I thought this post on clouds and climate modeling below from Steve McIntyre’s Climate Audit was interesting, because it highlights the dreaded “negative feedbacks” that many climate modelers say don’t exist. Dr. Richard Lindzen highlighted the importance of negative feedback in a recent WUWT post.
One of the comments to the CA article shows the simplicity and obviousness of the existence of negative feedback in one of our most common weather events. Willis Eschenbach writes:
Cloud positive feedback is one of the most foolish and anti-common sense claims of the models.
This is particularly true of cumulus and cumulonimbus, which increase with the temperature during the day, move huge amounts of energy from the surface aloft, reflect huge amounts of energy to space, and fade away and disappear at night.
Spot on Willis, I couldn’t agree more. This is especially well demonstrated in the Inter Tropical Convergence Zone (ITCZ) The ITCZ has been in the news recently because early analysis of the flight path of Air France 447 suggests flying through an intense thunderstorm cell in the ITCZ may have been the fatal mistake. There is a huge amount of energy being transported into the upper atmosphere by these storms.
Here are some diagrams and photographs to help visualize the ITCZ heat transport process. First, here is what the ITCZ looks like from space. Note the bright band of cumulonimbus clouds from left to right.
Here is a pictorial showing a cross section of the ITCZ with a cumulonimbus cloud in the center.
And finally, a 3D pictorial showing ITCZ circulation and heat transport. Note the cloud tops produce a bright albedo, reflecting solar radiation.
And here is the post on Climate Audit
Cloud Super-Parameterization and Low Climate Sensitivity
“Superparameterization” is described by the Climate Process Team on Low-Latitude Cloud Feedbacks on Climate Sensitivity in an online meeting report (Bretherton, 2006) as:
a recently developed form of global modeling in which the parameterized moist physics in each grid column of an AGCM is replaced by a small cloud-resolving model (CRM). It holds the promise of much more realistic simulations of cloud fields associated with moist convection and turbulence.
Clouds have, of course, been the primary source of uncertainty in climate models since the 1970s. Some of the conclusions from cloud parameterization studies are quite startling.
The Climate Process Team on Low-Latitude Cloud Feedbacks on Climate Sensitivity reported that:
The world’s first superparameterization climate sensitivity results show strong negative cloud feedbacks driven by enhancement of boundary layer clouds in a warmer climate.
These strong negative cloud feedbacks resulted in a low climate sensitivity of only 0.41 K/(W m-2), described as being at the “low end” of traditional GCMS (i.e. around 1.5 deg C/doubled CO2.):
The CAM-SP shows strongly negative net cloud feedback in both the tropics and in the extratropics, resulting in a global climate sensitivity of only 0.41 K/(W m-2), at the low end of traditional AGCMs (e.g. Cess et al. 1996), but in accord with an analysis of 30-day SST/SST+2K climatologies from a global aquaplanet CRM run on the Earth Simulator (Miura et al. 2005). The conventional AGCMs differ greatly from each other but all have less negative net cloud forcings and correspondingly larger climate sensitivities than the superparameterization
They analyzed the generation of clouds in a few leading GCMs, finding that a GCM’s mean behavior can “reflect unanticipated and unphysical interactions between its component parameterizations”:
A diagnosis of the CAM3 SCM showed the cloud layer was maintained by a complex cycle with a few hour period in which different moist physics parameterizations take over at different times in ways unintended by their developers. A surprise was the unexpectedly large role of parameterized deep convection parameterization even though the cloud layer does not extend above 800 hPa. This emphasizes that an AGCM is a system whose mean behavior can reflect unanticipated and unphysical interactions between its component parameterizations.
Wyant et al (GRL 2006) reported some of these findings. Its abstract stated:
The model has weaker climate sensitivity than most GCMs, but comparable climate sensitivity to recent aqua-planet simulations of a global cloud-resolving model. The weak sensitivity is primarily due to an increase in low cloud fraction and liquid water in tropical regions of moderate subsidence as well as substantial increases in high-latitude cloud fraction.
