by Judith Curry
“Our results also serve to highlight the importance of Atlantic multidecadal variability in mediating the rate of global warming, and they suggest that these variations deserve more explicit consideration in twentieth century climate simulations and in attribution studies based on recent observations of the rate of change of [global mean surface temperature]. — Wu et al. (2012)
On the time-varying trend in global mean surface temperature
Zhaohua Wu, Norden E. Huang, John M. Wallace3, Brian V. Smoliak and Xianyao Chen
Abstract. The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s. In Wu et al. (2007) we showed that the rapidity of the warming in the late twentieth century was a result of concurrence of a secular warming trend and the warming phase of a multidecadal (~65-year period) oscillatory variation and we estimated the contribution of the former to be about 0.08°C per decade since ~1980. Here we demonstrate the robustness of those results and discuss their physical links, considering in particular the shape of the secular trend and the spatial patterns associated with the secular trend and the multidecadal variability. The shape of the secular trend and rather globally-uniform spatial pattern associated with it are both suggestive of a response to the buildup of well-mixed greenhouse gases. In contrast, the multidecadal variability tends to be concentrated over the extratropical Northern Hemisphere and particularly over the North Atlantic, suggestive of a possible link to low frequency variations in the strength of the thermohaline circulation. Depending upon the assumed importance of the contributions of ocean dynamics and the time-varying aerosol emissions to the observed trends in global-mean surface temperature, we estimate that up to one third of the late twentieth century warming could have been a consequence of natural variability.
Full manuscript available online [here].
Excerpts from the Summary and Discussion:
In the previous sections, we have presented the results of EEMD analysis, which indicate that the secular warming trend during the 1980s and 1990s was not as large as the linear trends of the observation-based global-mean surface temperature (GST) estimated in AR4 (IPCC 2007); and that the unprecedented rate of warming in the late twentieth century was a consequence of the concurrence of the upward swing of the multidecadal variability, quite possibly caused at least in part by an increase in the strength of the thermohaline circulation, and a secular warming trend due to the buildup of greenhouse gases. We estimate that as much as one third the warming of the past few decades as reported in Fig. TS.6 of the Summary for Policymakers of AR4 (IPCC 2007) may have been due to the speeding up of the thermohaline circulation. Other researchers have reached a similar conclusion: Keenlyside et al. (2008), Semenov et al. (2010) and DelSole et al. (2011) on the basis of numerical experiments with a climate model capable of representing the variability of the Atlantic meridional overturning circulation; Wild et al. (2007) on the basis of long term trends in the character of the diurnal temperature cycle at the Earth’s surface; and Swanson et al. (2009) based on an analysis of the partitioning of the GST trends using linear discriminant analysis. Furthermore, by analyzing the temporal derivatives of ST, we have demonstrated that the secular warming trend in GST has not accelerated sharply in the past few decades.
| 1. |
The time derivative of ST of GST in the later twentieth century, as estimated by EEMD, is subject to future adjustments depending on how rapidly the atmosphere warms over the next decade or two.
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| 2. |
The contribution of aerosol forcing to ST remains uncertain, as are the relative contributions of aerosol forcing and Atlantic MDV to the observed MDV of GST.
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These caveats notwithstanding, the results presented here further substantiate the reality of human-induced global warming, as evidenced by the similarity between the secular trend curve recovered from EEMD of GST and the buildup of atmospheric greenhouse gas concentrations and by the near-global extent of the temperature increases associated with the secular trend. Our results also serve to highlight the importance of Atlantic multidecadal variability in mediating the rate of global warming, and they suggest that these variations deserve more explicit consideration in twentieth century climate simulations and in attribution studies based on recent observations of the rate of change of GST.
JC comment: On the Trends, Changepoints, and Hypotheses thread, I described three hypotheses that explain 20th century climate variability and change:
I. IPCC AGW hypothesis: 20th century climate variability/change is explained by external forcing, with natural internal variability providing high frequency ‘noise’.
II. Multi-decadal oscillations plus trend hypothesis: 20th century climate variability/change is explained by the large multidecadal oscillations (e.g NAO, PDO, AMO) with a superimposed trend of external forcing (AGW warming).
III: Climate shifts hypothesis: 20th century climate variability/change is explained by synchronized chaos arising from nonlinear oscillations of the coupled ocean/atmosphere system plus external forcing (e.g. Tsonis, Douglass).
Wu et al. fall squarely in II. Their conclusion that as much as one third of the warming in the last few decades of the 20th century provides further weight to arguments that multi-decadal natural internal variability needs to be included explicitly in attribution assessments. The error bars on the ‘one third’ need some investigating, and there are additional modes of natural internal variability beyond the Atlantic Meridional Overturning Circulation. More investigations along these lines (both II an III) are very much needed.
Roy Spencer made some early efforts at II on his blog a few years ago, and recently we have seen some blogospheric efforts by Vaughan Pratt and Girma. I personally think that III is a more robust hypothesis than II, but working on II can help us with III.
Based on the abstract, Wu et al. (2012) appear to have missed the multidecadal variability of the North Pacific sea surface temperature anomalies, which are similar in magnitude to those in the North Atlantic, but slightly out of phase with the AMO. The following graph compares detrended North Pacific sea surface temperature anomalies (NOT the PDO) to the AMO, which is presented as detrended North Atlantic sea surface temperature anomalies:
http://i56.tinypic.com/t9zhua.jpg
The graph is from this post:
http://bobtisdale.wordpress.com/2010/09/03/an-introduction-to-enso-amo-and-pdo-part-3/
Thanks for the link and the post.
E.M. Smith has an insightful analysis of the reasons why government policies are now directed by “clueless academics”
http://chiefio.wordpress.com/2012/05/23/practically-dis-educated/
Almost every major field of study has been seriously compromised by the misuse of federal research funds to promote government propaganda since 1945.
http://omanuel.wordpress.com/about/#comment-70
The current crop of academics are indeed clueless about basic principles of science needed to save society from impending collapse.
With kind regards,
Oliver K. Manuel
Former NASA Principal
Investigator for Apollo
http://www.omatumr.com
The authors of this and similar articles seem to be unaware that the model they need to compare their modelling to is that of multidecadal ocean oscillations PLUS ongoing warming from the Little Ice Age, because the latter has been presented over the longer time frame, from the middle to late 17th century (1650-1680 AD), while these other articles, arguing from a biased belief in the carbon dioxide “greenhouse effect”, only go from 1900 (or 1850) onwards. So the ocean oscillations theory has already better explained the global mean surface temperature (GMST) variation since the 17th century.
The “wattsupwiththat” website ran a post on this topic back around July 25, 2011 (I don’t have a link for it at hand), to which I posted the following comment (ignore references below, specific to the article presented at WUWT, unless you can look it up for yourself from the date I’ve given for my comment):
“There is no physics at all in this, any more than in the IPCC-supported modelling. 1) there is no greenhouse effect of atmospheric warming due to increase in CO2:
Venus: No Greenhouse Effect
so there is no mechanism for AGW. 2) The satellite tropospheric and sea surface (SST) data differ from the HADCRUT surface temp anomaly, with the present temperatures of both right at the same level as in 1991 (while Fig. 1 here shows an increase over 1991 of about 0.25 °C). This also brings up the subject of 3) possible deliberate positive adjustments in the HADCRUT data, in the last 20 years at least. 4) The use of the Beer-Lambert law, behind conclusion no. 1 in the article, is problematic, since that law is valid only in the absence of multiple scattering, and any ‘greenhouse gas’ IR in the atmosphere is generally scattered many times over (it is simply the IR portion of the heat transfer in the atmosphere, which is diffusive, not directed) — yet another fundamental misunderstanding by the ‘consensus’. 5) Akasofu and others touting the multidecadal ocean oscillations theory already claim a 0.5 °C/century rise from the Little Ice Age, since the mid-to-late 17th century, while the modelling in this article shows only about 0.2 °C/century for that effect, so it seems they are underestimating it substantially, and simply giving its contribution to AGW.
I’m sorry, this is more farce, probably done because it allows the ‘lukewarmers’ to claim their 1 °C per doubling of CO2 is ‘true’, or ‘most reasonable’. It is not; there is no greenhouse effect as claimed by the climate ‘consensus’. Period.”
Coming from a physics background myself, I find your hypothesis appealing. But it seems to me that it faces a pretty serious challenge from the emperical data, which shows us that the Earth’s average temperature has, in fact, changed radically over the geological time scale. If the temperature is purely a function of solar irradiation, how could we have jungles on Antarctica at one time and glaciers over Indiana at another? The only answer I can imagine is that solar irradiation has been much more variable than we currently believe.
I’d be interested in testing your hypothesis with additional data. Firstly, you ought to be able to replicate your results with temperature and pressure data from Mars, as well. Assuming those results are encouraging, I suppose we might begin looking for evidence of climate changes on Venus and/or Mars that are synchronized with those on Earth.
Incidentally, another problem I see in your analysis is that it does not account for heat from internal nuclear reactions in the core of the planet. I recall once calculating the amount of the Earth’s temperature that is the result of ongoing nuclear fission, and finding that it was a non-trivial amount (on the order of several degrees). Because that heat is generated in an amount that is proportional to the mass of the planet (presumably, anyway), but is radiated away at a rate proportional to its surface area, Mars should be somewhat cooler than your model predicts.
Climate scientists don’t seem to consider the hot core of earth has anything to to with surface temperatures. I think they have blinkers on. I presume you would agree….
“…. If the temperature is purely a function of solar irradiation, how could we have jungles on Antarctica at one time and glaciers over Indiana at another? The only answer I can imagine is that solar irradiation has been much more variable than we currently believe. ”
I doubt quantity of solar flux has changed much. It seems that with steady amount solar energy coming from the sun, one can have glacial and interglacial periods. I think these largely to do with Milankovitch cycles. And Milankovitch cycles are dependent arrangement of the world’s continents. If the planet were uniform such all land or all water, then these cycles would little effect.
Having the Antarctic where it is, one of the amplifying affect related to Milankovitch cycles.
Solar activity and other factors seem possible that they could have globally affects on cloud coverage, giving global temperature difference in range of 1 or 2 C
So the Little Ice Age wouldn’t be a result of Milankovitch cycles but a combination solar activity, and large volcanic activity:
Mount Tambora in 1815, being the most latest and most significant and known volcanic eruption:
“The eruption caused global climate anomalies that included the phenomenon known as “volcanic winter”: 1816 became known as the “Year Without a Summer” because of the effect on North American and European weather. Agricultural crops failed and livestock died in much of the Northern Hemisphere, resulting in the worst famine of the 19th century.”
http://en.wikipedia.org/wiki/Mount_Tambora
Though the Little Ice Age is said to start earlier than this, and earlier than the long period of recorded low sunspots: Maunder Minimum- 1645 to 1715.
It seems to me that if we another Tambora type event, next tuesday, and had something like Maunder Minimum going on, everyone would expect much cooler climate as result [if not “the end of the world”].
Actually the idea that the observed global surface temperature is made of cycles is not knew and it is at a very advanced stage.
The most important cycles are at quasi 9-yr, 10-11-year, 20-year, 60-year, 115-year, 130-year, ~1000-year. Then there are some super- and sub-harmonics. In particular the global temperature since 1850 can be decomposed and reconstructed using quasi 9-yr, 10-11-year, 20-year, 60-year major cyclicities. In addition, the upward trend since 1850 is due to a millennial cycle + some modulation from a 115-year cycle.
These cycles are all associated to astronomical cycles.
These things are quite extensively discussed in my papers. Look at my web-site.
Thanks, Dr. Scafetta.
It is absolutely incredible that such well known cycles would be ignored by research scientists in climatology.
The same problem extends across almost every field of government science today.
Most of the current crop of “research scientists” have been trained to report findings that will generate more research funding.
In my opinion, the impending collapse of social and economic systems cannot be avoided if we do not quickly find a way to restore integrity to the scientific information that world leaders use to formulate policies.
With kind regards,
Oliver K. Manuel
Former NASA Principal
Investigator for Apollo
We tried to make the model of circular orbits fit the data with massive numbers of smaller “epicycle” orbits. At some point, one begins to suspect that a more elegant solution is the right one. I’ll confess climate is a rather more complex system than orbital mechanics, but I’m still inclined to doubt that this model describes the underlying physical reality.
If the secular trend accounts for nearly a degree and growing and the 65-year oscillation has an amplitude of 0.2 degrees, which should we be more concerned with regarding future impacts? All the studies so far of these 60-year oscillations have not pointed to anything more than 0.2 degrees, which we shouldn’t care about in the context of long-term climate change.
I thought studies such as BEST suggested 0.8 C over 150 years? Am i thinking of combined land/ocean? This study said 1/3 of the changes in the 1980’s to 1990’s was natural, correct? Sorry, just had surgery, not able to verify all this very easily. But if the temp’s went up say 0.3 C in these two decades, then 0.1 was natural and 0.2 was GH gases?? Where does your 1.0 and 0.2 come from? This would only be .2/1.2 or 1/6 or 15%.
Jim D, you seem to claim that the ‘oscillations’ are limited to short-term (~60 years) climate changes. That’s a very extraordinary claim. Without extraordinary evidence we should assume that it does the same at longer-term time-scales too. There’s for sure evidence for that (paleo and historical).
HADCET summers
.009C/decade
http://sunshinehours.wordpress.com/2012/05/14/hadcet-june-july-and-august-trend-for-350-years-is-a-measly-009c-per-decade/
2007 and 2011 were below the long term mean.
It’s a hybrid of II & III, with AGW probably of minor significance and solar variation, unknown, of major significance. We’ll see if the ‘secular trend’ of 0.08 deg C. continues as the sun acts up with its Cheshire Cat sunspots.
========
I haven’t found any evidence of AGW in satellite-era sea surface temperature data, but I’ll keep looking.
Deception in global temperature data is only a minor, but glaring, example of the pervasive dishonesty that has destroyed the ability of world leaders to formulate policies in the best interest of society.
Social and economic collapse are ahead if skeptics cannot quickly find a way to restore integrity to government science!
That is, in my opinion, the most important issue facing the world today.
World leaders do not understand science, and shouldn’t be expected to.
Unfortunately they cannot expect help from the self-serving group of advisors who gave them misinformation – leaders of the United Nations, the US National Academy of Sciences, the UK’s Royal Society, the Nobel Prize Committee, publishers of Nature, Science, PNAS, PRS, etc., and leaders of scientific organizations and mainstream news media.
With kind regards,
Oliver K. Manuel
Former NASA Principal
Investigator for Apollo
http://www.omatumr.com
omanuel says: “Deception in global temperature data is only a minor, but glaring, example of the pervasive dishonesty that has destroyed the ability of world leaders to formulate policies in the best interest of society.”
I also find NO “deception” in the satellite-based sea surface temperature data, So I’m not sure what you’re driving at with this reply to my comment,
I did not mean to imply that satellite sea surface temperature data are deceptive. The AGW scare campaign is not limited to satellite sea surface temperature data.
I.e., “I haven’t found any evidence of AGW in satellite-era sea surface temperature data, but I’ll keep looking” is a very biased approach to observations that is sure to deceive the observer eventually.
omanuel says: “…is a very biased approach to observations that is sure to deceive the observer eventually.”
Please clarify your comment.
Bob, it is biased to “look for” something that is not in the observation..
It is also biased to purposely “overlook” what is in the observation.
“I haven’t found any evidence of AGW in satellite-era sea surface temperature data, but I’ll keep looking,”
Example: The solar neutrino puzzle – far less neutrinos than predicted by the standard model of hydrogen-filled stars – plagued the solar physics community for decades. But they “kept looking” for a solution that would preserved their cherished standard solar model.
