
Oh dear, now we have three peer reviewed papers (Lindzen and Choi, Spencer and Braswell, and now Richard P. Allan) based on observations that show a net negative feedback for clouds, and a strong one at that. What will Trenberth and Dessler do next? Maybe the editor of Meteorological Applications can be persuaded to commit professional suicide and resign? The key paragraph from the new paper:
…the cloud radiative cooling effect through reflection of short wave radiation is found to dominate over the long wave heating effect, resulting in a net cooling of the climate system of −21 Wm−2.
After all the wailing and gnashing of teeth over the Spencer and Braswell paper in Remote Sensing, and the stunt pulled by its former editor who resigned saying the peer review process failed, another paper was published last week in the journal Meteorological Applications that agrees well with Spencer and Braswell.
This new paper by Richard P. Allan of the University of Reading discovers via a combination of satellite observations and models that the cooling effect of clouds far outweighs the long-wave or “greenhouse” warming effect. While Dessler and Trenberth (among others) claim clouds have an overall positive feedback warming effect upon climate due to the long-wave back-radiation, this new paper shows that clouds have a large net cooling effect by blocking incoming solar radiation and increasing radiative cooling outside the tropics. This is key, because since clouds offer a negative feedback as shown by this paper and Spencer and Braswell plus Lindzen and Choi, it throws a huge monkey wrench in climate model machinery that predict catastrophic levels of positive feedback enhanced global warming due to increased CO2.
The cooling effect is found to be -21 Watts per meter squared, more than 17 times the posited warming effect from a doubling of CO2 concentrations which is calculated to be ~ 1.2 Watts per meter squared. This -21 w/m2 figure from Richard P. Allan is in good agreement with Spencer and Braswell.
[While the -21wm2 and ~1.2 W/m2 values are correct, the comparison is wrong, and it is my mistake. The values are Top of Atmosphere and Surface, which aren’t the same. This prompts a new rule for me, I shall not publish any posts after midnight again (other than something scheduled previously during the day), because clearly I was too tired to recognize this mistake. I’ll add that I have emailed Dr. Allan regarding the question of feedback on hisfigure 7, and have not received a response. – Anthony]
Here’s the paper abstract, links to the full paper (which I located on the author’s website) follow.
Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere
Richard P. Allan
Abstract: Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of short wave radiation dominates over the long wave heating effect, resulting in a net cooling of the climate system of -21 Wm-2. The short wave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact long wave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.
1. Introduction
Earth’s radiative energy balance (solar radiative energy absorbed and terrestrial radiation emitted to space) determines current patterns of weather and climate, the complexity of which is illuminated by satellite observations of the evolving distribution and diversity of cloud structures. Representing clouds and the physical processes responsible
for their formation and dissipation is vital in numerical weather and climate prediction, yet many approximations must be made in these detailed models of our atmosphere (e.g. Bony et al., 2006; Allan et al., 2007). Observations of cloud characteristics from satellite instruments and in situ or ground-based measurements are crucial for improving understanding of cloud processes and their impact on Earth’s radiative energy balance (Sohn, 1999; Jensen et al., 2008; Su et al., 2010). The energy exchanges associated with cloud formation and precipitation are also a key component of the global water cycle, of importance for climate change (Trenberth, 2011). In this paper, initially presented at a joint meeting of the Royal Meteorological Society and Institute of Physics on Clouds and Earth’s Radiation Balance (Barber, 2011), the utility of combining weather forecast model output with satellite data in estimating the radiative effect of cloud is highlighted. Using a combination of models and satellite data a simple question is addressed: how do clouds influence the radiative energy balance of the atmosphere and the surface.
As an example of the radiative impact of cloud, Figure 1 displays thermal infra-red and visible channel narrow-band images of the European region from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on board the Meteosat-9 satellite (Schmetz et al., 2002).

