Observing water vapor feedback during 'the pause'

From AGU highlights, measurements from 2002 to 2009 show short term feedback still subject to short-term climate variability, long term feedback still in the realm of models.

Measuring the effect of water vapor on climate warming

Water vapor is a potent greenhouse gas. In the atmosphere, the concentration of water vapor increases with the temperature, setting up a powerful positive feedback loop. This water vapor feedback is the strongest known positive feedback, with the potential to roughly double the effect of warming caused by other sources. Determining the exact strength of the water vapor feedback, then, is incredibly important to limiting uncertainty in future climate change projections. 

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. This value, however, is only the “short-term” feedback—the strength of the feedback as measured during the observational period. This value is subject to short-term climate variability. The true value of the feedback, the “long-term” value, is what the short-term observed values should trend towards when given enough time.

Using a series of climate models, the authors estimate the strength of the long-term water vapor feedback. Extrapolating from their short-term observations they calculate a long-term feedback strength of 1.9 to 2.8 watts per square meter per degree Celsius. They find that most models get to within 15 percent of their long-term value within 25 years. The accuracy of calculations, then, could be improved with a longer set of observations.

Source: Journal of Geophysical Research-Atmospheres, doi: 10.1002/2013JD020184, 2013 http://onlinelibrary.wiley.com/doi/10.1002/2013JD020184/abstract

Title: An observationally based constraint on the water-vapor feedback

Authors: N. D. Gordon: Lawrence Livermore National Laboratory, Livermore, California, USA; A. K. Jonko: National Center for Atmospheric Research, Boulder, Colorado, USA; P. M. Forster: School of Earth and Environment, University of Leeds, Leeds, UK: K. M. Shell: College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA.

Abstract:

The increase in atmospheric concentrations of water vapor with global warming is a large positive feedback in the climate system. Thus, even relatively small errors in its magnitude can lead to large uncertainties in predicting climate response to anthropogenic forcing. This study incorporates observed variability of water vapor over 2002–2009 from the Atmospheric Infrared Sounder instrument into a radiative transfer scheme to provide constraints on this feedback. We derive a short-term water vapor feedback of 2.2 ± 0.4 Wm−2K−1. Based on the relationship between feedback derived over short and long timescales in twentieth century simulations of 14 climate models, we estimate a range of likely values for the long-term twentieth century water vapor feedback of 1.9 to 2.8 Wm−2K−1. We use the twentieth century simulations to determine the record length necessary for the short-term feedback to approach the long-term value. In most of the climate models we analyze, the short-term feedback converges to within 15% of its long-term value after 25 years, implying that a longer observational record is necessary to accurately estimate the water vapor feedback.

 

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RS

Seeing that atmospheric CO2 was over 1000 and as much as 8000 ppm in dinosaur days without the planet going Venus, I would say that there is no strong positive feedback loop.

Berényi Péter

The notion of strong positive water vapor feedback is not supported by observations. We have slightly more than 13 years of CERES radiative balance measurements right now, which have their own problems, but still, they indicate a pretty attenuated response to increasing carbon dioxide mixing ratio.

Isolate the water vapor variable from all other possible feed backs in the real world, clouds, precipitation, aerosols,, then plug it into faulty models and create the scenario that fits the established projections —- catastrophe.

Bill Illis

Full paper at:
http://www.researchgate.net/publication/259534208_An_observationally_based_constraint_on_the_water-vapor_feedback/file/9c96052cf1064dc1af.pdf
This paper derives water vapor feedback from 2002 to 2009 to be 2.2 W/m2/1.0C. This amount is roughly equivalent to an increase in water vapor of 7.0% per 1.0C increase in temperatures which is also the number that is derived from the Clausius Clapeyron relation and is central to the global warming theory.
The recent IPCC AR5 report revised their water vapor feedback assumption down to 2.0 W/m2/K from 2.3 W/m2/K in previous reports. This AR5 feedback value results in a CO2 sensitivity of 2.52C per doubling (including the values for the other feedbacks like cloud and albedo) but for some reason, this sensitivity number was not outlined in the report.
But here is a far longer timeseries of water vapor feedback going from 1948 to Feb 2014. Its from NCEP Reanalysis (starting in 1948) and from RSS (starting in 1988) which uses SSM/I F08 through F15, SSMIS F16 and F17, AMSR-E, WindSat and cross-calibrates with ground-based GPS water vapor data demonstrate. This then includes far more data than this study which just uses the AIRs satellite data.
So this chart shows water vapor back to 1948 and the forecasts from IPCC AR5 (which is lower than this study) and also the ENSO since it seems to be the main governing factor.
http://s27.postimg.org/eexakr5wz/ENSO_PCWV_48_Feb14.png
Yeah, the models are way off.
In addition, if one starts the data at 2002 and then ends in 2009, right at the height of a very large El Nino, you are going to get a large positive feedback value. But this cherrypicking.
Starting in 1958 versus the lower troposphere temps, the water vapor feedback is only 4.14% per 1.0C versus the 7.0% in the theory (and the numbers from this study.)
http://s21.postimg.org/5g73ffe87/Temps_vs_PCWV_Scatter_1958_Feb14.png
This feedback rate is enough to drop the climate sensitivity to 1.8C per doubling rather than 2.5-3.0C in the theory.
All water vapor studies from pro-global warming scientists cherrypick starting and ending timelines to take advantage of the ENSO conditions.

Guess I ought to wait until someone else takes this to bits, but it is really becoming tiresome.
“Radiative transfer”? If that was all that is involved I would not be here writing this. Don’t they know that the effect works in both directions? Eg cloudy days are cooler than sunny days? And at night, sure, it takes longer for the heat to escape if there is cloud overhead here at 19°S but it is still gone well before sunrise.

Pete

Question from a non-scientific learned person …
If, as some have said, the warming impact of increases in CO2 have been significantly overstated (thereby making CO2’s impact fairly low) does it therefore appear that a key driver of warming assuming a more “nature-driven” warming (ie., termination of the Little Ice Age circa mid-19th Century) is water and/or water vapor?
Many thanks for your insights.
Pete

milodonharlani

Bill Illis says:
March 11, 2014 at 5:36 pm
Like, totally awesome, dude!
Actually, I’m surprised that IPeCaC´s assumption is even that close to observations (4.14% v. 7.0%).

