The feedbacks in these posts are defined from the top-of-the-atmosphere (TOA) perspective. A positive feedback increases the net absorption of radiation by the planet when the global average temperature increases (i.e., the increase in absorbed solar radiation is greater than the increase in outgoing longwave emission). In the case of water vapor, for example, the outgoing longwave radiation (W/m^2) _de_creases with temperature (K), so it’s a positive feedback.
Evaporation and precipitation don’t directly affect the TOA energy budget. They merely redistribute energy within a column (and horizontally if the evaporation and precipitation occur in different locations). Of course, this could alter the temperature, water vapor, surface albedo, and cloud structure. Thus, the TOA effects of changes in evaporation and precipitation are indirectly included in the other feedback terms.
Evap and precip are extremely important for the surface energy budget, but that a whole other post.
Buck Smith (#1): Just to expand a little bit on what Karen Shell said in response to your statement, I think the zeroth-order response to a radiative forcing, such as an increase in CO2 levels, assumes that the energy flows between the surface and the free troposphere adjust in such a way that the lapse rate in the troposphere remains unchanged.
The “lapse rate feedback” then accounts for the fact that the lapse rate is actually expected to decrease somewhat with increasing temperature. (This is because in the tropics the lapse rate closely follows the moist adiabatic lapse rate, the magnitude of which is a decreasing function of the surface temperature. In the polar regions, I think things are expected to go the other way…i.e., the lapse rate is expected to increase…but on the global scale, the net effect is still a decrease in the lapse rate, although smaller in magnitude than in the tropics alone.)
So, to the extent that evaporation and precipitation end up changing the temperature structure of the troposphere, it should show up in the lapse rate feedback.
Finally, it is hard to overstate the importance of adopting a top-of-the-atmosphere (TOA) energy balance perspective. Over at “skeptic” blogs, much of their confusion about various subjects can be traced to their not understanding things from a TOA perspective and trying to figure out what is happening considering the surface energy balance, which is generally much more difficult to do.
Joel #5. But if you don’t know the magnitude of evaporation effect on lapse rate how can one expect to accurately model TOA fluxes, let alone surface temps? Evaporation/Precipitation is not affected by CO2 levels. If Evaporation/Precipitation is increasing it will “short-circuit” CO2 warming, right?
I have been looking for an interactive site with GCMs where once can plot projections of many paramters, Evaporation/Precipitation being one of them. My assumption is the model show Evaporation/Precipitation pretty much flat. This because a 5% increase in the 80 W/m^2 number in the Trenberth diagram of energy fluxes would completely conteract the total forecasted effect for CO2 doubling including positive feedbacks.
[Response: there is model output of this sort on the GISS website (look at datasets/modelE simulations etc). But you will find that your assumptions are wrong – evap and precip increase at roughly 2% per degree C warming. Your confusion is in associating changes in the surface energy budget with the TOA radiative forcing. The former are generally substantially larger than the latter because of the water vapor and other feedbacks. – gavin]
In the correlation diagram shown above, the vertical bars are intended to be the means of the observations in the dry and moist zones. The models are clustered around the moist mean rather nicely but seem to be way off (and way moister) than the mean of the dry zone observations.
1. Am I reading this correctly?
2. Given that much of the planetary cooling occurs in dry atmospheres, does this mean that the models are missing an important cooling feedback?
Or is my premise in the second question even correct?
Actually CO2 does impact precipitation independently of changes in temperature, (generally precipitation goes down at higher greenhouse levels in a fixed SST run) since it impacts the atmospheric energy budget, of which radiative cooling is a critical ingredient. But in fact one could concoct different forcing agents which increase the tropospheric temperature but also change the stability in such a way that temperature and column vapor goes up, but evaporation/precipitation goes down. These latter terms are constrained by energetics rather than Clausius Clapeyron.
