Guest Post by Willis Eschenbach
I had an idea a couple days ago about how to estimate cloud feedback from observations, and it appears to have panned out well. You tell me.
Figure 1. Month-to-month change in 5° gridcell actual temperature ∆T, versus gridcell change in net cloud forcing ∆F. Curved green lines are for illustration only, to highlight how many of the datapoints fall outside those lines in each of the four quadrants. Results have been area-weighted, giving a slightly smaller slope (-1.7 W/m2 per degree) than initally reported (- 1.9 W/m2 per degree). Data colors indicate the location of the gridcell, with the Northern hemisphere starting with blue at the far north, slowly changing to yellow and to red at the equator. From there, purple is southern tropic, through pink to green for the farthest south latitudes. Updated.
Cloud feedback is what effect the changing clouds have if the earth warms. Will the clouds act to increase a warming, or to diminish it? The actual value of the cloud feedback is one of the big unknowns in our current understanding of the climate.
The climate models used by the IPCC all say that as the earth warms, the clouds will act to increase that warming. They all have a strong positive cloud feedback. My thunderstorm and cloud thermostat hypothesis, on the other hand, requires that the cloud feedback be strongly negative, that clouds act to decrease the warming.
My idea involved the use of what are called “gridded monthly climatologies”. A monthly climatology is a long-term month-by-month average of some climate variable of interest. “Gridded” means that the values are given for each, say, 5° latitude by 5° longitude gridbox on the surface of the planet.
My thought was to obtain the monthly actual temperature gridded climatology. This is the real temperature “T” as measured, not the anomaly. In addition, I would need the gridded net cloud forcing “F” from the ERBE (Earth Radiation Budget Experiment) data. Net cloud forcing is the balance of how much solar energy the clouds reflect away from the earth on the one hand, and on the other, how much the same clouds increase the “greenhouse” downwelling longwave radiation (DLR). Net cloud forcing varies depending on the type, thickness, altitude, droplet size, and color of a given cloud. Both positive and negative cloud forcing are common. By convention, positive net cloud forcing (e.g. winter night-time cloud) is warming, while a negative net cloud forcing (e.g. thick afternoon cumulus) is cooling.
Remembering that a cloud feedback is a change in net forcing in reference to a change in temperature, I took the month to month differences of each of the two climatologies . I did this in a circular fashion, each month minus the previous month, starting from February minus January, around to January minus December. That gave me the change in temperature (∆T) and the change in forcing (∆F) for each of the twelve months.
The ERBE satellite only covers between the Arctic and Antarctic circles, the poles aren’t covered. So I trimmed the polar regions from the HadCRUT absolute temperature to match. Then, the HadCRUT3 absolute temperature data are on a 5° grid size, while the ERBE satellite data is on a 2.5° grid. Since the grid midpoints coincided, I was able to use simple averaging to “downsample” the satellite cloud forcing data to correspond with the larger temperature gridcell size.
The results of the investigation are shown in Figure 1. The globally averaged cloud feedback is on the order of -1.9 watts per square metre for every one degree of monthly warming.
This result, if confirmed, strongly supports my hypothesis that the clouds act as a very powerful brake on any warming. At typical Earth surface temperatures, the Stefan-Boltzmann equation gives about five watts per square metre (W/m2) of additional radiation per degree. That is to say, to warm the surface by 1°C, the amount of incoming energy has to increase by about 5 W/m2. This, of course, means that if there were no feedbacks, a doubling of CO2 (+3.7 watts per square metre per the IPCC) would only cause about 3.7/5 or about three-quarters of a degree of warming. The models jack this three-quarters of a degree up to three degrees of warming by, among things, their large positive cloud feedback.
But this analysis says that the cloud feedback is strongly negative, not positive at all. As a result, a doubling of CO2 could easily cause less than eight-tenths of a degree of warming. If the cloud negative feedback is actually -1.9 W/m2 per degree as shown above, and it were the only feedback, a doubling of CO2 would only cause half a degree of warming …
If confirmed, I think that this is a significant result, so I put it up here for people to check my math and my logic. I’ve fooled myself with simple mistakes before …
Code for the procedures and data is appended below.
