Most people who follow climate science are aware that one of the natural factors which affects global temperate is the el Niño Southern Oscillation (ENSO). It’s a mode of natural variation in the tropical eastern Pacific ocean which is indicated by sea surface temperature in that region, as well as patterns of atmospheric pressure, surface winds over the ocean, even precipitation over a much larger region. As such, ENSO — whatever its cause (and it’s been happening naturally for a long time) — has far-reaching affects on weather over a large area, and a notable impact on global temperature. When the ENSO is in its “high” state (called simply “el Niño“) our climate tends to be warmer, but when it’s in its “low” state (referred to as “la Niña“) earth tends to be cooler.
Computer simulations of earth’s climate system can actually reproduce the ENSO phenomenon, showing that it might be a straightforward consequence of the circulation of wind and ocean currents. But those computer models which do recreate ENSO do so in apparently random fashion, as though it were a stochastic (i.e. random) phenomenon. This too is, as far as we know, correct — ENSO is a natural mode of variation within earth’s climate system rather than a response to some forcing agent. And, the ENSO state of the world has proven unpredictable on anything but the shortest time scales, just as we expect from a stochastic phenomenon.
Because of its impact on global temperature, ENSO can cause large fluctuations of the global temperature trend on time scales of a decade or even longer. Computer models of global climate simulate this too, but again, they do so at random times which don’t necessarily match the timing of the ENSO pattern we see in the real world. One of the consequences is that if you run multiple computer simulations of earth’s climate, then average the results, the simulated ENSO events get scattered throughout time and end up being averaged out, so that the model average ends up looking like it doesn’t have a strong ENSO impact even though the individual model runs do.
While the ENSO phenomenon has a potent impact on global temperature, it’s one of those phenomena which doesn’t create a long-term trend. It can and does cause temperature to go up and down and up and down and down and up and down and up, so that short-term (a decade or even longer) trends are profoundly affected, but on longer timescales (30 years or more, which we usually associate with “climate”) the ups and down mostly cancel each other and the long-term trend impact is minimal. But the short-term effect confounds the global temperature changes which are due to other influences, in particular to climate forcing agents like the man-made increase in greenhouse gases in the atmosphere. If we could account for the influence of ENSO on global temperature, we could isolate the influence which is due to other factors and, we hope, better understand how those other factors affect earth’s climate.
There have been many attempts to do so. One approach is to estimate global temperature as a simple function of climate forcing and ENSO through a regression approach; perhaps the best-known example is Foster & Rahmstorf (2011), which found that when the impact of natural factors (volcanic eruptions, solar variations, and ENSO) is removed, the trend in global temperature has been remarkably steady since 1979 (when satellite observations of atmospheric temperature begin). Another strategy is to use a climate model — not a climate simulation like most computer models are, but a simple mathematical model — which includes the affect of ENSO. I did so using a 2-box energy balance model here and found again that there’s nothing mysterious or inexplicable about the most recent pattern of global temperature, it is still following the path we expect — which means that it is still showing the warming influence of man-made CO2 and other greenhouse gases.
The bottom line is that those who claim that global warming has “stopped” or even “paused” are deluding themselves. The phrase “global warming” refers to climate change, including temperature increase, which is caused by mankind, and that has continued unabated. In fact, if it weren’t for the continued warming due to human activity, natural variations (like ENSO) would have brought about a notable cooling over the last decade or so. But earth hasn’t cooled during that period, not even at the surface where we notice it most immediately, and that’s because the man-made component — global warming — has continued.
Those attempts have some severe limitations. For one thing, they’re linear models, in which the impacts of various factors (man-made greenhouse gases, ENSO, natural climate forcings) are additive, but while that is often a good approximation, the real world is nonlinear. For another, they’re based on global models which don’t capture the differences of the response of various regions, or subsystems, or their interactions (although there are some attempts to extend the scope of regression models, for example here and here). It’s reminiscent of the old joke about a physicist analyzing bovine behavior by starting with a simple model: “Assume a spherical cow.”
It might be very useful to run a computer model simulation in which the ENSO is constrained to follow its known historical behavior, so we can see how it might have affected actual history rather than a gereric “earth system.” That’s exactly what was done in a new paper by Kosaka and Xie (2013, Nature, doi:10.1038/nature12534) which investigates the impact of the tropical Pacific sea surface temperature on global temperature change. That’s the region whose variations are often referred to as the el Niño Southern Oscillation (ENSO).
The new research uses multiple runs of a coupled ocean-atmosphere computer model to simulate global temperature changes in response to climate forcing when the sea surface temperature (SST) in the el Niño region follows its historically observed values. They also estimate temperature change when those SST are not so constrained. In this way they hope to estimate the impact of actual el Niño/la Niña fluctuations on observed temperature.
They computed 10 runs each of three different scenarios. The “HIST” model runs use historical data for climate forcing, to estimate the average temperature change (and other variables) simply due to climate forcing. The “POGA-H” model also uses historical data for climate forcing, but constrains sea surface temperature in the tropical eastern Pacific (the ENSO region) to follow their historical values. This doesn’t constrain global temperature because this region covers only 8.2% of earth’s surface. Finally, the POGA-C runs constrain tropical east Pacific sea surface temperatures but do not follow historical data for climate forcing, instead holding climate forcing fixed at its 1990 values.
The HIST runs reveal that climate forcing causes reasonably steady warming since the 1970s and especially since about 1992, but that ENSO can still cause natural cooling for periods of a decade or more so that even though the man-made influence continues to cause warming, it is cancelled by ENSO cooling and results in a “hiatus” of global temperature increase:
In individual HIST realizations, hiatus events feature decadal La-Niña-like cooling in the tropical Pacific6 (Extended Data Fig. 2), …
In the 10 HIST model runs those kinds of events happen haphazardly, so that when they’re averaged the mean behavior shows steady recent warming:
However, When the model is run using historical data for SST in the ENSO region, the last decade’s la Niña dominance causes sufficient cooling to cancel out most of the warming due to climate forcing in the last 10 years:
If we take the difference between the POGA-H models (with ENSO constrained to follow historical data) and the HIST models, we see the estimated influence of ENSO on global temperature history:
This is, according to the new research, how ENSO has modified global temperature since 1950. The influence is clear: a pronounced recent ENSO-induced cooling which has cancelled the continued global warming due to man-made CO2, leading to the “hiatus” in the increase of global temperature.