As mentioned before though, evaporation more or less sets the temperature difference between the ground and lower atmosphere, not the absolute SST
“Thus, Fasullo and Trenberth conclude that the relative humidity observations are most consistent with higher climate sensitivities (around 4°C for a doubling of CO2).“
That’s fine, but are fast feedback climate sensitivities of 4°C for a doubling of CO2 consistent with real-world observations? What I mean is: Presumably it’s possible to have a model in which relative humidity matches real-world observations well, even though the climate sensitivity inherent in that model is actually higher than in the real world, because *something else* in the model is wrong. My understanding is that the best (most reliable) figures for climate sensitivity are derived from palaeoclimate data because that by definition includes all the physics that actually takes place in the climate system. So, if your model does well at RH but its climate sensitivity is 4°C and palaeoclimate data tells us that it’s actually closer to 3°C, isn’t it a bit misleading to imply that the models tell us it’s 4°C? I remember reading articles here which say that a fast feedback climate sensitivity of 3°C is most consistent with the modern instrumental temperature record as well.
New paper by James Hansen et al in review at Phil Trans Roy Soc:
Climate sensitivity, sea level, and atmospheric CO2
Cenozoic temperature, sea level and CO2 co-variations provide insights into climate sensitivity to external forcings and sea level sensitivity to climate change. Pleistocene climate oscillations imply a fast-feedback climate sensitivity 3 ± 1°C for 4 W/m2 CO2 forcing for the average of climate states between the Holocene and Last Glacial Maximum (LGM), the error estimate being large and partly subjective because of continuing uncertainty about LGM global surface climate. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify total Earth system sensitivity. Ice sheet response time is poorly defined, but we suggest that hysteresis and slow response in current ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state-dependence of climate sensitivity, finding a strong increase in sensitivity when global temperature reaches early Cenozoic and higher levels, as increased water vapor eliminates the tropopause. It follows that burning all fossil fuels would create a different planet, one on which humans would find it difficult to survive.
wili: Yes. If I’ve understood them correctly, Hansen’s papers argue for:
Fast feedback climate sensitivity of 0.75 ± 0.125°C/W/m² (3 ± 0.5°C per doubling);
Climate sensitivity including slow albedo feedback of 1.5°C/W/m² (6°C per doubling);
Climate sensitivity including slow albedo feedback & non-CO2 GHGs of 2°C/W/m² (8°C per doubling);
Climate sensitivity including all feedbacks between Holocene & ice-free state of ~2.4°C/W/m² (9.5°C per doubling) – although the ice albedo feedback would be ‘played out’ when the ice sheets disappear so this is a bit hypothetical.
(Hansen & Sato 2011)
Of course this does depend on estimates of global temperature change being correct.
In this new submitted paper Hansen seems to argue for about 4 degrees fast-feedback climate sensitivity in the current state, and about 6-8 degrees for earth system sensivity, although he doesn’t seem very clear on this, but maybe that’s my lack of understanding.
Comment by Lennart van der Linde — 5 Jan 2013 @ 5:39 PM
Karen Shell says:
4 Jan 2013 at 10:19 AM
“Evap and precip are extremely important for the surface energy budget, but that a whole other post”
If Evaporation/Precipitation is increasing it will “short-circuit” CO2 warming, right?
No…The only way this could happen is if the effect of this was to decrease the lapse rate much more than is expected, for example, to have an even stronger tropical tropospheric amplification (sometimes called the “hot spot” in the tropical troposphere in “skeptic” circles). There is no reason I know of to believe this would happen…And, as you may be aware, “skeptics” like to claim that the expected amplification as you go up in the tropical troposphere is occurring less, not more, than predicted. (In reality, the data is not really good enough to determine if there is a discrepancy with the models or not, but it would certainly be quite novel to suggest that the data is so bad that the amplification is actually much more pronounced than what the models predict!)
Again, I think this notion of evaporation/precipitation short-circuiting the warming, quite popular in “skeptic” circles, stems from trying to figure things out from a surface energy balance perspective and not a TOA perspective. Using the latter, it is much easier to understand why this notion does not make much sense…and certainly does not have any empirical support.
Icarus62@11: Regarding the 6°C, 8°C and 9.5° per doubling figures in your post, I can’t seem to locate them in any of the 2011/2012 Hansen et al. papers I have access to. Which paper exactly are you referring to? They write long papers, so I might have just overlooked it, but I also tried searching on related terms with no luck. The papers I searched are as follows:
shouldn’t there be some sort of correlation between cloud types vs. relative humidity (RH) and subsidence/ascendance of the air mass? of course the turbulence mixes thing up somewhat creating vertical clouds but does it affect the broader distribution of RH and air pressure too? high cumuliform clouds are somewhat an exception in the grand scheme of things (no such things in f.e. other planets), and maybe just a special case of water(H2O) clouds so are they so important to get correct? of course they are important in estimating extreme events but they are local clouds (though much more common in some land areas than others) and producing just local disasters, so it might not be too bad to leave them out all together on some projections if they’re taking too much of the computing time?
perhaps i’m using wrong terms here. does the air pressure drop in the cloud when it starts to rain and increase the pressure below the cloud. for sure te droplets evaporate somewhat during their fall? yes i’ve heard of the rain in saudi arabia with RH of 15% but surely this is not the level in the cloud? anyway just throwing out some questions that have come to mind reading about diffiulties with clouds.
