Pielke Sr. on Zeke's zinger

Even more basically, it starts with the assumption that feedback is in fact positive for CO2. What if it isn’t?

yabut if you put more joules into the ocean, it gets warmer. In any event, how are you going to measure those joules if not with a thermometer. (commieBob now ducks and hides under his desk) 😉

Well I have been trying to discover for years, just who or what first described Climate Sensitivity in terms of its relation between teh global mean surface Temeprature, and the logarithm of the atmospheric CO2 abundance.
I was under the impression that this was a creation of the late Dr Stephen Schneider at Stanford..
I take a dim view of people who say that some relationship is “logarithmic”, unless they can demonstrate either by measurement or theory, that such a relationship is mainatained over at least several orders of magnitude (three min) of the variable whose logarithm tracks the other variable.
My point is simply that just because a relationship, is non-linear; does not automatically mean it is logarithmic. When somebody says it IS logarithmic, that to me means that a CO2 increase from 280 ppm to 560 ppm produces the same Temperature increase, as going from 1 ppm to 2 ppm. That IS alogarithmic relationship.
Mathematical curve fitting experimental data, to some function is a well practised art. In the Mauna Loa era, we have somewhat less than 1/3 of one doubling of the ML CO2 number, from 325 ppm to today’s 390 ppm.
That data can easily be fitted to an ordinary power series, over some restricted range, and to as accurate a fit to the data, as can say a logarithmic equation.
Usually one looks at logarithmic relationships; when some theoretical basis for believing it is logarithmic, exists, such as radioactive decay for example, or the Current-Voltage relationship of a Semiconductor diode junction at constant Temperature.
GHG absorptance of LWIR radiation has its roots in Beer’s Law relating the absorptance of chemical solutions to the molar concentration.
But one must not confuse optical absorptance with energy transmission.
The energy transmitted by an optically absorbing medium, can be orders of magnitude higher than (1-a) where (a) is the optical absoptance for some spectral region, and can have a Beer’s Law relationship.
That transmitted energy will likely be in a quite different spectrum, from that represented by the Beer’s law absorption.
This situation exists in the CO2 GHG absoption case. CO2 has well understood infra-red absorption spectra; but it is also well known that the absorbing CO2 molecule, seldom gets a chance to re-emit the photon that sent it to an excited state. The energy will become thermalized through molecular collisions that occur thousands of times faster than spontaneous emissions of the decay of the resonance absorption modes. and that energy simply raises the Temeprature of the main atmospheric gases. They in turn radiate a purely thermal (BB-like) continuum spectrum, that just happens to overlap the same range as the absorption band (of lines) for CO2.
That radiation is emitted isotropically from every level in the atmosphere, from the very surface to the end of the atmosphere, and only in the highest coldest rarest atmospheric regions does the CO2 get a chance to spontaneously emit its own characteristic band of frequencies. And at every level in the main body of the atmosphere, about half the emitted radiation is emitted upwards towards space, and half downwards to the surface. It matters not whether the surrounding layers are transmissive or absorptive. The transmitted portions of the spectrum, still travel about half in each direction, and the absorbed portions simply lead to a subsequenct emission of some thermal spectrum, that likelwise splits in two hemispheres.

Roger Pielke:

The range of temperatures of “1.5 C and 4.5 C for a doubling of carbon dioxide” refers to a global annual average surface temperature anomaly that is not even directly measurable, and its interpretation is even unclear, as we discussed in the paper

Why do you think that it is an indirect measurement is an issue? There are plenty of quantities that get measured indirectly in meteorology, climate and other sciences. (More that get measured indirectly than not, I’d think.)
The question of interpretation (and utility which is really what you are driving at) depends on what you are planning on using the number for. We live in the surface layer, most of the land biosphere does too, so knowing how the temperature responds to CO2 does act as a proxy for the impact of CO2 emissions on humans (changes in growing seasons, shifts in dry belts etc).
Are there other numbers? Sure, and any policy maker needs to read further than just global mean temperature change.
You are right to say that there is perhaps too much fixation on CO2 sensitivity, but your more general definition of climate sensitivity could be quantified by including a list of global values, which would have to include global mean temperature, as well mean precipitation, mean ocean pH and so forth.

I agree that global average annual temperature is not an incredibly useful metric of “climate” sensitivity, but only of temperature sensitivity. But, if one understand the implications of that temperature sensitivity, one can see the implications for the longer-term (but not daily) statistics of weather. For example, if we know that at 2 degrees C of global warming, we will get 7 to 10 C above the Arctic circle, than that also tells you to expect sea ice and permafrost to decline. This decline in sea ice has implications for atmospheric circulation patterns which of course affect longer-term weather patterns. What it comes down to is that experts can understand the potential implications of global temperature changes and thus sensitivity to GH gas increases measured in this manner can be very useful in making future potential scenarios based on that sensitivity. Those scenarios could be completely wrong of course, but they require some measurement of sensitivity to output anything at all.

