Spencer on his AGU presentation yesterday

This whole thing must be extremely frustrating for you skeptical scientists (sad that I have to make that distinction). Heads high, guys. Some of us really appreciate all you are doing. There will be vindication somewhere down the line.

It was standing room only…close to 300 scientists by my estimate. There were only a couple of objections to my presentation…rather weak ones. Afterward I had a number of people comment favorably about the ‘different’ way I was looking at the problem.
And while that should be comforting, it is also disturbing. Since when in science did the issue of ‘causation’ become a foreign concept? When did the direction of causation between two correlated variables (in my case, clouds and temperature) become no longer important?
If temperature and clouds vary together in ‘sort of’ the same way in satellite observations as they do in climate models, then the models are considered to be ‘validated’. But my message, which might not have come across as clearly as it should have due to time constraints, was that such agreement does NOT validate the models when it comes to feedback, and feedbacks are what will determine how much of an impact humans have on the climate system.
I for one would be extremely happy if the debate were to continue along these lines. Even if we discover CO2 is a dangerous driver of climat, and we need to curb emissions, I would still be happy (at least content, not happy as such).
May dialogues such as this prosper and draw both fruit and other real scientists into the light once more.

“I come along with an extremely simple climate model that explains the behavior of the satellite data in details that are beyond even what has been done with the complex climate models…”
Which is how it usually is. There’s nothing like a mass of complexity to hide the fact that they don’t know what they’re talking about.

Dr. Spencer–
Many thanks for posting here. THIS is real science, because it is assembling feedback data first and then going about deducing the right hypothesis from the data. The AGW movement has been doing the opposite for over 20 years.
It is, as you say disturbing, that your work is controversial. Your work is sound science, and frankly sound logic. It’s what all scientists should be doing. Your work is controversial because by challenging AGW orthodoxy, you put their funding at risk. The AGW movement is driven by carbon trading schemers and ‘Gaia’ kooks. The scientists are along for the ride because of the grant funding the money changers line up for them. That’s how AGW rolls. So wrong.

Bullshit baffles brains.
This is nice and simple and very clear unlike the AGWarriors.
Now when will charges be laid against Jones, Mann et al?

“There seems to be great reluctance to consider the possibility that these computerized prophets of doom, which have required so many scientists and so much money and so many years to develop, could be wrong. I come along with an extremely simple climate model that explains the behavior of the satellite data in details that are beyond even what has been done with the complex climate models…and then the more complex models are STILL believed because…well…they’re more complex.”
There is a French saying that goes: “Pourquoi faire simple quand on peut faire compliqué? (Why do simple when you can do complicated?)

Seems that at Al Gore and Goldman Sachs’ Chicago Carbon Exchange, you can buy carbon credits for 10USC/MT, down from a dollar in June. That is they have lost 90% of their nominal value.
http://www.chicagoclimatex.com/
Next time you meet a warmist, ask them if they have any “green” investments. If they say yes, point out politely that their interest may be colouring their view.
If they say no, ask them why not? After all, at 10c they can hardly fall much further. Hell I might buy myself a coupla hundred Mt just for the hell of it.

Spencer should consider writing another post to explain this a bit more. It seems as if the role of clouds is a key to the question of how much CO2 matters, and I get the sense that Spencer has a different way of thinking about this, but I honestly found the PDF to be incomprehensible.

“..and then the more complex models are STILL believed because…well…they’re more complex.” Spot on: I spent too many hours of my career listening to talks on mathematical models by twerps who, when asked why their work should be viewed as being superior to what had gone before, would say it was because their models were more “sophisticated”. Partly, I suspect, this just reflects a typical character defect of the sort of p[eople who get absorbed by mathematical modelling, but partly it was a lack of good judgement caused by their narrow experience – typically they did no experimental work.

Great read Dr. Spencer……What happened to the KISS method? It would seem that the more complicated you make something the bigger the chance that there will be an error or break down with in it. If it is to complicated then one runs the risk of not being able to find it especially if you are not well versed in modeling or computer programing as shown in the e-mail leaks. But if you need to hide something with in the model or program then complicated is the way to go. I have read your blog many times Dr. thank you for being a voice with fresh ideas even if they are considered ” controversial”.

Since when in science did the issue of ‘causation’ become a foreign concept?
Scientists are people too. They believe what the tv and Hollywood tells them.

“But most of the talks presented followed the recipe that has become all too common in recent years: analyze the output of climate models that predict substantial global warming, and simply assume the models are somewhere near correct.”
I’ve been working in computational fluid dynamics (CFD) for over 20 years, and this recipe is used in our discipline as well. That is, run a flat plate boundary layer with your CFD code, show how great the agreement is with experiment, then run your code on a full jet aircraft aerodynamics simulation and assume your results are equally as accurate! However, nature and non-linearity have a funny way of humbling you…
Since I know how difficult even some very basic fluid dynamics problems are to solve with standard Navier-Stokes solvers, I am amazed that people doing climate modeling ascribe so much validity to their models given that the problem they’re attempting to solve is 10 times more complex – particularly when it comes to predictions (or projections) that are supposed to represent the state of the climate 50 years from now. There is no way, in my mind, that those solutions can remain uncorrupted by numerical error given they utilize essentially the same time-marching approaches as used for numerical weather forecasting. And I’m convinced it takes a lot of tuning to even get the hindcasts right.
Then, of course, there is the issue of code documentation and validation, which (in my opinion) groups like NASA GISS do very poorly, lending little confidence in their results…

“And while that should be comforting, it is also disturbing. Since when in science did the issue of ‘causation’ become a foreign concept? When did the direction of causation between two correlated variables (in my case, clouds and temperature) become no longer important?”
And equally important, when did negative feedback become incomprehensible? Any time you have a system that remains nearly stable over long periods of time despite all sorts of inputs, you KNOW you’ve got multiple negative feedback loops. Before the digital age, this was both obvious and familiar to everyone. Now it’s a foreign and radical idea.