We can compare the POGA-H models’ average to observed temperature history (according to HadCRUT4 as the authors use) to see how well the models reproduce what has actually happened:
The agreement is outstanding, including over the last decade and more, with correlation between the models and observations of 0.93. Using just the data since 1970, when — according to the authors — sea surface temperature data is more accurate, the correlation is an impressive 0.97. This is powerful evidence that the recent slowdown in global temperature increase is not a slowdown of “global warming,” i.e. man-made climate change, it’s simply partial cancellation of global warming by the natural fluctuations due to ENSO.
Some people have not just misunderstood this new research, they seem to have bent over backwards to misunderstand. Probably the most nonsensical example comes from Judith Curry. She looked at the POGA-C results (in which ENSO was constrained by historical data but climate forcing was held fixed):
Her first mistake — quite an embarrassing one really — was to assume that this was the influence of ENSO on global temperature history. This quite misses the point, that one of the strengths of the new approach is that it allows climate forcing and ENSO to interact in a nonlinear manner. The actual estimate of the influence of ENSO, according to the new research, is shown in the graph labelled “POGA-H minus HIST.”
But her bigger mistake, which is so embarrassing that, in my opinion, she should actually admit how wrong she was and apologize, is cherry-picking the lowest value of the POGA-C average and its 2nd-highest value and calling that the influence of ENSO. Yes, folks, as hard as it may be to believe, Judith Curry actually took this as the estimated influence of ENSO on recent global temperature:
On that basis, she estimate the ENSO influence to be 0.4 degr.C, and the net global warming to be 0.68 deg.C, then declared that natural variation was responsible for more than half of recent global warming.
As the graph labelled “POGA-H minus HIST” shows, the influence of natural variation, at least that part of it from ENSO, has been cooling, not warming, and if we want to assign a percentage we should say that natural variation has been responsible for about negative 25% of global warming. Not only did Judith Curry execute one of the most blatant, most obvious, and most ludicrous examples of cherry-picking, she couldn’t even get the sign of the influence right. That’s what I’ve come to expect from her.
Open Mind 
The obvious question, then, is why the change in behaviour of the ENSO since about 2000? Is it just the way the randomness has come out or is there a higher-level influence (PDO or whatever)? Are there previous long-term pattens in the ENSO (runs of la Niña or whatever)? E.g., could it account for the 1940s to 1970s cooling or does that still get put down to aerosols? Earlier?
I think this has a strong bearing on how commentary on the current hiatus should go. If there’s a significant probability of a 30 year run of la Niña it’d be silly to make predictions on the assumption things could flip back in the next year or two. Also, it’d be horrible as there’d be even more trouble stored up (in the form of deep ocean heat) while undermining motivation to deal with the matter.
Has there been a change in behaviour since 2000? I have heard that since 1998, when the Interdecadal Pacific Oscillation went from positive to negative, la Nina has dominated over el Nino. I don’t claim to understand the details. Maybe someone could enlighten us.
[Response: I have heard it suggested that global warming itself might affect the ENSO. But the time since 2000 isn’t really long enough to confirm a genuine change in behavior.]
I was sure I’d read ‘since 1998’ for negative IPO but trying to find confirmation I found Rob Painting referring to post-2000. At skepticalscience.com he said –
“The Interdecadal Pacific Oscillation (Power [1999]) is an index for the mean state of the north and south Pacific Oceans. During the positive phase, El Niño is the dominant global weather pattern, and during the negative phase, La Niña is dominant. During the late 1990’s the positive IPO phase weakened considerably and has been in the negative phase since the year 2000. In other words, La Niña been the dominant pattern
of late. It is therefore not surprising that global surface temperatures during the 2000’s have warmed less than previous decades (1977-2000) – when the IPO was in a positive (El Niño-dominant) state.”
I don’t know how clear that correlation between IPO and dominance of one ENSO state over another is shown historically.
Tamino, I would be interested in what you think of what Rob Painting had to say about IPO and ENSO ( http://www.skepticalscience.com/A-Looming-Climate-Shift-Will-Ocean-Heat-Come-Back-to-Haunt-us.html ) It does seem like he is saying that post-2000 IS qualitively different to the period preceding it. There is no suggestion of it being anything abnormal.
[Response: I think it’s fascinating. I don’t have as much confidence in the influence of IPO as others, but time will tell. We live in exciting times regarding climate research — but dangerous times regarding climate.]
I’ve a CW2011 based chart and would appreciate a very quick second opinion?
It’s interesting that the 1997-98 El Nino doesn’t stand out in the “POGA-H minus HIST” plot. Does this imply that the exceptional warming in 1998 wasn’t due to an exceptional El Nino after nonlinear interactions are considered?
Also, here’s an archived copy of Dr. Curry’s remarks.
Perhaps the 1998 surface temperature peak resulted from the persistently positive el Nino conditions leading up to 1998. The fit between POGA-H and the observed record is very striking (visually and, apparently, when analyzed as well)– and it seems to capture the 1998 peak in particular…
If that was the case, wouldn’t we have gone back to temperatures as they were before the peak, instead of having similar temps again in 2005 and more recently? The decadal averages do not support your hypothesis.
Philippe– I’m not discounting the underlying (and ongoing and increasing) forcing at all. The only point was to say that the link between 1998’s peak and el Nino isn’t necessarily weakened by the visual appearance of the POGA-H minus HIST plot as DS above suggested…
Maybe the answer to my question is obvious to an expert.
How do exactly do Kosaka and Xie fix their sea surface temperatures? The paper says that they adjust the sensible heat flux, which as I understand it is the energy transferred by (convection and) conduction from the sea surface to the atmosphere. That sounds OK.
My question is what they do with this flux? When the SST must be cooler than the models would otherwise show is the heat from the sensible flux ‘disappeared’ or is it retained in the atmosphere? Or is something else happening?
I guess that if the flux is ‘disappeared’ that would suggest that the true process maybe something like storage of heat in the ocean. If the heat is retained in the atmosphere I’m surprised there is such a strong cooling effect.
I’ve been wondering that too. Cannot access the paper unfortunately.
My suspicion is, that in the model, the solution process for each epoch is reformulated mathematically as minimizing some norm. Then, you can add the square sum of differences model temps vs. observed temps in the Eastern tropical Pacific to that norm to be minimized. My guess.
This should work correctly as we know that those observed temperatures are compatible (plus/minus all kinds of uncertainties) with the physics embodied in the GCM model. I.e., the expected values of those differences are zero.
No, it’s much simpler. I now got access to the paper, and it’s just as you say.
I would assume that all that happens is that the transport of heat is changed in the model: if surface air temps in the model are too high compared to observations, more heat is made to go down into the ocean, and vice versa. But conservation laws are respected.
