I’m always searching for better and simpler ways to explain the reason why I believe climate researchers have overestimated the sensitivity of our climate system to increasing carbon dioxide concentrations in the atmosphere.
What follows is a somewhat different take than I’ve used in the past. In the following cartoon, I’ve illustrated 2 different ways to interpret a hypothetical (but realistic) set of satellite observations that indicate (1) warming of 1 degree C in global average temperature, accompanied by (2) an increase of 1 Watt per sq. meter of extra radiant energy lost by the Earth to space.
The ‘consensus’ IPCC view, on the left, would be that the 1 deg. C increase in temperature was the cause of the 1 Watt increase in the Earth’s cooling rate. If true, that would mean that a doubling of atmospheric carbon dioxide by late in this century (a 4 Watt decrease in the Earth’s ability to cool) would eventually lead to 4 deg. C of global warming. Not good news.
But those who interpret satellite data in this way are being sloppy. For instance, they never bother to investigate exactly WHY the warming occurred in the first place. As shown on the right, natural cloud variations can do the job quite nicely. To get a net 1 Watt of extra loss you can (for instance) have a gain of 2 Watts of forcing from the cloud change causing the 1 deg. C of warming, and then a resulting feedback response to that warming of an extra 3 Watts.
The net result still ends up being a loss of 1 extra Watt, but in this scenario, a doubling of CO2 would cause little more than 1 deg. C of warming since the Earth is so much more efficient at cooling itself in response to a temperature increase.
Of course, you can choose other combinations of forcing and feedback, and end up deducing just about any amount of future warming you want. Note that the major uncertainty here is what caused the warming in the first place. Without knowing that, there is no way to know how sensitive the climate system is.
And that lack of knowledge has a very interesting consequence. If there is some forcing you are not aware of, you WILL end up overestimating climate sensitivity. In this business, the less you know about how the climate system works, the more fragile the climate system looks to you. This is why I spend so much time trying to separately identify cause (forcing) and effect (feedback) in our satellite measurements of natural climate variability.
As a result of this inherent uncertainty regarding causation, climate modelers are free to tune their models to produce just about any amount of global warming they want to. It will be difficult to prove them wrong, since there is as yet no unambiguous interpretation of the satellite data in this regard. They can simply assert that there are no natural causes of climate change, and as a result they will conclude that our climate system is precariously balanced on a knife edge. The two go hand-in-hand.
Their science thus enters the realm of faith. Of course, there is always an element of faith in scientific inquiry. Unfortunately, in the arena of climate research the level of faith is unusually high, and I get the impression most researchers are not even aware of its existence.
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Further to “global average temperature” and whether it “exists”: I believe astronomers ascribe temperatures to distant stars based on their emission spectrums. Imagine that a sensor was located on one of the Voyager probes and it now could observe the earth, which, due to distance, would appear to be a point source of radiation, and that it was possible to filter out the portion of that spectrum which was reflected solar radiation, then you could ascribe a temperature to the whole earth based on the characteristics of the remaining emitted radiation and an assumption about what the global “grey body” coefficient of the earth is. If you watched that spectrum over time it might change so as to indicate an increasing, or decreasing, “global” temperature. Now try to imagine predicting, using thermometers here on earth and calculating a weighted average of the temperature readings taken, what we would expect the global temperature measured from the Voyager probe to be.
I haven’t had a chance to read all comments, but the 1 Watt increase in outgoing IR-plus-reflected solar is consistent with the IPCC models, which range from +0.8 W to 1.9 W per sq. meter extra loss per deg. C of Warming.
Any value less than 3.3 Watts (the loss of extra IR through temperature alone) is positive feedback, while greater than 3.3 is negative feedback. A positive value is required for a stable climate system, and all IPCC models have a positive net feedback parameter…but less than 3.3.
Re: Ron Dean (10:23:46)
Be careful.
Putting all ‘statisticians’ in the same basket is a serious error. Some of them are religiously devoted to 100%-untenable abstract assumptions, I assure you — and because of their algebraic wizardry, they wield hypnotic powers over the innocent masses.
Don’t get me wrong. These are incredibly intelligent people ….but their paradigm is based on X1, X2, X3, … random ~i.i.d. We have TONS of deterministic conditional dependencies to work out before we can satisfy such base assumptions — we are light years from firm statistical footing at present.
Everything that is done in statistics is based on assumptions. Good judgement hinges on sober awareness of their connection, if any exists, to reality.
Statistics students have enough on their plates plowing through volumes upon volumes upon volumes of derivations & proofs even if they expediently buy the assumptions wholesale (which most do, btw).
Furthermore, consider that the data they analyze (for the seeming-few who aren’t theoreticians…) come from diverse disciplines — and mathematical-statistics is such an expansive field that if stats scholars dare venture down too many paths towards common sense awareness in multiple disciplines, they may be lost at home (aside from some rare, gifted individuals perhaps…)
Interdisciplinary studies of complexity are necessarily ….complex.
