Guest post by Jens Raunsø Jensen
Preamble
Inspired by a statement by Dr. Kevin Trenberth in the e-mails referred to as Climategate 2.0 (#3946 discussed here), it is hoped that climate scientists will have “an open enough mind to even consider” that the global warming of the 20th century could have occurred mainly as abrupt changes in mean temperature linked with natural events. Observational data supports that claim, at variance with the AGW “consensus view”.
Summary
Abrupt or step changes in temperature regime has been the subject of many discussions on this and other blogs and in the peer reviewed literature. The issue is not only statistical. More importantly, any presence of major step changes in mean temperature regime may contradict the claims of the AGW theory and models, i.e. the claims of increasing and accelerating temperature and of human emissions of GHGs being the major cause for the relatively high temperatures in the second half of the 20th century.
In this post, 232 complete and unadjusted GHCN station records are analysed for step changes in the period 1960-2010, and it is argued that:
- Abrupt changes in temperature linked with natural climate events may be widely responsible for the “global warming” during the second half of the 20th century.
- 50% of sample stations have not experienced increased mean temperature (”warming”) for more than 18 years.
- 70% of Europe stations have not experienced warming for more than 20 years.
- The relative role of natural processes in global warming is very likely underestimated by IPCC.
- The global average temperature curve is ”apples and oranges” and is widely misinterpreted using linear trend and smoothing techniques as indicating a pattern of widespread uniformly increasing temperature.
Objective and methodology.
The post is in continuation to my earlier post on the subject (http://wattsupwiththat.com/2011/08/11/global-warming-%e2%80%93-step-changes-driven-by-enso/ ), now including a near-global station level analysis. The post is based on a ppt presentation including additional details given at a researcher’s workshop at University of Copenhagen, 15th November 2011 (http://www.danishwaterforum.dk/activities/Researchers_Day_Climate_Change_Impact_2011.html ).
The objective with this analysis has been (i) to examine the land-based temperature records at station and higher levels for the presence of step changes during the period 1960-2010, and (ii) to assess the implications for our assessment of global warming during that period. Please note that the objective has not been to dismiss a (likely) presence of an anthropogenic warming signal, or to establish a climate model, or to make projections for the future. The issue is step changes in observational data during 1960-2010.
I have used the documented Regime Shift Detection tool of Rodionov (2004, 2006; www.beringclimate.noaa.gov/ ). The results are considered to be statistically robust (ref. the ppt presentation for details on parameter settings and a verification of the assumptions of constant variance and a likely negligible influence of autocorrelation).
The station level data is from GHCN (“after combine”, http://data.giss.nasa.gov/gistemp/station_data/ ) and include ALL stations with a complete record in the period 1960-2010 in broadly defined sampling regions (ref. Fig. 1).
A total of 232 stations were identified, with 54% located in Europe and Russia. The sampling criteria result in wide differences between the “regions” in terms of station number, density and distribution. Also, the “regions” are more or less homogeneous climatologically. However, this is not of material importance for the following discussion and conclusions.
Fig. 1. Distribution of sample stations according to sampling criteria.
Results
Significant step changes are widely found in the T-records and representative examples for 3 “regions” are shown in Fig. 2a-c. The temperature increase in the steps is typically of a size which is comparable to the often quoted global warming during the 20th century.
Fig. 2a. Alaska T-anomaly (n=9). Step, 1977; T-change = 1.5 oC; significance 0.000001
Fig. 2b. Fichtelberg, Europe. Step, 1988; T-change = 1.0 oC; significance 0.00009
Fig. 2c. Malacca, South-East Asia. Steps: 1978, 1990 and 1998; T-change = 0.4+0.3+0.4 = 1.1 oC; significance, 0.0004, 0.0007 and 0.003.
Warming during 1960-2010 was clearly a non-linear process at station level, with the step pattern differing among the “regions”. The global average T-anomaly curve, constructed by averaging across station-level T-anomaly curves, is therefore highly deceptive in propagating a message of near-linearly increasing temperatures, contrary to the actual processes at station level. Thus, the global T-anomaly curve is inherently “apples and oranges” and can not be used to identify a meaningful global AGW trend if the step changes are neglected. Then, the apparent AGW trend will in reality mainly capture the aggregated effect of the sudden step changes (as e.g. in Foster and Rahmstorf, 2011).
