Guest essay by Dr. Antero Ollila
Water vapor feedback has remained a topic of debate since 1990. The laymen do not know that water has an essential role in calculating the warming effects of GH gases. In all Anthropogenic Global Warming (AGW) models the Relative Humidity (RH) stays constant. It sounds like a very neutral and harmless assumption. When GH gases increase the atmospheric temperature, the constant RH means that the absolute amount of atmospheric water also increases. Because water is about a 15 times stronger GH gas than carbon dioxide, this small increase of water content increases the temperature as much as GH gases. According to IPCC, the radiative forcing of GH gases is doubled by water (AR3 and AR4). IPCC calls this feature a positive feedback of water.
According to my spectral analysis calculations, the positive water feedback effect would be this magnitude. But in AR5 (20139 IPCC reports in Science Basis , p. 666: “The contribution of water vapor to the natural greenhouse effect relative to that of carbon dioxide (CO2) depends on the accounting method, but can be considered to be approximately two to three times greater.” There are no references to any scientific publications. This raises a question, if IPCC really knows how to calculate the effects of positive water feedback. The knowledge of water feedback in not getting more accurate but more inaccurate according to IPCC. It is a little bit of strange development after all the money used for climate change research.
The opponents of AGW theory have pointed out the RH measurements do not show constant RH trends as we can see in figure 1, (NOAA, http://www.esrl.noaa.gov/gmd/aggi/)
Figure 1. Relative Humidity (RH) trends from 1948 to 2012
I have called this figure a sight test. If you see that the trends are essentially at the horizontal position and not bending downward, you should test your eyes with the doctor. This is an example but not the only one that IPCC denies the direct measurements, when they do not fit into their theories.
The warming calculations are based on the climate models both in simple as well as in computer based General Circulation Models (GCM). The warming effects of GH gases are very small and there are many other factors. The ongoing pause in the global temperature is a good example of these other factors, which IPCC call natural effects. It is therefore quite difficult to show in the real climate, if there is positive water feedback or not.
Luckily there is one experiment which was organized by the Mother Nature itself. This was the eruption of the Mount Pinatubo. The main eruption began on the island of Luton in the Philippines on the 3rd of June, 1991 and concluded on the next day. Four large explosions generated eruption columns reaching the heights of up to 24 km in the stratosphere. The estimate of the stratospheric mass increase was 14 – 20 Mt of SO2, which created 21-40 Mt of H2SO4–H2O aerosols. The eruption also injected vast quantities of minerals and metals into the troposphere and stratosphere in the form of ash particles. The aerosols created a global layer of sulfuric acid haze over the globe and the global temperatures dropped about 0.5 °C in the years 1991 – 1993. Because of the aerosols and ash particles, the incoming solar radiation decreased 6 W/m2. At the same time there was a maximum increase of downward longwave radiation flux of 4.5 W/m2 caused by the very same aerosols and ash particles. Totally the radiative forcing at the surface was in maximum 1.5 W/m2. This radiation anomaly can be compared to the decrease caused by the doubling of the CO2 concentration from 280 ppm to 560 ppm. According to IPCC data this change is 3.7 W/m2.
I have carried out a dynamic analysis of the temperature effects caused by the eruption. I wanted to test two options for the climate sensitivity parameter (CSP). The radiative forcing (RF) at the top of the atmosphere has a linear relationship to the global mean surface temperature change dT:
dT = CSP*RF (1)
IPCC uses still equation (1) in its latest report AR5 but IPCC no longer keeps the value of CSP as almost constant. There is no information in AR5 as to, what the real value of CSP is or in which way it varies. The CSP value of 0.5 K/(W/m2) has been used in the former reports of IPCC and it includes the positive water feedback. Actually the CSP value of 0.5 still has the decisive role, because IPCC reports in AR5 that the transient climate sensitivity value is likely to lie in the range 1 to 2.5 °C giving the average value 1.75 °C. This value is almost the same as calculated by equation (1): dT = 0.5 K/(Wm-2) * 3.7 Wm-2 = 1.85 K. The value of 0.27 K/(W/m2) has been used showing no water feedback.
I carried out two simulations by a simple dynamic model to test these two CSP values. The results are depicted in figure 2. It is very clear that the CSP value of 0.5 gives results which deviate from the real response of the global temperature decrease.
Figure 2. Simulation of the Mount Pinatubo eruption using different climate sensitivity parameters.
There are two former studies about the dynamic temperature response in the Mt. Pinatubo eruption. Hansen et al. applied GCMs by name SI94 and GRL92 in their simulations published in 1992. Soden et al. also applied a GCM in the research study published in 2002. They also included the absolute atmospheric water content as a variable. The major results were that the GCM simulations could calculate the dT values close to the measured value, if the positive water feedback was included. The water content was calculated using the NASA Water Vapor Project (NVAP) values.
So there are research results which show very different results. What could be the reasons? The reasons are rather simple to point out. All other researchers including me have used maximal solar irradiation decrease value of -6 W/m2 but in these two studies the researchers have used the value -4 W/m2. In the same way other researchers have used the maximal deviation value of -0.5 C during the eruption but in these two studies the value of ~-0.7 C has been used. Soden et al. have included the RH change during the eruption and they have been able to show that there is positive water feedback needed to explain the temperature decrease.
