothesis that the CO2 was released because of a sudden change in SH sea ice is also very speculative. Given the nature of the Southern Ocean, it surely could not have extended the very large distance further north than it is today, to make this a mechanism.
This paper certainly creates a lot more questions than it answers.
bubbagyro says:
April 6, 2012 at 10:56 am
Downdraft says:
April 6, 2012 at 10:42 am
Obviously, all you need to do to arrive at an exact record of global temperatures is average all the proxy results.
Your point is not wrong, even if you sarced it!
Statistics says, that if you have enough sloppy measurers, the mean (not average) with the st.dev. is a more reliable result than the single number measured by the best measurer. Hard to conceptualize that, I know! Yet it is true science.
Well, not exactly. In this particular case it has to be a weighted average. The sites are not determined by a random statistical process (like generating a random point from a uniform surface distribution) and then finding a proxy at that point. Rather, there are some places on the Earth’s surface where, for better or worse, some sort of proxy of earlier temperatures is supposedly preserved. Since that is generally not true at arbitrary locations, one has to take what one can get.
Those locations are drawn from an environment that we know was not homogeneous (and this is of course immediately apparent in the data). In particular, there is a very clear latitudinal structure, as we might expect, but with surprises like Greenland that confound any simple rule we might use to relate a local measurement to a smooth function of expected temperature variation by latitude. However, beyond that we know perfectly well that temperatures on a seashore are often terribly correlated with interior/mainland temperatures, sometimes interior temperatures drawn from just a few miles away. San Francisco is a marvelous example — you can have multidegree differences in average temperature drawn from sites separated by a hill inside the city, let alone the temperatures drawn from coastal sites compared to sites ten or twenty miles inland. In other words, all of the problems we have now with GISS and HadCRUT, except that we have only a tiny handful of samples, we have no knowledge whatsoever about the moral equivalent of “UHI” effects (local environmental deviations from even a local thermal average because a site happens to be on what was a southwest facing hill 12,000 years ago until a major earthquake rearranged the landscape so now it faces north). Finally, because we are averaging on a sphere there is the eternal problem of the Jacobean.
Now a glance at the coverage map Willis placed up at the top reveals major problems. First of all, it looks like around 90% of the sites are coastal. Whoa, huge problem. Surface to perimeter of the continents being what it is, this means that nearly all of the land surface area remains unsampled. Indeed, areas omitted include things like “all of Asia” (except for enormous oversampling of coastal regions and islands, e.g. Japan) — what’s up with that? Coastal sites are the worst possible sites to sample, as they are buffered by the ocean and fail to show the full variability of the climate elsewhere, even elsewhere a very short distance away.
Second, although it is difficult for me to tell for sure on the 2D map provided, it looks like the coverage oversamples the poles compared to the tropics. I know, it is difficult to be sure, because one cannot see it very clearly, but there is a lot more area in a given latitudinal band near the equator than there is near the poles, and — did you notice the lack of samples from this thing called “the pacific ocean”, which covers a mere 1/2 of the planet, except for oversampled clusters at a few specific locations on its perimeter?
I do agree that one learns something by just averaging the renormalized data together, especially if one smooths the average laterally in time as well as vertically across the samples, but what one ends up with is not a valid estimate of any sort of global temperature or global anomaly. Rather it is a curve that one hopes is somehow a monotonic function of the global temperature and/or global thermal variation across the time frame in question.
If I wanted to turn this into an actual estimate of global temperature — presuming that one had the slightest hope of normalizing proxy data to an actual temperature scale at even 2-3K precision — I would absolutely not do a flat average. I might do a flat average of Japan — otherwise absurdly overrepresented and then weight Japan alone with a factor (ideally an empirically determined parameter) that I might hope is its correlation function with local areal temperatures — in other words to the extent that temperatures in Japan are predictors of temperatures in mid-China, one might create a reverse projection (with a very large error bar, obviously) to assign a very weakly weighted estimate of the probable temperatures in the unsampled place from the sampled place.
Ditto the other sites. For example, there appears to be a sample from or near the North Carolina Coast. The Coast is a lousy proxy for the interior. For one thing, it is 2-4K warmer, on average, in the winter, and 2-4K cooler, on average, in the summer. It is often sweltering in Durham but delightful — a full 10F — cooler at Beaufort when I teach there in the summer. In Durham we can have frost and snow in the winter, but palms and beaugenvillias and oleanders thrive in Beaufort. Durham isn’t a good proxy for Chapel Hill — the latter is on a hill where spring comes sooner but the summer stays a bit cooler. Neither is great for the Smoky Mountains or Appalachians or for the coastal plains. The sandhills trap and release water differently from the piedmont differently from the mountains differently from the oceanic moisture on the coast so the patterns of precipitation are different across the state. And this is just one state — go over the mountains into Ohio, go west to Kansas — just how good is that NC coastal proxy going to be at predicting the temperature — or even just the temperature variation — in Kansas? A change in patterns of prevailing wind over the 15,000 years of the proxies is enough to completely erase any modern correlations and replace them with something entirely different. A change in ocean currents would be far worse, and just such a change is supposed to have occurred and been involved in the Younger Dryas.