The steps are concentrated in few short periods. Disregarding 39 steps after 2005 (considered highly uncertain and “in progress”; 2/3 ups and 1/3 downs), it is found that:
- The steps occur predominantly (58%) in three 3-year periods: 1977/79, 1987/89 and 1997/99 (Fig. 3).
- 72% of all stations, and more than 50% of stations in each “region” (except Arctic), have one or more steps during these periods (e.g. 89%, 56% and 93% of Europe, Russia and South-East Asia stations, respectively; Fig. 4).
- 78% of Europe stations have a step change in 1987/89, during which the major part of the entire warming of the 2nd half of the 20th century apparently took place.
- 2 or 3 steps are common in South-East Asia (especially 1987/89 and 1997/99), but one step only is common in records from Alaska (1977/79), Europe (1987/89) and Russia (1987/89).
Fig. 3. Distribution of step changes by year of change.
Fig. 4. Percent of stations with one or more steps in indicated 3 periods.
Similar step changes are identified in national average records (ref. link to presentation above): US contiguous 48 states (GISS): 1986 and 1998; Australia (BOM): 1979 and 2002; and Denmark (DMI): 1988. The steps in the Global T-records are: Crutem3gl: 1977, 1987 and 1998; GISS L/O: 1977, 1987 and 1998; and Hadcrut3: 1977, 1990 and 1997.
The steps are statistically highly significant. But are they supported by a probable physical cause? The answer must be yes for the majority of steps. The steps occur in a temporal and spatial pattern coinciding with well-documented events and regime changes in the ocean-atmosphere system:
- 1976/77: the great pacific shift from a “cold” to a “warm” mode (e.g. Trenberth, 1990; Hartmann and Wendler, 2005).
- 1987/89 and 1997/99: the two clearly most intense El Niños of the period, 1986/88 and 1997/98, with the intensity here defined as event-accumulated nino3.4 anomalies (NOAA’s ONI index); there were two less intense events in 1982 and 1991, the impact of which was probably occluded by the major volcanoes El Chichon and Mt. Pinatubo.
- A regime shift in NH SST in 1988/89 (Yasunaka and Hanawa, 2005).
- A new regime of constant temperature after the 1997/98 El Niño, i.e. the now widely accepted “hiatus” in global warming.
- Documented step changes and regime shifts in marine ecosystems, e.g. the late 1980s in Europe and in the Japan/East Sea.
- The short-term regionally diverse global impact of ENSO events is generally well-known.
The empirical evidence, from this station level analysis and other sources, is unequivocal: the step changes in mean temperature are likely real and associated with natural events. The physical mechanisms remain to be understood, and this is certainly not to claim, that ENSO events are the only elements of the natural cause-effect chain.
It is therefore concluded, that the major part of the temperature change (global warming) in the 2nd half of the 20th century occurred as abrupt changes in mean temperature associated with natural events in the ocean-atmosphere system. Still, a warming/cooling trend – albeit relatively small compared with the step changes – could of course be hidden by the regime change model. But it seems inconceivable, that steadily increasing CO2 levels could be responsible for the major sudden changes observed as e.g. in Alaska in 1977, Europe in 1988 and South-East Asia in 1998. In principle, the natural events and step changes could have been amplified by human caused warming, but this is currently pure speculation.
Implications when accepting the presence of steps
“Increasing temperature and accelerated warming” : this study does not support general statements like that. The bulk of the “global warming” has likely taken place in abrupt steps, and 50% of the stations analysed has not experienced any significant warming for more than 18 years (Fig. 5). In Europe, 70% of the stations have not experienced significant change in mean temperature for more than 20 years.
In South-East Asia, the median value is 13 years as many stations here also experienced a step change in 1997/98 (Fig. 4).
Fig. 5. Years of constant T-mean prior to 2010. Box-Whisker plot, 1st and 3rd quartiles. (note: uncertain up and down step changes during 2006-2010 are disregarded).
Challenging the IPCC consensus view, i.e.: “Most of the observed increase in global average temperature since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse-gas concentrations”. However, the finding above, that abrupt changes linked with natural processes likely account for most of the increase in temperature during 1960-2010, contradicts the IPCC claim regarding the relative importance of natural and human causes. Thus, when IPCC (AR4) can only reproduce the T-curve by including GHG effects, then logically
- either the IPCC GCM models do not adequately model the natural processes of high significance for the temperature variations (there is still low confidence in the projection of changes in the ENSO variability and frequency of El Niños, ref. the recent SREX-SPM IPCC report),
- or/and the IPCC has overestimated the climate sensitivity to CO2 changes by eg. attributing natural temperature increases to CO2-induced feed-back processes.