It is not clear to me that either (a) conservation laws are respected or (b) that heat goes down into the deep ocean. Possibly the answers to these questions, and whether they matter, would be obvious to an expert but it doesn’t seem clear from the paper.
What they say is:
‘deep tropical eastern Pacific SST was restored to the model climatology plus historical anomaly by overriding the surface sensible heat flux to ocean’
The word ‘deep’ is a bit distracting, I take it to refer to deep in the tropics not to deep below the ocean surface. What they are referring to here are sea surface temperatures (SST), and what I take them to be modifying is the flux between the atmosphere and the sea surface (is that right?).
From a naive point of view I would expect that if they conserve energy then to cool the SST with this method they would have to warm the atmosphere, which is why I’m surprised this results in overall cooling (and in that case it would seem they have an accurate simulation where heat is not being buried in the oceans).
It seems to me most likely they do not conserve energy, but if anyone knows the answer please let us know.
I think so.
Yes, good point. I wonder if the direction of their F is right in the equation they give. I would definitely think (counter to your intuition) that cooling SST would require cooling the atmosphere above, as SST and SAT (surface air temperature) are tightly coupled. I.e., a downward heat flux.
Actually I think it is correct.
I think what we are missing here is that the whole purpose of the POGA mechanism is to bring the model ENSO in synchrony with the real-world ENSO. After synchrony is achieved, the differences T’ – T’* will be very small and varying around zero, as will be F in the area.This in no way precludes a large, global downward flux into the oceans due to the GHG forcing imbalance.
Bugger… I couldn’t resist a quick Google to see what she’d posted and now my head hurts. Damn.
Hi, I remember the joke as “Assume a spherical cow with a homogenous mild distribution.” :-)
I thought Dr. Curry was supposed to be one of the few “credible” skeptics (as opposed to flat out deniers of the existence of AGW). Skimming the 440 comments present on her post right now, it has significant similarities to the threads on WUWT. So, WUWCurry? What’s the chance you (Tamino) will actually have an open exchange with her about your two analyses?
[Response: If she admits that her “analysis” is flat-out ludicrous, it might be possible. I’m not holding my breath.]
I know cherry picking is a no no, but…
21st Century to date.
From 2000 to the end of El Nino conditions in the spring of 2010, despite a lot of La Nina/La Nina leaning conditions during that period, there was fairly pronounced warming – red trend line. The purple part of the graph includes the 2011 La Nina, which I have read was the 2nd strongest in the record.
In the brown part of the graph GMT is recovering. This despite the conditions being mostly either La Nina or ENSO neutral conditions on the La Nina side of side of neutral.
It looks to me like the pause is pretty dependent upon one large La Nina. If that’s right it would seem the pause will fade if it is not sustained by additional episodes of bit just La Nina, but very strong La Nina.
Embarrassing… milk distribution of course.
The fit of Kosaka and Xies POGA-H simulation is so stunningly good, that I would want to wait for another group to reproduce it, before believing it. I mean the precision of the fit. The general tendency is pretty plausible.
typo: sb “not just La Nina”, not “bit just La Nina.”
I’m puzzled as to why for 1996, POGA-H lies below HIST in the POGA-H vs HIST graph, but above zero in the POGA-H minus HIST graph?
[Response: Because I made a mistake, plotting HIST vs HadCRUT4 when I meant to plot HIST vs POGA-H. It’s now fixed.]
Also, would it be correct to interpret POGA-C as the indirect effect on global temperatures of climate forcing in the Tropical East Pacific?
[Response: The POGA-C runs are with climate forcing held constant, and I wouldn’t call the impact of ENSO a climate “forcing.”]
Excellent explanation for the Pseudopause in global warming.
Tamino, thankyou for the response. I appear to have been unclear in my second question, for which I apologize. I will try to phrase it better now.
To start with, the change in temperature in the tropical east pacific (TEP) can be assumed to be the result of two components, ie, the normal ENSO variability plus a response to forcing. When comparing HIST and POGA-H, both models include the response to forcing in the TEP, so that any difference is attributable to the ENSO fluctuations.
We can imagine making a similar comparison between POGA-C and a suite of unforced model runs with temperatures unconstrained in the TEP. Because the plotted data are the mean of ten model runs (presumably), the completely unforced, unconstrained models will approximate to a flat line, Ergo the difference between that conjectured set of runs and POGA-C will approximate to POGA-C.
The difference between POGA-C and a flat line will then be the result of introducing historical ENSO fluctuations plus historical forcings to the TEP. As the ENSO component is known to be negative from approximately 1990 (as per OP), the distinctly positive trend in POGA-C from 1975 to 2000 must be primarily the consequence of the historical forcings in the TEP, whose influence on global temperatures is retained in POGA-C by constraining TEP temperatures to match historical values (including any influence of historical forcings on those values).
My question then is, does HIST-C by itself show the residual influence on world temperatures of historical forcings as applied to the TEP alone, or is some further manipulation required to extract that signal (assuming it can be extracted)?
I can *hardly* wait to see Bob Tisdale’s response to this…if he’d actually have the guts to address it, here. You can darn sure betcha ol’ bob “All warming is the fault of ENSO” Tisdale will be commenting over at Willard Watts and His Flying Monkey Brigade’s website..:)
I posted this question over on Judith Curry’s Climate Etc. blog and got trashed (along with Jim Hansen) as being “about a decade behind the game.” The reason I asked the question is that Hansen et. al. put in historical ENSO data back in 2011 and got a close match to observed global average temperatures. What I don’t understand is what is new about Kosaka and Xie’s results. This is an honest question; I believe I am simply missing something, and I am certainly not questioning the importance of their results. So here’s the question I asked, can anyone here answer it?
“How does the Kosaka and Xie paper differ from James Hansen, et. al. GISS Surface Temperature Analysis from 2011, which comes to almost the same conclusion? See “GISS Surface Temperature Analysis, Global Temperature in 2011, Trends, and Prospects” by James Hansen, Reto Ruedy, Makiko Sato, and Ken Lo, NASA Goddard Institute for Space Studies, January 18, 2012 at http://data.giss.nasa.gov/gistemp/2011/“
Oh, spherical cows.
I miss The Poorman. There is also a graph.
This is consistent with the heat going into the oceans. It won’t be pretty when it comes out again.
BTW, be wary of the spherical cow metaphor.
Lawrence Krauss in Fear of Physics shows that the assumption of a spherical cow can be quite useful (though not for behaviour analysis, more for meat or milk production).
The original joke has a University sending out an economist, a biologist and a physicist to lecture to some farmers. The economist wows them with agricultural economics, the biologist impresses them with the genetics of animal breeding, then the physicist walk to the blackboard, draws a circle and says “Assume a spherical cow”.