ReCaptcha states ructsca, i don’t now what to make of it.
Lurker alert! You almost certainly won’t remember me from some time back when I was a somewhat sceptical lurker who briefly uncloaked himself on the subject of Arctic ice. After a sound thrashing in these forums and after a lot of reading later, I would now consider myself much more convinced lurker. I now have a pretty good understanding of the Greenhouse effect and TOA energy budgets etc, and fully understand that if the energy cannot escape as quickly as it did in the past, when CO2 was lower, that this will cause a rise in temperature. I also understand the effect of the various positive feedbacks, whereby a rise in temperature can cause a further rise in temperature without further external forcing. However my last remaining significant doubt is clouds.
I struggled with this post and just about understand the principle of the method used, but I still think there is no substitute for observation. To me it seems “common sense” (yeah, I know, it was once “common sense” that the world was flat!) that if the earth warms up that means more evaporation and water vapour and that in turn means more clouds. A cloudier world has a higher albedo and therefore less solar energy gets in, and so there is less to get trapped and raise temperatures. I understand the different effects of high and low cloud.
I have read that some sceptics call this the Earth’s “thermostat”, and it is a very appealing and logical sounding hypothesis. To me, the importance of this is highlighted by the fact that the largest sea surface temperature fluctation on Earth, ENSO, is driven by the presence or absence of the clouds associated with the trade winds around the Equator in the Pacific.
To me, the only way of falsifying or proving such a hypothesis is to observe the extent and types of clouds and how they correlate with temperature. Are there really no satellites existing, or planned, that can measure clouds (or albedo as a proxy)? If there are I would be very interested to follow any links.
On a side note, all the global warming positive feedbacks make very logical sense to me (such as ice / snow albedo decrease, permafrost methane release etc) except the idea that clouds are a positive feedback. I understand that clouds trap heat at night, but in the warm seas around the equator where most of the solar forcing happens, clouds bubble up during the day and fade away at night.
buck smith (#17): Yes, we are interested in the surface temperature response…but the easier way to determine this is by looking at the TOA energy budget and then using the lapse rate to get the surface temperature. The harder way to do this is to try to work out the surface energy budget.
It is not a matter of the surface energy balance being wrong in the model; it is a matter of people like you getting hopelessly confused because you are stuck in a point-of-view that is not the most useful point-of-view to understand what is actually going on. Your questions in this thread make it clear that your understanding is being hampered by this confusion.
Matthew wrote @19: “if the earth warms up that means more evaporation and water vapour and that in turn means more clouds”
Does it mean more clouds? While warmer surface temps do mean more evaporation, a warmer atmosphere is able to hold more water vapour before cloud formation. That means relative humidity can remain the same even as specific humidity rises.
But even if more clouds do form, they have to stick around to provide a forcing, either positive or negative, not dump their moisture in increased precipitation. But that’s exactly what we’ve seen recently: more intense precipitation events. So much so that the amount of water dumped on land temporarily slowed the rise in sea level. Clearly it is not quite as logical and common sense as it appears.
The key point is that cloud cover is not determined by the mean moisture content of the air; instead, clouds only form in saturated air, and so they are sensitive to the extreme tail on a probability distribution of the water vapor content. So it’s not inevitable that a moister world has more clouds.
The situation is even more complex than that, because even if you know cloud cover is going up, the net impact of clouds depends on the vertical profile of cloud cover and the competition between the greenhouse effect and albedo. Most if not all models simulate an “upward shift” in the general circulation and in the heights of the cloud tops (which generally strengthens the greenhouse effect). More sensitive models are generally sensitive because they dissipate low clouds. What’s more, the albedo of clouds is a strong function of droplet size; for the same water content, the albedo increases strongly for a cloud composed of smaller (say 10 micron) droplets and decreases for larger (say 50 micron droplets) and also depends on whether the cloud is liquid or ice. So there is no easy common sense answer to the magnitude or even sign of the feedback.