In either case, the relative importance of natural processes for the T-changes has likely been underestimated by IPCC.
Conclusion
This study has established that step changes in land-based temperature records during 1960-2010 are common and very likely real and linked with natural climate events. The step changes are statistically highly significant and with a systematic yet regionally diverse pattern of occurrence coinciding with major climate events and regime shifts. This finding has far reaching consequences for our analysis of climate records and for our assessment of global warming.
Thus, although many different statistical models can be applied to explore the pattern of T-change, the presence of step changes invalidates the widely used statistical techniques of linear trend and smoothing as means of identifying the pattern of temperature variation during 1960-2010.
Furthermore, the step changes account for the main part of the temperature changes during the 2nd half of the 20th century. The logical consequence is that natural processes have been the major cause for the temperature change during this period, leaving a secondary role to other causes such as the anthropogenic greenhouse effect.
Thanks for the many comments and suggestions. Being back from work, here is my response:
JT, Jan05 6:17 am: I do agree that the “natural processes” could have been influenced by an anthropogenic warming, but find that idea currently speculative as I mention in my post. Ref also Pamela Gray at 6:41 am
Gary, Jan05 6:19 am: pls. consult the reference link I have provided to the statistical tool I have used.
Leif Svalgaard, Jan05 7:33 am: you ask why the steps are always up? Why not? Pls. note that I am only concerned with the period 1960-2010.
R Gates, Jan05 7:52 am: I disagree with your assessment that Foster and Rahmstorf have factored out the “natural variability factors”; Bob Tisdale in his recent post on the subject provide insight on this issue.
A Physicist, Jan 05 8:18 am: I disagree completely with your preamble that models like Foster and Rahmstorf are simpler than the regime step change model. Also, as I tried to make clear in my introduction, this analysis is not an attempt to establish a climate model with predictive capability, but simply an attempt to let the observational data tell us what the pattern of temperature change during 1960-2010 was like. That pattern is adequately described as consisting of abrupt changes in mean temperature regimes.
Steve Garcia, Jan05 8;23am: the steps around 1987/89 and 1997/99 are also supported by independent published studies, a few of which I mention in the post.
Rob Potter, Jan05 8:35am: as I have mentioned, I am not concerned with the temperature pattern outside the period of “global warming”, only with the period 1960-2010. This is not an attempt to develop a climate model.
Steveta_uk, Jan05 9:32am: the significance of the trends during the “flat” periods are dubious due to short time periods and/or the influence of step change processes, and I would discourage that these short term variations be summarised in trends.
Steven Mosher, Jan05 12:35pm: What problem, “sparky”? the data set I have used is not old or to my knowledge corrupted significantly by the “combine” procedure; pls be more specific if you have evidence to the contrary. Regarding your suggestion to analyse US data: as I mentioned in the post, I have done the analysis also for US contiguous 48 states with a similar result (ref also the presentation I link to), clearly indicating what would happen if I were to analyse station level records in the US (which I am not).
BTW, what is your view on the subject of the post: are abrupt changes an important feature of the temperature records of the 1960-2010?
E M Smith, Jan05 1:28pm: I agree with your concern over the true origin of many T-records, but having inspected all the records I have used I do not think that many of the (relatively large) steps in my analysis (complete records only) can be artefacts of splicing. I did delete a few potential records from my analysis on a suspicion of homogeneity problems.
Jan de Ruiter, Jan05 2:21pm: pls refer to the link in my post for details on the statistical tool; the significance you refer to is the significance (probability level) for accepting the HO hypothesis that there is no regime change at the change point – basically a t-test.
Ian H, Jan05 4:40pm: you are unconvinced, ok. Try to reconsider the number of station level temperature curves that exhibit the step change pattern and the coincidence with documented physical and biological changes in the ocean-atmosphere system.
Regards, …. jens
In his posting at 8:35am. Rob Potter brought up a point that deserves further comment. He wrote: “…..averaging across very large geographic regions (and using such averages to fill in places where the data is not available) really is losing most of the information.” (I believe that some data are “averaged” over 1200 km.)
I live in New Brunswick, on the E coast of Canada. Cradled to our E is Prince Edward Island, and hanging off our SE extremity is the peninsula of Nova Scotia. We get weather forecasts covering all three provinces, and the conditions can be several degrees and several inches/cm of snow different, all within a distance of, say, 200 km or 200 miles. If our readings can be so different over such (relatively) short distances, how much can we trust data from 1200 km away? (We have the complication of large bodies of water near or around us, and that has a pronounced effect.)