All the best,
w.
PS – please, no claims that the “greenhouse effect” is a myth or that DLR doesn’t exist or that DLR can’t transfer energy to the ocean. I’m beyond that, whether you are or not, and more to the point, there are plenty of other places to have that debate. This is a scientific thread with a specific subject, and if necessary I may snip such claims (and responses) to avoid thread drift. If so, I will indicate such excisions.
NOTE: The slope of the trend line in Figure 1 is now properly area-adjusted, making the following section andFigure 2 superfluous. .[UPDATE] I’ve gone back and forth about whether to area-average. The problem is that the gridcells are not the same size everywhere. The usual way to area-average is to multiply the data by the cosine of the mid latitude, so I have done that.
Figure 2 shows the area-adjusted version. Still a significant negative feedback from clouds, but smaller than in the non-adjusted version.
FIGURE 2 REMOVED
Figure 2. Area adjusted cloud feedback. Note the lower estimate of the cloud feedback, a bit smaller than my initial estimate. Color of the dots indicates latitude, ranging from blue at the furthest north through cyan to the equator, then in the southern hemisphere through yellow to red at the furthest south.
Note that we still see the same form in the four quadrants. It is still rare for a large temperature drop to be associated with anything but a rise in the cloud forcing.
I’m still not completely happy with this method of area-adjusting, because it adjusts the data itself. But I think it’s better than no area-adjusting at all. The best way would be to convert both of the datasets to equal-area cells … but that’s a large undertaking and I think the final result won’t be much different from this one.
[UPDATE] Here’s the two hemispheres:
Figure 3. Northern Hemisphere Cloud Feedback. Color of the dots indicates latitude, ranging from blue at the furthest north through yellow in the subtropics, to red at the equator.
Figure 4. Southern Hemisphere Cloud Feedback. Color of the dots indicates latitude, ranging from green at the furthest south through pink in the subtropics, to purple at the equator.
[UPDATE] To better inform the discussion, I have made up the following maps of the variables of interest, month by month. These are the monthly absolute temperatures T, the monthly net cloud forcings F, and the month by month changes (deltas) of those variables, ∆T and ∆F.
Figure 5. Absolute temperature (T)
Figure 6. Net Cloud Forcing (F)
Figure 7. Change in absolute temperature (∆T)
Figure 8. Change in net cloud forcing (∆F)
APPENDIX: R code to read and process the data (not including the updated charts). I've tried to keep wordpress from munging the code, but it likes to either put in or not put in carriage returns.
===================================
# data is read into a three dimentional array [longitude, latitude, month]
diffannual=function(x){# returns month(t+1) minus month(t)
x[,,c(2:12,1)]-x
}
# rotates the circle of months by n
rotannual=function(x,n){
if (n!=0) {
if (n>=0){
x[,,c((n+1):12,1:n)]
} else {
x[,,c((13+n):12,1:(12+n))]
}
} else
x
}
#_averages_2.5°_gridcells_into_5°_gridcells,_for_[long,lat,mon]_array
downsample=function(x){
dx=dim(x)
if (length(dx)==3){
reply=array(NA,c(dx[1]/2,dx[2]/2,dx[3]))
for (i in 1:dx[3]){
reply[,,i]=downsample2d(x[,,i])
}
} else {
reply=downsample2d(x)
}
reply
}
# averages 2.5° gridcells into 5° gridcells for [long, lat] 2D array
downsample2d=function(x){
width=ncol(x)
height=nrow(x)
smallforcing=matrix(NA,height/2,width/2)
for (i in seq(1,height-1,2)){
for (j in seq(1,width-1,2)){
