Story submitted by Jens Raunsø Jensen
The IPCC dismisses in its AR4 report of 2007 natural climate variability as a major reason for the global temperature increase in the second half of the 20th century. The basic arguments are “greenhouse physics”, increasing and accelerating temperatures in the second half of the 20th century, and the inability of climate models to reproduce the temperature changes if only natural processes are considered.
However, many local, regional and global temperature curves for 1960-2010 may be summarised as consisting of step changes, coinciding with one or more major ENSO-related events (El Niño) and separated by periods of near constant temperature. Thus, the temperature increase (proxy for global warming) in the second half of the 20th century could have taken place in steps driven by major ENSO events. This challenges IPCC’s notion of increasing and accelerating temperatures and IPCC’s modelling argument for accepting the anthropogenic global warming (AGW) hypothesis as the major explanation for the observed temperature changes.
Methodology
Temperature curves have been analysed with many different tools to establish a perceived underlying pattern for statistical and/or for attribution purposes: smoothing, linear regression, waves and periodicities, break points, shifts etc. They all have their merits and limitations, and there is no general agreement on the pattern except as consisting of a relatively cold period from the mid 1940s to mid 1970s, followed by a warmer period during the 1980s and 1990s.
This post analyses temperature data using a tool for identifying step changes in the mean temperature, focusing on the period 1960-2010. This analysis complements many other similar analyses in the peer reviewed literature and on this and other blogs (see eg. Bob Tisdale here http://wattsupwiththat.com/2011/03/11/tisdale-on-enso-step-changes-in-rss-global-temperature-data/ ). The focus is on the land-based temperature record, the use of data up to 2010, and the application of a statistical tool that does not require a priori assumptions of the time or number of step changes. It is noted, that 1960 was selected as the start year for the analysis in order to cover the main period of interest from a global warming perspective. The step changes presented below remain the same when the entire historical observational records are analysed.
The tool, I have relied upon, is available from NOAA’s homepage and has been documented in the peer-reviewed literature (www.beringclimate.noaa.gov/). Trial runs on different annual temperature datasets suggest, that a robust solution (maximum correlation and low sensitivity to parameter setting) is obtained when using the following settings: a cut-off length parameter in the interval of 8 to 14 years (12 selected), a correction for autocorrelation by the IPN4 method, and an outlier definition of 3 s deviation in order to effectively give equal weight to all observations.
Results
The Fig.1 below shows the result for two of the many cases I have looked at: global (crutem3gl; http://www.cru.uea.ac.uk/cru/data/temperature/ ) and Denmark, DK (t_dk_k, from Danish Meteorological Institute DMI; http://www.dmi.dk/dmi/index/klima/dmi-publikationer/tekniskerapporter.htm ).
The T-anomaly is with reference to 1961-1990 (note: the DK curve has been shifted upwards by 2 oC to avoid overlap). At the bottom in the figure, the warm (red) and cold (blue) state of the pacific decadal oscillation (PDO) is shown together with major volcanoes (squares) and El Niños (triangles). Vertical lines show the PDO shift in 1976 and the start of El Niños in 1986 and 1997.
Notwithstanding the confounding influence of anthropogenic forcings, it is hard not to see this figure as suggesting, that natural processes have had a major influence on the course of the global warming in the second half of the 20th century, contrary to the assessment of the IPCC.
The identified steps are statistically highly significant, and 85% of the variation in the global land temperature during 1960-2010 may be explained by 3 upward steps, separated by periods of near constant temperature and with a lack of warming (insignificant trend) during the most recent 13 years. The step curve for Denmark explains 40% of the variance (as compared to 30% by the Gauss-filtered smoothing model of DMI), with a lack of warming during the most recent 23 years.
The three steps in the global curve occur at 1977, 1987 and 1998. This could be a statistical coincidence as eg. any curve with a true linear trend may be summarised as a step curve. However, the three years have a documented physical significance: 1977, the great pacific shift, with the PDO turning to the warm mode, and 1987 and 1998 being years of major ENSO activity. Thus, in terms of the accumulated nino3.4 anomaly, the El Niños of 1997/98 and 1986/88 were the most extreme on record (NOAA data, 3-month average nino3.4-anomaly). Furthermore, the linear trends of the four periods separating the change points are all non-significantly different from zero, but the power of this test is of course reduced in the periods of shorter length. (It is noted that the hadcrut3 and the GISS land-ocean datasets give essentially the same result, with steps at 1977/1990/1997 and 1977/1987/1997, respectively).
