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Global warming and the El Niño Southern Oscillation

What the science says...

The El Nino Southern Oscillation shows close correlation to global temperatures over the short term. However, it is unable to explain the long term warming trend over the past few decades.

Climate Myth...

It's El Niño

"Three Australasian researchers have shown that natural forces are the dominant influence on climate, in a study just published in the highly-regarded Journal of Geophysical Research. According to this study little or none of the late 20th century global warming and cooling can be attributed to human activity. The close relationship between ENSO and global temperature, as described in the paper, leaves little room for any warming driven by human carbon dioxide emissions. The available data indicate that future global temperatures will continue to change primarily in response to ENSO cycling, volcanic activity and solar changes." (Climate Depot)

The paper claiming a link between global warming and the El Niño Southern Oscillation (ENSO)  is Influence of the Southern Oscillation on tropospheric temperature (McLean 2009). What does the paper find? According to one of it's authors, Bob Carter,

"The close relationship between ENSO and global temperature, as described in the paper, leaves little room for any warming driven by human carbon dioxide emissions."

In other words, they claim that any global warming over the past few decades can be explained by El Niño activity.

How do they arrive at this conclusion? They begin by comparing satellite measurements of tropospheric temperature to El Niño activity. Figure 1 plots a 12 month running average of Global Tropospheric Temperature Anomaly (GTTA, the light grey line) and the Southern Oscillation Index (SOI, the black line).


Figure 1: Twelve-month running means of SOI (dark line) and MSU GTTA (light line) for the period 1980 to 2006 with major periods of volcanic activity indicated (McLean 2009).

The Southern Oscillation Index shows no long term trend (hence the term Oscillation) while the temperature record shows a long term warming trend. Consequently, they find only a weak correlation between temperature and SOI. Next, they compare derivative values of SOI and GTTA. This is done by subtracting the 12 month running average from the same average 1 year later. They do this to "remove the noise" from the data. They fail to mention it also removes any linear trend, which is obvious from just a few steps of basic arithmetic. It is also visually apparent when comparing the SOI derivative to the GTTA derivative in Figure 2:


Figure 2: Derivatives of SOI (dark line) and MSU GTTA (light line) for the period 1981–2007 after removing periods of volcanic influence (McLean 2009).

The linear warming trend has been removed from the temperature record, resulting in a close correlation between the filtered temperature and SOI. The implications from this analysis should be readily apparent. El Niño has a strong short term effect on global temperature but cannot explain the long term trend. In fact, this is a point made repeatedly on this website (eg - here and here).

This view is confirmed in other analyses. An examination of the temperature record from 1880 to 2007 finds internal variability such as El Nino has relatively small impact on the long term trend (Hoerling 2008). Instead, they find long term trends in sea surface temperatures are driven predominantly by the planet's energy imbalance.

There have been various attempts to filter out the ENSO signal from the temperature record. We've examined one such paper by Fawcett 2007 when addressing the global warming stopped in 1998 argument. Similarly, Thompson 2008 filters out the ENSO signal from the temperature record. What remains is a warming trend with less variability:


Figure 3: Surface air temperature records with ENSO signal removed. HadCRUT corrections by Thompson 2008, GISTEMP corrections by Real Climate.

Foster and Rahmstorf (2011) used a multiple linear regression approach to filter out the effects of volcanic and solar activity and ENSO.  They found that ENSO, as measured through the the Multivariate ENSO Index (MEI), had a slight cooling effect of about -0.014 to -0.023°C per decade in the surface and lower troposphere temperatures, respectively from 1979 through 2010 (Table 1, Figure 4).  This corresponds to 0.045 to 0.074°C cooling from ENSO since 1979, respectively.  The results are essentially unchanged when using SOI as opposed to MEI.

Table 1: Trends in  °C/decade of the signal components due to MEI, AOD and TSI in the regression of global temperature, for each of the five temperature records from 1979 to 2010.

table 3

Figure 7

Figure 4: Influence of exogenous factors on global temperature for GISS (blue) and RSS data (red). (a) MEI; (b) AOD; (c) TSI.

Like Foster and Rahmstorf, Lean and Rind (2008) performed a multiple linear regression on the temperature data, and found that although ENSO is responsible for approximately 12% of the observed global warming from 1955 to 2005, it actually had a small net cooling effect from 1979 to 2005.  Overall, from 1889 to 2005, ENSO can only explain approximately 2.3% of the observed global warming.