Speaking of which, just where did the Younger Dryas go? There it is, big as day in the antarctic ice cores, unmistakable and huge. Yet it completely disappears in the dot-o-gram of the collective data. Was the YD an antarctic polar event? I didn’t think so, but this data seems to more or less erase it elsewhere. This is perhaps not surprising, given that so much of the data is coastal and thermally buffered, but given the clear trace of the YD on the land — where it is correlated with things like severe drought and dust storms on the NA continent, clearly visible as sedimentation layers the gully walls of streams not far from my house — this means that it is a terrible proxy for climate elsewhere.
The point is that, with care, one might be able to do something with the data, but the data raises far more question than it answers. I remain unconvinced by the assertions that axial precession plus orbital resonance plus a touch of magic are responsible for the bistability of the Earth’s climate. Perhaps all of these contribute, but they were all present four or five million years ago more or less as they are today, but the Earth was stably warm in spite of it. Until we really know what went on to alter this and create the bistability, assigning a cause (set) to the warming that started 15000 years ago, trying to resolve CO_2 from the multiplicity of causes or contributing agencies is absurd. And in the end, the data needs to make sense. This dataset is not senseless, but it is filled with puzzles far more than it provides answers.
rgb
agfosterjr says:
April 6, 2012 at 11:56 am
When I buy a jigsaw puzzle I digitally scan the pieces to produce a Cartesian coordinate readout for each on a mm scale. Then I make the necessary transformations to digitally compare the sides of each in all possible combinations, making fits accordingly. I find this saves much time over eyeballing it.
xxxxxxxxxxxxxxxxxxxx
Ha ha ha ya mean you cheat?
Willis:
I admire your breadth and depth of knowledge and data analyses. Hang in there, the yip yappers can find a tiny fault here and there but I have not seen anyone yet that can refute your conclutions in any of your articles. I hope for many, many more of yoru articles. Kudos and bravo!
Great work, and good discussions.
As a scientist, I find it devastating to see what the scientific establishment has come to. Eventually Science, and facts, will win out.
Willis. I downloaded the data. Thanks for making it so easy.
1. The yr BP column starts at zero and is positive increasing with points every 15-30 years. So I made the column negative (e.g. =-B1 etc).
2. I plotted Temperature versus yr BP for NGRIP (Greenland) and Vostok (Antarctica).
3. Temperature for NGRIP was fairly constant until -14,750 BP when it suddenly jumped higher (over a ~400 year period).
4. Temperature for Vostok was fairly constant until -16,808 BP when it started a gradual but continuous rise (over ~5,500 years).
From these two graphs it would seem that temperatures in the Antarctic started to rise 2,000 years before the Arctic and that the temperature change in the Arctic was both later and more abrupt.
Isn’t this contrary to the paper’s claims that the Arctic warmed first, melting the northern ice sheets, which stopped the conveyor belt, which warmed the southern oceans, which led to a CO2 increase in the atmosphere, which led to warming of the Antarctic? Even the raw data would seem to refute this theory.
bubbagyro says:
April 6, 2012 at 10:56 am
Statistics says, that if you have enough sloppy measurers, the mean (not average) with the st.dev. is a more reliable result than the single number measured by the best measurer. Hard to conceptualize that, I know! Yet it is true science.
In applying the rules of statistics properly there is more to say here. Your statement in my opinion only holds, if the measurements are about the same phenomenon and done with the same or comparable methods and units. This has to be so in order for the data to be open for meaningful statistical analysis in the first place.
You can do a perfect statistical analysis of bogus data. Whatever the result, it has no practical scientific value.
You could try running a “Kernel Smoother” over the pseudo-temperature data (the black dots in the last figure) to obtain a single black line from the data which would illustrate more clearly whether the black dots are leading or lagging the red dots.
http://en.wikipedia.org/wiki/Kernel_smoother
I spent two hours trying to make sense of that last graphic, then all of a sudden the dots resolved into an image Of Hansen’s face. It was a sublime moment.
Hi Willis, the dip in temperature at 11.7 Ky is also present in the levels of CH4, N2O and CO2 in the Antarctic. The log(dust) levels give a very good correlation with the line shape of these data, and there is a rather nice change in dust radius.
The Fe levels fall away at 17 Ky. No Fe in the oceans, less biotic, more CO2.