Local and regional temperatures are generally known to be differently affected by ENSO events. Accordingly, many local temperature curves across the globe can similarly be summarised by the step model, with one or more steps at or close to one or more of the steps identified above in the global record. For example, the Denmark curve in Fig. 1 displays one step in 1988; Alaska curves display only one but very significant step in 1977 (GHCN data, 4 stations analysed, not shown); USA have steps in 1986 and 1998 (GISS, contiguous 48 states, not shown); and Australia have steps in 1979 and 2002 (BOM data, not shown).
Finally, sidestepping a bit with some food for thoughts: inspired by the current discussion on the role of natural causes for the changes in the atmospheric CO2 concentration, it may be mentioned, that the annual change in ppmv CO2 at Mauna Loa displays significant upward shifts in 1977 and in 1998, on average increasing the annual concentration increment by 58% and a further 33%, respectively. It seems that there could be a strong influence of ENSO also on the annual increment on the CO2 curve during 1960-2010.
Implications
It is demonstrated above that the temperature increase in the second half of the 20th century could have taken place in steps driven by major ENSO events. The significance of the finding does not mainly rest on the statistical significance of the model fit, but on the physical support of the ENSO observations for the step changes, identified without making a priori assumptions on the timing or number of steps.
If this was indeed the case – and it could be, unless proven otherwise – then the following implications arise:
1. Natural processes in the ocean-atmosphere system may have had a major influence on the global temperature change in the second half of the 20th century. If so, then something must be wrong with IPCC’s climate models, as the models according to the AR4 can not at all reproduce the observed temperature curve by considering natural causes only. This could question the climate sensitivity of the models and the models ability to adequately describe the natural processes in oceans and atmosphere (eg. ENSO phenomena). While it is generally accepted, that ENSO events can produce abrupt changes in global temperatures, the IPCC considers such effects to be short lived (albeit based on a poor ability to model ENSO processes), whereas the observational data when summarised as step changes imply a longer term effect on both local and higher-level average temperature curves.
2. The linearity assumption underlying the use of linear regressions for trend analysis of the temperature records is in principle violated by the presence of steps. Thus, the global temperature should not be considered as simply uniformly increasing or accelerating, and claims of average temperature increases and accelerations may be erroneous and misleading. The use of linear regression for analysing temperature (and other climate-related) curves should be reconsidered.
3. Regional and global temperature anomaly curves are “apples and oranges”, as they average over locations differently influenced by natural processes and in different states of the climate system. There is a need to emphasise more on the analysis of local temperature curves.
4. It was recently suggested, that the lack of warming during 1998-2008 was driven largely by natural factors (Kauffmann et al., 2011). Referring to Fig. 1, then what is the explanation for the apparent lack of increase in global temperature during 1977-1986 and 1987-1997? And what is then the conclusion for the overall cause of global warming during 1960-2010?
Finally, I want to make it clear, that I do agree with the presence of an anthropogenic greenhouse effect. But I find reasons in the observational data to doubt, that the IPCC, in its current analysis (AR4, including only data up to 2005), has assessed the relative importance of natural and anthropogenic causes for the temperature changes correctly. The role of natural processes could have been significantly underestimated.
“and the inability of climate models to reproduce the temperature changes if only natural processes are considered.”
There are climate models that are capable of accurate reproductions with human influences included?
very good
Fascinating analysis. Thank you for this work. I’ve seen similar suggestions about the step patterns, and as we get more data they are becoming more apparent. Coincidence is always possible, but the real test of this hypothesis you posit will be the apparent negative phase of the PDO we are heading into. If we do switch to such a phase, we could predict, as a test, that we would see step wise patterns of decrease in global temperature.
Of course, this is confounded by the relative contribution of the ENSO events to temperature changes verses other factors; but the signal should still be apparent in a similar form if this hypothesis is correct, I would think (if only that the stepwise increases in temperature would cease).
Hi Anthony,
first a belated thanks for your incredible efforts with the watts up with that climate homepage; I enjoy reading the posts and the discussions, well done.
Pls notice that the figure of hadcrut temperatures has been mixed into the post; kindly remove.
thanks …. jens
REPLY: Done, I thought that was the figure your were referring to in the link you provided, as you did with the other figure. – Anthony
Figure 1 gives a somewhat false impression by using a zero baseline instead of the actual trend line from the LIA. This chart shows the difference: click
Thanks for this, Jens. Very interesting.