Ultimately, all the data analysis shouldn't distract us from the physical reality of what is happening to our climate. Over the past 4 decades, oceans all over the globe have been accumulating heat (Levitus 2008; Nuccitelli et al. 2012, Figure 5). The El Niño Southern Oscillation is an internal phenomenon where heat is exchanged between the atmosphere and ocean and cannot explain an overall buildup of global ocean heat. This points to an energy imbalance responsible for the long term trend (Wong 2005).

Fig 1

Figure 5: Land, atmosphere, and ice heating (red), 0-700 meter OHC increase (light blue), 700-2,000 meter OHC increase (dark blue).  From Nuccitelli et al. (2012),

Data analysis, physical observations and basic arithmetic all show ENSO cannot explain the long term warming trend over the past few decades. Hence the irony in Bob Carter's conclusion "The close relationship between ENSO and global temperature leaves little room for any warming driven by human carbon dioxide emissions". What his paper actually proves is once you remove any long term warming trend from the temperature record, it leaves little room for any warming.

Intermediate rebuttal written by dana1981

Last updated on 10 July 2015 by pattimer. View Archives

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Argument Feedback

Please use this form to let us know about suggested updates to this rebuttal.

Further reading

NOAA have a very useful resource ENSO Cycle: Recent Evolution, Current Status and Predictions which features recent ENSO activity as well as model predictions of ENSO activity in the near future.

Denial101x video

Comments

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Comments 51 to 75 out of 205:

  1. It is interesting to not the varying scales used by Kayell @49. He uses at least three (possibly four) different inconsistent scales for the Global - East Pacific SST. Not until the sixth graph (the one showing timing of El Nino events, and volcanoes) that he shows a close approximation to the correct scale. His inconsistent scaling is unexplained, and is germain.
  2. IanC says: “PDO (regardless the physical cause) is fundamentally a basin-wide mode of variability over inter-decadal timescale.” Incorrect, IanC. The PDO Index is derived from (it's the leading principal component of) the sea surface temperature anomalies of the North Pacific, north of 20N, after the global sea surface temperature anomalies have been removed. By definition it cannot be a “basin-wide mode of variability over inter-decadal timescale” because it does not represent the data of the basin. JISAO includes the basin maps to show the “El Niño like” spatial patterns in the North Pacific (north of 20N). To help with your bearings, look for Hawaii on the maps. It's at about 20N latitude. IanC says: “A change of PDO index from 1 to 0 corresponds to a relative cooling of 0.4 degrees over 1982-2010, which is large enough to account of the lack of warming in eastern pacific.” Also incorrect, IanC. The PDO does not represent the sea surface temperature anomalies of the North Pacific and it definitely does not represent the sea surface temperatures of the East Pacific. Over decadal timescales the PDO is inversely related to the sea surface temperature anomalies of the North Pacific: http://i52.tinypic.com/15oz3eo.jpg Please also detail with data how you determined “A change of PDO index from 1 to 0 corresponds to a relative cooling of 0.4 degrees over 1982-2010…” when the PDO does not represent sea surface temperature anomalies in any way, shape or form. IanC says: “Your point (d): Is this post the basis of your point? If so, your reasoning is fundamentally flawed, as a correlation does not imply causation, it is equally, if not more, likely that SST anomaly causes a change in air pressue.” There’s no flaw in my reasoning or understanding of what causes the PDO. Using different methods, Di Lorenzo came to the same conclusion. IanC says: “Regarding ENSO: Your references all appear to be linear regression analyses, which assume that surface temperature respond proportionally to El Niño and La Niña, which is very different from your assertion in post 40, where you said: ‘According to numerous peer-reviewed papers, surface temperatures respond proportionally to El Niño and La Niña events, but it’s obvious they do not.’” You’ll need to expand on why it’s different, IanC.
  3. doug_bostrom asked, “…is it the claim of Bob Tisdale that there's no trend in global ocean heat content, or if anything that global ocean heat content has in fact decreased as global surface temperature has increased?” Nope.
  4. Intriguing discussion. Can Mr. Tisdale please direct us to a peer-reviewed paper in a reputable journal in which he has presented his hypothesis and provided supporting evidence of said hypothesis? Talking of journal papers, I think it safe to assume that Mr. Tisdale agrees with and understands exactly how Douglass and Knox (2012) analyzed the OHC data. Additinally, would Mr. Tisdale stake his "reputation" (in the "skeptic" blogosphere) and his hypothesis on the aforementioned paper? He can respond to the last statement and question onthe relevant DK thread.
  5. Further to Bob's reply at #53, I don't see what relevance Bob's ideas have to global warming. If global surface temperature is increasing along with global ocean heat content more or less simultaneously on a scale greater than a decade or so, what's the relevance of ENSO to the long term problem of global warming? "Increasing global ocean heat content" means the net warmth of the entire ocean is increasing, which in turn means the notion of energy shifting from one portion of the global ocean to another to produce the false impression of warming doesn't pan out. Which I suppose is the point of the rebuttal. Presuming that Bob is asserting that the E. tropical Pacific is responsible for warming the entire remaining planet on scales greater than a decade, something else I don't understand is how the E. tropical Pacific could do so without becoming more than a touch cooler itself. It seems we ought to be seeing a relatively drastic cooling of the region but we don't. If anything, we see the opposite.
  6. Bob, Yes I understand how the PDO index is constructed. The point is that you can get an idea of how the rest of the basin varies by regressing the SST anomaly (SSTA) onto the PDO index to extract the inter-decadal variation that is associated with the PDO. While the PDO index is constructed using N. pacific data, the subsequent regression demonstrate that there is strong evidence that the tropical Pacific ocean vary coherently with the N Pacific. There are ample evidences of a basin-wide inter-decadal oscillation. Here are two: Zhang et al. 1997, did an EOF with SSTA of the entire basin . For the low-pass filtered (c.f. fig 3) computation, the dominant mode has a similar spatial structure as the one depicted on the JISAO website. Furthermore, the principal component varies similar to the PDO index. Shakun and Shaman 2009 showed that if you do a similar analysis with data from the southern Pacific, and the principal component is again highly correlated to PDO index. Furthermore, they again recover similar spatial structure across the entire pacific ocean. Conclusion is that no matter which way you look