IanM
“The relative role of natural processes in global warming is very likely underestimated […]” / “This study has established that step changes in land-based temperature records during 1960-2010 are common and very likely real and linked with natural climate events.”
“very likely” is putting it way too collegially. I would suggest replacing misdirected loyalty to severely misguided colleagues with loyalty to overpowering natural truth. Nature mercilessly crushes the abstract belief systems of misguided colleagues.
“The empirical evidence, from this station level analysis and other sources, is unequivocal: the step changes in mean temperature are likely real and associated with natural events.”
Again, “likely” suggests possible willingness to be a voluntary victim of natural correction. Everyone: Please see Judith Curry’s article on error cascades: http://judithcurry.com/2012/01/05/error-cascade/ .
It will be interesting to see if the mainstream risks “double or nothing” by continuing to push an abstract solar-terrestrial narrative that is MERCILESSLY contradicted by observational data. At some point the brighter leaders in the mainstream community should realize that even if they get wool over eyes temporarily, there’s no avoiding eventual bust. The longer the delay in narrative correction, the more damaging will be the height from which the fall occurs. The damage potential isn’t increasing linearly; it’s increasing EXPONENTIALLY. I soberly hope that the brightest academic leaders have paused to consider this (and the implications, including severe costs to society & civilization).
Sincerely.
–
Moving on (from forest-level-view) to some more technical considerations (i.e. some tree-level-views)…
“[…] the presence of step changes invalidates the widely used statistical techniques of linear trend and smoothing as means of identifying the pattern of temperature variation during 1960-2010.”
It doesn’t invalidate the techniques, but I can agree that some parties exercise grossly insufficient interpretive care. I advise those careless parties to diagnostically explore a MUCH wider range of stats, keeping in mind that different stats have different properties. I also sternly caution against the hazards of making unconscious assumptions as a function of bad cultural habit (e.g. as happens notably in the fields of economics, physics, & mathematical statistics).
Compare the following:
1. http://wattsupwiththat.files.wordpress.com/2012/01/2d6nxhj1.gif
2. http://wattsupwiththat.files.wordpress.com/2011/12/image10.png
Lesson for those who expect global average temperature to follow the solar cycle:
There’s such a thing as spatiotemporal VARIANCE (and other moments).
In the field of advanced physical geography there are pockets of awareness of the need to explore the variability of parameter estimates as a function of scale. Those carefully taking advice from the enlightened few can learn something quite interesting about QBO-timescale coherence in the early 1970s.
I can recommend the following article to stimulate new perspective on old surroundings falsely assumed to be “well-understood”:
Lilly, J.M.: & Olhede, S.C. (2009). Higher-order properties of analytic wavelets. IEEE Transactions on Signal Processing. 57(1), 146-160.
http://www.jmlilly.net/papers/lilly09-itsp-cp.pdf
See particularly Figure 6 on p.12 to foster a generalized view.
“78% of Europe stations have a step change in 1987/89, during which the major part of the entire warming of the 2nd half of the 20th century apparently took place.”
Vincent Courtillot has warned about this. It’s encouraging to witness multi-track awareness convergence.
This graph is also beautiful:
http://wattsupwiththat.files.wordpress.com/2012/01/11llqg41.gif
(I hope readers have noticed that Jens has the geography organized roughly by latitude.)
Thanks for these important contributions Jens:
http://wattsupwiththat.files.wordpress.com/2012/01/11llqg41.gif
http://wattsupwiththat.files.wordpress.com/2012/01/2d6nxhj1.gif
Best Regards.
Leif Svalgaard says:
January 5, 2012 at 7:33 am
Why are the “steps” always up?
Why was the great climate shift of 1976 up.
Now come on Latitude, not fair, you’re not supposed to lift the curtain and show temperature data prior to 1880.
It’s interesting to note the lack of correlation between CO2 and Temperatures.
@Jens Raunsø Jensen
“there were two less intense events in 1982 and 1991, the impact of which was probably occluded by the major volcanoes El Chichon and Mt. Pinatubo.”