Thank you for being a normal scientist. This is exactly what should take place. A breath of fresh air is contagious.

Models are used in my field. Like climate models they are tuned to existing conditions and then run off into the future to gain insight into “what if”.
Very few policy makers understand what a model does or how it works internally, and a clever modeler can easily hide an agenda within the model code, fudge factors or assumptions.
While these models don’t have trillions of dollars resting on their output, policy makers often make important decisions based on their results. All too often when shown that a simple approach to the problem addressed by the models provides a quite different (and often less costly) approach, the policy makers will defer to model simply because it is complex. Their reasoning being that the complexity allows for a more thorough analysis.
Dr. Spencer’s simpler model, which directly addresses the core issue, is similar to above example. By not being complex, the policy makers are able to dismiss it because it doesn’t have enough complexity to address the more complex issue of climate.

Dr. Spencer will cause most people to pause as soon as he asserts what seems to be an alternative reality: clouds cause temperature change instead of temperature change causes clouds. He should stop doing this. For most people there is only one reality.
And that is: The sun warms the surface and the temperature change causes evaporation. The warming and evaporation causes convection which results in clouds forming at the altitude where adiabatic cooling causes saturation. The clouds cause a radiative effect, often cooling. Since clouds move with the atmospheric circulation, they may have their radiative effect at a location different from where they were formed.
Now, the clouds may move from place A where they are formed to place B where they have their radiative effect, but does this give the appearance of a reversal of cause and effect? It should not. It is simply part of the process at work here.
Dr. Spencer must stop asserting that we have confused cause and effect. He must rethink his concept of what is going here so that it includes all of the processes involved.

“Check the math!”
When so called “scientists” can’t check their own math (or computer programs) their theories and knowledge aren’t going to fly very far. Are they? (Well.. unless they have a bunch of politicians, investors, and media types behind them for any number of dubious reasons.)
Climatologists, etc., who must rely on “experts” called computer programmers to do and check their math aren’t really scientists by the classical definition. Are they?

Dr Spencer
Your work in this area always demonstrates balance and integrity. It is good to know that the true scientific principle of asking questions is alive and well.

Thank you for your service to humanity – to Science – to Truth.

I understand and agree! You are talking about occam’s razor: “When you have two competing theories that make exactly the same predictions, the simpler one is the better.”
The IPCC’s complex models rely upon many free parameters. In July 2009, Geophysical Research Letters published a study by Reifen and Toumi, “Climate projections: Past performance no guarantee of future skill?” which found that each IPCC model could only predict the period of the 20th Century that it was designed to predict. When applied to a different period without changing its parameters, it did no better than chance. In other words, these models predict nothing.
You can read that study here:
http://www.leif.org/EOS/2009GL038082.pdf

dearieme (06:00:38) :
“..and then the more complex models are STILL believed because…well…they’re more complex.” Spot on: I spent too many hours of my career listening to talks on mathematical models by twerps who, when asked why their work should be viewed as being superior to what had gone before, would say it was because their models were more “sophisticated”. Partly, I suspect, this just reflects a typical character defect of the sort of p[eople who get absorbed by mathematical modelling, but partly it was a lack of good judgement caused by their narrow experience – typically they did no experimental work.
Not for nothing did the word “sophisticated” originally mean “adulterated”.
IanM

Reference?
“I come along with an extremely simple climate model that explains the behavior of the satellite data…”
Anyone knows where this simple model is described in details?

It’s been my experience that for any given simulation, the number of user defined (preprocessing) inputs increases proportionally with a given code’s “complexity.” An increase in user defined inputs increases the probability of a “tweaked” solution.
A very smart CFD person once told me this is called the “power user problem.”

This is one of the things that has long bothered me about climate models (and financial models for that matter). As someone who does a huge amount of modeling in a different field, I expect that if I’m modeling some system with complex emergent behavior, I should get the behavior to arise without directly modeling it. For example, if I am making a climate model, I should not have to model the effects of ocean currents: ocean currents should arise from my ocean model. If they don’t, my ocean model is wrong, I don’t understand the problem, and my other results are thus likely to be off, perhaps dramatically so.
Any time you have a system with simple inputs, complex outputs and high sensitivity to initial conditions – in other words a chaotic system – you have emergent behavior – behavior that is not predicted by simple observation of the inputs and the system’s characteristics, but emerges from the interactions of large numbers of “particles” within the system. Climate science appears to be such a system: the inputs are energy from the sun, energy from the Earth’s still-hot core, and tidal energy; the system is open due to radiative heating into space, which is the only output that crosses the system boundary; the environmental conditions are gravity, the fluid characteristics (like viscosity) and chemical composition of the air and water, the resistance various kinds of ground cover to fluid movement, the shape of the ground at any given point, and albedo at any given point. There may be a few other, but not many: the basic conditions of the model are simple to understand – hard to calculate and sometimes hard to measure, but simple to understand. Currents, jet streams, clouds and the like should emerge from the model regardless of initial conditions, or the model is not valid.
Once the model is validated, specific input conditions need to be determined, and the divergence of the model from reality over time has to be quantified. Then, and only then, can you start to trust the outputs of the models.
We don’t even appear to have climate models that predict known phenomena; they have to include those as part of the model. Thus, I cannot take seriously the outputs of any of the models.

