(Only slightly marred at the end by my pet peeve redundancy: “solar insolation.” People write this all the time, presumably not realizing that “insolation” already covers the “solar” bit–but since it had been explained earlier in the piece that the term is derived from (“INcoming SOLar radiATION”), this reference was jarring. OK, I’ll shut up about this now.)
(Oh, and figure 3 didn’t display, but this may be my browser, not the article.)
My comment is in regarding the the Antarctic data CO2/temperature record.
I am interested in the lags in the climate system and to see how the limit cycles may respond to minor amounts of positive feedback, such as that due to CO2 outgassing with temperature. I can understand how the feedback of CO2 release with temperature increase is weak and self-limiting but it has to play at least a part of the process. We also obviously see the limit cycles with the seasonal ripples on the Mauna Loa data. This is my analysis: http://theoilconundrum.blogspot.com/2012/03/co2-outgassing-model.html
The Vostok data is in the first part of the analysis and then I look at Mauna Loa data at the end. I estimate 3 PPM/degree transient and 10 PPM/degree long-term sensitivity due to outgassing.
The other significant point in all this is that the adjustment time of CO2 is different for naturally induced temperature changes than it is for artificial releases. This hasn’t really been clearly articulated as far as I can tell, but the implications are huge when one compares our current situation to historical glacial cycles.
Comment by Pete Dunkelberg — 28 Apr 2012 @ 9:26 AM
Edward Greisch, as has already been explained to you in an earlier thread, the citation links in the article lead to the bibliography at the bottom of the article. But let me put in another vote for seeing figure 3!
Very interesting stuff. I’ll mention that although orbital variation (precession) causes opposite insolation changes in the two hemispheres, axial tilt (obliquity) variation causes synchronous insolation changes in the two hemispheres. Precession dominates *midsummer* high-latitude insolation (the usual Milankovitch metric), but obliquity has a stronger influence on Huybers’ notion of “summer heat” (which takes into account the astronomical influence on length-of-season.
I’m also intrigued by Raymo’s idea that an important factor is that during recent glacial cycles, the ablation zone of N.Hem ice sheets is land-based but that of S.Hem ice is ocean-based. This raises the possibility that changes in sea level can profoundly affect the S.Hem ice — wasting of N.Hem ice sheets can raise sea level, “unpin” and destabilize the S.Hem ice, helping make the changes global. This may also help explain why, before about 800 ky ago, glacial cycles were dominated by the 41 ky obliquity cycle, while precession had very little effect. In those colder, older times, the S.Hem ice edge was land-based so the influence of sea level changes was not a factor.
Chris – Thanks for a very informative overview of our evolving understanding of the last deglaciation. I don’t think there was much prior uncertainty in the literature over the general notion that orbital forcing changes were an initiating factor and that consequent rises in CO2 contributed a major subsequent warming influence, but the timing (regional vs global) and the interaction between the hemispheres has not been well illuminated. The recent work, particularly including Shakun et al, is beginning to paint a clearer picture, although important details are still missing.
I’ll comment on two specific points you raise. The first is to emphasize your point that degassing of CO2 from the oceans is not simply a matter of warmer water reducing CO2 solubility, and that important additional factors include changes in wind patterns, reduction in sea ice cover to reveal a larger surface for gas escape, and upwelling of CO2 from depths consequent to the changing climate patterns.
The second point relates to a WUWT analysis by Willis Eschenbach challenging Shakun et al, and I bring it up because I expect some WUWT readers may also visit here and may wonder what was wrong with Willis’s analysis.
Unfortunately, it started out with a serious error (unless I misread what he wrote), and that error more or less makes it impossible to extract a meaningful interpretation of the temperature data from the way he transformed the data. As a preface, I’ll point out that temperature change can’t be expected to be the same everywhere in a global survey. There are major differences dependent on latitude, ocean basin, proximity to specific land masses, and in the case of some proxies, seasonal effects. Different proxy records should reflect these differences and differ therefore in the magnitude of recorded temperature change. What Eschenbach apparently did was to “standardize” the temperature data instead of leaving it alone. He took each proxy record (typically composed of values rising over time), treated it as a normal distribution, computed a standard deviation, and then divided the values from that proxy by its SD to yield “standardized” values. What this does, of course, is tend to “compress” large temperature changes in some proxies toward the smaller values from other proxies, to the extent that the larger changes are accompanied by larger SDs, which is often the case, thereby homogenizing the extent of actual temperature change. How much this process distorted the actual record isn’t known, but it almost certainly did, and was unnecessary.
Surprisingly, I don’t think any of the many dozens of WUWT readers who commented picked up on the error, which makes me wonder about their level of climate sophistication.
I don’t think Shakun et al is the last word on this subject, but it offers valuable clarification of the timing and regional distribution of the CO2/temperature relationship.
Thanks or the summary and pointing out Shakun, et al. As you point out a number of issues remain. What initiated the global temperature rise about 20 kya? It’s been suggested (Wolff alludes to it) that the northern hemisphere’s ice sheets reached such a vertical extent as to modify atmospheric circulation in the mid- and upper-latitudes. If so, would such changes be felt globally? Could such changes have occurred rapidly enough to bring on the increase in CO2 about 17 kya? If you combine orographic effects with changes in insolation, is this enough to initiate the temperature rise?
I just wanted to let the RC folks know that this showed up in my RSS feed several days ago. I’m not sure what happened, if it was showing a post under construction or if it was temporarily published and then removed. Just a heads up so you all can review your processes and make any refinements to prevent posts not yet ready for public consumption from being accessible. Also, for some reason the site is in French, the field is Nom not Name, the button is Dites-le not Say-it.
Thanks, Chris. Yet more of the details of the jigsaw appear. The broad picture has been clear for a long time, but any small holes are always picked on by those who stand to lose their unsustainable way of life.
This is no surprise that CO2 does not lead everywhere, after all something has to start the process. Then the feedbacks begin to take over. It’s a bit like a Schmitt trigger, where the input has to reach a certain level before anything happens. Then feedback kicks in and the change is dramatic.
I didn’t keep the links but there is at least one d18O study from the Pacific Warm Pool which clearly indicates that first the deep ocean warmed there, followed later by the CO2 increase and then the shallow ocean warmed, leading to the LGM to Holocene transition.
Comment by David B. Benson — 28 Apr 2012 @ 10:22 PM
@Fred Moolton 8 – thanks for the Tony T Watt link. The Eschenbach response is pretty funny (don’t understand your problem with his ‘standardized’). He basically itemizes nearly all the proxies reaching their peaks after the CO2 peak is reached … while trying to claim the data “is all over the map”.
Excellent article here. No surprise that the Shakun paper has stirred up Mr. Watt and other pollution priests – years of budgie lessons teaching “CO2 lags temperature rise” took a head-shot.
On the missing ‘issues'; here’s some outside recollections. There are studies of Holocene-onset fossils showing animal downsizing trends along the Caribbean Antilles (chain turned islands). There is the Bosporus portal ‘Sea of Death’ isolation. 14,000 years ago the Dead Sea was finally shut off from the Mediterranean. Tamino’s point about ocean levels may have a corollary in the re-organization of regional climates and air currents. Milankovitch is nice, but the big cycle trigger may need the lower-ocean context to work.
Very good article, and not a second too early given the constant barrage of denial and misrepresentation around the Shakun paper started by people like Michaels and Idso, promoted for the WUWT crowd by ignorant conspiratards like Don Easterbrook and Willis Eschenbach and more recently also pushed by Motl and Shaviv.
I would also note that Schmitt et al., 2012 have indeed provided a key scientific advance on the topic of the source of the CO2, but that it still seems that things are far from being definitely settled (and the role of permafrost might still be a lot bigger than expected), plus the mystery of the 14C isotope that is clearly mentioned at the end of Schmitt et al., 2012!
Comment by nuclear_is_good — 29 Apr 2012 @ 4:38 AM
Figure 3 still does not work in either Safari or Firefox.
I think this is a topic well worth further study. My hunch is that when we understand better the Milankovitch ‘trigger’ and ‘propagation’ mechanisms we will have a clearer idea of how other aspects of climate interact. I’ve tended to accept without questioning the conventional view that the Milankovitch radiation at 65N in July is critical. Around this latitude a higher proportion if the earth is land rather than ocean and is covered (at least at present) with Boreal forests which have a high snow-covered/bare-branch difference in albedo. However 65S in January has a similar radiation profile to 65N in July except for the precession of the axis component which has the effect of introducing a circa 10,000 year phase difference. Could it be (and I’m just floating an idea) that exit from (or entry into) an ice age starts in the north and is reinforced in the south. After all the sea/ice albedo difference is large and the southern oceans are more likely to be part of an ocean mechanism for propagating the Milankovitch effect.
I see one of the Shakun authors is Bette Otto-Bliesner. She is also a lead author of the paleo chapter in ar5. It will be interesting to see how much weight is given to this study relative to previous conflicting studies.
Fred Moolten’s analysis is highly illuminating. I might even add (correct me if I’m wrong?) that it reminds me of the coefficient of variation. I can remember at least that much from engineering statistics. Except a normal COV would divide the standard deviation by the mean, providing a dimensionless number for the magnitude of dispersion.
So, if one does takes the 1/x of dispersion, it appears that logically we obtain a measure of non-dispersion or precision in the data. However it has a completely different meaning from the data itself.
Sorry to interlude but I’ve had this question for a long time and didn’t know who or where to go to ask. I’m a layperson with only highschool education so please go easy on me.
This is about the temperature didn’t seem to increase/change in last 10~15 years in relative to increase in CO2. But ice-melts are increasing around the globe at the same time, though.