Figure 3. Relative Humidity trends according to NCEP/NCAR Reanalysis and NVAP-M datasets.
In Figure 3 the NVAP dataset values as well the NCEP/NCAR (National Center for Environmental Prediction / National Center for Atmospheric Research) values are depicted. The NVAP water content trends show great seasonal changes of about 3 TPW mm. Soden et al. have reported that there has been ~0.75 TPW mm peak reduction during the Pinatubo eruption. The graphs show that the peak reduction estimate can be regarded a correct estimate. But this choice of using the peak values only can be questioned, because the trend line of NVAP-M values show an increased rate of absolute water content and it is an opposite trend! The figure 3 shows that the RH measurements are not accurate enough to be used as evidence about RH feedback. The average value of these two datasets show practically zero trend during the eruption.
The results of Hansen et al. and Soden et al. can be explained by proper data selection, which is called cherry picking. I have used the most commonly applied data values and the results show no water feedback. This result means that the Climate Sensitivity (CS) is 0.27 K(W7m2) * 3.7 W/m2 = 1 K. Many researchers using different methods have found that the CS would be in the range of 1 to 1.2 C, if the RF value of 3.7 W/m2 of CO2 (increase from 280 ppm to 560 ppm) has been applied. There is only one question remaining, is the RF value of 3.7 W/m2 correct. According to my analysis this value is calculated in the atmosphere, where there is constant RH and therefore positive water feedback. My calculations using three different methods show that the RF value of doubling the CO2 concentration is 2.12 W/m2. Therefore climate sensitivity is only 0.27 * 2.12 = ~0.6 C assuming constant absolute water content in the atmosphere.
The paper:
Physical Science International Journal, ISSN: 2348-0130,Vol.: 9, Issue.: 4
Climate Sensitivity Parameter in the Test of the Mount Pinatubo Eruption
Antero Ollila1*
1Department of Civil and Environmental Engineering (Emer.), School of Engineering, Aalto University, Otakaari 1, Box 11000, 00076 AALTO, Espoo, Finland.
Abstracts
The author has developed a dynamic model (DM) to simulate the surface temperature change (ΔT) caused by the eruption of Mount Pinatubo. The main objectives have been 1) to test the climate sensitivity parameter (λ) values of 0.27 K/(Wm-2) and 0.5 K/(Wm-2), 2) to test the time constants of a simple first-order dynamic model, and 3) to estimate and to test the downward longwave radiation anomaly (ΔLWDN). The simulations show that the calculated ΔT of DM follows very accurately the real temperature change rate. This confirms that theoretically calculated time constants of earlier studies for the ocean (2.74 months) and for the land (1.04 months) are accurate and applicable in the dynamic analyses. The DM-predicted ΔT values are close to the measured value, if the λ-value of 0.27 K/(Wm-2) has been applied but the λ-value of 0.5 K/(Wm-2) gives ΔT values, which are about 100% too large. The main uncertainty in the Mount Pinatubo analyses is the ΔLWDN flux, because there are no direct measurements available during the eruption. The author has used the measured ERBS fluxes and has also estimated ΔLWDN flux using the apparent transmission measurements. This estimate gives the best and most consistent results in the simulation. A simple analysis shows that two earlier simulations utilising General Circulation Models (GCM) by two research groups are depending on the flux value choices as well as the measured ΔT choices. If the commonly used minimum value of -6 Wm-2 would have been used for the shortwave anomaly in the GCM simulations, instead of -4 Wm-2, the ΔT values would differ from the measured ΔT values almost 100%. The main reason for this error seems be the λ-value of 0.5 K/(Wm-2).
Full paper here: http://sciencedomain.org/abstract/13553
Yes OK
So answer this question:-
Why are tropical rainforests with their very high humidity COOLER than dry deserts at the same latitude?
Because the rainforest can’t stand the hot and dry desert day, nor the large diurnal temperature changes. But of course, your idea makes sense; RH is going down, temperature is going up. /ducks
Or simply put, why don’t you just tell that you disagree with the idea that H2O is a GHG. Well then, you have right to that.
More or less Hugs. I have worked in both dry desert and rainforest and I can tell you that dry deserts are much hotter than rainforests. I have measures 55C in the shade in a desert but only 38C in a rainforest. The desert heat is more comfortable because your sweat evapourates and the latent heat requirment cools you.
The GHE theory states that rainforests are hotter than deserts. Clearly incorrect so refuting the theory.
Because your thermometer is set to ‘temperature’ and not ‘misery index’. Here, let me fix that for you. [click]
Now it all makes sense. As a drippy sweating mammal sitting here in the jungle whose internal regulation of heat has been impaired by slowed evaporation due to excess humidity, I find it easier to believe that water vapor is a GHG. It is not surprising that our computer models would be created in our own image, that of a drippy sweating mammal. /ducks
I don’t have the data, but I believe that your assertion is wrong. Tropical rainforests are NOT cooler than dry deserts at the same latitude. Their maximum temperature is cooler, but their minimum temperature is quite warmer than that of the dry deserts. Overall, I suspect that the rainforest is warmer.