Why is water vapor considered feedback to enhance the CO2 “greenhouse effect” when it is a “greenhouse gas” at concetrations much greater. The direct greenhouse effect of water vapor is probably at least an order of magnitude greater than any CO2 effect. Add clouds and it gets even more complex.

chris y

Hmmm.
They derive a short-term, all-in water vapor feedback of 2.2 W/Km^2. Now, doubling CO2 is equivalent to about 3.7 W/m^2 and results in about 1 K of temperature increase before feedbacks kick in. That means the water vapor positive feedback is (3.7+2.2)/3.7 = 1.6.
That is, a 1 K temperature increase from CO2 results in an additional warming of 0.6 K from water vapor feedback.
Put another way, CACC has been ‘nailed to its perch.’
Why is this positive feedback so much lower than previous claims?
Since they have found positive water vapor feedback based on measurements, did they also mention where the water vapor induced tropospheric hot spot is hiding? Perhaps below 2000m in the oceans?

pokerguy

“Determining the exact strength of the water vapor feedback, then, is incredibly important to limiting uncertainty in future climate change projections.”
Sorry, pet peeve of mine but risking being called a pointy headed nitpicker because I think it weakens an important post. Of course you don’t mean “incredibly important.”
“Important” by itself is sufficient. Or you could use “critical,” or “crucial.”

pokerguy

Oops, never mind. I missed who wrote this. My bad.

Gary Pearse

Bill Illis says:
March 11, 2014 at 5:36 pm
The temperature record has been fiddled upwards on the recent end and downwards on the earlier end (recent end constrained, thank goodness, by satellite measurements), particularly by Hansen who had a mission to get rid of the exasperating 1930s records in the USA in 1998 because he saw this El Nino as the last chance to get a new global temperature high. We seem fated to use this abused record. Hadcrut 4 was a way to exploit the incomplete coverage of the polar regions by satellite and the “amplification” permitted lifting the recent temps a bit as did a recent paper purporting to show that there was not ‘pause”. Willis with Ceres data showed the amplification was countered by lower heating in the tropics so the adjustment wasn’t necessary.
I think 4.14% water vapor increase is an index of the cooking the temperature record has taken. Probably, in reality, it represents 4.14/7.0 *1.0 degree Celsius as the amount of temp rise we are talking about. This works out to 0.59 degrees C temperature rise. Yeah, that’s about right they’ve jacked it up several tenths of a degree. I see that Clausius Clapeyron is going to be helpful when we come to undo the damage done by zealots. It also shows how naive it is to think you can fiddle with a part of such a complex system without screwing up other parts.

BioBob

“2.2 plus or minus 0.4 watts per square meter per degree Celsius”
Is that with an African or a European swallow’s tailwind ? Or both with a string?
The purported precision of these “global studies” is always hilarious and instructive.

Gary Pearse

Actually the plateau in temperatures is probably part of the screw up. If you raise these temps too steeply, you end up starting the plateau too early and making it too long. Let’s not let any of these linear thinkers undertake any geoengineering – the unintended consequences certain to occur could ruin a perfectly good planet.

Curious George

Where exactly do clouds appear in Clausius Clapeyron? Or in models?

Kit Blanke

Let’s see now. Increased heating, more water vapor, more clouds, increased albedo, less heating.
Looks like negative feedback to me.

Bill Illis

We should recognize that water vapor does go up with increased temperature (and down with decreased temperature). Specific Humidity does go up when it gets warmer. The tropics have far more water vapor in the atmosphere than does the poles. The Clausius Clapyeron equations are mostly right.
It is important to understand that climate science and the water vapor feedback is not one single feedback loop. It feeds back on itself so that there are several rounds of temperature increases which then leads to more water vapor which then leads to more water vapor increase which then …. and so on and so on. It really take a loop of about 11 feedbacks on feedbacks before the diminishing impacts set in and there are no more temperature impacts from increased water vapor.
11 feedbacks on feedbacks rather than 1.
So a very small change from 7.0% per 1.0C or 2.2 W/m2/K results in a big change in the eventual temperature change from a 1.2C increase in temperatures from a doubling of CO2 (if one assumes this was calculated correctly and I don’t necessarily believe that either).
But if one does accept the 1.2C from CO2 doubling, the X.X W/m2/K water vapor feedback value is then carefully chosen so that it does not result in a runaway greenhouse impact or a minimal greenhouse impact. Double the assumed water vapor feedback assumption to 4.4 W/m2/K and one gets 35C of temperature change per doubling of CO2. Drop it by half to 1.1 W/m2/K and one gets just 1.6C of temperature increase per doubling.
So a small change in the way the real Earth(tm) responds to GHG increases is indeed a very important change in the eventual warming.
Make clouds a negative -0.75 W/m2/K (instead of a positive 0.75) and drop the water vapor feedback to 4.14% per 1.0C (as the actual data shows), then the climate sensitivity is only 1.1C per doubling.
Climate science did these little feedback assumption calculations long ago and decided to keep all the assumptions at rates which would result in 3.0C per doubling. They then built these numbers into their climate models.
It is important to find out how the real Earth(tm) responds because it is a make or break on the eventual warming. Climate science likes to reinforce itself rather than find out what’s really happening. And they are willing to adjust temperature records (which is why I use the lower troposphere non-adjusted ones) and why they cherrypick timelines to keep the feedback assumptions at the right level. Much money and reputation is at stake.

Gail Combs

fhhaynie says: @ March 11, 2014 at 5:51 pm
Why is water vapor considered feedback to enhance the CO2 “greenhouse effect” when it is a “greenhouse gas” at concetrations much greater….
>>>>>>>>>>>>>>>
Because CO2 is a wimp. Only by adding in H2O as a ‘Feedback’ of CO2 can you get Catastrophic Global Warming and even then you have to completely ignore the fact H2O unlike CO2 changes phases thereby giving you Willis’s Thunderstorm Thermostats

Box of Rocks

Combined with a radiative transfer model,
*****
Model based upon what?

FrankK

The same old pseudo-science. Neatly summarised by the following:
http://kitshaper.files.wordpress.com/2011/08/cga0226l1.jpg

Edim

In average, the surface cooling by evaporation is greater than the claimed water vapor GHE. So, H2O is cooling the Earth’s surface overall (net cooling effect). Even the consensus agrees with this.

Steve Case

Gordon, Jonko & Forster ignore clouds, never mention ’em, but posters at “Watts Up With That” bring ’em up right way. Why do you suppose that is?

Berenyi
AIRS is observations. In fact you might want to familiarize yourself with the sensors.
Launched in 2002 it will fly until 2020.

M Seward

Allegedly increased water vapour means increased latent heat of vapourisation shunting energy to the upper atmosphere and out into space a la Trenberth diagram as part of an energy flow about 200 times greater than the 0.4 Watts/sq metres from C02. 1 kg of water evaporated can cool about 2000 kg of air by 1˚C. Sound very much like a negative feedback to me and that is before we talk about clouds.
The paper sounds like more good for a goose therefore good for propaganda to me.