Bishop Hill has an relevant post regarding climate forcings that quotes another blogger’s question to Freeman Dyson and his answer about important climate issues:
“1. What questions should intelligent lay-people be asking about climate, and to whom should these questions be directed?”
“Answer to your question”
“1. Both for humans and for wildlife, water is more important than temperature. Intelligent lay-people should be asking questions about water. What are the trends over the last hundred years for total rainfall, total water vapor in the atmosphere, total volume of ice on the continents, volume of fresh water in aquifers, distribution of droughts and floods, and last but not least, sea-level? Why did the Sahara change from green six thousand years ago to desert today? What are the implications for public health and natural ecology of the changes in flow and abundance of water?”
http://bishophill.squarespace.com/blog/2011/2/28/some-correspondence-with-freeman-dyson.html

“Climate Sensitivity is the response of the statistics of weather (e.g. extreme events such as droughts, land falling hurricanes, etc), and other climate system components (e.g. alterations in the pH of the oceans, changes in the spatial distribution of malaria carrying mosquitos, etc)”
Hmmm. Changes in the spatial distribution of malaria may conceivably occur as a result of climate sensitivity, but the emphasis must be on the “may”. Certainly malaria has moved well southwards in Southern Africa since the mid ‘seventies, but without any detectable change in climate. The southern drift that has occurred can all be attributed to anthropological causes. The population has grown tremendously over that time period resulting in considerably greater movement of people and consequent greater carrying of the insect. Anti malaria preparations that worked unfailingly in the mid seventies are no longer nearly as effective. Governmental chemical actions to fight the the mosquito spread, have in some parts (Zimbabwe in particular) either become less effective or have broken down altogether.
I feel that the scientific community should avoid this type of bland statement, if for no other reason than that there will no lack of Governments who will happily claim compensation for the damage done to them by the West’s nasty CO2.

Great post by dr. Pielke!
Carrick: Why do you think that it is an indirect measurement is an issue?
“Global mean temperature” is not only indirect, it’s also wrong. Even if we covered the earth with a grid of more than a billion temperature sensors of previously unmatched quality, the arithmetic mean of those readings would be a bad measure of “global warming”, since +10 C in the arctic corresponds to much less incremental athmospheric heat content than +10C in the tropics.

Judy Curry’s weblog article Spatio-temporal chaos is exactly what I have been looking for for years!
I am glad that someone like Judy Curry has expressed so well the unavoidable facts about chaotic systems and how they relate to climate.

Thanks for the feedback that has been sent. I have just two further comments here. First, while ocean heat content requires the measurement of temperature, it also includes mass so that the proper unit of global warming (Joules) can be calculated. This is not true with the two dimensional analyses of surface temperatures which are used to calculate global averge surface temperature anomaly. There is no mass associated with this determination of heat.
Secondly, even with respect to surface temperature, it is a flawed metric. For example, what height is this temperature measured at (e.g. the surface, 2m etc). This matters in terms of the anomaly values that are computed as we have shown, for example, in our recent paper
Steeneveld, G.J., A.A.M. Holtslag, R.T. McNider, and R.A Pielke Sr, 2011: Screen level temperature increase due to higher atmospheric carbon dioxide in calm and windy nights revisited. J. Geophys. Res., 116, D02122, doi:10.1029/2010JD014612.
http://pielkeclimatesci.files.wordpress.com/2011/02/r-342.pdf
There is the issue that anomalies in absolute humidity alter the anomalies in temperature even if the total heat of a volume of air does not change, as we showed in our paper
Pielke Sr., R.A., C. Davey, and J. Morgan, 2004: Assessing “global warming” with surface heat content. Eos, 85, No. 21, 210-211.
http://pielkeclimatesci.wordpress.com/files/2009/10/r-290.pdf
These are just two of a number of issues with this data set. We can add all of the seminal work that, Joe Daleo, Anthony Watts and surface project volunters have done on the quality of the siting, as well as the failure of the land part of the surface temperature record to clearly define how they massage the data in order to create what they call a “homogenized” analysis.
We will have more to report on the surface temperature data set soon. My recommendation, however, is to scrap the use of surface temperatures to indirectly diagnose global warming and replace with upper ocean heat content change which is a direct measure of climate system heat changes.

Zeke’s problem is formulating “climate change sensitivity” in terms laid out by the IPCC authorities.
In an important sense, Zeke is parsing a different problem from the narrower one Pielke, Sr., attacks above. Zeke and Lucia’s friends attempt to declare and decide on the range of probable and improbable problems pertinent to climate change science. Zeke hopes to move beyond debate to zero-in on genuine scientific problems; this makes agreement (or “consensus”) a priority before progress can be made.
Yet all of this is highly speculative, dependent upon the context of one’s selective knowledge of the literature, and besides the point of genuine scientific criticism. “How many angels can dance on the head of a pin” theology speculations, but dressed up as science. Furthermore, Zeke shows us that Linzen’s lessons about the corrupt fatuities of climate science have not yet been learned by his cohorts. (SEE “Climate Science – is it currently designed to answer questions,” Nov 2008) Instead, they must be papered over and denied as genuine problems.
This is not science, but politics IPCC-style, plain and simple.

R Gates: you said “I agree that global average annual temperature is not an incredibly useful metric…” You made up a new term there. Perhaps you meant global average temperature anomaly?
I would ask for support for “For example, if we know that at 2 degrees C of global warming, we will get 7 to 10 C above the Arctic circle,…” but your answer is probably climate models. Are those the same models that predicted that AO would increase? The ones that were trumpeted as validated when AO was increasing in the 90’s And now that AO is decreasing, those models are quietly tossed aside for new speculations that ice loss causes negative (decreased) AO? Bottom line: your claim is an unknown. The decline in sea ice was a well known prediction in the 90’s yet those models predicted the opposite of what is now happening.

Zeke has an agenda to drive. He believes that by making those statements they must be true. Unfortunately, he and his fellow AGWs have provided no empirical evidence for their ‘believe’ and probably never will. I just wish, like Willis, that htese people would provide the science with their absolute statements so that we can all become believers like them.

