Guest Post by Ira Glickstein.
The graphic from RealClimate asks “How well did Hansen et al (1988) do?” They compare actual temperature measurements through 2012 (GISTEMP and HadCRUT4) with Hansen’s 1988 Scenarios “A”, “B”, and “C”. The answer (see my annotations) is “Are you kidding?”
HANSEN’S SCENARIOS
The three scenarios and their predictions are defined by Hansen 1988 as follows
“Scenario A assumes continued exponential trace gas growth, …” Hansen’s predicted temperature increase, from 1988 to 2012, is 0.9 ⁰C, OVER FOUR TIMES HIGHER than the actual increase of 0.22 ⁰C.
“scenario B assumes a reduced linear growth of trace gases, …” Hansen’s predicted temperature increase, from 1988 to 2012, is 0.75 ⁰C, OVER THREE TIMES HIGHER than the actual increase of 0.22 ⁰C.
“scenario C assumes a rapid curtailment of trace gas emissions such that the net climate forcing ceases to increase after the year 2000.” Hansen’s predicted temperature increase, from 1988 to 2012, is 0.29 ⁰C, ONLY 31% HIGHER than the actual increase of 0.22 ⁰C.
So, only Scenario C, which “assumes a rapid curtailment of trace gas emissions” comes close to the truth.
THERE HAS BEEN NO ACTUAL “CURTAILMENT OF TRACE GAS EMISSIONS”
As everyone knows, the Mauna Loa measurements of atmospheric CO2 proves that there has NOT BEEN ANY CURTAILMENT of trace gas emissions. Indeed, the rapid increase of CO2 continues unabated.
What does RealClimate make of this situation?
“… while this simulation was not perfect, it has shown skill in that it has out-performed any reasonable naive hypothesis that people put forward in 1988 (the most obvious being a forecast of no-change). … The conclusion is the same as in each of the past few years; the models are on the low side of some changes, and on the high side of others, but despite short-term ups and downs, global warming continues much as predicted.”
Move along, folks, nothing to see here, everything is OK, “global warming continues much as predicted.”
CONCLUSIONS
Hansen 1988 is the keystone of the entire CAGW Enterprise, the theory that Anthropogenic (human-caused) Global Warming will lead to a near-term Climate Catastrophe. RealClimate, the leading Warmist website, should be congratulated for publishing a graphic that so clearly debunks CAGW and calls into question all the Climate models put forth by the official Climate Team (the “hockey team”).
Hansen’s 1988 models are based on a Climate Sensitivity (predicted temperature increase given a doubling of CO2) of 4.2 ⁰C. The actual CO2 increase since 1988 is somewhere between Hansen’s Scenario A (“continued exponential trace gas growth”) and Scenario B (“reduced linear growth of trace gases”), so, based on the failure of Scenarios A and B, namely their being high by a factor of three or four, it would be reasonable to assume that Climate Sensitivity is closer to 1 ⁰C than 4 ⁰C.
As for RealClimate’s conclusion that Hansen’s simulation “out-performed any reasonable naive hypothesis that people put forward in 1988 (the most obvious being a forecast of no-change)”, they are WRONG. Even a “naive” prediction of no change would have been closer to the truth (low by 0.22 ⁰C) than Hansen’s Scenarios A (high by +0.68 ⁰C) and B (high by 0.53 ⁰C)!
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Phil. March 23, 2013 at 4:54 pm:
Thanks for the link to Climate Audit, but it dates from 2008. Do you have anything more recent for CFCs, CH4 and N2O?
I respect McIntyre and accept his conclusion that Hansen 1988 way, way, way over-estimated the grown of “Greenhouse gases” other than CO2. Therefore, actual CFCs, CH4 and N2O levels fell considerably below even Scenario C assumptions, and way, way, way below the Scenario A and B assumptions.