If I may presume to make a suggestion, it may be worth analysing the previous warming period (1910-40), to see if the same step changes occurred during a warming phase which was less likely to have been influenced by anthropogenic effects.
This analysis is almost certainly prone to an excessive Type I error as it has used an inappropriate null hypothesis. If you have a positive anomalies (ie ENSO) superimposed on a positive trend with white noise, these positive anomalies are likely to appear to be steps using your procedure. Before you can draw any valid conclusions, you need to use an appropriate null model, and it would help to have some physical mechanism for sustaining positive steps. Without these, this is numerology.
Very astute analysis. But there are several flaws or “oversights”. One, you have perpetuated the myth that global temperatures are increasing, when it is well known that the globe is cooling. Your curve for Denmark is accurate though because local temperatures ARE increasing. Second, as Smokey astutely illustrates, you have perpetuated the “myth of the baseline”. Since we don’t know the “natural” temperature of the Earth (it fluctuates), there is NO baseline.
Thirdly, your step changes are arbitrarily chosen based on your preconceived (“a priori”) notions of when they should occur. I have done a similar analysis modeling a step change for EACH year. The model is highly significant and the annual step changes account for 100% of the measured global temperature increase!
Fourth is a question. What event could be causing an annual step change in global temperature? It is a mystery and I believe that man was not meant to know.
Placing the main focus on natural processes is the wave of now and the future in climate science and it has always been the wave of science. Great work! Good Bye, Gaia Models.
Smokey says:
August 11, 2011 at 9:41 am
“Figure 1 gives a somewhat false impression by using a zero baseline”
Any trendline gives false impression. Recently I did some analysis in how temperature trends have been changing over past 30 years so I calculated trends between any two months. The result is here:
graph
explanation
In that graph you can cherry-pick any trends you like, including what is presented to us in this article and many its variations. I could complete the timeline out of just negative trends (with some steps in between) if I wanted – but that’s not science, it’s numerology.
And another fact is that any calculation of global average temperature has a great deal of uncertainity. It’s funny how some evaluate it to three decimal places when with greatest precision you can achieve you can’t get much below 1°C standard deviation – that’s more uncertainity than how much the world has supposedly warmed up in last 50 years.
I think Bob Tisdale was ahead of the curve on this one . . .
Cargo-cult ‘science’ is the process of justifying politically motivated hypotheses by assuming what is to be proved and then using methods that force-fit ‘adjusted’ data to the preconceived conclusion, all the while triumphantly waving the results of fantasy-based computer models. True scientists encountering such a blatant travesty are expected to keep their government-funded mouths either shut or chanting the approved AGW catechismal phrases, lest they be branded as ‘deniers’. Lysenkoism was but a practice run for the AGW cult. It only ruined Soviet agriculture, while AGW seeks to ruin modern civilization itself.
That’s good Smokey.
Measuring anomolies from a flat line seems pretty stupid and biased. As if “normal” = no change.
Yes we have been witnessing the whittling down of CO2 as an overarching driver of global temp increases. If following the step-up from an ENSO event, temps were to then rise linearly along the tread of the step, that might be a good measure of CO2 affect. The tread actually declines in between step-ups, but it could be argued (and probably is argued) that the CO2 effect impedes the decay after the step up. In any case, studies of this and other phenomena have trimmed projected CO2 driven temp increases from as high as about 5C/century back to something less than 0.5C/century.
I believe a psychological analysis would have arrived at a comparable result. When you present CO2 as the only important culprit (remember NOAA’s ‘control knob’) you are going to attribute much higher sensitivities, larger positive feedbacks, insignificant negative feedbacks (ignore clouds or include them as positve feedbacks); you are going to say UHI and solar activity is unimportant, you are going to manipulate the data to get rid of past warm periods and cool periods – because these historical events alone show that natural variation can be several degrees up or down, Finally, when one looks at proxy data, one has choices that can be made in where in the noise to choose a data point, where to most advantageously start and finish our curve, ranges of how we can manipulate the data, or even truncate it. We can be 100% certain that the figure for CO2’s effect given by the IPCC can be cut in half and still be in the true high range because there is no chance such an organization would ever come close to making an underestimate.
Bob Tisdale and Smokey are always ahead of the curve.