They report the low end sensitivities noted in the workshop as follows:
We have performed similar +2 K perturbation experiments with CAM 3.0 with a semi-Lagrangian dynamical core, CAM 3.0 with an Eulerian dynamical core, and with the GFDL AM2.12b. These have λ’s of 0.41, 0.54, and 0.65 respectively; SP-CAM is about as sensitive or less sensitive than these GCMs. In fact, SPCAM has only slightly higher climate sensitivity than the least sensitive of the models presented in C89 (The C89 values are based on July simulations)…
The global annual mean changes in shortwave cloud forcing (SWCF) and longwave cloud forcing (LWCF) and net cloud forcing for SP-CAM are _1.94 W m_2, 0.17 W m_2, and _1.77 W m_2, respectively. The negative change in net cloud forcing increases G and makes λ smaller than it would be in the absence of cloud changes.
Wyant et al (GRL 2006) is not cited in IPCC AR4 chapter 8, though a companion study (Wyant et al Clim Dyn 2006) is, but only in the most general terms, no mention being made of low sensitivity being associated with superparameterization:
Recent analyses suggest that the response of boundary-layer clouds constitutes the largest contributor to the range of climate change cloud feedbacks among current GCMs (Bony and Dufresne, 2005; Webb et al., 2006; Wyant et al., 2006). It is due both to large discrepancies in the radiative response simulated by models in regions dominated by lowlevel cloud cover (Figure 8.15), and to the large areas of the globe covered by these regions…
the evaluation of simulated cloud fi elds is increasingly done in terms of cloud types and cloud optical properties (Klein and Jakob, 1999; Webb et al., 2001; Williams et al., 2003; Lin and Zhang, 2004; Weare, 2004; Zhang et al., 2005; Wyant et al., 2006).
(Bretherton 2006)
Dessler et al (GRL 2008) made no mention of strong negative cloud feedbacks under superparamterization, stating that sensitivity is “virtually guaranteed” to be at least several degrees C, unless “a strong, negative, and currently unknown feedback is discovered somewhere in our climate system”:
The existence of a strong and positive water-vapor feedback means that projected business-as-usual greenhouse gas emissions over the next century are virtually guaranteed to produce warming of several degrees Celsius. The only way that will not happen is if a strong, negative, and currently unknown feedback is discovered somewhere in our climate system.
There are a limited number of possibilities for such a possibility, but it is interesting that cloud super-parameterizations indicate a strong negative cloud feedback (contra the standard Soden and Held results.)
This is not an area that I’ve studied at length and I do have no personal views or opinions on the matters discussed in this thread.
References:
Bretherton, C.S., 2006. Low-Latitude Cloud Feedbacks on Climate Sensitivity. Available at: www.usclivar.org/Newsletter/VariationsV4N1/BrethertonCPT.pdf [Accessed June 12, 2009].
Wyant, M.C., Khairoutdinov, M. & Bretherton, C.S., 2006. Climate sensitivity and cloud response of a GCM with a superparameterization. Geophys. Res. Lett, 33, L06714. eos.atmos.washington.edu/pub/breth/papers/2006/SPGRL.pdf
Bretherton, C.S., 2006. Low-Latitude Cloud Feedbacks on Climate Sensitivity. Available at: www.usclivar.org/Newsletter/VariationsV4N1/BrethertonCPT.pdf [Accessed June 12, 2009].
Wyant, M.C., Khairoutdinov, M. & Bretherton, C.S., 2006. Climate sensitivity and cloud response of a GCM with a superparameterization. Geophys. Res. Lett, 33, L06714.
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As I commented on a couple of occasions before, large thunderstorms are incredible heat pumps that move vast amounts of heat energy to high altitude in a matter of minutes to easily be radiated away at the tropopause, while simultaneously creating a huge shroud of brilliant white cloud to shade the lower atmosphere and ground, along with the cooling effect of evaporation cooled air and rain.
As a storm chaser you witness the cooling power of these storms repeatedly, sitting for hours in a hot car in sweltering heat only to have the entire region cooled by 20-30 deg F in less than an hour. When strong thunderstorms kick off here on the high plains of Colorado you can have an area 200 miles wide by 400 miles long go from 18% reflection ground exposed to bright sunshine absorbing solar energy with air temps of 85 deg F to the same area in deep shade, at 55 deg F, with cold rain, with a canopy of brilliant white cloud tops at 55,000 to 65,000 ft altitude radiating heat out to space. All this can happen in less than an hour or two.