Related to this issue that Roger raises, is a featured article in the Jan 2011 issue of Physics Today, which is a free Journal of the American Institute of Physics. It’s a quite extensive article authored by Peter Humbug; who lurks around c-R. It’s a very readable article and one I think everyone should find and read. It has been mentioned here at WUWT before.
In the very first sentence of this paper, we learn that the Temperature of the earth would be nearly 800,000 K after a billion years of absorbing sunlight with no means of escape. Well I dare say that if the earth is actually 4.5 billion years old, then it’s Temperature would likely be closer to 3 million Kelvins, than 800,000.
Of course it wouldn’t have any of its present atmosphere, and no oceans of course (of H2O). At that 800,000 Kelvins, the mean molecular velocity would likely be greater than the escape velocity, so all of those molecules would be gone; and since mass goes down faster than surface area, as the surface layers of the earth ablated, the incoming solar energy rate, would not decline as fast as the earth mass does, so the Temperature would likely continue to increase indefinitely, until the whole earth had evaporated and blown away.
But of course that model of earth (Peter is a model maker evidently) assumes it has no way of getting rid of any energy.
That’s a strange assumption for a model; because later in the paper, he plots a graph, that purports to be an actual theoretical calculation for the Radiance for LWIR emissions from the earth. Well he calls it “flux”, and he has it overlaid with actual measured “flux” from the AIRS Satellite Instrument.
According to his graph, the earth actually CAN radiate a nearly infinite amount of energy. His actual plotted data, both measured and calculated, have a peak value of close to 0.12 Watts per (square metre-Steradian) at around 550 cm^-1 wavenumber and again at around 750 cm^-1 on the other side of the CO2 hole. The Radiance drops to about 0.07 on the same scale at the Ozone hole at 1050 cm^-1, and then at 1250 cm^-1, it drops to about 0.2 or less for the water hole.
He has similar graphs for both Mars, and Venus; since his theory is applicable to any planet. Of course the detail numbers are different for different planets.
So how is it that such a graph predicts a near infininte amount of radiated energy.
Well let me repeat, the Units of his “flux” are WATTS PER SQUARE METRE PER STERADIAN; or if you prefer W/(m^2.sr). You get the idea; those are units of Radiance; the radiant equivalent to “candle power”.
What they specifically ARE NOT, is units of SPECTRAL RADIANCE., so that presumably is the calculated and measured radiance at each and every possible frequency (wave number) within the range , of roughly 100 to 2000 cm^-1 as plotted, and there is an infinite number of such frequencies (the thermal spectrum is a continuum) so the total radiated energy is infinite.
The author also states that planets with Temperatures between about 50 K and 1000 K emit IR spectra in the range of 5-50 microns in the far infrared; which he calls the Thermal IR (fine with me).
This thermal IR spectrum is presumably somewhat black body like; modified by some appropriate (spectral) emissivity.
This is a rather weird piece of information, since we know that for planet earth which roughly averages 288 K and emits 390 W/m^2 total radiant emittance, the corresponding BB spectrum would contain 98% of its energy between the wavelengths of 5.0 microns to 80 microns, with the spectral peak at about 10 microns.
Wow ! that an even longer spectral range, than the author claims for the whole planetary Temperature range from 50 K to 1000 K.
The way I figure it (I do not have a Teracomputer), the 1000 K spectrum, would have its peak emittance at 2.88 microns, and 98% of the energy would be between 1.44 microns, and 23 microns; whereas the 50 K planet, would have 98% of its energy between about 29 microns, and 460 microns, with a peak at 58 microns.
Apparently my stick in the sand is not quite as accurate as his Teracomputer.
Well I could go on, and mention a few other glaring questionable statements; but I would not want anyone to be put off from reading the entire paper.
The most important sentence in the whole paper is the second to last sentence which says:-
“The precise magnitude of the resulting warming depends on the fairly well known amount of amplification by water-vapor feedbacks and the less known amount of cloud feedback.”
The final sentence says:- “There are indeed uncertainties in the magnitude and impact of anthropogenic global warming, but the basic radiative physics of the anthropogenic greenhouse effect is unassailable.”
I would suggest to the author that those two statements are quite incompatible. The radiative Physics cannot be unassailable so long as the cloud feedback is unknown; and it certainly is unknown. Even the most battle hardened AGW warrior can’t tell you how the clouds work to control the Temperature of the earth.
It’s a shame, that such a respected Teramodeller, can write a paper like this, and even more surprising that Physics Today chose to publish it.
But do read it anyway; he does address some of the myths; such as the CO2 bands being saturated; but I think his explanation leaves a lot to be desired. There’s that “shoulders” of the CO2 absorption band explanation of what adding more CO2 does. Nothing about the same amount of absorption occurring in a thinner atmosphere layer, if the CO2 abundance increases.

So how many 100′s of billions have been spent and the arguments still cover the basic principles, amazing.
Mod please delete first post, hit post when attempting to correct typing.