My question is that does it require extra energy/heat to melt ice? I remember I learned that it takes extra energy(to cool) to freeze 0 degree C water to 0 degree C ice in school a long time ago. So I’d think it takes extra heat/energy to melt 0C ice to 0C (freezing) water, eventhough temperature wouldn’t change? The proccess of melting ice itself, changin a state of solid to liquid is part of the temperature rise, eventhough actual temperature wouldn’t go up?
I’m sure the scientists are already considering this but I’m just curious.
If anybody can just drop me a line or two to clear my mind I’ll appreciate it. Thank you.
First, welcome. Sincere questions are always welcome.
Second, if you can find a thread marked “Unforced Variations,” that’s an open thread, so your question won’t be “off topic”.
Third, yes, ice does take a lot of energy to melt. However, the amount of ice being melted isn’t large enough to significantly affect the rate of warming (<10%, I think last time I looked). However, there is also a huge reservoir of cold water in the deep oceans. Some of the heat may be going there.
Finally, look up Rahmstorf and Foster 2011–it shows that if you account for El Nino, volcanic eruptions and changes in solar forcing, the warming has continued apace. Take care, Ray
CRV9- Yes, it takes energy to melt the ice which won’t go into temperature manifestation. This is actually important for the seasonal cycle at high latitudes.
David Beach- Sorry, I just pulled those figures from the papers; paleoclimatologists have weird customs with time axes and showing multiple graphs with lots of squiggly lines on just one figure. You just have to look at them for an extra minute to interpret properly :-)
Warming, if not actual temperatures, has clearly continued unabated. For example, note that the most recent La Nina episode (2010-2011) was warmer than all previous La Ninas, andwarmer than all but the three most recent El Ninos. In other words, what was once a cool exursion (La Nina) is now warmer than past warm excusions (El Nino).
Yes, it does take ebergy to melt ice, which would not manifest itself in a temperature change. However, you may want to read some of the responses on the Arctic sea ice volume thread, which discusses this issue in depth. One of the theories discussed is the prevaling winds and currents affecting the sea ice much more than temperature. Cheers.
Ray Ladbury wrote at 27 “However, there is also a huge reservoir of cold water in the deep oceans. Some of the heat may be going there.”
About 90% of the heat is initially absorbed by the oceans. The NOAA calc is that about 16% (not sure if that’s from-total or from-ocean) goes into the deeper layers. Gavin Schmidt has had some quotable posts about it here.
@’the lack of heating’, the best comment was from a Royal Society spokesman in 2007 around the time of the Keenlyside ‘AMOC shutdown’ simulation … ‘global warming could pause … even for a decade’. La Nina’s, volcanic activity … even violent cold-weather ejections from both polar regions … the discussion has turned into sitting and waiting for the next bubble from the teapot water. Responding is just ‘swinging at a pitch in the dirt’.
Thanks Chris, Suny, for an excellent piece. It’s been fascinating to watch this story unfold over the last couple of decades. For me, the AGW lightbulb moment came with the Vostok CO2 record. The ice age orbital correlation is old knowledge; there all those years ago in my high school geology text*, along with the observation that the insolation change is way too small to provide a simplistic explanation. CO2 provided that explanation … but wait, that could only mean these guys must be right … oh shit.
Then we had the lead / lag thing, which changed nothing much, despite absurd obfuscation. Temperature increase triggers carbon cycle response which triggers bigger temperature increase, and that’s supposed to be a surprise? And now we finally have the mechanism.
The pieces are not quite all there, but the picture is clear.
[*Holmes’ famous tome; the only high school text still on my shelf. Yes I know, an odd choice at that level, but a good one I think … from an odd but rather good teacher.]
“One of the theories discussed is the prevaling winds and currents affecting the sea ice much more than temperature.”
Pretty much everything you say is based on dissembling, isn’t it? Nice not to hamstring one’s agenda with such mundane things as citations to the peer-reviewed literature published in reputable journals.
But then it wouldn’t be called hand-waving then, would it?
I’m also an amateur trying to make sense out of climate trends. The situation is confusing. As you say, there is no apparently connection between CO2 levels and recent temperature trends. I’ve done regression studies that show this, using data from 1969 on. That’s true even when CO2 levels are lagged out to 6 years. It’s also true even when controlling for el_nino and volcanos, no matter what Rahmstorf and Foster say.
The climate scientists’ response is that one cannot judge by short term trends. But that is not a good argument; they emphasize the temperature increases from about 1977-97 as confirming their theories.
The scientists should do a better job of addressing their critics. They are losing the public-opinion battle against the energy interests. Their science is largely wasted if they cannot do an effective job of persuading the public and policy makers.
In the end, the answer to your question seems to be that the CO2 greenhouse effect, according to theory, works stronger in cold temperatures. CO2 has less direct effect in lower latitudes. The temperature in the artic (but not the anartic) has increased much more than the rest of the globe, as theory would suggest. Thus the ice melt. My regression analysis shows a sizeable impact of CO2 on artic land temperatures. More CO2 leads to higher temperatures there a few months later.
Artic temperature and ice are the canary in the mine, an advance warming. The effect on the rest of the world seems to depend largely on a complicated, and presumedly irratic, set of forces that transfer heat around. This relationship is diffuse enough that one might not expect a noticeable relation between global CO2 and temperature.
Huh? Dude, have you even bothered to look at the physics of climate? Climate is noisy. If you look at the period from 1977-1997, it is also quite easy to pick 10 year periods that show little or no net warming, and yet warming over the period is significant.
And actually, if you look at the warming over the past 35 years, the correlation with delta ln(CO2) is quite significant. The purpose of science is to yield an understanding of the phenomena being studied. Period. It is not to persuade morons who’ve never taken a frigging science class–whether those morons are at you family’s Thanksgiving dinner table or in the halls of Congress.
Roy Schwitters referred to the current generation of ideologues as “the revenge of the C students”. Of course, that was back in the ’80s and ’90s. We’ve probably moved on to the D students by now. Maybe the answer is to ask the smart kids.
t marvell wrote: “The scientists should do a better job of addressing their critics. They are losing the public-opinion battle against the energy interests.”
Paid propagandists are not “critics”, and your claim about public opinion is a blatant falsehood:
“… a just-released poll from the Yale and George Mason climate change communication programs reveals the lie in this claim. 63 percent of respondents said the United States should move forward to reduce greenhouse gas emissions, regardless of what other countries do … In the same poll, the public supported — by a margin of 63 percent to 37 percent — requiring electric utilities to produce at least 20 percent of their electricity from renewable energy sources, even if that would cost the average household an extra $100 per year.”
And a recent Gallup poll found that 65 percent of Americans support “imposing mandatory controls on carbon dioxide emissions/other greenhouse gases”.
And keep in mind, two-thirds of the American people support mandatory controls on GHG emissions in spite of the relentless onslaught of fossil fuel industry propaganda, and the lies of commission and omission, that have dominated the public discourse for a generation.
The claims of global warming deniers that public opinion is on their side are as bogus as their pseudo-science, pseudo-economics and pseudo-ideology.
Perhaps YOU “should do a better job” of addressing reality.
t. marvell @34
You say “…there is no apparently connection between CO2 levels and recent temperature trends.” What “connection” would you expect there to be?
Before you answer, do remember that climate adjusts to a CO2 forcing over many decades such that the rising CO2 prior to Keeling’s first measurements would even now still be a component in today’s changing climate, albeit a minor one. And also do remember that CO2 is not the only positive anthropogenic forcing and, although it is increasing faster than the rest, it is presently not much more than half of such forcings. And let’s not forget the negative anthopogenic forcings. And the natural ones too.
So what “apparently connection (sic)” should we be looking for?
I just like to thank you all for replying to my question. It was very kind of you. I will check the ‘Unforced Variations’ section one day.
As part of the public, I must say that we, most of us, only have highschool level understandings or less. We’re usually too busy making our ends meet. However we all have the same one vote. Thank you, again.
Eager – 38&41. About the fact that the temperature growth curve seems to grow consistently upward if you factor in El_Nino. These studies are suspicious – they look at El_Nino several months prior, using that to smooth the curve. The question is why they selected these lags. It looks like a case of fishing for the best model to get the results you want. In fact my regression analysis shows that El-Nino has a huge impact on temperature, but only for the same month (witout lag), with a lesser impact lagged one month, and nothing for additional lags. Also it’s not really an “impact” – temperature is an element of El_Nino measures, so when one says that El_Nino affects temperature, one is largely saying that temperature affects temperature, an identity.
#43–To be fair though, SA, the deltas in the Gallup poll are unfavorable, even if the overall numbers are not. I don’t think that’s a long-term trend, which is to say that I think you are more right than not, but unfortunately there is some evidence suggesting the denialist machine is having some effect.
The following is part of an entry sent to the bore hole. SecularAnimish criticized me, using information that I think is incorrect, and I explain why. By leaving SecularAnimist’s comment unanswsered, it gives the impression that it is correct.
About public opinion polls. You cite polls that find that people say they are concerned with climate warming. That’s simply not true (I don’t expect climate scientists to understand polls). People tend to say “yes” to whether they are concerned about something, like reducing climate warming, that seems good. But that is meaningless without knowing how conerned. In fact few people care much about climate change.
The real facts are shown in a recent Harvard survey of young Americans, 18-29 years old. The researchers asked people to rank domestic policy concerns, 12 of them, and “combating the impacts of climate change” came in last. See:
T Marvell wrote: “The question is why they selected these lags.”
Well, since one of the authors of Rahmstorf and Foster (2011) is a regular contributor here at RC, why don’t you ask him? You could also head over to Open Mind and ask the other author. And finally, you could ask John Nielsen-Gammon why here.
They’ve shown their work, now how about you show yours.
T Marvell wrote: “The question is why they selected these lags.”