Via phase-aware methods, I believe we may one day know enough of deterministic conditional dependencies in climate to satisfy randomness assumptions for residuals, but we’re not remotely near there yet. [Don’t fall for all this misguided fluff about ‘red noise’.]
Grumpy old man,
“A model using data from Mauna Loa for CO2, and satellite temperature data shows that temperature changes seem to be related to the rate of change of the CO2 level, not the absolute level.”
That would be great news if it were true, since it means we could avoid warming by merely keeping the current CO2 level at the current level with no need for cuts.
However, whereas the recession only began 2 years ago, the warming ended a decade ago, so the model isn’t even empirically valid.
Re: Jimbo (09:40:46)
Excellent quote of Trenberth – I’ve always had the sense that he is interested in the truth (…but perhaps caught up in some unpalatable social ‘dynamics’…)
Thanks for the laugh:
Ron de Haan (03:04:38) “Dutch Government Educative Publication: Skeptics are white males (It’s because of the testosterone, not the science)”
Dr. Spencer,
Slightly off topic, but over at ‘Deltoid’ they are giving you some stick because you changed your satellite lower atmosphere chart from a running 13-month average to a running 25-month average. They are becoming fearfully excited and I worry for them. Perhaps you could explain if you have a moment. I am happy to pass the message on if you prefer not to be contaminated!
http://scienceblogs.com/deltoid/2010/01/roy_spencer_hides_the_increase.php#comments
John (02:55:50) :
No, no, no!
Assumming there is no other source of energy. The Earth recieves ~1400 w/m2 from the Sun. This energy is absorbed as a circle but emmitted as a sphere so divide by 4 and the Earth emitts 350w/m2 back into space. (…)
Absorbed as a circle? That would seem a severe oversimplification. With the Earth as a sphere, by simple optics at some point as you get to the edge of the sphere the angle of reflection must be accounted for, thus the apparent cross-sectional area for energy absorption calculations would be smaller. You would have to calculate different values of the angle for the different substances in the atmosphere and the surface, for the different wavelengths of radiation, figure out adjustments for how clouds shade the surface, etc. Plus there may be problems with treating the Earth as a series of spheres with smooth surfaces, the roughness may have to be accounted for.
With satellite measurements over a long enough period, preferably observing the Earth at quite some distance away, you could figure out an observed general value for energy calculations. But to simply calculate by saying the Sun is giving off this amount of energy per area measurement at Earth orbit distance, there is this much cross-sectional area, so just multiply the two for how much energy the Earth receives, doesn’t seem very scientific.
“”Vincent (02:02:22) :
lgl (00:44:42) :
“More Realistic View” ?
1 Watt net loss and 1 C warming? Does not make sense to me
This is based loosely on blackbody radiation. If something gets warmer, it radiates more energy. Thus, the 1c of warming would be associated with extra radiation into space – 1 watt in this case.
The question I have is that in the example on the right, the diagram shows an extra 3 watts radiated into space, but in the body of the text it says “The net result still ends up being a loss of 1 extra Watt.” I don’t follow that logic, which brings me onto:
sHx,
“”
This doesn’t really make sense to me either.
A 1 deg C rise in surface T is going to raise the emitted radiation at the surface by around 5.5 w/m^2. The atmosphere for clear sky wil block about 30% of the outgoing or pass through 70% (3.8w/m^2). Clear sky accounts for about 48% of the surface, the rest is clouds which are going to block outgoing radiation from the surface. The extra power going out is going to be around 1.8 W/m^2 after accounting for the outgoing absorption and the cloud cover fraction.
It would seem the ipcc is claiming that something else – such as a change in cloud cover is going to result in only 1w/m^2 additional being emitted. It is probably coming from one of their defective models. I don’t see where Roy’s is coming from. He seems to be assuming a drop in cloud cover and that may be based upon measurements like the 1997/8 heat spike. If that’s the case though, he may have a causality problem as the rise in T was probably due to the drop in cloud cover not the cloud cover being reduced by a rise in T. I didn’t see where he explained just what was happening or how it was happening. To me, that means his explanation is confusing and unclear. Just saying that T goes up and radiated emission goes up because of clouds just doesn’t explain or clarify anything. It’s just too simplified to make any sense.
The Earth’s surface albedo is around 0.08 and it is for incoming solar power that is mostly visible and near IR. That 0.08 is the combination of mostly ocean – under 0.04 albedo and land surface, averaging between 0.1 and 0.2 and includes current ice cover. As one goes towards longer IR wavelengths, the surface emissivity which is related to surface albedo at the longer wavelengths, is going to be approaching 1.0 as the surface tends towards being a blackbody, absorbing most of the longwave IR and permitting stefan’s law to work fairly well.
NOTE: my above post stated 48% clear skies and it should be more like 38% with Earth having around 62% typical total cloud cover. That reduces the 1.8 w/m^2 down to around 1.5 w/m^2.