I’m a firm believer in KISS when it comes to doing science and I think this model clearly demonstrates that less is more, in terms of information content.
The current crop of GCM’s and linear models fail the future predictability tests – doing hind-casting is much simpler, of course, although using the synthesised CRU/GISS/IPCC global average temperature anomaly data as a benchmark means that this has no information content.

Met Office’s CET hasn’t been updated since the 13th (usually 2 days behind). http://hadobs.metoffice.com/hadcet/cet_info_mean.html

Sorry off topic:
Kevin Rudd the Australian PM reads out letter from a scared 6 year old too COP15 delegates.
Isn’t mental cruelty listed under child abuse?
How else could a scared naive 6 year old be motivated to write a letter without it?
In my opinion Kevin Rudd may as well have read a statement written by a torture victim.
The rights and wrongs of AGW are one thing but to USE and SCARE kids is plumbing new depths for the warmists.

For those that want to read the Abstract of the paper that is the basis of Dr. Spencers presentation here is the link to Dr. Spencers Site, it explains what you are seeing in the PDF:
http://www.drroyspencer.com/research-articles/satellite-and-climate-model-evidence/

The following email from Climategate gives a candid look at how J Shukla, an IPCC Lead Author for Chapter 8 (Climate Models and Their Evaluation), views the utility of current climate models. Interestingly, 90+% of the chapter discusses technical details of models and comparisons between models, but says almost nothing about how well models compare with observations (ie the scientific method).
In Item 2), the phrase “model fidelity and model sensitivity are related” comes from a Shukla paper that shows that high sensitivity models do a somewhat better job of reproducing CRU’s 20th century seasonal temperature record. Does this mean “model democracy” will lead to the abandonment of low sensitivity models?
http://www.eastangliaemails.com/emails.php?eid=861&filename=1202939193.txt
From: J Shukla
To: IPCC-Sec
Subject: Future of the IPCC:
Date: Wed, 13 Feb 2008 16:46:33 -0500
Cc: [Many names. probably AR4 WG1 Lead Authors]
Dear All,
I would like to respond to some of the items in the attached text on
issues etc. in particular to the statement in the section 3.1.1
(sections 3: Drivers of required change in the future).
“There is now greater demand for a higher level of policy relevance in
the work of IPCC, which could provide policymakers a robust scientific
basis for action”.
1. While it is true that a vast majority of the public and the
policymakers have accepted the reality of human influence on climate
change (in fact many of us were arguing for stronger language with a
higher level of confidence at the last meetings of the LAs), how
confident are we about the projected regional climate changes?
I would like to submit that the current climate models have such large
errors in simulating the statistics of regional (climate) that we are
not ready to provide policymakers a robust scientific basis for “action”
at regional scale. I am not referring to mitigation, I am strictly
referring to science based adaptation.
For example, we can not advise the policymakers about re-building the
city of New Orleans – or more generally about the habitability of the
Gulf-Coast – using climate models which have serious deficiencies in
simulating the strength, frequency and tracks of hurricanes.
We will serve society better by enhancing our efforts on improving our
models so that they can simulate the statistics of regional climate
fluctuations; for example: tropical (monsoon depressions, easterly
waves, hurricanes, typhoons, Madden-Julian oscillations) and
extratropical (storms, blocking) systems in the atmosphere; tropical
instability waves, energetic eddies, upwelling zones in the oceans;
floods and droughts on the land; and various manifestations (ENSO,
monsoons, decadal variations, etc.) of the coupled ocean-land-atmosphere
processes.
It is inconceivable that policymakers will be willing to make
billion-and trillion-dollar decisions for adaptation to the projected
regional climate change based on models that do not even describe and
simulate the processes that are the building blocks of climate
variability. Of course, even a hypothetical, perfect model does not
guarantee accurate prediction of the future regional climate, but at the
very least, our suggestion for action will be based on the best possible
science.
It is urgently required that the climate modeling community arrive at a
consensus on the required accuracy of the climate models to meet the
“greater demand for a higher level of policy relevance”.
2. Is “model democracy” a valid scientific method? The “I” in the IPCC
desires that all models submitted by all governments be considered
equally probable. This should be thoroughly discussed, because it may
have serious implications for regional adaptation strategies. AR4 has
shown that model fidelity and model sensitivity are related. The models
used for IPCC assessments should be evaluated using a consensus metric.
3. Does dynamical downscaling for regional climate change provide a
robust scientific basis for action?
Is there a consensus in the climate modeling community on the validity
of regional climate prediction by dynamical downscaling? A large number
of dynamical downscaling efforts are underway worldwide. This is not
necessarily because it is meaningful to do it, but simply because it is
possible to do it. It is not without precedent that quite deficient
climate models are used by large communities simply because it is
convenient to use them. It is self-evident that if a coarse resolution
IPCC model does not correctly capture the large-scale mean and transient
response, a high-resolution regional model, forced by the lateral
boundary conditions from the coarse model, can not improve the response.
Considering the important role of multi-scale interactions and feedbacks
in the climate system, it is essential that the IPCC-class global models
themselves be run at sufficiently high resolution.
Regards,
Shukla