The reason is that those were the lags which gave the best fit to the data. It’s rather a standard approach. We were hardly the first to determine that there’s a lag in the impact of el Nino (and volcanic eruptions) on temperature. It was even demonstrated in a paper by prominent global-warming denialists (who correctly estimated the lag, but the rest of their thesis was rebutted here).
If your “regression analysis shows that El-Nino has a huge impact on temperature, but only for the same month (witout lag)” then your regression analysis is wrong.
P.S. The claim that “when one says that El_Nino affects temperature, one is largely saying that temperature affects temperature” is incorrect, because it’s mistaken to flatly assert that “temperature is an element of El_Nino measures.” It is for some (such as the Nino3.4 index), but isn’t used at all for measures such as the Southern Oscillation Index.
I’d say that the one who is “fishing for the best model to get the results you want” is you.
…You cite polls that find that people say they are concerned with climate warming. That’s simply not true (I don’t expect climate scientists to understand polls)…In fact few people care much about climate change.
The real facts are shown in a recent Harvard survey of young Americans, 18-29 years old.
Oh, my. You seem to be claiming that:
1. a pool of 18-29 year olds serves as a proxy for people of all ages regardless of the results of another, alll-ages poll and
2. the fact that some things concern them more than global warming proves that they’re not concerned about global warming.
Being sent to the bore hole is not something to be proud of. Why advertise one has maundered on or otherwise transgressed so badly that one has descended to being a frightful bore? Why bother coming here, where you have access to top people ready and willing to address your questions, only to promote yourself? Are you so sure of yourself that you have nothing to learn? I doubt it.
I asked for the same, but it seems t marvell has no time to present his work or link to his publications. He is now fully occupied with educating the scientists here with how shortsighted and smallminded they are. Compared to Galileo, Einstein, Feynman, did I miss out somebody.
About Foster and Rahmstorf http://iopscience.iop.org/1748-9326/6/4/044022/fulltext/#erl408263bib19
They use a single lag (e.g., lagged two months) of the Multivariable ENSO Index (MEI) to adjust the temperature data. There are several problems with their procedures. First they use levels data, as opposed to differenced (change) variable, which one should never do without testing whether the data series is stationary. Climate data are generally non-stationary, requiring that the variables be differenced (in fact, climate scientists assume that temperature is non-stationary). Second, they give very little information about how they selected the lag. They say they get the “best fit”, but using what procedure? Third, and most important, they select only one lag of MEI, without looking into whether using more than one lag would provide a better fit, as I’m sure it would. Other odd choices are that they do not use all the years available for analysis, and they had different lags for differerent temperature measures.
I used a Granger regression to study the relationship betwen MEI and global temperatures, from 1960 to present. The dependent variable is global temperature, NCDC data for monthly anamalies. Both temperature and MEI are differenced (current year less prior year). I entered 12 lags of MEI (along with 12 lags of temperature, making it a Granger regression). All 12 lags of MEI have similar coefficients, and most are statistically significant. That is, there is no reason to select any one lag as being more important than others, and if one selects only a single lag, one is leaving out many additional important lags.
It is interesting that the MEI produces many significant lags, while ENSO3.4, which I have used in the past, is only significant to one lag.
Foster and Rahnstorf also factor in volcanos, using an aerosol index. Volcanos affect temperature almost exclusively in the summer, but their analysis assumes volcanos have the same impact year around.
As for my contention that the El_Nino measures contain ocean temperature as an element: First, it is important that when using lagged, differenced variables and a Granger regression, this is not important because there is no current-year relationship in the regression, directly or indirectly. Even so, it is worth noting, in case anyone wants to compare current-period temperature and El_Nino, the measures do indeed contain elements of temperature.
The Southern Oscillation Index (SOI) is indirectly based on temperature. It is “based on the (atmospheric) pressure difference between Tahiti and Darwin, Australia. It is highly correlated with tropical sea surface temperature anomaly indices recorded in Niño3.” http://www.cpc.ncep.noaa.gov/products/outreach/glossary.shtml
Low atmospheric pressure tends to occur over warm water (and high over cold water), partly because of deep convection over the warm water. So the SOI is indirectly based on temperature because it is largely caused by it.
First they use levels data, as opposed to differenced (change) variable, which one should never do without testing whether the data series is stationary.
There’s no reason you can’t analyze non-stationary data, but more to the point, what’s important is whether the *noise* is stationary. The residuals from the fit in Foster & Rahmstorf are indistinguishable from a stationary time series. I doubt you bothered to find out. First-differencing, on the other hand, introduces very strong lag-1 autocorrelation, which I seriously doubt you accounted for.
Second, they give very little information about how they selected the lag. They say they get the “best fit”, but using what procedure?
Lags were selected as those which gave the best fit from a sizeable range of possibilities which are made explicit. “Best fit” means least sum of squared residuals. A real scientist would make that assumption (since the fit it by least-squares), which is why the reviewers expressed no confusion and raised no objection. With this point you make it abundantly clear that the only thing you’re doing is trying to find fault. But you’re doing a miserable job of it.
Third, and most important, they select only one lag of MEI, without looking into whether using more than one lag would provide a better fit, as I’m sure it would.
Nobody claimed that including more lags won’t give a better fit. In fact it *will*. But that in no way invalidates the results of F&R, and it certaintly doesn’t alter the fact that when you remove a realistic estimate of the influence of exogenous factors, the remaining temperature evolution contradicts all claims that global warming has “stopped” or even “slowed down.”
Other odd choices are that they do not use all the years available for analysis, and they had different lags for differerent temperature measures.
The time span was chosen as that for which all five data sets have coverage. Having different lags for different temperature measures was indicated by the *data itself*. The lags are only estimates, you wouldn’t expect all the data sets necessarily to give the same result, and the difference between surface and lower-troposphere temperature lags is almost certainly physically meaningful.
Volcanos affect temperature almost exclusively in the summer
Now you’re just making stuff up. This is really pathetic.
It is “based on the (atmospheric) pressure difference between Tahiti and Darwin, Australia. It is highly correlated with tropical sea surface temperature anomaly indices recorded in Niño3.
The Southern Oscillation Index is the pressure difference between Tahiti and Darwin. Your claim that because it correlates with temperature it is somehow “based on” temperature, is absolutely nonsense.
Your screed is blatantly, obviously, and pathetically nothing more than an attempt to save your own face by throwing mud on F&R. It demonstrates that your bias makes you unqualified to discuss the subject intelligently. You do not discuss, you babble.
Feel free to have the last word. I’m done with you.
“It may well be a consequence of the warm winter, as oppose to any real movement.”
Yes, but if so — interesting that it’s just with Independents. But that’s why I said that we’ll see what happens in June. One cool feature of our time series is that it has temporal/spatial resolution fine enough to see weather effects, should they occur.
I’ve decided to try to help you understand where you’ve gone wrong. I’m skeptical that you’ll listen with an open mind, but I’ll try anyway.
By first-differencing the temperature data, you’ve eliminated the trend. But it is precisely in the trend that the causal relationship with CO2 lies. Steadily rising CO2 levels are the cause of the overall rising trend in temperature for at least the last 40 years and most of it for the last century or so. If you leave the trend in place, the long-term correlation of temperature and CO2 (or more generally, climate forcing) is obvious.
Of course correlation is not causation. The causation is in the physics, which frankly, cannot be denied sensibly.
When you eliminate the trend, only the short-term fluctuations remain. One cannot hope to detect the causal chain CO2 ==> temperature in them, because temperature fluctuations are dominated by other factors (including ENSO, volcanoes, solar variations, and “natural variation”) which overwhelm the impact of CO2 change on short time scales. That’s one of the points of Foster & Rahmstorf 2011.
In addition, there are short-term factors which affect both temperature and CO2, which could mislead you into believing the opposite causal direction. One such factor is el Nino. It changes surface temperature, and it also changes patterns of rainfall over large areas of the globe. These changes alter the biospheric carbon cycle, and can significantly affect how much carbon is cycled through plant matter, in turn causing changes in atmospheric CO2. This has been well-known in geophysics for quite some time. Hence the causal chain el Nino ==> *both* temperature and the carbon cycle, could easily mislead you if you eliminate the trend in temperature data (even more so if you also eliminate the trend in CO2).
I know that first-differencing to remove trend is common in time series analysis, and especially prevalent for those who approach it from an economics background. But in this case, it eliminates the very phenomenon which one is trying to determine — the effect of CO2 on long-term temperature trends. Seeking that very real relationship using only the short-term fluctuations is destined to fail.
There is a lively debate about Foster & Rahmstrof, between me on one side and Ladbury and tamino on the other. I think this is very important, for both substantive and methodological reasosn.
First, to answer Ladbury (#63),
1 – He said, “It would appear that you are claiming that ENSO is equally likely to manifest at any of the following 12 months–but we know that is not so.” I didn’t say that. I said there are “similar coefficients,” some significant and some not. The point here is that Foster and Rahmstorf selected only one lagged value of ENSO, when they should have added all lags that made a difference in the analysis. It looks like they are cherry picking.
2 – He questions my contention that the impact of volcanos is largely limited to the summer. Let me quote from WJ Burroughs, Climate Change, 2ed ed, p. 161, “. . . major erruptions produce a substantial drop in summer temperatures for two or three yeara. If anything, the effect on winter temperatures is a warming, . . .” My own regression research corroborates this. If Foster and
3 – He said, about ENSO measures “‘correlated with temperature’ is not the same as temperature based” He misquote me. I said temperature “is and element of” ENSO measures (such that same-year relationships between temperature and ENSO are largely an identity.
To answer tamino (65).