Larry
Anthony, I think it would be interesting to convert Stephen Wilde (06:17:18) : to a full fledged post and get comments from the community on his theory. To me, it makes more sense than the fully atmospheric focus of most of the papers and topics.
It’s not scientific, but a more convincing picture is one from an airplane, like I saw while flying the other day. The shadow the cloud puts on the ground is impressive.
Great comments about how weather and climate work. To this layman, convection is the big engine for heat transport from surface to space. On micro and macro scale, both vertically (e.g. local cumulus) and horizontally (e.g. Hadley cells). And within this transport cycle, water is a huge carrier of heat. Upward. I just wonder how many gigaJoules it takes out of the energy budget, every day, to get the sun to pop those water molecules loose off the ocean surface and move them upward into air packets that have to overcome gravity and eventually discharge their cargo as rain/snow/hail at great heights. Which not only requires the lifting energy to get the water up there, but releases the latent heat (at altitude) when the vapor condenses out.
Simplistic, I know, but surely that process accounts for a big big part of the budget? And it is a process that has strong negative feedback: the warmer the air gets, the more moisture it can hold, the stronger the vertical temperature gradient, the more (and more quickly) there will be stuff lifted.
Water: the world’s way of sweating.
deepslope (04:29:48) :
Title “Carbon Emissions Linked To Global Warming In Simple Linear Relationship” – and excerpt: “… These findings mean that we can now say: if you emit that tonne of carbon dioxide, it will lead to 0.0000000000015 degrees of global temperature change.
of course, it’s mostly based on modeling…
Such simplistic linearity seems like utter balderdash to me, but I haven’t read the full paper yet. Any insights and comments?
It is. The linear relationship between temperature and CO2 has long since been disproved.
http://www.ecd.bnl.gov/steve/pubs/HeatCapacity.pdf
I find it funny how people can actually think a complex system is so simplistic. It reminds me of the time when I was in school learning physics. To help us learn, everything was ideal. But in the real world, nothing is ideal. It is almost like these people were never taught nothing is ideal.
Annabelle raises an important point. I don’t believe Hansen, Schmidt, Mann or anyone that is under government employ should be allowed to withhold their data or methods. Yes it is their work, but they and their research are funded by the public’s money. These fellows would have only one reason I can think of for not being transparent,…….
The big point of consideration is cloud cover in the tropics, for it is the tropics that get the most insolation. Increased cloud cover in the tropics would begin a process (which would probably take years) in which there would be less warm air being transported poleward. The same would probably hold true for the oceans (but would even take longer). In the end, if this condition persisted, both the oceans and the atmosphere would cool.
Of course, our oceans and atmosphere are more complex, but generally speaking, more cloud cover in the tropics means an obvious negative feedback.
The ice cores and marine sediment cores only have annual-type resolution in the shallower & younger sections. But they do have decadal- and century-scale resolution back many thousands of years.
Dansgaard-Oeschger events (ice cores) and Heinrich/Bond events (marine sediment cores) indicate that large-scale (~1C to 2C) have occured with onsets measured in a few decades. The cause of these cycles is no known. Broecker and others have suggested changes in deep marine ventilation and oceanic circulation. Holger et al (Nature 2005) related the Dansgaard-Oeschger events to a 1,470-year solar cycle. Although their correlation doesn’t explain a causal relationship.
The ~1,500-year cycle would include the Medieval Climate Optimum and Little Ice Age. The amplitude of this cycle is about 2C. The current climate is about 1.5C to 2C warmer than the Little Ice Age.
5C changes are more on the scale of glacial-interglacial cycles.
Anthony,
I have a question.
To summarize Steve’s paper in my own words: the parameter “cloud” within each cell of the model was determined by taking a random draw for cloud cover between minimums and maximums for the cloud characteristics. This parametric approach was replaced by an explicit physics based model of cloud formation (“small cloud-resolving model (CRM)”). If this is correct, then the CRM is on a small enough scale (or high enough fidelity/resolution) that it could be verified through observation. That is, they can observe starting conditions, take measurements over the life cycle of the cloud, from formation (or not, both are necessary for an accurate model) to dissipation. These observations can then be compared to the out put of the CRM. This would establish that the CRM had accurately captured the physical behavior of the system.