More likely that 1982/3 El Nino was so strong due to a response to the cooling from the stratospheric aerosols. The cooling driving the other El Nino`s is due to falling solar wind speeds. What this means is that a major step up such as 1976/7 is actually rooted in the 1973-76 La Nina, when solar wind speeds were continuously high and were warming the oceans more, but is not until the SW speed has started to fall, and the trade winds drop, and the Ekman pumping of the equatorial Pacific ceases to produce an El Nino episode, that we see the full effects of the temperature rise.
I think the steps are due to sun cycle activity.
I have a graph here for Tandil. (southern Argentine)
http://letterdash.com/HenryP/de-forestation-causes-cooling
Look at the minima (green line)
It reaches its lowest point in 1984, then 1995, and then 2007,
corresponding with sun cycles?
Steven Mosher: If you want to do regime shift detection ( I used that package back in 2007-2008) I would
suggest that you
1. Not get your data from the GISS site, but go directly to the source: Ghcn monthly, or better
Ghcn daily.
2.. Not use data where stations have been “combined” . Either use raw or homogenized
3. Have a look at some of the better struc change packages out there ( see Cran )
4. look at the US records as well.
I for one hope that jens raunsø jensen takes that advice. The analysis that he reported here is informative, and it presents a good possibility about the climate system, namely that gradual accumulations of heat in the system produce step changes in many locations, where the step changes are driven by increased energy flows in the many naturally occurring and identifiable processes. Nonlinear dissipative dynamic systems with fluctuating inputs can behave that way. His analysis is completely independent of any particular hypothesis about mechanisms causing the increase in global spatio-temporally averaged temperature: it neither supports nor undermines the hypothesis that the increased temperature is caused by increased CO2 in the atmosphere. As written, it makes no predictions about the future, except that if mean temperature continues to increase there ought to be more identifiable step changes in temperature records of particular recording sites: in that, it is analogous to statistical modeling of radioactive decay, where the aggregate decay rate is exponential, and where each atom decays discretely but unpredictably; there are other macro stepwise processes, such as animal learning, where each animal learns a task at a particular trial, but the mean performance of the animals is gradually increasing across learning trials.
jens raunsø jensen says:
January 6, 2012 at 9:36 am
Those are good responses to mostly responsible comments. I want to thank you for your work (caveat some problems pointed out by others) and I hope to read a followup. Arguments that you are wrong are generally inadequate; I am skeptical, but my curiosity has been stimulated.
Leif Svalgaard says:
January 5, 2012 at 7:33 am
Why are the “steps” always up?
It would be interesting to see whether any of these steps correlate with the mass extinctions of “cooler” weather stations, and/or “upgrades” in measuring equipment.
@Jens Raunsø Jensen
With all due respect, I am afraid that very few of your opponents will lose many seconds of sleep over this. If you try to link abrupt shifts to ENSO influence while rejecting a strong underlying linear forcing/trend, then you obviously should expect the overall trend 1960-2010 to be flat(ter) in an analysis like Foster & Rahmstorf´s which removes the ENSO signal – and quite to the contrary, they find a strong and much clearer linear trend. Whether you agree or disagree with the overall conclusions of F & R: How do you reconcile this?
And besides, your reply to Leif Svalgaards criticism:
Leif Svalgaard, Jan05 7:33 am: you ask why the steps are always up? Why not? Pls. note that I am only concerned with the period 1960-2010.
appears to be a complete non-answer. Surely you are aware that there has been quite a few instances of both El Niño and La Niña in your selected period, right? Are you seriously trying to argue that ENSO/El NIño can cause upward abrupts shifts, while ENSO/La NIña are simultaneously unable to cause similar cooling? That would require some serious rewriting of presently acknowledged oceanic physics (not to mention, of course, why this phenomenon apparently failed to exert its influence during e.g. 1860-1910 or other 50-year cycles of overall cooling). And as far as I´m concerned, there has been no trend in ENSO influence at all over your timeframe:
http://cses.washington.edu/cig/pnwc/aboutenso.shtml
Overall, your argument suffers from the same problem as has been pointed out at many other occasions where people have tried to find “stepwise abrupt shifts”: There are no physically supported explanations behind your reasoning, just handwaving and appeals to plausibility without too much afterthought. Do you honestly hope to come up with serious challenges to the mainstream climate science, or are you merely happy to provide a little entertainment for gullible and/or not too insightful members of the choir?
The latter is, in my opinion, a little sad for someone claiming to do science. Surely, it is well below the usual standard at the University of Copenhagen that apparently presently funds both you and me.