The joke is meant to illustrate the irrelevance of physics to everyday life, Karuss’ book is a defence against that view.
Pity the physicist wasn’t an atmospheric physicist!
A physicist would always start with a spherical cow. It makes perfect sense. You figure out how it works with spherical cows, and then look at refinements later.
Even better is the cylindrical Earth approximation from Geophysics….
Hell, take away the legs and a cow looking over its shoulder (from the right perspective) could pass as a reasonable sphere….
YMMV…..
Flakmeister, I can’t help noting that taking the legs away from a cow is how we get ground beef.
Actually the cylindrical-Earth approximation makes everybody happy: the flat-Earthers because Gaussian curvature vanishes, but also the non-nutters as mean curvature is positive…
As kxcd says, compromise theory
Reblogged this on uknowispeaksense.
An interesting paper, “Clustering of a positive random field as a law of Nature” by V. I. Klyatskin, will appear in the September issue of Theoretical and Mathematical Physics. I think this paper has some implications for considering the use of climate models. I quote some suggestive portions of this paper:
“We first state the main problem of the statistical analysis of stochastic dynamical systems as we understand it: based on a statistical analysis of these systems, to reveal their common features that are realized with probability one, i.e., for almost every realization of the relevant dynamical system.
“We say that such processes and phenomena occurring with probability one are coherent. This “statistical coherence” can be regarded as a kind of organization of a complicated dynamical system, and identifying its statistically stable characteristics is similar to the notion of coherence understood as self-organization of multicomponent systems that results from chaotic interactions of their elements (see, e.g., [1]).”
“Here, we restrict ourself to analyzing stochastic dynamical systems with random parametric excitation. Such systems occur in numerous domains of physics and can be described by both ordinary and partial differential equations. On one hand, the parametric excitation is then attended by an increase with time of all the conventional statistical characteristics of the problem solution, such as moments and correlation functions of any order. On the other hand, along with these, stochastic nonstationary phenomena such as mixing, localization, and clustering in the phase and the physical spaces can occur in particular realizations of random processes and fields.
“Clustering of a field is the occurrence of compact domains with large values of this field on the background of surrounding domains with relatively low values. Naturally, all information about clustering is lost in statistical averaging.”
I note that this paper is NOT about climate science. It is a theoretical analysis of properties of certain kinds of dynamical systems (climate models are examples of dynamical systems), and it establishes conditions under which “clustering” MUST occur almost certainly, in other words, conditions under which we should expect something like ENSO. This may also apply to other similar features that are lost in averaging an ensemble of model runs and (IMHO) might be kept in mind whenever discussing climate model “predictions.”
re “That’s what I’ve come to expect from her.”
What I’ve come to expect is acting as a platform for obviously wrong antiscientific posts deemed “interesting”, and commenting in a handwaving manner, usually on uncertainty.
For Curry to say anything actually falsifiable, or indeed to do any quantitative analysis whatever is very unusual.
I used to comment there occasionally, but the descent of her commentariat beyond the usual tedious denier memes into personal bullying verging on homophobic attacks was too much for me to stomach.
I’d be extremely surprised if you get any engagement from her whatsoever. Her approach is providing her a platform – addressing Congress, media interviews etc her science would never give her, and with no obvious downside. When shown to be wrong in the past, she’s simply ignored her detractors.
So, thank you for the insight into the paper. I hope she proves me wrong and engages with you on her interpretation of it.
1st four paragraphs: B-I-N-G-O
Judge Judy’s Zoo of Mythological Creatures.
Last sentence of last paragraph: IMHO, not going to happen. Ever.
All this sound and fury coming from Curry’s corner made me wonder what path her rate of citation in the literature has followed. I exported the data from Scopus and found a very interesting trajectory.
From 2007 onward her work is about as visible as it was when she first started in the 80s, which is not a good sign for a publishing scientist as it indicates senescence.
And yes… to date, she has had no citations of anything she’s authored in the 2013 scientific literature, as listed in Scopus.
She’s been bouncing around zero since she started here blog. Connection?
Using the 2-box model, I got an R² value of 0.93 over the GISS series (1881 to 2011). This takes account of anthropogenic influences plus solar irradiance, volcanic stratospheric aerosols and ENSO. It doesn’t leave much room for influences from the PDO, or galactic cosmic rays, or a larger-than-previously-realised solar forcing, or… you get the picture. It suggests that any other forcings, or unforced natural variability, must have a fairly minor impact on global temperature on decadal timescales. The only way I can see this being wrong is if (for example) the aerosol forcing is smaller than the NASA GISS forcing data tells us it is, and the effect of something else happens to be larger by an equal amount.
Curry is not misled. She is malicious. Understood that way, her actions become quite clear and easy to understand.
I have found a strong negative correlation between my “F” drought time series and Gross World Product. Unfortunately (for my thesis), Granger causality tests with a one-year lag show the direction running more strongly from dQ to F and not vice versa. I don’t understand that. Still no smoking gun for drought as a danger. I can’t even prove (statistically) that drought is bad for agriculture! Wish I knew what I was doing wrong.
Doesn’t sound as though you are doing anything wrong. If you are looking dispassionately at what the data tells you, then you are doing the most important thing right.
I am quite ready to (tentatively) hypothesize that Gross World Product indeed causes drought. Now you only need to establish the physically causal mechanism. I believe such does exist and is currently in action.
Does El Niño –cause– anything or is El Niño one of the aspects of a general oscillation of the climatic system? Correlation is not equal to causation. If El Niño is a cause, which is the cause of El Niño? I prefer to understand climate as a very long series of multiple frequencies non-linear positive and negative feedback oscillations of the coupled system of fluids that cover around 10 km below and 10 km over the average seal level of the Earth. If there is no cause of El Niño-La Niña, but it is an oscillation of the coupled equatorial Pacific air-ocean system, other oscillations are coupled with this one.
deFreitas and McLean have a new one out:
http://www.scirp.org/journal/PaperInformation.aspx?PaperID=27382
Notice the high quality of the publisher :-). The money quote:
“The approach used here avoids a focused statistical analysis of the data…”
That deFreitas and McLean paper is from January 2013, with (so far) a single citation in Energy and Environment. And published in one of the SCIRP journals, with as I understand it rather terrible impact factors.
A witless prank of a paper, predictably enough….
Yes, I forgot to mention the elided portion “because we got schooled last time we tried this…”
I note that on Wattsupia their incisive analysis of this DeFreitas & McLean paper consists of saying that it is a “paper that reaches a similar conclusion” to that of Kosaka & Xie. They do not elaborate but simply cut & paste various parts of the paper into their post with just one helpful comment. Apparently Figure 1 “is interesting.”