It was standing room only…close to 300 scientists by my estimate.
As it is here on WUWT, with perhaps more scientists but plenty of room.
Good KISS model. Let me suggest, however, that the presentation lacks contorted, Machiavellian “tricks” that are a prerequisite for peer-reviewed publication.
/sarc

Thank you Dr. Spencer for keeping objectivity in climate science. What you are observing among your “peers” is politically motivated subjective research. They are searching for “positive feedback” that would create an unstable run away process that they can blame on CO2. In engineering, Feedback is a control mechanism that puts limits on the the output. It promotes stability.
From my study of climate data, I believe that water in all it’s forms is the earth’s thermostat that regulates the global distribution of temperature. CO2 is just going along for the ride. The energy transfer in the processes of evaporation, condensation, freezing, and thawing is orders of magnitude greater than the absorbtion of a couple of IR vibrational frequancies of a relatively low concentration of CO2. The tail isn’t waging the dog.

It’s pretty sketchy, but interesting. I think that it would be a very good idea for Dr. Spencer to collaborate with someone in the electrical engineering dept. to determine the real meaning of the loops and striations. What it seems to be saying to me (not completely understanding what he’s saying in that sketchy PDF) is that there are a couple of second-order processes with different time constants. But possibly not. He really needs to go over this in detail with a signal processing expert, and get to the bottom of exactly what order of process and time constants this implies. That, in turn, might suggest the nature of the processes themselves.

OK, having read his website, scratch the last comment. He’s already there.
It seems like he’s discovered what EEs knew 100 years ago – that the product of two cyclical variables integrates out to a higher value when they’re in phase, and goes to zero when they’re 90 degrees out of phase. I’d say this is a productive line of inquiry. It explains in fairly straightforward terms how a phenomenon can appear to have a high feedback, but in the long term, not amount to much.
Which leaves a lot of 20th century warming unattributed.

Keep up the good work, Dr. Spencer.
I’m interested in commentary the Richard Alley lecture: “The biggest Control Knob: Carbon Dioxide in Earth’s Climate History” Preferably, something beyond “he’s a fraud”.

Dr. Spencer,
If you’re reading these comments, I’d appreciate it if, time permitting, you could write a post on your site (or here) about the NASA AIRS observations (link below) and how they relate to your research.
Thanks,
David
http://wattsupwiththat.com/2009/12/16/nasa-says-airs-satellite-data-shows-positive-water-vapor-feedback/

Neo (07:16:23) :
I keep wondering why nobody seems to deal with these problems more like a signal processing problem. Looking at 1st order effects seems .. backward .. equivalent to using “using stone knives and bear skins.”
I mean, many of these sorts of systems have multiple phase delays to the looping components (i.e the oceans would have very long delays while the gases in the atmosphere very short delays) I would expect that there is some sort of impulse response to the system that could account for the phase delays or lags. The components could then be separated from the impulse response based on lag and their magnitudes examined.
Frankly, my observations of “climate science” gives me the impression that these scientists have missed the last few decades of engineering advancement. I suggest that you folks find a signal processing guy with experience in signal cancellation.’
I read a book many years ago about statistical searches for weather cycles. It was effectively the use of Fourier Transform analysis on datasets and it highlighted most of the repeating ‘cycles’ flagged up today. But it didn’t go into mechanisms too much, as the author was a mathematician.
Your post suggests that an interaction between climatologists, engineers and electronics guys might be valuable.
Perhaps it is already happening somewhere?

Jim (08:37:39)
Clouds are indeed effective moderators but the process is driven by solar energy into oceans.
If it were cloudy all the time solar energy would still get in but very much less. Unless, that is the, clouds were dense enough to exclude ALL solar energy. There would still be some geothermal energy though.

This whole thing must be extremely frustrating for you skeptical scientists (sad that I have to make that distinction).

Yes, that is sad. It was the way I was taught that science works that scientists were by nature to be “skeptical”.

@Andreas
It’s not so much looking at what they got in the model that can be kicked out, its actually the opposite. Dr. Tim Ball on Climate Audit related what happened at a seminar that a climate modeler put on. At the end of the presentation a Physictist got up and wrote a very long equation on a chalkboard and asked the modeler if that is the formula hs model was based on. The Modeler answered yes, then the Physictist started asking if a certain factor in the equation was taken into account in the model and for each No he scratched it off the board. By the time he was done 80% of the equation was scratched out, ie not taken into account in the model. Oh the Modeler is that Dr. in Copenhagen that used the UN security to get the guy to quit asking him pesky questions.

crosspatch (09:48:40) :
Actually, skepticism comes quite easily with modern AGW climate science, given that they have come to rely upon the *** hysterical press release *** as a means of disseminating their message to the masses…

Interesting perspective – signs of retreat as seen in the use of argument.
http://www.samizdata.net/blog/archives/2009/12/climategate_the_1.html