So, let us take score:
1) A close look at Fig 2 from Hansen 1988 indicates that they assumed the warming effect of CO2, alone, was about equal to the combined warming effect of CFCs, CH4 and N2O. So, if they over-estimated one (CO2) and underestimated the other (CFCs, CH4 and N2O) by about the same amount, we should expect that the temperature anomaly would flatline, which, over the past decade and a half, it did. Score one for dumb luck!
2) Scenario A got the exponential increase in CO2 pretty much correct, but they way, way, way over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario A is so much higher than actual temperature anomalies.
3) Scenario B assumed a linear increase in CO2, which turned out to be pretty much correct, since the actual exponential increase is very mildly upward. But they way, way, way over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario B is also much higher than actual temperature anomalies.
4) Scenario C assumed a linear increase in CO2, until the year 2000, where they assumed it would flatline. That to this dayturned out to be wrong, because CO2 has continued its mild exponential rise. They slightly over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario C is only 31% higher than actual temperature anomalies.
Bottom line score; 1 for 4, and that 1 was dumb luck. Not too good. Not even for Scenario C, the closest to actual temperature anomalies.
Yet, they say their model (or “simulation” as RealClimate recently called it), in their words “while not perfect … has shown skill”.
RealClimate is comfortable with that. Are you? If so, they have one foot in a bucket of scalding water, and the other foot in a bucket of ice, but, on the average, they are comfortable :^)
Ira
Ira Glickstein, PhD says:
March 24, 2013 at 6:34 pm
“Scenario A got the exponential increase in CO2 pretty much correct…”
Good comment in general, but I must take issue with this. The increase in atmospheric CO2 concentration is not exponential. It is at best quadratic.
The derivative of an exponential is an exponential. As is readily apparent in the graph I keep bringing up, the derivative is at best linear, and in fact is decelerating along with the globally averaged temperature in the last decade or so.
[Bart, you are correct. According to Wikipedia:Quadratic growth is a special case of a convex function, and should not be confused with exponential growth, a better-known growth function. “Convex growth” means “increasing at an increasing rate” (the second derivative or second difference is positive), while quadratic growth means “increasing at a constantly increasing rate” (the second derivative is positive and constant), and exponential growth mean “increasing at a rate proportional to current value” (second derivative is proportional to current value, which is positive; this is because the first derivative is proportional to the current (positive) value, hence (taking derivatives) second derivative is proportional to first derivative, hence (proportional to proportional is proportional, second derivative is proportional to first derivative). That is, quadratic and exponential growth are both different special cases of convex growth. Thank you for clearing this up. Ira]
Bart:
In building a model, the deductive approach has a shortcoming. It assumes that information needed for deductive conclusions is not missing but information is, in fact, missing. The inductive approach introduces problem not faced under the deductive approach; this problem is called “the problem of induction.” In each circumstance in which an inference is made by the model there are several candidates for being made. How can the one candidate that is correct be discriminated from the many that are incorrect?
This problem was solved circa 1963 by the theoretical physicist Ronald Christensen. Logic could be extended from its confines in the deductive logic and through the inductive logic via replacement of the rule that every proposition had a truth value by the rule that every proposition had a probability of being true.
In the resulting “probabilistic” logic, every proposition had a unique measure. The measure of a proposition was its entropy. It followed from the existence and uniqueness of the measure of an inference that the problem of induction could be solved by a kind of optimization. Depending upon circumstances, the correct inference was the one that minimized the entropy or that maximized the entropy under constraints expressing the available information. Christensen called this rule “entropy minimax.” Logic held principles of reasoning. The principles of reasoning were entropy minimax.
In concert with colleagues who included me, Christensen tested this hypothesis in a number of real world circumstances. It held up to testing. Among the scientific theories that were produced by entropy minimax were thermodynamics, the modern theory of communications and the first successful long range weather forecasting models.