In both images clouds appear bright: this denotes relatively low infra-red emission to space and relatively high reflection of visible sunlight to space. The hot, generally clear regions of northern Africa are also noticeable in both images since they are associated with substantial thermal emission to space (dark regions in the infra-red image) and high surface reflection from the desert surface (bright in the visible image). The brightest clouds in the thermal image correspond with (1) a trailing cold front extending from the coast of Norway, across Scotland and to the west of Ireland, (2) a developing low pressure system to the west of Iceland, and, (3) a low pressure system in the Mediterranean centred on Sardinia.
These are regions of ascending air with relatively high altitude, low temperature cloud tops which depress the thermal emission to space compared with surrounding regions. These features are also present in the visible image. However, many more cloud structures are also present. There is a prevalence of low altitude cloud over the oceans: this cloud contains large amounts of water droplets which are highly reflective (e.g. Stephens et al., 1978). The imagery captures the complex cellular structure of this cloud (e.g. Jensen et al., 2008) over the region surrounding the Canary Islands. These cloud types are thought to contribute strongly toward uncertainty in climate projections (Bony et al., 2006). While these clouds also strongly attenuate infra-red radiation, their impact on the thermal radiation escaping to space is modest since cloud-top temperatures are not dissimilar to the surface at night and so they do not contribute significantly to the strong natural greenhouse effect of the clear-sky atmosphere.
The altitude and optical thickness of cloud determines the overall radiative impact of cloud, a combination of the warming greenhouse effect and the surface-cooling solar
shading effect. Yet, probably an even stronger influence does not relate to the cloud itself. The time of day and time of year dictate the incident solar radiation and, therefore,
modulates the strength of the short wave reflection: clearly at night the solar influence of cloud is absent.
…
7. Conclusions
Exploiting satellite measurements and combining them with NWP models initialized through assimilation of available observations enables the effect of clouds on the Earth’s radiative energy balance at the surface and within the atmosphere to be quantified for the present day climate. Consistent with previous results (Ramanathan et al., 1989; Su et al., 2010), the cloud radiative cooling effect through reflection of short wave radiation is found
to dominate over the long wave heating effect, resulting in a net cooling of the climate system of −21 Wm−2.
The short wave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of −53 Wm−2 for the global multi-annual mean. The magnitude of this effect is strongly modulated by the incoming solar radiation and the dominance of cloud short wave cooling over long wave greenhouse trapping is maximum around local noon (Nowicki and Merchant, 2004) while the cloud long wave heating effect dominates at night.
The long wave greenhouse effect of cloud measured at the top of the atmosphere is manifest primarily as a heating of the atmosphere in the moist tropics, consistent with calculations by Sohn (1999).
Over the marine stratocumulus regions and across higher latitudes the cloud-base emission to the surface becomes substantial and dominates over the reduced outgoing long wave radiation to space resulting in enhanced radiative cooling of the atmosphere and heating of the surface. The cloud radiative influence on the exchange of radiative fluxes between the atmosphere and the surface are intimately linked with the water cycle through radiativeconvective balance. While tropical, high-altitude clouds act to stabilize the atmospheric profile radiatively, clouds over polar regions tend to cool the atmosphere while heating the surface through enhanced atmospheric longwave radiative emission to the surface. In future work it would be informative to categorize these effects by cloud type further (e.g. Futyan et al., 2005) and compare with climate model simulations. These analyses are vital in constraining cloud feedback processes further and in linking to future changes in the water cycle (Stephens, 2005; Bony et al., 2006; John et al., 2009).
A particular challenge is the accurate quantification of surface radiative fluxes due to the sparse ground-based observing network (Roesch et al., 2011) and also monitoring current changes in cloud radiative effect in satellite data, reanalyses and models (Wielicki et al., 2002); combining meteorological reanalyses with satellite data and surface observations provide a vital methodology for meeting these challenges.
