Guest Post by Willis Eschenbach
Well, another productive ramble through the CERES dataset, which never ceases to surprise me. This time my eye was caught by a press release about a new (paywalled) study by Gordon et al. regarding the effect of water vapor on the climate:
From 2002 to 2009, an infrared sounder aboard NASA’s Aqua satellite measured the atmospheric concentration of water vapor. Combined with a radiative transfer model, Gordon et al. used these observations to determine the strength of the water vapor feedback. According to their calculations, atmospheric water vapor amplifies warming by 2.2 plus or minus 0.4 watts per square meter per degree Celsius. (See Notes for sources)
Hmmm, sez I, plus or minus 0.4 W/m2? I didn’t know if that was big or small, so I figured I’d take a look at what the CERES data said about water vapor. As the inimitable Ramanathan pointed out, the distribution of water vapor in the atmosphere is shown by the variations in the clear-sky atmospheric absorption of upwelling longwave.
Figure 1. Distribution of Atmospheric Water Vapor, as shown by absorption of upwelling surface longwave (LW) radiation, in watts per square metre (W/m2). In areas of increased water vapor, a larger amount of the upwelling radiation is absorbed in clear-sky conditions. Absorption is calculated as the upwelling surface longwave radiation minus the upwelling top-of-atmosphere (TOA) longwave radiation. The difference between the two is what is absorbed. Contours are at 10 W/m2 intervals.
As Ramanathan saw, there’s only one greenhouse gas (GHG) that shows that kind of spatial variability of absorption, and that’s water vapor. The rest of the GHGs are too well mixed and change too slowly to be responsible for the variation we see in atmospheric absorption of upwelling surface radiation.. OK, sez I, I can use that information to figure out the change in clear-sky absorption per degree of change in temperature. However, I wanted an answer in watts per square metre … and that brings up a curious problem. Figure 2 shows my first (unsuccessful) cut at an answer. I simply calculated the change in absorption (in W/m2) that results from a one-degree change in temperature.
Figure 2. Pattern of changes in clear-sky atmospheric absorption, per 1°C increase in temperature. This is the pattern after the removal of the monthly seasonal variations.
The problem with Figure 2 is that if there is a 1°C increase in temperature, we expect there to be an increase in watts absorbed even if there is absolutely no change in the absorption due to water vapor. In other words, at 1°C higher temperature we should get more absorption (in W/m2) even if water vapor is fixed, simply because at a higher temperature, more longwave is radiated upward by the surface. As a result, more upwelling longwave will be radiated will be absorbed. So I realized that Figure 2 was simply misleading me, because it includes both water vapor AND direct temperature effects.
But how much more radiation should we get from a surface temperature change of 1°C? I first considered using theoretical blackbody calculations. After some reflection, I realized that I didn’t have to use a theoretical answer, I could use the data. To do that, instead of average W/m2 of absorption, I calculated the average percentage of absorption for each gridcell, as shown in Figure 3.
Figure 3. As in Figure 1, showing the distribution of water vapor, but this time shown as the percentage of upwelling surface longwave radiation which is absorbed in clear-sky conditions. Contours are at intervals of 2%, highest contour is 40%. Contours omitted over the land for clarity.
This is an interesting plot in and of itself, because it shows the variations in the efficiency of the clear-sky atmospheric greenhouse effect in percent. It is similar to Figure 1, but not identical. Note that the clear-sky greenhouse effect in the tropics is 30-40%, while at the poles it is much smaller. Note also how Antarctica is very dry. You can also see the Gobi desert in China and the Atacama desert in Peru. Finally, remember this does not include the manifold effects of clouds, as it is measuring only the clear-sky greenhouse effect.
Back to the question of water vapor feedback, using percentages removes the direct radiative effect of the increase in temperature. So with that out of the way, I looked at the relationship between the percentage of absorption of upwelling LW, and the temperature. Figure 4 shows the average temperature and the average absorption of upwelling LW (%):
Figure 4. Scatterplot of 1°x1° gridcell average atmospheric absorption and average temperature. The green data points are land gridcells, and the blue points show ocean gridcells. N (number of observations) = 64,800.
As you can see, the relationship between surface temperature and percentage of absorption is surprisingly linear. It is also the same over the land and the ocean, which is not true of all variables. The slope of the trend line (gold dashed line in Figure 4) is the change in percentage of absorption per degree of change in temperature. The graph shows a ~ 0.4% increase in absorption per °C of warming.