Zeke wrote:
“… surface temperature response to doubling CO2 (e.g. standard climate sensitivity) is not a full description of the effects of a climate forcing, but rather a limited subset of those effects. However, discussing how the full effects (which are characterized by even more uncertainty than sensitivity itself) should be communicated to the public and policy makers is a separate issue from what our best understanding of the science says about climate sensitivity as generally defined.”
This is what really pisses me off. Maybe before trying to “communicate” some “generally defined” concepts to “the public”, one needs to communicate to himself that change in globally-averaged surface temperature IS NOT A PROXY FOR CHANGES IN HEAT CONTENT of climate system. It was shown mathematically on JCurry blog that a three-dimensional FIELD of temperature cannot be meaningfully characterized by a single number (“global temperature”) when the field is not spherically symmetrical. It is quite obvious and can be shown with simple examples that global average can go up while system is globally cooling, and global average can go down even if system is gaining heat. More importantly, the global average temperature can go up or can go down even if the heat content does not change at all. Please communicate this to yourself first.

Carrick wrote:
“The short answer to why you don’t need one billion sensors comes from the sampling theory: This theory is the basis for digitization of audio and video signals. If there were an error with this theory, we would viscerally see it and hear it. If you ask how many samples you need to fully capture the Earth’s temperature field, based on a correlation length of 500-km (this is a smaller number than is quoted by Hansen’s group for the correlation length), that works out to around 2000 instruments world wide.”
Totally wrong. We could “viscerally see and hear” disconnects in video and audio signals, but it doesn’t affect much of information we receive. We might see some “snow” or “popping”, still old VHS tapes or vinyls could be well enjoyable. More, while information content is still fine, estimates of some average of signal could be over the roof, a technique that was used in early copy protection of VHS tapes. Even more, modern communication channels (such as USB) explicitly define “isochronous steams” where it is not necessary to retry blocks of signal if checksum does not match, and simply ignore the data block. These are the streams dedicated for video and audio information. So you could not be more wrong.
Regarding temperatures, you do need much higher density of sampling. As I reported elsewhere, there are many pairs of stations that are just 50-60km apart while exhibiting OPPOSITE century-long temperature trends. It means that you/we have no clue what is actually happening to climate-scale trends between stations that are 300-500 miles apart. It means that the field is undersampled. How badly? Opposite warming-cooling trends on a distance of 50km means that you need AT LEAST 25km REGULAR grid, which translates into about 800,000 stations world-wide.
So, your assertion that “it works out” to 2000 stations is unconditionally, blatantly wrong. Please get yourself familiar with Nyquist-Shannon-Kotelnikov-Whittaker sampling theorem, and study the effect called “aliasing” when sampling density does not conform to the sampling theorem.

Alex, you and I aren’t going to see eye to eye on this, if for no other reason than you refuse to use an analytic approach to buttress your arguments, and you prefer to substitute ugly personal attacks for reasoned argument. Sorry but I just find that very boring.
My comments about the number of locations needed based on a correlation length of 500-km and a (band-limited) sampling period of 1 month/sample follow straight fro the sampling theorem. So, either there’s something wrong with the sampling theorem, or there’s something wrong with the statement that the correlation length for a 1-month band-limited signal is 500-km.
Those are the only two possibilities.
Your discussion about old VHS systems, etc are so incoherent or OT I have no idea what you are even trying to drive at, other than some petty desire to show me “totally wrong”.
Address the science, or expect to be ignored.

Steven Mosher said:
It would be a good thing, if Peilke and others explained what they agreed about.
This is not about talking a poll and deciding the truth. It’s about seeing what agreement there is and what disagreement.
—————————————————————
It is perfectly reasonable to ask Dr Pielke what his views on a particular topic are, and decide whether or not you agree with them, and debate them. But, there are no ‘others’, at least in a real scientific discussion. Convenient as it would be for those who do not buy the IPCC view of the world to form a nice homogeneous bloc, it is not the case. Given the vast range of disciplines and often uncharted territory involved, there would be something very wrong if it was the case.

steven mosher says:
February 28, 2011 at 1:47 pm
“It would be a good thing, if Peilke and others explained what they agreed about.”
Mosh, how about this:
(1) Its gotten warmer since the last mini ice age
(2) Dumping large amounts of CO2 and other by-products of fossil fuel combustion into the atmosphere is hazardous to human life and to the common welfare
(3) We should be aggressively pursuing alternative sources of cheap clean energy as a national priority
(4) Climate science has been corrupted by politics and some prominent climate scientist are willing to falsify results and cherry pick data in order to achieve power, fame and career advancement.
(5) Prominent climate scientists have systematically overstated confidence in results and the degree of scientific consensus
(6) The climate science community is unwilling and unable to enforce a meaningful code of professional conduct.
(7) Global mean surface temperature is meaningless and attempts at measuring it are illusory.
(8) Modeling of the climate with any degree of predictive power (beyond a few weeks) is well beyond the current state of technology
(9) Current estimate of climate sensitivity are unsupported by direct evidence
(10) We have not been able to characterize natural variability in the climate and as such we are unable to determine the significance of the anecdotal warming

“climate forcing”
Surely a less-wrong term for that is “perturbation”.
Terminology consistent with control systems theory and Engineering.