at it, there appears to be a robust inter-decadal mode of variability in the pacific. The main point is that although looks like the ENSO, there are two distinctive differences: - 20-30 years for PDO vs 6-18 months for ENSO. - ENSO is most prominent in the tropics, while for PDO the responses in N. Pacific and Tropics are similar in amplitdue. PDO index is one of the ways you can characterize this oscillation, the same way SSTA from a limited region (e.g. NINO3.4) can characterize the state of a basin wide oscillation (ENSO). Your assertion that the PDO index has no relation to the SSTA is wrong, because one cannot interpret the PDO index (principal component) without concurrently consider the spatial structure (EOF), simply because a mode of variability in an EOF/PC analysis is actually represented by EOF*PC. Here you'll see that you have to choose a normalisation, because if you take c*PC and EOF/c (c is a constant) you get the same thing when you multiple the two together. Take a look at the EOF and PC for the PDO (from Deser et al. 2010 : Notice that the units for the top panel (the EOF) is in degrees per standard deviation. The PC (PDO index) is given in standard deviation, so to recover the SSTA you indeed have to multiply the two to get the right units. The average of the EOF in the N. Pacific definitely negative (<0), but probably no smaller than -0.4. Taking the average you get -0.2 degrees C per SD, which is exactly the scaling factor you found. You are technically correct in saying that "PDI index is not SSTA", but you are completely missing the point: the PDI index, in conjunction with the EOF, does in fact describe SST variations. In the eastern pacific (as you defined it), if you average the EOF you probably get 0.3 degree per SD. Between 1980-1985 and 2005-2010, the PDO index went from +1 to -0.5, so ΔSST= -1.5 * 0.3 = -0.45 degrees C you can probably argue for a couple of tenths either way, but the key is that the change in eastern Pacific due to PDO is large enough to explain the lack of warming in the eastern pacific. You said "There’s no flaw in my reasoning or understanding of what causes the PDO. Using different methods, Di Lorenzo came to the same conclusion." In your blog post, the crux of your argument is fig7, where you plotted 85-month smoothed PDO - Nino3.4 as well as N. Pacific air pressure index (NPI). The figure shows a good correlation between the two series, which you then said "Is The Difference Between NINO3.4 SST Anomalies And The PDO A Function Of Sea Level Pressure?, the answer appears to be yes." (1) Nowhere in your analysis did you present an argument of causality.. (2) In addition, you applied a 85-month filter, which will likely wipe out any signal in ENSO. In fact if you plot a 85-month smoothed PDO index against the NPI I suspect you will get just as good of a result, so likely what you have found is a good correlation between PDO index and NPI. Can you post the reference to di Lorenzo? Final point: In your original post, you said ‘According to numerous peer-reviewed papers, surface temperatures respond proportionally to El Niño and La Niña events'. I think the reasonable interpretation, based on your wording, is that numerous papers concluded that surface temperatures respond proportionally to El Niño and La Niña events; this is very different from papers assuming the same.
  7. Kayell, Part 1: The main problem here is that you are working with a noisy dataset, and you elected not to apply any statistical test, or even some quantitative measurement. Eyeballing, is not a particular good tool. Your claim that "The ENTIRE global rise above the NINO3.4 occurs at two specific instances. Not at any other time." is demonstrably false. Sphaerica shifted the events at La Nina events and produced a plot similar to yours, so is it La Nina? I played around with the data, and if I allow myself two shifts, the ones that minimizes the overall difference between the two dataset actually occurs in 1984 and 1996. In this case perhaps the best explanation is volcanoes? Simply put, without doing any rigorous analysis, you cannot not rule out other possibilities, so you are not entitled to claim that your interpretation is correct. More on part 2 later.
  8. Albatross: “Additinally, would Mr. Tisdale stake his ‘reputation’ (in the 'skeptic' blogosphere) and his hypothesis on the aforementioned paper? He can respond to the last statement and question onthe relevant DK thread.” Curious tactic, Albatross. Nice try, but I have no reason to stake my reputation on the work of someone else. Douglass and Knox (2012) analyzed ocean heat content data on a global basis. I typically don’t bother investigating global data. Why? Looking at global data can be misleading. It’s best to divide the oceans into logical subsets, because coupled ocean-atmospherics processes impact ocean basins in significantly different ways. Realistically, that’s the only way anyone can attempt to perform an attribution study on the warming of ocean heat content data--or sea surface temperature data. Regards
  9. @Bob Tisdale #58: In your response to Albatross, you conveniently ignore the first question hea had posed, i.e., "Can Mr. Tisdale please direct us to a peer-reviewed paper in a reputable journal in which he has presented his hypothesis and provided supporting evidence of said hypothesis?" If Albatross hadn't beaten me to the punch, I would have asked the same question.I suspect that many other readers would have as well. The ball, as they say, is in your court, Mr, Tisdale.