Finally, to convert this percentage change in absorption to a global average water vapor feedback in watts per square metre per °C, we simply need to multiply the average upwelling longwave (~ 399 W/m2) times 0.443%, which is the change in percentage per degree C. This gives us a value for the change in absorption of 1.8 ± .001 W/m2 per degree C.
Finally, recall what the authors said above, that “atmospheric water vapor amplifies warming by 2.2 plus or minus 0.4 watts per square meter per degree Celsius.” That means that the CERES data does not disagree with the conclusions of the authors above. However, it is quite a bit smaller—the Gordon et al. value is about 20% larger than the CERES value.
Which one seems more solid? I’d say the CERES data, for a couple of reasons. First, because the trend is so linear and is stable over such a wide range. Second, because the uncertainty in the trend is so small. That indicates to me that it is a real phenomenon with the indicated strength, a 1.8 W/m2 increase in absorbed TOA radiation.
Finally, according to Gordon et al. there is both a short-term and a long-term effect. They say
By forcing a radiative transfer model with the observed distribution of water vapor, we can understand the effect that the water vapor has on the TOA irradiance. Combining information on how global mean surface temperature affects the total atmospheric moisture content, we provide an estimate of the feedback that water vapor exerts in our climate system. Using our technique, we calculate a short-term water vapor feedback of 2.2 W m–2 K–1. The errors associated with this calculation, associated primarily with the shortness of our observational time series, suggest that the long-term water vapor feedback lies between 1.9 and 2.8 W m-2 K–1.
So … which one is being measured in this type of analysis? I would argue that the gridcells in each case represent the steady-state, after all readjustments and including all long-term effects. As a result, I think that we are measuring the long-term water-vapor feedback.
That’s the latest news from CERES, the gift that keeps on giving.
Best to all,
w.
NOTES:
Ut Solet
If you disagree with something I (or anyone) says, please quote my words exactly. I can defend my own words, or admit their errors, and I’m happy to do so as needed. I can’t defend your (mis)understanding of my words. If you quote what I said, we can all be clear just what it is that you think is incorrect.
Data and Paper
Press Release here.
Paywalled paper: An observationally based constraint on the water-vapor feedback, Gordon et al., JGR Atmospheres
R Code: CERES Water Vapor (zipped folder 750 mb)
CERES Data: CERES TOA (220 Mb) and CERES Surface (115 Mb)
[UPDATE]
An alert reader noted that I had simplified the actual solution, saying:
Since one of the feedbacks is T^4 it would probably come out as T^3 in a percentage plot and this curve has strong upwards curvature.
To which I replied:
Not really, although you are correct that expressing it as a percentage removes most of the dependence on temperature, but not quite all of the dependence on temperature. As a result, as you point out the derivative would not be a straight line. Here’s the math. The absorption as a percentage, as noted above, is
(S- TOA)/S
with S being upwelling surface LW and TOA upwelling LW.
This simplifies to
1 – TOA/S
But as you point out, S, the surface upwelling LW, is related to temperature by the Stefan-Boltzmann equation, viz
S = sigma T4
where S is surface upwelling LW, sigma is the Stefan Boltzmann constant, and T is temperature. (As is usual in such calculations I’ve assumed the surface LW emissivity is 1. It makes no significant difference to the results.)
In addition, the TOA upwelling longwave varies linearly with T. This was a surprise to me. One of the interesting parts of the CERES dataset investigation is seeing who varies linearly with temperature, and who varies linearly with W/m2. In this case TOA can be well expressed (to a first order) as a linear function of T of the form mT+b.
This means that (again to a first order) I am taking the derivative of
1 – (m T + b) / (sigma T4)
which solves to
(4 b + 3 m T)/(sigma T5)
Over the range of interest, this graphs out as
Recall that my straight-line estimate was 0.44% per degree, the average of the values shown above. In fact, the more nuanced analysis the commenter suggested shows that it varies between about 0.38% and 0.5% per degree.
When I saw these clouds I thought of Willis.
None of the above explains why dry deserts are HOTTER than water vapour rich rainforest.