Agreed, Nylo. Your point goes to show that humidity is what prevents the night reradiation and heat losses from occurring, thus reducing the diurnal temperature variation. Heat is released from the rainforest daily in the form of upwelling rain clouds.
If the remaining constituents of the ‘greenhouse gas gang’ really are increasing the retention of heat in the atmosphere, it should be most apparent in the desert at night, cancelling out the lack of water vapor to reradiate outgoing infrared. The smoking gun for sans-H2O greenhouse gas warming (seems to me) should be minimum temperature increases under very low relative humidity and wind conditions with temperature data only compared under near-identical wind and RH% conditions.
If the present assumptions of carbon-compound gas forcings were correct, it should have been obvious by now, without any need for authority to indoctrinate the beliefs upon the masses.
It would appear that you are correct for the one case I checked. Comparing average annual precipitation in inches and temperatures in degrees F for two coastal cities at close to the same latitude, Belize City and St. Louis, Senegal:
Rain, In. T, Hi. T, Lo.
BC: 79.27, 86, 72.5
SL: 10.29, 89+, 68.4
Mean of high and low for rainy Belize is 79.25. For drier St. Louis it is 78.75, although over ten inches of rain isn’t quite a desert by some people’s estimation, and coastal location would moderate night temperatures, which can be quite cold in continental interior deserts. So IMO the difference for interior locations would be more pronounced, especially perhaps in nonurban areas. I used the coast so that both would be at about the same elevation above MSL.
There is also the issue with cloud formation lowering the maximum heat during the day.
Nylo says, March 8, 2016 at 4:41 am:
Simple answer: No.
https://okulaer.wordpress.com/2014/11/16/the-greenhouse-effect-that-wasnt-part-2/
The reduction of heating during the day is a considerably stronger effect than the reduction of cooling during the night, on average. So the annual mean surface temperature is significantly lower in tropical rainforest areas (humid and cloudy) than in tropical desert areas (dry and clear). Which goes directly against the whole rGHE idea …
New Orleans vs Phoenix
It is clear that none of these so-called climate scientists ever had to design an actual hardware feedback amplifier; or for that matter ANY kind of feedback system.
Their water feedback system: more CO2, warmer air, same humidity, more water vapor, warmer air, same humidity, more water vapor, warmer air, …..>
That system will go to thermal runaway.
Earth’s water feedback system: Hey dummies, the CO2 doesn’t warm the air; the sun warms the air, the sun warms the ground, the sun warms the ocean, the sun is the source of ALL of the warming that happens, the sun is the INPUT TERMINAL, not the CO2, the sun warms the water(73% of the surface), the warmer surface puts more CO2 into the air, don’t need CO2 to make more water vapor, more water vapor makes more clouds, more clouds makes less sunlight reach the surface, less sunlight reaching the surface cools the surface, cooler surface stops putting more water vapor in the air, more clouds makes more precipitation, more precipitation, makes less clouds, less clouds makes more sunlight reaching the surface, more sunlight reaching the surface puts more water vapor in the air, ……
In a feedback system, a FEEDBACK SIGNAL that is a monotonic function of the OUTPUT SIGNAL, is fed back to the INPUT TERMINAL to alter the effective INPUT SIGNAL to the system.
The FEEDBACK is either POSITIVE or NEGATIVE depending on whether it INCREASES the EFFECTIVE INPUT SIGNAL or whether it DECREASES the EFFECTIVE INPUT SIGNAL.
The INPUT SIGNAL is the SUN, not the CO2.
NO you don’t need to put air muffs on; I’m not shouting. The upper case words, are the only words you need to read.
G
Hello George, Actually I used to be an automation engineer and I have planned, tested and tuned numerous control circuits with the hardwired and digital systems. There is one question, I would like to ask: How do you explain that the outgoing radiation of 240 W/m2 corresponds to the temperature of -18 C? And as we know the average surface temperature of the Earth is about 15 C. As far as I know, the only scientific explanation is the GH phenomenon. But it is totally a different issue, how much the elevated concentrations of CO2 can actually increase the surface temperature.
George, That’s too simple. Seven grade science. I wonder what they are teaching in the seven grade now a days.
Compression heating. The difference between 15 C at the surface and -18 C of the radiative layer is compression heating on account of the pressure difference between the two altitudes.
There are some complications in climate, so the concept of “feedback” is not exactly the same as in electrical engineering. Two main ones, (a) the effectiveness of feedback degrades with concentration due to saturation of bands (GHG increases have logarithmic effect, and there are similar limits to things like ice albedo feedback), (b) there is a built-in negative feedback in that as the planet warms it gets better at cooling off via radiation to space (“Planck response”), such that even with positive feedback thermal runaway will not happen (new equilibrium will be found). Per Stefan-Boltzmann, the fourth-power increase of flux with temperature is a built-in feedback allowing planets to come into equilibrium with their energy source.
They are not cooler, if you average the desert temperatures over a year, (night day, winter summer) you find tropical rainforests are warmer.