Ron Dean (10:23:46) :
This brings us to global average temperatures. As a weather number, global average temperatures are worthless. However, since climate is statistics, it has mathematical meaning. It shows a trend, not an occurrence.
By that reasoning, and I am not saying I disagree with it, we should get just as much information by just measuring the temp in just one location. That is also a statistic and may infer just as much information.
Kwinterkorn (07:44:17) :
Tantalisingly close.
Without giving away someone else’s farm. Procession of syzygies of the inner planets and the gas giants with regard to Northern hemisphere winter, as opposed to its Southern counterpart – its own summer. Harmoniously wondrous cycles.
Roy W. Spencer.
First of all, thank you so much for clarifying your ‘lead post’ within the ensuing thread. This practise is SO helpful to ‘thread posters’.
Thanks for explaining the normal use of the ‘satellite product’, but this mostly corresponds to a static use, as in a ‘clockwork’ representation of the local ‘Mandelbrot set’, etc. However, a climate predictor would need to be far more ‘organic’ than this and show ‘chaos’ to some degree.
Without a mathematical model that shows a realistic inclusion of chaos it’s ‘a dead animal’ (an incomplete model). Without the representation of a ‘chaos factor’ a model can’t represent any degree of ‘evolution’ of ‘the system’, or possible changes within ‘attractors to climate’ that give rise to ‘change’. Thus, can’t even offer an ‘alternative reality’ to climate per se. However, an ‘organic model’ would show true variability (at least).
You have offered two possible scenarios here that both show the same outcome and outline, the ‘duplicity’ of ‘static models’ (worst case and best case scenarios).
I concur. A lot of data and scenarios are still missing.
Best regards, suricat.
“Unspecified Cause” sounds a bit like Intelligent Design, doesn’t it Roy?
[REPLY – Three choices: 1.) Atheism/Agnosticism, 2.) Deism, 3.) Intelligent Design. Pick one. You can be like ~90% of the world and go for option 3, ~10% and go for option 1, or ~0% and go for option 2. As for me, I’m option 1. Thus endeth the theological lesson for today. ~ Evan]
Basically this is saying that the Earth isn’t just a giant test tube – it’s more complicated than that! We’re just not sure HOW complicated!
Sorry for the exclamation marks, just a bad habit!!!
Leif,
This must be the second or third time you have taken the time to help me out. Thank you so much. I really appreciate it and you are one of the experts that posts regularly and who make this blog so interesting. If I had not left behind a fully funded masters research grant in physics to fly to far flung places with the oil industry, I might not be quite so muddled and in need of so much help!.
Paul Vaughan (12:25:01) :
Your posts are always most enlightening, Paul. Thanks.
Chris
Norfolk, VA, USA
Jeremy (18:11:54) :
If I had not left behind a fully funded masters research grant in physics to fly to far flung places with the oil industry, I might not be quite so muddled and in need of so much help!.
Your interest is what is important.
Evan
As for me, I’m option 1.
Random-ism/Anti-gnosticism. Preclusion is not scientific.
robr (16:39:23) :
“By that reasoning, and I am not saying I disagree with it, we should get just as much information by just measuring the temp in just one location”.
Well my friend don’t laugh but you are onto something here that I’ve suggested in the past.
How about “some” stations in “dry” or water vapour poor areas?
Afterall, there is a big bruhaha about the level of feedback from WV, so why not find stations that eliminate WV as much as possible? That way, the increased CO2 in the atmoph should show up as higher night time lows.
I
Head’s up on AO (Arctic Oscillation):
I’ve found what appears to be a systematic bias in the 1899-2002 AO reconstruction (which is based on SLPs). I have found a VERY SIMPLE way to reduce the variance in the residuals BY A FACTOR OF 2 (i.e. the size of the errors can be cut in half – & with ease).
This is stuff a good Stat 101 student would notice.
I also discovered a sloppy join part-way through 2001.
The pre-existing term was “drivers,” I think, and they should have stuck with it instead of trying to twist people’s arms.
Phillip Bratby, Average Temperature
In 2008, Briggs, a statistician, wrote two entries related to “You cannot measure a mean.” For those interested in average temperature, they may be useful for further understanding of the issues.
http://wmbriggs.com/blog/?p=104
http://wmbriggs.com/blog/?p=106
He also has problems with the use of smoothed data when when used for statistical prediction:
http://wmbriggs.com/blog/?p=735
The point being: we don’t really understand the “Other Stuff” – that is the random factors that drive temperature through wild swings around the average or mean value – and that we are placing too much reliance on our model’s ability (model being a mean with linear trend) to predict future climate.
Phil. (09:23:40)
What you say usually makes sense, but are you really trying to say that washing will not dry on a hot overcast day?
Try and tell my wife that her washing will not dry on the line if it is hot but overcast, and she will laugh at you, put her washing out, and have it dry in an hour or two, wind or no wind.
Convection is enough, wind just makes it dry faster.
What do you do with a theory that doesn’t match real world experience?
Wind Turbine technology…perfect for countries visited by typhoons 26 times a year on average!