However, though Christensen published his work, few scientists or academics read these publications. (Among the few who read some of them were a couple of professors from Ira Glickstein’s systems science department at Binghamton University. One was the department chairman, George Klir)
In their ignorance, scientists continued to build models as they had done so for centuries. This was by discriminating the one correct inference from among the many candidates using the intuitive rules of thumb that I call “heuristics.” However, in each instance in which a particular heuristic selected a particular inference as the one correct inference, a different heuristic selected a different inference as the one correct inference. In this way, the method of heuristics violated Aristotle’s law of contradiction thus being illogical.
Almost all of the models that are used today in practical decision making were built by the method of heuristics. Kalman filters are built by it. Use of this method introduces variability in the quality of the models that are generated in which the quality depends upon the model builder’s luck in the selection of heuristics.
If you’d like to follow up, I recommend that you start with one of two tutorials. Judith Curry published one of them in her blog as a three part series under the title “The Principles of Reasoning” in 2011. The other, also written by me, is at http://www.knowledgetothemax.com . A bibliography is available at the same URL.
Entropy minimax builds the best possible model from given informational resources. With the availability of this idea, generalizations can be reached about the possibilities from climatological research. One of these generalizations is that informational resources are insufficient for the construction of a model that predicts global temperatures over a horizon long enough (about 30 years) for this model to be usable for making policy on CO2 emissions. In ten thousand years, we may have enough observed events for this to happen. In the interim, entropy minimax will dictate that the global temperature varies independent of the CO2 level.
Terry Oldberg March 25, 2013 at 8:26 am:
THANKS Terry Oldberg for reminding me of my days as a part-time Masters and then PhD student in the System Science department at Binghamton University! George Klir was chairman of the department while I was a student. He pronounces his name “clear” and, what I most remember about him was that he was not “clear” to me at all. As I recall his work, he was very focussed on information theory and characterized all kinds of uncertainty into probabiity, possibility and a few other levels and sets as fuzzy, crisp and so on and on.
A computer program captured some of Klir’s theories and allowed a complex system to be reduced by, as I recall, sequentially eliminating links that had the lowest interconnectivity and interdependency between subystems and components.
After Klir retired as chairman, and after I got my PhD (at age 57 in 1996), I taught System Engineering and Human Factors in the System Science Department and Artificial Intelligence in the Computer Science Department as an Adjunct at Binghamton University. That was part-time because my “real” job was as a Sr. System Engineer at Lockheed Martin (formerly IBM) in Owego, NY.
Ah, the “good old days” (when the air was clean and sex was dirty :^) -Or so our distorted memories claim-
Ira
D.B. Stealey says:
March 24, 2013 at 3:58 pm
Phil.,
What would it take for you to admit that AGW is either non-existent, or so minuscule that it isn’t worth worrying about?
Scientific evidence.
Numbers, please: how many more years of little or no global warming would it take? How much more human-emitted CO2 without runaway global warming would it take?
Since we’re not in a period of no warming that’s not an issue, I have never expected runaway global warming in any case.
Or, is your mind made up to the point where nothing can possibly convince you that your “carbon” conjecture was/is wrong? <— [Like Hansen's true belief.]
Planet Earth is not agreeing with you, Phil. Who should we believe, you and Hansen? Or the planet?
Believe the planet, in a couple of years time when the arctic is devoid of sea ice perhaps you’ll start to see the light?
[Phil: You have never expected RUNAWAY global warming -GOOD TO HEAR- but, but you expect the arctic to be devoid of sea ice in a COUPLE YEARS TIME ? Forgive me, but that seems inconsistent. Ira]
Phil and D.B. Stealey :
Arguments being made in this thread have become disjointed. In another part of it, I believe I have convinced participants that we have no way of knowing of the effect of raising the CO2 concentration upon global temperatures because, in organizing their study of global warming, climatologists such as James Hansen have blown their assignment. We’d might as well have shoveled the 200 billion US$ spent by Hansen and his colleagues down a rat hole.