mpaul says:
February 28, 2011 at 4:35 pm
“Mosh, how about this:”
If I may give my take…
The following numbered statements are your suggestions, the indented statements are my replies.
(1) Its gotten warmer since the last mini ice age
—-As expressed as a global average this is true. Regionally its less clear-cut, locally it varies. But the rise in sea level after ~6000 years of stasis and evidence from borehole data indicate the recent warming is a robust signal.
(2) Dumping large amounts of CO2 and other by-products of fossil fuel combustion into the atmosphere is hazardous to human life and to the common welfare
—-The degree of hazard it represents has more to do with how robust human agricultural systems and societies are to the changes that increasing CO2 will inflict.
You cant change just one thing in a compex interactive system, so raising CO2 will cause other changes. Even if we knew EXACTLY what changes it would cause, whether such changes are hazardous is dependent on societal adaptability.
Only if you regard any and all change as hazardous is it valid to ignore the magnitude or the societal response.
(3) We should be aggressively pursuing alternative sources of cheap clean energy as a national priority
—-Obviously.
(4) Climate science has been corrupted by politics and some prominent climate scientist are willing to falsify results and cherry pick data in order to achieve power, fame and career advancement.
—-Despite the frequency of this claim there is little or no good evidence for its accuracy.
Politics has distorted Climate science for its own ends. Sometimes to raise ‘alarmist’ scenarios and sometimes to eschew it.
(5) Prominent climate scientists have systematically overstated confidence in results and the degree of scientific consensus
—-Overstated confidence is occasional rather than systematic, and the degree of scientific consensus has been understated. The degree of confidence with which the AGW theory is rejected vastly exceeds the obverse, and media ‘balance’ tends to imply its a fifty:fifty split, or perhaps ten-to-one while the reality is over 98-1.
(6) The climate science community is unwilling and unable to enforce a meaningful code of professional conduct.
—-No more or less than every other field of science. Other fields of research have equally patchy, or worse records of unprofessional behavior.
(7) Global mean surface temperature is meaningless and attempts at measuring it are illusory.
—-Global mean surface temperature is a very rough metric of global heat content. Until satellite observations no attempt was made to measure it. It was derived from local measurements taken to measure the local weather. This makes the surface temperature record less than ideal as a source for calculating global mean temperature.
(8) Modeling of the climate with any degree of predictive power (beyond a few weeks) is well beyond the current state of technology
—-Wrong.
You cant predict the weather, but models would predict that January of 2019 in Northern Europe will be colder than August 2019. I would suggest this is a robust result from modeling.
(9) Current estimate of climate sensitivity are unsupported by direct evidence
—-The qualifier ‘direct’ is the problem here. How direct do you consider the evidence from volcanic climate change like Pichon/Pinatubo or glacial cycles?
(10) We have not been able to characterize natural variability in the climate and as such we are unable to determine the significance of the anecdotal warming
—-We CAN characterize natural variability but with varying degrees of accuracy and resolution over different timescales.
The significance of recent warming is that it is certainly exceptional compared to natural variation of the last 500 years. If you expand the timescale the uncertainty increases, there COULD be comparable events a few thousand years ago, but you have to go back to the end of the last ice-age and the Holocene optimum around 8000 years ago to get any good evidence of similar warming. Expand the timescale further and resolution drops way down, but there are credible candidates for natural variability greater than the present warming.
The trouble is that present technological advanced societies are a recent development, within the last few centuries, so multi-millennial periods are of rather less relevance. Agriculturally based society is only ~8000 years old so again deep time variability is of less significance. Our present society is adapted for the stable climate of the last few centuries, and the warming most likely to derive from doubling CO2 will exceed the natural variability seen over the same time period. How significant that is depends on how robust present complex technological society is in the face of variability outside the natural range already experienced.

mpaul “(3) We should be aggressively pursuing alternative sources of cheap clean energy as a national priority”
Mosher “Yes, but define aggressively.”
Manhattan Project to build a commercially viable thorium reactor
mpaul “(4) Climate science has been corrupted by politics and some prominent climate scientist are willing to falsify results and cherry pick data in order to achieve power, fame and career advancement.
Mosher: “Overgeneralized motive hunting. I would stick to particular cases and then
realize that I cannot know with any certainty what lies in man’s heart. I’ve seen
no evidence of willful falsification of data. I’ve seen questionable methods.”
“Censored” directory; R**2 testimony
mpaul “(5) Prominent climate scientists have systematically overstated confidence in results and the degree of scientific consensus”
Mosher “Again, I would stick to the cases I have studied. There appears to be some
overconfidence.”
Climate Change Assessments Review of the Processes and Procedures of the IPCC, InterAcademy Council, 30 August 2010: “… authors reported high confidence in some statements for which there is little evidence. Furthermore, by making vague statements that were difficult to refute, authors were able to attach ‘high confidence’ to the statements. The Working Group II Summary for Policymakers contains many such statements that are not supported sufficiently in the literature…”
mpaul: “(8) Modeling of the climate with any degree of predictive power (beyond a few weeks) is well beyond the current state of technology”
Mosher “False. Ill specified. the term you are looking for is actually “skill” skill is a technical measure. GCMs have skill. This is typically measured as skill over a naive forecast.
No. “Skill” is a term used by academics. I’m an applied scientists. I’m using the term predictive power in a precise sense. To quote von Neumann: “If you allow me four free parameters I can build a mathematical model that describes exactly everything that an elephant can do. If you allow me a fifth free parameter, the model I build will forecast that the elephant will fly.”
mpaul “9) Current estimate of climate sensitivity are unsupported by direct evidence”
Mosher “False. There are multiple lines of evidence supporting the range of estimates.”
Name one.

Carrick wrote: “Just an average of stations in 5° latitudinal bands.”
You seem to miss a simple point: if you don’t have sufficient density of sampling, you don’t (and can’t) know what you are missing. Data collected without regard for theoretical requirement for sampling are garbage. The only way to have confidence in a series of spatio-temporal data is to have substantially high sampling density first, then gather convincing evidence that further increases (and decreases) in sampling density don’t change the result significantly, and then back up to smallest reasonable density. Whoever does not understand this simple procedure is practicing garbage science, and all results must be safely discarded and conclusions ignored.