About stationarity – in time series analysis one simply must difference a variable if it is not stationary (unless it is cointegrated with another variable, which is not the case here). There is probably nothing more basic in time series analysis. Otherwise one gets what is technically called a “nonsense regression.” There are many tests for stationarity; the most basic is the Dickey-Fuller test, and it shows that temperature is not stationary [it is I(1)]. Neither tamino nor Foster & Rahmstrof test for stationarity. Tamino also claims that first differincing introduces autocorrelation. Without differencing temperature data, one gets huge (positive) autocorrelation (which is typical of a non-stationary variable in levels). Differencing typically introduces negative autocorrelation, not as bad as the positive correlation in levels.
Again tamino says that the lags were selected by finding the best fit in least squares. What test was used, if any? More important, tamino admits, which is obvious, that Foster and Rahmstorf did not actually look for the best fit because they did not look to see if they could get a better fit after entering more than one lag.
Tamino (and Foster & Rahmstrof) say the time span was chosen to be the same for all five data sets. Why is that important? In general, in time series analysis one should use all the data available.
About volcanos, see above. Foster & Rahmstorf should not have used the volcano variable.
tomero continured (#68).
This makes no sense. First differencing is done to prevent a “nonsense regression.” It is not done to remove a linear trend, which can be easily done in levels analysis. The fact that two variables generally move in the same direction does not imply causation. Even if there is causation, it says nothing about which variable causes which. This whole post is about the two-way causal relationship between CO2 and temperature.
This brings up a problem with Foster & Rahmstrof that I did not see before. Regression analysis assumes that the researcher is sure that the dependent variable (left side) does not cause the independent variable (right side). As this post makes clear, higher temperatures lead to more CO2 because warmer water outgasses more. The Foster & Rahmstrof analysis suffers from “simultaneity bias”, which renders the results are meaningless.
To summarize, the Foster & Rahmstrof paper sufferes from 3 unquestionably deadly mistakes:
1) doing the regression in levels
2) not properly looking for the best fit, because they include only a single lag
3) simultaneity bias.
[Response: You are wrong on multiple counts here. The evidence would be whether your proposed methodology would succeed in determining the correct causality in a perfect model situation that contains the relevant physics – it won’t. Volcanoes do have an impact on the annual temperature – see Thompson et al (2009), lean and rind etc. And Hansen et al 2007, shindell et al 2004 for more detailed model data comparisons. As taming notes, first differencing removes the signal one is trying to explain, and if this is a problem for your methods, so much the worse for your methods. The physics says that a linear trend in GHGs will cause (all other things being equal) a trend in temperature. Declaring that this is non-stationary and must be removed is perverse and aphysical. However, please remember that no one is claiming that CO2 is causal purely because it is going up- that would be prone to spurious regression issues. – gavin]
[PS: This general subject has been discussed ad nauseum in previous years – see here for instance, and has appeared in the literature as well (for instance, Kaufmann and Stern (2002)). You are following a well-worn path. – gavin]
To dismiss one common method of dealing with serial correlation in climate data by saying, “the causation is in the physics” won’t wash. Most thinking sceptics accept the “the physics”; what they argue about is the balance between the natural and anthropogenic component of temperature change. If there was perfect correlation between the dependent and independent variables then the first order differences would also be correlated. The use of regression to identify the relationship between the differences would only break down if the underlying trend was linear.
Foster and Rahmstorf deal with autocorrelation in an appendix to their paper by considering the reduction in the number of effective of degrees of freedom.
The question of autocorrelation is an important one and it is probable that no ideal method dealing with it exists. It should however be possible to demonstrate that the underlying relationship remains valid despite the presence of autocorrelation. Any paper which ignores it would, rightly, be panned by both thinking and unthinking sceptics.
“About stationarity – in time series analysis one simply must difference a variable if it is not stationary (unless it is cointegrated with another variable, which is not the case here). There is probably nothing more basic in time series analysis.”
Cointegration requires finding a linear combination of the variables that is stationary. In F&R and some other cases, the models serve this purpose. If the residual series generated by a model show no significant autocorrelation, as tested by Ljung-Box portmanteau statistics, then they are not distinguishable from white noise — a covariance stationary process.
“About stationarity – in time series analysis one simply must difference a variable if it is not stationary (unless it is cointegrated with another variable, which is not the case here). There is probably nothing more basic in time series analysis.”
Cointegration requires finding a linear combination of the variables that is stationary. In F&R and some other cases, the models serve this purpose. If the residual series generated by a model show no significant autocorrelation, as tested by Ljung-Box portmanteau statistics, then they are not distinguishable from white noise – a covariance stationary process.
To dismiss one common method of dealing with serial correlation in climate data by saying, “the causation is in the physics” won’t wash.
I didn’t bring up the physics because of serial correlation. It was to address the issue of “correlation is not causation.” I think you’re confused about the meaning of this.
Re: #69 (t. marvell)
No, there isn’t a “lively debate.” Your response is just absurd.
Perhaps much of your nonsense is rooted in the fact that you have confused “stationary” with having a “unit root” (which is what the Dickey-Fuller test is for, not for stationarity). And by the way, when it comes to unit root in temperature data, no, there is not.
I was foolish to think you might listen with an open your mind, but it was worth it for the sake of other readers. Enjoy your extended stay in Dunning-Kruger land…
A rapid depletion in 13C between about 17,500 and 14,000 years ago, simultaneous with a time when the CO2 concentration rose substantially, is consistent with release of CO2 from an isolated deep-ocean source that accumulated carbon due to the sinking of organic material from the surface.
First, the chart underneath it seems to show the concentration falling – the vertical axis in the upper figure is reversed, perhaps the one in the lower figure should be?
Second, any idea what the isolated deep-ocean source might be?
If I understand the issue correctly we can determine that the Mak cycles produce relatively large regional variation in energy hitting the surface but globally the differences are very small. The question then becomes why do we get ice ages?
When I look at the globe I see mainly land mass in the Northern Hempisphere (especially near the pole) and mainly ocean in the South (again especially near the pole). A 30 W/m change in energy hitting the surface of the earth is enough to cause snow to accumulate – but this can only happen on land. Hence when the Mak cycle leads to reduce energy in the North ice sheets form, this increases albedo which reduces overall energy being absorbed by the plant and we have an ices. Conversely when the cold is in the South the ice sheets cannot form on open ocean?
How much does the above (which clearly happens) account for the observed historical record and therefore how much is left to explain but other factors such as CO2?
If my maths are correct – ice sheets down to the 45deg North will have a signifacnt albedo effect?
Ladbury (74) You say “please tell me that you are not really saying that if A correlates with B then A must be based on B. That is not just wrong, it is a logical fallacy”
Yor’re not immune from the fallacy. In comment 38 you said “if you look at the warming over the past 35 years, the correlation with delta ln(CO2) is quite significant.” From the context it is clear that you are arguing that more CO2 leads to higher temperatures (you answered my earlier comment that I could find no evidence that CO2 affected temperaturee in near term; I said nothing about a lack of correlation). Of course, the correlation you mention could also be due to higher temperatures increasing CO2 due to outgassing.
Comments 62 on, about Foster & Rahmstrof –
tamino – your’re right, I checked and the monthly temperature data that Foster & Rahmstrof use is trend stationary, so regression in levels with a trend is OK.
It seems that you have no answer to my original objection to Foster & Rahmstrof, that their “best fit” procedure is bad, mainly in that they would have had a better fit by using more lags. More lags would have given them a more accurate adjustment of the temperature series.
Ladbury (74) About regressing in differences with trending variables – differencing does not lose the trend; it goes into the intercept coefficient. Again, if the trending variable isn’t stationary, one ordinarily has to difference.
– About cherry picking. Climate scientists on RC often accuse others of cherry picking. Only others do it?
T Marvell, OK, so now you are saying that it is a logical fallacy to cite the combination of a good correlation between ln[CO2] and temperature rise + the well known physics of greenhouse warming as evidence in favor of the consensus view? Really? Isn’t that pretty much the basis of the scientific method?
Let’s be clear here so I can figure out just how dumb you are: Are you really questioning the existence of the greenhouse effect, which has been known since the 1850s? Are you questioning whether CO2 is a greenhouse gas? Or do you think that somehow the greenhouse properties of CO2 magically stop once it reaches 280 ppmv?
As to you contentions of cherrypicking, no one claimed immunity from that failing–I merely said that taking the best fit according to least-squares is NOT cherrypicking, and to contend otherwise is ludicrous.
Finally, your contention that F&R should have used multiple lags is problematic. It is certainly true that allowing multiple lags might have given a better fit–after all it has to be at least as good since the >=1 lag models contain the single-lag model as a subset.
However, the goal in scientific modeling is not mere explanation but rather predictive power, and generally the simpler model that explains the data adequately has greater predictive power. The model in F&R is elegantly simple and does a good job of showing that a linear trend due to CO2 + a few forcings that we know to be operant and important are sufficient to explain most of the variability in all of the temperature datasets. That is an important and robust result–but then to understand that, you’d have to be able to find your but with both hands and a GPS when it comes to scientific modeling.
It’s a bit hard to find words to describe the range of techniques used by artificial skeptics to discredit progress in science. “Cherry picking” is just one shortcut to describe that, for example, isolating counter-trendaceous segments of the temperature record doesn’t work, or that each of the proxy records has shortcomings but taken in sum they add to our knowledge. An open-minded reading of Mike Mann’s latest gives an overview of much of the hard work over time to try to find ways to extend and verify the record, and others have tried as well. http://www.skepticalscience.com/graphics.php?g=47
Your tone is arrogant, but your conclusions make you sort of undressed in public to real scientists who do this work every day.
It’s not that real questions don’t need to be answered: they do. It’s that these kinds of questions come up over and over and over … hundreds, thousands of times, and the responses are not heeded.
They are a kind of dragon’s teeth and the more they are discredited the more they appear.
It is not surprising that scientists, who are not known to suffer fools gladly, to say the same thing in a different way, like most intelligent people are impatient with nonsense, are more than tired of posturing, whether naive or dishonest.