Where did the lava flow go in that simulation ??
g
John Marshal: Where did you find, on Earth, tropical rain forest at the same latitude as deserts? I looked at Google Earth but I didn’t find any tropical deserts. Deserts are hotter because they lack humidity. It takes heat to evaporate water and that heat is not sensible (as temperature), it’s latent. Tropical nights are warmer than desert nights because water vapor is a strong greenhouse gas.
“In all Anthropogenic Global Warming (AGW) models the Relative Humidity (RH) stays constant. It sounds like a very neutral and harmless assumption.”
No reference given. It’s just not true. GCMs make no such assumption.
I see the Journal here is somewhat dubious.
Carle Mears in his new paper claims RH is “near-constant”. How near is near?
It is hard to make a person see a variable if he is paid to see it as a constant.
To see constants as variables in modern compilers you have to turn off all advanced optimization features and sanity checks, and engage in subterfuge that sets the initial value in a way beyond its scope of analysis that leads the language to believe it may be set again.
This is difficult to do for people who have been compiled at a young age. It is better to just work with interpreted or threaded people.
Why is assuming constant water content any better ??
Who does that?
Guest essay by Dr. Antero Ollila
Nick writes
It appears to be true and here is the reference
https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-6-3-1.html
Not sure what part of that ref. you were wishing to focus on. However, “”simulations typically reduces feedback strength slightly” may not be inconsistent with the graphs here , depending upon the meaning and definition of “slightly”.
Maybe others would chose to see that as not so sight.
Another part of the quote is
The whole reference strongly implies that RH is indeed close to constant in the GCMs contrary to what Nick has stated. Of course in his typical racehorse way, he’s bound to chime in with “close to” isn’t the same as constant and he’ll argue that Dr. Antero Ollila had in mind that it was simply hard coded as constant or something.
I’m talking about the claim that RH is assumed constant. That is just untrue. It may well turn out that
“To a first approximation, GCM simulations indeed maintain a roughly unchanged distribution of RH”. That’s an outcome, not an assumption.
“Absorption of LW radiation increases approximately with the logarithm of water vapour concentration, while the Clausius-Clapeyron equation dictates a near-exponential increase in moisture-holding capacity with temperature. Since tropospheric and surface temperatures are closely coupled (see Section 3.4.1), these constraints predict a strongly positive water vapour feedback if relative humidity (RH) is close to unchanged.”
IPCC Fourth Assessment Report
This being the case, that graph from NOAA blows up the GCM’s, at least the ones who follow IPCC’s assumption of constant RH. RH has clearly dropped, and more and more the higher into the atmosphere we go. Despite this author appearing to be a disciple of Miskolczi, he has a strong point.
And there you have it.
Michael Moon writes
This is exactly the change needed to undo the anthropogenic CO2 enhanced greenhouse effect which was theorised to be that the ULR would be captured higher in the atmosphere by the additional CO2 increasing the effective radiating altitude and radiating at a lower temperature causing the radiative imbalance.
So instead of enhancing the greenhouse effect, the water vapour changes are minimising it.
So it is the IPCC themselves who are the answer to Nick’s question. Sure says humidity stays constant, in my copy of that paper.
g
Tim,
Yup. Observation shows that water vapor is a net negative feedback effect on CO2.
“these constraints predict a strongly positive water vapour feedback if relative humidity (RH) is close to unchanged”
That is just a simple bit of reasoning. It doesn’t assert that RH must be constant. As quoted earlier, the factual basis there is:
“To a first approximation, GCM simulations indeed maintain a roughly unchanged distribution of RH under greenhouse gas forcing.”
That’s an observation about an outcome. They then say that if that holds, there is positive wv feedback. But there is no GCM that starts with that assumption.
TimTheToolMan: from the reference you linked to:
To a first approximation, GCM simulations indeed maintain a roughly unchanged distribution of RH under greenhouse gas forcing. More precisely, a small but widespread RH decrease in GCM simulations typically reduces feedback strength slightly compared with a constant RH response (Colman, 2004; Soden and Held, 2006; Figure 8.14).
…
In the planetary boundary layer, humidity is controlled by strong coupling with the surface, and a broad-scale quasi-unchanged RH response is uncontroversial (Wentz and Schabel, 2000; Trenberth et al., 2005; Dai, 2006). Confidence in GCMs’ water vapour feedback is also relatively high in the extratropics, because large-scale eddies, responsible for much of the moistening throughout the troposphere, are explicitly resolved, and keep much of the atmosphere at a substantial fraction of saturation throughout the year (Stocker et al., 2001). Humidity changes in the tropical middle and upper troposphere, however, are less well understood and have more TOA radiative impact than do other regions of the atmosphere (e.g., Held and Soden, 2000; Colman, 2001). Therefore, much of the research since the TAR has focused on the RH response in the tropics with emphasis on the upper troposphere (see Bony et al., 2006 for a review), and confidence in the humidity response of this region is central to confidence in modelled water vapour feedback.
It appears from this language that some simulations keep RH constant, whereas others do not.
Nick writes
Neither did the original article. It said…”In all Anthropogenic Global Warming (AGW) models the Relative Humidity (RH) stays constant.”
That’s a statement about what happens not what must happen. The following line about assumption doesn’t mean it either and to me at least reflects how they work and how they’ve been tuned. And more importantly how post run analysis is accepted by those who build them.