Box of rocks.
The radiative transfer models are engineering. Your cell phone was designed using them. Radar design uses them. UAH uses them. Stealth fighters were designed using them.
Ir astronomy uses them. All sensors in space rely on them. Given the atomospheric conditions they calculate the transmission absorbtion and reflection of EM.

After a very short time gathering information, they fired up the old computers withe their models and wrote up this paper. Give us a bunch of money to really do a study!
Ever wonder about the quality of peer reviewed published scientific papers.
Do scientific papers ever seem like unreadable gibberish to you? Well, sometimes they really are. Some 120 papers published in established scientific journals over the last few years have been found to be frauds, created by nothing more than an automated word generator that puts random, fancy-sounding words together in plausible sentence structures. As a result they have been pulled from the journals that originally published them.
http://www.foxnews.com/science/2014/03/01/over-100-published-science-journal-articles-just-gibberish/
Some professors said that pay rules that base professor salaries on the number of papers they publish may lead to fakes.“Most schools have merit raise systems of some kind, and a professor’s merit score is affected by his or her success in publishing scholarly papers,”
A fatter paycheck may be the driver, not the science. pg

NotAGolfer

In coal combustion, for every molecule of CO2 produced during combustion, 1 molecule of H2O is produced. In natural gas combustion, for every CO2 molecule produced, 2 molecules of H2O are produced. What makes them think that the increased water vapor is from feedbacks, rather than being directly evaporated into the atmosphere from energy plants?

BioBob

>> Steven Mosher says: radiative transfer models uses them.
And I am sure all sorts of global, regional & local climate models use them & other things as well. But at some point of upscaling, all models meet their match. There is not a model created that can accurately predict results of chaotic heat engine effects (weather) past a few days in the future.
There ARE some things that exceed our capabilities.

Bart

“The true value of the feedback, the “long-term” value, is what the short-term observed values should trend towards when given enough time.”
OR, the estimated short term ‘value’ reflects just short term random fluctuation, and the actual long term value is totally other. Reminds me of Dessler’s awful analysis, where he assumed an instantaneous response, and got a result which was basically just jumping at shadows.

Steven Mosher says:
March 11, 2014 at 7:07 pm (replying to)
Box of rocks.
The radiative transfer models are engineering. Your cell phone was designed using them. Radar design uses them. UAH uses them. Stealth fighters were designed using them.
Ir astronomy uses them. All sensors in space rely on them. Given the [atmospheric] conditions they calculate the transmission [absorption] and reflection of EM.

OK, I’ll bite.
Now, your much-vaunted, much treasured radiation models and General Circulation Models are all developing the myth of catastrophic global warming over the next 100-200 (up to 1000 years!) based on a “calculated” difference of (energy absorbed – energy lost) of only 3.0 watts/m^2 (worldwide, of course). This after a top-of-atmosphere radiation of 1314 1410 per m^2 that varies day-by-day over the year.
Now, you have placed your personal trust and reputation on these models.
Therefore, show me the actual calculated “from-these-models” values for the ocean, for every 10 degrees of latitude, for the 22nd of every month of the year for 12:00 noon and 24:00 midnight the following values for the year 2013 of their model run – AND THEIR ERROR ESTIMATES.
1) Longwave radiation losses to Tsky (and the value of Tsky assumed for that date, and the estimated value of emissivity for that Tsky you have assumed..)
2) Evaporation losses per square meter, wind speed assumed to predict that calculated evaporation loss, humidity and air temperature assumed to predict that assumed evaporation loss.
3) Convective radiation losses per m^2, wind speed assumed, air temperature assumed and water temperature assumed.
If the models – globally and universally over 100 years are accurate – then the models’ specific information at specific latitudes and specific times of the day and days of the year on a specific year’s date will be accurate and can be checked. Right?
And, if the entire CAGW mythology is based on a 3 watt/m^2 difference spread over 100 years in the future, then – on a year when actual data is available – the models’ actual results for specific areas on a global-ocean-basis-by latitude are going to be accurate against measured data for those dates on a year only 1 year past, right?

Crispin in Waterloo

About 10 years ago at breakfast I bumped into a professional European global warming-monger who was in Johannesburg to alarm the Government of South Africa’s Transportation Ministry. He showed me a set of printed charts and figures he was presenting to the Minister in an effort to convince them to spend vast sums of money on ‘solving the crisis’. Of course it included M Mann’s fake hockey stick temperature chart which I pointed out was nonsense.
He disagreed with that and we disagreed about something else which was newly in vogue at the time which was trying to claim that water vapour in the atmosphere was “only a feedback” meaning that without CO2 the Atmosphere wouldn’t have any. If you recall Gavin at RC was making similar claims at that time. It was widely repeated in discussion fora. The hope was apparently to shout it long and loud enough so it would not be challenged. A more brainless assertion about atmospheric physics it is hard to imagine.
This paper rides on the wave of ignorance given impetus by that professional alarmist to South Africa hoisted on the staff of ‘Water vapour is only a GHG once it has been turned into one by CO2’. If it were true, then the warming by CO2, as imagined, could be divided into the water vapour concentration as other GHG’s are merely nominal. Presto, water vapour feedback. Calculate away.
But the assertion is bunk. On a water planet there would always be water vapour even it it started off as sublimated ice. The temperature above a cold, atmosphere-less Earth is largely caused by water vapour and it’s water vapour-induced feedback. The heating is constrained by the formation of clouds as is well known to readers of proper scientific investigations of the matter.
Of all the forcing experienced, most is water vapour and a small fraction is caused by CO2 which of course adds a tiny additional amount of water vapour, causing the clouds to shut off the sun that little bit sooner. This is not even complicated. The upper limit to ocean temperature is about 31 Celsius after which negative feedbacks overwhelm all positive feedbacks. Ultimately additional CO2 can only warm Earth in places where it is not already in a state of net feedback stasis.

Katherine

fhhaynie says:
Why is water vapor considered feedback to enhance the CO2 “greenhouse effect” when it is a “greenhouse gas” at concetrations much greater. The direct greenhouse effect of water vapor is probably at least an order of magnitude greater than any CO2 effect. Add clouds and it gets even more complex.
Because the government can’t claim water is a pollutant—at least not water vapor. They need something else to limit and tax.