  10. I typically don’t bother investigating global data. Thereby conveniently avoiding the problem of explaining how net ocean heat content is increasing, along with atmospheric temperature. Realistically, that’s the only way anyone can attempt to perform an attribution study on the warming of ocean heat content data--or sea surface temperature data. By ignoring ocean heat content?
  11. I'm not sure who is using "curious tactics" here. Albatross's question was straight and simply formulated. In what article has Bob Tisdale subjected his ideas to scientific peer-review? I read Albatross' post and at no point had I the impression that BT was asked to stake his reputation on the DK paper. I don't see how it could even be construed this way, especially by one who claim to be so brilliant that his ideas escaped all of the SkS contributors. At any rate, it was a perfectly legitimate question, is there an answer? Tom Curtis also asked an interesting question @45, to which I have not yet seen an answer. IanC raises some interesting points above too. I hope that, for the sake of clarity, all these will be addressed before the conversation drifts to other things.
  12. IanC says: “ENSO is most prominent in the tropics, while for PDO the responses in N. Pacific and Tropics are similar in amplitdue.” They are? I believe you’re wrong, IanC. The PDO is standardized. NINO3.4 sea surface temperature anomalies typically are not. The first PC of detrended North Pacific residuals (North Pacific minus global sea surface temperature anomalies) has a standard deviation of approximately 0.18 deg C. In other words, standardization exaggerates the value of the PDO by a factor of 5.5, giving people the impression that it’s similar in magnitude to NINO3.4 sea surface temperature anomalies. IanC says: “Zhang et al. 1997, did an EOF with SSTA of the entire basin . For the low-pass filtered (c.f. fig 3) computation, the dominant mode has a similar spatial structure as the one depicted on the JISAO website. Furthermore, the principal component varies similar to the PDO index.” All of the analyzed subsets have major variations in response to ENSO giving them similar appearances, but there are subtle differences, so please confirm your last claim with data. Additionally, you’d need to analyze the dataset being discussed, which is the East Pacific, not the North Pacific or the Pacific as a whole. When you examine the data, you’ll discover the East Pacific responds differently than the other portions of the Pacific you’re attempting to compare with it. IanC says: “You are technically correct in saying that "PDI index is not SSTA", but you are completely missing the point: the PDI index, in conjunction with the EOF, does in fact describe SST variations.” You missed my earlier comment, where I noted that the PDO was inversely related to the North Pacific residuals (North Pacific minus global sea surface temperature anomalies): http://i52.tinypic.com/15oz3eo.jpg Same thing holds true for the variations in the monthly data: http://i52.tinypic.com/1zo8686.jpg With respect to Zhang et al 1997 and to Shakun and Shaman 2009, both papers concluded ENSO leads the ENSO-like patterns. In fact the title of Shakun and Shaman is “Tropical origins of North and South Pacific decadal variability.” So why deal in abstract forms of sea surface temperature data like the PDO, IanC? Why not simply compare the East Pacific to a scaled ENSO index and say that the East Pacific has mimicked the NINO3.4 sea surface temperature anomalies over the past 30 years? It’s much easier for people reading this thread to understand: http://bobtisdale.files.wordpress.com/2012/09/figure-111.png IanC says: “In your original post, you said ‘According to numerous peer-reviewed papers, surface temperatures respond proportionally to El Niño and La Niña events'. I think the reasonable interpretation, based on your wording, is that numerous papers concluded that surface temperatures respond proportionally to El Niño and La Niña events; this is very different from papers assuming the same.” In your quote, you forgot the ellipse, IanC, to indicate my sentence continued. In other words, you’ve taken what I wrote out of context. That sentence read in full: “According to numerous peer-reviewed papers, surface temperatures respond proportionally to El Niño and La Niña events, but it’s obvious they do not.” When the entire sentence and the graph linked in that original paragraph… http://bobtisdale.files.wordpress.com/2012/09/figure-13.png …are included as I has intended, then your interpretation of what I had written doesn’t ring true. Those papers didn’t conclude global temperatures respond proportionally to El Niño and La Niña; they assumed it. In fact, of those papers that I linked for you in my earlier reply, only one acknowledges ENSO residuals. It was Trenberth (2002). In their concluding remarks, they wrote, as I quoted earlier: “Although it is possible to use regression to eliminate the linear portion of the global mean temperature signal associated with ENSO, the processes that contribute regionally to the global mean differ considerably, and the linear approach likely leaves an ENSO residual.” And as I noted earlier, the divergences in brown… http://bobtisdale.files.wordpress.com/2012/09/figure-13.png …are those ENSO residuals, which are not accounted for in any of the studies I linked for you. Regards
  13. John Hartz: “In your response to Albatross, you conveniently ignore the first question hea had posed, i.e…” John, I’m not sure why you’re belaboring the point. You and Albatross know quite well that they have not appeared in a peer-reviewed journal. All I do is present data, and it contradicts the hypothesis of anthropogenic global warming. Now it's my turn to ask you and Albatross a question: how would my findings make it past the gatekeepers of AGW peer review?