Has this work been done?
erlhapp (05:29:37) :
The evidence is that this zone of the upper troposphere heats and cools with the change in stratospheric ozone that goes along with the QBO. As ozone levels increase in the middle stratosphere the upper troposphere is observed to warm.
The QBO is driven from below. As we discussed many times, you have cause and effect reversed.
This article is a great reminder of the importance of water in the air as water vapor, in the oceans as liquid, at the poles as ice and in aerosols as clouds. With the uncertainty that the IPCC knows it has in understanding clouds, it was a reckless overreach to give 90% certainty on anthroprogenic global warming and predict at 2-3C warming by the end of the century. The alarmist climate modeling community reminds me of the CEO from Circuit City (Schoenover??) who knew how to calculate how much money he would save if he layed off the top earning employees of the company. He could not accurately calculate how much that would cost him in turnover of experienced people he retained or in sales (which turned out to be much more than he saved). So he took action based on the numbers he could calculate and within 18 months his company was in Chapter 11 and less than 6 additional months later, Chapter 7 liqudation. I think the alarmist climate modeling community has fallen into the same trap as its easy to look at the radiative budget in a very large system but extremely difficult and complex to look at all the vagueries of the water cycle, particularly clouds and weather, so they simple dismiss what they know they don’t understand well and cannot model easily as not important.
You are correct in your assertion that clouds have both positive and negative effects. Daytime clouds usually keep temps cooler while nighttime clouds during the winter may help trap heat and make the overnight low warmer.
There is a complete lack of transparency in the climate models used by the IPCC, et al, for making their predictions of a run-away greenhouse effect.
Nobody but the modelers themselves know how they simulate cloud feedbacks, but my understanding is most models use clouds as a positive feedback. (See http://www.drroyspencer.com/2009/05/ and other posts at Dr. Roy Spencer’s blog). According to Dr. Spencer, the climate modelers assume warming causes fewer clouds, but in the real world, fewer clouds usually mean for warmer days. In other words, they appear to have cause-and-effect reversed.
We’ll never know until everything involving these models is fully disclosed. Until the modelers release the design notes and other documents, the inputs and the full, working source code, we are just left with accepting their conclusions without knowing how they reached those results.
I wondered lonely as a cloud,
that floats on high o’er vales and hills,
when all at once I heard a shout,
get off the bl@ur momisugly#dy daffodils.
W Wordsworth (original version with raw data)
S 🙂
Does anyone do any computer modeling with this data?
And here again a clear demonstration on the thermoregulatory effect of oceans. I knew the oceans were the drivers of climate since my childhood, when professor Melly taught us that, “without oceans, the Earth would be a furnace or a freezer”.
Why after so many years some guys come with tales about a gas, which is not a primary source of heat and is essential for life, is the main driver of climate and that we must reduce its concentration in the atmosphere, even when we know that it is not toxic, not a pollutant, not more dangerous for life than water?
Generating flawed knowledge against true knowledge, through ignoring the preponderant role of the oceans -the main maker of clouds, on the Earth’s climate is antiscience.
Re the BBC, I overheard a remark today on their ‘Feedback’ programme to the effect that ‘the BBC doesn’t have a point of view – that’s it’s job’. If only that were true!
While this is an improvement, we still have to remember that we are talking about the GCM models. They have been falsely geared to a high sensitivity by assuming that all the warming of the late 20th century was caused by human emissions of greenhouse gases; an assumption that is obviously wrong for many reasons. ‘Adding in’ the negative feedbacks from the improved cloud model will result in a lower sensitivity, but one that is still too high, due to the erroneously high ‘starting’ sensitivity in the models.
I believe that further reductions in the sensitivity will be found when we truly understand the water vapor feedback. From the beginning, it was the only leg the AGW folks had to stand on and they have found little evidence that it exists as they imagined. Cloud physics and the water vapor feedback are intimately tied together. We cannot understand one without the other and these recent studies indicate that the ‘water vapor feedback’ component in the old models is probably as poor as the cloud modeling.
Stephen Wilde has it right. The oceans trump the atmosphere everytime when it comes to augmenting global climate on multidecadal time scales. Those who recognized the importance of ocean cycles successfully predicted the recent lack of warming/global cooling, while the expensive GCMs still haven’t got a clue!