Upwelling long wave surface radiation is obtained from Planck’s Law. Absorption of LW in CO2 and wv wavebands is also obtained from Planck’s Law by integrating the area under the curve. Traverse to extinction through the atmosphere is obtained from Steffan Boltzman knowing the emissivity for length of traverse and GHG concetration and equating it to the absorbed LW in W/m^2.
http://acmg.seas.harvard.edu/people/faculty/djj/book/bookchap7.html
7.5.2 Clouds
Feedbacks associated with changes in cloud cover represent the largest uncertainty in current estimates of climate change. Clouds can provide considerable negative feedback to global warming. We find from Figure 7-14 that the radiative forcing DF from an increase DA in the Earth’s albedo is
(7.24)
An increase in albedo of 0.007 (or 2.6%) since preindustrial times would have caused a negative radiative forcing DF = -2.5 W m-2, canceling the forcing from the concurrent rise in greenhouse gases. Such a small increase in albedo would not have been observable. We might expect, as water vapor concentrations increase in the atmosphere, that cloud cover should increase. However, that is not obvious. Some scientists argue that an increase in water vapor would in fact make clouds more likely to precipitate and therefore decrease cloud cover.
To further complicate matters, clouds not only increase the albedo of the Earth, they are also efficient absorbers of IR radiation and hence contribute to the greenhouse effect. Whether a cloud has a net heating or cooling effect depends on its temperature. High clouds (such as cirrus) cause net heating, while low clouds (such as stratus) cause net cooling. This distinction can be understood in terms of our one-layer greenhouse model. Inserting a high cloud in the model is like adding a second atmospheric layer; it enhances the greenhouse effect. A low cloud, however, has a temperature close to that of the surface due to transport of heat by convection. As a result it radiates almost the same energy as the surface did before the cloud formed, and there is little greenhouse warming .
Surely as well then regarding the supposed warming effect of co2 -( A low cloud, however, has a temperature close to that of the surface due to transport of heat by convection. As a result it radiates almost the same energy as the surface did before the cloud formed, and there is little greenhouse warming) co2 would cause little warming within this range.
NASA- clouds on average cause cooling.
“Using our technique, we calculate a short-term water vapor feedback of 2.2 W m–2 K–1. The errors associated with this calculation, associated primarily with the shortness of our observational time series, suggest that the long-term water vapor feedback lies between 1.9 and 2.8 W m-2 K–1.”
Any reader should keep in mind that so implying warming by increased LW absorption has not been shown to consider the net effect, where the net effect includes extra water vapor leading to extra clouds with increased SW reflection. For instance, as a thought experiment, if nearly no water vapor was entering the atmosphere, there would be nearly no clouds able to form either. Within temperature ranges above freezing, higher temperature tends to lead to increased SW reflection, with increased albedo via increased clouds.
“The overall reflectance (albedo) of planet Earth is about 30 percent, meaning that about 30 percent of the incoming shortwave solar radiation is radiated back to space. If all clouds were removed, the global albedo would decrease to about 15 percent, and the amount of shortwave energy available for warming the planet surface would increase from 239 W/m2 to 288 W/m2 (Hartmann 1994). However, the longwave radiation would also be affected, with 266 W/m2 being emitted to space, compared to the present 234 W/m2 (Hartmann 1994). The net effect of removing all clouds would therefore still be an increase in net radiation of about 17 W/m2. So the global cloud cover has a clear overall cooling effect on the planet, even though the net effect of high and low clouds are opposite”
http://www.climate4you.com/ClimateAndClouds.htm
(Hartmann 1994 may be an old publication, but that’s a bonus in ways: usually the older the publication, the less likely it is to have intentional error in data).
A runaway greenhouse effect doesn’t happen, and there isn’t just net positive feedback from additional evaporation of water vapor for:
an increase in a GHG (e.g. CO2 or a fluctuation in water vapor) -> warming -> more GHG release from the warming -> more warming -> more GHG release -> etc.
A couple of years ago I ran some MODTRAN tropical atmosphere calculations, and compared the predicted temperature change with “constant water vapor pressure” to “constant humidity.” (Note that constant humidity means water vapor pressure increases at higher temperatures.) It calculated a 1.65x greater temperature increase with constant humidity. In other words, water vapor amplification of CO2-induced warming was calculated to be only 65%.
Even including that amplification by water vapor, MODTRAN calculated that a doubling of CO2 from pre-industrial levels should only cause about 1°C of warming (and additional CO2 has a diminishing effect, due to saturation of the associated IR absorption bands):
http://www.burtonsys.com/climate/MODTRAN_etc.html
Additionally, water-cycle cooling should contribute a strong negative (stabilizing) feedback mechanism. Higher temperatures increase evaporation, which removes large amounts of heat of evaporation from the surface and carries it to the middle troposphere, where the heat is released when the water vapor condenses into clouds, rain & snow. (This is a classic refrigeration cycle, just like what happens in your air conditioner, except that the refrigerant undergoing the phase changes is water instead of Freon, and it’s the wet surfaces of the Earth being cooled instead of the interior of your home.)