  14. @Bob Tisdale #63: Actaully, I know very little about you and your analyses. The fact that you have not published anything in a mansitream peer-reviewed journal explains why. Either you are confident about the validity of your work, or you are not.
  15. doug_bostrom says: “Thereby conveniently avoiding the problem of explaining how net ocean heat content is increasing, along with atmospheric temperature.” Not sure how you could conclude that from what I had written, doug. I wrote and you quoted part of, “I typically don’t bother investigating global data. Why? Looking at global data can be misleading. It’s best to divide the oceans into logical subsets, because coupled ocean-atmospherics processes impact ocean basins in significantly different ways.” doug_bostrom says: “By ignoring ocean heat content?” Where in the sentence that you quoted (Realistically, that’s the only way anyone can attempt to perform an attribution study on the warming of ocean heat content data--or sea surface temperature data.) does it say that I ignore ocean heat content, doug? An example for you, doug, of how I address data in logical subsets: Here’s an annotated graph of the Ocean Heat Content of the North Pacific north of 20N (the same area that’s used for the PDO). http://i48.tinypic.com/2l9gqxf.jpg Now it’s time for me to ask you questions, doug. How does the AGW hypothesis explain the cooling of the North Pacific (north of 20N) from 1955 to the late 1980s? And how does it explain the sharp rise over a two year period? And how does it explain that the North Pacific north of 20N would have cooled over the entire term of the data if it wasn’t for that 2-year rise?
  16. Philippe Chantreau says; “I read Albatross' post and at no point had I the impression that BT was asked to stake his reputation on the DK paper. I don't see how it could even be construed this way, especially by one who claim to be so brilliant that his ideas escaped all of the SkS contributors.” Here’s what Albatross wrote, Phillipe: “Additinally, would Mr. Tisdale stake his ‘reputation’ (in the 'skeptic' blogosphere) and his hypothesis on the aforementioned paper? He can respond to the last statement and question onthe relevant DK thread.” He quite clearly stated in his question, “would Mr. Tisdale stake his ‘reputation’ (in the 'skeptic' blogosphere) and his hypothesis on the aforementioned paper?”
  17. Philippe Chantreau says “Tom Curtis also asked an interesting question @45, to which I have not yet seen an answer.” Sorry I missed his question. Tom Curtis asked, “Thankyou. I notice that the strongest correlation between Nino 3.4 and global SST is when global SST lag Nino 3.4 by nine weeks. In your comparison, you say you used a 6 month (equivalent to a 26 week) lag. Why did you use a lag 17 weeks longer than that indicated by the data?” Please advise where you’re noting that the strongest correlation between NINO3.4 and global SST is when global SST lag NINO3.4 by 9 weeks. Also, in my comparison, assumedly this one… http://bobtisdale.files.wordpress.com/2012/09/figure-13.png …it’s not a global dataset. It excludes the East Pacific Ocean where the direct effects of ENSO would be felt. Also note how well the scaled NINO3.4 data and the Rest of the World data align during the evolution of the 1997/98 El Niño. The 6-month lag works quite well.
  18. IanC @57, I'm sorry, but it appears we're not looking at the same dataset here. Please examine one more time the second and third figure in my Part 1 post and then the animation at the end. Then read once more what I point to. What exactly are we looking for? "[...] places where the global curve diverge permanently from the NINO curve. There are only (and by that I mean ONLY) two cases between 1981 and 2012 where the extra heat piled up globally after an El Niño and during the transition to the first following La Niña is never fully made up for before the ENSO pendulum turns and the heat comes in again, both in the NINO3.4 region and globally." If you observe the second figure (Level 1), how can you miss these two instances? Only in 1987-88 and in 1998-99 does the global curve lift its mean SSTA level up from the NINO3.4 curve and stay there. Nothing of consequence happens at any other time between the two curves. You must not forget that in this exercise we're always relating the global curve to the NINO3.4. In Part 2 I also show you WHERE the two specific upward shifts originate - check out the second figure in my Part 2 post. You say it's a noisy dataset. I've shown you just how 'un-noisy' it really is. If one simply cares to take a closer look at the data. The global curve pretty much consists of two component signals: 1) the regular large-scale NINO ups and downs and 2) the two sudden and significant hikes in mean temperature level as compared to the NINO3.4 after the El Niños of 1986/87/88 and 1997/98 respectively. Sphaerica is only obfuscating and confusing the matter. He/she isn't reading what I'm writing. He/she isn't looking at my plots. Let's have a look at his/her graph. (Compare with my second figure in Part 1.) The first chosen La Niña is an extended, yet fairly weak event, fluctuating in and out of La Niña territory. There is absolutely no 'extra' global heat accumulating here. No need whatsoever for a downward adjustment. Then he/she skips the next La Niña (88/89) altogether, which as it