OT – Anthony mentioned in another article:
http://www.naplesnews.com/news/2009/jun/11/guest-commentary-climate-change-reconsidered-reaso/
@Stephen Fisher Wilde (06:17:18) :
“Any ocean surface warming is caused by solar energy previously absorbed working it’s way back to the surface. “
Are you implying then that the ocean surface cools when the ocean surface absorbs energy? You might want to get rid of that word “any” in that sentence because it’s leaving me to wonder what was going on at the surface when the ocean was absorbing energy. [/nitpick]
Stumpy, Dave, and Maximus5: “positive feedbacks” do not imply “runaway climate”. The reason being that radiation away from the earth increases approximately as T^4 (Stefan-Boltzmann law for a black body) – you need a lot of positive feedback to overcome that.
Another way to think about it is infinite series: X + X/2 + X/4 + X/8 + … = 2X. Basically, a given unit of heating might cause additional heating, and that additional heating might cause even more heating – but as long as each increment of additional heating is less than the increment immediately before, then the series will eventually converge.
So looking at historical temperature changes, the question is not “why would the earth have stable temperature if there are positive feedbacks?” but rather “why would the earth’s temperature have changed as much as it has if there are negative feedbacks?” If the climate system really has strong negative feedbacks, it makes it very hard to explain the glacial – interglacial cycle – large ice sheets are one positive feedback mechanism that we don’t have anymore, but calculations suggest that ice sheet retreat alone is not sufficient to explain temperature differences between today and 30,000 years ago. Indeed, it would be very difficult to explain the temperature changes over the last century if there were strong negative cloud feedbacks.
Stephen Wilde:Only huge catastrophic changes capable of altering the temperature of the whole body of the oceans can set a new global equilibrium in the short term
If we imagine a system like a fridge system, what the post is describing it is only the heat exchange, radiator at back of the fridge and the freezer and compression/decompression system, and you complete the fridge by adding the liquid cooling gas (the seas), then and only then, as you point out, we have our “fridge” completed with all its parts.
The old and faithful “water cycle”. Similarity would be closer to reality if we compare this “earth fridge” with those kerosene fridges of the 50’s, where a small candle like burner heated the liquid. (that constant or almost constant TSI which Dr.Svaalgard uses to refer to).
Thanks for the simplicity and for returning us to common sense.
“”” Dessler et al (GRL 2008) made no mention of strong negative cloud feedbacks under superparamterization, stating that sensitivity is “virtually guaranteed” to be at least several degrees C, unless “a strong, negative, and currently unknown feedback is discovered somewhere in our climate system”:
The existence of a strong and positive water-vapor feedback means that projected business-as-usual greenhouse gas emissions over the next century are virtually guaranteed to produce warming of several degrees Celsius. The only way that will not happen is if a strong, negative, and currently unknown feedback is discovered somewhere in our climate system. “””
“”” This emphasizes that an AGCM is a system whose mean behavior can reflect unanticipated and unphysical interactions between its component parameterizations. “””
Do classical climatology courses at modern Universities ever explain to the students, the meaning of the word “gobbledegook”.
Gobbledegook can be found in almost any scientific peer reviewed paper. It is the standard language of scientific paper abstracts; so that is where to look for it.
“”” The conventional AGCMs differ greatly from each other but all have less negative net cloud forcings and correspondingly larger climate sensitivities than the superparameterization “””
Now everybody knows what a “parameter” is; it’s a fancy four syllable word for “variable”. Quite often “parameters” are used in equations, as “dummy” variables, that are actually not a part of the function being described; so they may not even be measurable variables in a real system.
A good example of the use of parameters can be found in the parametric form of the Tchebychev Polynomials, Tn(x). Which are power series polynomials in which every other power term is zero, either all the even powers or all the odd powers.
They can be described in the “Parametric” form :
x = cos(p) ; Tn(x) = cos(np)
Here (p) is a parameter having nothing to do with the Tchebychev polynomials, which have the form:
T0(x) = 1
T1(x) = x
T2(x) = 2x^2 – 1
T3(x) = 4x^3 – 3x etc
T(n+1)(x)=2xTn(x)-T(n-1)(x) is a recursion formula that generates the entire set.