Thanks Chris and Jim, obviously a very complex subject.
Clearly it is not quite as logical and common sense as it appears.
Clearly not, but I suspected as much! One thing looking into climate change has taught me is how un-amenable science is to “common sense”, the extreme case in point being being quantum mechanics, but I digress.
Does the paleantological record would show up a relationship between rainfall, cloud and temperature?
Are there any direct proxies to cloud cover?
Would it be fair to say that a cloudier world has a higher rainfall?
If that is the case then is the reverse also true, that a world with more rain is a cloudier world?
What was it like when the world was colder than now? More or less rain?
Obiously difficult to tell what was happening over the sea but a “wetter” world will have more vegetation and fewer and less extensive deserts on land. Is the world “greener” when it is warmer?
From this it appears that during the ice ages, when the tropics were relatively cold, Earth’s deserts were more extensive and the tropical rain forests were smaller and more constrained into small areas near the equator. There was also less “temperate” climate area as the higher lattitudes were swallowed under the ice sheets or low temperature precluded plant growth. Similarly when the Earth has been warm forests and vegetation generally have been more extensive and intensive, that is denser vegetation and a larger proportion of the land areas were “green”.
This would suggest from the long term climate records that a warmer world has more precipitation, and presumably there cannot be more precipitation without more clouds. From that I would hypothesise that a warmer world has more extensive and intensive rainfall and therefore would necessarily have more cloud cover and a higher “cloud albedo” (although of course a lower “ice albedo”). The hypothesis would therefore be that the paleontological record suggests that as temperature increases cloud albedo increases and acts as a negative feedback to a warmer climate.
How would one go about testing / falsifying that hypothesis?
Obviously that is not the whole story (as Jim discusses clouds trap energy as well), however if the energy bounces straight back out to space before it can enter the system there is less energy to trap, so that is necessarily a secondary positive feedback that is dependent on the extent of the primary negative feedback (albedo).
Presumably I am not the first person to consider this and people have done research but I am not sure where to look.
So there is no easy common sense answer to the magnitude or even sign of the feedback.
Are you saying that it is not certain what the cloud feedback sign is?
As clouds are probably the fastest acting and most extensive feedback mechanism in the climate system surely that has major implications for climate models?
How sensitive are models to a negative cloud feedback and what does the long term projection of temperatures look like if one assumes the sign is negative?
Lots of questions, sorry about that! Not expecting to get all the answers here, but would appreciate a pointer to a good source of information.
I have a question. Since an increase in water vapor with a warmer planet would mean the potential for more clouds, wouldn’t you need a somewhat proportional increase in condensation nuclei to form the extra clouds? Or is it just a given there will be enough dirt floating around in the atmosphere to do the job?
I am fairly confident that the longwave (greenhouse) component of the cloud feedback is positive. Dennis Hartmann has some good work on the mechanisms involved which seem robust across the CMIP3 and (I think) CMIP5 models. Most of the spread in cloud feedback estimates (and climate sensitivity) seems to stem from low cloud feedbacks, which primarily affect the planetary albedo. So if you argue that cloud feedback is negative, then by implication, you’d probably need to argue that climate sensitivity is on the low end of the IPCC estimates.
The challenge is that the greenhouse effect of clouds is heating the planet by something like 30 W/m2 and the albedo impact of clouds is cooling the planet by about 50 W/m2 in the climatological mean. This means that clouds are cooling the planet by about -20 W/m2. If cloud feedback is positive that number might go down to -19 W/m2, etc, so you’re looking for a small residual amongst two very large and competing terms.
You need to be careful talking about precipitation/evaporation changes or their relationship to water vapor or cloud feedback. The nature of precipitation events (or the spatial distribution of the precipitation field) can be altered even for a small change in global mean precipitation or cloud cover (e.g., by having fewer but more intense precipitation events). The most intense events actually depend more on the Clausius-Clapeyron relation, while the global mean change in precipitation goes up much less rapidly than the column water vapor. But suppose for example that one put a bunch of absorbing aerosols (e.g., black carbon) in the high atmosphere, such that the albedo went down and a higher fraction of incident solar energy was absorbed in the free troposphere. In this case, it would be possible to warm the troposphere (and thus accumulate more water before condensation occurred) while simultaneously reducing the energy available for evaporation, and making the air more stable to convection (reducing precipitation). So you need to be careful when linking the different aspects of the hydrological cycle.