I think that both scientists and skeptics agree that the world’s climate is a noisy, variable system. This analysis does not differentiate between a stepwise mechanisms and a consistent linear increase (as expected from increasing GHG) coupled with natural variability. This post shows why peer review is needed to evaluate alternative hypothesies.
Christoffer Bugge Harder, Jan08 4:33pm:
Your comments seem to rest on the assumption that I am presenting a climate model. As I have emphasised time and again (see also post), this is not a climate model, but an attempt to clarify the pattern of temperature change during the period of global warming 1960-2010 based on an empirical analysis of the station-level observational data using a documented and published statistical method. Next, basic implications of the pattern are discussed. In my world, this is a perfectly valid scientific undertaking.
The observational data shows beyond any reasonable doubt that abrupt changes may account for the major changes in temperature during that period. Furthermore, these regime changes coincide with major documented events in the ocean-atmosphere system as exemplified by ENSO. Furthermore, the regime changes are widely documented in independent climate and ecosystem studies published in the peer-reviewed literature (see examples in post). Do you disagree with that?
Pls. note that I make it explicit in the post that I do not see ENSO as the only element in the cause-effect chain. I have no further speculations to offer as to the mechanisms and the relative roles of Nino and Nina, especially not for periods outside 1960-2010 as you ask for. Again and again, I am not discussing a climate model, pls. focus on the objective of the analysis.
Finally, read the preamble and ask yourself if you have really read the post with a scientist’s open mind. And if you want to continue the dialogue with me, then please refrain from using abusive ad hominem statements.
Regards ….. jens
Dear BillD
I would like to ask you to read my report
http://www.letterdash.com/HenryP/more-carbon-dioxide-is-ok-ok
and let me know what you think of it.
As far as peer review is concerned:
I so much liked this post by Craig Goodrich here on WUWT (I am sure he does not mind if I quote him again):
I am sick to death of their rote yapping about “peer review,” when they have perhaps irremediably corrupted the process, and when the point of science was never “peer review” per se but complete openness as to methods and data — which they have steadfastly, almost neurotically, refused to allow. I am nauseated when I hear their “oil funding” chorus, when Greenpeace and the WWF have each received more than two orders of magnitude more funding from corporations than all the free-market think tanks combined — let alone the skeptical science community.
But what makes me really sick is the realization that the $100 billion or so wasted on “climate science” — not quite yet an oxymoron, thanks only to Lindzen, Christy, our own Willis, and a small brave band of real scientists — could have bought an insecticide-impregnated mosquito net for every bed in Africa and South Asia, plus enough DDT to control mosquitoes in swamps near populated areas, with enough left over to keep NASA’s Mars program viable.
But instead of eliminating malaria and keeping mankind’s restless ambition alive, thanks to the warm-mongers we spent the money gazing at our global navel hoping to find the Global Warming Fairy, while at the same time utterly devastating millions of acres of wildlife habitat and peaceful countryside with useless industrial wind turbine phalanxes — which generate no actual power but lots of tax breaks and subsidies — in the quest for some delusional “renewable energy,” clearcutting rainforests for palm oil and fraudulent “carbon sinks,” and doubling world food prices by supporting ethanol production.
So having worked as hard as ever they can to destroy what natural environment remains in the developed world, and to murder as many as possible through starvation and disease in the undeveloped world, these wonderful people preen themselves and vaunt their moral superiority as “humanitarians” and “environmentalists.”
—
Sorry, I had to go get my barf bag.
—
I realize that WUWT, CA, and the rest of the climate realist blogosphere attempt to maintain a civilized level of objective scientific discourse, free from the diatribes that pervade warmist rhetoric. But sometimes it is necessary to vent, and my infrared iris opens up…….
If I’m reading this right, you are modeling this as separate step changes in n=232 station records, with (from eyeballingfigure 3) about 2-3 steps per series at the best fit times.
Doesn’t this methodology ultimately end up fitting about n*5 parameters, or about 1400 unconstrained coefficients in the 232 multiple-step-change models?
The claim that the presence of step changes, rather than a linear increase, in T (which he hasn’t even shown) somehow contradicts AGW is absurd. Tamino has posted a good debunking of this claptrap.
http://tamino.wordpress.com/2012/01/09/steps/#more-4606
I don’t buy into the “step change” idea. To me the argument presented at Open Mind is pretty convincing with regard to the perils of this analysis: http://tamino.wordpress.com/2012/01/09/steps/
@ur momisugly Andy and Utahn – “Tamino” has an agenda – he’d try to “debunk” a straight line made of two points if it was posted here. Heh. Let’s see what Jens has to say.