Unfortunately, this is all playing out in a real world that is heading, like the Titanic, for steadily worsening conditions as the real causes and problems are ignored and politically motivated naysayers decide they know everything bout reality.
“There is a lively debate about Foster & Rahmstrof, between me on one side and Ladbury and tamino on the other.”
Lively? Maybe. Debate? No, not so much. You express no awareness of whom the two individuals are that you are engaging in “debate” with nor the credentials they bring to the table. And you consistently ignore the advice & feedback given you by Gavin (do you even understand who he is?) plus the mountainous body of evidence in flagrant contradiction to your position.
If the Drake passage became ice covered a the Last Glacial Maximum, that would have had a large influence on scale and patterns of Thermohaline Circulation. Note the question marks around the southern tip of South America, and the fact that the Falkland Islands kelp genetics indicate ice scour at the LGM – Figure 3 http://www.pnas.org/content/106/9/3249.full. Coupling from the Antarctic Circumpolar Vortex to the Antarctic Circumpolar Current, flow through the Drake Passage, and Eckmann transport driving the Atlantic Meridional Overturning Current would all be changed – see http://climate.gmu.edu/research/drake.php, especially Figure 4. Perhaps the upper panel in figure 4 is similar to the conditions of an ice covered Drake Passage, with the cutoff current loop to the South of 50 degrees representing a carbon pool of unventilated water. As Milankovic warming in the norther hemisphere is carried into the shallow return current, the Antarctic Ice margin retreats; a tipping point is reached where the Drake Passage flow restarts or increases above a threshold. This starts bringing old water from deeper in the ocean, releasing more CO2 into the atmosphere, and driving the end to the glacial age. (Yes I know it’s a lot of speculative qualitative handwaving &;>)
Ladbury (83) Anderson (85). I am not a skepting about human-caused global warming. I am very skeptical about the ability of climate scientists to convey that idea to the public. Their defensiveness is enough to turn people off. Any criticism gets emotional reactions. Anderson: In my view, the climate scientists are standing behind the helm of the Titanic, looking at the iceburg, but doing almost nothing.
I’ve been trying to research the skeptics’ claims. Some don’t pan out at all, like the notion that sun spots or cosimic rays are behind the temperature growth. On the other hand, I cannot rule out other claims, particually that there is no statistical relationship indicating that CO2 causes temperature growth. A big issue here is that any correlation between the two can be due to CO2 outgassing. Gavin – please tell these jerks that this is likely. Just because skeptics make this claim does not mean it is false. This whole post is about the two-way relationship between temperature and CO2.
Gavan linked me to an article by Kaufmann and Stern, saying that greenhouse gasses are cointegrated with (i.e., closely tied to) greenhouse gases. Cointegration says nothing about causal direction, yet they claim that the cointegration is due to greenhouse gases causing temperature. Any knowledgable skeptic would laugh at that paper. From the point of view of an outsider, Foster & Rahmstrof has the “look and feel” of confirmation bias.
As part of the general defensiveness, I’m sure that you consider me a “closet skeptic”. I’m not. But I am very angry that the climate science community is “circuling the wagons” in defense, rather than trying to do an effective job of persuading people to act to combat global warming.
I’m trying to figure out why, statistically, there is no causal link from CO2 to temperature. A theory I am working on is that a strong direct link only occurs in cold temperatures, where the greenhouse effect is greatest. Links to temperature in other areas are diffuse. So far this holds up statistically, at least with respect to land temperatures in the north. I’ve got a lot more work to do.
Can anybody point me to sources that explain why the greenhouse effect is greatest at the poles, and how much greater it is? I’ve just seen general statements to that effect.
One last, but interesting, point. All this has gotten me to look more at the issues of stationarity. I was surprised to find out that land tempature since 1900 is stationary (NCDC data, monthly anamolies, ADF with 12 lags). Ocean temperature is far from stationary, but it is trend stationary. There appears to be some self-regulating factor on land, while ocean temperatures plow upwards.
“particually that there is no statistical relationship indicating that CO2 causes temperature growth”
I think that skeptics have rediscovered that (statistical) correlation does not prove causation.
On the other hand, if polyatomic gas molecules in the atmosphere absorb Lambertian infrared radiation coming from the ground and re-emit it isotropically, the effective emissivity decreases, and the surface will warm until balance between insolation and radiation is achieved. More CO2 from fossil fuels will increase the intercepted radiation, and further raise the temperature. More water vapor from rising temperatures will further increase the temperature rise. Rising temperatures will cause outgassing of CO2 from the oceans, but its C12/C13 ratio will be that of the atmosphere when sinking thermohaline circulation took the CO2 from the atmosphere ~1600 years ago, which is different from fossil fuels. This will cause a higher climate sensitivity, but with a long lag ’til equilibration(800 years, perhaps; sound familiar?). Rising temperatures will melt snow and ice, mostly near the poles, and cause larger temperature rises at the poles, firstly in the Northern Hemisphere.
On the third hand, Causation forces correlation; if these causal chains have occurred, there will be correlation. Is this model wrong? Nope. If you describe the model with equations, instead of narrative, and plug in the numbers, the models are inaccurate; partly because the initial conditions aren’t known precisely(measurement noise), partly because the system is chaotic(turbulent, locally divergent – THIS rising bubble of warm moist air got a head start because a farmer plowed his field yesterday, decreasing the albedo, starting the thunderstorm that sucked up lot of nearby warm moist air, and spawned a tornado that flattened Picher OK), and partly because those two things interact(the butterfly effect).
Have the skeptics created an internally consistent narrative model which describes a different outcome? Let us take for example something you touched on, “…A big issue here is that any correlation between the two can be due to CO2 outgassing…” plus the argument that “the Medieval Warm Period was warmer than today” or “CO2 increases lag temperature increases by 800 years”. The ice cores don’t show 390ppmv+ CO2 that would have outgassed if these arguments were true. See Figure 3 of “Atmospheric CO2 fluctuations during the last millennium reconstructed by stomatal frequency analysis of Tsuga heterophylla needles” Kouwenberg et al http://fm1.fieldmuseum.org/aa/Files/lkouwenberg/Kouwenberg_et_al_2005_Geology.pdf Yet another hockey stick, and declining CO2 ~950-1200 AD – the peak of the MWP according to http://www.co2science.org/data/timemap/mwpmap.html
As for paleoclimate CO2/temperature changes around the Younger Dryas, “The reconstructed atmospheric CO2 reduction of ≈25 ppmv indicates a temporarily enhanced North Atlantic sink for CO2 at the time of the 8.2-ka-B.P. cooling event.” http://www.pnas.org/content/99/19/12011.long; somewhat less than the ~110ppmv modern increase in CO2.
Which leads me to another question – the melting glacial/Greenland/Antarctic ice water is depleted in CO2(check out the bubbles in your ice cubes) – how much additional CO2 is being sequestered by this runoff into the oceans, and what happens to CO2 increase when we run out of glaciers? My S.W.A.G. is that there’ll be so much runoff from Greenland/Antarctica by then that it won’t make much difference.
Dodge 89 – I have no trouble with this.
You say “if polyatomic gas molecules in the atmosphere absorb Lambertian infrared radiation coming from the ground and re-emit it isotropically, the effective emissivity decreases, and the surface will warm until balance between insolation and radiation is achieved.” What I need to know is whether the absorbsion and emmissions depends on temperature – is it greater for CO2 when temperatures are colder? Do you know of anything I can read about this? As a non-climate scientist, I have difficulty navagating the literature.
69 t marvel says, ” There is probably nothing more basic in time series analysis.”
I’m assuming you’re not a climate scientist. Please correct that assumption if appropriate.
When I read something by not just an expert, but a top-notch one, and my initial thought is that it violates something that is “most basic”, yet other experts in the field don’t seem to “get” the “obvious” flaw, then I try very hard to figure out what it is I’M missing. The PIOMAS thread is a perfect example. I STILL don’t understand the reactions – on one hand the models are “predicting” triple the current ice (since ice has a short memory, initial conditions should only have a weak influence), yet on the other hand people seem to be predicting another record or near record low while at the same time not objecting about the “super-flawed” models. It makes no sense to me. It is “most basic” that either the ice should double or triple quite quickly or the models are seriously flawed. My conclusion is that I don’t quite get it yet, not that the experts are failing at undergraduate-level concepts. Perhaps you’re in a similar situation here as I’m in there.
And if anyone would kindly go to the PIOMAS thread and help me with my conundrum, I’d appreciate it. Thanks.
Well, Gavin is too polite to call me a jerk, but I’m happy to be one if that helps. However, I’m not one of the the many knowledgeable people here who are worth the attention if you can get those plugs out of yours ears/brain.
The arrogance is even more apparent when the namecalling comes forward.
“circling the wagons” is not what is happening here. People are trying hard to help you out, and you are not paying attention and doing your homework, which irritates people who have better things to do than be ignored.
It is profoundly boring to have someone self-righteously trying to reinvent the wheel and demonstrating a lack of observation and critical thinking in the process.
If you have this notion that ocean outgassing is the cause of the current CO2 increase, I recommend you do some simple calculations for yourself (see below). The calculations will require you to look up some things, but they’re all freely available on the internet. No scientific literature required.
The calculations are as follows:
1. Calculate the average annual increase in total CO2 in the atmosphere in the last decade
2. Calculate the average annual net emissions of CO2 by humans over the last decade
3. If you believe oceans are responsible for the increase, calculate how big its average net annual emissions must be to overwhelm those of humans; you calculated the latter value in point 2. Just assume that the net annual emission by the ocean must be more than 50% of the net emissions by humans
4. Now calculate how much CO2 must be taken up, annually, by some third ‘source’ (a net sink) in order to allow point 1 to still be valid.
You will have to make some assumptions here and there.
