Guest Post by Willis Eschenbach
Like anyone else, I’m not fond of being wrong, particularly very publicly wrong. However, that’s the price of science, and sometimes you have to go through being wrong to get to being right. Case in point? My last post. In that post I looked at what is known as “net cloud radiative forcing”, and how it changed with surface temperature. Net cloud forcing is defined as the amount of downwelling upwelling longwave radiation (ULR, or “greenhouse radiation”) produced by the cloud, minus the amount of solar energy reflected by the cloud (upwelling shortwave radiation, or USR). If net cloud forcing is negative, it cools the earth below.
I found out that indeed, as temperature goes up, the net cloud radiation goes down, meaning the clouds have a greater cooling effect. I posted it, and asked for people to poke holes in it.
What could be wrong with that? Well, I forgot a very simple thing, and none of the commenters noticed either. The error was this. Net cloud forcing is cloud DLR ULR minus shortwave reflected by that same cloud. But what I forgot is that reflected shortwave is the cloud albedo times the total insolation (downwelling solar shortwave radiation).
The catch, as you probably have noticed, is this. If the cloud doesn’t change at all and the total insolation rises, the net cloud forcing will become more and more negative. The upwelling reflected solar is the cloud albedo times the insolation. As insolation rises, more and more sunshine is reflected, so the net cloud forcing goes down. That’s just math.
The problem is that as insolation rises, temperatures also rise. So by showing net cloud forcing goes down with increasing temperature, all I have done is to show that net cloud forcing goes down with increasing insolation … and duh, the math proves that.
However, recognizing that as the problem also gave me the solution. This is to express the net cloud forcing, not as a number of watts per square metre, but as a percentage of the insolation. That way, I could cancel out the effect of the insolation, and extract the information about the clouds themselves. Figure 1 shows the results of that analysis.
Figure 1. Net Cloud Forcing (W/m2) as a percentage of gridcell insolation (W/m2), monthly averages from 1985-1989. Average percentage results shown above each map are area-averaged. Missing data shown in gray. Cloud forcing data from ERBE, insolation data from NASA.
This is an interesting result, for a variety of reasons.
First, it is quite detailed, which gives me confidence in the geographical accuracy of my calculations. For example, the cooling effect of the thunderstorms in the Inter-Tropical Convergence Zone (ITCZ) is clearly visible in the Pacific as a horizontal blue line slightly above the equator, and can be seen in the Atlantic Ocean as well. The ITCZ is the great band of equatorial thunderstorms around the planet that drive the Hadley circulation. Remember that the majority of the energy entering the climate system is doing so in the Tropics. Because of that, a few percent change in the equatorial net cloud forcing represents lots and lots of watts per square meter.
Second, the differing responses of the clouds over the land versus clouds over the ocean are also clearly displayed. In general, land clouds warm more/cool less than ocean clouds. In addition, you can see that while the clouds rarely warm the NH ocean, they have a large warming effect on the SH ocean.
Third, and most significant, look at the timing of the seasonal changes. Take December as an example. In the Northern Hemisphere this is winter, the coldest time of year, and the clouds are having a net warming effect. In the Southern Hemisphere summer, on the other hand, clouds are cooling the surface. But by June, the situation is reversed, with the clouds having a strong cooling effect in the warm North, while warming up the winter in the South. (Note that the NH warming effect is somewhat masked by the fact that there are large areas of missing data over the land in the NH winter, shown as gray areas. The effect of this on the global average is unknown. However, by using a combination of gridcells which are adjacent temporally and gridcells which are adjacent spatially, it should be possible to do an intelligent infill of the missing areas and at least come to a more accurate estimate of the net effect. So many paths to investigate … so little time.)
I have hypothesized elsewhere that the earth has a governor which works to maintain a constant temperature. One of the features of a governor is that it cannot be simple fixed linear feedback. By that, I mean it must act in two directions—it must act to warm the earth when it is cold, and to cool the earth when it is warm. This is different from linear negative feedback, which only works to cool things down, or linear positive feedback, which only works to warm things up. A governor has to swing both ways.