We all know that the short term water vapor feedback is positive, that is, a short term temperature increase causes an increase in specific humidity. Climate models assume that the long term water change is similar, but that assumption disagrees with multiple datasets. Other things change to reduce or eliminate the water vapor response in the upper atmosphere where its effects dominate the greenhouse effect. Only upper atmosphere water vapor “matters”. Calculations by line-by-line code computer programs show that a water vapor change at 200 to 300 mb pressure level (9 to 11 km) has 81 times the effect on OLR than the same change in the 1013-850 mb near-surface layer. Graph here:
http://www.friendsofscience.org/assets/documents/FOS%20Essay/OLR_PWV_bar.jpg
The annual NOAA specific humidity data, 1960 to 2013, shows linear striations increasing from bottom left to top right, confirming that higher temperatures relate to higher specific humidity over short time intervals at the 400 mb layer (8 km). But the overall trend is down, proving that specific humidity in the upper atmosphere declines with increasing temperatures over longer time scales.
Graph here:
http://www.friendsofscience.org/assets/documents/FOS%20Essay/SH400TropicsVsTemp.jpg
If water vapor increased over time with warming, there would be an enhanced warming rate in the tropics in the upper troposphere at least double the surface warming rate. (This is because increased water vapor changes the lapse rate.) But balloon and satellite measurements show no such enhanced warming. Graph here:
http://www.friendsofscience.org/assets/documents/FOS%20Essay/spencer-models-epic-fail.jpg
So either the balloon humidity AND balloon temperature data AND satellite humidity AND satellite temperature data are very wrong (but all agree with each other), OR the climate model assumption is wrong. This paper just assumes the climate model assumption is correct and ignores the long term data.

Crispin in Waterloo

Ken Gregory:
Very well said. As I mentioned above, another assumption is that water vapour (all of it) is ‘feedback’. I would like to add, ‘I don’t know how they can get away with it,’ but they can’t. Certainly not around here.

davidmhoffer

Steven Mosher says:
March 11, 2014 at 7:07 pm
Box of rocks.
The radiative transfer models are engineering. Your cell phone was designed using them. Radar design uses them. UAH uses them. Stealth fighters were designed using them.
Ir astronomy uses them. All sensors in space rely on them. Given the atomospheric conditions they calculate the transmission absorbtion and reflection of EM.
>>>>>>>>>>>>>>>>
Steven,
You use this explanation often. It doesn’t matter how often you use it, IT IS WRONG
The examples you give are all predicated on sensors that measure what goes through the atmosphere. The debate here is about what DOESN’T go through the atmosphere. That is something that we cannot measure directly with sensors for the simple reason that it gets absorbed and never gets to the sensor to be measured. Please stop propagating this notion. It is confusing and absolutely incorrect.

catweazle666

This is complete BS.
Solomon et al showed a decrease in atmospheric water vapour of approximately 10% over the decade post 2000, Humlum and Vonder Vaar show no visible trend from ~1980.
Oh, hang on, we’re talking computer games again, aren’t we?
Jolly good. Carry on.

SIGINT EX

Epic AGU Fail.

Chad Wozniak

It’s my understanding that in lab experiments at least, water vapor has been shown to reduce, not increase, the greenhouse effect of CO2 (such as that may be) – someone please correct me here if I am wrong. But in any event, there is so much more water vapor in the air all the time – except in the very driest and coldest places, it’s 30 to 140 times as much as Co2, depending on temp and humidity. If, as also appears to be the case, water vapor is many times more powerful than CO2 as a greenhouse gas (the figure I keep hearing is 8.5 x) – then the greenhouse effect of water vapor is hundreds of times that of CO2, no matter how the latter is enhanced – if it is enhanced at all. This would seem to reduce the effect of CO2 to statistical insignificance by itself, even without considering the Sun or ocean current oscillations.

Arno Arrak

Problem with these guys is that they think water vapor feedback is positive when it is actually negative. How do you think the hiatus could still persist if there were positive water vapor feedback? The hiatus can only be explained by the Miskolczi theory that applies when more than one greenhouse gas are simultaneously absorbing in the IR. In such a case, an optimal absorption window exists that they jointly maintain. For the earth atmosphere the gases that count are carbon dioxide and water vapor. The optical thickness of their joint absorption window in the IR is 1.87. This comes from first principles and is experimentally observable. If you now add more carbon dioxide to the atmosphere as we constantly do it will start to absorb, just as IPCC tells us. But this will increase the optical thickness and water vapor will immediatly react by diminishing its concentration, raining out, until the original optical thickness is restored. This is in fact negative feedback because it counteracts, instead of increasing, total IR absorption from CO2. That is the explanation of why constant addition of carbon dioxide to the atmosphere cannot cause any greenhouse warming. Its further implication is that there cannot be any such greenhouse warming that Hansen imagines having discovered in 1988.

Jim

Imagine how amazing it would be to discover greenhouse gases do the exact opposite of what they are claimed to do. Water vapor – a significant greenhouse gas! when the earth gets warm it puts out more water vapor, a natural thermal response of water to heat. When oceans warm up their ability to retain dissolved carbon dioxide decreases so it too follows along and begins to build up in the atmosphere. This is how the earth looses heat, by conducting it to space via thermally interactive gases. Just referring to the atmosphere as being like a greenhouse is very elementary nieve and wrong..

Konrad

H2O is the working fluid of a giant vapour-condensate heat pump removing energy from the surface by non-radiative transport and dumping it to space via LWIR radiation. This is the primary cooling mechanism for the surface and atmosphere of our planet.
Lets examine “strongly positive water vapour feedback” –
Strike 1. To be produced, water vapour must be evaporatively cooling the surface.
Strike 2. Water vapour increases the buoyancy of air masses, the speed of vertical convective circulation and the speed of non-radiative energy transport from the surface.
Strike 3. Water vapour increases the radiative cooling ability of the atmosphere.
But, but but, what about increased down-welling LWIR?! DWLWIR has little or no effect on the cooling rate of the oceans or vegetated areas. Thock! (That ball gets them as they are slinking from the field.)

otsar

This paper seems to be only addressing one of the phases of H2O. There are two others that produce different feedbacks, depending on the physical configuration: water droplets as in clouds, liquid water in the oceans, ice and snow.

Alcheson

I didn’t see any mention of clouds. Higher water content should also mean more clouds which are more consistent with negative feedback if I understand Spencer’s work correctly. Also more water in the atmosphere should also increase convection of heat from the lower atmosphere to the upper (a negative feedback). Warm moist air from the ground is less dense and rapidly rises thru the atmosphere, releasing it’s heat and falling back down to the ground in the form of rain. So to say the water is a positive feedback, and neglect to take into account all forms of water and various cycles seems to be less than honest with the aim of promoting the CAGW agenda. Also, if water is such a strong positive feedback, why has there yet to be any runaway global warming in earth’s history so far?