There was none, until the actual solution to the solar neutrino puzzle was published in March 2001 [“The sun’s origin, composition and source of energy”, Lunar and Planetary Science XXIX]
http://www.omatumr.com/lpsc.prn.pdf
Within a few months, one hundred and seventy-eight (~178) scientists associated with the Sudbury Neutrino Observatory reported solar neutrinos just oscillate away [Q. R. Ahmad et al. (~180 co-authors), “Measurement of charged current interactions produced by 8B solar neutrinos at the Sudbury Neutrino Observatory,” Physical Review Letters 87 (June 30, 2001)]
http://arxiv.org/pdf/nucl-ex/0106015v2
http://prl.aps.org/abstract/PRL/v87/i7/e071301
In exactly the proportions needed to salvage the standard solar model of Hydrogen-filled stars that Sir Fred Hoyle had proposed in 1946.
http://omanuel.wordpress.com/about/#comment-70
The above events preceded the release of Climategate emails and documents by several years, as did efforts by NASA to hide isotope data from the Galileo Probe of Jupiter that independently showed the standard solar model is wrong in 1995 [O. Manuel, “Isotopic ratios in Jupiter confirm intra-solar diffusion”, Meteoritics and Planetary Science 33, A97, 5011 (1998)]
http://www.lpi.usra.edu/meetings/metsoc98/pdf/5011.pdf
omanuel says: “Bob, it is biased to “look for” something that is not in the observation…”
Bias is blatantly obvious when researchers fail to consider all possible alternatives.
omanuel says: “It is also biased to purposely “overlook” what is in the observation.”
I assume this is a rhetorical add on your part and assume that you’re not stating that I purposely overlook the obvious.
Note to self: Never reply to one of omanuel’s comments in the future.
BOB–LOL. Your comment about oliver made me laugh.
Bob,
Looking forward to your upcoming post (?) on Met Office OHC data.
What exactly does the SST record in the satellite era consist of? (i.e. type and source of measurements). PS I’ll probably be familiar with your sources, but don’t know offhand how to categorize the group you’re referring to.
BillC: The satellite-era sea surface temperature data I’m referring to is the Reynolds OI.v2 dataset.
Hypothesis IV:
Misuse of statistics and arbitrary adjustments to data?
An underlining trend wouldn’t of neccessity have to be forced. There could be an oscillation of the heat tranfer of the THC superimposed on a trend of heat transfer by the THC which we do not yet have the data available to identify.
While not minimizing the importance of understanding the Atlantic multidecadal variability, why not consider the importance of the early 20th century rise which resulted in a 0.45C permanent heating between 1905 and 1940? See my ‘Alternative theory of climate change’ on http://members.iinet.net.au//~alexandergbiggs . Was the IPCC justified in ignoring this?
” I personally think that III is a more robust hypothesis than II, but working on II can help us with III”
I agree. I think that both Tsonis and Douglas missed a shift around 1995 though.
http://i122.photobucket.com/albums/o252/captdallas2/rsstlsoceans1994shift.png
That is a pretty wicked shift in the stratosphere.
http://i122.photobucket.com/albums/o252/captdallas2/rssfrom19945.png
And that is fairly long time with no significant trend. :)
Did I mention that the OHC appears to have peaked?
III.
I’m unfamiliar in climate with any parallel paper along the lines of http://www.biomedcentral.com/content/pdf/cc2948.pdf
Abstract
Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered
variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients.
Those seeking to explain III. could do worse than to develop some similar guide, I think.
Very true Bart R, in a complex system with apparent pseudo cyclic patterns there should be physical mechanisms that explains the cyclic nature. If not, then you are nothing but a cyclomaniac.
Interestingly, there are physical mechanism that explain some of the cyclic variability. Did you know that water vapor has an interesting non-linear feedback? It seems that mixed phase clouds, water and ice, have not only a radiant negative feedback at the right altitude, but they also tend to eat ozone. It is pretty obvious in the Arctic, but Susan Solomon seems to be of the opinion that the impact on the ozone concentration in the tropical stratosphere has a greater than anticipated cooling impact on surface temperature. There is even a possibility that a by-product of the ice/ozone reaction reacts with CO2 at low temperature in the presence of a electromagnetic field. Pretty interesting stuff.
When the oceans are cooler than average, the greenhouse effect is stronger so the only region that would have significant ozone eating going on would be the Antarctic. With the oceans at temperature, the average radiant layer would rise slightly enabling other regions to do some ozone eating.
Pretty remarkable world we live on..
capt. dallas 0.8 +/-0.2 | May 23, 2012 at 10:05 pm |
“Did you know that ..”
Know it? No.
Expect it possible but as yet not well-established and understood? Sure.
Remarkable world indeed.
UAH shows no warming in the 1980-1999 period in question, except for the big ENSO at the end, which presumeably is natural. So the first and fundamental sentence of the abstract is false. There was no warming, except at the tailend, much less unprecendeted warming. They are analyzing something which may well not exist, a boundary layer artifact at best.
If people insist on using surface statistical models to measure atmospheric warming they have to first rectify this contradiction. Atmospheric energy is not a boundary layer phenomenon. AGW is about energy, not surface temperature.
Ignoring real measurements of atmospheric energy, in favor of questionable and abstruse surface measurement statistical models, is the source of the AGW scare. This has been questioned repeatedly. Why then is this rich literature getting richer? Is it because if we accept the satellie measurements the question disappears?
David Wojick | May 23, 2012 at 9:45 pm |
Is this UAH with, or without, correction?
http://www.washington.edu/news/articles/new-research-brings-satellite-measurements-and-global-climate-models-closer
Spencer doesn’t seen too enthralled by the results of this paper. You may want to check his web site to see why.
steven | May 23, 2012 at 10:39 pm |
Spencer doesn’t seen too enthralled by the results of this paper. You may want to check his web site to see why.
I did look at his website! I had no idea he had such a sense of humor.
And then I saw that Spencer was being serious, somehow.
Oh well, it’s still funny to Mosher, for the reasons he states below.
Bart, Steve didn’t adress Spencer’s crtitique. He addressed David’s comment.
Bart, I have no doubt there are problems with the satellite data, but they are dwarfed by the deep methodological problems with the surface statistical models. The satellites are instruments doing what they were designed to do. There is no designed sampling system for surface temperatures.
David Wojick | May 24, 2012 at 9:31 am |
I can grant that there are problems with all the data; as there are three satellite datasets in some degree of disagreement, and the length of their record is so short overall, and we can demonstrate that we collect at least an order of magnitude (probably two orders) too little data to employ for the uses to which it is being put, it’s impossible to make statements of relative inadequacy with much confidence.
The data collection is all pretty insufficient for climate analysis. Which is not much to be wondered at, as it is just an improvised use of weather collection never originally intended for use in climatology, and governments worldwide appear to have recoiled from the duty to bring advancement to monitoring of conditions — one of the few obligations even a minarchist might agree is incumbent on any state — as if knowledge were dangerous to them.
Huh.
1. An honest person looks at all the data. no hiding declines david. So we have two “observations” of the the troposphere. These arent really observations, but rather are data products produced by applying algorithms to sensor voltage. Those algorithms rely on the same physics that tell us more GHGs will produce warming.
2. I see a that a least squares fit for both data products shows a positive trend
http://www.woodfortrees.org/plot/uah/from:1979/to:2000/plot/rss/from:1979/to:2000/plot/rss/trend/plot/uah/trend
If you accept UHA or RSS then you accept the physics used to create them.
That means you accept radiative models because those data products DEPEND UPON radiative physics being correct. That physics teaches us that more C02 means a more opaque atmosphere and a warmer surface.
If you ever took the time to look at the code required to estimate temperature from a sensor brightness you would see code that lies at the heart of every GCM
Steve,
Just curious (and I am not doubting your logic which as always is compelling) but if you look at the graph you posted what do you really see – just sit back and look with your undoubted critical eye? Are the “trend” lines that you have added what really “jumps” out at you? For me the “spike” around 1998 it the thing that “jumps” out. Take that away and all I see is a process in “control” – not much happening just alot of noise. For me understanding this spike will inevitably lead to a much greater understanding of what is happening. Of course a lot more data would always help.
BTW – always enjoy reading your frank and direct posts!
Cheers
Mosher, the physics teaches us no such thing, because the physics includes whatever exists, including feedbacks and other forcings. So we rely on observations, of which the satellites are far superior to the surface statistical models. The satellites tell us that the ghg warming is not occuring. In fact the warming looks like a small abrupt event, probably due to a change in ocean circulation.
You cannot derive AGW from the fact that the satellites use radiative physics, when they In fact show no ghg warming. That they do this using radiative physics is all the more compelling.
Mosher, in simple terms, your hypothesis is that radiative physics dominates climate physics, even though climate physics is much more complex. The satellite observations say this dominance hypothesis is false, not that radiative physics is false. What we need to understand is climate physics, include the failure of your dominance hypothesis.
And yes, I have no doubt that this dominance hypothesis is built into the GCM models. That is precisely the basic problem with them.
(PS: Starting a response with “huh?” is unflattering, to you.)
David, you write “The satellite observations say this dominance hypothesis is false, not that radiative physics is false”
Boy am I gald to see someone else writing this. To me, it is so obviously true, and it goes to the heart of why the proponents of CAGW are wrong. It is true that adding CO2 to the atmosphere changes the radiative balance. What is wrong is that there is any proper physics that allows us to go from a change in radiative balance to change in surface temperature. The assumption that this can be done by only looking at radiative effects has never been justified, and so far as I can see, and you clearly state, is just plain wrong.
But I am sure the proponents of CAGW will never admit this.
David & Jim:
You two are obviously True Experts in physics and climate modeling and data reduction. Your skepticism is like a laser cutting through a vacuum.
Once you are finished congratulating yourselves on how much more perceptive you are than the average climate scientist – you should try to find the time to publish your ground-breaking falsification of climate science that the stupid and evil real scientists have somehow all missed.
Of course, “I have no doubt” and “Boy am I gald to see someone else writing this” aren’t exactly solid evidence, except in blogging – but you guys must be onto something Very Important here, or I’m sure you wouldn’t be taking yourselves so seriously.
Carry on.
certeris, you write “You two are obviously True Experts in physics and climate modeling and data reduction. Your skepticism is like a laser cutting through a vacuum.”
I suggest you ought to have preceded this with “sarc on”. However, it is not anything I can write up. The key is the assumption on the part of the proponents of CAGW that quantitative estimates of change in surface temperatures can be made from a change in forcing, by only looking at radiative effects. I cannot find anyone who can justify this assumption; maybe you can.
But the point is that if this assumption is wrong, then there are no valid estimates of climate sensitivity. Where can I possibly write this up? And the proponents of CAGW refuse to address the issue. Will you engage in a discussion of this with me?
“And the proponents of CAGW refuse to address the issue.”
No we don’t. What you say is factually wrong and it’s been pointed out before.
Steven Mosher | May 23, 2012 at 11:51 pm | Reply
“These arent really observations, but rather are data products produced by applying algorithms to sensor voltage.”
Ah yes. In the same way that the surface record isn’t really observations but rather are data products produced by applying algorithms to the height of a mercury column in a glass tube. ROFLMAO
Mosher, why end the plot in 2000 when we have 11 more years of data?
http://www.woodfortrees.org/plot/uah/from:1979/to:2011/plot/rss/from:1979/to:2011/plot/rss/trend/plot/uah/trend
1979 – 2011 trend = 0.13C/decade
This is well below IPCC minimum estimate for lowest CO2 emission rate and yet anthropogenic CO2 emission has grown at the highest (no abatement) rate.
CO2 sensitivity is far below the lowest IPCC prediction. Game over.
Steven Mosher | May 23, 2012 at 11:51 pm | Reply
“If you accept UHA or RSS then you accept the physics used to create them.”
No, it means no such thing. MMU sensors are calibrated with radiosonde data. I accept the physics in the thermocouple temperature sensors carried by the sounding balloons. If the MMUs were all that reliable we’d be calibrating the radiosondes by MMU data not the other way around.
This reminds me of Darwinists saying that the theory of evolution by natural selection is as well established as the law of gravity. Funny thing is you never hear a physicist say that the law of gravity is as well established as the theory of evolution. Yer comical, Mosher, and way out of your league. LOL
Leave Steven Mosher alone. He’s going for Global Warming Salesman of The Year. ;)
Andrew
He’s going to lose if this is where he peddles it. The winner will undoubtedly be a Brit or Aussie who exclusively works as a guest speaker in elementary schools. The rest of the gullible population is already sold on it and/or they are too well educated (i.e. smarter than a 5th grader) to be persuaded.
Mosher
re “positive trend”
Per Springer’s observation, see details of 32 year satellite era trends by Lucia at the Blackboard:
April UAH TLT Bounces up: Current value + 0.295C
See Figure
Compare that 32 years “trend” with IPCC’s “model”:
With IPCC’s 0.2C/decade at the +2sigma from actual data trend, I would count that as outside 95% of the data, NOT >90% (“very likely”) anthropogenic.
I see that as IPCC missing major physics, or seriously distorting climate sensitivity by short term curve fitting and ignoring major natural variations.
Contrast Nicola Scafetta’s model with dominant natural cycles and minor anthropogenic component which both fore and hindcasts well when splitting the temperature data in half.e.g.
Scafetta N., 2012. Testing an astronomically based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models. Journal of Atmospheric and Solar-Terrestrial Physics 80, 124-137. DOI: 10.1016/j.jastp.2011.12.005. PDF – Supplement
(PS the trend has been “positive” since the Little Ice Age, BUT “negative” since the Holocene climatic optimum. The challenge is to differentiate and quantify the anthropogenic vs natural components)
Even if you concede that the warming is as high is they say, the statement is still unfalsifiable. Not a good way to start a scientific paper, with an unfalsifiable claim.
Judith,
Why do scientists miss following actual facts for theories that would only have worth in fiction?
Technology has changed over the last 100 years, yet these theories have no actual physical basis.
Errors are in abundance to actually doing physical measurements that are absolute facts.
I don’t see a testable hypothesis. I don’t see that their analysis says ‘have a look at the Mn isotope ratio in the nodules in the Pacific and they will show…..’
Where is the heat being move form and where to. Big movements of water should change all sorts of things, like deposition rates of marine skeletons, or the pO2 at the ocean bottom. Why can’t we have a prediction that can point to where we can find data to refute or support.
I can get a better fit with a polynomial.
DocMartyn | May 23, 2012 at 10:32 pm |
Polynomial fitting can always produce superior results.
They’re just generally wrong superior results, once more data comes along.
At which point, a new polynomial fit can be applied that is superior for all the data so far collected.
Which will be wrong again, generally sooner.
Which is the definition of a heuristic. A heuristic is always correct, until it is wrong, then a new heuristic comes along which corrects it. Then the cycle continues as the new heuristic becomes wrong again. That is trendology, which is the bizarre stuff that Girma practices, and what many of the skeptics here seem to be fans of.
WebHubTelescope
That is trendology, which is the bizarre stuff that Girma practices
It was correct since 1885, for 127 years!
http://bit.ly/HRvReF
Why not at least for the next 20 years?
How can you establish a theory before accurately describing the observed data?
Why not for the next 20 years? 127years is about 1 percent of the Holocene. That is not a lot of data and that data has a margin of error of about +/-0.2 C. The next 20 years is likely to fall within the range of your projection, but it is not very informative. With large enough error bars everything falls within the range of Hansen’s projections.
Now if you look at the various paleo reconstructions, current temperatures are about 0.4C above the average for the past 400 years and near the average peaks of the past 1500 years. Since those were peaks, it is likely we will see a downturn in temperatures, but most of those downturns seem to involve volcanic activity. Since your chart doesn’t predict volcanic activity or have any other mechanism to explain why it should continue on a trend that is short by historical standards, it isn’t very useful.