If we paid attention to Tamino’s way of seeing the world, there would never be any discussion allowed but his. WUWT is about open discussion of ideas like this, “Open Mind” is not.
Hi Anthony
Do you perhaps know if anyone ever measured the change in humidity over the years?
After looking at the daily average readings from about 20 weather stations all over the world I am finding a change of about -0.02%RH per annum.
http://www.letterdash.com/HenryP/henrys-pool-table-on-global-warming
So, if this estimate is not far from the truth, like my estimate on the means is not far off from what Spencer & others get, then the average global humidity is now about o.75% RH lower than it was 37 years ago.
If I am not mistaken (at 15 degrees C) that translates again to a loss of about 0.1% in absolute humidity.
You see how that compares with the increase in of CO2? (0.01% increase over the last 50 years)
@Jens Raunsø Jensen
to begin with, my comment was not intended as an ad hominem, so sorry for any careless wording and/or offense you may have felt in that regard. And I am well aware that your analysis is not a GCM model (if that is what you gathered from my comment, I must admit that I fail to see how you got that impression). What you are doing is simply to fit a regime shift model from Rodionovs software upon some selected station data – and then you hint at some suggested ENSO link (and some other even flimsier ones) as putative causes for “regimental” warming. Then you use this a basis for arguing that GHGs cannot be primarily responsible for the observed global warming.
However, I honestly do think that your analysis is well below normal, reasonable scientific standards (it certainly would not stand much of a chance passing any kind of fair and serious peer review) and your answers to the fair and well-argued comments you receive are either evasive or leaves the reader with the impression that you don´t understand the criticism. Let me elaborate:
If one tries, as you do, to claim that these putatively ENSO-linked “abrupt shifts” are primarily responsible for the temperature being about 0,7C warmer in 2010 compared to 1960, then I (along with all the peer-reviewed literature on the subject) certainly disagree, yes. As has been shown many times, the temperature pattern 1960-2010 fits very well with an overall increasing trend driven by GHGs, with ENSO, PDO/AMO superimposed upon as short-term (10-15 years) noise signal, either weakening or enhancing the GHG forcing. You do not even seem to be aware that the AWG theory does not even project that the temperatures should rise linearly?
According to the very same peer-reviewed literature you claim to rely upon, which has suggested exactly such models of climate shifts induced by ENSO or PDO – e.g. Keenlyside, Mojib Latif et al. in Science (2008), or Swanson and Tsonis (GRL 2009) – there is zero net positive (or negative) forcing from ENSO/PDO/AMO over time, since the warm and cold phases of PDO/AMO and El Niño/La Niña cancel each other out. Or, to put it simpler, oceans do not “generate” heat, they merely redistribute it. Really, this should be obvious to you just by looking at a simple graph of ENSO oscillations:
http://chartsgraphs.files.wordpress.com/2009/01/giss_enso_sato2.png?w=500&h=565
Both Latif and Swanson themselves has made this painstakingly clear when explaining their findings in order to avoid exactly these kind of common misunderstandings that you are repeating here. Here is Latif, who linked short term-changes to PDO (http://www.spiegel.de/wissenschaft/natur/0,1518,551060,00.html):
(Sorry that I could find an Englisch source, but I´m sure that as a fellow Dane, you read German.)
Thus you do have a major problem in your analysis that the steps are always up (as Leif Svalgard pointed out), since this shows precisely that there must be an underlying external forcing (such as GHGs, solar irradiation etc.) causing the overall warming trend – actually, if you try to link ENSO to data with significant net changes over time, then I fail to understand why analysing e.g. 1860-1900, 1940-75, 1960-2010 or any other comparable interval would matter the slightest to this argument, as you appear to think.
Whether you want to do climate modelling or not: If you are seriously trying to argue that ENSO (or AMO/PDO) influence is able to cause abrupt and permanent climate change, then you would need to demonstrate how this is physically possible, e.g. by identifying some previously unknown oceanic component – or by explaining how you think that oceans could be able to generate heat. (The latter would surely require some rewriting of major foundational physics as well, not to mention a very convincing demonstration as to why these abrupt one-directional upward shifts you think you have identified has not made the planet warm indefinitely. 🙂 You most definitely cannot link the main T-increase to any of these known natural cycles you mention, as has long been well known and documented. Thus, based on this major problem alone, there is no particular reason to explore your “hypothesis” further.