Of course a linear tend line will give you a very clean answer. (Fig 4) I think you need to draw two lines around the data. One will have the slope shown (1.8) and capture the lower bounding line of the points a second will be much steeper in order to capture the upper bounds of data. Therefore the two slopes will define your upper and lower limits… Probably 2.2 +\- 0.4. ..Or so.
Does it matter whether it’s 1.8 or 2.2? Either way, it’s way less than the nearly 20 needed for alarm.
“Taking the Measure of the Greenhouse Effect ” http://www.giss.nasa.gov/research/briefs/schmidt_05/
“If, for instance, CO2 concentrations are doubled, then the absorption would increase by 4 W/m2, but once the water vapor and clouds react, the absorption increases by almost 20 W/m2 — demonstrating that (in the GISS climate model, at least) the “feedbacks” are amplifying the effects of the initial radiative forcing from CO2 alone.”
Of course, giss.nasa.gov is down at the moment but the science has spoken, is clear, uncontrovertable, and settled! (lol) Ok, well perhaps not all that but the ballance of the evidence would suggest that there’s nothing to worry about, expect mild warming from the burning of fossil fuels. When can we move on?
johnmarshall says:March 24, 2014 at 3:46 am
None of the above explains why dry deserts are HOTTER than water vapour rich rainforest.
Isn’t it because the sunlight is not absorbed by the atmosphere and heats the surface and cools radically at night, a 50°F cycle. It is the water vapor giving more mass to the atmosphere that stabilizes the temperature.
rain forest Vs desert – so effectively water vapour cools during the day and slows down cooling at night.
The Atacama proper is in Chile. Its northern extension in Peru is the Sechura Desert.
There’s a huge ball of fire in the sky throwing a tremendous amount of energy at the earth. There are things that affect the amount of energy that gets ‘in’. There are things which use or otherwise hold on to that energy.
Given the (large) amount of energy available to get through, and a fact established from the start, that temp rise precedes CO2 rise, I can’t help but dismiss CO2 (1part in 2500 compared to water vapour 1part in 30,000 of atmsph mass) from the (long) lineup of suspects. It seems to me that the huge reflective area of clouds would have the biggest effect ‘at source’, so to speak, and clouds being clouds, there will be a link between clouds and water vapour.
So the twist I see in this is that water vapour shows a link to temperature but only through its link to cloud cover, not its ability to hold a relatively tiny amount of the heat that does get through. As with CO2, I feel that water vapour is a result of warming. It can’t hold on to something that isn’t there in the first place.
Brain in gear, questions coming.
What happens to the ULWIR once it has been absorbed?
At what height is it absorbed? Is it mostly in the lower atmosphere?
Does the lapse rate change the amount reradiated After it has been absorbed?
@ur momisugly steve keohane
It is the need for latent heat used in the evapouration of water and the cloud formation due to convection and cloud tops reflecting heat to space. Deserts have near zero water so zero latent heat requirement. Deserts also have a higher temperature range than rainforest. another reality fact not covered by the GHE theory.
I’ve used a similar approach with the reannalysis data http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl. There is a highly correlated relationship between the dependant variable, difference between black body radiation at SST and OLR at TOA, and the independant variables of precipitation rate and precipitable water. I have observed that including CO2 concentrations with these factors in multi-regressions indicate an insignificant effect of CO2.
So all of this is cherry-picked on ‘clear sky’ data. How the f*ck do u get any reasonable, real life data from this. Is this some sort of surreal post? God, Willis, you can come up with better stuff than this.
Richard says:
March 24, 2014 at 2:58 am
The least amount of water vapor in the atmosphere is in the Antarctic where the frost point is the lowest.
Was the ceres data gathered on the UN declared cloud free day? Or were they looking at gaps between clouds etc. and then extrapolating the results over 1200 kms?
@chemengrls Thanks for that.
Follow up question. As the upwelling surface radiation as calculated by Planck’s Law is dependent on the temperature of the body concerned, how is an accurate planetary temperature derived?