I wonder what that ‘similarity’ between the two papers could be. Use of the acronym “ENSO”? Both written in English? Both beyond Cap’n Watts comprehension?
Curry responds:
It’s interesting that within her post, Curry ignores the charge of cherry-picking, the transgression she was called on to “actually admit how wrong she was and apologize” for.
Still, she addresses the first mistake and says she was not wrong because of (1) non-linearity (the very same reason given in the post here for why she was wrong) and because (2) the model used is too sensitive to external forcing. Yet this appears not to be entirely conclusive as “all this is not easily untangled.”
And then Curry comes out fighting. Apparently, the argument in the post here (that ENSO is a cooling process) is “not convincing, particularly in context of … allowing for the PDO to be the pause cause since 2002,” a statement which is itself “not convincing” or indeed comprehensible. Perhaps this is because Curry’s analysis involves natural climate wobbles that work on “on multidecadal time scales,” phenomena that aren’t very easy to properly describe at the best of times. (Curry then links to a bit of unpublished wobblology that uses the “climate shifts” of 1910s and 2035 to assert that the shift of 1970s was not due to anthropogenic forcing. And then links to another paper that demonstrations of the use of Systems Theory in climate modelling. I assume the relevance of these two papers is in the obfuscating effect they provide within her post.)
Maybe Tamino will earn another C- from Curry!
Tamino,
Thanks for the analysis. It looks like Xie responded to Curry’s blog post on August 30 with the following (the link is on Curry’s post):
“1975 was a La Nina year, and 1998 followed the strongest El Nino in the instrumental record. My estimate indicates that the El Nino-La Nina difference accounts for 0.2-0.3 C difference of her 0.4 C in POGA-C. So for multi-decadal trend, PDO accounts for only 0.1-0.2 C for the longer period of 1950-2010. El Nino and La Nina are part of the short climate cycle of ENSO, averaged out over several decades. Our paper noted that the warm phase of the tropical Pacific Decadal Oscillation contributed to the fast warming during the 1970s-1990s.”
This clearly shows Xie also caught Curry cherry-picking the data points, but I’m curious as to how to square Xie’s statement (at least, as I read it) that “PDO accounts for only 0.1-0.2C [of warming] for the longer period of 1950-2010” with your statement that “natural variation has been responsible for about negative 25% of global warming.”
What am I missing?
In case people have missed another interesting analysis of this paper can be found on John Gammon’s blog:
http://blog.chron.com/climateabyss/2013/08/learning-from-the-hiatus/
I did the same type of quick analysis, and end up with slightly different trend lines. But over all, the conclusion is the same.
Aunt Judy “thinks” 1975 and 1998 were;
“Hi Marcel, interesting. You can pick different years than 1975 and 1998 (which were neutral relative to enso), …”
http://www.staatvanhetklimaat.nl/2013/08/30/xie-reacts-on-curry/
http://www.esrl.noaa.gov/psd/enso/mei/#data
But if 1975 were to start out in, or be in the middle of, a deep trough (which it does) and 1998 were to end in, or be in the middle of, a high crest (which it does), than Aunt Judy wins the Steve Goddard “I’m guilty of cherry picking” trophy for 2013.
An interesting tidbit… one can use Dr. Curry’s methodology and get the exact opposite answer she did, just by cherry-picking different years. Let’s look at roughly the same length of time but move the start/end to the more relevant time period when skeptics claim warming has “stopped” or “slowed” – the last 25 years.
POGA-C
1987: 0.11C
2012: -0.05C
This yields a ENSO/PDO contribution on global temperatures of ~0.16C in the negative (cooling) direction, according to Curry’s methodology. Using POGA-H as the global temperature dataset as Curry did, we see +0.2C change in global temperature from the 1987 point to the 2012 point (a trend line would be more accurate, but we’re following Curry’s methodology). To recap, that’s a -0.16C natural contribution to a +0.20C change in temperature, meaning that the human contribution was +0.36C.
So, using Dr. Curry’s methodology for the most-recent 25yr period, we’ve discovered that human activities are responsible for 180% (0.36/0.20) of the observed warming. She may want to rethink her analysis methodology.
If we read the POGA-H minus HIST graph, as marked out (by Tamino?) in red as significant, then El Nino dominated years (from 1950 to 1990?) produced a global temperature rise of a little less than + 0.05 degrees Celsius, while the so far much shorter La Nina dominated years (starting a little after 1990, roughly) produced a global cooling that now stands at – 0.2 degrees Celsius.
What might the large difference in those two numbers be telling us about the nature of ENSO? Since the ENSO surface area is a limited 8 % of the Earth’s area, that the waters in the Eastern Pacific themselves cool much more than they warm? That, since the atmosphere is strongly coupled to the Oceans, the changes in the speeds of the subtropical trade winds are far larger in an La Nina than in an El Nino? Trenberth would agree with the second suggestion. He wrote, “The cause of the shift is a particular change in winds, especially in the Pacific Ocean where the subtropical trade winds have become noticeably stronger, changing ocean currents and providing a mechanism for heat to be carried down into the ocean. This is associated with weather patterns in the Pacific, which are in turn related to the La Niña phase of the El Niño phenomenon.” (see: http://theconversation.com/global-warming-is-here-to-stay-whichever-way-you-look-at-it-14532). The “shift” refers tp an extra (30%) dumping of heat in the deep Ocean, below 700 meters.
We have a harasser. Some moron from a commonwealth country (because he called me an “arse” rather than an “ass”) reprinted a paragraph I posted above and then added the insult. It was a no-reply email, too, probably part of his boss’s business email. I just reported it as spam. Let me know if anyone else gets emails like that. Not that it matters much, but I thought I should mention it, in case he escalates.
meher engineer wrote:
“What might the large difference in those two numbers be telling us about the nature of ENSO? Since the ENSO surface area is a limited 8 % of the Earth’s area, that the waters in the Eastern Pacific themselves cool much more than they warm?”
That might be a slight misinterpretation of the single downturn in Tamino’s smoothed red curve. It doesn’t show an asymmetry in the respective surface cooling/warming potential of La Nina/El Nino events, respectively. What the downturn shows is the cooling effect that results from a shift from an extended El Nino dominated period to an extended La Nina dominated period. What the prior flat line tells isn’t that El Nino events don’t warm the surface as much as La Nina events cool it (since it smooths over the effect of individual El Nino events) but, rather, that over this whole period, prior to 2000, there wasn’t any shift from a La Nina dominated period to an El Nino dominated one. Hence, the ENSO cycle didn’t contribute at all to the long term trend in real surface temperatures over the period leading to 2000. The ENSO cycle was El Nino dominated all along. It may have warmed from a previous period not covered in the graph.