“In the planetary boundary layer, humidity is controlled by strong coupling with the surface, and a broad-scale quasi-unchanged RH response is uncontroversial”
Yes. This reflects what I was saying elsewhere. The “coupling” at the ocean surface approximately enforces RH=1. Winds continue to blow in much the same way, and rain to fall, and so water cycles from that constant RH boundary in much the same way. A “quasi-unchanged RH response“ is uncontroversial. But not assumed.
Well a simulation is NOT an observation, and moreover there is NO outcome.
You just press ‘enter’ again and run another non observation for another non outcome.
g
Nick, I wonder if autocorrelation is at work in “discovering” that GCM’s show constant values as an outcome. The dials on the super computer machine certainly place the output at risk of autocorrelation in several ways, especially during the tuning period.
“Finally, it should be noted that all the studies discussed above cannot be considered as truly “independent” because many of them (with the exceptions of Lohmann et al. (2000) and Ghan et al. (2001a)) use similar methodologies and similar relationships between sulphate mass and cloud droplet number concentration. Therefore it is suspected that the range of model results does not encompass the total range of uncertainties.”
Thanks for the empty link below….you know, where you point to a whole bunch of nothingness and expect everyone to understand. Anywhoooooooo, thank you, because I was able to review how much uncertainty there is in certainty!!!!
Well, I suppose you will tell me how the quote above doesn’t have anything to do with what you wanted me to find ( 6.8.2.2 Estimates of the second indirect effect and of the combined effect
) AND yes it does.
Everyone, except one, uses similar methodologies regarding….cloud droplet concentration.
Couldn’t find the words “relative humidity”….only words dancing around the thought of water vapor in the air.
Any specific section to point out?
No, what they do allow is a super saturation of water at the boundary layer, it is this function in the code that forces excess water into the simulation.
Try AR4 WG1 black box 8.1. It is not programmed in the models but is none the less the result of the programming. I disagree that there is no WVF. To a firstmorder approximation, based on precipitation misses, it is half of what models have. The underlying mechanism is via tropical convection cells (Tstorms) that havemtombe parameterized due to computable GCM grid scales. WVF impact is at least twofold. Lower upper troposphere specific humidity that Clausius Clapeyron would predict, and Lindzens adaptive infrared iris cirrus clouds.
Nick Stokes: GCMs make no such assumption.
How sure are you about that assertion? The GCMs used by Romps et al (12% increase in lightning strike frequency per degree C of warming) assume constant RH. Some assumption is needed in order to compute results, and constant RH is the assumption I have read most frequently.
“How sure are you about that assertion?”
Quite sure. There is just no way a GCM could implement constant RH. It has, as Micro noted, a sea boundary condition, which could be RH=1, but is probably more complicated. It has a precipitation model. These do what they do, and then the winds have to transport WV conserving H2O mass. There is no way in that you could constrain global RH.
As to Romps, I wish you’d give a quote or something. Link would have helped. I can’t see anything there that supports what you say.
The issue of climate sensitivity (CS) and the climate sensitivity parameter (CSP) is very unclear. It is true the scientist behind GCMs say that they do not assume any special RH behavior but in most cases it turns out to be constant. There is Table 9.5 on the page 818 in AR5. The average value of TCS of 30 GCMs is 1.8 C and the average value of CSP is 1.0. The average RF value for 2 * CO2 has been 3.7 W/m2. The CSP in this case seems to be applicable only for calculating the equilibrium CS = 1 * 3.7 but the average value of ECS is 3.2 C.
Since the GCMs estimate evaporation only increases about 3% per C warming whereas simple physics estimates about 6 to 7% for constant RH, (confirmed by Wentz’s data), it seems that GCMs over estimate water vapor with warming and hence water vapor feedback and underestimate the strong negative feedback of evaporation surface cooling. The reason is probably that GCMs do a bad job at cloud formation and resulting precipitation that reduces humidity.
The most likely reason for the climate models low estimate of evaporation is a relative humidity that increases with temperature. Data at the surface over many years show a drop in RH with temperature (Dia).
At least one reviewer seems to have tried?
http://www.sdiarticle2.org/prh/PSIJ_33/2016/Rev_PSIJ_23242_Joh_ANON.pdf
“There are many other tenuous claims that are made
but it is noteworthy that the author(s) don’t even
begin to present their model until line 320. In Equation
2, the authors state that the “climate process is a
combination of two parallel processes…” What does
this mean? What is Equation 2? Saying something is a
climate process is like saying nothing. The units don’t
work out in the equation. The denominators on the
right have terms with different units. There is no
description of justification of Equation 2. The
numerical scheme treats inflows and outflows at
different time steps. Regardless, this isn’t a onedimensional
model anyway. “
“There are no references to any scientific publications. This raises a question, if IPCC really knows how to calculate the effects of positive water feedback.”
It has been known for a long time. The AR3 has a well-referenced section.