Ira Glickstein, PhD says:
March 24, 2013 at 6:34 pm
Phil. March 23, 2013 at 4:54 pm:
Thanks for the link to Climate Audit, but it dates from 2008. Do you have anything more recent for CFCs, CH4 and N2O?
No but feel free to get the raw data and plot it, after all it’s you who wrote the post entitled “How well did Hansen (1988) do?”
http://cdiac.ornl.gov/oceans/new_atmCFC.html
http://www.esrl.noaa.gov/gmd/dv/iadv/graph.php?code=MLO&program=ccgg&type=ts
I respect McIntyre and accept his conclusion that Hansen 1988 way, way, way over-estimated the grown of “Greenhouse gases” other than CO2. Therefore, actual CFCs, CH4 and N2O levels fell considerably below even Scenario C assumptions, and way, way, way below the Scenario A and B assumptions.
That wasn’t his conclusion!
You continue to give me the impression that you haven’t read the paper we’re discussing, you certainly don’t understand it!
So, let us take score:
1) A close look at Fig 2 from Hansen 1988 indicates that they assumed the warming effect of CO2, alone, was about equal to the combined warming effect of CFCs, CH4 and N2O. So, if they over-estimated one (CO2) and underestimated the other (CFCs, CH4 and N2O) by about the same amount, we should expect that the temperature anomaly would flatline, which, over the past decade and a half, it did. Score one for dumb luck!
2) Scenario A got the exponential increase in CO2 pretty much correct, but they way, way, way over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario A is so much higher than actual temperature anomalies.
The point of Scenario A was to illustrate what would happen if existing trends in emissions continued, thus it was referred to as ‘business as usual’. “Scenario A assumes that growth rates of trace gas emissions typical of the 1970s and 1980s will continue indefinitely”. They didn’t over-estimate the increase, by definition that was what it was!
“Scenario A…., must inevitably be on the high side of reality in view of resource constraints and environmental concerns”
“Global warming…..occurs in all three scenarios…….depending on trace gas growth”
3) Scenario B assumed a linear increase in CO2, which turned out to be pretty much correct, since the actual exponential increase is very mildly upward. But they way, way, way over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario B is also much higher than actual temperature anomalies.
Scenario B assumed growth so as to maintain the rate of growth in greenhouse forcing stayed at the current rate. Hansen judged that “Scenario B is perhaps the most plausible of the three cases.”
4) Scenario C assumed a linear increase in CO2, until the year 2000, where they assumed it would flatline. That to this dayturned out to be wrong, because CO2 has continued its mild exponential rise. They slightly over-estimated the increase in CFCs, CH4 and N2O, which have pretty much flatlined. That explains why Scenario C is only 31% higher than actual temperature anomalies.
Scenario C was chosen to be the result of “a more drastic curtailment of emissions than has generally been imagined.”
The scenarios were chosen to “yield sensitivity experiments for a broad range of future greenhouse forcings”. The goal being to bracket possible future climates, in this they were successful as you admit. In fact the then accepted value for sensitivity was somewhat high, if the currently accepted value is used then the result falls between B & C as one would expect from the actual emissions.
Bottom line score; 1 for 4, and that 1 was dumb luck. Not too good. Not even for Scenario C, the closest to actual temperature anomalies.
Pretty much bang on for a 25 years in the future!
Yet, they say their model (or “simulation” as RealClimate recently called it), in their words “while not perfect … has shown skill”.
Indeed it has, try reading the paper and understanding it.
RealClimate is comfortable with that. Are you? If so, they have one foot in a bucket of scalding water, and the other foot in a bucket of ice, but, on the average, they are comfortable :^)
Yes because I understand the paper, and have read it several times, clearly you haven’t.
Phil. says:
March 25, 2013 at 5:05 pm
Since we’re not in a period of no warming that’s not an issue, I have never expected runaway global warming in any case.
“Planet Earth is not agreeing with you, Phil. Who should we believe, you and Hansen? Or the planet?”