Also note that taking POGA-H minus HIST to be representative of the evolving influence of internal variability (ENSO,PDO,IPO,HBO,ELO…) assumes that the forcing in HIST is a match, at least in terms of its temporal shape, for the forcing which actually occurred and resulted in the equatorial Pacific SST observations used in POGA-H.
In particular, aerosol emissions in the Pacific region have been increasing dramatically since the early-1990s with highly uncertain net impact on forcing. It’s plausible the HIST coupled simulations underestimate the cooling influence of aerosols in the Pacific over the past 20 years and that would explain some of the difference alongside what appears to be a clear signal of internal variability.
Let me add that it is possible to blind oneself to those facts (as Judith Curry seemingly does) through seeing POGA-C, instead of POGA-H minus HIST, as a representation of ENSO’s independent effect on global surface temperatures. It indeed may look like ENSO contributed a significant rise prior to 1998 and a small drop after that. But that’s an illusion since, although the external forcing has been held constant in POGA-C, the actual effect it likely has had historical tropical Pacific temperature trends hasn’t been removed. Had it been somehow removed, then POGA-C would tell a similar story as POGA-H minus HIST.
A question – why is there no symmetry between the cooling effect of La Nina after ~1995 or so, and the warming effects of El Nino before? If natural variability is a sort of sine wave effect, and just moves the energy around, why did La Nina have a greater cooling effect in the recent period after 1990 than El Nino had a warming effect previous to that?
The recent period has a ~ -0.2C effect due to a negative ENSO, and the earlier one a ~ +0.05C effect due to a positive ENSO before 1990. My figures may be ropey but I hope the question is clear.
I have been asked this question, and did not have a ready answer. I can see that “the data are what the data are”.
I am not a scientist, but I would not expect the atmospheric temperature to increase as much over El Nino as it would decrease over La Nina. When I lived with my parents in New Mexico from 1956 to 1962, I learned that we cooled our house in the summer by adding heat energy brought in from outside, i.e., I figured out the difference between heat energy and temperature by puzzling over the working of the evaporative air conditioner on the roof of our house. (See http://www.youtube.com/watch?v=6ooAAcsbf_0 — 1:48.)
When I now consider a thought experiment with two boxes A and B and I put cool air and warm water in box A (El Nino) and warm air and cool water in box B (La Nina), I would expect the increase in the air temperature at equilibrium in box A to be less than the decrease in air temperature in box B BECAUSE the humidity of the air in box A will be higher than the humidity of the air in box B.
Having lived in Anchorage, Alaska, for 16 years, I have had personal experiences of the significant difference between the adiabatic temperature change with altitude of moist air and dry air. A Chinook wind coming down from the Chugach mountains is quite interesting: “As moist winds from the Pacific (also called Chinooks) are forced to rise over the mountains, the moisture in the air is condensed and falls out as precipitation, while the air cools at the moist adiabatic rate of 5°C/1000 m (3.5°F/1000 ft). The dried air then descends on the leeward side of the mountains, warming at the dry adiabatic rate of 10°C/1000m (5.5°F/1000 ft).” (Quoted from http://en.wikipedia.org/wiki/Chinook_wind) In other words, the specific heat capacity of moist air is greater than that of dry air.
Pierre-Normand,
I think you have been trying to answer my question (great anticipation!) – maybe you could expand on what you have written.
What I was suggesting was, first, that for ENSO to be persistently (or predominantly) positive (or negative) over a long period wouldn’t create a temperature trend over that period. Even an initial step change in external forcing can’t do that (except for a merely transient response). It’s a sustained change in forcing that creates a sustained temperature trend.
Furthermore, what the ‘POGA-H minus HIST’ graph suggests is that, were it not for the actual external changes in forcing, ENSO would have contributed negligibly to the surface temperature trend from 1950 to 1990 (or even 1950 to 2000). It just so happens that the secular trend in the actual external forcing might be strong enough to fully account for the increase in (smoothed) tropical Pacific surface temperature. Tropical pacific surface waters easily warm just as much in model-runs that apply historical external forcing values and let the simulated ENSO cycle do its random stuff. HIST is an average of 10 such runs. When removed from POGA-H, the remainder is the independent effect of the actual ENSO evolution on the global surface temperature trend, and this effect just happens to be negligible before 1990, and non-negligible thereafter.
Finally, it’s unsurprising that ENSO noise shows up more readily over shorter periods (1997 until now) than over longer periods (1950 to 1998). The inclusion of the very warm 1998 El Nino year at the end (or start) of either of those two periods only has a significant effect on the trend over the shorter period.
Tamino- please don’t publish this if you think I’m wrong with this explanation…I’m not entirely happy with it, and if you wanted to give some pointers that would be great. But my objective is to show that basic thermodynamics and heat transfer considerations are all that are required to lead to the expectations the La Nina will cool more than El Nino warms.
Let me try give another answer to the question of La Nina Cooling more than El Nino warms.
Let’s start with an example: If I take a red hot poker and stick it in a swimming pool, we all expect it to cool the poker very rapidly, while the swimming pool warms up a little bit. If you take a cold poker and stick it in that swimming pool, it will never, ever warm back up to red hot temperatures. This is a demonstration of the thermodynamics of the situation, the effect of entropy. (In other words, this is an example of the second law of thermodynamics). Well, what about heating the air? If I leave the red hot poke sit outside, eventually it will cool to ambient temperature, but much more slowly than if I immersed it in the swimming pool. What about the pool heating the air, after we stick the red-hot poker into it? Assuming the pool was at equilibrium with the air before we stuck it with the red-hot poker, it will eventually cool to ambient temperature, and the air will warm up. But this will happen much more slowly.
Now let’s apply this to ENSO. The red-hot poker here is the sun. It’s a common mistake that people think the sun heats the air which heats the ocean and the land, but of course the air is largely transparent to the UV/VIS spectrum (except for the ozone blocking most of the harmful UV…and that does heat that part of the atmosphere). So sunlight passed through the atmosphere, hits the water and warms it, and the warmed water in turn heats the air. (same on land!) We know that 93% or so of the radiation imbalance from global warming is going into the oceans anyhow, so it should be obvious from that the ocean is largely a cooling source. (Someone somewhere I saw recently, maybe in this thread estimated that if all the excess heat in the ocean were distributed to the lower atmosphere instead the global mean surface temperature would be 36 C warmer. Ouch!