smallforcing[(i+1)/2,(j+1)/2]=mean(c(x[i,j],x[i+1,j],x[i,j+1],x[i+1,j+1]),na.rm=T)
}
}
as.matrix(smallforcing)
}
# EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE End Functions
# LLLLLLLLLLLLLLLLLLLLLLLLLL LOAD DATA ----- gets the files from the web
# HadCRUT absolute temperature data
absurl="http://www.cru.uea.ac.uk/cru/data/temperature/absolute.nc"
download.file(absurl,"HadCRUT absolute.nc")
absnc=open.ncdf("HadCRUT absolute.nc")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5jan/data.txt","albedojan.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5feb/data.txt","albedofeb.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5mar/data.txt","albedomar.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5apr/data.txt","albedoapr.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5may/data.txt","albedomay.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5jun/data.txt","albedojun.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5jul/data.txt","albedojul.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5aug/data.txt","albedoaug.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5sep/data.txt","albedosep.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5oct/data.txt","albedooct.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5nov/data.txt","albedonov.txt")
download.file("http://badc.nerc.ac.uk/browse/badc/CDs/erbe/erbedata/erbs/mean5dec/data.txt","albedodec.txt")
albnames=c("albedojan.txt","albedofeb.txt","albedomar.txt","albedoapr.txt","albedomay.txt","albedojun.txt","albedojul.txt","albedoaug.txt","albedosep.txt","albedooct.txt","albedonov.txt","albedodec.txt")
# read data into array
forcingblock=array(NA,c(52,144,12))
for (i in 1:12){
erbelist=read.fwf(albnames[i],skip=19,widths=rep(7,13))
erbelist[erbelist==999.99]=NA
erbeout=erbelist[,13][which((erbelist[,1]>-65) & (erbelist[,1]
length(erbeout)
forcingblock[,,i]=matrix(erbeout,52,144,byrow=T)
}
# DOWNSAMPLE FORCING DATA TO MATCH TEMPERATURE DATA,
# and swap lat and long to match HadCRUT data
smallforcing=aperm(downsample(forcingblock),c(2,1,3))
smallforcing[1:72,,]=smallforcing[c(37:72,1:36),,]# adjust start point
# GET ABSOLUTE DATA, TRIM POLAR REGIONS
absblock= get.var.ncdf(absnc,"tem")
smallabs=absblock[,6:31,]
#dim(absblock)
# GET MONTH-TO-MONTH DIFFERENCES
dabs=diffannual(smallabs)
dforcing=diffannual(smallforcing)
dim(dforcing)
#SAVE DATA
save(forcingblock,smallforcing,smallabs,dabs,dforcing,file="erbe_cloud_forcing.tab")
# make cosine weight array
cosarray=array(NA,c(72,26,12))
cosmatrix=matrix(rep(cos(seq(-62.5,62.5,by=5)*2*3.14159/360),72),72,26,byrow=T)
cosmatrix=cosmatrix/mean(cosmatrix[1,])
cosarray[,,1:12]=cosmatrix
cosarray[,,2]
# GET CORRELATION, SLOPE, AND INTERCEPT
#cor(dabs,dforcing,use="pairwise.complete.obs")
module=lm(dforcing~dabs)
m=module$coefficients[2]
b=module$coefficients[1]
#Plot Results
par(mgp=c(2,1,0))
plot(dforcing~dabs,pch=".",main="Cloud Feedback, 65°N to 65°S", col="deepskyblue3",xlab="∆ Temperature (°C)",ylab="∆ Cloud Forcing (W/m2)")
lines(c(m*(-20:15)+b)~c(-20:15),col="blue",lwd=2)
textcolor="lightgoldenrod4"
text(-20,-60,"N = 18,444",adj=c(0,0),col= textcolor)
text(-20,-70,paste("Slope =",round(m,1),"W/m2 per degree C of warming"),adj=c(0,0),col= textcolor)
text(-20,-80,paste("p = ","2E-16"),adj=c(0,0),col= textcolor)
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If cloud feedback was positive – as stated by the IPCC – it is difficult to see how exponential heating of the Earth’s surface would not occur. The argument is more CO2, therefore more heat, therefore more evaporation and therefore more clouds and therefore more heat and so on.