Once you are happy with a prediction based on limited information, you should search for a mechanism that tends to validate your prediction.
http://i122.photobucket.com/albums/o252/captdallas2/SouthernExtentreconstructionwithGISS24Sto44S.png
That is my crude reconstruction of the southern hemisphere energy using Neukom and Cook tree rings. Gertis et al has a new temperature reconstruction for the southern hemisphere that is posted on realclimate, http://www.realclimate.org/images//GergisFigure4-1024×461.jpg
So you can look at past approximation trends following similar peaks a describe which your prediction is more likely to follow. Looking at those, it appears unlikely that trend of the past 127 years is likely to continue.
So as Mosher and others have recommended, I suggest you expand your theory.
Thanks capt.
My aim is only for short-term predictions and to establish an approximate pattern to the observed data. I believe due to the huge reservoir of heat contained in the oceans, it will continue with the established pattern of the last 127 years at least for the next couple of decades.
Girma asks
If we look at Girma’s curve over the next 200 years, we see a continual oscillatory warming which eventually accelerates the temperature in a monotonically increasing fashion, culminating in a cumulative 3 degree change since 1900.
http://img26.imageshack.us/img26/7849/girmatrendology.gif
Of course, we can always refuse to play these trendology games that people like Girma engage in.
Girma | May 24, 2012 at 6:25 am |
“It was correct since 1885, for 127 years!”
This is the problem with your trendology.
Today you generate a curve that is correct for 127 years, you say. Let’s even pass by the obvious mistakes in calling your version correct, as clearly it is not when you look at the detailed data. But let’s pretend it is.
Three years ago, lacking the current three years of data, you generated a curve that also you claimed, to some standard, was correct since 1885. It was a slightly different curve then than it is now. The method you used was similar, the shape had similarities, but the actual fit you used was different 3 years ago than the fit you use today, slightly. That curve of 3 years ago is ‘wrong’ by the measure that you have stated, that there is only “ONE” truth.
Repeating the process of jumping back in time, pretending we do not have the most recent data, even of using the prior datasets (HadCRUT2, etc.) for the times before the current datasets existed, we will see your fitted curve as generated by your method evolve and change over and over again. Each of them different. All of them wrong.
In the limit as time approaches infinity, a succession of always wrong outcomes is being wrong forever.
There is no time when your method is actually right as a projection in the future.
Web
It is you who plotted that model until 2200.
I plotted it ONLY to establish the climate pattern of the 20th century and for predictions of ONLY the next couple of decades.
The graph you plotted is YOURS not mine.
Here is the graph that I defend => http://bit.ly/HRvReF
That’s your baby. You should be able to recognize your own children.
A testable and falsifiable hypothesis often works best for science but is not always necessary. One can simply investigate: “is there an effect”, or “what is the effect”. Do these two drugs interact?, ec.
“Many traditional decomposition methods, including the Fourier Transform and wavelet decomposition methods, utilize a priori determined basis functions, which may faithfully represent the characteristics of a time series in some segments but not in other segments of a non-stationary time series (Härdle 1990; Fan and Yao 2005).”
Wavelet methods are FAR more flexible than they suggest. I NEVER “utilize a priori determined basis functions”.
The Fourier transform is still the workhorse because it has the ability to capture the autocorrelation as a power spectral density through the Weiner-Khinchin theorem. (Of course I have a breakthrough research paper on applying this to environmental modeling in the works) Cheers.
Multiparameter windowing’s essential in plenty of data exploration contexts.
As David W. notes above, re-analysis of the patterns in terms of energy instead of temperatures is way overdue. And the big energy carrier is water, in all its forms and transformations.
We had Tomas Milankovic, Robert Ellison, and David Young discuss Hypothesis III, Climate Shift Hypothesis. I threw my two cents worth in observing that the global mean temperature seemed to be regulated as a homeostatic system and then abruptly changing to a new phase state. Tomas observed that we never pass twice the same space. My interpretation is that models built upon the past record can never predict the future; ie, hind casting skill has no relationship to forecasting. The conditions of the past are not likely to occur to the same timing, extent/degree, in the future. Does Wu et al mean that understanding the Thermohaline circulation we will be able to predict weather/climate?
They make up stuff about AMOC because they don’t know enough about wind. http://i49.tinypic.com/2jg5tvr.png
http://wattsupwiththat.files.wordpress.com/2011/10/vaughn4.png
“Abstract. The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s.”
Right. “unprecedented.” As in never, ever happened before. It didn’t take long for them to reveal their bias.
All of one sentence.
“The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s.”
Bull****.
Not a good way to start.
sunshinehours1
You need to start your article with such phrases in order to get published.
The main point of the article is to point out IPCC was wrong in reporting the global warming rate as about 0.2 deg C per decade without removing the warming rate due to the cyclic warming.
So please give the paper a credit for pointing out the major mistake of the IPCC.
This is a good point and really does show the bias and difficulty that must exist in publishing w/o showing you are a member of the team first.
There seem to be many examples where such statements of solidarity are thrown out there in papers where it is not necessary or sometimes even relevant. Anyone can look at the graphs and see that the 30’s and 40’s have similar slopes and certainly are the same within error.
That’s what I found out by working the data. The changes in temperature in the Greenland and Antarctic ice core data are fairly significant and operate over short enough times (within the granularity of the time series data) such that the rates of change we see now are historically plausible. But that may just show how sensitive the earth’s climate is to perturbations. It may be like a gun with a hair-trigger. The CO2 in the Vostok ice core data barely ever made it over 300 PPM, now it is nearing 400 PPM.
WHT, I am not sure what you are arguing:
Do you agree that your charts of the Greenland ice cores show much faster rates of warming in the past 8,000 years and even faster in the past 20,000 years than anything we have encountered in the past 200 years? (previously you acknowledged this is what they show).
So what that we are at 400 ppm? That is a very low CO2 concentration in Earth history, and the Earth is at a temperature well below its “normal operating temperature”. So I don’t see why that is scary. In fact, it may be good to be rising above the level at which life would be virtually wiped out (i.e. about 170 ppm).
The James Hansen Figure 1 here http://www.columbia.edu/~jeh1/mailings/2011/20110118_MilankovicPaper.pdf shows the planet is in a dangerous long term trend. It is getting colder and CO2 concentrations are reducing. That suggests catastrophe if that continues. Playing devils advocate, we could argue that raising CO2 levels is a precautionary step (good risk management) rather than an irresponsible and dangerous act.
If not for man’s CO2 contribution, how much colder would you predict the Earth would be in 200 years from now?
I do not understand what you are arguing about. If you want to talk time series analysis then fine, otherwise it is rhetoric in my opinion.
Typical avoidance of the real deniers (i.e. the Catastrophists / Alarmists)
No, the skeptics don’t like to play the math card. Because when they do, they always get called out on their gibberish.
To believe in such accuracy of the ice core gas data is mind-bogling to me. Especially when one knows about the problems with it and the suppression of the non-300-ppm measurements.
Yes, freezing their tushes off in polar regions for ice core data, and all Edim can come up with is a conspiracy theory.
The same old conspiracy theory strawman. Look up confirmation bias and groupthink.
I did and your name appears as an example.
Web, the rates of change we are seeing now are definitely historically plausible, especially in the northern hemisphere and the polar extents. That doesn’t mean that the Earth is overly sensitive to perturbations. With the S-B relationship, a tropical perturbation would be nearly doubled in the Antarctic and could be quadrupled in the high northern latitudes. Comparing the ice core temperature change to global temperatures without considering the energy required for that change leads to over estimation of global impacts. With predominately northern hemisphere higher latitude data, of course the impacts look greater than they are.
There are finally more southern hemisphere studies being published which will fine tune the interpretation of the “sensitivities”.
It does mean that the Earth is very sensitive to perturbations.
Regionally yes, globally not so much. Assuming the surface temperature record is perfect, there has been less than one degree change since the mid 1880s. That is +/- 0.5 C with the modern warming period of about 35 years. That is much too short a time and too small a variation to have a great deal of confidence in what is Anthropogenic and what is natural variation when comparing high frequency data to low frequency paleo, which is all we have of the past.
Orsi et al. have a new WAIS bore hole temperature reconstruction. http://www.agu.org/pubs/crossref/2012/2012GL051260.shtml
In figure 5 they compare the reconstruction to Steig et al 2009 and cloud masked satellite data with a pretty limited length. The bore hole reconstruction filters out the high frequency change leaving the appearance of a nice slow transition from one state to the next. So which is it? The chaotic highly sensitive change of the low thermal mass air temperature or the smooth transition indicated in the bore hole?
Antarctic temperature records are problematic, but Amundsen-Scot has a fairly long continuous record with reasonable temperature ranges (below -70 starts creating issues with the instrumentation giving a warming bias).
http://redneckphysics.blogspot.com/2012/05/antarctic-is-getting-some-scientific.html
Instead of looking at just the temperature I looked at the energy required to change the temperature. The ice in the cores had to come from the oceans somewhere, so I scaled to 0C, it could be higher, just a shot in the dark.
The bore hole appears to be a better match to the 0C baseline temperature.
When I threw together my little SH temperature reconstruction I also attempted to scale the reconstruction to available energy.
http://i122.photobucket.com/albums/o252/captdallas2/SouthernExtentreconstructionwithGISS24Sto44S.png
To me it looks like we are close to a fairly normal range with some increase due to Anthropogenic causes (that includes more than CO2) There is a new real SH reconstruction out now that is quite similar to my thrown together one by the way. http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-11-00649.1
WHT said:
The changes in temperature in the Greenland and Antarctic ice core data are fairly significant and operate over short enough times (within the granularity of the time series data) such that the rates of change we see now are historically plausible.
Isn’t that a bit of an understatement? I understand (perhaps misunderstand) the fastest rates of warming over the past 10,000 years you determined (i.e. 0.2 degree/year) (Figure 23 http://theoilconundrum.blogspot.com.au/2011/11/multiscale-variance-analysis-and.html ) were much greater than anything we have seen in the past 200 years.
By the way, what is the granularity of the times series data from the most recent Greenland ice core data?
Can buy neither their extrapolation nor their AMOC.
Advice: It’s not a univariate problem.
Here we have again one attempt to square the circle, i.e. to extract from data information that the data is not sufficient to produce.
The temperature time series by itself cannot tell the roles of trends, oscillations and other factors, for that additional assumptions must be introduced. The most straightforward assumptions like that of linear trend plus white noise are certainly poor, but they have the advantage that their influence on the outcome is rather easy to understand. Fits with a few parameters like those of Vaughan Pratt are more difficult to judge but still much easier than the one of Wu et al.
The great difficulty of judging the influence of the specific assumptions implied by the methodology of this paper makes it’s conclusion rather useless in my view.
The paper admits in part the impossibility of the task, but but doesn’t give proper weight on this fact in it’s conclusions. The locality and other features of the methodology are not well enough justified and the method hides additional assumptions that have a obscure influence on the outcome.
It’s not accidental that main stream data series analysis has proceeded along different lines. For a scientific methodology it’s most important that it’s influence on the outcome can be understood. As far as I can see this methodology fails that requirement.
I have again difficulties in getting WordPress to tell properly who I am.
Pekka Pirila
Thanks to Bart R’s prompt, I followed the link and found your interesting article: “How to decide on Carbon Policies” (dated April 2011) http://pirila.fi/energy/ .
You refer to Stern and Nordhaus. I get the impression you would not place a lot of value in the Stern analysis and consider Nordhaus’s analysis closer to more useful. I am interpreting that you would suggest that even Nordhaus’s discount rates are too low. (I understand Nordhaus RICE model (March 2012 update) uses discount rates that average 4.35% for 2005-2105: http://nordhaus.econ.yale.edu/ )
Have you written more on this subject since your April 2011 paper linked above? Can you recommend other papers or articles that you would consider improve further on how to decide on carbon policies? I am most interested in seeing analyses that use:
– realistic damage costs for warming
– realistic discount rates (demonstrated by markets and past experience)
Unfortunately I haven’t kept on extending my writing on those lines. For much of the last 12 months I have been rather busy with completely different interests (those, who know Finnish might be able to figure out what they are). I hope to come back to climate policy / environmental economics / energy policy and related issues in a couple of months.
For several weeks I haven’t had much time to follow Climate etc either or to comment here.
In my view the fundamental problem with discounting is not determining the right discount rate but in the whole approach, when applied to long periods. Discounting applies well to cases where the future is determined directly by present choices, but it fails, when later decision making dominates over immediate decisions. In principle discounting can be combined with approaches that allow for later decision making. Dynamic programming is a mathematically well defined approach that does that. In practice the inability to fix the details of such methods correctly are, however, overwhelming.
Whether we can apply any well defined mathematical methods or not we know, however, that future decision making will greatly reduce the ultimate consequences of most immediate decisions, while the consequences of some breakthrough events may grow to make them dominate the future.
When the real development dynamics is what I describe above, it really does not make sense at all to calculate discounted net values over very long periods like 100 years or more. That’s a wrong approach for being responsible. Stern review took this wrong approach to extreme and made it still worse by the chosen approach to handling risks. The results are totally meaningless. Even the fact that the resulting damage costs are much higher than mitigation costs is only an artifact of worthless methodology.
I’m not saying that higher discount rates give necessarily correct results. Calculations based on high discount rates have the advantage that they are meaningful, because the give little weight to the unknown distant future. While they are meaningful and internally consistent, they may well be wrong. Perhaps we should give much more weight for the distant future, but if that is the case, we have the dilemma:
– High discount rates give wrong results.
– Low discount rates fail to give any meaningful results at all.
My conclusion is that the whole concept of using discounted net values fails and some alternative approaches must be found to put economics of long term development on better ground. I have mentioned often Partha Dasgupta as his writing involves some ideas in that direction. He hasn’t solved the problem as far as I can see, but he has made some interesting steps forward.
“it really does not make sense at all to calculate discounted net values over very long periods like 100 years or more. That’s a wrong approach for being responsible.” Quite so, and models for economic policy advice look only ten years ahead. How can anyone looking at the unpredictable changes of the last 100 years, even the last decade, think that it is sensible to make economic projections for a 100 years? (Which is what the IPCC scenario modellers do.)_
Pekka,
Thank you. Very interesting. I’ll read Partha Dasgupta.
I have circulated the URL for your articles to a group who will be interested in what you say.
Pekka,
I am putting together what you say and what Richard Tol (2002) says.
You say:
Richard Tol (2002) “Estimates of the Damage Costs of Climate Change Part II. Dynamic Estimates” says (with lots of caveats about uncertainties), p157:
Looking specifically at this sentence:
Putting this together with what you say, wouldn’t justice be served best and fastest by getting the poorest countries and people out of poverty as fast as possible?
Isn’t this best achieved by allowing and facilitating economic growth (as Germany and Japan demonstrated after WWI, South Korea demonstrated after the Korean war, and China, India, Indonesia and many other Asian countries are demonstrating now)?
Wouldn’t pricing CO2 slow the rate of economic growth and, therefore, have the opposite effect on justice?
Hi Pekka
Nice to see you commenting here again.
I can’t offer a solution, just a simple observation based on prior employment in long range economic planning. Plans with equivalent NPVs can have dramatic differences in initial investment and flexibility to later reformulation. In dealing with future uncertainties, It’s essential to review multiple alternative plans which have employed diverse approaches.
+1
Small comfort though this may seem, considering the source, your clarity and knowledge will always tell readers properly who you are, sir.
ppirila
The great difficulty of judging the influence of the specific assumptions implied by the methodology of this paper makes it’s conclusion rather useless in my view.
There is no assumption. There is only interpretation of the data. It is about believing what we see => http://bit.ly/HRvReF
Too much pomp & pageantry filler. The whole article can be condensed to a graph with a few sentences. The method isn’t assumption-based. Other methods give the same observation. The wordy lament of the authors is about end effects, which are inescapable with ANY method. There IS a fundamentally flawed assumption, but it stems not from the time series method but rather from the authors’ hopelessly naive &/or comically deceptive decision that this is a univariate problem.