Condensation nuclei isn’t limiting; Earth’s atmosphere simply can’t sustain relative humidities much beyond 100%. Of course, aerosols are also changing during the same time that we’re monitoring clouds, so any component of cloud change may be due to the background aerosol content (indirect effect) rather than a temperature feedback. Internal variability is also significant over the satellite era. What’s more, part of the cloud “feedback” may be forcing dependent even for the same temperature change.
But as I mentioned before, even within a cloud, changed microphysical components (e.g., the transition from ice to liquid droplets in a warming climate) can impact the albedo.
Just so I am clear what you are saying, if the overall effect of clouds is to cool by -20Wm2 then in order for cloud feedback to be positive there would need to be one of two mechanisms:
1. less cloud cover as the temperature rises, and more cloud cover as it falls. This does not seem to tally with the science or the Paleo record.
2. the “net” cooling of clouds reduces in some way, from a rise in the greenhouse effect and/or a fall in the albedo effect.
Playing with numbers here, no idea of the real values:
Let us say a rise of global temperature of 2C produces a 5% increase in global cloud cover. In order for there to be no negative feedback from the extra clouds the net cooling effect of all cloud would have to reduce to -19Wm2. In order for the feedback to be positive then the change in negative feedback would need to be even greater than that. In other words the reduction in the cooling effect of clouds would need to more than offset than cooling effect of an increase in cloud cover.
And on top of that there is the complex relationship between cloud cover and ocean heat uptake, as demonstrated by ENSO. I can see why the modellers have difficulties with clouds!
Is there still no satellite data on cloud cover, or is it just that the records are just too short? That at least would pin down one of the variables in this complex equation.
Thanks for the explanation. I will Google Dennis Hartmann…
I’m not sure that deciding between a sensitivity of 3 C or 4 C per doubling is the strength of this work. What it seems to do is rule out low sensitivity models such as 1 C per doubling. Excluding the lower range makes clear that we face rather dire consequences as a result of currently increasing emissions. It is the reduced uncertainty, rather than the new central estimate that is most helpful.
I have not been here for a while. I liked the interchange between Matthew L. and Chris Colose.
Real reason for coming today: what is the best current book on the actual measured transfers of heat throughout the climate system? I have books by Pierrehumbert, Marcel Leroux, and James Holton.
Comment by Matthew R Marler — 10 Jan 2013 @ 4:46 PM
17 Buck S pondered, ” Regarding TOA versus surface – the surface is what we are trying to predict! EVen if TOA is correct, if the surface energy balance is wrong the model is no good.”
If you wanted to know the temperature 100 feet (to within a quarter inch) of a lone 100 foot tall tower, would you build a 100 foot wobbly outrigger or climb down, walk 100 feet, and build a second tower?
33 Chris D said, “What it seems to do is rule out low sensitivity models such as 1 C per doubling.”
Yet another nail for a well-nailed coffin. Skeptics should go with 2C. Doubling is 560. Safe is 2C. A fact, a publicly accepted axiom, and an assertion which is currently unslayable combine to make a compelling argument to drive carbon to 560 ppm, especially when the numbers have such numerological appeal.
There’s no paleoclimate proxy that records the vertical structure or optical thickness of cloud cover, so I don’t understand your point of contention #1. If you think the problem is tough with satellites, try solving it with a few ice cores or cave records.
In general, what one aims to do with the paleoclimate record (with respect to sensitivity) is to determine the difference between two different climate states with some information about the forced perturbation and concomitant temperature change (e.g., between the LGM and Holocene) rather than to determine the individual feedbacks in isolation. That information can then be used as a “proxy” for future climate change, either directly, or by applying the results of the past climate record in a perturbed or multi-model physics ensemble (e.g., since feedbacks are likely different between various base states).