Figure 1 clearly shows that, as I have been saying for some time, including both the longwave and shortwave effects clouds act strongly to warm the earth when it is cold (red areas in Figure 1) and to cool the earth when it is warm (blue areas in Figure 1). In addition, as I have also said (without much evidence until now to substantiate my claim), the ITCZ has a large net cooling effect.
So that’s where I am up to right now in my investigation of the ERBE data. Always more to learn, I’ll continue to report my results as they happen, the story of the ERBE data is far from over. I’ll be in and out of contact for a bit, I’m around today but I’m hitchhiking up to Oregon tomorrow for a friend’s bachelor party, so don’t think I’m ignoring you if I don’t answer for a bit.
w.
PS – there are some interesting results that I’ll post when I have time. These involve looking at the phase diagrams for cloud forcing, temperature, and insolation. Having the insolation available allows the phase of both the temperature and the forcing to be compared to what is actually the underlying driving mechanism, the insolation.
Regarding temperature and insolation, the ERBE data shows what is well known, that the temperature changes lag the insolation changes by about two months in the Southern Hemisphere, and by one month in the Northern Hemisphere. This is because of the thermal inertia of the planet (it takes time to warm or cool), along with the greater thermal inertia of the greater percentage of ocean in the south.
The interesting part is this: the phase diagram shows that there is no lag at all for the changes in the clouds. They change right in step with the insolation, in both the Northern and Southern Hemispheres.
This means, of course, that the clouds move first, and the temperature follows.
I’ll post those phase diagrams when I have some time.
[UPDATE: The phase diagrams, as mentioned. First, Figure 2 shows the temperature versus the insolation:
Figure 2. Insolation vs absolute temperature, from the equator to 65 N/S. The poles are not included because the ERBE cloud data only covers 65 N/S. This does not affect the phase diagrams. Black line shows no lag, gold line shows one month lag, red line shows two months lag between maximum insolation and maximum temperature. Numbers after month names show months of lag.
Since the driving signal (insolation) peaks in June and December, those months will be in the corners when the two cycles are aligned. In the Northern Hemisphere (upper panel), December is in the lower left corner with a lag of 1 month (gold line).
The Southern Hemisphere is half a cycle out of phase, so December is maximum insolation in the upper right corner. This occurs with a lag of two months (red line).
This verifies that temperatures lag insolation by a month in the Northern Hemisphere (the warmest time is not end June, when the insolation peaks) and two month in the southern hemisphere.
However, the situation is different with the clouds, as Figure 3 shows.
Figure 2. Insolation vs cloud forcing %, from the equator to 65 N/S. The poles are not included because the ERBE cloud data only covers 65 N/S. I suspect that the odd shape is a consequence of the missing gridcell data in the ERBE dataset, but that is a guess.
For the cloud forcing in both Hemispheres, there is no lag with regards to the insolation.
w.
Willis Eschenbach Stop being an ass! OK your smart! 🙂
@ur momisugly Willis
Read it again. Excellent post. The graphs are complex and takes a little study to understand, but necessarily so. Many less ‘comfortable’ with graphic presentations will be lost there. I don’t know how you could convey the data any better.
I like your approach to percentages as opposed to numeric values. Much more informative on overall picture.
Clouds, the last frontier?
Taking the simplistic view of a single cloud (mathematical limits of a sort): The solar radiation that contributes to the formation of a cloud for the most part bypasses that same cloud;is minimally reflected by that cloud. When the sun comes up, it shines under every cloud–cloud shadows fall out in space, not on land or sea, so no heat disruption from reflection. And while the sun’s radiation is admittedly minimal albeit growing as the morning progresses, just once a day does each spot on the earth experience maximum incidence angle–before or after that the sun’s energy falls a significant distance laterally from any cloud that may be in the way; for the most part, a cloud has no influence on the thermal energy that forms it.