Data alone tells what we see without any additional analysis, i.e. without any curves to lead or mislead our thinking or any interpretation in terms of trends, oscillations or any other similar concept. Data alone doesn’t tell anything about, what to expect from the future.
When we want to extract something like trends, oscillations or expectations we rely on a model (I use a wide interpretation of the word “model” and that may explain some apparent disagreement with Paul Vaughan and others). The model may be a linear trend, a combination of some kind of trend with oscillations or the model can be based on some other kind of assumptions like assuming that the methodology of the paper of Wu et al (or perhaps a wavelet analysis discussed often by Paul Vaughan) will give lead to an interpretation that can serve as basis for expectations about future.
All these approaches are based on some assumptions on the nature of the temperature behavior. Some kind of assumption of smoothness in the development of the temperatures is involved in every analysis, but how this assumption is introduced and how the assumption affects the outcome varies from case to case. The model of Wu et al is non-parametric, but it’s a model anyway in the meaning of the word I have in mind.
As Paul Vaughan writes and also the paper of Wu et al states in the introduction, the end effects are crucial. Looking at the data indicates clearly that one can imagine quite different future development, and that the interpretation of the temperature variations of the latest few decades will be very different in these cases. (Wu et al don’t mention end effects, but they write Distinguishing between cycles and time varying ST of a time series has long been regarded as a daunting problem, as exemplified by the statement of Stock and Watson (1988): “one economist’s ‘trend’ can be another’s ‘cycle’”.. This is just another way of expressing the importance of end effects.)
They do mention end effects. It’s clear that it’s at the forefront of their minds.
As for “model”: Is a microscope-view a “model”? If I adjust magnification &/or focal length, am I making assumptions?
Pekka: You are operating on a completely different paradigm. That’s a formidable part of the challenge we run into in these cross-disciplinary discussions.
In data exploration there are no assumptions. That’s statistical inference. In data exploration there are only sampling & aggregation criteria. Again: A different paradigm. Others will call it a model – e.g. W.S. Cleveland. So how can we understand one another?
How can we preemptively be vigilantly on guard for paradoxical misinterpretation if we do not assess the variability of parameter estimates as a systematic function of sampling & aggregation criteria? (I don’t call this “modeling”.)
The awakening has yet to occur in climate & solar science. Years back I witnessed it deeply transforming cutting edge thinking about perception in landscape ecology & physical geography.
This is observation:
http://i49.tinypic.com/2jg5tvr.png
It can be interpreted (by those with the necessary background).
Those who don’t bother to make the effort will keep saying things about climate that are inconsistent with observation, as have the authors of the paper being discussed.
Best Regards to All.
Paul Vaugan
You posted a pretty picture of weaving. http://i49.tinypic.com/2jg5tvr.png
What is the point of doing that with no explanation?
Peter,
Here’s a NASA-sponsored paper that should give you the background to understand:
Dickey, J.O.; & Keppenne, C.L. (1997). Interannual length-of-day variations and the ENSO phenomenon: insights via singular spectral analysis.
http://trs-new.jpl.nasa.gov/dspace/bitstream/2014/22759/1/97-1286.pdf
I strongly advise everyone to make it a TOP priority to assemble the background knowledge needed to understand the weave. It has been nearly 2 years since Le Mouël, Blanter, Shnirman, & Courtillot (2010) and I see that still people want to talk about “climategate” and other such diversionary wastes of time. I extended Le Mouël, Blanter, Shnirman, & Courtillot (2010) here:
http://wattsupwiththat.com/2010/12/23/confirmation-of-solar-forcing-of-the-semi-annual-variation-of-length-of-day/
I volunteered a background primer here:
http://wattsupwiththat.com/2011/04/10/solar-terrestrial-lunisolar-components-of-rate-of-change-of-length-of-day/
That gives the info needed to get a handle on global constraints & aggregation. Be SURE to dig into Gross (2007) and Sidorenkov (2005).
I’m drafting an article, but I’m a few orders of magnitude short on the time & resources I’d need to spoonfeed a narrative the way most (for example at WUWT) appear to want &/or need. If there are some volunteers who can write some good background articles on “thermal wind” and annual variations of atmospheric circulation, that could be tremendously helpful in paving the way towards widerspread understanding of the weave. Unfortunately, people lacking background are hung up on interpretation of the weave when we need to be getting on to implications. Can anyone volunteer to write background articles?
Regards.
Paul Vaughan,
Thank you for the links. I down loaded the WUWT links and had a quick look. However, they do not provide a summary to explain what the chart is about and what is the value of it. So I don’t know whether or not it is something I want to put time into reading long scientific articles, unless I can see up front that they may have relevance to what I am interested in exploring – i.e. damage costs of CO2 and cost benefit of mitigation v adaption. Does the solar weave chart help me? How?
Paul
I agree that in genuine data exploration there need not be any assumptions. I didn’t emphasize that, because I don’t believe that genuine data exploration is done often for issues like the temperature time series. Even when people use methods that allow for that they do it mostly in a a way where assumptions are introduced.
As an example they may start with a method that results in a large number of components that taken as whole are fully equivalent with the original data, but then they cut the number of components without proper justification. (The problems of the Hockey Stick belong largely to this class.)
After all people use various methods of analysis to make inferences. When data is sparse and very little can be inferred, the criteria may be relaxed and objectivity replaced by wishful thinking.
Theoretically well understood methods which includes wavelet analysis in appropriate cases allow for fully objective analysis. Methods based on more lacking theory differ in that. I admit that I haven’t gone fully trough the methods of Wu et al, but based on lacking understanding I remain skeptical on the completeness of the theoretical basis for their work.
Just a curiosity about the Dickey Keppenne paper.
They refer to Karhunen-Loeve expansion. Kari Karhunen whose 1947 paper has led to this name was a school mate and long time friend of my father, and I have met him many times during my childhood.
Peter,
You may want to wait until others finish building a trail. I’ve been off pioneering routes. I guarantee you these routes track constraints on climate, but I’m not yet at a stage where I can efficiently guide a lay audience over the terrain. I might have to go back to academia to find time & resources to simplify a spoonfeedable narrative.
Update: Just a few minutes ago I finished isolating the summary of LOD (length of day) that tracks solar cycle deceleration. This resolves the nature of relations between LOD & AAM (atmospheric angular momentum) at multidecadal timescales.
–
What should you make of the weave for now? It tells you that global wind patterns & ENSO are constrained by the solar cycle. This is serious stuff.
–
Rather than keep my explorations under wraps, I’ll be informally sharing what I can when I can.
At the very least, everyone should – without further delay – learn the basics of the concept climatologists call “thermal wind“. (A web search will turn up more than enough basic material.)
Best Regards.
Paul,
Are you sure that you constrain the climate rather than observe the influence of climate on LOD?
Pekka,
Dickey & Keppenne’s (1997) figure 3a & 3b (pdf p.24 & p.25) are of historical significance.
Best Regards.
Paul,
Figs 3a and 3b show the annual and semiannual cycles and some modulation in them. Rephrased on this basis, my question is:
What is the causal connection between the modulation and the climate?
What is cause ant what is the result?
What other phenomena are involved and is one of the other phenomena better related to the cause?
To me the most obvious idea is that variations of the Earth system (climate and oceans) affect LOD, which is of course affected by other factors as well. Thus LOD may be an indicator of some climate related property of the Earth system, but it’s an indirect indicator that is probably very difficult to use in gaining further understanding.
Pekka Pirilä | May 25, 2012 at 2:04 pm | asked:
“Paul, Are you sure that you constrain the climate rather than observe the influence of climate on LOD?”
There appears to be a misunderstanding/misinterpretation.
The sun constrains climate (and hence LOD).
Certainly I have learned from discussions at WUWT that those lacking background are quick to (falsely or accidentally) assume it’s being claimed that LOD drives climate. That’s a tremendously popular misinterpretation that will likely arise many more times in lay discussion.
If more discussion participants had a handle on absolute equator-pole gradients and thermal wind, things might go a little more smoothly.
This 1994 article might be of historical interest to more advanced readers:
Gross, R.S.; Marcus, S.L; Eubanks, T.M.; Dickey, J.O.; & Keppenne, C.L. (1994). Effect of climate change on seasonal length-of-day variations.
http://trs-new.jpl.nasa.gov/dspace/bitstream/2014/28080/1/95-0060.pdf
Pekka: You might find the linear regressions “interesting”. (Fits in with what you wrote above. I encourage you to explore how past extrapolation would have held up (to newer data). Data are here: ftp://ftp.iers.org/products/eop/long-term/c04_08/iau2000/eopc04_08_IAU2000.62-now .)
Regards.
Pekka, The weave can be isolated directly from AAM.
http://ftp.aer.com/pub/anon_collaborations/sba/
ftp://ftp.iers.org/products/geofluids/atmosphere/aam/GGFC2010/AER/
Pekka Pirilä | May 25, 2012 at 2:39 pm | wrote:
1. “To me the most obvious idea is that variations of the Earth system (climate and oceans) affect LOD, which is of course affected by other factors as well.”
2. “Thus LOD may be an indicator of some climate related property of the Earth system, but it’s an indirect indicator that is probably very difficult to use in gaining further understanding.”
1. This is well-known and uncontroversial. See for example the 1994 NASA JPL article to which I linked above.
2. This is where I must take very severe issue with you. The exceptional utility of LOD is that it is globally constrained by the Law of Conservation of Angular Momentum. This is no trivial constraint. I advise thinking through the implications with extreme care.
We may be able to productively further this exchange (in the weeks, months, & years ahead) after you’ve managed time to delve deeper into AAM / earth rotation basics.
Paul
Your latest comment under 2) is exactly what I had in mind when I wrote my comments. I’m strong enough in physics to realize that immediately, but I’m certainly not an expert in any details related to this particular problem. I just presented the first questions that your comments and some cursory reading of your references raised in my mind.
What I have learned so far makes sense, but doesn’t convince me that studying this phenomenon is likely to teach much useful about the Earth system. I don’t exclude that possibility, but my gut feeling based on relative sizes of various effects makes me skeptical.
Pekka,
It’s strictly inconsistent with observation to assume spatial uniformity of solar-terrestrial relations. The “relative sizes of various effects” (as you wrote) can be quantified rather than left to “gut feeling” (as you also wrote).
Dickey & Keppenne (1997) crystallize cross-scale QB & LF ENSO relations with the year. The solar cycle modulation of the multiparameter-windowed-envelope is small but it’s crystal clear (can be robustly isolated using dozens of methods) and rather importantly its accumulation is coherent with multidecadal oscillations.
The innovation that enabled Dickey & Keppenne (1997) to see cross-ENSO was tuned multi-parameter windowing.
I want to suggest that you don’t allow your vision to be blinded by false &/or accidental assumptions about ENSO. Perhaps you will need to develop deeper conceptual understanding of tuned multi-parameter windowing in order to see that ENSO is included in the weave.
Isolation & interpretation of LOD features is a subtle business. It requires careful attention to integration limits and order of integration. Aside from polar motion, can you point to any other climate record that affords such delicate work? I encourage you to recognize the depth of climate exploration opportunity that exists in globally constrained EOP (Earth Orientation Parameters) records.
I’m presently investigating the feasibility of correction of the earth rotation / climate narrative suggested here:
Buis, A. (2011). NASA study goes to Earth’s core for climate insights.
http://www.nasa.gov/topics/earth/features/earth20110309.html
More details at a later date.
Paul,
I wrote that I’m skeptical on the power of the approach in learning about the important properties of the Earth system. In science such skepticism should not be interpreted too strongly, prejudices like the one that I have, have often been proven wrong (although perhaps even more often right). Checking carefully, what’s really behind the idea, may well be worth considerable research.
You emphasize, how precise information there’s about the solar cycle and how that allows for sophisticated research. That’s fine, but that’s not enough, when the other phenomena, i.e. the climate related phenomena are complex and noisy.
You write also “Isolation & interpretation of LOD features is a subtle business. It requires careful attention to integration limits and order of integration.” To me this means that figuring out the statistical significance of the results is likely to be very difficult, perhaps impossible. When the methods are developed looking at the data being studied, the apparent statistical significance may be artificially strengthened very much, enough to make something of no real significance to look highly significant.
More specifically on your statement
The solar cycle modulation of the multiparameter-windowed-envelope is small but it’s crystal clear (can be robustly isolated using dozens of methods) and rather importantly its accumulation is coherent with multidecadal oscillations.
It may be clear, but how much information is involved and how significant this effect really is? In other words, how unlikely it is that an equally strong relationship of some kind would be present for some unrelated reason. The emphasis above refers to the fact that the observation is not an confirmation of an earlier specific prediction but on effect observed in the data that could not be quantitatively predicted.
Here is the way I think about : If per chance the climate was sensitive enough to be driven by second or third-order effects in the solar cycle, then certainly some equally large perturbations such as increased GHG and albedo changes could also cause significant changes to the climate.
WHT
You wrote
Believe it or not, you and I may be (almost) in agreement.
How about:
Agree?
Max
No, because they are not external forcings. Internal forcings can never accumulate. That’s what trips up most climate skeptics, the lack of appreciation of constraints and boundary conditions. That they rarely solve any practical problems by analysis or modeling accounts for this gap in their reasoning.
The obvious second order solar effect is solar UV interactions with ozone in the statosphere influencing especially the southern and northern sub-polar annular modes.
The most obvious measured albedo effect is ENSO and cloud.
The problem with Webby is that he doesn’t really understand very much.
Which is what Chief Little Big Man does not understand. If a continuous increase could be completely sustained by internal forcings, such as the heat capacity of the oceans turning over, then conservation of energy laws (and also entropy) would be violated.
That part is pretty basic.
Now the next point is about clouds. Pick one of two scenarios: Does the amount of cloudiness increase with increasing temperature? Or does the amount of cloudiness increase with decreasing temperature? And what is the altitude at which the appropriate clouds form? Are the cold weather clouds lower or higher in altitude?
Absent clouds, we know that increasing concentrations of atmospheric water vapor contribute to a stronger GHG effect. And the ocean outgasses more water vapor with increasing temperature. So if you want to say that clouds are a compensating effect for increasing temperatures, then one has to invoke increasing cloudiness with elevated temperatures to provide a sufficient negative feedback to the outgassing.
What I would like to see is a rough sketch that shows how increasing atmospheric water vapor will get translated into a positive GHG feedback factor and a (possible) negative cloud albedo feedback factor. If these two factors are both monotonic with concentration, then one effect has to overshadow the other. If, on the other hand, one or the other has inflection points, then the effect can conceivably switch at some specific temperature level.
If you choose the cloud as an overriding negative feedback factor, you just ruled out the fact that internal forcings can change temperature dramatically. All increases in temperatures will be damped out quickly.
Your logic loses every which way.
Something external has to force it. In the case of anthropogenic GHG gases, it is the external addition of energy that had previously been buried under the earth’s surface for millions of years. This energy was used to (over a short geological time scale) release vast amounts of CO2 into the atmosphere. With no fast sequestering path, the quasi-permanent layer of GHG gases then forms an IR trapping layer which will create an energy imbalance that will continue on for centuries.
You and your fellow skeptic have no equivalent scenario that is anywhere near plausible. Please describe how conjuring up demons from the deep as an ENSO oscillation will lead to an absolute and continuously increasing change in internal thermal energy.
If you do have a rhetorical reply to this argument, then get to a mathematical model PRONTO, as the first order-effect will be pretty obvious and you should be able to get a research paper out of it.
You missed it by that much. Sorry about that, Chief.
–
Pekka Pirilä | May 26, 2012 at 1:55 am | wrote of:
“[…] statistical significance […]”
I spent years indoctrinating students on statistical inference fundamentals and as I have said many times:
With few exceptions, not enough is yet known about climate to pursue meaningful statistical inference. More exploration is needed.
In particular, precise definition of constraints is needed before inference assumptions will be anything more than convenient fantasy applied to CHEAT mathematical intractability.