Well I’m not an AGU member; but if I had been, I would have gladly crawled on hands and knees, naked, over broken glass in a howling blizzard; to get from San Jose up to San Francisco, just to hear and support Dr Roy and his thesis.
In fact I don’t even need the good Dr or John Christy to convince me; “Hey, it’s the Water dummies !”
In fact, I just got an e-mail response this morning from the chap who is heading that global CO2 AIRS satellite program, after telling him that Water vapor is a perfectly good greenhouse gas; that simply puts CO2 to shame. For a start, it always exceeds the amount of CO2 in the atmosphere; and by a long way, and it absorbs a much greater percentage of the total Solar Spectrum radiation and the surface emitted LWIR thermal radiation, and thereby warms the atmosphere; just like CO2, only moreso.
And once the atmosphere is warmed, it pays no heed to whether it was warmed by H2O, or CO2, or O3 or any other method; nor whether the warming was due to absorbed solar spectrum radiation (longer than about 750 nm ) or LWIR in the 5-100 micron range. Warming is warming, and both H2O and CO2 are permanent constituents of the atmosphere.
And surface warming from the atmosphere; specifically ocean surface warming (only 70% of the total area is oceans) results in both Carbon dioxide feedback (ocean outgassing) and water vapor feedback (evaporation), so CO2 is just as much a feedback effect as H2O is.
If earth’s atmosphere contained not a single CO2 moelcule; nor an Ozone molecule, we would still be enjoying about the same comfortable temperature range; we would notice a little less cloud cover most of the time.
Well of course we wouldn’t even be here to care, if there was no CO2 in the atmosphere; but when we put it all back, all that is going to happen, is that the average global extent of cloud cover will increase.
You see H2O is the ONLY GHG that exists in the atmosphere in all three phases; vapor, liquid, and solid. While in vapor form it exhibits both negative feedback cooling (absorbs incoming solar spectrum energy, thereby cooling the ground), and positive feedback warming effects (capture of LWIR photons).
But when water vapor turns to liquid or solid, and forms clouds; well nobody ever observed it to warm up in the shadow of a cloud that just passed in front of the sun; it ALWAYS cools in the shadow zone.
And as for high level clouds (noctilucent) causing surface warming; well that goes right to Dr Roy’s comment on causality.
It makes sense doesn’t it; the higher altitude at which a cloud forms, the lower is the atmospheric density, and hence the lower is the amount of water vapor needed to reach the dew point. The temperature also drops for about thefirst 25 km, then rises to about 0C then drops again up to about 90 km where the density is less than 10^-5 of the surface density.
So the amount of water in those high clouds, is miniscule, which explains why just a small amount of energy can raise the temperature substantially; but there isn’t much thermal capacity to be heating the surface; and the higher you go, the less of that there is. Yes I’m sure that the higher clouds form, the hotter they warm the surface.
Alternatively one might consider that it is the warm or warmer surface, that is the cause of those high and higher clouds; not the result of them.
Well of course we do know that dry desert air cools rapidly at night, but less rapidly if there are clouds. So how come that evil CO2 doesn’t keep the desert air warm at night, when there is no water.
So I don’t buy that water is a feedback servant of CO2, any surface warming caused by any atmospheric warming (damn little) results in an increase in both CO2 and H2O in the atmosphere, but either one can do without the other.
So the AGW crowd needs to get off this kick that water is not a GHG but a mere feedback slave to CO2.
So right on Dr Roy; you tell them how it is. Well it would take one hell of a big attraction (Like Dr Spencer) to get me to ride to SanFrancisco, in a luxure Limo with Champaigne and Caviar laid on, and a red carpet reception.
I generally don’t go to that place for any reason. Last time was probably the King Tut first exhibit about 20 years ago.

RE: “Now it’s a foreign and radical idea.”
The percent of the population in most Western countries these days, who know what a Fourier or Laplace Transform are, let alone know how to use them, must be around 1%.

Thanks for trying to maintain the integrity of Science in the face of the current climate of ‘manufactured consensus’. (Is his analagous to Chomsky’s ‘manufactured consent ?)

Why you don’t need to be a publishing climatologist to have a superior view of climate:
“[…] recipe that has become all too common in recent years: analyze the output of climate models that predict substantial global warming, and simply assume the models are somewhere near correct.”

George E. Smith (10:58:46
‘Well of course we do know that dry desert air cools rapidly at night, but less rapidly if there are clouds. So how come that evil CO2 doesn’t keep the desert air warm at night, when there is no water.’
Back went I started looking into “Co2 drive the climate” thing, I did a comparison between Yuma, Arizona and Shreveport, Louisiana. Both have/had about the same populations number. Both are with in miles of being along the same latitude. The elevation is close to being the same. Both are about the same distant from a large body of water.
The average temperature lows were about the same, but Yuma’s average highs were 12 degrees F warmer than Shreveport. Why? Water vapor, clouds, and precipitation.