Believe the planet, in a couple of years time when the arctic is devoid of sea ice perhaps you’ll start to see the light?
[Phil: You have never expected RUNAWAY global warming -GOOD TO HEAR- but, but you expect the arctic to be devoid of sea ice in a COUPLE YEARS TIME ? Forgive me, but that seems inconsistent. Ira]
‘Runaway’ I interpret as heading towards a Venus like state, which I don’t believe will happen.
An increase of a few degrees however is another matter and is sufficient to cause problems for us. Melting of the Arctic sea ice would be one effect of such a change, I would be surprised if that isn’t substantially complete in a couple of years. Here’s a graphic of the progress so far:
http://iwantsomeproof.com/extimg/siv_september_average_polar_graph.png
Given the fragmentation of the present ice, which is mostly FYI, I wouldn’t be surprised to see another record low this fall.
DirkH says:
March 24, 2013 at 4:07 pm
Phil. says:
March 24, 2013 at 2:41 pm
“result to lie between B and C. Hopefully the ongoing melting of the Arctic sea-ice won’t lead to a recurrence of the growth in CH4 but current measurements in the Arctic suggest otherwise.”
The greenhouse effect of CH4 competes with H2O and is only measurable in dry winter weather. Are you SURE it’s a problem when it can’t even be measured in warm moist weather?
And yet it’s routinely measured by satellites, how do you suppose that is?
At the surface it’e easily measured with an FTIR spectrometer, so I don’t think that you premise holds up.
Phil. says: March 26, 2013 at 9:21 am:
DirkH and Phil: I accept that the “Greenhouse Effect” is real see this in my series on Visualizing the “Greenhouse Effect” and that CH4 is a “Greenhouse gas”.
However, as shown clearly here, all the CH4 peaks are coincident with portions of the spectrum where H2O is saturated or nearly so. Therefore, as DirkH is saying, given the prevalence of H2O, the contribution of rising CH4 levels (if they were actually rising) to actual warming of the Earth surface would be minimal, except in dry winter weather.
Ira
Please Ira, showing a low resolution cartoon of the spectrum shows nothing ‘clearly’. Also it’s for the surface the situation is much different at altitude!
To argue over the magnitude of the climate sensitivity ( aka the equilibrium climate sensitivity (TECS) ) is scientifically nonsensical, for the equilibrium temperature is not an observable.
Ira Glickstein, PhD says:
March 27, 2013 at 11:37 am
However, as shown clearly here, all the CH4 peaks are coincident with portions of the spectrum where H2O is saturated or nearly so. Therefore, as DirkH is saying, given the prevalence of H2O, the contribution of rising CH4 levels (if they were actually rising) to actual warming of the Earth surface would be minimal, except in dry winter weather.
Here’s a portion of the actual spectra rather than a cartoon.
http://i302.photobucket.com/albums/nn107/Sprintstar400/WaterCH4.gif
Bear in mind that at an altitude of the mid-troposphere the temperature is about 250K so CH4/H20 has increased quite a bit by then, we’re not just talking about dry winter weather!
Between 1300 and 1600 cm^-1 CH4 has ~36,000 absorption lines to ~4,000 water lines. Between 1200 and 1300 it’s even more dramatic, ~13,000 to 1,000 (this is around the peak of the CH4 spectrum!
Phil. March 28, 2013 at 9:42:
THANKS for the link to http://s302.photobucket.com/user/Sprintstar400/media/WaterCH4.gif.htm which PROVES MY POINT!
Please notice the SCALE on the left size of the graph. Both the H2O and CH4 graphs are the same physical height, but the CH4 graph is multiplied eight times as much in height, and the bottom 7/8ths are cut off! The H2O graph goes from 0.88 to 1.00 while the CH4 graph goes all the way from 0.00 to 1.00! This is all quite misleading.