Abstract is here: http://onlinelibrary.wiley.com/doi/10.1002/met.285/abstract
Full paper is here: http://www.met.reading.ac.uk/~sgs02rpa/PAPERS/Allan11MA.pdf
UPDATE: Some people in comments including Dr. Roy Spencer, (and as I was writing this, Dr. Richard Allan) suggest that the paper isn’t about feedback (at least in the eyes of IPCC interpretations, but Spencer adds “it could be”). Thus I’ve removed the word from the headline to satisfy such complaints. My view is that clouds are both a feedback and a forcing. Others disagree. That’s an issue that will occupy us all for sometime I’m sure.
Regarding cloud feedbacks, here’s what I noted in the paper in section 6, near the end. Allan is referring to figure 7 which shows (a) net radiation and (b) net cloud radiative forcing:
Substantial negative anomalies in net radiative flux from ERA Interim are apparent in 1998 and 2010, both El Niño years, suggesting that the substantial re-organization of atmospheric and oceanic circulation systems act to remove energy from Earth during these periods.

You can clearly see the famous double peak in the 1998 El Niño, but it is inverted. To me that looks like a thermostat action, and not one with stuck electrical contacts, i.e. a negative feedback. I’ve also updated the text related to the incorrect comparison I made. – Anthony
Normally, yes. But the issue raised was with a gain > 1.
John B says:
September 21, 2011 at 12:15 am
coaldust says:
September 20, 2011 at 5:20 pm
John B says:
September 20, 2011 at 2:06 pm
Yes, they go up and down – i.e. no trend, only variations. GCRs go up and down, as do other things, so those things can’t explain the trend.
You haven’t addressed my points.
The frequency spectrum of the inputs to a highly nonlinear coupled system is not insignificant. Thus, the rate of change may matter. The rate of change can vary without any trend. The non-linearity of the system means the extremes may matter. Our current understanding of the climate system is not mature enough to know if they matter.
So, what has shown a trend over the last couple of hundred years that might explain temperature rises?
Not CO2.
tallbloke
“The IPCC scientists claim that warming due to increased co2 will cause a positive water vapour feedback. This would cause more cloud and so cooling.
But cloud cover reduced while the planet warmed 1980-1998, so the supposed water vapour feedback to increased co2 is clearly overwhelmed by some other effect QED.”
“Some other effect”? Perhaps the fact that although absolute humidity has gone up over the last 40 years (an extra Lake Erie since 1970, I believe), the relative humidity amount changes with temperature, and the rise in absolute humidity has not kept up with temperature? So the relative humidity is, if anything, dropping along with the cloud cover (which means a positive feedback to temperature from clouds)? (http://en.wikipedia.org/wiki/Absolute_humidity)
It’s worth noting that the absolute humidity (total amount of water vapor in the air) drives the greenhouse effect from H2O, not the relative humidity – so that greenhouse effect is still going up.
This is pretty basic stuff, tallbloke. I sincerely hope that was a simple error on your part, not being disingenuous.
——————
KK,
It is a pleasure to see you participate here in an open, un-manipulated and enlightened venue. (thanks to Anthony for that)
I believe you are very very late to the party about updated observations on the paper’s interpretation in the original WUWT post. Indeed, the author, skeptics and non-skeptics had a civil discourse that quickly picked it up and discussed it.
Don’t you think this the best place for the free spirit of science? Got to love it.
John
sarc on/
PS – KK, on a personal note, I noticed your post is near the bottom of comments. Why did you do that? I think your comment should have been at the top . . . . shame on you. KK, take care of that, would you please? Really, near the bottom violates your integrity by the mere implication of hiding your comment, n’est ce pas? You are ‘entertainment’.
Sarc off/
[snip not interested in your snark “prufrocks” or whoever you are, note the blog policy on changing handles – Anthony]
I was totally serious. No snark. And I hear that RealClimate is the hypersensitive, deleter. Anyway, your post did nothing to diminish your credibility, and I like that fact that you and Steve Goddard are on top of things. Venus is hot because of high surface pressures according to PV=nRT; that totally convinced me. And I never would have known about Steve Goddard were it not for you. I’m a big fan of both of you guys.