“”” Dave F (11:28:09) :
George E. Smith (10:58:46) :
If it worked the way it has been postulated other places, wouldn’t the whole durn thing become unstable? Warming -> more water vapor -> more GHGs -> more trapped radiation -> more warming -> more water vapor -> and so on? “””
Well no it wouldn’t. Positive feedback can increase the gain; but only in certain conditions does it become a runaway situation.
Easier to describe in a simple Voltage amplifier feedback system (not necessarily a typical one)
Say I have a Voltage amplifier with a forward gain (A) =10, so if I apply a one Volt step to the input, the output will step up 10 Volts (which would saturate modern Op amps that may run off 5 Volts or less).
So now I apply some positive feedback by picking off 1% of the output Voltage and adding that to the input in such a way as to increase the input. My loop gain (A.beta) is 10 x 0.01 = 0.1 so my 10 Volt output signal will generate a 0.1Volt feedback signal (beta = 0.01).
So not my total input Voltage is 1 + 0.1 = 1.1 Volts. (I’m doing this in slow time, but my amplifier really has a much shorter propagation delay).
So after the forward propagation delay and the feedback delay, my total input signal is now 1.1 Volts, and my Amplifier gain of 10 dutifully turns this into an output Voltage of 11 Volts, and the feedback facto of 0.01 changes the feedback signal to 0.11 Volts, so now my totla input is 1.11 Volts after two prop delays. This now produces an output Voltage of 11.1 Volts, and a 0.111 Volt feedback signal giving a total input signal of 1.111 Volts.
Well you can see how this is going. After an infinite amount of time, it all quits changing, and the total output swing is now 11.11111111… Volts, or 100/9 Volts. So it is like the tortoise and the hare.
Now this happened because my loop gain (A.beta) is less than 1.000
so the ouput was definitely increased by the positive feedback; but it didn’t run away.
Because of the propagation delay (all physical processes take time to act), the feedback signal is slightly delayed from the original input signal that created it, and you have to vector sum the components, instead of simply straight line add them as I did.
so real feedback systems also involve a time response; and you can’t really define the stability criteria of a feedback system unless you know what that time response is.
Guess who was the last climate scientist to actually put the time (frequency) response into his feedback model. Well don’t ask me because I have never seen anyone do it.
In the case of our GHG system, the water cheats, and before the heating gets too far out of whack, all that water vapor starts to form clouds which blocxk out more and more sunlight (as well as reflect some back into space), so it is impossible for our system to runaway; well not untill we boil away all of the oceans to eliminate clouds.
And as to more water vapor causing more precipitation; it is well known that over time (climate) total global precipitation must equal total global evaporation. That has the advantage of keeping the oceans here on the ground, instead of up in the sky.
sell SCIENCE July-7 2007 Frank Wentz (RSS) et al; “How much more Rain Will Global Warming Bring?”
The answere is (he actually measured it) is a one degree rise in mean global surface temperature causes a 7% increase in evaporation, Precipitation, and total atmospheric water.
Those highly accurate computer climate models (well they call them GCMs) agree completely with the 7% increase in total atmospheric water content; but they say that the evap/precip, is only 1% to 3% per degree C. Well that is only a factor of2 2/3 to 7 times error from what the RSS team measured with actual satellites.
It is left up to the reader to decide whether to believe those high speed computer models, or to go with what was actually measured here on planet earth.

“”” old construction worker (13:35:56) :
George E. Smith (10:58:46
‘Well of course we do know that dry desert air cools rapidly at night, but less rapidly if there are clouds. So how come that evil CO2 doesn’t keep the desert air warm at night, when there is no water.’
Back went I started looking into “Co2 drive the climate” thing, I did a comparison between Yuma, Arizona and Shreveport, Louisiana. Both have/had about the same populations number. Both are with in miles of being along the same latitude. The elevation is close to being the same. Both are about the same distant from a large body of water.
The average temperature lows were about the same, but Yuma’s average highs were 12 degrees F warmer than Shreveport. Why? Water vapor, clouds, and precipitation. “””
Lemme guess, Shreveport LA also has exactly the same humidity as Yuma AZ does. And I am sure photgraphs taken around shreveport show the typical terrain looking exactly like Yuma.
Strange what causes places to be different.

Dr Spencer,
I am a great fan of your work and believe you have a very rare approach in climate science, that is to say the traditional scientific approach. I was very interested on your last comment of simplicity. I really like the simple model you have developed. It is unfortunate that the advent of high computing power has led scientists to suddenly favour complexity simply because we now can. It is completely against science to favour complexity in my view. Science demands that we go for the simplest model possible. Simple models are easier to disprove or falsify than complex models, being of a higher empirical content, and therefore should be naturally favoured by science. The more complex a model is the easier it is to account for a wider range of observations and the harder it is to falsify. F = ma is easy to falsify and therefore a very favourable scientific model. F = ma + ma^2 + ma^3 + ma^4 +va + va^2 + qa is not easy to falsify and should be a last resort for any scientist. Thankyou for your stimulating posts (here and on your blog) and for your refreshingly conventional scientific approach.
Regards,
Alex Buddery

George E. Smith (13:48:45) :
‘Lemme guess, Shreveport LA also has exactly the same humidity as Yuma AZ does. And I am sure photgraphs taken around shreveport show the typical terrain looking exactly like Yuma.
Strange what causes places to be different.’
Yep. If it was all based on CO2, both places would look the same

George, as I have said before the only thing worst than being cold and hungry is being WET, cold and hungry.

Norman;
“I(Norman) stated that if Carbon dioxide were the primary driving force for the Global warming then the U.S. should show a drastic upward spike since the Carbon dioxide concentration is highest in the U.S. (before it globally diffuses).”
Is it ? In terms of humans per square mile the USA is at about 1/10th of the UK and about 1/15th of Belgium.
So I might suggest that since Europe is running at about 10 times the number of humans per square mile the CO2 concentration should be higher in Europe than the USA (before it globally diffuses).
Adding that CO2 production is caused not just directly by humans but human activity – industry, intensive agriculture, etc.
Roughly;
Canada 8 persons per square mile
USA 82
UK 651
Germany 594
France 305

Dr. Spencer,
 Really good models, like theories, should predict an observation not yet made. What predictions does your model make that others can experimentally verify?
BTW, I am a big fan. Keep up the good (and difficult but much appreciated) work.
Mike Ramsey

Nic (15:14:26) :
“So (Nic) might suggest that since Europe is running at about 10 times the number of humans per square mile the CO2 concentration should be higher in Europe than the USA (before it globally diffuses).”
Thank you for your reply to my question. I was looking at the NASA map (on a previous article on this web site) but here is a link that shows how much each Nation emits of Carbon Dioxide. China is now #1, United States is #2 and the Entire European Union is #3.
The link: http://en.wikipedia.org/wiki/List_of_countries_by_carbon_dioxide_emissions
My basic question, if carbon dioxide is the primary driver for Global Warming then the United States temp for the last 100 years should be the one spiking, not the Global temp. Currently United States and China should have by far the biggest spikes of temp on any other spots on Earth if carbon dioxide is a primary warming driver.