Now, identify that “sink”, or ask those that claim the increase is due to ocean outgassing to identify that sink for you. Assess its likelihood of being a sink of such a large amount of CO2. Remember, this calculation you just did only applies to the last decade.
t. marvell: “On the other hand, I cannot rule out other claims, particually that there is no statistical relationship indicating that CO2 causes temperature growth.”
OK. I’m gonna try to be nice here. Where in the hell did you get this little nugget? The phrasing doesn’t even make sense! What is more, it is simply too vague even to tell you where you are going wrong. Ferchrissake, we have a 35-year warming trend; we have diurnal, seasonal and latitudinal dependence that is exactly what would be predicted from greenhouse warming; we have a cooling stratosphere even as the temperature warms; we have the glacial/interglacial cycle…do I need to go on? Where in the hell are you getting this crap?
WRT the source of the CO2, Brian has already pointed out the isotopic signature of the CO2, but over and above this, we’ve produced about 2x as much CO2 as has gone into the atmosphere! The oceans are becoming more acidic. You really haven’t looked at this much, have you?
WRT your “theory”, sorry, it doesn’t hold up. Temperature effects on the absorption of IR by greenhouse gasses won’t help you, as they are pretty tiny over the range of terrestrial temperatures. The distribution of energy states will follow the Maxwell Boltzmann equation. The reason you are having trouble finding out why you are wrong in the climate literature is because you are wrong on a much more fundamental level. This is basic atomic physics.
Even more fundamentally, you are trying to solve a problem that doesn’t exist by proposing a theory based on physics you don’t understand. Please, please, please, quit going to the skeptic sites until you have enough of an understanding of the actual science to avoid being fooled.
The reason why climate science has “circled the wagons” against the denialists is the same reason why biologists have circled the wagons against creationists or that medical scientists have circled the wagons against the anti-vaxxers. Science–science itself, not just climate science–is under attack. The same people are behind this as were behind the pro-tobacco crap of the 60s-90s–the exact same people.
t marvell, to say you are ignorant of climate science is not an insult. It is a fact. The way to rectify that ignorance is to learn the science, and you need a strong grounding in the mainstream science before you can evaluate its strengths and weaknesses. I have a PhD in physics. It took me about 2 years to learn enough of the basics that I felt grounded enough to understand what was going on. You seem like a smart guy, you could probably do it in a comparable time. There are plenty of others who have gone through the same process and would be happy to help you out as well. Do the math.
Ah yes “circling the wagons”, you do realize that that’s a golden oldie from the threadbare grab bag of lame denialist epithets?
So the frustrating thing seems to be here that in the “marketplace of ideas” AGW isn’t selling properly, so it must either be a bad product or badly presented. Perhaps we should just pause for a moment, take a deep breath and bow our heads to quietly reflect on this odd notion and the worldly marketplace upon which it is modeled.
You’d think that after the last few years, people would be a little more skeptical of marketplaces in general, seeing them less as shining citadels on the mountain top and more as tawdry bedlams of hawkers and posers, grifters and marks. On the other hand, I guess I can see how those wishing to elude culpability or deny their gullibility might wish to double down on burnishing the old illusions.
All I can say is wakey, wakey Gold Bricks! It’s time to get up and greet the new day. There’s work to be done. Perhaps we should begin by taking out all that libertarian garbage thats been piling up over the last few decades.
While claims of outgassing are valid during previous eras, there is one component present today that was not around back then. That is the burning of carbon-based fuels. In order for the CO2 increase to mostly a result of increasing temperatures, we would need to prove that the amount of CO2 being emitted is minor in comparison. Since most calculations contend that the amount of CO2 emitted shoudl has resulted in twice the increase measured, I would agree that the CO2 rise is not a result of outgassing.
Dhogaza 92, Anderson 94, Marco 94, Ladgurn 96, Dan H. 97.
The physics couldn’t be clearer – as water warms it can hold less gas, including CO2. If you are contesting outgassing, you are physics deniers.
I have discussed this in earlier comments – in the post on Lindzen in March – see 460, 482, 517. Gavin accepted the reality of outgassing. Again, my research finds that higher ocean (but not land) temperatures lead to more Co2 a few months later. The results are highly significant
statistically, although the magnitude is small compared to human-produced Co2.
[Response: Many things are correlated with the seasonal cycle. Concluding that seasonal correlations must relate to ocean outgassing is not however a sensible conclusion (indeed, this is a very small component). – gavin]
You can do a quick test of this relationship. Ladbury said above (#37) “if you look at the warming over the past 35 years, the correlation with delta ln(CO2) is quite significant.” Is that correlation due to CO2 increasing temperature, or temperature affecting CO2? To begin with, the former seems unlikely because the global warming effects of CO2 are unlikely to become manifest right away (the correlation between differenced variables, which Ladbury uses, only pertains to same-year relationships). I propose the following test:
Using annual CO2 and temperature levels (not anomalies), take logs and differences as Lanbury does (thus getting, essentially, yearly percent changes). Correlate last year’s CO2 with this year’s temperature, and then the other way around. It’s an easy analysis, and certainly Ladbury can do it. The results: last year’s CO2 has a negative correlation with current year temperature (almost certainly because volcanos give off CO2).
[Response: Nonsense. Volcanic signals are orders of magnitude too small to emerge in such an analysis. Most of this is related to deforestation variability and ENSO (and impacts of ENSO on the terrestrial carbon cycle). Nothing to do with outgassing. – gavin]
The correlation between lagged temperature and current CO2 is positive, large, and highly significant, much more so than the correlation between current year CO2 and temperature changes. The relationship occurs only for ocean temperature. That is strong evidence that higher ocean temperature increases CO2 in the short term.
Carbon sinking obviously is a countervailing factor. Whether it overshadows the outgassing effect depends on timing and location. Sinking takes time, since ocean mixing is slow below 200m. Outgassing is greater in select areas, such as when warm water mixes with cold water, causing the cold water to lose CO2. I don’t know if anyone has modeled the tradeoff between outgassing and carbon sinking over the short term (a year or two) that is relevant to Ladbury’s correlation and my regressions. Empirically, however, it is clear that outgassing dominates in the short term. I admit that the long term is more important, but Ladbury’s results are just for the short term. This positive feed-back between temperature and CO2 can accellerate AGW, and I hope it is incorporated into the climate models.
Maybe I misunderstood what you meant, but to me it sounded as if you claimed ocean outgassing is responsible for the current increase in atmospheric CO2. PLease correct me if I am wrong.
The calculation I proposed you’d perform would show you there’s a big problem in that claim: we’d need a sink that has taken up well over 100 Gigatons of carbon in the last decade alone.
96 Radge H says, “So the frustrating thing seems to be here that in the “marketplace of ideas” AGW isn’t selling properly, so it must either be a bad product or badly presented”
He’s attempting to improve the fortunes of a product which is superior but still not trouncing the opposition. It’s a good thing for a scientist to keep the public debate in his/her mind while choosing work, and much of that is already being done. Answering skeptical scientists’ dubious papers is a prime example. Then there’s Dr Hansen’s paper on extreme temperatures, which takes informing the public to a whole new level. And now, work on clouds will narrow the climate sensitivity range.
I’m looking at short/intermediate term effects, one to 72 months, largely for the practical reason that the research I know how to do pertains to that range. Climate scientists concentrate more on the long term. We’ve been talking past each other Ladbury obviously is thinking long-term, except that he brought foreward a correlaton that only pertains to the short term.
I have a feeling that climate scientists should pay even more attention to the intermedate term, say 2-10 years. One reason is to convince the public about the reality of AGW. People can easily judge short term (daily) weather forecasts, but not long-term forecasts. They could also judge intermediate forecasts. That’s a difficult period for climate scientists to handle, but I suspect that they should devote the great bulk of their resources there. (Also, of course, forecasts in this range have immediate practical consequences.)
You can detect the signature of ENSO (and Mt. Pinatubo seems to show up well) on CO2 growth rate…it’s small but it’s there. With just some quick looking, I found a good relation between the Nino indices (doesn’t depend very strongly on which one) and Mauna Loa monthly growth rate anomaly (at least a quarter of the variance explained) with the best fit at a ~8-9 month lag between the growth rate anomaly and the Nino index.
The physics couldn’t be clearer – as water warms it can hold less gas, including CO2. If you are contesting outgassing, you are physics deniers.
Yet the fact that oceans are currently a net sink for CO2 and actively absorbing in the neighborhood of 40% of the CO2 emissions generated by the burning of fossil fuels is well-documented through observations.
So either the observations are wrong or … perhaps … just something I’ll put on the table …
You don’t understand the physics.
I provided a link to a paper addressing CO2 absorbtion by the oceans above, which obviously you didn’t bother to look at.
Someone else above has done the same, which I doubt you’ll look at.
“I’m looking at short/intermediate term effects, one to 72 months, largely for the practical reason that the research I know how to do …”
Then you want to be talking to your weatherman about the weather, not to climatologists about long term global climate, your foreshortened perspective does not include the complete complex of cycles that affect the climate, which is in terms of decades, not months.
“People can easily judge short term (daily) weather forecasts, but not long-term forecasts. They could also judge intermediate forecasts.”
Again, you need to be talking to meteorologists – I judge their (daily) weather forcasts to be generally close, rarely perfect, or better than my own – I judge their intermediate term forecasts to be coin tossing, even the 7 day forecast changes daily, and at any given time it’s rarely close in retrospect, or again, better than my own. Seasonal forrcasts are pure hand waving – some online US weather site guru said last fall western Canada would have the coldest, snowiest winter in decades …. not even close. As for the long term weather, ask a farmer, they’ll tell you the climate has changed and greater change in a similar direction will not help grow your food.