Switch gears try something else, typical nick
+1
It looks like I am in error. The paper “Link between land-ocean warming contrast and surface relative humidities in simulations with coupled climate models” by Byrne and O’Gorman, Geophysical Research Letters 40, 5223-5227, 2013, cite variations in relative humidity as outputs from GCMs, and use those in further calculations of changes in relative humidities. For some reason I can’t cut and paste, but there are multiple references, for example in paragraph 5.,
As to Romps et al, it was in reading their references that I came across the assumption of constant RH, and in some other references. Since I am wrong about the GCMs, (about which the claim was made), I’ll not try to show that someone else, somewhere else, used constant RH. It looks like I overgeneralized from those readings.
Relative Humidity affects Temperature. No GCM could calculate both independently. Which came first, the chicken or the Temperature? In the engineering world, we call this “too many unknowns.”
Why is this any more realistic than constant RH ?
The simple answer is, because the direct measurements show that RH has not been constant since 1948. This paper of mine utilizes Pinatubo eruption to show that also experimental data do not support this claim.
I did an analysis of ERBE top of atmosphere energy change during Mt Pinatubo:
https://judithcurry.com/2015/02/06/on-determination-of-tropical-feedbacks/
This suggested a far stronger forcing from volcanoes than current modellers use, though it was very close to what the same people were saying in 1990 by science went on holiday to Venus.
Stronger forcing implies stronger feedbacks and less sensitivity. It seems the authors here have made the error of adopting the currently accepted valued of volcanic forcing.
We don’t measure the forcing we have AOD atmospheric optical data. That is then scaled. The scaling in one those fudge factors that modellers use to make the models to what they expect.
http://climategrog.files.wordpress.com/2014/04/erbe_vs_aerosol_forcing1.png
I do not understand how changes in W/V can e considered without (A) considering clouds, and (B) considering the affect at the surface, in particular the changes in energy entering the oceans.
One affect clouds have on earth’s energy budget, which as far as I know is poorly considered, is the affect on SW radiation reaching below the ocean’s surface. W/V alone in clear sky conditions greatly reduces surface insolation.
Clouds reduce a large volume of disparate S/W radiation penetrating the ocean’s surface. I have yet to see a study on the disparate residence time (days, weeks, months, years, decades and centuries)) of various S/W spectrum no longer reaching below the ocean surface. Without knowing this we cannot begin to know how to quantify cloud feedbacks. LWIR feedbacks to the atmosphere are virtually instant. SW radiation not reaching below the green house liquid ocean surface has a much slower response time to affecting the atmospheric T, but, due to the vastly greater residence time of said SW energy, any change in energy accumulation of depletion can continue for far longer.
I did a difference analysis of ERBE top of atmosphere energy change during Mt Pinatubo:
https://judithcurry.com/2015/02/06/on-determination-of-tropical-feedbacks/
This suggested a far stronger forcing from volcanoes than current modellers use, though it was very close to what the same people were saying in 1990 by science went on holiday to Venus.
Stronger forcing implies stronger feedbacks and less sensitivity. It seems the authors here have made the error of adopting the currently accepted valued of volcanic forcing.
We don’t have measures of the forcing we have AOD atmospheric optical data. That is then scaled. The scaling in one those fudge factors that modellers use to make the models to what they expect.
http://climategrog.files.wordpress.com/2014/04/erbe_vs_aerosol_forcing1.png
It is clearly seen that the TOA energy buget comes back much quicker than the aerosol forcing subsides. That is the climate reaction. That is where we need to look for the size and rate of feedbacks.
http://climategrog.files.wordpress.com/2014/03/tropical-feedback-adjusted.png
An 8 mo time constant provided a very good fit to observations. Climate models are in the range 36-48 months.
http://climategrog.files.wordpress.com/2014/04/tropical-feedback_resp-fcos.png
You suggest that Pinatubo created an experiment with a 6 W/m2 decrease in solar radiation.
We have annual demonstration of the effect of a change about 13 times this amount, or a 6.9% change in TSI. This occurs as the Earth moves through its perihelion and aphelion.
The effect is of this massive change is zero. Look at the temperature of Kirrabati, that sits across the equator. It is exactly 28 degrees, all year round. Big changes in rainfall between the seasons show how tropical thunderstorms act as a negative feedback and temperature controller.
The effect of doubling CO2 will also be zero, thanks to our natural thermo-regulators.
True Tony, although the actual GMT affect of January increased insolation is, contrary to what most would assume, to lower it! The reason is primarily two fold, Increased albedo in the NH winter, thus removing energy from the atmosphere, and increased insolation into the oceans, thus also removing energy, for a time, from the atmosphere. Does the earth gain or lose energy during this time? That question requires many answers which, like the question of W/V feedback, can not be yet answered as outlined in my previous comment on this post here… http://wattsupwiththat.com/2016/03/08/positive-water-feedback-not-found-in-the-mt-pinatubo-eruption/comment-page-1/#comment-2161406
David, The argument isn’t about whether the Earth gains or loses energy, it concerns whether CO2 causes “global warming”, that is, temperature change at the Earth surface. If an equivalent increase of 130 times current CO2 concentrations (ie the 6.9% TSI change) has no effect on temperature, if implies the tiny current CO2 changes have no effect on temperature.