I spent a decade around math/stats departments. I know the tricks, the winks & grins, and the good fun folks have being so “clever”.
Statistical inference is the easy part that well-paid, comfortable technicians can do in the future after more adventurous pioneers do the heavy lifting of careful exploration …which is the more interesting part of the puzzle by orders of magnitude anyway.
If you think the weave is mysteriously observed by pure chance, we might as well efficiently agree (sarcasm here) that 1+1=3 and (no sarcasm here) promptly end all discussion since with such “logic” there can be no trust.
If you explore your suggestion of possible lurking variable (3rd party parallel driver) phase confounding, you’ll immediately be confronted by a realization (if you do the calculations) that weave phase drift shows the same temporal nonstationarity that appears in solar records.
–
Pekka Pirilä | May 26, 2012 at 1:55 am | wrote:
1. “You emphasize, how precise information there’s about the solar cycle and how that allows for sophisticated research.”
2. “That’s fine, but that’s not enough, when the other phenomena, i.e. the climate related phenomena are complex and noisy.”
1. The comment was about the precision of Earth Orientation Parameter (EOP) records, not solar records.
2. I must again severely emphasize that there are NO such phenomena that can violate the Law of Conservation of Angular Momentum (LCAM). These “other phenomena” (as you wrote) don’t operate in some vacuum exempt from the Law, as I suspect you know very well in a moment when you are thinking more clearly, so I’m going to suggest that you take some time to be a LOT more careful before commenting further. For example, please take however much time is necessary to appreciate:
a) just how clean LOD variations are — for example see here
[ http://wattsupwiththat.com/2011/04/10/solar-terrestrial-lunisolar-components-of-rate-of-change-of-length-of-day/ ],
including this model
[ http://wattsupwiththat.files.wordpress.com/2011/04/vaughn_lod2_fig4a.png ].
b) How Central Limit Theorem (CLT) applies to what little “noise” remains unexplained.
Reminder: ENSO is contained in the weave. This is possible via LCAM & CLT.
–
I direct you to the following articles for foundations:
Gross, R.S. (2007). Earth rotation variations – long period. In: Herring, T.A. (ed.), Treatise on Geophysics vol. 11 (Physical Geodesy), Elsevier, Amsterdam, in press, 2007.
http://geodesy.eng.ohio-state.edu/course/refpapers/Gross_Geodesy_LpER07.pdf
http://geodesy.geology.ohio-state.edu/course/refpapers/Gross_Geodesy_LpER07.pdf
Sidorenkov, N.S. (2005). Physics of the Earth’s rotation instabilities. Astronomical and Astrophysical Transactions 24(5), 425-439.
http://images.astronet.ru/pubd/2008/09/28/0001230882/425-439.pdf
“Apart from all other reasons, the parameters of the geoid depend on the distribution of water over the planetary surface.” — N.S. Sidorenkov
Best Regards.
Long winded Webby rubbish.
‘Zhu et al (2007) found that cloud formation for ENSO and for global warming have different characteristics and are the result of different physical mechanisms. The change in low cloud cover in the 1997-1998 El Niño came mainly as a decrease in optically thick stratocumulus and stratus cloud. The decrease is negatively correlated to local SST anomalies, especially in the eastern tropical Pacific, and is associated with a change in convective activity. ‘During the 1997–1998 El Niño, observations indicate that the SST increase in the eastern tropical Pacific enhances the atmospheric convection, which shifts the upward motion to further south and breaks down low stratiform clouds, leading to a decrease in low cloud amount in this region. Taking into account the obscuring effects of high cloud, it was found that thick low clouds decreased by more than 20% in the eastern tropical Pacific… In contrast, most increase in low cloud amount due to doubled CO2 simulated by the NCAR and GFDL models occurs in the subtropical subsidence regimes associated with a strong atmospheric stability.’
I talk exclusively data and observation. Not nonsensical theories.
Copy and paste garbage from captain kangaroo, absolutely free of context as is typical from him.
Is that seriously the best you can do Webby? Complain about a quote from actual science that demonstrates my point?
Yes, Skippy,
that is the best I can do
for a Kangaroo,
As kim has already written, a combination of II and III with some slight AGW forcing sounds most reasonable.
This would also help explain the slight cooling we have witnessed since the end of 2000, despite atmospheric CO2 concentrations reaching record high levels.
Max
As others have shown, the recent La Ninas and the solar minimum are enough to explain the slight cooling since 2000. There’s no need for any cooling cycle.
lolwot
That’s what a “natural cycle” caused by “natural forcing or variability” is all about. This time it’s “natural cooling”.
Got it?
Max
JC, thank you so much for this post.
The most important passage in this article that contradicts IPCC’s statements but accurately reflects the observed data is the following:
This is Girma’s prediction for the future:
http://img26.imageshack.us/img26/7849/girmatrendology.gif
Girma believes that most of this growth is due to a quadratic factor in his model fit. This points to an accelerating temperature increase for the future, analogous to Newton’s law for falling bodies.
Of course most of the sane climate scientists do not believe in trendology of this sort and they would rather concentrate on the physics of climate science to make projections.
WebHubTelescope
It is you who plotted that model until 2200.
I plotted it ONLY to establish the climate pattern of the 20th century and for predictions of ONLY the next couple of decades.
The graph you plotted is YOURS not mine.
Here is the graph that I defend => http://bit.ly/HRvReF
If your graph is not going to continue to 2200 then how do you know it will even continue into the next few decades?
lolwot
A related but slightly different question is to ask people (climate scientists) who believe they can accurately forecast 100 years into the future is why they are unable to accurately forecast 5 years into the future.
Normally, if you really understand how a system works your near term forecasts have a much lower margin of error than the longer term forecasts. Funny how frequently doesn’t seem to be the case with climate forecasts. The same variables that are likely to disrupt the short term are likely to impact the longer term.
I don’t think what Girma has done is anything all that special, but he has produced a forecast based on historical performance. For people like Mosher to write that it is a terrible forecast, imo they should quantify what forcings they believe will impact that trend line when, and by what amount or keep quiet.
I take it you are not an engineer. Many short term forecasts are obscured by noise. This is not a problem that is unique to climate science. A 5 year forecast has to compete against noise fluctuations that can occur due to natural variability. When the forecast is longer term, the trend will rise above the noise level.
You are mistaken once again. I am an engineer and what you write about noise is unrelated to the climate system and 5 year projections
Because of the huge reservoir of heat in the ocean and its unique pattern for the last 127 years, it is reasonable the pattern will continue at least for next couple of decades. However, finally with the change in the climate forcing seen for thousands of years the current climate pattern will change.
“Because of the huge reservoir of heat in the ocean and its unique pattern for the last 127 years, it is reasonable the pattern will continue at least for next couple of decades.”
So do I take it then that you don’t think the Sun has a big role in climate?
If solar activity in coming decades returns to early 20th century levels your graph says temperatures will stay high.
lolwot
lolwot, think about that statement again – it is truly silly.
NO GRAPH that goes to year 2200 makes any sense at all.
Just imagine that if in Napoleon’s time some one had predicted how the world would look 200 years later.
Such long-term projections are pure rubbish, even if IPCC has been foolish enough to include one in its AR4 report.
Max
Rob and WHT
A long-term forecast (or prediction) is by definition more dicey than a shorter-term one.
All the “noise” about “noise” doesn’t change that basic fact.
If you have any doubt or question why this is so, read Nassim Taleb’s The Black Swan
Max
Could have fooled me. Aleatory uncertainty (i.e natural noise) is a property of just about any system, if only due to entropy and the arrow of time. The epistemic uncertainty is due to inadequacy of our measurement accuracy & precision and this of course becomes less of an effect as we are more certain of our measurement as we start to detect a larger signal.
Both aleatoric and epistemic uncertainty contribute to the signal/noise ratio that people are quite familiar with.
I suppose Curry will be surprised to learn that “noise is unrelated to the climate system and 5 year projections”, as that is what her research focuses on. Remember the uncertainty monster?
Why are you even on this commenting board if you have no interest in uncertainty?
Webby
If you think more about what you have written, you will realize it is foolish.
We only roughly understand how the system reacted in the past and thereby have poor information from which to model it for the future. It is a lack of knowledge of the variables and their respective weights and timing of impacts on the system and not system noise that is the issue. That is the uncertainty that is in question.
Ringo, That’s all projection on your part. Don’t pretend that inadequacies in your own knowledge are reflected on people that actually understand science.
This discussion has been about time-series analysis and on how Girma thought that his analysis had any meaning. You even said that “he has produced a forecast based on historical performance”, of which I contend can only fit into the aleatory and epistemic buckets, because he has no other scientific argument to back it up with!
Neither you nor Girma has a physical model, yet you think his forecast has meaning and that it is based on “historical performance”, yet then you turn around and say only “poor information” is available.
How quaint to see a duplicitous contrarian in action.
Webby
You continue to demonstrate a combination of stupidity and arrogance in your comments.
What Girma has produced IS a forecast based upon historical performance so what I wrote was an accurate statement. It is not necessary to have a knowledge of climate science to produce a forecast based on historical performance. The real question is to what degree have conditions changed so that historical performance is no longer a reliable predictor of future conditions.
Now people like Mosher can correctly argue that Girma’s forecast is simplistic and potentially inaccurate because it does not take into account changes in systems forcing that will result in a different curve in the future. What I wrote is that IMO it is inappropriate to overly criticize Girma’s forecast using Mosher’s argument unless one is willing to quantify what the specific changes in the forcing are and what impact they will have and when.
Your view that it is necessary to have your own model in order to evaluate the effectiveness of other models or theories is ridiculous. Think about it. You have to realize that.
Rongo Ringo,
Girma has no forecast because he can’t explain how long it extrapolates to.
He is making things up, much like you are.
It is justified to remove the short and long term oscillations in the global mean temperature data.
This is because when you remove the short and long-term oscillation from the observed global mean temperature (GMT), you are left with the Secular GMT and its correlation with the sea level rise is almost a perfect one as shown below.
Correlation between observed GMT and sea level rise => http://bit.ly/KJeMje
Correlation between secular GMT and sea level rise => http://bit.ly/JD4rvT
As a result, removing the interannual and multidecadal oscillations from the GMT in order to obtain the secular trend is justified.
WHT
If that is REALLY “Girma’s prediction for the future”, I’d like to see it posted by Girma, not by you.
It could be you simply didn’t understand Girma’s analysis of the observed past multi-decadal warming/cooling cycles.
Max
I just replotted Girma’s equation. I realize that is beyond your technical ability, which from the looks of it is even below that of Girma’s.
What Climate Etc blogger that are on the AGW side failed to explain is the observation in Figure 1 of the instantaneous warming rates.
Here is also my result for the instantaneous warming rates=> http://bit.ly/FO7Xhi
Does not this result show no warming for the next decade or two?
Girma shows that it will start to accelerate over the next 200 years:
http://img26.imageshack.us/img26/7849/girmatrendology.gif
His plot of temperature increase per year is increasing every year, which makes it an accelerating measure.
WHT
I don’t see anything in Girma’s plot about “the next 200 years”.
IMO only an idiot (or possibly the IPCC) would be so foolish as to project global temperatures for 200 years.
Max
So, according to your logic, all that Girma is doing is plotting the historical data points. Big whoop. We can simply look at the original data in that case. He can no easier justify a 20 year extrapolation than a 200 year extrapolation without a physical model behind it.
You are not justified to say that.
This is because when you remove the short and long-term oscillation from the observed global mean temperature (GMT), you are left with the Secular GMT and its correlation with the sea level rise is almost a perfect one as shown below.
Correlation between observed GMT and sea level rise => http://bit.ly/KJeMje
Correlation between secular GMT and sea level rise => http://bit.ly/JD4rvT
As a result, removing the interannual and multidecadal oscillations from the GMT in order to obtain the secular trend is justified.
Judith,
What is the oscillations being recorded?
That would be planetary tilting and rotation. These would NEVER be exactly duplicated due to the planet slowing.
The planetary tilting helps to circulate the atmospheric gases.
These again are all mechanical processes.
Isn’t the basic issue that 20 years is not climate?
“The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s.”
What?
OK, there’s less and less room for GHGs (CO2). What happens when they have to postulate a cooling CO2 effect? The secular trend could look like this:
http://tallbloke.files.wordpress.com/2012/05/stozhkov-prediction.png
Which they claim is due to transient comet dust clouds.
Edim thinks that the current level of CO2 is all due to temperature, so if he believes this stuff, then the atmospheric concentration will crash in the next few years, and all plant life in the world will die.
Or Edim could just be a contrarian and he arbitrarily believes in whatever suits him. That’s more the ticket.
Web, I am just showing what the so-called secular trend could look like. In fact, that particular ‘prediction’ will be more on point than the official one, IMO. I don’t know if it’s comet clouds, I have no opinion about it. I do have one about the global climate indices in the next few decades though. And about carbon cycle, GHG theory, Earth’s energy budget, correlations with solar/orbital variability and oscillations etc.
I don’t know how much exactly of the current CO2 is due to temperature, I think nobody really looked into it in detail. I wonder what exactly Salby researched. From what can be observed on the face of it, the annual change in atmospheric CO2 content correlates very well with global temperature indices. That’s remarkable. Total change (since ~1960, ~75 ppmv) is the sum of the annual changes. I would say, on the face of it, more than half is due to warmth. And I bet I’m closer to reality than consensus (i don’t really know what’s the accepted fraction, but I think ~insignificant).
The crash and the plant life in the world is just your hysteria and projection. Yes, I’m contrarian about bureaucracy, scientific dogma, suppression and pseudo-science.
Edim thinks the cumulative co2 is due to the sum of the annual changes. Edim ignores the fact that for every season there is a decrease as well as an increase. Edim conveniently ignores all the seasonal decreases.
I really don’t know what to make of such obstinance other than to suggest that Edim is simply a contrarian with ulterior motives.
Web if you’re claiming that the whole (total, cumulative rise) is not equal to the sum of its parts (annual changes), I’m really at my wit’s end with you.
Of course there’s an increase and a decrease for every annual cycle (oscillation) and the sum (the annual change) is the sum of those two (dCO2annual = increase – decrease, dCO2total = sum (dCO2annual-i).
Again, if can not agree that 1 + 2 = 3, what can we agree on?
That is a consequence of a limited education, obstinance, or petty contrarianism.
Thus the seasonal changes balance out each year, and you are left with the anthropogenic CO2 excess, which is around 100 PPM over the last century. Voila.
No wonder you are losing it.
Web’s totally losing it. He’s obviously claiming that the total (cumulative) growth in atmospheric CO2 is not the sum of the annual growths! That the total growth since 1959 (~75 ppm) is not the sum of these:
http://www.esrl.noaa.gov/gmd/webdata/ccgg/trends/co2_data_mlo_anngr.pdf
In this case exactly 77.03 ppm since 1959.
Edam and his namesake, the Dutch cheese, are equally dense.
I hate to have to do this but here is the year-to-year changes in carbon emissions estimated by the CDIAC.
http://img29.imageshack.us/img29/4921/co2andcarbon.gif
What everyone will find is that the atmospheric CO2 concentration is the convolution of the CO2 adjustment time impulse response function with the carbon emissions forcing function.
Response functions maintain the same underlying frequency spectrum of the forcing function when convolved so that is why one sees the general tracking agreement of CO2 with carbon emissions.
If you want some whine with that cheese, I will have to say that I am one of the few people with the technical skill to be able to provide a true picture of the situation. Ha ha.
Web’s backpedaling.
Regarding your new subject, year-to-year changes in CO2 emissions are too small, they are not even close in magnitude to 1 – 2 ppm. Plot your red line properly scaled and it will be obvious.
Edim can’t do mathematical or scientific modeling. Pity him.
The complete answer is here:
http://theoilconundrum.blogspot.com/2012/03/co2-outgassing-model.html#SST_CO2
Web, you were claiming that the total cumulative growth in atmospheric CO2 (since 1959) is not the sum of the annual growths. That’s a very extraordinary claim. Either you have no understanding of very basic math or you’re not being serious.