So why does this water vapour distribution show regular gaps through the tropics?
http://www.fourmilab.ch/cgi-bin/Earth
None of the above. According to the Miskolczi greenhouse theory (MGT) water vapor feedback is effectively negative. His theory applies to a situation where more than one greenhouse gas are simultaneously absorbing in the infrared. Arrhenius, Fourier, and IPCC cannot handle this. In such a case a common optimum absorption window exists that the gases present jointly maintain. In the earth atmosphere the gases that count are carbon dioxide and water vapor. From radiation theory it can be shown that the optical thickness in the infrared of their joint optimum absorption window is 1.87. This corresponds to a transmittance of 15 percent or absorbance of 85 percent. If you now add carbon dioxide to the atmosphere it will start to absorb just as Arrhenius says. But this will increase the optical thickness. And as soon as that happens, water vapor will start to diminish, rain out, and the optimum absorption window is restored. Miskolczi showed this empirically by using NOAA weather balloon database that goes back to 1948 by measuring the change in infrared transmittance of the atmosphere over time. It turned out that infrared transmittance stayed constant for 61 years while atmospheric carbon dioxide at the same time increased by 21.6 percent. Addition of this substantial amount of carbon dioxide to air had no influence whatsoever on the absorption of IR by the atmosphere.There goes that greenhouse effect of Hansen. More currently, this is the reason why there is no greenhouse warming now despite the fact that atmospheric carbon dioxide is higher than ever and is still increasing. Lets now take a note of how laws of nature operate. You can’t turn them on or off to magically create a temporary hiatus. If the greenhouse effect is inoperative today it has always been inoperative. You will naturally want to know how come that this all started only 17 years ago. The answer is that it did not start 17 years ago, it has always been like that. The reason people think there was greenhouse warming before is simply because any previous warming designated as greenhouse warming has been misidentified by over-eager pseudo-scientists anxious to point to their favorite warming. This includes Hansen whose claim that he identified greenhouse warming in 1988 is false. He had a poorly resolved temperature curve with one year temperature intervals. That was not enough to show him that there were three El Nino peaks between 1980 and 1988. His peak heights were also incorrect and his “100 year” high point turned out to be nothing more exotic than an ordinary El Nino peak, the 1987/88 El Nino to be precise.
johnmarshall says:
March 24, 2014 at 6:57 am
@ur momisugly steve keohane
Enthalpy.
Rik says:
March 24, 2014 at 1:26 am
Do water vapour increase because temperature increased or do temperature increase because water vapour increased? How can we differ?
My thoughts precisely!
The whole GHG thing is a straw man. A spectroscope is a beautiful piece of instrumentation for determining the signature of molecules (IR range). It is not a thermometer. The term ‘absorption’ does not mean it is a heat sink. The term ’emission’ does not mean it is a power source. These are terms that are applied to the spectrum. They have little to do with thermodynamic properties. The mechanics/optics are set up to ‘see’ extremely directional light, fractions of a degree. Any molecule between the source and the final sensor is going to ‘interfere’ (simplified) with the direction of photons, thereby appearing as an absorption band. The reality is that the photon comes from one direction, is ‘absorbed’ and emitted again in some random direction, not necessarily in the direction of the sensor. The emission is going to occur in any possible direction. Approximately 41,500 directions based on 1 square degree on a globular surface. So it is no surprise that a detector with limited view is going to see a blank space. This does not mean that the molecule has retained this energy for any appreciable time. Any retention time is measured in microseconds. A spectroscope could also measure emission lines , but it would have to be extremely sensitive because the emissions would have a 1 in 41,500 chance of hitting the sensor. That is why you have absorption spectroscopy in IR and not emission spectroscopy.
If you were to have 2 spectroscopes set at 90 degrees to each other with a heating source in front of one and a cold source, say, liquid nitrogen cooled on the other. Then you would obtain an absorption and an emission spectrum at exactly the same time.
Therein ends my basic physics and instrumentation lesson. The boys that played with spectrums over 100 years ago had fun. Unfortunately some had drawn the wrong conclusions. We are paying for it now
A positive water vapor feedback of 1.8 +/- 0.001 W/C is actually a little higher than the IPCC AR 5 estimate of 1.6 +/- 0.3 W/C
See table 9.5 http://www.climatechange2013.org/images/report/WG1AR5_Chapter09_FINAL.pdf
This means that this calculation gives a higher contribution to climate sensitivity from water vapor than the IPCC models, which is inconvenient seen from a climate sceptics point of view
Science sometimes gives surprising results. So I congratulate you Willis, with a good and honest job, good scientists do not silently throw inconvenient results away.