Tony: “Oh dear, now we have three peer reviewed papers (Lindzen and Choi, Spencer and Braswell, and now Richard P. Allan) based on observations that show a net negative feedback for clouds, and a strong one at that. What will Trenberth and Dessler do next? Maybe the editor of Meteorological Applications can be persuaded to commit professional suicide and resign?”
What were you saying about snark, Tony? I’m very aware this is the only example from you on your entire blog that even approaches snark, but I’d hate to see it become the beginning of a trend.
son of mulder says:
September 21, 2011 at 3:07 am
“Roy W. Spencer says:
September 20, 2011 at 4:46 am
Now, it might well be that since the average effect of clouds on the climate system in response to radiative heating by the sun is to cool the Earth, then a small increment in radiative heating (e.g. from more CO2) will ALSO result in clouds having a further increment in cooling.”
If the above statement is not true then there would be some point and mechanism between snowball earth and now when the average effect of clouds reached a maximum level of cooling.
What is that point and mechanism? I don’t think there is any theory or evidence for such.
Indeed, what is more important than clouds per se are the mechanisms and dynamics of cloud formation and dissipation and the (Lyapunov) stability of cloud systems.
That cloud albedo causes cooling is not exactly Nobel prize territory.
Ron Cram,
The paper studies cloud forcings–ie., what the net effect of clouds at a particular time is/was.
It does so, in part, to provide information to help constrain feedbacks–ie., how clouds (and thus their forcings) evolve over time in response to other variables–presumably warming, primarily.
The second point is what is discussed in the bits you highlighted. It’s customary for papers to say why it’s worth studying whatever they study–in this case, it’s worth studying cloud forcings so that we may understand cloud feedbacks better in the future.
Steve McIntyre just posted a new article questioning Dessler’s methodology: click
Regarding the strikken out text, comparing -21 W/m2 net TOA radiative effect of clouds and the 1.2 W/m2 surface forcing of a doubling of CO2:
There is a another, and more important reason why these numbers can’t be compared.
Watts correctly conceeds that -21 W/m2 is the (most commonly used) TOA forcing, and the CO2 number is the surface forcing indeed (more commonly for CO2 doubling the TOA forcing of 3.7 or 4 W/m2 is given),
The more important reason why this comparison fails, however, is that the -21 refers to the total effect of all clouds, whereas the 1.2 (or 3.7) does not refer to the total effect of all CO2, but rather to a doubling. Different beasts.
REPLY: Yep, that was a late night blunder. I’m rewriting the entire post while wide awake. I’m still hoping to hear from Dr. Allan reading Figure 7 – Anthony
Much respect to Anthony for correcting the original post!!!
In light of this update, shouldn’t more than just the title be changed? Take the first sentence for example. From what I understand of the comments, shouldn’t this sentence, and several others be changed?
>> “Oh dear, now we have three peer reviewed papers (Lindzen and Choi, Spencer and Braswell, and now Richard P. Allan) based on observations that show a net negative feedback for clouds, and a strong one at that.”
…..and that was bad for Solar panels too….
Oops, sorry. Didn’t see a comment where a re-write is in the works.
Anthony,
Unless the climate boffins have redefined the word “feedback”, which is a fundamental concept in analog electronics, then clouds provide negative feedback without a shadow of a doubt. Solar energy evaporates water from the surface of the ocean, it rises and forms a cloud, the cloud then reduces the amount of solar energy available to evaporate more water. This is the very definition of a negative feedback, no ifs ands or buts about it.
Now this “forcing” thing they just made up. Except for a few paltry milliwatts that leaks up through the crust from the earth’s hot mantle (which, contrary to Gorian legend isn’t millions of degress but it’s still hot enough to melt iron) there IS NO FORCING except sunlight. In electronics we don’t call it forcing but we do call it electro-motive force or more commonly “voltage”. GHGs don’t force anything. They act like a resister and diode in parallel. The diode allows energy to flow in one direction (a “current” in electronics parlance) from the sun to the ocean with essentially zero resistance. When the solar current is shut off (night) current cannot flow backward through the diode but can pass through the resister. Not as easily as passes the other way through the diode however. Absent any GHGs energy would pass through the atmosphere as easily in both directions. Alas, the klimate kiddes have bastardized the language of engineering and called the resistive property of GHGs a “forcing”. What’s really dumb is they still label the energy flow in Watts which is very common measure of electrical flow.