Water. water vapor and solid water have significant different IR absorption characteristics, here is a link to a study that provides the evident ,look it up: Water absorption spectrum by Martin Chaplin.
The report below proves that “water” in all it phases are negative feed back.
The Greenhouse Effect . . . Explored
Is “Water Vapor Feedback” Positive or Negative?
Carl Brehmer
© February 21, 2012
Abstract
An essential element of the “greenhouse effect” hypothesis is the positive “water
vapor feedback” hypothesis. That is, if something causes an increase in the temperature
this will cause an increase in the evaporation of water into water vapor. This new
humidity will absorb more of the infrared radiation coming off of the ground. This
increased absorption of infrared radiation is believed to warm the air even further. This
makes the air able to hold even more water vapor and this result in even more
evaporation, which increases the humidity even further and the cycle starts over. This is
called a “positive” feedback, since water vapor is believed to amplify atmospheric
warming. Being curious about the truth of this hypothesis I designed a simple
experiment to study the effect of rising and falling levels of humidity on soil and air
temperature and discovered that 1) the addition of water to a climate system exerts a
significant negative feedback against temperature changes night and day, 2) water vapor
has the same graphical relationship to temperature that insulin has to blood sugar and
insulin is known to exert a strong negative feedback against blood sugar levels and 3)
over the course of time the addition of water to a climate system causes a perceptible
drop in the yearly mean temperature.
Materials
1) Homemade Stevenson Screen with Temperature and Humidity Data Logger 4’10”
off of the ground.
2) Thermocouple attached to a Data Logger to acquire simultaneous soil surface
temperatures.
3) Internet records of yearly mean temperature and humidity readings for several
major cities in the world with contrasting climates.
4) Computer spread sheet to compile data and create graphs.
Procedure
Part #1:
1) Using 38 consecutive days of data harvested from the Stevenson Screen and
thermocouple I calculated the mean dew point over that 38 day period and
separated the days between those that fell above the mean, which I call “humid”
days, and those that fell below the mean, which I call “arid” days.
2) I then graphed the mean temperature curve of the “arid” days against the mean
temperature curve of the “humid” days to see what affect different levels of
humidity had on the daily temperature curve, specifically looking for a positive
feedback waveform, which we will discuss in more detail below.
Part #2:
1) Using two consecutive months of data harvested from the Stevenson Screen I
calculated the mean daily temperature and graphed it against the mean daily dew
point to see what the relationship is between ongoing temperature changes and the
dew point, which by the way is an accurate reflection of the absolute humidity,
again, specifically looking for an indication of positive feedback.
Part #3:
1) I selected four sets of cities with the following criteria:
a. A pronounced difference in their humidity levels
b. They were both be about the same distance above the equator so that they
both receive roughly the same amount of sunlight each day throughout the
year
c. They were both inland far enough not to be affected by sea breezes
2) With data harvested off of the Internet I compared the temperature (adjusted for
altitude) and the absolute humidity of these four sets of “arid” vs. “humid” cities,
looking for the effect that increased humidity has on the temperature of their
respective climates asking the question, “Does increasing the humidity cause a net
increase in the air temperature as the ‘greenhouse effect’ hypothesis along with
the “water vapor feedback” hypothesis says that it should?”
Findings:
Part #1:
An increase in the absolute
humidity produced a strong negative
feedback against temperature changes
day and night in that it inhibited
daytime warming and slowed nighttime
cooling as can be seen in this graph
which plots the mean temperature curve
of the “arid” days against the mean
temperature curve of the “humid” days.
Part #2:
a) When plotting two month’s worth
of daily mean temperatures against
the daily mean dew points, as seen
in this graph, I found that as the
mean temperature rose and fell
there was a strong correlation
between rising and falling dew
points levels as well, although the
change in the dew point lagged
behind the temperature changes by
about a day. This is the same relationship that rising and falling blood sugar has to
Fig. #2 Mean Temp vs. Mean Dew Point
Fig. #1 Affect of Humidity on Daily Temp Curve
rising and falling levels of insulin in that the waveform of insulin also echoes
changes in blood sugar levels while lagging behind the blood sugar in time. Since
insulin is known to exert a strong negative feedback against rising blood sugar
levels, this two-month long graph is consistent with humidity being a negative
feedback against increasing temperatures.
b) What bolsters this idea is the fact that it rained near the beginning of this twomonth
period and as the soil dried out over time the humidity levels trended
downward while the temperature trended upward, which again is consistent with
humidity being a negative feedback against increasing temperatures.
Part #3:
The four sets of cities that I used for my comparative study between “arid” and
“humid” climates were: Phoenix vs. Dallas, Las Vegas vs. Knoxville, Death Valley vs.
Huntsville, Riyadh, Saudi Arabia vs. Bogra, Bangladesh. In all four cases the more
humid climate had a significantly cooler yearly mean temperature than the arid climate.
Discussion
Scientific Definition of “feedback”:
So, let’s discuss these findings. Before we can identify the signature
characteristics of positive and negative feedback waveforms in the temperature record we
need to understanding of what a “feedback” is in science. The scientific definition of
“feedback” is this: “When the result of an initial process triggers changes in a second
process that in turn influences the initial one. A positive feedback intensifies the original
process, and a negative feedback reduces it.” 1
1 Working Group I: The Scientific Basis, Appendix I – Glossary, http://www.ipcc.ch/ipccreports/tar/wg1/518.htm
Fig #3 Phoenix vs. Dallas
Fig #6 Riyadh vs. Bogra
Fig #4 Las Vegas vs. Knoxville
Fig #5 Death Valley vs. Huntsville
To better understand this scientific definition of “feedback” let’s look at some
well known examples of positive and negative feedback. The first example that we will
look at is the body’s regulation of blood sugar levels through the negative feedbacks
exerted by the hormones insulin and glucagon.
This graph is a simulated curve of blood
sugar levels for about five hours after a meal.
Shortly after a meal is eaten blood sugar begins to
rise and in response the body releases insulin
whose effect is to lower blood sugar. Insulin’s
effect is called a negative feedback because it
counteracts the rise in blood sugar seen after a
meal. When the blood sugar begins to drop the
insulin level drops as well.
To keep the blood sugar from falling too
far too fast and to maintain a basal level of blood
sugar between meals the body releases a second
hormone called glucagon and its effect is
opposite that of insulin in that it works to slow
falling blood sugar. Insulin slows rising blood
sugars and glucagon slows falling blood sugars.
So even though the action of glucagon is
opposite that of insulin they are both negative
feedbacks because they counteract changes in
blood sugars rather than amplify them. Again, if
blood sugars are increasing insulin kicks in to
slow that increase and if blood sugars are
decreasing glucagon kicks in to slow that
decrease. As you can see this graph, a “second
process” that creates a negative feedback can
either be in phase or out of phase with the “initial
process.”
What makes feedback positive or negative then is not the direction of its force but
whether or not it inhibits or amplifies the change that triggered it. In nature negative
feedbacks create stability while positive feedbacks create instability.
Glucagon
Blood Sugar
Insulin
Meal
Fig. #7 Blood Sugar Curve After a Meal
Blood Sugar
Insulin
Fig. #8 Insulin Curve After a Meal
Glucagon
Fig. #9 Glucagon Curve After a Meal
Blood Sugar
Blood Sugar
Fig. #10 Blood Sugar, Insulin & Glucagon Curves After a Meal
Meal
Meal
These are two generic graphs of positive and negative feedbacks, one ascending
and one descending. The positive feedbacks are in red and the negative feedbacks are in
blue. As you can see, positive feedback amplifies the change while negative feedback
attenuates the change regardless of whether the direction of change is up or down.
If these graphs were of temperature curves then a positive feedback could either
cause greater warming or greater cooling depending upon the time of day. For example,
it is said that “water vapor feedback” is positive because it is believed to amplify
warming. If an increase in humidity were shown to amplify nighttime cooling that would
be a positive feedback as well, because that would amplify the temperature change
already occurring–cooling. I only bring this up because ironically the most common
example offered as proof that water vapor feedback is positive is the fact that humid
nights cool more slowly than arid nights and this is actually a negative feedback against
nighttime cooling. This is more than just a matter of semantics, because remember in
nature negative feedbacks bring stability while positive feedbacks bring instability. If we