Once again I refer to some work Edward Lorenz did regarding the so-called “index cycle”. He had noted a behavior of climate models, simple ones at the time (late 80s/early 90s?) admittedly, but significant enough to warrant his attention, that showed finite climate disturbances leading to climate not returning to its previous state. Possibly these were truly step changes, or perhaps they are changes with a time-constant so long they appear like step changes. Is El Nino and the subsequent climate response a case in point?
But even so, one can look at the observations wavering around a flat curve and wonder if this truly represents a long term trend, or is it a long cycle? The trouble with climate is that it exhibits cycles of longer and longer period superimposed — or at least this is so of the longest geophysical records available.
While this is certainly interesting, an step change is not, I think, in compatible with there being an underlying long term trend, and thus I am not particularly persuaded by most studies finding step changes as “proving” anything.
Here is a mathematical example:
Suppose I have a curve made up of two components: one is a line trending upward, the other is a kind of saw tooth pattern where every now and then, the curve shoots up and slowly falls back down. Let’s put such curves side by side:
0 0
1 0
2 3
3 2
4 1
5 0
6 0
7 3
8 2
9 1
Added up these curves become:
1
5
5
5
5
6
10
10
10
This looks like a curve that is characterized by step increases upward, rather than a gradual trend. The periods in between steps are even flat. But remember our components: A curve that is indeed trending upwards, and a sawtooth pattern. Thus one cannot conclude that the curve is just step changes, as a pattern of sudden onset slow decay spikes combined with a gradual trend can explain this pattern.
If you like step changes look for a step change in arctic sea ice extent following the 1998 El Nino a couple of years later. The lag is just about enough time for a warm current to travel from ENSO region to the polar sea ice and then for the ice to soak it up in latent heat of melting.
Thumbs up to Smokey!
Jens Raunsø Jensen: Many thanks for the reference in your post. The post you linked did describe the upward shifts in TLT anomalies, but I have many other than present the ENSO-induced upward shifts in SST anomalies and global land plus sea surface temperature anomalies—GISS LOTI data between 60S-60N. I also discuss the portions of the ENSO process responsible for the upward shifts.
My most recent post on that topic was written for those new to El Niño and La Niña events (ENSO), and it uses graphs and animations of sea surface temperature anomalies, etc., to show where, why, and how these upward steps occur:
http://bobtisdale.wordpress.com/2011/07/26/enso-indices-do-not-represent-the-process-of-enso-or-its-impact-on-global-temperature/
Most of my posts discussing these shifts use satellite-era data so I do not usually cover the 1976 climate shift. The 1973/74/75/76 La Niña should play a major role in it.
Regards
Arctic sea ice extent acts like the thermostat in an automotive water cooling system. It’s like an iris that opens up so that more heat can escape. Ice is a great insulator, you see. Take it away and the exposed surface can dump heat to space a lot faster. Note that effect is also evident in the temperature record with no significant warming or cooling since the step change in Arctic sea ice.
Amazing how it all works. It’s almost like the earth was designed to remain in a temperature range friendly to life. A thermostat that’s been working for billions of years…
I hate the map at the top of the page. Unless you know to look at the differing distances and areas involved with representing a sphere on a flat plane it is certainly misleading.
With the help of a little spherical math and google earth let’s put it into prospective.
First the math. Circumference of a sphere at any latitude is equal to the formula 2(pi)R*cosine(L) (using earth polar radius of 3950 mi from NASA). At Lat 80 Deg (the top dashed line) this works out to 4310 miles. So half the distance, Long 0 to 180 (Or the Line thru eastern England to a line on the west side of the Bering Straight) is 2155 miles. Now using Google Earth’s handy ruler feature, let’s compare some distances.
Miami to San Diego -2143 mi.
For our EU buddies Gibraltar to Beirut – 2281 mi.
Not forgetting our Down Under mates – Perth to Brisbane – 2217 mi.
Talk about size envy.
While looking at the size of Greenland on the map, it is hard to remember that it is actually less area than the state of Western Australia (GrLnd 2,166,086 km2 vs. WA-Aus 2,526,786 km2) and just over the combined size of Mexico, Nicaragua and Belize. (2,166,086 km2 vs. 2125010 km2)
Using Google Earth’s ruler function you can scale the area of the entire Arctic Circle inside the space between the eastern point of Brazil to the outlet of the Congo River in Africa.