happens was the deepest ENSO event since the 70s. Peculiar, don't you think? Here you DO clearly see the extra global heat accumulating, inducing an upward shift in mean SSTA level globally relative to NINO3.4. Sphaerica's next blue line is not a La Niña at all. It's Pinatubo. Then he/she places the next line right smack in the middle of the La Niña 98/99/00/01, but of course by doing so again misses the actual instance of global accumulation of heat, which quite evidently occured during the first La Niña-year after the 1997/98 El Niño (98/99). Sphaerica's last La Niña adjustment is again performed at a place along the curve where absolutely no downward adjustment is called for. He/she's completely missed what we're actually looking for. I'm telling you again (and I thought this was already made very clear in my two posts, I feel a bit silly having to repeat it), there is no extra global trend, no increasing divergence between NINO3.4 and global SSTA levels anywhere outside the two obvious upward shifts. (Referring once more to the second and third figure in my Part 1 and the animation towards the end.) You see, this isn't about playing around with statistical trickery. About who can produce the 'best' fit. It's about what the actual data at hand is showing us, telling us. What's in the data? That's all I've done so far. Explored the data. It's all right there. Right there in front of you. In the data. Something out of the ordinary is very clearly happening globally (outside the East Pacific) during the transition from specific, solitary and powerful El Niños to the deep La Niñas directly on their heels. This is all about natural processes. Readily observed to unfold. They happen. I still haven't gotten to those, though. That's for Part 3. The satellite-based Reynolds OI.v2 is a benchmark dataset for SSTs since 1981/82, globally comprehensive, a tried-and-true source of high-resolution data. It agrees well with surface-based datasets like the HadSST, HadISST and ERSST. To quote William M. Briggs: "We do not have to model what we can see. No statistical test is needed to say whether the data has changed. We can just look." Why not let the data speak for itself?
  19. Bob, I explained very carefully in my previous post how one should relate the PD) index to SST anomalies (relative to global temperature, or residuals if you prefer) (1) Do you agree that one cannot interpret the PDO index in terms of SST anomaly without the corresponding EOF? (2) Do you agree with my example, that -0.2 degrees C per standard deviation is a reasonable average for the EOF over N Pacific (NP)? (3) Do you agree that with (2), it explains why your observation that (a) PDO varies inversely with NP SSTA and (b) the PDO index "exaggerates" the fluctuation in NP SSTA? Regarding Zhang et al 1997: Here's their figure 3 HP: the EOF and PC shows that this is the usual ENSO mode. You can check the PC and it follows ENSO indices quite well. The spatial EOF also shows good agreement with ENSO: the hot spot on the east corresponds to 0.7 degrees per SD, the response in NW pacific is much weaker: -0.2 degrees per SD. LP: This is the PDO mode:comparing the PC (bottom) to the PDO index(top): You can see they agree reasonably well. Looking at the EOF, you can see that the response in the NW pacific (-0.3 degrees per SD) is comparable to the responds in the eastern pacific (0.4 degrees per SD). Your comment " Additionally, you’d need to analyze the dataset being discussed, which is the East Pacific, not the North Pacific or the Pacific as a whole." is puzzling. One of the central question here is whether PDO is a basin wide phenomena, and thus can account for the lack of warming on the eastern pacific. Can you elaborate on why using data from the entire pacific to determine the existence of a basin wide mode is inappropriate. ########################################## You said " Why not simply compare the East Pacific to a scaled ENSO index and say that the East Pacific has mimicked the NINO3.4 sea surface temperature anomalies over the past 30 years? It’s much easier for people reading this thread to understand" What that will accomplish exactly? NINO3.4 is part of the east Pacific so the fact that they vary similarly should not come to a surprise. How does that say anything about the long term decadal trend of the east pacific? ############################################# In your original post, the following quote appeared: “According to numerous peer-reviewed papers, surface temperatures respond proportionally to El Niño and La Niña events, but it’s obvious they do not.” The last sentence is largely irrelevant because it is clear that you are disputing something. The question is what are you disputing? My point is from what you've written you are disputing conclusions of papers (which is surprising so I asked for references), whereas in reality you are disputing the assumptions.
  20. Sorry Bob, but I've got a hanging question open here that you've not answered and which needs to be addressed if your hypothesis is to have any relevance to global warming. It is after all global warming that is the topic of this site; forgetting the rest of the globe and focusing on the E. Pacific is only a variation of the infamous "escalator." So I'm not really interested in the wee specifics of the E. Pacific, I'm more interested in the relevance of your hypothesis to the topic of this web site, global warming. It's a fairly simple question. Where is the energy required to produce net warming of the entire global ocean along with the atmosphere coming from? Put another way, are you claiming that the energy required to produce net warming of the global ocean and atmosphere is coming from the global ocean itself? Please don't answer by reference to the E. Pacific; the E. Pacific is after all a relatively small part of the global ocean and thus contains only a relatively small component of the net ocean heat content.