Well the problem is that Tn(x) is defined for all real values of (x) between =/- infinity, and Tn(x) has the same range.
The parametric form is only defined for -1<= x <= 1 since it is bound by the cosine function.
The cognoscenti may recognize that the parametric form of the Tchebychev polynomials describes the Lissajous figures formed with an n:1 vertical to horizontal frequency ratio, when you apply in phase sinusoidal signals to an oscilloscope.
I often think of parameters as being like catalysts that take part in a reaction but aren't a part of the reaction.
So what the blazes any of that has to do with "superparameterization" and clouds is way beyond my pay grade.
The role of clouds in climate, as in temperature control, is something you can do with a stick on the sand of a desert island.
You don't need some megaparameterizationology science to understand what is going on.
More surface temperature warming leads to more evaporation (7% / deg C); more evaporation leads to more atmospheric water vapor (7% / deg C) ; more atmospheric water vapor leads to more clouds; and more clouds leads to more precipitation (7% / deg C), and more clouds leads to more albedo; more albedoe leads to more solar energy reflected back into space; more precpitable clouds leads to more heating of that atmosphere; which leads to more moisture and energy being transported to higher altitude, which leads to more energy loss to space; and more precipitable clouds leads to blocking more solar radiation from reaching the surface, and less solar radiation reaching the surface leads to lower surface temperatures.
In summary, more surface warming leads to more surface cooling; a reasonable definition of NEGATIVE feedback.
So why does this "Climate Process Team" of fatheads, have to make something so simple, into something so complicated; and then make up silly buzz words to describe what they are doing.
They are superparameterizing themsleves into oblivion.
CLOUDS ARE NEGATIVE FEEDBACK; ALWAYS !
High clouds at night are way up there BECAUSE it was hot and steamy during the day; and the hotter it was, the higher those clouds will form when the moist air finally gets to the dew point temperature.
And when it is cooler and dry during the day, it will get even cooler when the sun goes down and there will be no clouds formed.
The temperature causes the clouds NOT the other way round; there is NO positive cloud feedback; it always gets colder when a cloud passes between the sun and the surface (in the shadow zone).
George
PS a nice find there Steve; I guess they want to bamboozle us with BS.
“”” Peter Hearnden (05:14:49) :
“How do they get away with ignoring clouds negative feedback?”
Who is? No one.
Fact is there are both negative and positive cloud feedbacks. The question is which one (if any) predominates if the world warms. “””
So give us a simple Physical explanation of how more cloud cover leads to more surface warming; i.e. positive feedback ?
Just one example will do; unless you know more than one.
George
Seems like there are two situations – daytime and nightime:
In the daytime you have the heat of the sun radiating to the earth together with the heat of the earth reradiating heat outward. It doesn’t seem hard to see that if you insert a cloud barrier between the two you are not only shutting down the direct heat of the sun but you’re also shutting down that process that supplies heat to be re-radiated by the earth.
At night the situation is different; only the earth radiates at night and so the cloud barrier could be said to have a warming tendency. And it is my experience that cloudy winter nights where I live tend to be warmer than bitterly cold clear nights. Please notice though, that saying cloudy nights are warmer is a bit of a misstatement because what is really happening is that you are only slowing down cooling. Climatologically, nights are still cool and days are warm – on balance all that really happens at night is cooling.
Take the above understanding together with my guess is that most clouds are generated during the day. And take from that, that the average day should have more clouds in it than the average night. I have to conclude that any tendency for the earth’s atmosphere to warm inherently carries with it a cooling effect through the increase action of cloud generation. In other words clouds must provide a negative feedback.
H.R. (09:22:18)
Thanks for highlighting that point. It is impossible to achieve perfection in communication of new ideas and any feedback is helpful.
In fact the cooling of ocean surfaces means that more solar energy is being retained and the ocean heat content will increase UNLESS solar input is too low to take advantage of the reduced energy emissions to the air (as at present, I suggest).
Likewise, the warming of ocean surfaces means that less solar energy is being retained and the ocean heat content will decrease UNLESS solar input is so high that it more than replaces the losses (as during the period 1975 to 2000 I suggest).
Note that ocean heat content normally increases when the air cools and vice versa subject only to an overriding contribution from solar input or lack of it.
The word ‘any’ seems to be correct.