So wouldn’t this spherical geometry and the fact that clouds are elevated make clouds secondary in the system? You say:
But on a daily basis, my little cloud starts with no shading function whatsoever, and it declines again to zero as the sun sets. And because temperature is a function of the sun, it seems temperature would move first, followed by clouds.
Scott says:
October 11, 2011 at 9:25 pm
What is “Insolation” as you use the term?>>>
noun ~ When you are impervious to insolence, you are said to be well insolated, or to have insolation. Mann’s considers tree ring data that doesn’t show a hockey stick pattern to be insolent. He wrote a computer program that was designed with insolation to any other data.
adjective ~ opposite of insolvent. Mann and Trenberth earn sufficient money from consulting fees that they are unlikely to become insolvent. They however do not have Al Gore’s level of insolation either in monetary wealth or body type.
adjective2 ~ as in unable to solve. Trenberth considers the missing heat to be insoluble, insulting, and incredible. The missing heat is insolated from discovery. Similar to isolated, invisible and incredibly-tragic.
No, wait… oh yeah, its the measure of the sun’s energy flux. watt/m2.
Willis,
Please note I intend no offence. Feel free to squash me like bug, if you wish. However : –
If you place anything at all between a source of heat e.g. the Sun, and an object, e.g. the surface of the Earth, the object will not miraculously heat up. It cannot and will not. The temperature is maximal when exposed to the direct radiation from the heat source. Placing some sort of magic gas between the radiation source and the body will not cause the body’s temperature to rise.
It doesn’t matter if you talk about thermostats, rheostats or aerostats. You can analogise and conduct thought experiments until your brain explodes. You can try with ethane or methane or carbon dioxide, it makes no difference.
I have seen diagrams of bouncing balls, coloured arrows, scales, springs, big letters and numbers and all the rest, until my eyeballs spin. You can subject me to Fourier transforms, fourth order derivatives, vector calculus, the Riemann hypothesis, until I scream for mercy.
The physics won’t change. And yes, I am aware that all bodies above absolute zero radiate heat. That presumably is how we establish they are not at absolute zero.
The atmosphere appears to have a mild insulating effect. This makes the Earth’s surface a little warmer during the night, and a little cooler during the day, than it would be in the absence of atmosphere a la the Moon. Clouds “block” radiation by reflection. Therefore, clouds can reflect insolation during the day, and reflect “reverse insolation” (outgoing heat) during the night.
There is no “magic” required. Anybody who believes in some magic “additive” effect of greenhouse gases, should join one of the many Over Unity forums. They have plethora of diagrams, formulas, calculations etc., to prove perpetual motion is possible, and plenty of tinfoil hat conspiracy theories to explain why perpetual motion machines don’t actually work.
Just like the AGW theories that assign magic properties to CO2. Does anybody stop to consider that Man’s activities generate heat, and in most cases CO2 results from burning something? In other words CO2 results from living and combustion, which is how we generate most of our energy for industrial and domestic use.
If you lift a ball, your muscles generate heat. This results from cellular activity, and you will eventually purge CO2 as a combustion product from your body via the lungs. Some energy is stored in the ball as potential energy. Drop the ball and the energy is dissipated as heat energy as the ball loses energy and comes to rest. The activities of Man generate lots of heat, including the heat from atomic power plants and submarines. Wind generators create heat – losses in bearings, conversion, line losses, and eventual conversion to kinetic energy or direct heating.
Luckily, heat radiates. Stop producing heat, and the effects are lost to the near absolute zero of outer space in short order.
There is NO greenhouse effect that can magically warm the Earth, Never was, never will be.
Thanks.
Let me see if I have this correct.
Winter time no clouds: Cold and dry
Summer time no clouds: Hot and dry
Winter time clouds: Warmer and wet
Summer time clouds: Cooler and wet
This is obvious and observable.
So then if the tropics have more clouds than the poles and the tropics are always warm then clouds would have an obvious total net global cooling effect (forcing or feedback take your pick).
Is this too obvious to be true?
If clouds are a buffer, reducing them might subject us to greater extremes.
If the above is true, then…
So, lets see what this means in terms of Global Warming, Climate Change, or Climate Disrution.