The geological record shows this has never happened, so there has to be a balancing mechanism in the Earth’s climate – negative cloud feedback makes perfect sense.
From the standpoint of feedback considerations, it might be important to distinguish between two cloud types, which are fundamentally different. The first type I will call an atmospheric advection cloud. These are created by the interaction of two different air masses moving against each other. Thus they have little thermal contact with the surface except via LWIR. Surface conditions have little to do with the formation of these clouds, so I would expect minimal direct ground feedback in this case.
The second type I will call a surface convection cloud. As the formation of these clouds do depend on surface temperature, I would expect a strong, probably negative, feedback associated with them. So, in studies of this kind, I think the word ‘cloud’ by itself may be incomplete if we do not make a distinction between surface convection clouds and atmospheric advection clouds.
Willis Eschenbach says:
October 9, 2011 at 12:12 am
For example, big drops in temperature are usually associated with a rise in cloud warming, and hardly ever associated with more cloud cooling. In other words, when it gets colder, the response of the clouds is a warming.
This looks to me like it could be a visual of the known water cycle, (which is excluded from the AGWhype because it doesn’t suit to have negative feedback in CO2 is driving temps). With the water cycle taken out of the atmosphere temp would be 67°C. That’s a lot of cooling by the water cycle taking up heat from the surface in water vapour and forming clouds, (clouds form when water vapour gets cold enough, at dew point it condenses out into water to form clouds so the heat is already released and temps beneath clouds will drop). Cloud cover impeding convected rising heat may well temporarily keep temps higher beneath, but prolonged such will impede the Sun’s thermal infrared from reaching the surface to heat it to continue the cycle, a ‘year without a summer’ type situation could result. Regardless rising CO2 ‘backradiating’ like mad..
I added Northern and Southern Hemisphere graphs to the head post, colored by latitude.
w.
Willis Eschenbach says:
October 9, 2011 at 12:12 am
“But in fact there is such a relationship. For example, big drops in temperature are usually associated with a rise in cloud warming, and hardly ever associated with more cloud cooling. In other words, when it gets colder, the response of the clouds is a warming.”
“cloud warming” and “cloud cooling”.
Are you sure you don’t mean more cloud formation and less cloud formation?
And if so, how is that any kind of revelation?
Water vapour transports energy, it doesn’t add energy. Clouds are a channel or a conduit, they are not a “forcing”. The term “forcing”, in respect to the atmosphere, is a logical fallacy. To claim that clouds, and even water vapour can cause warming is a circular argument.
Temperature is simply a measure of perceived or perceivable, thermalised energy. The water vapour content of the atmosphere, is not determined by the water vapour content of the atmosphere. It is determined by almost everything but.
I live in the UK where we are immersed in the Gulf Stream. The Gulf Stream keeps the UK unseasonably mild. This extra energy is not provided by the clouds, it is merely transported by them from the warmer region of the Gulf of Mexico near to the Equator.
Clouds may effect localised temperature but they cannot and do not effect the global “energy budget” as it is referred to. Clouds effect diffusion of incoming and out going energy, not the amount of energy. The confusion originates in the fallacy that all incoming solar EMR is SW. It is more than 50% LW
Clouds intercept incoming solar EMR. Some of the SW frequencies are reflected, while more of the LW frequencies are diffused through the system. This diffused energy has been rebranded DLR. Yet it is simply diffused solar EMR. Near the Equator some of the energy emitted by the ground causes some atmospheric warming but, over most of the globe the opposite is the case. As can be seen in the global radiosonde data.
Like it or not Willis, these facts are not conducive to the current “greenhouse effect” hypothesis.
“Giss in absolute?”
Since only the monthly differences are used, I don’t think it matters.
Willis, I find the difference between North & South extremely interesting, it shows your “Thermostat” very well.