mislabel a negative feedback and call it positive feedback, we might be led to believe that
the addition of humidity to a climate system will destabilize it!
Let’s turn our focus to positive
feedback for a minute. As you can see in
this graph, examples of positive feedback
have a distinctly different look. They
have a signature exponential curve that
usually ends abruptly because of a
“terminating event.”
An example of positive feedback
in nature can be seen in the labor pains of
childbirth. Known as the “Ferguson Reflex” each contraction stimulates a higher release
of the hormone oxytocin, which increases the strength and frequency of the contractions.
The “terminating event” is the birth of the child at which time contractions abruptly stop.
Another example of positive feedback is the squeal heard through a PA system when the
microphone is placed near the speaker and sound from the speaker is picked up by the
mic and fed back through the amplifier. Everyone hears an abrupt loud squeal that
terminates just as abruptly when the speakers blow, the mic is moved away from the
Fig. #11 Positive and Negative Feedback – Ascending Fig. #12 Positive and Negative Feedback – Descending
Terminating Event
Fig. #13 Positive Feedback Waveform
Exponential Curve
speaker or the amp is turned off. Another example of positive feedback is the growth in
the debt of a company whose expenses are consistently greater than its receipts year after
year. Its debt will continue to grow exponentially until it is terminated by bankruptcy.
The signature trait of a positive feedback waveform is that it is very “spiked”
compared to the rounded waveform seen in negative feedback.
Departing from this classical scientific definition of “feedback” contemporary
literature defines positive water vapor feedback one-dimensionally and implies that
positive water vapor feedback always results in a warmer temperatures and when you see
a counter argument that asserts that water vapor feedback is negative the term is also used
one-dimensionally and implies that negative water vapor feedback always results in a
cooler temperatures. Again, positive feedback will only result in a warmer temperatures
and negative feedback will only result in a cooler temperatures if the basal temperature is
already trending warmer as it does every day from sunrise to mid afternoon. If the basal
temperature is trending cooler as it does predictably and repeatedly every night then
positive feedback would make the temperature even cooler and a negative feedback
would result in a warmer temperature at the end of the night.
The Experiments (Part 1):
Using this understanding of the scientific definition of “feedback” let’s take a
look at the results of my experiments starting with the study of the effect of humidity on
the daily temperature curve.
For 38 days I measured soil
and air temperatures along with the
dew point every 30 minutes and
averaged these readings to produce
this graph of the daily temperature
and dew point curves. The bottom,
green line is the dew point, which is
a good reflection of the absolute
humidity. As you can see the only
time during the day that
evaporation takes place and the absolute humidity increases is between sunrise and early
Fig. #14 Positive Feedback Waveform Fig. #15 Negative Feedback Waveform
Fig. #16 24-Hour Soil and Air Temp Curves
Plus Dew Point Curves: 38-Day Average
Period of increasing
Humidity
Period of increasing Humidity
afternoon. If positive water vapor feedback that results in higher temperature happens it
happens during this period of the day, since an essential element in the positive water
vapor feedback hypothesis is rising absolute humidity levels coupled with rising
temperatures. For the rest of the day both temperature and humidity are in decline and a
positive feedback during that time would accentuate that rate of cooling.
So, the first thing that I did was to find the 38 day mean dew point and divide the
days up between those that fell above the mean—the “humid” days—and those who fell
below the mean—the “arid” days. I then averaged their respective daily temperature
curves and plotted these curves on a graph.
In this graph the red line is from the “arid” days and the blue line is from the
“humid” days. The light blue line is the average dew point curve from the “humid” days
and the orange line is the average dew point curve from the “arid” days.
As stated above, since the positive “water vapor feedback” hypothesis requires an
increasing absolute humidity coupled with a rising temperature and this only occurs daily
between sunrise and early afternoon, I focused my attention on that period to see if the
increased humidity on the “humid” days amplified the rate of temperature increase during
that period. Here is the graph:
In this graph the red line is the
soil temperature on the “arid” days and
the blue line is the soil temperature on
the “humid” days. The light blue line
is the dew point on the “humid” days
and the orange line is the dew point on
the “arid” days. Opposite from the
positive water vapor feedback
hypothesis we see that as the humidity
raises the rate of soil warming
decreases! This is a strong and
pronounced negative feedback. Again,
as the level of humidity increases in the atmosphere the rate of soil warming decreases
Fig #13 Comparison Between Soil Temperatures On “Humid” vs. “Arid” Days
Fig #14 – Temp and Dew Point Curves Sunrise – 2PM
during the period of the day when evaporation happens thereby slowing the evaporation
process. If humidity exerted a positive feedback on soil temperatures then the rate of soil
warming from sunrise to early afternoon would increase as the humidity increases but it
doesn’t; it decreases!
Here are the same readings in bar
graph form. The two bars on the left are
from the “arid” days and the two bars on the
right are from the “humid” days. The red
bars are mean temperatures and the blue bars
are the mean absolute humidity. These are
the averaged readings in temperature and
absolute humidity from sunrise to 2PM. As
you can see, as the humidity increases the
temperature decreases during the period of
the day when evaporation is occurring, during the only part of the day in which positive
feedback would result in higher temperatures. Again, this is a clear and distinct negative
feedback.
To complete our analysis of
the affect of humidity on the daily
temperature curve let’s look at the
rest of the day—from 2PM until
sunrise the next morning. The blue
line is the soil temperature on the
“humid” days and the red line is the
soil temperature on the “arid” days.
The light blue line is the dew point
on the “humid” days and the orange
line is the dew point on the “arid”
days. As you can see an increase in the absolute humidity is accompanied by a delay in
nighttime cooling. This, again, is a negative feedback in that it counteracts the more
rapid cooling trend seen on “arid” days.
Those graphs were of soil temperatures and if we look at air temperatures we see
the same negative feedback day and night.
I feel that something needs to be clarified at this point. I am not asserting that the
negative feedbacks seen in the above graphs are the effect of water vapor alone, because
Fig #15 – Soil Temp and Dew Point – Sunrise to 2PM
Arid Humid
Fig #16 – Soil Temp and Dew Point – 2PM to Sunrise
Fig #18 – Air Temp and Dew Point Fig #17 – Air Temp and Dew Point: Sunrise-3PM – 3PM to Sunrise
water vapor does not exist in isolation. Higher humidity in the air is accompanied by
more cloud cover, which shades the earth during the day and creates temperature
inversions at night slowing or stopping nighttime upward convection currents (an actual
greenhouse effect.) More clouds also usually mean more rain or snow, which further
cools the soil since precipitation falls from an altitude where is it colder than the ground
and this cold precipitation cools the soil by direct contact. More humidity also usually
means that there is more water in the soil, which has at least two affects on the
temperature: 1) More water is available to cool the soil through latent heat transfer, i.e.,
evaporation and 2) increased water in the soil increases the specific heat of the soil,
which will by itself dampen the swing in diurnal temperatures seen in dry climates.
These graphs manifest the net effect of all of those forces combined and all of those
forces combined as you have seen produce a pronounced negative feedback against
temperature changes day and night.
It is beyond the scope of this paper to sort out the contribution of each separate
force to the net affect on temperature. I am simply asking, “What affect does the addition
of water to a climate system have on the overall temperature within that climate system?”
The “greenhouse effect” hypothesis combined with the “water vapor feedback”
hypothesis asserts that the addition of water to a climate system should cause a marked
increase in temperatures within that climate system since the addition of water brings
with it increased humidity and water vapor is said to trap heat in the atmosphere.
As we have seen the addition of water to a climate system, manifest by a higher
absolute humidity, causes less warming during the day coupled with less cooling at night,
but we don’t know if over time whether or not these two opposing feedbacks cancel each
other out or if one or the other is dominant and swings the mean temperature higher or
lower. So let’s expand our time frame to two months and look at daily mean
temperatures vs. dew points over that period of time.
The Experiments (Part 2):
So, here is a graph of
the daily mean air
temperatures vs. the
daily mean dew points
over a two-month
period. The red curve is
the daily mean
temperature and the
blue curve is the daily
mean dew points, which
again is an accurate