For Warming, it means that the governor will kick in and reduce the warming of increased CO2 to below what we need to worry about.
For Change, more CO2, more heat, more evaporation, more clouds, less change.
For Disrution, less change means less disruption, smaller temperature swings even in short time frames.
You may have just caused the whole CAGW movement here to plum run out of names.
RockyRoad:
Your simplistic view is egocentric- you are looking at the sun and cloud from your point of view whereas the sun shines on a whole hemisphere at a time- at an angle of 90 degrees over the tropics increasing to 180 degrees to the north south east and west.
Where I live in the tropics, during the day a cloud makes it cooler; at night cloud keeps it warmer. But also higher humidity has a similar effect at night even without cloud, and in daytime with high humidity, while it is terribly muggy, the temperature is less (just doesn’t feel that way!). It’s complicated.
RE: Like anyone else, I’m not fond of being wrong, particularly very publicly wrong. However, that’s the price of science, and sometimes you have to go through being wrong to get to being right.
I think it’s reasonable to expect that what may seem correct at the time, ends up being flawed. In other words, no one bats 1,000.
Making a mistake, later discovering it, and correcting it, that’s one thing, but making a mistake and then “hiding the decline”, that’s another. The first person has my respect, the second person is shameful.
davidmhoffer says:
October 11, 2011 at 8:55 pm . . .
Oh, silly me, I should have realized that, shouldn’t have I . . . 🙂
Seriously, though, sure would like to see this idea get expanded and researched more – wonder if Dr. Spencer could help ( . . he seems to like to work with clouds . . ) – ref his recent posts . . .
This is great work Willis. I appreciate the time and effort it takes to prepare and present these. (and envy the internal excitement you must experience doing the work)
The thing that hits me at first glance is the size of the numbers we’re dealing with with respect to clouds.
Then we compare that to the size of the numbers we’re dealing with with respect to 2 x CO2. A small margin of error in clouds easily overshadows a large margin of error in 2 x CO2. (I think I expressed myself ok there?)
I know where my research time and resources would be directed to.
p.s. warms in winter cools in summer eh? Substitute the word CO2 for clouds and the statement is still true.
If clouds are a buffer, reducing them might subject us to greater extremes.
I have a solution to the ‘naming problem”, “Climate Boredom”.
More CO2, more heat, more evaporation, more clouds, less temeprature swings of all kinds. Enough clouds, the winters will be warm, the summers cool, nothing will ever change…
We will all get so bored with the undending, dreary monotony of the weather that we will all be tempted to commit ritual suicide.
Quick, cut CO2!
Willis : I have shown that when the planet gets colder, cloud forcing increases, and that when the planet gets warmer, clouds act to cool it.
I’m sorry Willis, but you most certainly did NOT show that at all.
What you did was take the cloud forcing at each pixel (which we know a negative number on average) and divided it by the insolation at each latitude (which we know is a positive number). So result is a negative number for each pixel, which you then plot.
That’s still the ‘forcing’ and not the ‘feedback’.
To show negative feedback, you cannot simply divide, but you need to take the derivative : You need to show that if the surface temperature goes up that the forcing goes down (becomes more negative).
For example, you could show that over a full year, that the most negative (most cooling) cloud forcing occurs in the tropics. That would suggest negative feedback. Well, lets see what ERBE tells : here is a plot of the ERBE results from a full year (1989) :
http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean1989/netcf.gif
And, surprise, surprise, the most cooling (most negative cloud forcing) occurs in the cooler (higher latitudes) regions, which suggests that clouds amplify temperature change, which hints at positive cloud feedback.
Ramanathan also hinted at positive cloud feedback from these ERBE results when he wrote :
For example, during past glaciations a migration toward the equator of the field of strong, negative cloudradiative forcing, in response to a similar migration of cooler waters, could have significantly amplified oceanic cooling and continental glaciation.
Now I don’t want to by sarcastic here, but you started with the wrong definition of cloud forcing, then confused forcing and feedback, then used the wrong math and finally interpreted your results incorrectly. It looks like you may need to write another post called “Wrong again..”