Because it’s not inevitable that a warmer world has more cloud cover, even simple thought experiments about the feedback don’t work. But I don’t particularly see much use in a variable “total cloud cover” either, since as I mentioned before, clouds influence the radiation budget in different ways as a function of the vertical distribution (I’m not the observationalist to ask, but one issue is that satellites have a tough time detecting low clouds when high clouds overlie them) and also microphysical properties. The sensitivity is also determined by the latitude of the cloud cover. Even for unchanged cloud fraction, a poleward shift in the storm tracks for example, could push cloudiness into areas of less sunlight, such that they have less impact on the planetary albedo.
Chris, re comment #32 point #1 I am commenting on total cloud cover, not the structure, optical properties or greenhouse effect of individual clouds, which is my point #2.
In point #1, where I say it does not appear to be compatible with the paleoclimate record, I am referring to my question and hypothesis in comment #26. In the warm interglacial periods the world has had much more extensive forest cover than during colder glacial periods when it has been much more arid. More forest extent = more extensive rain, more rain extent = more cloud extent.
The alternatives to the above hypothesis are either:
A: as it gets warmer, cloud extent stays the same while at the same time rainfall extent increases. In other words clouds change from non-rain bearing to rain bearing. Or
B: as it gets warmer, rainfall extent does not change at the same time as tropical and temperate high density forests are increasing massively in extent across the globe or
C: I am barking up the wrong tree (pun intended) and that it is just a coincidence that forests increased in extent when temperatures rose.
Would any serious climatologist argue any of those hypotheses? I cannot see how it is possible to have such a massive worldwide increase in the extent of forest cover without there being a similar increase in the extent of rain bearing clouds. Or am I missing something?
I understand that the rain/cloud relationship may not be linear, but there does seem to be a strong positive correlation between global temperature and global cloud extent.
My point in #2 is the one you make about the structure of clouds changing with higher temperatures such that their albedo may fall and greenhouse effect rise.
So, to repeat my final point, positive cloud feedback implies that the change in greenhouse effect and optical properties of clouds is more influential on global mean temperatures than a change in the extent of clouds. I understand that is a very difficult relationship to pin down without a direct measurement of cloud extent. And of course the whole point of the original article!
Dan H. #34
The Climate4You chart highlights the problem of separating feed back from forcing. This is showing the instantaneous relationship at any point in time between cloud cover and temperature. A feedback is a delayed response.
I think what the C4Y chart shows is that it is warmer when there is less cloud (more sunlight “forcing” a warming of the surface). What it does not show is the effect that the higher temperature has on subsequent cloud cover (a feedback), a much more difficult effect to pin down.
Agreed. Much work has been done showing that increases in cloud cover reduce incoming solar radiation, and lead to temperature reductions. Related work on droughts shows that the decreasing cloud cover leads to temperature increases in addition to the drought conditions. The temperature is a feedback of the drought, not a forcing.
What effect increases in temperature have on subsequent cloud cover is much less understood. Increases in water vapor associated with temperature increases are well known. Intuitively, increased humidity should lead to increased cloud cover. However, that is not necessarily the case, and the warm air can hold more water (as mentioned previously).
Studies in the tropics show that temperature increases lead to significant evaporation, cloud formation, and precipitation. The precipitation occurring late in the day is followed by cooling (aided by nightfall), and a reduction in cloud cover. This natural thermostat is one of the regions that studies in the tropics are poor proxies for global temperature changes. Expanding this process to the midlatitudes or polar regions has been difficult to ascertain. Was the reduced cloud cover observed in the late 90s a forcing or feedback?
Your forest increase in relation to temperature increases can also be observed in the reduction in desert area with similar temperature increases.
Matthew- I can’t agree that forest cover is a useful indicator of cloud coverage (but any relationship works the other way too, replacing a desert with an Amazon forest would have large changes on the local and global hydrologic cycle)…
In any case, the radiative forcing structure was much different between the last interglacial and projected CO2 rise.
“With little moisture in the soil to evaporate and dissipate some of the sun’s energy, more solar radiation is converted to sensible heat.”
“It is more plausible that evaporation actually decreases during drought because of less precipitation, and that drought drives increases in temperatures because there is less evaporative cooling and thus a higher sensible heat flux warming the air. Short-term temperature anomalies are likely to be a response to drought.”
“short term temperature anomalies”
You toss out two quotes followed by three cites
— but where did you get your quotes? Your first quote Your second quote
and then you cite the <a href="PDSI paper you brought up earlier.