Dhogaza (105) – As I said, outgassing and carbon sinking are obviouswly opposing factors. I find only that upward changes in ocean temperatures are followed about 6-12 months later by upward changes in CO2. Beyond that, out to 6 years, I see no connection – both are absent or they cancel each other out. In the long haul, obviously, sinking outweights the outgassing. I’d be very interested in any research about the timing – how quickly does sinking occur as oceans warm and CO2 increases (how many months or years should one expect a noticable adjustment). The same for outgassing – i.e., are my fidings supported or refuted anywhere?
This short term stuff is not relevant to Shakun or the post above. But I suspect deniers have found this short term link, which is easy to find. It’s best that climate scientists not deny it, but to have an answer as to why it does not explain the CO2/temp connection in the long haul, over the time period that AGW is a concern.
103 t marvel said, “I have a feeling that climate scientists should pay even more attention to the intermedate term, say 2-10 years. One reason is to convince the public about the reality of AGW.”
Your suggestion boils down to “Climate scientists and meteorologists should team up to aggressively work on ENSO forecasting.”
Predicting weather over a year in advance is a daunting challenge, but you’re probably right that advancements in long-term weather forecasting will help convince the public that climate science is on the right track, regardless of the strength of the connection. Here’s a link which shows recent model output. http://iri.columbia.edu/climate/ENSO/currentinfo/SST_table.html
Now that it’s clear to one and all that this dance with T Marvell has been done before, right here at Real Climate, and that he’s not budged a micron from his science denier stance, is impervious to honest attempts to supply him science resources to set him straight, I suppose we should just ignore him.
Shame on me for paying attention to you, T Marvell. I wasn’t smart enough to recognize that you’d been down this bullshit path months earlier here at real climate.
If you can’t learn, that’s not my problem.
If you really think you’re overturning modern physics and statistics, that’s not my problem, either.
Bailey (110), etc. I like climate4you as well as MARodgers’ and dhogaza’s sites. The graphs are entertaining. They are helpful entry points. Climate4you is skeptic, but his charts are interesting. Earlier I suggested that RC add links to the first two. I don’t search to see what the skeptics say, but one cannot avoid hearing about their arguments.
Just because I take positions you don’t like doesn’t mean I’m a closet skeptic. I don’t hold these positions very strongly (I look at the ice extent charts every day with amusement more than concern). As an outsider I’m not devistated if I am wrong, and there is obviously a lot I don’t know. I get a lot of help from commenters on RC. The adverse comments are what I would expect as a novice and outsider. I’m going on vacation tomorrow, so I won’t be able to play the fool very much.
Gavin (In 99) colose (104). I ran that rudemtary correlation between lagged CO2 and temperature without years 91-93 and 82-84, and got the same result. So volcanos are not the reason for the negative correlation. I don’t put much stock in correlations unless backed up by regression results.
MARodgers (108) you bring up my “finding” that CO2 changes are followed several months later by changes in ENSO2.4. The relationship is negative and highly significant statistically. I have now replicated that result with the MEI index — CO2 increases are followed by MEI declines some 2-10 months later. A wacko result. If I were not an outsider, I would probably keep mum about it because it makes me look wacko. It’s not due to any seasonal factor, which I control for in several ways. I checked aerosols, and they don’t explain it. I like to view unexpected results as fun detective work rather than annoyances.
This negative lagged relionship between CO2 and El_Nino might have something to do with the negative correlation between temperature and lagged CO2. More CO2 drives El_Nino down, which drives temperature down. In my regressions there is a small but noticable negative relationship between lagged CO2 and ocean temperature, which goes away when I enter El_Nino as a control variable (EMSO2.4 or MEI). Fun.
my post 89 – I said that land temperature is stationary. That would be an interesting finding, but I now think it is wrong. I used the Augmented Dickey-Fuller test, which includes lags of differences (of the variable in question) as controls. One is supposed to include all significant lags. I concluded that lag 12 was the last significant lag since additional lags up to 15 are not. But now I have checked out further lags, and there are many significant lags out to at least 60. When the extra lags are entered, land temperature no longer is stationary. Moreover, its not stationary with a trend. Nor is total temperature.
The implication is that temperatures are not stationary (don’t tend to come back to a level or to a trend over the long haul). This makes them difficult variables to deal with. They probably should be always differenced. One can try to deal with stationarity by correcting for autocorrelation, but as far as I know one cannot tell definitely whether this actually removes the non-stationarity. The dangers when using a non-stationary variable in a levels regression are potentially so bad (a nonsense, or spurious regression) that the safe course is to do the regression in differences. The drawback there is that one loses information about long term trends. Perhaps if a differenced regression reaches results consistant with a levels regression, the latter is acceptable.
Another reason for using differences is to limit collinearity, which is especially likely when entering many lags of a variable.
t marvell, would you like some dressing to go with that word salad? Given that you’ve chosen to ignore the FACTS of ocean acidification, delta C-13 and C14 and much else, I see considerable evidence to cast doubt on your bona fides. Don’t forget to sweep up the ashes of your credibility.
Marcus (116) Right. As I said earlier, it takes special situations for outgassing, like when warm water mixes with cold water. If I’m not mistaken, the cold water might be saturated because it is neutrant rich, and regularily mixes with warm water in the South Pacific.
[Response: Outgassing is very regionally dependent since it is a function of the upwelling of deeper (colder) water that is high in dissolved inorganic carbon (mainly from the remineralisation of falling biological matter and the advection of polar water to depth). Effectively, CO2 is absorbed into the ocean in polar regions and is outgassed via the tropics and other upwelling zones. It is not very sensitive to the seasonal cycle, and doesn’t vary hugely as a function of ENSO either. The short term signals in the atm. CO2 record are dominated by tropical deforestation variations, and terrestrial carbon cycle changes (respiration in soils, deciduous plants, droughts etc.). They have very little to do with the long term trend (driven by fossil fuel burning) but are important for understanding the sensitivity of the carbon cycle to changes in climate. – gavin]
(Gavin 120)From my limited point of view, this is very important. As CO2 and temperature are cointegrated, which means a virtually ironclad causal connection between the two. They have to trend together. The only major uncertainty left is the causal direction, which cointegration says nothing about. Outgassing is the only causal connection I can think of in the Temperature-to-CO2 direction (but my knowledge is limited). My regression analysis shows pretty clearly that the temperature-to-CO2 connection is short term, less than a year, with no apparent impact over the next 5 years. It is also small compared to the yearly increase in CO2. Perhaps other research reaches the same result. This is evidence that the part that outgassing plays in creating cointegration is small. This doesn’t address longer causal connections, but if the net impact of temperature on CO2 can be shown to be neutral or in the negative direction over then long term, than cointegration probably means that CO2 is causing global warming. I’m sure there are studies quantifying how much CO2 gets absorbed in the ocean in short and longer terms. That impact can be compared to the short term effect of outgassing.
[Response: I pointed you to some of the Kaufmann work on this earlier. But I have to counsel some caution as to your conclusions. Statements about what apparently cointegrated data must do are based on infinitely long time series, while actual time series are finite, and with plenty of auto-correlation and so the ‘true’ level of cointegration is not that certain. Secondly, I can build physically meaningful timeseries of climate that show any number of connections and degrees of I() for each variable for short periods (have CO2 climb quadratically = I(2), but have a deep ML and plenty of noise, SAT will look like I(1), and yet the entire trend will have been caused by the CO2, but with an acceleration term that is not detectable statistically). Your first differencing removes the trends for the large part and so restricts you to short term variability – much of which is related to hidden variables in your analysis (i.e. ENSO, volcanic AOD etc.), thus causality is going to be tricky. People have done a lot of work on the physics of the carbon cycle on short time scales, and outgassing changes are just very small, while terrestrial responses are much larger. – gavin]
Whenever I look at temperatures curves showing the last several glacial cycles, I’m struck by the asymmetry of the process. The glacial advance is long and with many fluctuations, but when it bottoms out at maximum glacial advance, the reversal is much, much quicker and with fewer and smaller fluctuations. And this is despite what should be a huge increase in the Earth’s albedo with all that ice surface, that I’d expect to positively reinforce the ice extent.
This discussion is not directly addressing that, but I take away the idea that CO2 increases rapidly enough, by a variety of processes, to greatly amplify what would otherwise occur just due to orbital (Milankovitch) cycles. Oversimplified, but essentially true?
And geological processes reducing atmospheric CO2 continue:
“Erosion and World Climate
Global climate is a good example—not today’s global warming episode, but long-term climate changes on the scale of many millions of years. This geological climate cycle depends to a large extent on the geological (not biological) carbon cycle…..”
“PS: Human activities increase erosion; in fact we now play a major role in Earth’s cycle. If strong erosion tends to cool the Earth, might this eventually counteract global warming from the greenhouse effect? Maybe, but not in time. The geological carbon cycle is far slower than the biological one.”
Andrew Alden’s geology explanations at About.com are well worth reading and pointing to: clear, well cited explanations in a few well chosen words.
I think you understate the importance of cointegration here. With annual data, 50 years is short, but the results are very clear With land temperature, the critical value is -7.1 and the DW 1.94. The probability level has to be less than one in a million, alhtough I’m sure no one has bothered to calculate that. For this kind of analysis results like that are highly unusual, all the more so because the limited number of time periods. I get similar results, slightly less strong, with monthly data and with ocean temperature. Almost all time series analysis assumes an infinate series, but uses finite data. But that assumption is not considered critical (just about any kind of analysis anywhere makes assumptions, and this assumption is less damaging then many), With results this strong there is litte chance that this is an issue.
The uncertainties you mention pertain to stationarity of temperature time series, not to cointegration. Stationarity is indeed a problem (see my 115 above). The ADF test results are uncertain (I haven’t checked other tests). As I said, it is very risky to assume stationarity, since in levels one cannot know whether the results are spurious.