I’ll also note that I’ve posted my own analyses, as well as those of others. Al Tek as yet to post a single plot of his own. This comment says all it needs to say.

To Carrick: I’ve seen your analysis, and already commented on it. Earlier I looked at real (GISS) data, and found that several adjacent pairs of stations have opposite “climatological” trends. This observation alone establishes that, for the purpose of testing TRENDS and their average, the sampling density is insufficient in accord with established mathematical discipline. This observation invalidates the “correlation” analysis, and I don’t need to present any alternative mathturbation, because the data are flawed from the very beginning, insufficient. Any own or else plot will be garbage. What is so difficult to understand here?
One more time: mo matter how do you massage insufficient data, you cannot get more information out of this data set than it is already. Homogenize it, grid it, select subsets, it does not matter, you will not have any new information. That’s why all your “analyses” show about the same result, which is a garbage predefined by under-sampled wrongly-spaced initial station set. The only way to increase information from the field is to increase sampling density of the data acquisition system. When you do this and get the similar result to your current mathturbations, then you might be up to something.

Larry asks: “how can a science that has only about 50 years of satisfactory, reliable measurements … “
You are overly optimistic here. The point I am arguing here is that current measurements are not reliable and do not sufficiently represent the object in space nor in time, and therefore are way far from being satisfactory for the purpose of characterizing climate and its change.

“Average Global Temperature” is completely meaningless. What you want to know is the amount of heat in the system.
Which has more heat, a cubic meter of air at -100 degrees Fahrenheit or a cubic meter meter of water at +31 degrees Fahrenheit.

Or better yet. Which has more energy a cubic meter of air, or a cubic meter of air at 10 meters above and with essentially the same temperature and pressure as the first cubic meter of air?

It also depends on the global systems being in equilibrium with regard to temperature. It never is!
There is also the anomaly problem. To state that there is an anomaly one has to know that there is a temperature difference from what is ‘normal’. We do not know what is normal and on a planet with a chaotic climate system we never will know.

Izen says:
“The graph you link to shows the sea level rise at the end of the last ice age… and shows that it has altered little in the last ~6000 years as I stated.”
Are you sure about that? I believe the rate of SLR is about 2 to 3 mm pa – say 3mm. That’s 3m per millenium or 30m in the last 10,000 years. But I am sure sea levels have risen more than that. For example, the North Sea with its mean depth of 90 metres, was completely dry during the last ice age. Doesn’t that mean that sea levels have historically risen more than 3mm pa in the past?
Just wondering.

MarktT:

No, temperatures of gases that do not have an identical composition cannot be “averaged,” period. That’s the only problem.

This statement exposes just how much thermo 101 you don’t understand. Gas mixtures is not a problem.

I read the link above to Judith Curry’s discussion on spatio-temporal chaos. It is certainly challenging and reminds me of Prime Minister Palmeston’s description of the intractable Shleswig Holstein question in the 19 century. He said only two people apart from himself had understood it. One was dead and the other was in an asylum.
So without implying that I am in an asylum or within the 1% who understand the theory I would ask this question. Global climate history over geological time has indeed varied but always within a relatively small range. This evidence points to the existence of boundary conditions, the principle of which surely would be in conflict with this chaos theory.

steven mosher says:
February 28, 2011 at 2:52 pm
Here’s a nice little presentation that will give you some ideas.. using Ocean heat content: http://www.newton.ac.uk/programmes/CLP/seminars/120812001.html
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steven mosher says:
February 28, 2011 at 11:21 pm
Bruce,
What I’m saying is that you cannot derive a sensitivity from a time series as you have attempted to.
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Steven,
Thanks for replying. I’ll leave off the question of deriving 2XCO2 from time series (even though it is a reasonable question), because your link to Magne Aldrin’s presentation was bugging me.
After some thought, what I think is Dr Aldrin is statistically overestimating CO2 sensitivity. This is because (see slide 13, p 14 of the PDF) he seems to be underestimating solar sensitivity.
I say this because the correlation of solar cycle length to temperature suggests solar sensitivity is quite high. If as seems reasonable you can posulate this correlation is reflective of total solar sensitivity (since something to do with the Sun’s behaviour is causing the correlation) then SCL encompasses what Mr Rumsfeld might say the ‘known knowns’ of solar sensitivity plus the ‘unknown unknowns’ of solar sensitivity.
What I suspect is happening is Dr Aldrin is using a measure of solar forcing as an input to the model which reflects only the ‘known knowns’. Because of this the solar ‘unknown unknowns’ would contaminate the calculated CO2 sensitivity and make it too large. To misquote, saying CO2 is “the only thing we can think of” means a GCM approach will tend to estimate CO2 sensitivity on the high side if other sensitivities are underestimated or discounted. I can’t be certain of this without looking at how the code handles the solar radiative forcing input data, but it looks likely to me that it is underweight.
If you graph SCL vs temperature this shows a significant empirical correlation. I suspect this is comprised of the direct component (known known) as Dr Aldrin has in slide 13, and an unidentified component(s), possibly a positive feedback, that people such as Drs Svensmark and Rao and others have been linking to cosmic rays, UV etc. I don’t know enough to tell whether they are right, but this is about lifting the lid on the ‘unknown unknowns’.
This is the intrinsic problem with the modelling approach – if you inadvertently leave out a significant variable, the variable you are trying to measure will tend to be an over-estimate. I know this from multiple regression – if you leave a statistically significant variable out, your parameter vector will be too large since the regression is trying to minimise the residuals, particularly with noisy data. You learn to be wary of this. In this case both pCO2 and solar rose in the time series, especially in the last 50 years or so, so it is not surprising if some solar derived variance is misassigned to CO2. Dr Aldrin’s approach is effectively a form of multiple regression.