Maybe anytime this layout is used it should include a note like the passenger side mirror – “Objects may Be Closer than they Appear”
By the way, when identifying periods where temperatures were flat it is help most of the time to identify the influences of major volcanic eruptions. Take the 1987-1997 period as an example. The middle of this period contained the major climate/weather effecting eruption of Mount Pinatubo. This made temperatures for a few years afterward lower. These cold years will be concentrated in latter half of the period, thus having a negative influence on the trend over that period. The same is also true for 1977-1986 where the middle of the period is characterized by the eruption of El Chicon. These two eruptions plausibly explain the general flatness of the temperatures over those two periods. The lack of anywhere near as much volcanic ash as during either of those two eruptions doesn’t seem to stop some from postulating that some small effect of relatively minor eruptions can “explain” the recent lack of warming, too. That doesn’t quite wash, there simply hasn’t been enough dust throw up into the stratosphere by those smaller eruptions. I recall the WUWT post the accumulated AOD was maybe a tenth of the Pinatubo eruption. So the final period, recent period is the single most difficult to explain period of “lack of warming”. A pretty simple explanation is the underlying trend is pretty small, so natural variations can pretty easily overcome it.
The graphs on previous posts concerning steps are more convincing, but it can be correct. In particular I looked at sea surface temperature (July 2011) steps caused by ENSO, and of itself is quite plausible but in the grand scheme of things, if the rise in CO2 is caused by increased sea temperature then the Mauna Loa CO2 rise since 1958 would also be stepped and it isn’t – apart from the annual variation (Vegetation in Northern Hemosphere?) the underlying increase is quite linear and even predictable.
David Stockman provides step change analysis to temperatures, showing five separate trends from 1950-2010
Stockwell asks: Is the Atmosphere Still Warming?
DD More says:
August 11, 2011 at 11:38 am
“I hate the map at the top of the page. Unless you know to look at the differing distances and areas involved with representing a sphere on a flat plane it is certainly misleading.”
You’re right, it sure isn’t an equal-size projection, the greenland is too big on it (for comparison: Lambert cylindrical projection).
But as long as it is here just to illustrate events near the equator I believe emphasized polar areas do not matter that much in this case.
It is true in principle that global warming in steps bumped up by ENSO events (big el Ninos) is not necessarily incompatible with CO2 driven global warming.
However there are aspects of the ENSO system that make this view problematic. The ENS oscillation has at its core a positive feedback between Eastern Pacific (Peruvian coast) deep ocean upwelling and equatorial trade winds. This feedback is well established and is termed the Bjerknes feedback (thanks to Bob Tisdle for this info!):
http://stratus.astr.ucl.ac.be/textbook/chapter5_node4.xml
(Figure 5.3, half way down the page)
If the ENSO was only an atmospheric phenomenon, then hypothetically, CO2 driven late 20th century warming could influence ENSO itself, so as some argue (e.g. R Grates) the ENSO driven up-steps are the outworking of CAGW. Indeed if you accept the narrative of some for whom ENSO is about trade winds and nothing else, then this picture is plausible.
However ENSO is not only about trade winds, trade winds are only half of the story. The other half is the Peruvian upwelling. This upwelling, like all upwelling, is connected to and part of the global thermohaline deep ocean circulation (THC). So the ENSO phenomenon is inseparable from THC.
This is where the problems arise or those suggesting that CO2 increase in the last few decades only can have affected ENSO and even be controlling it. The time-course of global THC is of the order of a millenium (e.g. for a water parcel downwelled in the Norwegian sea to return to where it started). Thus for CAGW to be currently affecting ENSO, it would be necessary for CAGW to have been pumping excess energy into the oceans for several centuries in order to affect the THC, which is not the case.
Thus if the thesis of Jens Jensen and also of Bob Tisdale is correct, that recent warming is stepwise and proximally attributable to ENSO, then this is a big problem for CAGW. Anthropogenic CO2 rise is too recent and shortlived to have yet significantly affected the THC and the THC-related ENSO.
phlogiston-Actually, assuming that the ENSO is largely or entirely natural or not is not the biggest problem for the “steps instead of trend” interpretation of the data. Namely it is that the mathematical intepretation of the steps over reaches in declaring them necessarily distinct from the presence of an underlying trend. See my post above, a combination of saw tooth sudden increases with slow decreases afterward, overlayed on top of a continuous linear trend, gives the appearance of step shifts in data. The presence of these shifts is thus not at all proof that there is not a trend component. There may well be one. That is how these views can be compatible.
A says: “There are climate models that are capable of accurate reproductions with human influences included?”