reflection of absolute humidity. As you can see, as the temperature rose and fell the dew
point rose and fell as well. Let me make a couple of comments about this graph.
Fig. #19 Mean Air Temp vs. Mean Dew Point
a) First, although there is a strong correlation between the waveform shapes of these
two trends the temperature changes precede the dew point changes by about 24
hours demonstrating that the temperature is driving the humidity level as has been
observed in other studies2 and which is the first premise expressed within the
“water vapor feedback” hypothesis. As the temperature goes up more water is
evaporated into water vapor and as the temperature goes down more water vapor
is condensed back into water.
b) Conventional wisdom asserts that this correlation between temperature and dew
point increases and decreases proves that water vapor feedback is positive, yet we
see the exact same pattern of correlation present in a negative feedback. As we
have already discussed, rising blood sugar levels are followed by rising insulin
levels and dropping blood sugar levels are followed by dropping in insulin levels
and insulin is known to exert a profound negative feedback against rising blood
sugars. Therefore, this graph is consistent with the presence of water in a climate
system being a negative feedback against increasing temperatures.
c) It just so happens that there was precipitation near the beginning of this two-month
period and, as you can see, as time passed and the soil dried out the level of
humidity in the air trended downward as the temperature of the air trended upward
even though the “rise and fall” correlation remained present. This is an inverse
relationship and is, again, consistent with negative feedback rather than positive
feedback. The fact that as the soil dries out the general level of humidity drops
demonstrates an important reality. Water vapor feedback cannot exist where there
is no water in the soil such as the dry sand of an arid desert. So, what we will do
next is compare a few arid climates with a few humid climates to see if the
presence of water in these respective climate systems has a warming or a cooling
affect.
The Experiments (Part 3):
I did this comparative study under the assumption that if water vapor traps heat in
the atmosphere then it will trap the heat in the location where the humidity is. That is the
humidity that is present in Dallas, Texas does not trap heat in Phoenix, Arizona.
Whatever heat is trapped in Phoenix will be the doing of the humidity that is present in
Phoenix.
So, let’s start by comparing Phoenix to Dallas. They are both about the same
distance north of the equator and therefore receive about the same amount of sunlight
every day throughout the year. They are also both inland far enough not to be affected by
“sea breezes.” Since Phoenix only receives about 7 inches of precipitation annually
while Dallas receives about 35 inches, the air in Dallas is much more humid than the air
in Phoenix. If the “greenhouse effect” hypothesis is true and the amount of heat that the
atmosphere traps increases as the humidity increases then the mean annual temperature in
humid Dallas should be much higher than the mean annual air temperature in arid
Phoenix. So let’s take a look.
2 Wentz, F. J. and M. C. Schabel, (2000) Precise Climate Monitoring Using Complementary Satellite Data Sets, Nature, 403(6768),
414-416.
In this chart the bars on the
left are from Phoenix and the bars on
the right are from Dallas. The blue
bars are the yearly mean absolute
humidity in grams per cubic meter
and the red bars are the annual mean
temperatures adjusted for altitude3 in
degrees Celsius. These numbers are
from the National Weather Service.
As you can see even though Dallas is
significantly more humid than
Phoenix Dallas is never the less significantly cooler on average than Phoenix.
Next let’s compare Las Vegas, Nevada with Knoxville, Tennessee. Again, these
cities are both about the same distance north of the equator and therefore receive about
the same amount of sunlight every day throughout the year. They are also both inland far
enough not to be affected by “sea breezes.” Since Las Vegas only receives about 4.5
inches of precipitation annually while Knoxville receives about 48 inches, the air in
Knoxville is much more humid than the air in Las Vegas. If the “greenhouse effect”
hypothesis is true and the amount of heat that the atmosphere traps increases as the
humidity increases then the mean annual temperature in humid Knoxville should be much
higher than the mean annual air temperature in arid Las Vegas. So let’s take a look.
Again, in this chart the bars
on the left are from Las Vegas and
the bars on the right are from
Knoxville. The blue bars are the
absolute humidity in grams per cubic
meter and the red bars are the mean
annual temperatures adjusted for
altitude in degrees Celsius. Again,
these numbers are from the National
Weather Service. As you can see
even though Knoxville is
significantly more humid than Las Vegas Knoxville is never the less much cooler on
average than Las Vegas.
Let’s take a look at Death Valley, California compared to Huntsville, Alabama.
Again, these cities are both about the same distance north of the equator and therefore
receive about the same amount of sunlight every day throughout the year. They are also
both inland far enough not to be affected by “sea breezes.” Since Death Valley only
3 The International Standard Atmosphere published by The International Organization for Standardization (ISO), ISO 2533:1975
states that for every 1,000 meters that the altitude is lower the temperature raises 6.5 °C on average due to adiabatic heating. Based on
that formula these numbers estimate what the annual mean temperature would be if both cities were at sea level.
Fig #17 – Phoenix vs. Dallas Humidity & Temperature
Fig #18 – Las Vegas vs. Knoxville Humidity & Temperature
receives about 2.4 inches of precipitation annually while Huntsville receives about 57
inches, the air in Huntsville is much more humid than the air in Death Valley. If the
“greenhouse effect” hypothesis is true and the amount of heat that the atmosphere traps
increases as the humidity increases then the mean annual temperature in humid
Huntsville should be much higher than the mean annual air temperature in arid Death
Valley. So let’s take a look.
In this chart the bars on the
left are from Death Valley and the
bars on the right are from Huntsville.
The blue bars are the absolute
humidity in grams per cubic meter
and the red bars are the mean annual
temperatures adjusted for altitude in
degrees Celsius. As you can see even
though Huntsville is significantly
more humid than Death Valley it is
never the less much cooler on average
than Death Valley.
Let’s look at one more example from the international arena. Let’s compare
Riyadh, Saudi Arabia with Bogra, Bangladesh. Again, these cities are both about the
same distance north of the equator and therefore receive about the same amount of
sunlight every day throughout the year. They are also both inland far enough not to be
affected by “sea breezes.” Since Riyadh only receives about 3.7 inches of precipitation
annually while Bogra receives about 63 inches, the air in Bogra is much more humid than
the air in Riyadh. If the “greenhouse effect” hypothesis is true and the amount of heat
that the atmosphere traps increases as the humidity increases then the mean annual
temperature in humid Bogra should be much higher than the mean annual air temperature
in arid Riyadh. So let’s take a look.
In this chart the bars on the left are from
Riyadh and the bars on the right are from
Bogra. The blue bars are the absolute
humidity in grams per cubic meter and
the red bars are the mean annual
temperatures adjusted for altitude in
degrees Celsius. As you can see even
though Bogra is significantly more
humid than Riyadh it is never the less
noticeably cooler on average than
Riyadh.
These observations might seem counter intuitive since we often perceive humid
climates to be warmer than arid climates, but as we have seen that is just a sensory
illusion. Since our bodies are water cooled through perspiration, which is more efficient
in low humidity environments, people who move from Dallas to Phoenix or from
Fig #19 – Death Valley vs. Huntsville Humidity & Temperature
Fig #20 – Riyadh vs. Bogra Humidity & Temperature
Knoxville to Las Vegas think that they are moving to a cooler climate; but they are not.
It just feels cooler.
Conclusion:
So what does this all mean? Although it is true that warmer temperatures create
higher humidity in climates where there is water in the soil to evaporate, that greater
humidity demonstrably does not lead to even more warming. Quite the contrary, as we
have seen the presence of water in a climate system exerts a negative feedback on
temperatures both day and night, which stabilizes the wide diurnal swings in temperature
seen in arid climates and, over time causes humid climates to be some what cooler on
average than arid climates. In this sense water acts as the earth’s thermostat and not its
heater. The observations made in this paper also falsify any notion that there could ever
be runaway global warming driven by positive water vapor feedback where the oceans
evaporate into the atmosphere and all life on earth perishes. Why? Because “water
feedback” is negative feedback and if it were going to happen it already would have.
These empirical observations do not deny that the various climates around the
world continue to experience variations over time, but rather they demonstrates that the
presence of water on our planet continues to act as a stabilizing force as it exerts negative
feedback against temperature change up or down.