Over the sea in the South and towards the equator in the North the values are much less scattered.
The effects of the land masses in the North seem to be causing a lot of scattering.
“In other words, when it gets colder, the response of the clouds is a warming.”
Well, you don’t know that – correlation is not causation. It could equally be that the clouds cause the cooling (despite the sign of the forcing). But more likely the common root cause – the seasonal rise and fall of the sun. When the sun declines, it cools and you get more clouds, which do give a positive forcing, but which can’t outweigh the loss of sunlight.
Personally, I’m not bothered by the different time periods – as you say, you’re just looking at climatologies.
Someone needs to volunteer to adjust the GCMs to predict the observations that you are using.
@Willis Eschenbach
You make a point about cloud and DLR:
“Net cloud forcing is the balance of how much solar energy the clouds reflect away from the earth on the one hand, and on the other, how much the same clouds increase the “greenhouse” downwelling longwave radiation (DLR).”
Then a big generalized leap:
“That is to say, to warm the surface by 1°C, the amount of incoming energy has to increase by about 5 W/m2. ”
This generalization does not hunt. The type of energy and type of surface makes a difference. For instance if the surface is ice and the energy is shortwave it will raise the temperature very little. If the surface is water and the energy is shortwave it will raise the temperature very much.
More to the point, if the energy is longwave and the surface is water it will not raise the temperature very much. This is predicted by the physics and experimentally confirmed.
http://tallbloke.wordpress.com/2011/08/25/konrad-empirical-test-of-ocean-cooling-and-back-radiation-theory/
This is extremely relevant to your hypothesis, Willis. Snipping challenges to underlying assumptions in your thesis is not very scientific.
I’m putting this comment in a macro and will repeat it ad infinitum in every thread of yours until you acknowledge it. If that doesn’t work I’ll start placing it in threads you don’t control.
Are we clear on what I think about censoring critics and how I intend to respond to you now?
[UPDATE: Dave, you apparently have mistaken me for someone who gives a flying flock about your ideas. If you wish to make a fool of yourself by screaming, thinking that repeating your claims more loudly or more frequently will somehow make them true or will convince people to pay attention to you, I fear I can’t help you.
So, this time I’ll leave your comment here, in the hopes that it will convince you to be polite and go away. You remember “polite”? That’s where, when someone says “Please discuss that claim on another thread, we’re discussing something else on this thread”, you say “OK”, and you discuss it elsewhere.
If you want to prove that you are a jerk, Dave, go ahead and keep repeating your claims, and persevere in trying to butt into a conversation where those kinds of claims are not being discussed. However, people here won’t get to read them, I’ll snip them all day long. WE ARE DISCUSSING ANOTHER MATTER HERE, how hard is that to understand?
So if you wish to pound yet again on your one-note drum, have the common courtesy and simple decency to do it somewhere else. I will snip it here, but not because it is scientific nonsense. It is nonsense, but that’s not the reason. I will snip it because we are talking about something else on this thread, and your contribution is neither appropriate nor wanted.
PS: Threats don’t work with me. You say that you are “putting this comment in a macro and will repeat it ad infinitum in every thread of yours until you acknowledge it.” Yeah, I’m shaking in my boots with fear now, that’s a brilliant plan, everyone appreciates being spammed, the lurkers will love you, and you’ll never get banned for that kind of childishness … you don’t seem to get it. REPEATING YOUR CLAIM DOESN’T MAKE IT TRUE. So go ahead, spam your message on every site you can find. A site discussing cross-stitching methods for needlepoint? Perfect, you’ve proven you don’t care in the slightest what others want to talk about, you are an equal-opportunity bore and you insist on your right to talk “radiation can’t heat the ocean” no matter what the thread is about. So go ahead post your claims on the cross-stitching site and every other one you can find, that’ll show the world you’re not a man to be messed with … – w.]
@Willis Eschenbach
[SNIP – please discuss your claims that radiation can’t heat the ocean elsewhere. -w.]