Anyhoo, if you accept their bastardized definition of (forcing) then there’s no doubt that clouds are a forcing agent 24 hours a day. We just need to be clear that anything which resists the current (or causes drop in force across the barrier) is what they call a forcing. In that case clouds have both a negative feedback and a positive forcing. The net of feedback and forcing however is a negative number – less energy gets to the surface with a cloud than without a cloud on a global average basis taking into account all types of clouds. According to the paper in the OP the net negative is some 21 Watts per square meter.
Kevin, thank you for the response.
Kevin McKinney says:
September 21, 2011 at 12:48 pm
Ron Cram,
The paper studies cloud forcings–ie., what the net effect of clouds at a particular time is/was.
The language regarding forcing and feedback are unclear. It is my understanding that a forcing is something which directly acts on the radiative budget such as solar, CO2 and clouds. In this paper, Allen shows clouds during the day increase albedo reducing radiation into the lower atmosphere and surface which causes cooling at the surface. Feedbacks are a response to changes in the climate system from rising temps. Feedbacks can be either positive (causing more warming) or negative (causing cooling). The computer models generally treat clouds as a positive feedback because the models predict an increase in clouds and clouds hold warmth in at night. However, Allan’s paper indicates that the cooling effect of clouds during the day (the forcing) completely dominates the warming caused by clouds at night (the mechanism by which clouds are thought to be a feedback). So then as temps rise and more clouds are formed, cooling from the clouds during the day will completely swamp any extra warming at night (the feedback mechanism).
I understand Allan is not attempting to quantify the cloud feedback, but it seems clear to me that his paper states the cloud forcing is linked to feedback. How could it not be? If the clouds are reflecting solar rays to outer space, then there is less heat for clouds to hold in at night. And if clouds increase due to warmer temps, then increased clouds look to be a negative feedback.
Dave Springer:
September 21, 2011 at 7:00 pm
I do like the electronic resistor/diode analog! It seems to reduce the complexity to it’s simplest form. How far down the various electrical mathematical formula can you carry it? Curious is all as to what relational perspectives may pop. GK
Sorry my above comment should have been addressed to:
Dave Springer:
September 21, 2011 at 7:00 pm
Kev-in-Uk.
My point is very simple.
In order to turn a sensor reading into a data product there are a series of algorithms applying.
I’ll give you a simple example. SST. person X see a data product from a satillite. That product is SST, the sea surface temperature. They like that data product. They use that data product to make arguments. I am saying that they must also accept the algorithms used to make that data product. You cannot accept the data product and reject the algorithms used to produce it. so you will find people who use satillite data ( clouds, SST, you name it ) without realizing that those data products are actually the output of a model. raw sensor output is run through algorithms to create data products. So, you wantt o use the data product in an argument? you “own” the physical models used to create it. You use your cell phone? then you tacitly accept the physical laws used to design it. whether you acknowledge that or not in some way you rely on that physics being true.
That physics happens to be RTE.
“”””” EJT says:
September 21, 2011 at 4:15 am
George,
Build an electronic circuit and try it. Assuming some lagg. It’ll be underdamped. Overshoot on the way down. Overshoot even more on the way up, etc. Untill the oscillation amplitude is reaches a saturation. “””””
Well EJT, as they say, if you have been building feedback (negative) amplifiers , off and on, for longer than the last 55 years; then you probably know more about it than I do. Of course, back in those days we did it with valves and such; but when I do it today, it is most often done with some Analog CMOS process or other, often starting right down to the “bare metal” as they put it when you need to design your own diffusion layers (or ion implants.)
I’ve even built a few positive feedback amplifiers; with extremely accurate gains of +1. And yes the do oscillate, and at a very precise frequency, since they used highly stable mechanical resonators to derive the feedback signal.