Please forgive me if I come off completely obtuse, since I read this site out of curiosity, and not because this is my field of study. My background is Mechanical Engineering and HVAC. The effects you described reminded me of something I was taught about passive building techniques for cooling and heating of buildings, be it a Clerestory or an over hang on the southern side (for us NH people) of a building. This is a link to a slide show presentation I searched for on Google that can explain it far better than I, page 14 is the money graphic.
http://phobos.ramapo.edu/~bmakofsk/energysociety/Passive%20Solar%20Design.ppt
So the first thing that popped into my head when you showed the graphics with the clouds having the opposite affects in the opposite hemispheres in the same time frames, was that what is occurring is something similar to the architectural shading techniques used on buildings.
Or an effect similar to using deciduous trees – provides shade in the summer, allows sun through in the winter. (same in effect not in application as deciduous trees have nothing to do with angle of incidence)
I’m not sure if this is a rabbit hole that everyone has been down before or not.
Regards,
Andrew
dp, let’s say, your blanket is 3cm away from your skin. Nothing hinders your skin from emitting heat according to Boltzmann’s formular. The heat hits the blanket after 100ps (pico seconds) and its temperature increases. Nothing hinders the blanket to emit heat according to Boltzmann… in any direction, some of it hitting your skin after 100ps… which may lead to the impression that your skip doesn’t cool (after the blanket reached about the same temperature as your skin) but in fact both (skin and blanket) play sort of ping-pong.
HTH
Rob Dekker says:
October 11, 2011 at 11:56 pm
Thanks, Rob. You keep thinking of it as feedback. It is not. It is a shift in cloud types and altitudes and colors as the earth warms and cools. The important thing is, when the earth cools, the clouds act to warm it, and when the earth warms the clouds act to cool it.
And yes, I did show that, Figure 1 shows it clearly. See how at any moment the clouds are warming the cool parts, and cooling the warm parts? You are right, that’s not the feedback at all, because as I have pointed out, it’s not about feedback. What you are looking at in Figure 1 is a different bird from feedback. It is a governor.
w.
For all the critics here: Willis invited a review process by WUWT readers. He invited criticism, as he was searching for the truth – can you imagine an alarmist ‘climate scientist’ ever doing that?
As many tens of thousands were invited to comment, it can be seen as a genuine peer review process. It was not a closed circle pal review process so loved by ‘climate scientists’.
He also admitted he was wrong, something never done by ‘climate scientists’.
The concept of the Earth having some kind of self-correcting temperature governor over time has to be self-evident, or life on this planet would have ceased to exist many millions of years ago. I guess this perfectly obvious concept must be yet another of the grand heresies of the AGW cult.
Willis: I have shown that when the planet gets colder, cloud forcing increases, and that when the planet gets warmer, clouds act to cool it.
I think you have, in figure 1.
However, in figure 1 you compute the mean forcing across the whole globe. Could you compute those means by latitude bands: 65S -55S, ,,, 5S-5N, ,,, 55N-65N. The June + effect is confined to a very interesting band that contains little land. In ANOVA terms, you appear to have a nice latitude by month interaction with no main effects. However, you probably want a general linear model, with latitude linear or linear + quadratic(centered at 0, so 65S = -65), and with month represented by a cos(2*pi ([month]/12 – 6) ). (the phase, 6, is “estimated” by eyeball, since June and Dec are the peaks of S and H hemispheres, respectively. estimating it in this fashion allows you to use a general linear model. You have to reduce the residual df by 1, but that will affect the test statistics very little.) ANOVA may work, but you have many df for the model, whereas some parameterization like this has only 2 – 5. It sounds post-hoc since we have already seen the graph, but some of us already asked for disaggregation by latitude, and latitude by time is an obvious thing to model because of the tilt of Earth’s axis.