Furthermore, please notice that the graphs you linked to extend only from Wavenumber 1200 (8.3 microns) to 1300 (7.7 microns). The LWIR spectrum of interest extends down below 7 microns up to 20 microns or more! So, those graphs are showing only a tiny fraction of the LWIR spectrum responsible for the Atmospheric “Greenhouse” Effect. The strong portion of the H2O absorbtion spectrum extends from 7 to 9 microns, and from 12 to 20 microns and beyond.
PLEASE NOTICE:
1) H20: The H2O graph extends from 0.88 to 1.00, which is NEAR-SATURATION (88%) to COMPLETE SATURATION (100%). Also notice that there is 100% saturation for well over 95% of the spectrum. Yes, there are several narrow spectral lines that are not 100% saturated, but, the first three of these go down only to 96% saturation, the next one goes down to 90% saturation,and so on and the worst one goes down only to 88% saturation.
2) CH4: The CH4 graph extends all the way down to 0.00, which gives a totally misleading impression. If the H2O graphic was plotted to the same scale, it would only be about 1/8th the height! Also notice that the CH4 graph has many, many spectral lines that are less than 20% saturated and some that approach ZERO saturation.
I don’t have the base data for these graphs, however I would love to see a graph and calculation of what percentage of absorbtion of LWIR that a doubling of CH4 would contribute to the total absorbtion of H2O plus CO2. My guess is that it would be well under 1%. And, as your link to Climate Audit indicated, CH4 is not increasing very much, if at all.
I appreciate your contrubutions to this Topic thread and hope you answer the above.
advTHANKSance
Ira
Ira please look at the legend of the graph, it’s transmittance not absorbance! In the region shown CH4 has many strong lines whereas water has a few weak ones.
Ira Glickstein, PhD says:
March 28, 2013 at 8:58 pm
Phil. March 28, 2013 at 9:42:
THANKS for the link to http://s302.photobucket.com/user/Sprintstar400/media/WaterCH4.gif.htm which PROVES MY POINT!
I’m afraid not!
Please notice the SCALE on the left size of the graph. Both the H2O and CH4 graphs are the same physical height, but the CH4 graph is multiplied eight times as much in height, and the bottom 7/8ths are cut off! The H2O graph goes from 0.88 to 1.00 while the CH4 graph goes all the way from 0.00 to 1.00! This is all quite misleading.
As indicated briefly above you have misread the spectrum, as indicated on the legend it is a transmissivity spectrum so the H2O spectrum shows very little absorption in that region compared with CH4!
Furthermore, please notice that the graphs you linked to extend only from Wavenumber 1200 (8.3 microns) to 1300 (7.7 microns). The LWIR spectrum of interest extends down below 7 microns up to 20 microns or more! So, those graphs are showing only a tiny fraction of the LWIR spectrum responsible for the Atmospheric “Greenhouse” Effect. The strong portion of the H2O absorbtion spectrum extends from 7 to 9 microns, and from 12 to 20 microns and beyond.
I presented this in response to your statement which I highlighted: “all the CH4 peaks are coincident with portions of the spectrum where H2O is saturated or nearly so.”
As I showed this is not true for the main CH4 peak between 1200 and 1300 cm^-1, what water does elsewhere is not relevant. That’s the problem of working with a low resolution cartoon!
The H2O spectrum while extensive is very sparse in terms of lines as referred to above, in the upper atmosphere there are many gaps where other gases can be effective.
PLEASE NOTICE:
1) H20: The H2O graph extends from 0.88 to 1.00, which is NEAR-SATURATION (88%) to COMPLETE SATURATION (100%). Also notice that there is 100% saturation for well over 95% of the spectrum. Yes, there are several narrow spectral lines that are not 100% saturated, but, the first three of these go down only to 96% saturation, the next one goes down to 90% saturation,and so on and the worst one goes down only to 88% saturation.
2) CH4: The CH4 graph extends all the way down to 0.00, which gives a totally misleading impression. If the H2O graphic was plotted to the same scale, it would only be about 1/8th the height! Also notice that the CH4 graph has many, many spectral lines that are less than 20% saturated and some that approach ZERO saturation.
completely wrong because of the misreading of the spectrum.