Accurate? The Multi-model mean of the models used in the IPCC’s AR4 have no basis in reality. I’ve illustrated this using Sea Surface Temperatures during the satellite era. Refer to:
http://bobtisdale.wordpress.com/2011/04/10/part-1-%e2%80%93-satellite-era-sea-surface-temperature-versus-ipcc-hindcastprojections/
And:
http://bobtisdale.wordpress.com/2011/04/19/492/
richard telford says: …and it would help to have some physical mechanism for sustaining positive steps.”
Looking at SST anomalies since 1982 (satellite era), the East Pacific SST anomalies have not risen based on the linear trend:
http://i55.tinypic.com/28bs7xv.jpg
The rest of the world (Atlantic-Indian-West Pacific) rises in steps, and there is no trend during the periods between the major ENSO events:
http://i55.tinypic.com/2u97uc1.jpg
Refer to:
http://bobtisdale.wordpress.com/2011/07/09/does-the-sea-surface-temperature-record-support-the-hypothesis-of-anthropogenic-global-warming/
Now let’s divide the Atlantic-Indian-West Pacific into two additional subsets. Basically we’ll isolate the North Atlantic, leaving us with the South Atlantic, Indian and West Pacific data. Its SST anomalies rise in response to the significant El Nino events, driven by the redistribution of warm waters in response to those ENSO events, and then decays between them:
http://i55.tinypic.com/12524rb.jpg
Those negative trends between the ENSO events are countered by the positive trends of the North Atlantic SST anomalies, driven by the additional mode of variability known as the Atlantic Multidecadal Oscillation:
http://i54.tinypic.com/35d3j1h.jpg
Refer to:
http://bobtisdale.wordpress.com/2011/08/07/supplement-to-enso-indices-do-not-represent-the-process-of-enso-or-its-impact-on-global-temperature/
Andrew says: “phlogiston-Actually, assuming that the ENSO is largely or entirely natural or not is not the biggest problem for the “steps instead of trend” interpretation of the data. Namely it is that the mathematical intepretation of the steps over reaches in declaring them necessarily distinct from the presence of an underlying trend….”
And this is why I present the processes that cause the upward shifts.
Yes I agree. There was clearly a major step change following the 1974 la Nina and clealy a period of relative stability following the large El Niño in 1998. The question will be what happens after the most recent La Nina. I wonder if we should be thinking about this the other way round. During an El Niño the ocean is effectively dumping heat into the atmosphere and ultimately space – little wonder that we then experience a period of stability or cooling as everything then equilibrates. The opposite holds for a La Nina, when the ocean is effectively taking on heat, which then leads to warming as it balances out – or something along the lines.
I’m not convinced that a step-change response is inconsistent with AGW. Yes, it is inconsistent with the models, which for all their compute power seem pretty stupid to me in insisting on an “inexorable increase” kind of response. But if you think of greenhouse gases reducing the ability of the planet to shed excess heat, then I don’t see why a step-change response centered around major El Nino’s isn’t an entirely appropriate model consistent with AGW and increased C02.
At least it would make a lot more sense to me than the current models and their “inexorable” tuning.
Bob Tisdale says:
August 11, 2011 at 3:29 pm
“And this is why I present the processes that cause the upward shifts.”
That is what separates your scientific and lively work from their Gaia models and magical statistics. We are investigating natural processes (in addition to radiation) and someday we will have the physical hypotheses that describe them fully.
Bob Tisdale-I have read many of your posts on this subject. I have to say that I am not sure you have demonstrated that the step changes can be distinguished from decaying, non-additive spikes overlayed on a temporal trend. I’m not saying that your interpretation is wrong, just that I am not convinced (but quite willing to be so, if you can point me to some arguments I may have missed) and so I think there is still room for the alternative. From the temperature data, the two interpretations look identical. Can you explain why you think one is really more valid than the other?
There were also major ENSO events starting in 1972 and 1982, yet these do not show up in the analysis. Why are these ignored, while the others in included? In fact, sources I looked at consider the 1982 event as stronger than the 1986 event, yet you select the 1986 date instead.
I would like to see some sort of relationship between the size of the events and the size of the change.
Satellite data is telling a different story: click
Satellite record with trend: click
The Holocene: ΔT, ΔCO2: click
Trend, 1979 – 2010 temperature anomalies: click
Many more charts at http://www.climate4you.com
Jens;
some of your statements are a bit confusing because of over-use and misuse of commas. Please study the rules in English grammar for them; they are not just decoration!