Then you changed the subject and claimed that the variability in the annual growth is caused by year-to-year changes in anthropogenic CO2 emissions. That’s a very extraordinary claim again because the year-to-year changes in human emissions are ~one order of magnitude smaller than the changes in annual growth. Even IPCC is aware of this. Again, either no understanding or not bein serious.
Are you that dense?
I explain the cumulative as an anthropogenic cause, which has to be incremental over the years .
Fortunately I have that described in my book published last year, so you can not call me on that.
The yearly ripple is natural and your deficiency in math prevents you from following that argument as well.
Edim is left to parse the noise. Maybe he can find a pony somewhere in there.
An overall fail on his part.
I think WHT is a bot – how else can one explain his nonsense? Maybe a zombie?
A bot isn’t going to write first-rate data-driven blog analyses like these:
The fat-tail in CO2 persistence
How shock model relates to CO2 rise
The sensitivity of global temperature to CO2
Fat-tail impulse response of CO2
Derivation of MaxEnt diffusion applied to CO2 adjustment times
Temperature induced CO2 adds to the problem
CO2 outgassing model
Read them and weep. This is how ongoing analysis is done in the modern age, a gradual process of updating a model as one digs deeper into the data.
This is the exact opposite of the way you go about it, which is to make up wild assertion after wild assertion, with absolutely no math to back up your assertions with.
The drivel Edim preaches is also known as blowing smoke.
OK, a zombie then.
My assertions don’t need any complex math, it’s basic logic/math.
1) The total cumulative growth is the sum of the annual growths. This is a fact. The whole is the sum of its parts.
2) The year-to-year changes in atmospheric CO2 annual growth CANNOT be caused by variations in anthropogenic emissions simply because the year-to-year variations in emissions are ~one order of magnitude too small. IPCC agrees, consensus agrees, not that it matters. Again, no special math/model is necessary – just VERY simple math/logic.
These two points are not debatable.
Web, then your next installment could be land use impact on CO2 sources and sink during the Agricultural revolution.
Edim | May 30, 2012 at 9:07 am |
My assertions don’t need any complex math, it’s basic logic/math.
Now that’s a comment I like. One that appeals directly and solely to logic and basic math.
1) The total cumulative growth is the sum of the annual growths. This is a fact. The whole is the sum of its parts.
So “Sum(all years)= Year1 + Year2 + Year3.. Year-current”?
While it’s technically true, its also useless to us. We have trouble with validation, which any careful mathematician does (“checking your work”) as a basic step. We have trouble with trendology (sigma operations are not as easy to work with for curve fitting as other models). We have conceptual issues (what does ‘growth’ mean in this context).
We start with a baseline pooled CO2 concentration of 280 ppmv known to vary over the course of millennia in a range between 180 pmmv and 280 ppmv, with occassional excursions as high as about 305 ppmv but never so high as 310 ppmv, from the Antarctic ice core record as far back as 800,000 years ago. We have extremely high confidence in that data, and the contrary interpretations do not rise to the level to overthrow this claim.
So how do we define growth on a thing that itself is varying, has strong regional and seasonal differences, time of day differences, and feedbacks? Well, we don’t start by making the case too simple.. but when it’s currently almost 400 ppmv, and right now over 31% above the most rarified extreme peak level of the last 800,000 to twenty million years, and 41% above the top of the usual (sigma six) range, we can say we have seen extraordinary growth in only a quarter millennium. If we treated it as an instantaneous compound interest problem, with growth like that we would know the interest rate is tiny but positive. If we grew only at the linear quarter milliennium rate, we would see a doubling of CO2 in perhaps 55 thousand years. But that rate itself has been doubling lately with fair frequency, which makes this a problem on the scale of decades, not millennia. And oh look, we’re already 26 decades into the trend.
2) The year-to-year changes in atmospheric CO2 annual growth CANNOT be caused by variations in anthropogenic emissions simply because the year-to-year variations in emissions are ~one order of magnitude too small. IPCC agrees, consensus agrees, not that it matters. Again, no special math/model is necessary – just VERY simple math/logic.
This claim is mathematical nonsense, as any business operator knows. I can move $50 million in inventory in 52 stock turns a year, never having more than $1 million in inventory on hand. I promise you the interest rate on that $1 million is a tiny fraction of $50 million, and yet it deeply concerns me, while my margin on that $1 million, also a tiny fraction of $50 million, is keenly important to me.
These two points are not debatable.
Exactly. Basic math and logic wipe them out at first glance, so we never have to look at them again.
Except I expect them to be trotted out again and again and again by people who just can’t do math or logic.
Bart R,
Again those two points are not debatable. If you dispute any of them, there can be no reasonable debate. These two points came up because Web was disputing them.
1) The whole (total growth) is the sum of its parts (annual growths). Useless or not, the claim was that it’s wrong.
2) Interannual variations observed in the atmospheric CO2 growth rate CANNOT be caused by variations in human emissions – the variations in emissions are simply way too small compared to the changes in the atmospheric CO2 annual growth (~one order of magnitude). It doesn’t add up. Think! This is really basic.
The stupid, it does hurt.
Say that a CO2 increase from one year to the next is:
dCO2 = Year2 – Year1
Then sum of dT over all yearly increments up to year N is the total change:
CO2 = (Year2-Year1)+(Year3-Year2)+(Year4-Year3)+ … +(YearN-YearM)
Notice that all the pairs except for the first and last cancel in the arithmetic summation, and we are left with:
CO2 = YearN – Year1
which Edim thinks is some sort of genius finding and explains how CO2 and temperature are related.
Now he will go to some other misundesrtanding on his part and try to project it on me.
BTW, there is plenty of anthropogenic CO2 to account for a 100 PPM increase. Only about half of the CO2 has been sequestered so far, due to slow diffusive pathways, and the rest makes up the 100 PPM atmospheric increase.
Finally Web!
I guess I had to lay it out plainly for you to understand basic arithmetic.
I’s OK if you have to lay it out to understand basic arithmetic. I don’t need any laying out to understand 1 + 2 = 3.
I guess in 5 years you will be laying it out for us skeptics to understand basic physics of climate system and how it can’t be significantly affected by atmospheric CO2. Stupid skeptics, can’t lay out!
A huge fraction of the excess atmospheric CO2 has been contributed by man. The incremental increases of yearly emitted CO2 add up (minus the part that is gradually sequestered) to the excess we see today. The concise mathematical representation of this is the emission curve convolved with the adjustment time impulse response curve. In physics, the impulse response is also known as a Green’s function.
Salby has likely retracted his paper, and it will remain vaporware. You will be left to your own devices, sans mathematics. Boo hoo.
Ou hostes gives three possibilities, namely:-
I. IPCC AGW hypothesis:
II. Multi-decadal oscillations plus trend hypothesis:
III: Climate shifts hypothesis:
She then goes on the write
“I personally think that III is a more robust hypothesis than II, but working on II can help us with III.”
I am sorry to keep on writing about the same thing, but why oh! why cannot our hostess bring herself to state clearly that if she believes that the truth lies somewhere between II and III, then I, the IPCC hypothesis, must be wrong. All the evidence supports the contention that the IPCC is just plain wrong. Why doesn’t Dr. Curry say so, in words on one syllable?
Just curious: Why does Judith Curry’s monosyllabic opinion matter? Do you think that Dr Curry is such an authoritative voice that her words make facts? Do you think that if Dr Curry “come out” as a denialist that it would help things along for you in the wide world of climate science?
Hint: That she is willing to cite Dr Roy Spencer’s blog commentary as a form of scientific research is a bit of a dead give-away.
It’s actually rather amusing that a climate scientist would cite three hypotheses in her commentary and then discuss but two of them. It’s almost as though she is assuming that her audience has already discounted the IPCC reports!
certeris you write “Just curious: Why does Judith Curry’s monosyllabic opinion matter? Do you think that Dr Curry is such an authoritative voice that her words make facts? Do you think that if Dr Curry “come out” as a denialist that it would help things along for you in the wide world of climate science?”
My answer to your second and third questions is a very definite YES. As to the first question, the answer is a little more lengthy. At the moment just about all the professional scientific societies, led by the Royal Society and the American Physical Society have come out with very strong statements in support of CAGW. I have had discussions with my Member of Parliament here in Canada, David McGuinty, on this isuue, and have no answer to his claim that if all these organizations are so unanimous, how can I possibly be correct.
However, if we sketics are right, and we are, then sooner or later this unanimous opinion is going to break down. Someone or some institution is going to have to start this process. Once it starts, I believe it will be impoossible to stop. But how do we deniers get it to start? There have been people like Dr.Lovelock who have tried and failed. I believe a very strong voice who could start this process is that of Dr. Curry. And that is my answer to your first question.
”
However, if we sketics are right, and we are, then sooner or later this unanimous opinion is going to break down.
”
“And we are”?
That’s personal faith, my friend, not scientific fact.
Deniers / skeptics / whatevers can’t even agree amongst themselves what it is that believe and don’t believe – let alone propose a coherent alternate theory of the climate. In science, it is not enough to say “I disagree” – You must show how the current theory is undermined by supplying falsifying data, or a better-confirmed theory. Denialists typically fail at this because they are ignorant of the basics of climate science, most being far too busy being frightened by possible policy consequences (taxes bad!) or expressing outrage (again!) to bother studying such esoteric things as lapse rates and photochemistry.
“But how do we deniers get it to start?”
This whole “We’re right, but we’re being oppressed by the establishment” thing is getting old. You are not the first person to doubt estimates of climate change – Callendar’s and Plass’s early works were criticised – by other scientists – and as a consequence, the quality of later estimates was improved by the inclusion of better physical models.
You can’t get no respect?
You do what scientifically-minded people have done for generations – you get off your rhetorical flourish and DO science. You know, measurements, experiments, analysis, publications. No one is stopping you. Really.
ceteris
You’re a bit confused here, ceteris..
CAGW “believers” accept the CAGW premise of IPCC, namely that human GHGs have been the primary cause of recent global warming and that AGW, caused primarily by CO2 emissions, therefore constitutes a serious potential threat to humanity and our environment. Unfortunately, this premise is not falsifiable.
Rational skeptics may object to the validity of this premise for many reasons, which may not all be the same. but they all do not accept the CAGW premise until it can be validated by empirical scientific data from actual physical observations or reproducible experimentation, which has not yet occurred.
It is up to the proponents of the CAGW hypothesis to provide the specific empirical evidence to support this hypothesis, not up to the skeptics to provide such evidence that it is false.
Until the CAGW hypothesis has been validated by empirical data or has successfully withstood repeated falsification attempts, it remains an uncorroborated hypothesis, which rational skeptics have every justification to reject.
Max
I. external forcing, with natural internal variability providing high frequency ‘noise’.
II. large multidecadal oscillations with a superimposed trend of external forcing
III: synchronized chaos arising from nonlinear oscillations of the coupled ocean/atmosphere system plus external forcing
They all have some external forcing, varying from being the main event to just noise. External forcing could be GHG or many other things.
Looked at like this, type I includes hypotheses in addition to the IPCC’s.
Type I and III are complete explanations; type II needs something more to explain those oscillations, unless it is type III in disguise.
“observations of the rate of change of [global mean surface temperature].”
…and of course the rate of change of GMST is not observed, it’s calculated. Duh.
Andrew
A question … Can Professor Curry, or any of the other experts contributing here, comment on whether the mechanism behind hypothesis III is also able in principle to explain the 1/f scaling behaviour observed in geophysical time series over time scales longer than a few decades?
Life is short, and there are so many papers and blog articles on climate that one has to develop criteria for which ones to read. One of mine is that when I get to something that I know is demonstrably false, I stop reading. With this paper I didnt get beyond the first sentence of the abstract – which has been pointed out by numerous people above. As everyone knows, the rate of warming in the 80s and 90s was about the same as in the 20s and 30s. Did the authors look at HADCRUT? Did they look at their own figure 1? Was the paper refereed? Bizarrely they attribute their erroneous statement to the IPCC, who made no such claim. Perhaps the authors fell for the IPCC’s trick of comparing long and short-term trends (number 1 on my site).
Paul M
You have hit the nail on the head.
IPCC has used the “short-term/long-term” comparison to claim that we are seeing an acceleration in global warming.
In a cyclical record, such as we have observed in global temperature, one can always “cherry-pick” short-term tends which appear steeper than the longer-term trends.
One can do the same in reverse, i.e. the warming trend for the first half of the century was steeper than the trend for the entire century, but this certainly does not demonstrate a deceleration in the warming trend.
This is IPCC “smoke and mirrors”, that’s all.
Max
The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s
I look at the ice core data from The North and from the South and I see that the recent warming is well inside the range of the past ten thousand years and really well inside the range of the last eight hundred thousand years.
The thing that is unprecedented is the paradise of the most recent ten thousand years. Earth temperature is inside the plus and minus one degree range of most of the last ten thousand years. Earth temperature is well inside the plus and minus two degree outer limit range of all of the last ten thousand years.
http://hot-topic.co.nz/wp-content/uploads/2010/05/GISP2rescaled997.png
lolwot
Thanks for posting Greenland (reconstructed) temperature graph.
It shows (for what it’s worth) that MWP was slightly warmer than present global warming and more distant warm periods were even warmer yet.
And all that without any human CO2!
Max
NOPE. Untrue.
The Earth warmed at the same rate in the early 20th century. Phil Jones himself has conceded that the warming period in the late 20th century is statistically indistinguishable from that in the early 20th century – so there is nothing “unprecedented” at all.
Max
You’re going to have to prove that statement about the early 20th century. The evidence isn’t there based on the stats –
http://www.skepticalscience.com/pics/2_WarmingRates.png
According to WHT’s Figure 23 http://theoilconundrum.blogspot.com.au/2011/11/multiscale-variance-analysis-and.html
rates of warming of up to 2 degrees per year have been experienced during the past 10,000 years (WHT, please confirm or correct this statement if it is a misinterpretation of your chart).
What is the fastest rate of warming (degrees per year) experienced during the past century?
Woops, that should be 0.2 degrees per year.
There’s more than just 3 scenarios.
The sun in the latter half of twencen was in a phase referred to as The Modern Maximum. This can easily replace CO2 as the external forcing in any of the first three scenarios. There is compelling correlation between past solar minima and maxima and climate cooling and warming respectively. Moreover recent experimental work by Svensmark and CLOUD researchers that most of us here are aware of pins a causal tail on the solar magnetic field donkey. Eminent climatologist Richard Lindzen buttresses this as well with a cloud iris hypothesis which Roy Spencer agrees with as well. Recent work published by H. Moysés Nussenzveig finds an unexpected quantum effect by which light tunnels through cloud water droplets and is refleced precisely 180 degrees backwards which explains a long unexplained phenomenon called “The Glory” and makes clouds more reflective than was previously thought. High clouds modulated by solar magnetic field and cosmic ray flux are very likely the smoking gun behind the twentieth century “trend” and it ain’t secular.
One more thing is that the temperature record itself has been and remains pencil whipped to decrease temperatures in the earlier record and increase it in the later record. Removing two adjustments” (SHAP and TOB) from the raw data comprising the land temperature record completely removes the “secular trend”. There was never a warming trend in the raw data taken from thermometers. While the adjustments in question may have some validity it’s likely exaggerated which means there is less of a trend that begs for an explanation.
So, are you suggesting that the SHAP adjustment is wrong.?
If a station was at the top of a mountain from 1900 to 1930 and then
moved down the mountain, you are arguing that this record is good and should be left alone.
If a mountain-top station was moved down the mountain, it should not be a station move. The result should be two different stations with separate IDs. Please show a real-life example of where a station was moved down a mountain and retained the same ID.