Interesting post. given that you often identified as one of the prominent ‘skeptic’ scientists I’ve always wondered how you (and others) are treated in private/professional setting especially given the vitriol that can be found so quarters. Also what proportion of climate/earth scientists are motivated in their work by their own environmental politics or basic scientific curiosity.
It’s interesting you mention Dessler, I ended up on one of his papers yesterday after reading the posting about the AIRS data on WUWT.
The paper is Dessler, A. E., Z. Zhang, and P. Yang (2008), Water-vapor climate feedback inferred from climate fluctuations, 2003’2008, Geophys. Res. Lett., 35, L20704, doi:10.1029/2008GL035333.
and as you mention it’s focus is feedbacks between water vapour and temp. I felt he was mixing cause and effect with this work. Identifying anomalies in temp caused by ENSO and then doing analysis of the temp/vapour relation ship. He comes with a conclusion of positive feedback between temp and vapour (the common sense conclusion) but seems to forget that it is ENSO (changes in ocean and atmosphere currents) that is driving this process rather than temperature per se.

Keith Minto (17:36:01) :
“Steve Short (16:16:09), those comments were interesting, most research is involved in the physics and not the biological/chemistry of seawater.
The upper limit for solar penetration I have seem is 50m, my understanding was that it was a lot less.”
Thanks Keith. If interested, please see a post of mine on Nichel Modeling some time back:
http://landshape.org/enm/oceanic-cayanobacteria-in-the-modern-global-cycle/
(I’m not responsible for the misspelling in the URL 😉

Just throwing this out there, OT. I saw the report of the most recent underwater volcano. Do we have even a close/accurate count of underwater volcanoes? How can we understand how CO2 interfaces with warming when we can’t have an accurate count of undersea activity and the amount of CO2 being added to the ocean at depth? Another component to consider when trying calculating how much CO2 the ocean will absorb from the atmosphere.
You guys always get me thinking 🙂

Fred H. Haynie (15:17:15) :
George E. Smith (14:37:30)
‘Bear in mind, in the Weather is not climate vein; that when you talk about more clouds bringing more cooling; you are talking about an increase in average cloud coverage, over climate time scales; last night’s weather does’t matter much.’
We don’t live in a black box and true last night’s weather does’t matter much. But what would happen if wind patterns change a little and Yuma received more moist air from Baja and Shreveport started getting more dry air out of the northwest. Day by day, week by week, year by year, their climate condition for their area would change. Some times, I think people forget, we don’t live in a calm atmosphere. It is violent. Always changing. Co2 has very, very, very little to do with it.

Just throwing this out there, OT. I saw the report of the most recent underwater volcano. Do we have even a close/accurate count of underwater volcanoes?
The team’s “heat in the pipeline” has been found.

last I heard, they took a small survey of undersea volcanoes in that region of the world and were shocked to find that there were many that were unknown. Extrapolating outward from the small survey region, these people thought there could be thousands of them currently active that have never been observed. Unfortunately, I don’t recall any details about where I saw this, only that there could many thousands spread out around the pacific. Whether that could result in serious amounts of co2 being injected into the deep water or whether it could cause a significant amount of heating in the lower areas when averaged over the oceans are two good questions. The skeptic in me causes me to doubt at least the warming factor as being insignificant and to be doubtful that the co2 injection could have much of an effect either but not enough for me to have an opinion one way or another.

“”” cba (08:13:13) :
”
Keith Mento
An interesting report by Ohlmann, et al. http://www.icess.ucsb.edu/~davey/MyPapers/Ohlmann_etal_JClimate_1996.pdf claims that the amount of energy in the deeply penetrating spectral wavebands (relative to total solar energy) can be at least 14% larger under clouds!. They claim that clouds shift energy into the blue green spectrum that penetrates to greater depth. By eyeballing some charts it seems to me that 520nm has the greatest depth penetration.
Steve Short (16:16:09), those comments were interesting, most research is involved in the physics and not the biological/chemistry of seawater.
The upper limit for solar penetration I have seem is 50m, my understanding was that it was a lot less. “””
“”” They claim that clouds shift energy into the blue green spectrum that penetrates to greater depth. By eyeballing some charts it seems to me that 520nm has the greatest depth penetration. “””
Now do they by any chance disclose the Physics of this “shift of energy to the blue green part of the spectrum”
They are certainly correct that the blue green part of the spectrum penetrates deepest in the oceans. But what exactly causes the spectrum energy shift ?
It is possibly true that scattering in the clouds eliminates other portions of the spectrum; but what kind of freuency shift could actually increase the total energy in the blue green. Sounds like a sloppy statement to me. What are the Watt’s per square metre in the blue green, before the clouds, and after the clouds ?
As for trapping for 9 months; anything that warms the deeper waters is going to create expansion and a vertically upward convective current. So I would like to see more proof that the thermal energy stays down there for nine months before it can return to the surface. But an interesting paper.