The ENSO-step changes are not “incompatible” (fave IPCC weasel-word) with AGW, but constrain CO2 sensitivity to very low (virtually irrelevant) numbers.
On the subject of ENSO… how’s Dr Hansen’s super El Nino looking this year?
Synthesizing information…
Has everyone forgotten this?
http://www.appinsys.com/GlobalWarming/ClimateRegimeShift_files/image005.jpg
From here:
http://www.appinsys.com/GlobalWarming/ClimateRegimeShift.htm
—
Some of the nasty comments directed at Jens Raunsø Jensen are based on patently untenable assumptions. Thanks to Jens Raunsø Jensen for providing a stimulating contribution. Best Regards.
“3. Regional and global temperature anomaly curves are “apples and oranges”, as they average over locations differently influenced by natural processes and in different states of the climate system. There is a need to emphasise more on the analysis of local temperature curves.”
Sure, but not just in isolation since none of them are independent of one another, as emphasized by Tomas Milanovic at Dr. Judith Curry’s blog Climate Etc.
The biggest bottleneck in the climate discussion, by far, is misconception of spatiotemporal variability, particularly interannual spatiotemporal variability.
Regards.
Thanks for all the comments
to Andrew at 11:00:
As I mention in the post, I am aware that eg. a perfect straight line with a trend will end up with step changes. Thats why the main significance of the analysis lies in the fact that step changes are physically supported by the simultaneous occurrence of major ENSO events without making a priori assumptions to that effect. This does not preclude a presence of an albeit relatively weak underlying net temperature trend..
to Tim Folkerts at 5:54:
Thanks for bringing this point up. I did not ignore the other ENSO events you are referring to, I made no a priori assumptions of steps. I only note that it is hardly a coincidence that the significant steps coincide with the most significant ENSO events of the period. I did not speculate on what happened at the other events. And pls notice that this is not a climate model.
to Brian at 6:59:
Thanks for reminding me of the commas, shall keep that in mind. I agree that step changes are not incompatible with AGW and the presence of an underlying trend (I do indicate that in the post). But if the step changes have the significance that I (and others) suggest, then something must be wrong with the IPCC models as I discuss in the post..
to Poul Vaughan at 9;18:
thanks for a timely reminder of Appinsys.com, that site has also inspired me.
best … jens
jens;
I was hardly recommending or supporting the AGW thesis! I was merely highlighting how feeble and deceptive a word “compatible” is.
My judgment is the human-CO2-caused-warming is so small that it is properly described as “negligible”, meaning
A couple of points about this analysis:
the deviations of the data from the steps your are suggesting are often larger than the steps themselves. To this level of correlation one could fit any number of forms to the data. While I don’t see it as incorrect , I do not find it persuasive and hence any conclusions that follow are similarly lacking.
In view of the intervals of approx 10 yr you could also fit some cyclic or solar pattern on top of a linear increase and get a similar quality of correllation. I agree that you have identified a regular change on top of the overall rise but , I’m not persuaded that it is step-like.
Second point, ocean currents are not a source of energy in the sense of global energy budget, they are mearly a transport medium. That means that if there is a correlation with ENSO it simply shows ENSO modulates the underlying variation, it does not provide a “natural cause” for part of that change.
In so much as El nino/nina reflect upwellings of warmer/cooler waters they cannot be a cause of long term change just a cause of short term variabilty. In fact they could just be modulating a totally AGW trend (though I do not believe that is the case) so the correlation to ENSO does not prove a non AGW component to warming as you seem to be suggesting.
For the record I think climate models are exaggerating AGW by , on average, about 300% , the rest being natural variation primarily due to cloud cover changes as Roy Spencer maintains. The root cause being extra-terrestrial probably as suggested by Henrik Svensmark
“phlogiston”, where are you getting this THC ENSO stuff? I hope oceanographer & occasional WUWT commenter “sky” will address your upthread musings.
jens raunsø jensen wrote (August 12, 2011 at 12:43 am)
“thanks for a timely reminder of Appinsys.com […]”
http://www.appinsys.com/GlobalWarming/ClimateRegimeShift_files/image005.jpg
Solar max interrupts the terrestrial pole-equator semi-annual heat-pump. The flat segments coincide with pump outages. All of the step changes occur when the pump is alternating at high variance. For those wondering why the steps can go either way (up or down): The cycle’s in the variance, not the mean. Changes in the mean are a function of acceleration/deceleration. “Bottom up” spectral analysis techniques that ignore the spatial dimension & scale-dependent time-localized properties of time series will miss the preceding, in part due to the blinding strength of interannual spatiotemporal variation. Complex (as in complex numbers, not as in complicated) “top down” methods can see the pattern clearly even if there are data quality issues.