All adjustments are wrong and unnecessary. Humans are too good at fooling themselves. Just leave it alone. If even the very small station subsets (~200?) show the same pattern like the whole set, why do we need so many? Just choose absolutely the best quality stations (no moves, reliable history, far from anthropogenic impact rural or urban…).
Mosher re; SHAP
I’m implying that with thousands of station moves the number that resulted in a cooler environment should have been statistically negated by an equal number of stations moving to a warmer environment.
Explain why that is not so.
I’m implying that the adjustments are opportunities for mischief and further that the opportunity was taken.
“There is compelling correlation between past solar minima and maxima and climate cooling and warming respectively.”
There’s no correlation between solar activity and global temperature in the last 50 years.
That there’s a correlation at other times is rather strong evidence that the recent warming has a different cause.
Which about “the modern maximum” did you not understand? I even linked it to its wikipedia article. The sun was more active from 1950 to 2000 than anytime in the past 400 years. Moreover now that is has gone into a quiet period there’s been no more global warming. LOL indeed.
‘In principle, changes in climate on a wide range of timescales can also arise from variations within the climate system due to, for example, interactions between the oceans and the atmosphere; in this document, this is referred to as “internal climate variability”. Such internal variability can occur because the climate is an example of a chaotic system: one that can exhibit complex unpredictable internal variations even in the absence of the climate forcings discussed in the previous paragraph.- http://royalsociety.org/policy/publications/2010/climate-change-summary-science/
‘Thinking is centered around slow changes to our climate and how they will affect humans and the habitability of our planet. Yet this thinking is flawed: It ignores the well-established fact that Earth’s climate has changed rapidly in the past and could change rapidly in the future. The issue centers around the paradox that global warming could instigate a new Little Ice Age in the northern hemisphere.’ http://www.whoi.edu/page.do?pid=83339&tid=3622&cid=10046
‘Recent scientific evidence shows that major and widespread climate changes have occurred with startling speed. For example, roughly half the north Atlantic warming since the last ice age was achieved in only a decade, and it was accompanied by significant climatic changes across most of the globe. Similar events, including local warmings as large as 16°C, occurred repeatedly during the slide into and climb out of the last ice age. Human civilizations arose after those extreme, global ice-age climate jumps. Severe droughts and other regional climate events during the current warm period have shown similar tendencies of abrupt onset and great persistence, often with adverse effects on societies.
Abrupt climate changes were especially common when the climate system was being forced to change most rapidly. Thus, greenhouse warming and other human alterations of the earth system may increase the possibility of large, abrupt, and unwelcome regional or global climatic events. The abrupt changes of the past are not fully explained yet, and climate models typically underestimate the size, speed, and extent of those changes. Hence, future abrupt changes cannot be predicted with confidence, and climate surprises are to be expected.
The new paradigm of an abruptly changing climatic system has been well established by research over the last decade, but this new thinking is little known and scarcely appreciated in the wider community of natural and social scientists and policy-makers.’ http://www.nap.edu/openbook.php?record_id=10136&page=1
The Royal Society, the National Academy of Sciences and the Woods Hole Oceanographic Institute support hypothesis 3. Is this a consensus?
There is a single complex dynamical system in climate and the variability can be seen in modes such such as ENSO, PDO, SAM, NAM, etc. These are standing waves in the climate system that vary abruptly. They modulate thermohaline circulation, ice, cloud, snow and biology which result in variability in solar forcing.
http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=CERES_MODIS-1.gif
Chief
Let me boil it down:
That’s why plotting several curves projecting global warming for various scenarios of human GHG increase out to year 2200 (as IPCC has done in AR4 WG1 report) is total nonsense.
Nassim Taleb in The Black Swan tells us that the problem with “experts” making predictions is NOT “what they know”, it is “what they do not know”.
Yogi Berra is quoted as saying: “Making predictions is tough – especially about the future”.
Donald Rumsfeld put it in slightly different words.
You’ve pointed out (here and in earlier posts) some of the many reasons why “climate surprises are to be expected”. Thanks.
Max
Let’s go back and look for a moment at JC’s comment here. She says:
On the Trends, Changepoints, and Hypotheses thread, I described three hypotheses that explain 20th century climate variability and change:
I. IPCC AGW hypothesis: 20th century climate variability/change is explained by external forcing, with natural internal variability providing high frequency ‘noise’.
II. Multi-decadal oscillations plus trend hypothesis: 20th century climate variability/change is explained by the large multidecadal oscillations (e.g NAO, PDO, AMO) with a superimposed trend of external forcing (AGW warming).
III: Climate shifts hypothesis: 20th century climate variability/change is explained by synchronized chaos arising from nonlinear oscillations of the coupled ocean/atmosphere system plus external forcing (e.g. Tsonis, Douglass).
________
Certainly the 20th century is a long time frame to try and characterize completely under either I, II, or III above. With the rapid increases in CO2 seen over the course of the century, the first half, or even first 3/4 of the century could have a far different set of dynamics going on as CO2 (and other greenhouse gases) increased greatly between 1900 and 2000, such that the period of 1900-1925, might have a far different weight of natural variability to external forcing, where one predominated more in the first quarter of the century, and one predominated more in the later quarter. Indeed, in private correspondence, Nir Shaviv wrote to me:
“I do agree that if you look at just the last few decades that the relative role of the human contribution is larger, in fact, probably larger than that of the sun. In any case, the relevant question is not that of how much warming there was by which source. Instead the really important question is what is the climate sensitivity.”
I agree with this completely. Furthermore, one must also take into account a period of time in which anthropogenic forcings (i.e. aerosols versus greenhouse gas increases) worked in opposition to each other, such that if the other one were not present, a far different global surface temperature response would have been seen and that external forcing by itself might have been greater as an overall trend than natural variability would account for.
What this amounts to, is that at some point, what starts as a small forcing or noise in the overall system can increase to become the dominant signal, and that as far as the human influence on climate, both our greenhouse gas forcings and aerosols forcings can have an impact that are opposite in effect and cancel each other out during certain periods. Each can also work in the same direction as natural variability, with for, example, CO2 increases working in the same direction as a more active sun or strong El Nino, or human aerosols working in the same direction as volcanic activity.
Bottom line: Trying to characterize an entire century under I, II, or III above may not only be not useful, but not helpful and lead to less, rather than greater understanding of the underlying dynamics.
To follow up on my previous post. This graph I think gives a very nice perspective on the relative importance of natural versus anthropogenic forcing and variability in the first part of the 20th century versus the later half:
http://www.skepticalscience.com/pics/KnuttiAttributionGraph.png
Notice how very different the relative natural versus anthropogenic attribution is from 1900-1925, versus 1975-2000. Quite a different mix and thus no single scenario seems to fit both periods nor the entire century.
R. Gates
The Knutti “natural vs. anthropogenic” graph posted in SkepticalScience should be taken with a grain of salt. This shows around 0.2 degC attributed to “natural” (out of 0.7 deg C total) or around 29%.
There are several studies by solar scientists, which show a higher solar contribution (overall 50+% on average). Just to name a few there are Stockwell (2011), Shapiro et al. (2010), Scafetta + West (2006), Stott et al. (2003), Geerts + Linacre (1997) and Solanki et al. (2004).
Hoyt + Schatten (1997) showed a good longer-term correlation between solar activity and US mean annual temperature.
Both Knutti and the solar estimates are quite a bit higher than the amount attributed to natural (solar) forcing by IPCC AR4 (only 7%).
All estimates do agree that the %-age solar impact was higher in the early 20th century warming than it was in the late 20th century warming, but the totals in the solar studies are higher than in the Knutti (or IPCC) estimates.
Max
PS to R. Gates
I’d agree with you that the data indicate a greater “relative importance of natural versus anthropogenic forcing and variability in the first part of the 20th century versus the later half”.
The open question is how much of the TOTAL past warming can be attributed to natural versus anthropogenic forcing and variability.
IPCC says 7% natural, 93% anthropogenic.
The solar studies seem to average at a bit more than 50% natural.
Knutti’s graph would ilie in the middle at around 29% natural.
Since IPCC AR4 tells us that all other anthropogenic forcing factors other than CO2 (other GHGs, aerosols, etc.) essentially cancelled one another out, we can estimate the 2xCO2 temperature response since 1850, when the HadCRUT3 record started, using the above extremes for natural versus anthropogenic forcing.
This calculation would show a 2xCO2 temperature response of between 0.8 and 1.4 degC.
Max
We can discuss relative percentages of anthropogenic versus natural forcings and variability and how they varied throughout the century forever with me citing one study and you citing a different one, and we would not come to an agreement. But this is not my point– my point is that it very likely is inappropriate, and even might lead to confusion to assume that the entire 20th century should be considered under scenario I, II, or III alone as we can agree that the mix of forcing, and what was noise in one part of the century may have become an underlying signal or trend in another. But the other point I was making was that anthropogenic warming alone doesn’t tell the whole story of the anthropogenic influence on climate in 20th century (or indeed, early 21st) as we must consider anthropogenic aerosol effects as well.
R. Gates
Disagree.
This is a much better one => http://bit.ly/HRvReF
Girma,
Not having followed your posts in any great detail, I’d be curious about the basis of this chart, and especially this “secular” trend as you’ve called it. Also, the cooling period from 1940 to the 1970’s has been studied in depth by many, and there are some fairly strong indications of what the negative forcings were that led to this cooling, but I’d of course always love to hear another take on it.
Not true Gates – this is not a system that responds linearly to so called forcing. So it is characterised as complex dynamical system – it is a sysytem with control variables and abrupt and non-linear change. It cannot be understood in terms of forcing and linear responses.
Anastasios Tsonis, of the Atmospheric Sciences Group at University of Wisconsin, Milwaukee, and colleagues used a mathematical network approach to analyse abrupt climate change on decadal timescales. Ocean and atmospheric indices – in this case the El Niño Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation and the North Pacific Oscillation – can be thought of as chaotic oscillators that capture the major modes of climate variability. Tsonis and colleagues calculated the ‘distance’ between the indices. It was found that they would synchronise at certain times and then shift into a new state.
It is no coincidence that shifts in ocean and atmospheric indices occur at the same time as changes in the trajectory of global surface temperature. Our ‘interest is to understand – first the natural variability of climate – and then take it from there. So we were very excited when we realized a lot of changes in the past century from warmer to cooler and then back to warmer were all natural,’ Tsonis said.
Four multi-decadal climate shifts were identified in the last century coinciding with changes in the surface temperature trajectory. Warming from 1909 to the mid 1940’s, cooling to the late 1970’s, warming to 1998 and declining since. The shifts are punctuated by extreme El Niño Southern Oscillation events. Fluctuations between La Niña and El Niño peak at these times and climate then settles into a damped oscillation. Until the next critical climate threshold – due perhaps in a decade or two if the recent past is any indication.
This figure from Tsonis’s paper suggests these climate shifts explain the early 20th century global warming but not the recent rise in global temperature. In fact the corrected temperature record looks almost apocalyptic in a hockey stick sense.
http://www.skepticalscience.com/images/Temp_minus_variability.gif
lolwot
The problem with the Tsonis curve from SkepticalScience, which you posted, is that it stops around 1998.
“Apocalyptic”? Indeed.
Taking out “natural forcing and variability” from a climate trend is a rather foolish (and impossible) endeavor to start off with. Most of our planet’s historical climate oscillations have been a result of natural factors, and it is very likely that this is also the case for the most recent ones – both the early and late 20th century warming cycles, the mid-century cycle of slight cooling, and possibly also the current start(?) of a new cycle of slight cooling.
Max
Captn.,
I have aboslutely no doubt about the strong influence of these oceanic and atmospheric cycles in the historic climate record, and the larger role they may play as modulators of short and longer term solar variations, but the abruptness of the late 20th century warming has a strong anthropogenic fingerprint. These natural cycles are of course still present but the underlying warming from anthropogenic greenhouse gas forcing lead directly to events like 2011’s global temperature, where it was not a record warm year overall, but it was record warm La Nina year, which is signficant for two reasons:
1) It came during the a weak solar cycle
2) It was during a the cool phase of the PDO
You are again incorrect
The solar cycle is not material – TSI varies by a Watt or so per m^2 at TOA and is not sufficient to by itself to be of much significance. At any rate the data from SORCE shows the cycle at or near a peak as we approached 2012. – http://lasp.colorado.edu/sorce/total_solar_irradiance_plots/images/tim_level3_tsi_24hour_640x480.png –
Over a longer time frame this may be of more significance. It is still not a linear response and not predictable as such.
The cool Pacific mode is interesting but it involves both the PDO and the frequency and intensity of ENSO. http://www.esrl.noaa.gov/psd/enso/mei/
A cool La Nina mode to 1976, a warm El Nino mode to 1998 and a cool mode since. The shifts between Pacific decadal modes is associated with changes in cloud radiative forcing. The data sources are a little problematic is quality and timing but the post 1998 climate shift for instance is captured by ERBS – http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=Wong2006figure7.gif, ISCCP-FD – http://isccp.giss.nasa.gov/zFD/an9090_SWup_toa.gif and Project Earthshine – http://www.bbso.njit.edu/Research/EarthShine/
The changes this century are captured by CERES. More intense and frequent La Nina are expected in a cool Pacific mode for a decade or three more. This will of course be associated with more low level marine stratocumulos in the central and north Pacific and result over a period in less energy stored in the global system. You can see both the uptick in cloud cover and reflected SW after 2009. This must result in ocean and atmospheric cooling.
http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=CERES_MODIS-1.gif
The Pacific accounts for most interannual variability in global climate and is non-stationary and non-Gaussian. A control variable for this in the non-linear system is solar UV and one of the feedbacks is cloud cover.
Captn,
The first and last sentences of your post would seem to be self-contradictory. Which is it? Does the sun play a role in climate modulation or not?
UV doesn’t carry much energy – it is a secondary effect involving ozone warming in the stratosphere and feeds into the sub-polar annular modes as I said. The direct changes in TSI you were referring to seem fairly minor. You really will have to try harder.
R. Gates | May 25, 2012 at 7:38 pm:
This is really the point.
Emphasizing the attribution of observed temperature variations would be the natural issue to study, if the starting point of the AGW worries would be in observations. But it is not, the starting point is in theory based expectation that developed in 1970’s and became strong before all significant empirical evidence for the effect.
The real case is that we have a theory based on well known physical principles but highly incomplete and incapable of telling accurately what the climate sensitivity really is. The “no-feedback climate sensitivity” can be calculated reliably but it’s not a real sensitivity of the Earth system but an artificial concept that’s likely to tell the order of magnitude of the real sensitivity while allowing for significant deviations to either direction in absence of further evidence from empirical observations and more refined and confirmed theories.
From this way of thinking it follows that the important question is not the share of AGW but directly the strength of AGW. For this question the natural variability is important as a factor that makes estimating the strength of AGW difficult but not on it’s own right.
For the climate science as a science the issues related to natural variability are of course central, perhaps even more central than AGW, but for UNFCCC related climate policy the natural variability is not as important as the climate sensitivity.
It is good to see you corresponding here again.
Your insights have been missed.
I would like if I could be certain that climate sensitivity were the important question.
That certainty would simplify cases; the fact of a means to remove all uncertainty about one single, knowable, climate sensitivity value would imply much about our understanding of climate in such a certain world, and about climate, too.
However, as you say, the real case is science about climate sensitivity is “highly incomplete and incapable of telling accurately what the climate sensitivity really is.”
I don’t foresee that condition being lifted in the near future.
Without substantial and intensive data collection and analysis, perhaps ten or a hundred times more than is carried on today, the situation will not change much.
Even if we did have such level of data as to be able to confidently pick out signals from natural and non-GHG anthropogenic sources to so great a degree of certainty, there are other problems.
If we could obtain a single simple approximation of the GHG component, we still would have questions perhaps too difficult to answer, about relative contributions of feedbacks, and even the linearity of climate sensitivity.
Rationally, a question that can’t be answered is never the important one.