Hi Willis. I’m not getting fig 3 showing up. Also legend for fig 4 Southern hemisphere gives colours for regions from the North to the equator. Last time I looked, the equator is in the North in the Southern hemisphere.
[Thanks, fixed the note. Figure 3 shows up for me, is anyone else having problems with it? – w.]
I can only agree that an analysis of this nature is long overdue. Of course we are all happily wagging our tails because it seems to confirm what many (most?) of us here believe. However, I would feel a lot more confident of the validity of the outcome if the suggested sub-sets of land/water, day/night, etc could somehow be done. Should such individual results hold form in the sense of intuitive logic, the value of the overall outcome here would be vastly strengthened. On the other hand, should individual analyses give counter-intuitive results, it would deminish the overall result as perhaps being an artifact of some sort. Whatever such outcome, this certainly is an area where some serious grant money would be well spent!
@Willis Eschenbach
You missed the memo from NASA.
[SNIP – you missed the memo about me snipping off-topic comments. w.]
Are we seeing a ‘corkscrew’ plot as we march from the poles to the equator?
Does the slope revolve like a propeller as we move from cold-pole to hot-equator?
hi willis,
it might be useful to run a series of fits sliced by latitude. this would also remove the need for area weighting. it would also give u some sense of the stability of the effect at least on a spatial basis.
d
Philip Bradley says:
October 8, 2011 at 6:43 pm
Maybe I am missing something here, but I have difficulty seeing how a month on month temperature change can cause a month on month change in cloud forcing.
I’d expect the cloud forcing to be a direct function of temperature. Warmer = more clouds = increase in the cloud forcing. What matters is the temperature, not whether the temperature has increased/decreased.
So I’d expect to see a similar (or larger) effect if cloud forcing were plotted against monthly temperature.
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
That is what I saw looking at afternoon thunderstorm formation in the summer along the east coast of the USA. The number of afternoon thunderstorms per week decreased going from Florida to Fayetteville NC/Rocky Mt. This seemed to be the Northern most point with numerous summer thunderstorms. It is also the “Snow Line” that is the point where you can expect at least some snow each winter.
Other independent analysis:
“…Pall ́ et al (2004a) correlated the earthshine data with International Satellite Cloud Climatology Project (ISCCP) cloud data to construct from the latter a proxy record of the Earth’s reflectance. They showed from that proxy that the Earth’s albedo decreased by about 6 W/m2 from 1985 to 2000, while direct earthshine observations from 1999-2003 revealed that the decline had stopped and even reversed to an increasing trend in reflectance. The ISCCP project however, recently released the FD product, which contain estimates of the top of the atmosphere (TOA) albedo. These data are based on ISCCP cloud properties, plus some modeling estimates to derive shortwave and longwave fluxes, and they indicate a more muted long-term albedo decrease from 1983 to 2000…. Meanwhile, data collection has continued, and in the past couple of years, all datasets in the aforementioned literature have been re-calibrated and/or re-analyzed, so it is now proper to make a new comparison….
Over the 1999-2007 period, there is an increasing reflectance trend from 1999 to 2003, but after that year the reflectance does not seem to vary. In fact, except for 2003, the Earth’s reflectance as measured by earthshine has not changed since 2001.” http://bbso.njit.edu/Research/EarthShine/literature/Palle_etal_2008_JGR.pdf
This indicates a decrease in cloud cover/albedo during a time period when the overall temp was increasing and an increase/plateau when the overall temp “stagnated” see Dr. Roy Spencer’s Data: http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_September_2011.png.
I think the correlation is badly confounded because of the effects of other factors and different cloud types. It is interesting that the southern hemisphere data is much more tightly clustered compared to that of the northern hemisphere perhaps indicating the ocean effect.
I agree that separating land vs ocean data should be the next step. We already know that the oceans effect temperature from the other work that has been done.