But I’m quite happy to accept your confession, that your negative feedback amplifiers oscillate. A different line of work, might suit your skills better.
Steven Mosher says:
September 21, 2011 at 9:21 pm
I guessed that was your point – you were trying to say that models are good, again?
I think you are stretching it a bit far though. The physics model used for everyday objects, and simple measurements is usually straightforward. RTE’s are well described and used, of course – and it is based on a ‘model’. The trouble is that this model is ‘simple’ – certainly when compared to GCM’s, for example – and (and this is the most important point) – as a simple model, can be easily the radiative transfers can be readily ‘observed’ to confirm the model is correct/working!
I’d suggest that applying RTE’s to the climate, and in particular radiative transfer of CO2 molecules, etc is massively more complex and difficult to match to standard EM energy for example. (My physics is old and rusty, so outside my knowledge to be fair – so I defer to others to demonstrate this either way).
I do accept your point that models are useful – but I do not accept that the climate system is a readily ‘modelable’ system – and certainly not based on our current knowledge/understanding.
@george and EJT and anyone following the electronics analogy.
Feedback is called feedback because it feeds back from an output to an input, and usually it is the same input that is giving rise to the output to add to it (+ve) or subtract from it (-ve). The gain of any amplifying system is not relevant to the feedback fraction unless that gain is unstable or non-linear. If the feedback fraction is zero then the amplifier behaves as an open loop system. The more negative the feedback fraction, the more it damps the amplifier response. The more positive, the more it will tend to oscillate. With very slight negative feedback, oscillation is possible is response to small transients (from wherever) but the ringing response dies out with time, depending on the feedback fraction.
What could be interesting in the discussion is how the feedback fraction can be frequency dependent so that at one frequency the damping is heavy and at another there is oscillation and even a resonance, however, in these cases the effect is still positive feedback, not negative.
The simple model of the Earth heat transfer system as a diode and a resitor is a good starting point, but the analogy needs a large charging capacitor to represet the sea. The Resistor could be better represented as three resistors in series where one represents CO2 at night, one represents clouds at night, and one represents the night time atmosphere when free of either clouds or CO2. Which resistor would be the largest?
Anyone good at modelling?
🙂
Dave Springer says:
September 21, 2011 at 7:00 pm
I totally agree with your comment. They seem to have deliberately coined the term forcing to reflect some kind of ‘new’ energy introduction to the system – which of course, is absolute tosh. In reality, any chopping and changing of the energy ‘whizzing’ about still relies on the net incoming vs the net outgoing radiation. A temporal delay in outgoing radiation (commonly called the GHG effect) is not via the introduction of new energy! (and I have heard the man made energy argument too – but it’s still peanuts compared to the constant incoming solar!).
As for clouds – of course they must be net negative feedback items – or ‘reflector/shields’ if you prefer – it is common sense. The warmist arguments that they keep us warm at night (whilst true) are not presented properly in order to hide the fact that during the day their albedo has a much more pronounced effect – so whilst clouds do ‘both’ – the negative/cooling effect is significantly larger than the positive/warming effect. I really do think the IPCC cronies have deliberately misdiagnosed the cloud issue to keep the falsification of serious AGW going.
Stephen Mosher,
I’ve noticed that you are defending the use of models in climate ‘science’ through examples of models being used to create real world data, which is fine.
However,is there not a difference with a model using real world observation to create real world data and a model used to create future world data where the model is filled with assumptions?
My problem with climate models as science is that they require the assumption that climate science is sufficiently competent to input all variable within the climate system. It is this assumption that defeats climate models as science.
To use an accounting analogy. A balance sheet might fail to balance by a small sum. This small imbalance could be the result of many large/small assets and many large/small liabilities being omitted from the balance sheet (climate system). You could further complicate matters when you understand that the value of the missing assets/liabilities (forcings/feedbacks) change over time.
Climate models as projections of future climate is not science because it presumes we have more knowledge than we actually do.
Paul
.