“David, The argument isn’t about whether the Earth gains or loses energy, it concerns whether CO2 causes “global warming”, that is, temperature change at the Earth surface. If an equivalent increase of 130 times current CO2 concentrations (ie the 6.9% TSI change) has no effect on temperature, if implies the tiny current CO2 changes have no effect on temperature.”
The reason is because the Earth’s annual orbital TSI changes are cyclical. And as David A explains the warming in the SH is offset by the NH cooling. Then come the SH winter there is a reduced global TSI.
Whatever energy the Earth as a whole receives in January is balanced by that in August – obviously – else it would be continually warming/cooling.
The GHE is continuous.
Toneb,
There is no “offsetting” an increase of 6.9% TSI to BOTH hemispheres. However this massive increase in radiation produces ZERO warming, thanks to the Earth’ natural negative feedbacks.
You have only told half the story, at the same time as the earth gets closer to the sun the length of day shortens due to the change in orbital speed. See Kepler’s Laws.
Kepler’s Law has nothing to do with it. It’s the axial tilt that causes the change in the length of day(light). The rotational period of the earth does not change with it’s orbital position.
The length of day could double and have no effect on temperatures at the equator. If the temperature at Kirrabati is 28 degrees year round, averaging it more (or less) fast makes no difference. If the TSI change of a massive 6.9% each year has zero effect on temperature, a faster spin will do nothing.
This paper does bring up a point, which is why look at CSP, or TCS or ECS of CO2 when the atmosphere is totally dominated by water vapor. The author here uses the value of W/V 15 times more powerful GHG as CO2, and I have seen estimates as high as 80.
The CRC Handbook of Chemistry and Physics gives the composition of the atmosphere as 2-5%. Let us use the 2% value, just because it seems to be a popular value. Now there is 50 times more W/V than CO2, 2.0% vs. 0.04%. So 50 * 15 (GHG potential) = 750 times more greenhouse effect from W/V than from CO2. The effect of CO2 must be lost in the noise of any W/V fluctuations. This might explain why getting a good read on CSP, TCS and ECS turns out to be so darn hard.
How do you convince people that water vapor is dangerous and how do you tax it?
Oh dear. Same as was done with CO2.
Start the propaganda campaign as soon as possible in the public schools, and start in the earliest grades possible. The effort requires purging all factual content from all science in the curricula, as much of it would be contradictory to the propaganda effort. In the place of biology, chemistry, physics, a cherry picked set of scientific “facts” supporting the effort is presented. This allows one to claim an integrated, holistic approach to science. It will not matter that the effort will produce students who are profoundly scientifically illiterate. This is actually exactly what the propaganda campaign requires to be successful.
By the time the students get to college, they will be a loud, vocal, active voting block, clamoring for protection from this terrible thing which will wreck the planet.
How do you tax it?
Simplicity in itself. Mandate an emissions trading scheme, and force everybody to participate. As a bonus the cronies can make a financial windfall by organizing up the trading markets. An outright tax would never fly politically, of course. So we take the naked force and full coercive power of the police state, and simply package it up as a “Free Market Solution”. Easy, made in the shade.
Sometimes, I wish I had my own country to run.
How about the old dihydrogen monoxide bit? 😉
Water vapor being 2-5% of the atmosphere sounds like a typo. 5% means a partial pressure of 38 mm Hg at the surface, which is the vapor pressure of water at 33 degrees C. 2% is a partial pressure of 15.4 mm Hg at the surface, which is the vapor pressure of water at 18 degrees C.
If you like to see, in which way I have calculated the warming effects of water and other GH gases, please visit my web page: http://www.climatexam.com
Start with the slideshows, where you can find many good illustrations. A figure/picture can tell more than thousand words.
I took a look there – what is the prcm that increases from 2.60 to 2.66 as a result of CO2 increase causing warming on its own of .38 degree C? If this is percent by molecules in Earth’s atmosphere or its troposphere, this can’t be true as a worldwide figure – at sea level pressure, this means water vapor partial pressure of 19.8-20.2 mm Hg, which means 100% relative humidity at 22-22.3 degrees C. Worldwide average ocean surface temperature is much colder than this.
At the 500 millibar level (which is in the mid-troposphere), 2.6 to 2.66 percent water vapor by molecule count means water vapor partial pressure around 9.95-10 mm Hg. This corresponds to 100% relative humidity at about 11.3 degrees C. The 500 millibar level is generally below freezing.
I am adding the images about the absorption bands of GH gases, because I think it is a very good one:
Comment to the prcm question below.
The acronym prcm means precipitated water in cm’s and the another acronym is tpw = total precipitable water. The value of 2.6 prcm means that if all the humidity of the atmosphere would be condensed, it would cover the Earth’s surface with the layer having the height of 2.6 cm = 1 inch.
Regarding the explanation that prcm is precipitable cm, and that the water vapor in the global atmosphere would amount to 2.6 – 2.66 cm of water worldwide if condensed: That is 26 to 26.6 kilograms of water per square meter. The weight per square meter of this is 255 to 261 newtons per square meter or pascals. The total atmosphere at average surface pressure at sea level has a pressure of about 101,325 pascals, or newtons per square meter. To make things simple with a round number, I would say 100,000 pascals at average elevation earth surface. 261 pascals from water vapor out of 100,000 means the atmosphere is .261 percent water vapor.