I don’t have the base data for these graphs, however I would love to see a graph and calculation of what percentage of absorbtion of LWIR that a doubling of CH4 would contribute to the total absorbtion of H2O plus CO2. My guess is that it would be well under 1%. And, as your link to Climate Audit indicated, CH4 is not increasing very much, if at all.
Over its lifetime in the atmosphere CH4 averages over 20X greater effect /mole than CO2 so a doubling from the current ~2ppm the effect would be equivalent to an additional 40ppm of CO2, also it has a greater sensitivity than log. My reference to CH4 was: “Hopefully the ongoing melting of the Arctic sea-ice won’t lead to a recurrence of the growth in CH4 but current measurements in the Arctic suggest otherwise.” So although the flattening anticipated by Hansen’s Scenario C has occurred, present measurements in the Arctic are indicating recent releases, probably due to local warming.
I appreciate your contrubutions to this Topic thread and hope you answer the above.
Terry Oldberg says:
March 25, 2013 at 8:26 am
I had to travel, and was unable to respond. I am familiar with the MEM in signal processing. The methodology I advocated could be couched in those terms, involving as it does identification of the system dynamics, and following through with optimal prediction of its evolution. MEM identification methods can be employed, but the system at hand has high SNR, and it would really just be gilding the lily.
Bart:
A generalization can be drawn from experience in building information theoretically optimal models. This is that 150 observed independent events is about the minimum for construction of a predictive model. Going back to the beginning of the various global temperature time series in the year 1850, there are between 5 and 6 events of 30 years’ duration each; 30 years is the duration that is canonical in climatology and is the approximate period in which power producing facilities depreciate to nil. Five events is too few for construction of an information theoretically optimal model by a factor of at least 50. Thus, I can’t agree with you when you claim it to be easy to extract the signal from the noise. Under current circumstances, it would be impossible to extract such a signal at all.
By the way, as a signal would come to us from the future, it would have to travel at a superluminal speed. It follows from the impossiblility of such a speed under Einsteinian relativity that a signal power greater than nil is not possible. Thus, the signal-to-noise ratio is undefined. In view of this state of affairs, I prefer to replace the term “signal” by the term “message.” The message that one might hypothetically receive would be a sequence of outcomes of events in the underlying statistical population. As global warming climatology references no such population, the existence of such a message is not currently possible.
Terry Oldberg says:
March 30, 2013 at 8:30 am
“It follows from the impossiblility of such a speed under Einsteinian relativity that a signal power greater than nil is not possible”
Not according to absorber theory.
In any case, I don’t really want to be arguing over how many angels can dance on the head of a pin, or whether our universe is a grain of detritus lodged in the fingernail of a giant. Such conversations are best conducted when one is an undergraduate, in a relaxed atmosphere among friends sharing mind altering substances.
The method I am advocating is a converging series of inferences based upon actual measurements, rather than a scattershot series of random guesses to which one then attempts to reconcile the data. The latter is the process in which the IPCC et al. are engaged, and it is horrible science. I think we agree on that, at least, so let us leave it there until we meet again. Cheers.
Bart:
“Despite theoretical arguments against the existence of faster-than-light particles, experiments have been conducted to search for them. No compelling evidence for their existence has been found.” ( http://en.wikipedia.org/wiki/Tachyon )
Phil. March 29, 2013 at 3:37 am
You are correct, the graphs you linked to say “Transmittance” along the Y axis.
However, they are in conflict with the graph in http://en.wikipedia.org/wiki/File:Atmospheric_Transmission.png (which you call a “cartoon”). I agree the graphs you linked to are more precise and focussed on the narrow spectral absorbtion region for CH4, than the broader and coarser graph that I linked to from Wikipedia.