Notice the pattern? Those aren’t about this topic: climate sensitivity.
Your Nasa News link is about attribution of individual short term anomalies — quoting John Christy on a heat wave event.
The quotes were directly from the citations. Read the links, and you can find the quotes, there is no need to perform a google search, when all the information is readily at hand.
Are you in agreement with the rest of us that drought is the precursor to the heat wave, and not vice versa? This is all related to cloudiness, which is suppressed during droughts. Clouds are still the largest uncertainty in determining climate sensitivity.
Suppose the land masses were infested with something akin to Maxwell’s daemons, possessed of a capacity to actively monitor CO2 and alter the requirement for moisture underlying our conventional notions of that required to sustain “forest areas”? Plant life possesses evolved genetic machinery to strike the trade between water-loss and carbon-capture which antedates the (depressed) Pleistocene norms. Stomata.
I can recall a sense of astonishment in learning some fifteen years ago, that stomatal area constriction in grasses employing the C4 path, ran in the tens of percent, in response to contemporary carbon loadings over pre-industrial. Sage & Monson (1999) assess the relative efficiency of C4 to C3 grasses, per molecule of CO2 fixation, at 277 water molecules lost, vs. 833, and the C4 plants are now thought to account for nearly a third of terrestrial fixation (Osborn & Beerling, 2006).
Most scientists acknowledge that clouds have a dual-acting mechanism; blocking incoming solar radiation, and retaining terrestrial radiation. The general view is that the blockage of incoming radiation is greater, resulting in a net temperature reduction. Also, different cloud types have a larger impact; high, cirrus clouds block less solar and more terrestrial, while low, stratus block more solar and less terrestrial.
The bigger question is, to what effect will global warming affect cloud formation? There is a scientific divide on this. On one side are those who contend that increased temperatures will lead to increased evaporation, and increased cloud formation. On the other side are those who feel the opposite. There appears to be more evidence to support the former side that warming will lead to increased cloudiness, and hence, the negative direction (lower CS). As Kevin says, there are clues, but what is lacking is certainty.
“The Partial Radiative Perturbation (PRP) method, that excludes clear-sky changes from the definition of cloud feedbacks, diagnoses a positive global net cloud feedback in virtually all the models (Colman, 2003a; Soden and Held, 2006). However, the cloud feedback estimates diagnosed from either the change in CRF or the PRP method are well correlated (i.e., their relative ranking is similar), and they exhibit a similar spread among GCMs.”
There’s no doubt that clouds provide a net cooling effect of the planet, but that doesn’t mean they provide a negative feedback. It’s a confusion of the sign of a function with the sign of its derivative…
The assumption has been a (nearly) constant relative humidity (RH) global annual average. Somewhere I glanced at a recent claim of a slight decrease in RH. I would suppose that implies a slight decrease in cloudiness?
Comment by David B. Benson — 23 Jan 2013 @ 5:12 PM
2000 figures make the difference
When the researchers at CICERO and the Norwegian Computing Center applied their model and statistics to analyse temperature readings from the air and ocean for the period ending in 2000, they found that climate sensitivity to a doubling of atmospheric CO2 concentration will most likely be 3.7°C, which is somewhat higher than the IPCC prognosis.
But the researchers were surprised when they entered temperatures and other data from the decade 2000-2010 into the model; climate sensitivity was greatly reduced to a “mere” 1.9°C.
The critical issue is the behavior of the function Rc(Ts) where Rc is the net cloud radiative impact on the planet (R_cloud – R_clear sky, where R is the difference in the net solar radiation and outgoing thermal radiation), and Ts is surface temperature. This function may have interesting structure and even bifurcation points that deviate significantly from linear over a wide range of climate regimes.
The problem here is to understand its behavior over a very small range on the energy-temperature surface that is relevant for modern global warming. For example, I have plotted twodifferent hypothetical functions dictating how clouds impact the net radiation balance of the planet. In both cases, they are acting to cool the current planet at a modern temperature of ~290 K by -20 W/m2. However, in one example, the slope of the curve is locally positive…indicating a tendency for less cooling in a warmer climate (i.e., a positive feedback), and in the other case, the slope is locally negative, indicating a tendency for further cooling (i.e., a negative feedback) in a warming climate.