AMO+PDO= temperature variation – one graph says it all http://wattsupwiththat.com/2010/09/30/amopdo-temperature-variation-one-graph-says-it-all/
In my view snipping comments because the thread originator decides they are off topic is not a good direction for this site . . . . . on the grounds of abuse, stalking etc it definitely makes sense. It leaves wattsupwiththat open to charges of censorship. . . probably the last thing it needs in the climate debate. . . And yeah this comment is off topic . . but it would be pretty pointless to snip it though . . . if there’s widespread disagreement with it then fair enough you’ll have snipping policy support for the future . . . . .
I think that in figure 4 south should replace north.
Figure 4. Southern Hemisphere Cloud Feedback. Color of the dots indicates latitude, ranging from blue at the furthest south through yellow in the subtropics, to red at the equator. [Thanks, fixed. w.]
How does this work match up to Roy Spencer’s calculations.
I do find it frustrating different scientists can use the same data and equations and yet seem to come up with diametrically opposed answers, such as Spencer and Dessler.
Paul Homewood says:
October 9, 2011 at 6:06 am
How does this work match up to Roy Spencer’s calculations.
I do find it frustrating different scientists can use the same data and equations and yet seem to come up with diametrically opposed answers, such as Spencer and Dessler.
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
Welcome to the workings of true science.
It is perfectly acceptable for different scientists to have different interpretations of the same data and form different hypotheses, as long as NO ONE is censored and it leads to experiments to prove or disprove those hypotheses
The problem comes in when a clique of scientists decide to censor anything that does not agree with their thoughts.
Science advances one funeral at a time. — Max Planck
Willis, both graphs 3 & 4 have the same note about coloring of dots, description for #4 cannot be right. Interesting how tight the SH is compared to NH. One might assume the difference is land mass ocean ratio, and/or a difference in cloud cover related to that ratio. I would think on land there are a lot of differences in localized thermal gradients, whereas the ocean would be more homogenous in albedo and topography. The topography of the land causes changes in water vapor, for example, air moving over mountains loses water content. From the first graph, it is interesting that solid water 0°C cools as clouds.
Steven Mosher,
Have you ever thought of doing aerosol masks? I’ve been thinking it’d be good to mask areas where there are large concentrations of man made and land based aerosols good for cloud nucleation where levels are consistently high). Then look at clouds, crf, and albedo and ocean heat.
Willis,
I’m out of my league here – poor in math and knowing nothing of climate science. So let me just jump in with both feet firmly in my mouth:
From Wikipedia, approximately 53% of incoming radiation from the sun is infrared.
From NSIDC(.org) approximately 30% of incoming solar shortwave radiation is reflected back into space. The remaining 70% strikes the earth and is re-emitted as longwave (infrared) radiation.
———————————–
The above stuff I got from the Internet, so if I’m wrong already, forgive me.
———————————–
Assume 1,000 Watts of radiation strike the earth from the sun.
530 Watts is longwave and will have a positive forcing (warms the earth).
470 Watts is shortwave of which 30% is reflected back, leaving 70% or 329 Watts to strike the earth and be re-emitted as longwave (infrared).
Regarding the clouds, do they prevent the incoming shortwave (the 530 W) from reaching the earth’s surface to the same extent that they will prevent the outgoing shortwave (the 329 W) from leaving the earth?
Seems to me that clouds would always have a negative forcing (cooling effect) when incoming infrared is greater than outgoing, at least to a first order approximation.
So what is wrong with my logic here?
jim hogg says:
October 9, 2011 at 5:46 am
I“n my view snipping comments because the thread originator decides they are off topic is not a good direction for this site . . . . . on the grounds of abuse, stalking etc it definitely makes sense. It leaves wattsupwiththat open to charges of censorship. . . probably the last thing it needs in the climate debate…. “
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Actually I do not see it that way at all.
Willis stated very clearly that he wished the thread to stay on topic and focused because he is looking on feed back about his work. As he said there are plenty of other posts on WUWT where those who wish to can discuss the topics he wishes to avoid.