However, the Wikipedia graph is clearly based on actual measurements of the Atmosphere and it covers the entire region of LWIR emissions from the Earth that are absorbed and retransmitted back towards the Surface and that make the Atmospheric “greenhouse” effect (AGE) work. Everyone is welcome to look at that graphic and will notice that, even in the narrow band where CH4 is active, its absorbtion peaks below 50%. In that same narrow band, H2O is either totally saturated at 100% absorbtion, and, for part of that band, it goes down only to around 50%. Thus, even in that narrow band, H2O overwhelms CH4 in effectiveness and thus in importance for AGE
If we look at the entire LWIR band, from about 6 to 30 microns, H2O is saturated for a major portion, and, when combined with CO2, together they are saturated for the majority of the band of interest.
The narrow CH4 band graphs you linked to, marked “Transmittance”, do not have any information about where or what part of the actual Atmosphere they refer to. Are they for dry winter conditions in the Arctic? It seems to me we should be using average worldwide Atmpospheric conditions. You do not give a source for your graphs, except for the legend “Spectracalc.com”. I went to that website and found a calculator application where the user could enter various conditions and assumptions, What did you (or whoever generated these graphs) enter as assumptions?
Do you have any explanation for why the graphs you linked to contradict the Wikipedia graph?
Please reply because I am interested in this issue. advTHANKSance
Ira
A brief reply Ira I’ll respond in more detail later. Firstly you’re mistaken on the provenance of the spectrum you linked to, it’s actually a synthetic spectrum not measured. It’s actually made from the same source as mine, spectracalc! It does not say which location in the atmosphere it is calculated for so it’s not clear how much H2O is assumed. The spectrum is smoothed which is why the structure is not apparent so strong lines might not be apparent and the sparse nature of the H2O spectrum is lost. You are incorrect about the relationship of the CH4 and H2O spectra, look carefully the CH4 is at the edge of the H2O spectrum, this is even more important when you don’t look at a smoothed spectrum such as the one you presented.
Phil., yes, the chart I linked to is generated from Spectracalc as you say, but it is clearly intended to represent some version of an “average” worldwide Atmosphere, which is what is needed here to visualize how the various “greenhouse” gases contribute to AGE.
I took the largest available version of the chart and blew it up and, using a drawing tool, compared the CH4 part of the spectrum to the corresponding H2O portion and found that, while the CH4 averaged perhaps 25% saturation over that narrow range, the H2O averaged well over 50%. (I would appreciate it if you or some other reader would do the same and report conclusions.)
Then, considering that the CH4 band of absorbance is only about an eight of the strong LWIR band of Earth Emission, it seems to me there is no other conclusion than that H20 dominates, that CO2 covers a portion where H2O is weakest, and that CH4 contributes next to nothing because it is narrow, weak, and happens to overlap an H2O regioin that is stronger than the CH4 by a factor of at least two.
Again, please report the conditions assumed by Spectracalc for the graphs you linked to. Do you agree the person who requested that Spectracalc plot specified an extremenly dry period (e.g., winter) or location (e.g., arctic) and therefore obtained results that, while true for that period and region, are not representative of averages for the whole Earth and all Seasons.
Ira
PS: I reallyappreciate your sticking with this Topic thread. THANKS.
Phil: While waiting for your reply to my previous posting, I found this at: http://en.wikipedia.org/wiki/Greenhouse_gas It appears to be fact-based and is certainly not on the skeptic side regarding Global Warming! The bottom line for me is that methane is well below water vapor and carbon dioxide and contributes less than half as much as CO2 and a ninth of H2O.
So, taking the low ends to, according to the text, “account for overlaps with the other gases” we get Methane at 4%, compared to CO2 at 9% (over twice the contribution) and H2O at 36% (nine times the contribution).
Or, to put it another way, if I listed the “greenhouse” gases in order of importance, it would be: H2O, H2O, H2O, H2O, H2O, H2O, H2O, H2O, H2O, CO2, CO2, CO2, CO2, CH4 …
Ira