If the warm water heated by the sun is driven by the wind into the deeper layers, and also bringing colder deep waters to the surface, the surface stays cool, the heat is transferred down, and La Nina works its cooling magic on the globe. When the turnover slows down, the usual heat uptake by the ocean resumes, which is only a bit less. The rate that heat can be transferred into the ocean is governed by the absorption of light from the sun (the red-hot poker). But the rate at which the ocean can transfer heat to the atmosphere is far slower, governed by the difference in air and water temperature (which at the surface are often not much different), and combined convective and conductive heat transfer coefficients of water to air. (There’s an equation for this). The temperature differential of water and air is controlled by ocean currents and circulation and wind. Given the ocean’s huge thermal mass, it takes a very long time to warm it up. So the ocean can soak up an enormous amount of heat, barely change temperature, and thus barely increase the rate of transferring heat to the atmosphere. La Nina can soak up more than El Nino can give back. If fact it’s probably a better idea to think of La Nina simply being more efficient heat uptake by the ocean, and El Nino being less efficient heat uptake, with a consequence of less or more heat being available to transfer to the atmosphere, than to think of El Nino as warming and La Nina as cooling.
So simply from basic thermodynamics and heat transfer considerations when you’re dealing with a radiative imbalance El Nino is likely to heat the earth up as much as La Nina cools it. You don’t need fancy models to figure this out. But this does show why “common sense” expectations don’t work, and you need to know something about science to understand this. Now if you can imagine conditions where the ocean stops taking up 93% of the heat, and that drops to 85%, we’re playing an entirely different game. But that’s for another time.
One thing: your formulation of La Nina ‘cooling’ the Earth must be interpreted to refer specifically to surface temperature to be true.
Consider, as you say, that “If the warm water heated by the sun is driven by the wind into the deeper layers, and also bringing colder deep waters to the surface, the surface stays cool, the heat is transferred down…” If we agree that oceanic warming (especially at depth) means more heat in the overall system without a corresponding increase in its radiative efficacy, then from a systems point of view, La Nina warms, not cools. Contrarily, El Ninos have a *cooling* effect on the system overall, since radiative efficacy does increase. And if memory serves, that’s just what satellite observations of OLR show.
opps…that’s an isn’t in the last paragraph 3rd line…sorry. Dave
Variability of El Niño/Southern Oscillation activity at millennial timescales during the Holocene epoch
http://www.nature.com/nature/journal/v420/n6912/full/nature01194.html
At short time intervals (decadal) there is substantial variability over much longer time intervals. Despite the authors’ claim of a statistically significant 2000 year quasiperiod, I assert this is just more pink noise.
Here is John N-G’s analysis of temperatures since 1970:
http://blog.chron.com/climateabyss/2012/04/about-the-lack-of-warming/
I think this is particularly clean.
Please tell me that Georgia Institute of Technology has a clause that can be invoked if an employee is shown to bring the institution into disrepute, or if they are guilty of scientific misconduct.
Judith can try and play the “victim” card, she can try dodging, ducking and diving, but her repeated cherry picking and misrepresentation of data is paramount to academic misconduct and academic dishonesty. That fact, that reality, cannot be denied or obfuscated or disappeared.
Curry is no more interested than learning the truth than is Monckton. All she is interested is herself and garnering attention. Pretty pathetic IMHO.
Once tenure is granted almost nothing can dislodge it. If the institution of higher education can prove falsifying data for a paper in a peer reviewed journal that might do it.
So far Judith Curry is solely guilty of ‘going emerita’, as the current phrase has it.
Judith Curry is using ENSO data as a proxy for PDO, and arguing that PDO is potentially a signficiant forcing for global temperatures. She is not interested in the same question that Xie asked, but in the IPCC analysis that AGW has contributed to >50% of global warming since 1950. Her recent post moderates her initial assertions, but she still doesn’t seem to have answered various criticisms.
Tamino, you wrote a long time ago a post on PDO, remarking on the connection between ENSO and PDO, and promising an imminent follow-up, which was interrupted by posts on Australian drought. I was unable to find one.
As the ‘sekptics’ so frequently argue that PDO is largely responsible for the global temperature changes over the last ~100 years, I wonder if you did a follow up that looked at this claim, or if you might do an update in the near future.
Since the PDO data is available, why the heck is she doing that? I would hope she was more competent than that!
She seems to conflate them:
See what she did there?
Not having full access to the Xie paper, I’m guessing that they dealt with ENSO, not the PDO, but because the conversation is about Pacific temperatures, Curry is drawing them together, for which there is some (less simplistic) precdedence in the literature, to support the proposition that the PDO has a strong influence on global temperatures. If PDO, like ENSO, influences temperatures, but on multi-decadal (20 – 30 years) timescales and with similar impact, then she can question the IPCC statement of >50% anthro contribution to global warming prior to 1950.
And so I get curious. Does PDO, like AMO, lag global temps, suggesting that the oscillations carry residual global temperature fluctuations on decadal timescales? Or is the PDO index discrete (it is detrended from long-term warming)? I also hark back to a more general question in my mind – if ENSO can have a strong impact on global temps, could not this also be the case for other ocean/atmosphere quasi-periodic systems? I often read that these systems simply “move heat around,” but that seems to be short of the mark when there are papers that both sides take seriously that look at the contribution of these systems to global surface temps over 15+ years (like Xie). In the blogosphere, we are happy to examine ENSO to explain a haiatus, but seem to downplay the effects of other, more long-term systems.
AFAICT, there is sufficient uncertainty of the impact of PDO on a global scale that skeptics can exploit to downplay AGW. That system seems to be their strongest card – hence my questions. I’ve read the rebuttals on PDO (averages out over the long-term, shows opposite sign since 1975/79, etc), but they don’t seem sophisticated enough to completely discredit theses like Curry’s, notwithstanding the woeful flaws in her first post on it that inspired the article above.
Aunt Judy never met an analysis she couldn’t misunderstand!
Apologies for posting on this thread, but the previous one is now closed to comments.
Those folk curious about the movement of land relative to sea level around different parts of Australia may be interested in this paper:
http://gji.oxfordjournals.org/content/early/2013/04/29/gji.ggt131.abstract
Correct me if I’m wrong, but I think it’s fair to say that even if we went suddenly into a permanent La Nina, it would not make the subsequent trend less steep, just drop its starting point a bit. Over longer periods it can;t have a significant effect on the trend no matter how non-random it turned out to be.