Carrick: “Third the measured data show a striking correlation with distance. “
Third time: there is nothing striking at all. Look at the details of Hansen-Lebedeff algorithm (section 3):
http://pubs.giss.nasa.gov/docs/1987/1987_Hansen_Lebedeff.pdf
Then look at any pair of temperature data. Inter-annual variation in any temperature series vastly exceeds long climatic trends, always, I hope you will not argue with this fact. Therefore, the correlation coefficient between a pair of time series is dominated by high-amplitude inter-annual variations, that’s why their correlation is “strikingly good”.
However, this has no bearing to the question at hand, about climate (30-100years) trends. As I submitted, there are many met stations (Crossbyton vs. Lubbock, Ada vs. Pauls Valley, etc) , 30-50 miles apart. I am absolutely positive that their inter-annual variations would correlate to near 100%. It is obvious, they see nearly the same weather and same seasons, and same skies. However, their 90-years trends are OPPOSITE. This is a documented hard fact, see GISS.
Now, you invoke the satellite argument. Satellites measure something that is fairly different from station’s temperature. The information comes form a vast layer of several km thick, so it does not have the necessary resolution. It is an integral parameter. Yes, it resembles the ground signal to some degree. However, despite all efforts to fudge output account for all corrections, there is still a difference of 0.4-0.6C between sats and grounds:
http://www.woodfortrees.org/plot/gistemp/from:2006/plot/hadcrut3vgl/from:2006/offset/plot/uah/from:2006/offset
This discrepancy amounts to the entire magnitude of “global warming”. [Note: in your example you have introduced various “offsets” to your time series, up to 0.21C. Why would you do so, to skew results by 30% of the entire “global warming” effect?]
More, even if satellites “measure” the same averages and do it correctly, or if there could be sufficient number of ground station, it still does not mean that the globe has radiative imbalance due to man-made CO2 increase as AGW theory asserts. As I mentioned, it can be shown that globally-averaged temperatures can go up or down while there is no global radiative imbalance at all.
As I see, you prefer to ignore these inconvenient facts. More, you continue to express nonsense – Berkeley project or not, the information from current scarce set of stations cannot be fundamentally improved, because the density of sampling grid is insufficient to represent the complex fractal-style topology of temperature field, and its crude boundary layer variability. But it as apparent that it is useless to argue this kind of details with you.
P.S. I’d like to express many thanks to Tamino who re-introduced the term “mathturbation”, which perfectly describes various mangling with temperature data sets including his own meaningless statistical efforts.

Carrick: “One of the easiest ways to look for undersampling is to look at the frequency domain. For data that follow an approximate 1/f power law, aliasing will show up as a high-frequency plateau.”
No, this would happen only if you undesample just a tiny bit, less than a factor of two. Ground station data suggest however that the land surface field is undersampled by a factor of 100. Try to find some decent sampling-aliasing java applet and educate yourself. Average of your restored signal could be anything, from -1 to +1.
Actually, we have been here before, at Blackboard “physicsts” thread, half a year ago.
http://rankexploits.com/musings/2010/physicists/
I don’t see any progress.

@-Vince Causey says:
March 1, 2011 at 6:25 am
” I believe the rate of SLR is about 2 to 3 mm pa – say 3mm. That’s 3m per millenium or 30m in the last 10,000 years. But I am sure sea levels have risen more than that. For example, the North Sea with its mean depth of 90 metres, was completely dry during the last ice age. Doesn’t that mean that sea levels have historically risen more than 3mm pa in the past?
Just wondering.
Yes, during the meltwater pulse 1A as shown on the graph that ‘SMOKEY’ so helpfully provided there was a rise of about 20m per 1000 years or around ten times the present rate. But that was during the height of the glacial-interglacial transition when the major northern ice-caps were melting. During the glacial transition there was about 120m of sea level rise over ~8000 years.
Once all those except Greenland and Antarctica had gone the sea level stabilized around 6000 years ago and has certainly not being rising for the last 6000 years at the rate of a foot per century. There is ROBUST archaeological, geological and direct observational records that constrain any rise over the last 6000 years to much less than the present observed rate of ~3mm per annum.
@-Smokey says:
March 1, 2011 at 4:18 am
“Still having fun with your CAGW scam, Izen?”
If the ‘C’ in CAGW stands for catastrophic then as I think I have stated before I am agnostic about whether the AGW will be catastrophic as that has more to do with how ROBUST a society is in the face of change rather than the magnitude of the change.
We may agree – at least to some extent – on how much of a ‘scam’ it is to claim that AGW will be catastrophic. I prefer the term ‘political froth’ to scam for such claims for or against the impact of AGW on modern technological societies. Clearly if we were all still hunter-gathers as the human population was during the last Eemian interglacial period any global warming – or the eventual cooling was not catastrophic because such societies – small bands without agriculture are much more robust in the face of changing climate.
I wonder if you could post the link again to the Post-Glacial Sea Level Rise graph, it does make the point rather well….
Sea level may be a better indicator of the global heat content of the climate that any manipulations of surface temperature data.