“”” Keith Minto (17:36:01) :
Tallbloke (15:37:00)
Research follows the money and most is involved in looking at UVB penetration into seawater. The Spectral distribution of solar energy at sea level was reported to be 3% for UV, 44% for visible and 53% for IR. Sea water albedo at low to mid latitudes was reported to be 0.06.
An interesting report by Ohlmann, et al. http://www.icess.ucsb.edu/~davey/MyPapers/Ohlmann_etal_JClimate_1996.pdf claims that the amount of energy in the deeply penetrating spectral wavebands (relative to total solar energy) can be at least 14% larger under clouds!. They claim that clouds shift energy into the blue green spectrum that penetrates to greater depth. By eyeballing some charts it seems to me that 520nm has the greatest depth penetration.
Steve Short (16:16:09), those comments were interesting, most research is involved in the physics and not the biological/chemistry of seawater.
The upper limit for solar penetration I have seem is 50m, my understanding was that it was a lot less. “””
Don’t know who wrote what above.
From the Infra-Red Handbook (Wolfe & Zissis)
Sea water has its minimum attenuation at about 470 nm (definitely blue) at about 0.0001 Absorption coefficient (cm^-1) That means 470 nm blue light (aka blue LEDs) will be attenuated to 1/e (37%) in 10,000 cm or 100 metres. So the 50 metre limits is way too shallow. Any scuba diver can tell you the surface is still visible easily at 150 ft depth (open ocean water). The absorption coefficient increase to 0.01 at about 770 nm in the deep red, and about 300 nm in the UV, so that would be just one metre penetration to 1/e intensity. Water is most sea opaque at 3.0 microns wavelength in the IR at about 8000 cm^-1, giving a 1.25 micron penetration depth to 1/e, but the general absorption coefficient away from that 3.0 micron max is about 1000 cm^-1 which puts the 1/e depth for most of the IR longer than 2.5 microns at about 10 microns depth.
Sunlight penetrates much deeper in the ocean than many people think.

George E. Smith (11:12:44) :
‘Well you won’t get any disagreement from me on that score. I was merely pointing out that just because some high clouds at night may slow the evening cooldown, does not negate the fact that the increased cloud cover will block far more solar energy from the surface during daylight hours; so ANY cloud increase ALWAYS causes cooling over time.’
I wasn’t disagreeing with you, but sometimes people do not realizes how over time nothing remains the same. The Rocky mountains are getting higher while at the same time Appalachian Range is washing out to sea. In the great lakes area the crust is still up lifting from the Ice Age. Each will have an effect on local climate. The question is how many other parameters must be accounted for just to pin point how hard or where the wind blows.
I would have been more impressed with the “Co2 drives the climate” thing if a young meteorologist looking at weather balloon data and wonder why the upper troposphere was warming than a politician wanting a reason to build nuclear power plants.

cba and George E Smith. T
The chart that I ‘eye balled’ was figure 4,a and my 520nm on second sight looks like 490nm, close to the 470nm stated by George. cba I agree that clouds would attenuate and not frequency shift. I guess my interest in this is how much heat is going into the ocean from sunlight and it appears that clouds would decrease IR reaching the ocean. The light penetration issue is interesting but complex,turbidity and backscattering would influence depth penetration and well as light wavelength. The fact that IR penetrates only the surface layer (prior to mixing) is probably the part that interests me and thanks for that info.
Part of the conclusion to the linked article is interesting, “Values for solar penetration computed here for 10deg N,10deg S,140-170E, mean solar flux penetration is 12wm2,a figure 40% less than that produced by Ramanathan”.

Keith Minto,
You can forget IR having any penetration into the ocean. Even Red goes away quickly. Having clouds overhead significantly increases the IR coming down rather than decreasing it overall as the clouds may block solar IR but they have their own longer wave IR to emit.
There has been some effort made by some to harp on the skin effect with claims that it blocks or reduces heat flow. What is really going on with that is the fact that at the surface, there is insufficient heat flowing in to maintain a higher temperature and that it is losing too much heat by evaporation and radiation. The give away to that is that in conduction and convection, the heat flow quantity down lower depends upon the temperature differential down lower and nowhere else. If the skin warms up some, that cannot affect the flow of heat down below the skin unless it affects the temperatures down below as well. If the warmer skin could warm the area immediately below it, then it could reduce the flow of heat from lower down. But then, there wouldn’t be a skin effect. Heat flow in conduction is modeled just like current flow in electric circuits where there is a thermal resistance, a heat flow ‘current’ and a temperature (voltage equivalent) difference. Where there is a temperature difference (like voltage) it’s because of a resistance to the flow of heat (electric current) and the heat (current) is restricted more at that point than elsewhere. What’s happening to the skin is that it is getting rid of more heat than is coming in when it is at a higher temperature so it cannot by conservation of energy maintain that temperature.

Forgot the other half…
Thus, the data are consistent with a rise in temperature creating an increase in radiative flux at some time later, which could be due to a dominant negative cloud feedback, which increases outward radiated flux, rather than a dominant positive water vapor feedback which would decrease radiated flux.

I was at the AGU on Thursday and there were a LOT of great posters and papers there, most of them showed the MWP and the Holocene optimum and not a hockey stick in sight!