I think that’s probably wrong: if La Niña puts more heat into the deep ocean, then it’s conceivable that a long sequence of La Niña events could depress the warming trend for the duration of the sequence. There’s an awful lot of cold water in the deep ocean…
On the other hand, a long sequence of La Niñas could produce some very large regional excursions in temperature. IIRC just such a sequence has been proposed as an explanation for the Medieval Climate Anomaly (by Mike Mann and others).
Correct me if I’m wrong, but El Nino doesn’t “warm” the atmosphere, because there is still a net transfer of heat from the air to the ocean.
In El Nino years, the ocean merely absorbs less heat (from the air) than it does in normal or La Nina years ?
I don’t have the numbers, so feel free to correct me.
El Nino takes the warm water piled up in the Pacific Warm Pool and spreads it out for the entire equatorial Pacific. This also shuts off the cold Humboldt current around Peru.
@Dave123
You could try sending your comment to Science of Doom SOD who specialise in such arguments, but I warn you that they prefer equations to words.
If you must restrict yourself to words you have to be very complete and precise. As an example your conclusion, stated near the start, is that “la Nina cools more than El Nino warms” is vague. Presumably you mean a patch of water on the ocean cooled by a value D degs.C would reduce the surface temperature by more than an equal and opposite patch of water warmed by D Degs.C would warm it *. You should state the second law of thermodymamics in words , and show how your version of it can be used to deduce something very precisely described to advance your argument.
————–
*. That conclusion is something about which I have an opinion. The relevant laws such as Planck’s law , Clausius Clapeyron etc. can all be linearised over the small temperature changes involved. That would mean that a cooling is the same as a warming but with a reversed sign.
Thanks all for your comments. Of course I didn’t do equations here. I have no idea how to post even the simple heat transfer equation and have it look proper.
-Deconvoluter- I don’t mean what you said, at least as how I think you framed it. Your patch can’t include the x1000 meters of ocean underneath. And we’re not talking at equilibrium either, where microscopic reversibility can apply. Essentially the entire ocean’s average temperature is below that of the global mean average surface temperature, and thus we do not have a true thermodynamic equilibrium, but only the appearance of one because the rates of heat transfer are so slow. I’m thinking out loud here, but if I understand PAGES2k results correctly our now interrupted descent out of the last interglacial, heading for the next glacial necessarily means the oceans get colder, and that they in turn are the buffer, slowing the descent.
Anyhow, what I was attempting was a non-modeling, simple means of making the case that the intuitive appeal of symmetry in ENSO isn’t a scientific expectation. Modeling has an enormous virtue, (at least to me) because you can break down the system into pieces, and simply deal in a mechanistic fashion with heat and mass transfer for each of your n compartments. The risk is that your model wanders completely away from real physics through some buried error, but the benefit is that if you can isolate the main forces in the system and how they affect it, then you can later put together something that is a plain English narrative of the situation. Here I’m expressing a great deal of sympathy for a recent comment by Gavin Schmidt over on RealClimate about models: “Ah. Being “correct” in my definition is very different from being “useful”. I’m a strong proponent of the latter despite the absence of the former. “
> Dave123 …
> Tamino- please don’t publish this if you think I’m wrong …
Don’t rely on that.
Tamino, you state that ENSO can be considered as a Random phenomenon. I wonder if it can actually better described as Chaotic with coupling of the 4 major indices, for example in the Tsonis et al paper 2007. Your opinion ?
[Response: I expect it’s more likely to be chaotic than genuinely random … but then, it’s an open question whether there’s anything at all in physics that’s truly random besides quantum phenomena. Still, we can treat it as random (all models are wrong, but some are very useful). As for Tsonis et al., I don’t find their ideas very persuasive at all.]
An ARMA(2,1) statistical model describes ENSO fairly well.
@_Arthur: If by ‘warm’ you mean ‘increase the temperature of’, then el Nino does ‘warm’ the atmosphere (by reducing net heat transfer from the atmosphere to the ocean surface).
Actually, the ocean does warm the atmosphere–solar insolation is absorbed by the ocean and heat is then transferred to the atmosphere. Very little solar insolation directly heats the atmosphere. There is an asymmetry to the heat transfer as well because much of the heat is transferred by evaporation (latent heat), and the amount of evaporation goes up strongly with water temperature. So, La Nina reduces the latent heat transfer, while El Nino greatly increases it.
RE Old salt. Your comment its correct for the sun’s radiation heat but not for the infra red radiation from the Earth’s surface that GHG’s, whether natural or man made, absorb the absorption heat the atmosphere which re radiates up and down. The total downward IR radiation is powerful, it amounts to around 300 watts per square meter on average. Please see http://scienceofdoom.com/2010/07/24/the-amazing-case-of-back-radiation-part-two/ for a clear account. the point made about latent heat is correct of course.
Hey, just a note. Back in 2012, I asked if the slowdown was related to the cool Pacific, and mistakenly called it the PDO negative state (here: https://tamino.wordpress.com/2012/12/13/global-temperature-update/
I did a little reading and it appears that it’s not the PDO state, it’s the QDO (quasi-decadal oscillation) state, that is making it cool. So I think maybe I had the right idea but the wrong oscillation.
Anyway, I wrote a post praising your great article here: http://tugpullpushstop.blogspot.com/2013/09/in-case-you-didnt-understand-cause-of.html
Thanks.
This is nearly completely off-topic, but I’m going to post anyway, given that John Abraham has recently challenged His Lordship to a bet. I have a bloke on the hook at The Week who wants to bet me $5000 US (to charity of choice) that the 60-month centered average for 2015 for GISS L-OTI won’t be above the same for 2005. I have not yet thrown in the volcanic exception, but I imagine he’ll accept it. I am going to knock him down to $10, because I’m in no position to be throwing about anything in three figures, much less four. However, I thought I’d throw the opportunity to anyone and everyone before I did so.
The conversation is here: http://theweek.com/article/index/248646/has-global-warming-hit-a-plateau#comment-1030084141
You’ll note that the dude is clueless (“Since surface temperature ncreased significantly from 1976 to 1998, one would expect the deep ocean to warm too, not because it’s absorbing additional heat but because of the that increase in surface temperature. Furthermore, ocean temperature change is known to be cyclical (see, e.g: https://en.wikipedia.org/wiki/…. In sum, the ocean heat absorption theory is, to be kind, questionable. “)
Hey, I kind of brought it back on topic. I tried to pry open his intellect, but to no avail.
I understand why ENSO and PDO aren’t considered climate forcings, but if these phenomena are shown to be affected by AGW shouldn’t these wind and current changes be practically treated as short-term (centuries), non-persistent climate feedbacks (persistent while the deep oceans can effectively sequester the heat added by true forcings)? Similar to the DO events during the Pleistocene.