Step changes in temperature and Arctic sea ice extent can be more than measurement or statistical artifacts. Phase changes in water are step events. For instance when ice melts it changes from a solid to a liquid with no change in temperature but to go from a solid at 32F to a liquid at 32F requires that it absorb a lot of energy. So you’ll see a step change in temperature around that point. It’ll be absorbing a lot of heat with no change in temperature then suddenly it melts and the energy that was driving the phase change can all of sudden start raising the temperature of the water dramatically instead. Same thing happens on the flip side as ice is forming. Water at 32C must give up a lot of heat to become ice at 32F. I’d have to think more about step changes in regard to phase change between liquid and vapor because it usually doesn’t involve boiling which happens all at once but rather in faster or slower rate of evaporation. Evaporation isn’t like boiling in that it can happen at any temperature and only happens in a surface layer just a couple microns deep but it still requires the individual water molecules absorb or give off a lot of heat to make the phase transition.
Answer to Richard Telford at august 11 10:07am
Hi Richard,
thanks for your comment and sorry for delaying my answer.
Numerology! Quite a balloon word in my vocabulary. Is it numerology, when eg. the IPCC applies linear regression to establish trends in de facto non-linear temperature records with “cooling” and “warming” periods? Or is it just a basic violation of the rules of statistics?
I do recognise in the post, that the steps could be a statistical artefact, but the statistical significance of the step model and the physical support from the coincidence with major ENSO events suggest otherwise, does it not?
I have focused on what the observational data (temperature and ENSO) may tell us assuming a step model, and please note that I have not made any firm conclusions. The title ends with ?, and I have only demonstrated “that the temperature increase in the second half of the 20th century could have taken place in steps driven by major ENSO events.” Is that not a valid conclusion, and does it not potentially question some of the “established” science?
I then go on to discuss the implications “if this was indeed the case”, and I end by clearly stating, that the main concern is the relative importance of natural and anthropogenic causes for the temperature changes.
regards
Trading companies should be legally forced to point out what the CO2-effects of their products are.
Pelikan;
Congrats for the most pernicious and stupidest suggestion I’ve ever seen on WUWT. You’ve had stiff competition, but this is the real deal.
Paul Vaughan says:
August 12, 2011 at 5:31 am
“phlogiston”, where are you getting this THC ENSO stuff? I hope oceanographer & occasional WUWT commenter “sky” will address your upthread musings.
Where would you, or your big brother Sky, get the notion that ENSO and THC are unconnected? How would that be possible?
Paul Vaughan says:
August 12, 2011 at 5:31 am
“phlogiston”, where are you getting this THC ENSO stuff? I hope oceanographer & occasional WUWT commenter “sky” will address your upthread musings.
Where I got it from was explained and referenced in the first post. The Bjerknes feedback that lies at the heart of ENSO is a feedback between Peruvian coast upwelling and the trade winds. The Peruvian coast deep upwelling, like all major upwelling sites, are integral parts of THC.
http://stratus.astr.ucl.ac.be/textbook/chapter5_node4.xml
(Figure 5.3, half way down the page)
phlogiston (August 13, 2011 at 4:01 pm) linked to [ http://stratus.astr.ucl.ac.be/textbook/chapter5_node4.xml ] to defend claims of THC-driven ENSO.
A quick in-page text-search reveals instances of neither “THC” nor “thermohaline”.
…but perhaps I’ve misunderstood which THC you’ve in mind.
phlogiston, you pointed to figure 5.3 [ http://stratus.astr.ucl.ac.be/textbook/chapter5_node4.xml#image5x03 ]. I suggest you read here [ http://stratus.astr.ucl.ac.be/textbook/chapter1_node9.html ] to correct your erroneous conflation of wind-driven surface currents & THC.
Paul Vaughan says:
August 15, 2011 at 7:00 am
Both oceanic upwelling and downwelling are parts of global THC. I’m puzzled by your confusion on this.
Why the new interest in oceanography? Why not stick to astrophysical cycles and statistics.