You simply don´t seem to realise this? I´m sorry, but this really is very simple physics that certainly should not bother you, if you think a little more carefully about it.
Furthermore, even just considering the statistics part of your analysis, you surely must be aware that your regime shift tool will be able to find “regime shifts” in just about any kind of data with an increasing trend and some noise? As Grant Foster has shown here (http://tamino.wordpress.com/2012/01/09/steps/#more-4606), dummy data designed artificially to have a perfectly linear trend with red noise is found to have several significant “regime shifts” by Rodionov´s software. Clearly, this is nonsense, and it should not be surprising to anybody having used a “fit model to X” function in a standard statistics package, as I´m sure you have done a number of time. This merely shows that the null hypothesis of no-change is wrong, not that a stepwise model is the best way to describe this change. In fact, he shows that just by using the Akaike criterion for model selection, a two-way linear model subdividing your data for Malacca into a flatlining 1950-75 part and another trending linearly upward from 1975-2010 is superiour to your stepwise model. Thus, even leaving out all the erroneous interpretations of your findings regarding ENSO/PDO links, you fail even to show why your preferred model is superiour.
So finally, having reread the preamble, I have just this to say: As a humble PhD student, I´m certainly trained to have an open mind. But I have also learned to be sceptical of simple model fits, especially if followed by bold interpretations without any supporting physical documentation or justifications. Furthermore, I know that with an ENSO trend of about zero over 50 years, then an interpretation linking warm shifts to warm phases in this period of time requires implicitly ignoring all the equally cool shifts. I think we both know that just leaving out data that do not fit a hypothesis is at best sloppy scholarschip, typically reflecting either a poor understanding of the subject in question or a confirmation bias often resulting in self-delusion. Honestly, I think Trenberth and all his fellow climate scientists would laugh, were they ever to read this, and I also think that you will realise the obvious problems yourself if you try to owe up to your own preamble.
Regards,
Christoffer
Christoffer Bugge Harder says
“fits very well with an overall increasing trend driven by GHGs”
Henry@Christopher
Honestly, looking at the results of maxima, means and minima together, apparent ratio: 7:3:1
which you can only see in my own tables, of summarised results of 20 weather stations,
http://www.letterdash.com/HenryP/henrys-pool-table-on-global-warming
I don’t know how you can possibly figure out that that statement you made can possibly be true.
Come to me with test results that prove that minima are rising, pushing up means, and we will talk again.
Well, Henry,
I certainly agree that comparing nighttime and daytime temperatures would constitute an excellent test of the GHG fingerprint. But hey, let´s take a look at the global result, rather than just 20 random (or carefully selected?) weather stations, shouldn´t we?
http://www.nicholas.duke.edu/thegreengrok/Members/fig32.jpg
Obviously, the ratio since 1950 is 2:1 in favour of the nighttime temperatures.
(Let me hazard a couple of guesses on the response: You don´t trust pre-1975 data for some unspecified reason/you don´t trust post1975 data for another unspecified reason/the nighttime temperatures are subject to significant UHI/daytime temperatures are subject to even larger uh-oh no smaller UHI or whatever/you only trust stations close to Northern Ireland/Hockey stick fraud Michael Mann is bald and so is Gavin Schmidt/all surface data are manipulated and the BEST team is part of the plot/yeah, but…..AL GORE!)
Well, Henry,
I certainly agree that comparing nighttime and daytime temperatures would constitute an excellent test of the GHG fingerprint. But hey, let´s take a look at the global result, rather than just 20 random (or carefully selected?) weather stations, shouldn´t we?
http://www.nicholas.duke.edu/thegreengrok/Members/fig32.jpg
Obviously, the ratio since 1950 is 2:1 in favour of the nighttime temperatures.
I see the juvenile CBH is trolling WUWT again.
Hi Christopher
Interesting challenge.
But it is not clear from the graphs that you quote from which station(s) they were collected?
It reminds me vaguely of an interesting controversy I encountered during the collection of my data:
http://letterdash.com/HenryP/what-hanky-panky-is-going-on-in-the-uk
Apart from the above, where I wanted to see what is going on with the data coming from Gibraltar,
I can assure you that I did select my stations randomly.
Continuous daily data from pre 1975 are indeed difficult to find from randomly selected weather stations.
Christopher says:
and the BEST team is part of the plot
Henry@Christoper
I remember that the BEST results only show the mean average
I thought at the time when the controversy here raged, that those results were rather useless (to me).