You say differencing removes trends – no, the trends go into the intercept. If you are advocating for any other kind of trend being lost by differencing, it is likely to be a trend that causes non-stationarity. It’s not quite right to say that differencing limits the analysis to short term trends. With differencing one can usually enter numerous lagged depenedent variables without risking collinarity (I routinely use up to 72). These lags actually pin-point the location of any lagged impact, unlike levels analysis. Levels analysis, on the other hand, can vaguely suggest longer term relationships, but not if the data are non-stationary.
Earlier I said that cointegration does not indicate causal direction, so one must rule out a Temperature-to-CO2 relationship, and I had found such a relationship, but only short term. You said that relationship (out gassing) is minor, which I found. The question is whether it is overshadowed by the opposite effects. I suspect it is, but that I don’t know enough about it.
More important, my analysis earlier strongly suggests that the outgassing is caused by ocean temparature only, and not by land temperature. I don’t know if there is any theoretical argument why land temperates would affect CO2 levels appreciably. I doubt that reverse causation is a factor in the land temperature & CO2 connection.
I left my copy of Kaufmann at home (I’ve on vacation), but my feeling about it is that it established ccintegration between temperature and CO2, but that it left the causal issue hanging, and probably more important, that relationship got buried with a lot of other analysis.
It seems to me that the climate scientists have not sufficiently picked up on a big story. Cointegration like this is hugely important. If economists ever get similar results, they’d be dancing in the streets.
I think that climate scientists are putting too much emphasis in their models (which I would guess involve assumptions that are much more uncertain that cointegration analysis). The models have not been able to persuad people and policy makers to move. Cointegration, although also an tecnical topic, can probably be explained to lots of people, more so than the climate models.
It’s a poor sort of memory that only works backwards.
Cointegration analysis of hemispheric temperature relations
RK Kaufmann – J. Geophys. Res – math.ku.dk
“… Evidence is mounting that changes in global surface temperature can be attributed to human activities that increase the atmospheric concentration of greenhouse gases and tropospheric sulfates [Sanier et al, 1996a, 1996b]. This evidence comes from two sources: …”
Allow me to acquaint you with a concept that has evidently escaped your attention: the scientific literature. Do a search. There are thousands of climate scientists. Do you really think nobody has looked at the fricking time series?!
I clearly said that the coinegration between temperature and CO2 is nothing new, and mentioned Kaufmann. My argument is that the cointegration is much more important than seems to be acknowledged. Also I have ten more years of data after Kaufmann, important since the CO2 data series is short.
I don’t know if there are other papers on the subject. In general I find it difficult to research the literature in climate studies.
You say “Cointegration … can probably be explained to lots of people, more so than the climate models.” and this may be why you rate its importance. Yet people-wise, you have a pretty ‘soft’ target with the folk here but even so your cointegration approach appears to be making very heavy weather of it.
Do consider the situation if you (or others) ever do show some incredibly strong statistical link. Would it not become but another line in the “Oh yes it is. Oh no it’s not.” pantomime?
Far more straightforward approaches with nice graphical outputs that smooth out the wobbly rise in global temperatures (eg Foster & Rahmstorf & Neilsen-Gammon ) have failed to impress the ‘great unwashed.’
So, if your cointegration approach does prove successful (which is something that I consider unlikely), what magic ingredient do you employ to make it irrefutable in the face of reluctant public & political opinion and in the face of aggressive contrarian opposition?
MARogers – Foster & Rahmstorf don’t address the issue of AGW. They just try to straighten out the temperature curve.
Cointegration. on the other hand, nails down the CO2-to-temperature connection. It’s much easier for people to accept the notion that temperatures are rising than it is to accept the notion that humans are causing it (as opposed to natural variation).
To me it is odd that the climate scientists have not emphasized cointegration.
It’s hard to overstate the importance of cointegration. It is probably the strongest statistical evidence that two variables have a causal relationship. The two economists who created the concept received a Nobel prize for it. I think it is the only Nobel given for a statistical technique. Cointegrated variables move around but in the long run cannot move too far apart. They are like two dogs tied together by an elastic cord. They can run around the field separately, in any direction, but when the distance becomes large enough, they are pulled back such that they move in the same general direction together in the long run.
The 2002 Kaufmann&Stern article shows this relationship. The article might lose impact because it doesn’t test CO2 specifically, just a concoction of greenhouse gases, and because it includes a lot of additional analysis. Here, to get the AGW message across, I think it is important to focus in on the main message, CO2 and temperature.
I suspect that nearly every economist and statistician would accept AGW if they accept (replicate) my finding that the cointegration is very strong.
It kind of cracks me up when economists try to teach math to physicists. I never could get into the study of economics because the rigor so often breaks down into hand-waving, ideology and polemics. You want to talk about politicized science, look to econ.
T Marvell, cointegration is not the only Nobel in Econ for a statistical technique. Look at the most recent one for vector autoregression, there are probably others but who cares about Nobels anyways. Could it be that cointegration is your hammer, and climate is just another nail to you?
As for overstating cointegration being the best way to establish causation: Despite its name, Granger causality is not sufficient to imply true causality. If both X and Y are driven by a common third process with different lags, one might still accept the alternative hypothesis of Granger causality. Yet, manipulation of one of the variables would not change the other. Indeed, the Granger test is designed to handle pairs of variables, and may produce misleading results when the true relationship involves three or more variables. A similar test involving more variables can be applied with vector autoregression.
For other readers, Granger was one of the guys who got the Nobel in 2003 for cointegration who authority T Marvell is appealing to.
Comment by Unsettled Scientist — 13 May 2012 @ 4:09 PM
Unsettled – you mix up Granger causality with cointegration. The two happened to be created by the same guy. Cointegration is based on stationarity tests of residuals. the Granger causation test is based on lags, and only implies priority in time, as you say, and was not worth a Nobel prize.
There’s all kinds of math.
t marvell @131
Ask yourself – who are the folk who would require the least convincing of the merits of your ‘cointegration approach’? Who would consider ‘nailing down the CO2-to-temperature connection’ a really worthwhile achievement?
If you cannot convince the audience here, your ‘approach‘ is in trouble!
And guess what? There appears to be no takers for your ‘approach‘.
It has been explained to you before that the conventional wisdom is that tbe wobbles of ENSO induces wobbles in both global temperature & in atmospheric CO2. This causality may result in statistical correlations between ENSO-temperature-CO2 being found. Indeed, they can be observed if the three values ENSO, dTemp & dCO2 are plotted out on a graph.
It may be interesting to know that statistical correlation is stronger between, say, CO2 –> temp or CO2 –> succeeding negative values of ENSO, but does this go anywhere? Is it explained by an evident physical process? Does it pass the Gwilym Jenkins test (ie have you graph it out, my boy!)? The answer is no & no.
This explains why you are having dificulty convincing folk here. And which ever route you choose to travel, the roads gets stonier away from here.
Climate scientists say “our models show AGW. we are the experts. trust us.” Econometricians are the time-series experts. But you say “I don’t need to understand that. I can just ignore it.” You cannot have it both ways.
Unsettled (133) – You say that economists’ use of statistics is mixed up with their ideologies. That’s basically true. But the time series math is the province of the econometricians, who as far as I know don’t build ideology into their math.
What’s this about ENSO causing more CO? Outgassing? Even the circular link you proposed exists, it’s not relevant to cointegration, which takes account of such quirks. For one reason the mechanism you posit is short term, while cointegrationis long term (I’m now trying to estimate the lag between CO2 increases and noticeable increases in temperature, and it seems to be at least 10 years.)
A major benefit of cointegration is that one can regress temperature and CO2 in levels, whereas ordinarily that would lead to a spurious regression because the variable are not stationary in levels. A levels regression leads to highly significant positive coefficients.
Seriously, this is the same R.K. Kaufmann — right? Cointegration analysis of hemispheric temperature relations[PDF]
RK Kaufmann – J. Geophys. Res – math.ku.dk
“… Evidence is mounting that changes in global surface temperature can be attributed to human activities that increase the atmospheric concentration of greenhouse gases and tropospheric sulfates [Sanier et al, 1996a, 1996b]. This evidence comes from two sources: …”
Time series math is not the province of econometricians. That which is applied to economics is … but there are those of us who are statisticians, pure and applied mathematicians, and yes, practicioners of the physical sciences, and we not only know the math, we know how to apply it to physical sciences better than econometricians. Your claim is not just appeal to authority, it’s repugnant hubris.
As for your poorly-thought-out devotion to cointegration: it’s true that the drunk and her dog wander all over the place but never stray very far from each other, because they’re cointegrated. It’s also true that CO2 and temperature don’t stray very far from each other. What you fail to get is that they don’t wander all over the place.
Take a look, for instance, at CO2 concentration from, say, the year 1000 to about 1750 (before the industrial revolution). Try the data from the Law Dome ice core. No, it doesn’t “wander all over the place.” Neither does temperature for that matter.
The truth is, you’re impressed with how ingenious cointegration is — and well you should be. You’re also impressed with how smart you are, which is ill advised. And, you have elevated admiration of cointegration to worship. A previous commenter was right, that it’s your hammer and you love it so much you think everything is a nail.
By the way, your earlier statement that Foster & Rahmstorf “just try to straighten out the temperature curve” was both mistaken and insulting. It illustrates how your preconception biases your judgement. What that paper does is estimate the effect of El Nino, volcanic aerosols, and solar variations on global temperature. The only way to believe that they don’t affect temperature is to deny the laws of physics. When those factors are accounted for (not perfectly, but a fair approximation of them), lo and behold! — the temperature curve straightens out dramatically. Imagine that.
You could learn a lot here, but only if you do two things. First, abandon the notion that your understanding is better than everybody else’s — ’cause it ain’t. Second, accept the fact that you’ve got a lot to learn.