Carrick says:
Espen claims that we need a billion thermometers
My oh my, I never said such a thing. If I say “Even if the moon were indeed made of Wensleydale cheese, it would be too old to taste good”, do you think I claim that “we need a moon made of Wensleydale cheese”?
but that would only be you need immediate psychiatric evaluation
Wow, now I really have to bow before your intellectual superiority.

steven mosher says:
March 1, 2011 at 2:30 pm
Thanks, Steven, lots to go through. First one I’m fairly randomly looking at is:
Why hasn’t Earth warmed as much as expected? Schwartz, S. E., Sept. 22, 2010
I note two empirical options he lists are:
“Instrumental record ΔTemperature/(Forcing – Flux)
Satellite measmt.: [d(Forcing – Flux)/dTemperature]-1”
The latter is of course the method used by Drs Spencer and Braswell (2010) which I referred to.

steven mosher says:
March 1, 2011 at 2:43 pm

espen and al dont believe in an MWP or an LIA.
too few thermometers to establish an average during those times.

Please don’t use carrick’s misinterpretation of what I wrote to make silly psychic readings, will you?

Moderators, please delete the last line of my previous post – I intended to delete that question since too few understand what it means.

[done]

Carrick says:
March 1, 2011 at 11:34 pm
Espen, you said:
Even if we covered the earth with a grid of more than a billion temperature sensors
What is this supposed to imply?

You are unbelievably persistent! Don’t tell me you haven’t seen conditional sentences with purely hypothetical antecedents before.
The meaning is simply that the precision of the measurements is irrelevant – the real problem is that mean global temperature anomaly is a bad measure of global warming. Again: A +10 C anomaly in Arctic Canada in January represents only a fraction of the excess heat of a +10 C anomaly over an equivalent area in Amazonas.

Carrick wrote:
“All this based on the cherry picking a few station locations, without providing any details how you did the analysis, what time periods the trends were calculated over or anything.
We won’t see eye to eye, because your beliefs are articles of faith, and data contrary to your beliefs simply gets dismissed instead of given the proper weight they deserve.”
I think you are expressing your own (and wrong) philosophy of research. You have expressed a belief that weather is 1/f noise, that it is spatially correlated including 100-year climate trends, and your sensors must show warming trend because you believe that man-made CO2 exerts radiative “pressure”. It is you who dismiss data that contradict your belief.
You call my examples as “cherry picking”. Yes, I specifically selected these examples, because it takes only one example to dismiss your belief system. After a short look I found a dozen. Some practitioners of climate data mathturbation declare that my examples are “statistically insignificant”. Obviously they failed to realize that weather is not a noise, and 100 years of consistently declining data at 500 stations are not a statistical aberration. Even with relatively poor accuracy of station thermometers, there is no way to reverse trends on these stations, although keepers of the data keep making continuous attempts to “re-analyze” and “correct” data sets to squeeze them into their belief.
You say, “without providing any details”. This is false. I provided several links to several posts of mine, to avoid repetition. If you follow my links, you would find references to exact GISS stations I am talking about, and pull out data charts. You are just trying to obfuscate the subject and hide behind your laziness. But since you value your time so much, I will re-post pointers to just one pair of stations, Pauls_Valley_4wsw and Ada, with some “mathturbation”. These stations are 55km apart. Time span is 1907 to 2009.
Pauls_Valley_4wsw:
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425746490030&data_set=1&num_neighbors=1
Trend equation: y = +0.0071x – 13.98, or warming 0.7C/100y
Ada:
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425746490040&data_set=1&num_neighbors=1
Trend equation y = -0.002x +3.87, or cooling of 0.2C/100 years
It is interesting that if I partition the Ada data into three climatologically significant (30 years) time blocks, 1907-1936, 1943-1972, 1980-2009, and average corresponding data, I get a nearly perfect regression line y = -0.0015x + 2.96 with R2=0.9985
To summarize: The fact that many close-by pairs of stations show opposite centennial trend is totally inconsistent with the concept of atmospheric radiative imbalance from man-made “excess of CO2”.
The fact that there are many close-by pairs of stations with opposite centennial trend means that you are looking for your warming signal in wrong measuring metrics.
These are my facts. What are yours? These fuzzy clouds of seasonal correlations from logically deficient Hansen-Lebedeff study? Do you know that Hansen averages everything in 200x200km box? This requires an assumption of uniform change (+ “noise”) in instrument reading, which is based on AGW belief. My facts show that this assumption is wrong. Does it carry any weight? I think the weight is devastating, but of course you would disagree and try to find some other goofy excuse to dismiss the facts.

Pielke’s idea of using the ocean heat content as a metric is nothing new, and no revelation to the world’s climate scientists.
http://www.realclimate.org/index.php/archives/2005/05/planetary-energy-imbalance/
It is of course harder to make measurements of ocean heat content than to process the existing temperature data of the world’s weather stations.
Historically, the global average surface temperature and the ocean heat content have gone pretty much in the same direction.
http://i38.tinypic.com/zxjy14.png
http://data.giss.nasa.gov/gistemp/graphs/Fig.A2.gif
The ocean heat content data base is newer, with data only since 1955.
Also the ocean heat content data base is more problematic than the temperature data base.
http://pielkeclimatesci.wordpress.com/2010/01/04/guest-weblog-by-leonard-ornstein-on-ocean-heat-content/