  21. Bob, I'm still working through your analysis, but I have to say: the 'gatekeepers of the science' claim is pretty pathetic. Surely you don't buy into that garbage. If someone held your hand to the fire and forced you to attempt publication, what would your hypothesis or (better yet) research question be? That's something I'm still not clear on. I'm also not clear on the physical mechanism you're proposing (if indeed you are). How does a step change fit into Walker circulation dynamics, what is the trigger mechanism, etc.? And does the results of Tokinaga et al. (2012) change the way you look at the trends and relations? Kayell, data, in this case, are the result of a set of dynamically integrated physical processes. Untangling those physical processes is the only way to understand the data in a meaningful way. See David Rose, for example, who makes a colossally dumb statement to the public at large based on a simplistic reading of a data set that itself is limited in a variety of ways in terms of representation. I can buy a step change if I see a physical mechanism. If it's there, it's there. What I fear, though, is that you're trying to argue for a step change not in order to advance the science but in order to present a specific message to the public at large, a message that may or may not be supported by investigations into the physical processes at work.
  22. Bob Tisdale. Further to Doug Bostrom's latest asking of the matter concerning from where the internal heat comes to persistently warm the planet over decades, I'm also curious about where you think the heat being trapped by the anthropogenic component of atmospheric CO2 is ending up, and why it isn't warming the planet. Numbers and references are welcome.
  23. Bob Tisdale @67, thankyou for answering my question. I am unsure why you draw attention to the fact that you used East Pacific vs the rest of the world in your figure. There is even less correlation between the East Pacific and the rest of the world than there is between Nino 3.4 and the globe, or Nino 3.4 and the rest of the world (ie, gobal minus East Pacific). Indeed, Nino 3.4 vs the rest of the world even gives the best correlation with much greater lag than does any other comparison I have made, with a correlation of 0.076 at thirty one weeks lag. All other comparisons other than Nino 3.4 vs Global show the highest correlation with zero lag, and as previously indicated Nino 3.4 vs Global shows its best correlation (0.382) at nine weeks lag. Here is the data: "Indian Ocean" refers to a band between 5 degrees North and 5 degrees South in the Indian Ocean having the same area as Nino 3.4, and as you can see correlates better both with the globe minus the East Pacific, and the globe than does Nino 3.4 Given this data, your response that you lagged the rest of the world vs East Pacific data is an evasion rather than an answer. Doing so provides less justification for the lag you have chosen, not more. This leaves you in the position where your only justification of the lag that you have chosen is that it helps you make your point. That is, you have a rhetorical, not a scientific justification for your chosen manipulation of the data. As an aside, I was considering the first of your graphs reproduced by Kayell here, which I now realize is not lagged (final clause added in edit). Correctly lagged it looks like this: (Both detrended) What also becomes clear using the proper lag is that the way in which global temperatures track ENSO events is noisy. Focusing on just one or two such events will simply focus on noise in the system. It is, in other words, simply cherry picking. (Edited to delete faulty analysis, TC)
  24. Kayell, So, here is your "detrending", based on presumed El Niños (although since such events last a year or more, it's still a little vague as to where Tisdale actually made his breaks, or why the breaks would be at specific points in time): Here is mine, pretty much randomly using spots in various La Niñas (no, there's no real, objective justification for my selection of points, any more than there is for yours): And here is the data detrended properly, over time, using a linear coefficient (courtesy of Tom Curtis): Personally, I think the proper statistical method gives the best fit, my tongue-in-cheek La Niña method the second best fit, and Tisdale's magical El Niño Gremlins method the worst fit. But, all in all, I think anyone would agree that there's not really any strong reason to argue that one is notably better than the other. So why wouldn't a simple, linear and correct detrending apply (Occam's Razor)? Why are we wasting any time at all on this discussion?
  25. I really like the idea of gatekeepers for science, I don't think it's a bad thing. Without gatekeepers, soon you get fruicakes publishing stuff about how the Earth has been expanding over the past 5000 years and yet even more fruitcakes touting the piece around saying "see, it's published science." A gatekeeping process is necessary. Sorry for the OT, end of sopabox moment. I guess the conclusion is that Bob Tisdale's work has not even been proposed for publication? I'll interpret his response as such unless told otherwise.

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