The rational investigator moves the question up a level, out a layer, to “what might we answer that is of use to us?”
Bart,
I’m not sure whether I’m coming closer to what you have in mind, but the climate sensitivity is, indeed, only a part of the really important issues. I emphasized it, because it’s closer to what’s needed for policy decisions than the understanding of natural variability or the relative sizes of AGW and natural variability.
Climate sensitivity is, however, only closer to what’s directly useful for decision making, not all the way to the target. Real policy priorities do not involve climate indicators like anticipated temperatures, real policy priorities should concern human well-being over long periods and sustainability. In practice some indicators are needed to connect the ultimate priorities to near term decision making. Climate sensitivity and emission pathways allow for making estimates for future global average temperatures, but well-being or sustainability is not based on the global average temperature, it’s determined in much more complex way on the future climate as well as on all actions that will be done as part of climate policies.
For estimating the real influences on well-being many more issues must be considered in addition to the expected global average temperatures. For that a better understanding of climate is needed and that understanding should tell also about regional climates and about the risk of sudden transitions (tipping points). We need more advanced climate science, but we don’t need the ratio of natural to anthropogenic variability. We may learn more about that ratio, but we don’t have any specific use for that number.
Pekka Pirilä | May 26, 2012 at 4:04 am |
I appreciate the timeliness of your thoughtful and considered reply.
It raises for me some questions of premise.
We can agree climate sensitivity is only part (and I think we agree it is a part we cannot expect to directly and confidently comb out from the tangle) of a larger set of issues and questions. At some level, it seems obvious that there is such a set of issues and questions needed for policy decision-making.
However, what if this larger set is like the Gordion Knot?
What if the questions can never be disentangled the one from the other?
Then we must take a very different approach to policy. (If I follow your argument, “..real policy priorities should concern human well-being over long periods and sustainability.. In practice some indicators are needed to connect the ultimate priorities to near term decision making,”, we come to a very similar conclusion along a slightly different line of reasoning.)
It is important to decide, therefore, first if we can take a policy approach built on the answers to all of these issues and questions taken one-by-one, or must like Alexander at Telmissus choose from among the policy approaches that recognize the intractability of this problem set to reductionism, and slice through the whole set of questions with a sharper instrument of decision-making.
I propose that climate sensitivity may itself have sensitivity levels, to temperature and Earth surface albedo changes, to aerosol levels and ocean circulation phases, to such a degree it is invalid to speak ever of a single climate sensitivity to CO2.
We have good mathematical grounding in the Physics that this must be so, mechanically. The climate is not a simple homogeneous blob sitting on a sphere, but a kinetic mobile floating by the loosest tethers above the Earth’s solid surface. Kinetic motion is driven by heat. Heat the climate, and you move its features. Those features include cooling factors. The short-term net effect will inevitably be cooling phases within the GMT, if the climate is anything but the simplest linear system.
Our observations tend to support this position. Between 1940 and 1980, clearly, the CO2 level rose while the GMT fell. We could shrug at this as a matter of ‘natural variability’ of temperature due longer-scale influences; or we could observe that two decades is plenty of time for the global climate to integrate CO2 levels and observe that we had two full runs of two decades each under a regime where the climate sensitivy as measured was the opposite of the climate sensitivity of linear prediction from Physical properties. The “longer-scale influences”, being largely kinetic (ocean circulations, and aerosols changing as an indirect result of differences in circulations) are impossible to separate out from that globally integrated CO2 effect.
So the sign of climate sensitivity, in that sense, can itself change. We can try to work with a ‘no-feedback sensitivity’ vs. one with feedbacks, but again, as heat is not the only outcome of increased CO2 level (and must by the thermomechanical principle never exceed 50% of the total output), it may be possible that however large — and especially moreso if it is larger — the no-feedback climate sensitivity, then so long as we only measure temperature (and poorly measure it, too), then we will never be able to pick it out from the feedbacks. Each effect in the path of outcomes of CO2 rise will add chaos, raise the climate system to a new level of complexity, as it integrates with climate response.
I propose Alexander’s sharp blade is proportional distance of CO2 level outside the range of 260-280 ppmv alone as the only climate measure relevant to policy decision-making.
We can know this for a fact from first order logic and observation.
A) We know to fair confidence levels from research that runaway glaciation is only an issue below 240 ppmv, whether the glaciation causes the CO2 to drop or the CO2 drop causes the glaciation.
B) We know from ice cores that the baseline polar CO2 level of the past 800,000 to 20 million years has over 99.99% been between 180 ppmv and 280 ppmv, never in all that time so far as we can measure or extrapolate rising above 300 ppmv until the Industrial Age.
C) We were at the peak. While at the peak, the most reasonable interpretation of the facts is we moved the level above the peak by our actions and with the feedback responses to our actions, into more and more unfamiliar levels.
D) Familiarity is a good thing. It excuses mental laziness. We can know all the workings of a system, if we are clever, and fine tune them, or we can reason that the system has always worked while within familiar bounds, and not be bothered to try to monkey with it.
I say we lack the maturity yet to monkey with the unfamiliar.
Hence, being below 260 ppmv would be a concern, but above 280 ppmv is likely our own fault and (as we know the higher the level of complexity of a nonlinear system, the less stable and more given to extreme states and unpredictable phase changes) increasingly more expensive the farther from familiar levels we get.
Everything else in climate? Preparing for emergencies and planning for conditions is increasingly less feasible, as the level of complexity rises due rising CO2E. Costs for preparation, for insurance, will rise. More and more the policy decision will not be to prepare or insure, or even to adapt, but just to write-off losses.
ppirila
You are not justified to say that.
This is because when you remove the short and long-term oscillation from the observed global mean temperature (GMT), you are left with the Secular GMT and its correlation with the sea level rise is almost a perfect one as shown below.
Correlation between observed GMT and sea level rise => http://bit.ly/KJeMje
Correlation between secular GMT and sea level rise => http://bit.ly/JD4rvT
As a result, removing the interannual and multidecadal oscillations from the GMT in order to obtain the secular trend is justified.
No warming for 14 years:
1998 0.528667
1999 0.303583
2000 0.278083
2001 0.40675
2002 0.4545
2003 0.46675
2004 0.443667
2005 0.474333
2006 0.425
2007 0.396833
2008 0.329167
2009 0.435917
2010 0.469917
2011 0.339417
How many more years of no warming is required to falsify AGW?
Girma,
One things that I don’t hear you or too many others talking about is the effects of anthropogenic aerosols. IMO, any model of climate of the 20th century and early 21st that doesn’t include anthropogenic aerosol effects isn’t worth much.
R. Gates
It may be true, as you write that
But it can also be said that our knowledge of global anthropogenic aerosols and their impact on global temperatures is so rudimentary that:
either
If aerosols are simply being “plugged in” to make the observations fit the theory, including them is worse than useless.
Max
I disagree about modeling the effects of anthropogenic aerosols. The science of their effects is not nearly so rudimentary as you state, and we can even distinguish their effects from those of natural aersol sources. While much remains to be discovered and quantified related to
Anthropogenic aersol effects, we do know enough to include them in global climate models with decent fit to both 20th and 21st century negative forcing effects on the global climate.
Girma,
Seems you are focused on the puny heat reservoir of the troposphere. Why is that? It has such a low thermal inertia and low heat capacity, that it would seem obvious that anyone who wanted to really look for a long-term “secular” effect in Earth’s energy system would look first and foremost to the ocean.
R. Gates
I agree. The pattern is due to ocean cycles.
Are “ocean cycles” a cause or effect? And what “pattern” over what timeframe are you talking about? The “secular” trend may not be a single trend at all, but simply a composite of all forcings and their related feedbacks driving the climate at any one time. The only scientific thing to do (which is exactly what is being done) is to identify through attribution the forcings that go into making up the given composite “secular” trend. Solar, volcanic, aerosol, greenhouse gas, ENSO, PDO, AMO, etc. must al l be taken into account when unwrapping the composite trend into it’s components and their short and long term feedbacks. It is the individual components and their feedbacks that have real physical meaning. In looking at them, only then does a picture of the climate begin to emerge that starts to make sense and the use of the term “secular” trend have some justification.
R gates
You inexplicably keep disappearing from threads;
http://judithcurry.com/2012/05/24/heartburn-at-heartland/#comment-203276
tonyb
If one conducts a monte carlo simulation, and allows temperature by chance to increase, decrease or remain the same you end up with a record that looks very much statistically like the record of global average temperature. Sometimes temperatures go up for long periods, sometimes they go down. Without any forcings.
Why assume that climate needs forcings to change? This assumption underpins much of modern climate science, yet has never been demonstrated to be true. Where is the science behind climate science?
Girma | May 25, 2012 at 11:35 pm | Reply
No warming for 14 years:
How many more years of no warming is required to falsify AGW?
I believe it was Gavin (or Mann?) on RC said that it was impossible that temperatures would not respond within 15 years if AGW was correct. However more recently I believe it was Trenberth that said 17 years.
I would expect this limit to increase as we approach 17 years. Some factor such as carbon black 47 will be discovered to have help temperatures in check while CO2 was rising, even though CO2 is by far the strongest driver of climate according to the IPCC. While in the same breath they admit clouds are not well understood. They know they are not important to climate for this very reason. If they were, they would be better understood.
ferd, it was Ben Santer who wrote that it takes 17 years for a temperature trend to become statistically significant.
http://www.agu.org/journals/jd/jd1122/2011JD016263/
We now have a trend of slight cooling since January 1998:
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1998/plot/hadcrut3vgl/from:1998/trend
That’s over 13 years.
I’d agree with you that one of the “Team” will move the goal-posts soon.
Max
Correction
Pardon me, ferd. We now have over 14 years of slight cooling (not 13)
Max
Years and years of almost monotonic increase in ocean heat content.
http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/heat_content2000m.png
I am not a climate scientist but I do understand that relative heat capacities and the heat contained in large capacity objects (oceans) are much more important than transient measures of temperature in low capacity objects (atmosphere).
Web
So we agree sometimes.
And since that heat continues to increase without abatement, I see that Girma is no longer a global warming skeptic.
WHT
Tell it to IPCC.
They have been touting “globally and annually averaged land and sea surface temperature” (as measured by HadCRUT3 since 1850, “warts” and all) as the primary measure of “global warming” for years.
So now that this indicator is showing a trend of no warming (or even slight cooling), you feel we should change indicators?
(BTW, I fully agree with your logic that ocean heat content would be a much more indicative metric than the surface air temperature, for the reasons you, as well as Pielke, have stated.)
The problem is, WHT, the data we have are so poor and dicey (especially prior to Argo in 2002) that they are essentially meaningless. And since Argo, we have had conflicting series showing cooling versus warming, with NOAA experts telling us of “speed bumps”, “warming bias” of earlier expendable XBT devices, etc.
Let’s wait until we have an extended record from Argo (let’s say around 2022, with 20 years of data) before we draw any conclusions.
Max
We have seen this before of course many times.
This from von Schuckmann is much more detailed in the period of better data – http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=vonSchuckmann-OHC.gif –
This from Wong et al 2006 shows part of the reason why prior to CERES and ARGO.
In the CERES era we have this – http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=CERES_MODIS-1.gif
Webby lacks the knowledge to discuss any issue in detail and then insists that he is the only one who can use a one dimensional formula for the multidimensional carbon cycle. He is the only one who wants to. Bizarre. :lol:
Wong et al – http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view¤t=Wong2006figure7.gif
Kangaroo posts charts free of context, because he is nutso.
To difficult to google Wong et al 2006?
TAKMENG WONG, BRUCE A. WIELICKI, AND ROBERT B. LEE III (2006)Reexamination of the Observed Decadal Variability of the Earth Radiation Budget Using Altitude-Corrected ERBE/ERBS Nonscanner WFOV Data
I had obviously neglected to link this in the comment above. But I have quoted, linked and described this many times. I use peer reviewed literature to understand not insults and nonsense to flatter my ego. I have yet to see you reference anything of any substance – only your own loser website.
Correction. It is a blog and a winner of a blog it is. I like the way that Google has it indexed so that I can dig up whatever I need by a simple search. The lesson is that you get out whatever hard work you put into it.
Measured by traffic it is such a loser website. Measured by relevant, useful and correct content – it is just insane.
Skippy the Kangaroo said:
BTW, it’s a blog, not a website. Technically, a website would have more than just a blogspot blog, which is why I think you are confused by the lack of other features that one would normally associate with a website.
Fixed a typo. It should be “insanely great”. I think you fell asleep at the keyboard.
BTW a websire is simply a collection of pages. Why do you insist on stupid comments like this one? If you actually did some homework instead of winging it all the time – you know in depth and at length. As opposed to short opinion pieces of no value at all and invariably wrong.
Did you read and understand the reference or are you simply posting immature, irrelevant and unwelcome ad hom? I think I know the answer.
Web, I can’t say I agree with your comments on long term trends in natural variability being unable to cause long term trends in temperature. There are more to clouds than type and quantity. There is also location. Should there be a long term trend in heat transfer by an ocean current, the storm patterns will change location thus changing the albedo of the earth.
Which changes will show a reinforcing (i.e. positive) feedback? Where’s your model?
Web, I don’t have to have a model. I get to speculate on anything I want to. If my speculations required a model I would be doing the work I currently pay others to do with my taxes. If they need me to do their work they should find a new job. Where is their model showing it doesn’t?
People do not usually model what won’t happen. Otherwise one would have to model the improbability of monkeys flying out your butt. That and an infinite number of other scenarios.
Web, what leads you to believe it isn’t already happening? We have no long term data on ocean heat transport of any reliability. They have run the models to show what would happen if the THC slows down and the results were anything from a slight cooling of the N.H. to a drastic cooling of the N.H. I suspect they have already run the models on a long term increasing trend and it shows such a trend would warm the N.H. and I just can’t find the results. You need to broaden your horizens some. There is more to the puzzle than are you doing the math right. There is also the question are you doing the right math.
I follow the basic and essential science. I have no skin in the game. A warming is a warming and the only uncertainty is in the extent.
Warming from the sun and a small amount from the earth’s core is responsible for our current temperature. And the GHG’s of H2O and CO2 is responsible for the 33C excess warming above the purely radiation energy imbalance arguments. Why is it so hard to believe extra CO2 will cause extra warming?
It is a most laughable exercise in how the skeptics can keep up the charade.
“Why is it so hard to believe extra CO2 will cause extra warming”
Because there’s no need to believe anything in science, au contraire – it’s essential not to believe. Another reason is that there’s no evidence – in fact there’s evidence that it will not.
Edim | May 30, 2012 at 9:16 am |
Because there’s no need to believe anything in science, au contraire – it’s essential not to believe.
This statement is true.
However, it’s also essential never to dismiss.
No amount of evidence interpreted (so far as I can tell in Edim’s case, irrationally, but I haven’t seen all evidence or all interpretations) as contrary to a claim suffices to completely dismiss it.
Of all the hypotheses, the group of hypotheses put out by the IPCC in 2007 remain by and large the most probable of the ones extant in 2007.
The last five years haven’t especially overthrown much of that body of work, and the core AGW hypotheses of rising man-made temperature and serious risks of harm and cost are more, not less, apparent.
That’s the simple state of things as they stand today overall.
I don’t have a problem with extra. I just want it quantified a little better than “extra” before I can support a complete revamping of our energy base. The most laughable exercise is how anyone can claim we have the evidence to support such action at this point.
The paper says “A spurious temperature drop in the GST time series derived from HadCRUT3v data, with an amplitude of about 0.3°C occurs starting in August 1945, when the U.S. Naval fleet, which was measuring sea surface temperature (SST) using thermometers embedded in the condenser intake returned to port and British ships, which were taking bucket measurements of SST, replaced them as the dominant source of SST data (Thompson et al. 2008, 2009).”
-6 and 9 August 1945, Little Boy and Fat Man
??
Set the atmosphere on fire, or on ice.
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