TimTheToolMan

Mosher writes “AIRS is observations. In fact you might want to familiarize yourself with the sensors.”
Its all about the imbalance at the TOA and measures like expected surface warming vs water vapour increases are interesting but essentially meaningless in understanding AGW.
If you look at increasing water vapour and say the radiative transfer models infer the forcing must increase then you’re ignoring possible negative feedbacks such as changed lapse rates with an increased water cycle which apply at the TOA.
Its important that Berényi Péter is considering measurements during this period of “hiatus”.

Frank

If they used 7 years of data, how can they tell which water vapor is the result of short term feedback and which is long term? Maybe I read the materials too quickly.

Susie

This is one of the most bizarre papers I’ve ever read. Surely, if we’ve only seen 15% of the water vapour feedback predicted by the models in 25 years, it’s more likely the models are wrong than there is 85% more feedback in the pipeline.

charles nelson

Water vapour is the one of the main media carrying heat away from the equator to temperate and cold regions of the earth. More water vapour can only result in more cooling.

What about the issue of water vapor NOT being an evenly distributed greenhouse gas, and that its distribution is key to its feedbacl potential. It’s recently been observed, I believe, that the increase in water vapor concentrations due to warming has been confined to the lower troposphere, where its greenhouse effects are negligible, whereas there has actually been a decrease in water vapor content in the higher elevations, where most of the greenhouse effect takes place, all of which produces a net negative, or cooling, feedback. Which might help explain phenomena like the pause and the lack of the equatorial “hot spot” predicted by most models.