Some people make the incorrect interpretation that clouds act as a negative feedback in any climate regime that falls underneath the zero point (dashed red line). I just made these functions up randomly, and the real behavior depends on much more than temperature (humidity, wind speed, stability, etc) but it’s at least illustrative. It also points to the problem of using much different climate analogs or linear feedback analysis in climate sensitivity interpretation. This is still an under-explored problem in the subject of climate sensitivity.
“The critical issue is the behavior of the function Rc(Ts) where Rc is the net cloud radiative impact on the planet (R_cloud – R_clear sky, where R is the difference in the net solar radiation and outgoing thermal radiation), and Ts is surface temperature. This function may have interesting structure and even bifurcation points that deviate significantly from linear over a wide range of climate regimes.”
Shouldn’t Rc be a function of, if anything the tropospheric and strato temp ?
Why in the world would you make Rc a function of T surface ? T surface as well as well as rel. humidity, and density of CCN and a host of other things, but why only T surface? I see that surface T might impact on R clear sky, but R_cloud cannot depend only on T surface.
If you insist on graphing Rc against Tsurface, ofcourse you will see bifurcations and other strange animals because there are more gremlins on heaven and earth than are dreamt of in your philosophy.
Yes, cloud behavior depends on those other things. The atmospheric temperature is not independent of the surface temperature, but climate sensitivity is often defined with respect to the surface boundary…even if the radiation flux depends on the vertical integral. Of course, there may very well be two or more solutions for any given Ts in the example plots above, depending on forcing agent or even the history the climate took to get to a particular point (as is the case in Snowball Earth hysteresis diagrams).
There are certainly a lot of theories and lots of complicated math to back them up. However, there are at least three enormous factors that are not known for certain that make ALL of the theories worthless in predictive value.
1. There is no way to predict accurately the la Nina/el Nino warming/cooling effects.
2. There is no way to accurately predict cloud behavior and I have seen many theories that ‘prove’ that clouds are positive feedback and others that ‘prove’ clouds are negative feedback. Both sides admit that cloud effects vary depending on their altitude, density etc.
3. Although most theories now espouse that volcanoes are primarily a negative feedback, NOBODY knows when, where and how powerful the next eruption will be.
If you can predict temperatures, flows and the magnitude of la Nina and el Nino, perhaps you can share that trick with us. As far as I can tell, nobody can even predict if there is one or the other, let alone any of the specifics.
Clouds are even more chaotic a factor. [see above]
If you can foresee volcanic eruptions, get yourself over to Asia, they know there will always be more volcanoes, but not when, where or how big they will be.
After you take care of all those, the most important factor of all – climate sensitivity to a doubling of CO2. Oh sure, there are estimates and ranges, but the exact figure is absolutely necessary in order to make any prediction that are more accurate than blind guesses.
Essentially what we have now is a set of big, complex formulas with several extremely critical factors unknown and unknowable.
Here’s something else to think about. Wall Street has billions and billions of dollars at stake daily depending on predictions based on FAR fewer unknowns, yet they haven’t perfected the calculations necessary to buy at the bottom and sell at the top. They have had a 70+ year head start as well.
The exact figure is probably not absolutely necessary. However, somewhere much closer than our current range of possibilities would be nice. One last piece to add to your uncertainties is how they may change in the future with higher atmospheric concentrations of carbon dioxide.
Doctor Delos, Things look complicated to you because you haven’t bothered to study them for fear that it would spoil your “objectivity”. Absolute knowledge is not essential in any field of science–in fact,it is anathema to it. As to the rest of your post…well let’s just say that you aren’t wowing us with your understanding or finance either.
Your analogy fails because of bounds. The stock market can fall to 0 or go to 10000000000000000, but temperatures are tightly bound to CO2 concentrations. Yep, ENSO can warp things up or down, as can volcanoes, BUT the central tendency as described by CO2 concentrations CAN NOT BE CHANGED. So yep, we get WEATHER, but CLIMATE is determined by CO2 concentrations, as driven by orbital variations and human activities.
[Response: “Cannot” is a pretty strong statement, and almost certainly wrong in detail. Your general points is well taken though.–eric]
“…climate sensitivity to a doubling of CO2. Oh sure, there are estimates and ranges, but the exact figure is absolutely necessary in order to make any prediction that are more accurate than blind guesses.”
Uh, no. There’s a big difference between ‘ranges’ and ‘blind guesses.’