It took me multiple readings to figure out what you have done here. If I have figured it out. Probably this is not the last word on estimating/representing cloud cover, but it’s good. The hysteresis plots are good also, but I hope that eventually you can disaggregate the latitudes more. As time goes by, everyone will want more detail: land vs water, relation to other climate fluctuations like ENSO, Pacific and Atlantic Oscillations, night vs day, test of serial correlations in the residuals.
A Deming quote: Statistics conceal the information in the data; graphics reveal the information in the data.
This is pretty neat.
Rob Dekker says:
October 11, 2011 at 11:56 pm
I’m totally uninterested in annual averages, Rob, they are a snare and a delusion. The clouds are warming the surface during the cold part of the year, and cooling the surface in the warm part of the year. An annual average throws away all that information, its a foolish move. Sure, you can calculate and ponder the annual average, it will be near zero, the two hemispheres offset mostly … but that tells you nothing about both the extensive heating and the extensive cooling that are going on.
And in fact, the most intensive cooling doesn’t occur in the tropics. I refer you again to Figure 1. Where is the most intensive cooling occurring?
w.
Rob Dekker says:
October 11, 2011 at 11:56 pm
A man who doesn’t want to be sarcastic isn’t sarcastic, and doesn’t have to issue disclaimers. You are, in fact, being sarcastic, and in addition you are dissembling about it.
w.
Willis: See how at any moment the clouds are warming the cool parts, and cooling the warm parts? You are right, that’s not the feedback at all, because as I have pointed out, it’s not about feedback. What you are looking at in Figure 1 is a different bird from feedback. It is a governor.
“Governor” again implies teleology, like “Gaia”, or “intelligent design”. If current increased clouds are a result of recent warming, and if they result in cooling, then clouds are a feedback. If current reduced clouds resulted from recent cooling, and if the reduction results in warming, then they are a feedback. Each way, they are a (probably nonlinear) negative feedback.
If I remember correctly, I wrote a similar comment after your report on your TAO/TRITON analyses. After reading those, I am surprised that you can get this result with monthly aggregate data.
In my opinion (pending another self-discovery of a blatantly obvious (*) flaw), this is better work than Andy Dessler’s 2010 Science paper.
* yeh, right — obvious to the master perhaps.
sincerely,
Matt
Rob Dekker: So result is a negative number for each pixel, which you then plot.
If I understand the scale beneath each globe in figure 1, the number is not negative for each pixel at each time. It’s negative in the summer and positive in the winter, at each location. To average across the year would really obliterate the signal.
I noticed a curious thing…
Just off the west coast of South American, in the center, and off the west coast of Africa, a bit below center, there are areas where the net effext is always cooling. Looking at reference pages show these areas always seem to have sea surface temperatures below the average of the other waters at that latitude.
The question is, what would cause this to be always true, all the year round? Is there a certain type of cloud always at these two spots which always creates this net negative effect? Is there some other effect, say a current or some such, which creates this year long pattern? How do these spots effect the weather/climate/currents etc?
Legatus says:
October 12, 2011 at 12:48 am (Edit)
Interesting catch, Legatus. My guess is trade winds blowing towards the west plus subsurface eastward-flowing currents hitting south america/africa cause year-round upwelling, but we’re a ways into speculation there.
w.
OK, this is likely to be contentious, I’m way out on a limb here … but I suspect that the net effect of the clouds is not negative (cooling) as is commonly believed. I think it is much closer to zero.
I say this after a close examination of Figure 1, while trying to figure out why June is so different from the rest in the phase diagram. What I found was the satellite coverage in June goes almost all the way to the tip of the Antarctic Peninsula just as it did in April, and the effect is of strong warming.
Now look at the months on either side of June. Both May and July are missing data, and it is obvious that the data would show warming. The same is true at the other end, with December showing good coverage. In that case the problem is not as marked, but there is missing data in the months on both sides of December.
Other than July in the North, in the areas where the clouds have a cooling effect, there is little missing data. The overwhelming majority of the missing data would show warming.
Like I said, my guess? All that missing warming data would bring the net forcing back to way nearer to zero. Should be possible to get a rough estimate to see if my guess is good. Let me think about it.
w.