Assuming for simplicity a representative pressure level of the tropopause globally being at the 200 millibar/hectopascal level (it varies widely with things such as latitude zone, season and surface temperature) and 99% of the water vapor in the atmosphere being below the tropopause, the troposphere is .32 – .33 percent water vapor.
On average at the surface atmospheric water is ~1%, over the atmosphere as a whole it’s about 0.4%.
It’s more than one percent. Over the moist tropics, it’s 40,000 ppm or more, ie 4%, or two orders of magnitude greater than CO2 concentration. Over much of the temperate zones, it’s not a great deal less, maybe still above 30,000 ppm. The hot deserts are lower, naturally, but only in the cold, dry polar deserts during winters does it get down to CO2 levels.
Since water vapor varies by volume in the lower atmosphere from a trace to about 4%, as a global average, it’s probably between two and three percent of the molecules in the air. IMO, closer to three.
Regarding the claim by Gloateus Maximus that percentage of molecules in the lower atmosphere ranging from very low to 4% indicating an average of 2-3%, probably closer to 3%: There is a strong nonlinearity here favoring greatly lower – please check out a vapor pressure table for water. Those tables are usually in mm Hg, where 100% of standard sea level atmospheric pressure is 760 mm Hg. Partial pressure means partial by molecule count. These tables indicate how much partial pressure at 100% relative humidity in equilibrium with pure water. Most of the world’s atmosphere is too cold to have 2% water vapor even at 100% relative humidity.
” The knowledge of water feedback in not getting more accurate but more inaccurate according to IPCC. ”
Should that be IS not ?
Knowledge IS more inaccurate, or alternatively, knowledge is less accurate.
When looking for a needle in a haystack, first of all you need to find the haystack !
Hey ipcc ; Look over here; see the big orange ball up there; that’s the sun; that’s the input terminal; look there for where to put the feedback.
Yes these dummies have less accurate knowledge.
G
Perhaps we should first find the haystack with a needle in it?
TonyL says:
750 times more greenhouse effect from W/V than from CO2.
The effect of CO2 must be lost in the noise of any W/V fluctuations. This might explain why getting a good read on CSP, TCS and ECS turns out to be so darn hard.
First of all, I have isolated and restated that because it is the crux of the while argument against AGW.That CO2 in Earth’s atmosphere is a bit part player compared to water.
Secondly FFS don’t tell the US administration, we dont want H2O emissions on the list of EPA pollutants..
It’s long been known that monohydrogendioxide is lethal in sufficient quantities. It should be banned.
“It should be banned.”
Outright banned or just regulated and heavily taxed? It is pretty powerful stuff.
monohydrogendioxide?
HO2, that would be one very reactive species, if you could make it in the first place.
Maybe you meant dihydrogen monoxide, there is an effort to ban the stuff.
Website here:
http://dhmo.org/
Go visit, and notice the advertisement for “Acme Klein Bottles”
Where yesterday’s future is here today
The link is real, and takes you to a sales website with a most curious product line.
Gifts for your mathematically inclined friends.
How about Hydrogen Hydroxide ? or Hydroxyl Acid ?
Sounds much more deadly stuff.
The whole damn ocean is Hydroxyl Acid, a little CO2 isn’t going to make it much more acid than that.
g
HO2, hydroperoxyl radical, very reactive an intermediate in combustion reactions.
“First of all, I have isolated and restated that because it is the crux of the while argument against AGW.That CO2 in Earth’s atmosphere is a bit part player compared to water.”
No it’s not.
CO2 is accumulating.
Up from 280 to 400ppm – 40%.
WV precipitates out.
Still a bit player.
If average concentration of H2O be 30,000 ppm in the troposphere and other GHGs be trivial, then the effect of raising H2O and CO2 together from 30,280 to 30,400 clearly shows CO2 still to be a bit player. Besides which, H2O is around 50% better at “reradiating”, and the two GHGs’ bands overlap. That’s why the models need to invent a positive feedback loop not in evidence.
Only in the cold polar deserts, where both H2O and CO2 occur at around four molecules per 10,000 air molecules would adding an extra CO2 (up to four from the prior three) have any measurable effect. Possibly also higher in the atmosphere, where there is less water.
Toneb, Does WV precipitate out completely? Is WV constantly being replenished?
Well, this a bit of good news and bad news. If water precipitates out at the same speed as CO2, then it eliminates the warming effects of CO2. The warming effects of CO2 are overestimated by IPCC.
Its just because you using a 1D-Model, but climate system has some parts more, oceans, Land, Cyrosphere. . For that there are slow moving elements and fast moving elements which are interacting.
And the biosphere reacts to changes in the other spheres.
Even the lithosphere reacts, albeit very slowly to changes in the other spheres.
I don’t see anything which resembles that graph , where did it come from?
The assumption of constant relative humidity is not correct. Here is a graph of global average annual relative humidity at various elevations in the atmosphere expressed in millibars (mb) from 300 mb to 700 mb for the period 1948 to 2013. [Standard atmospheric pressure = 1013 mb. 1 mb = 1 hectopascal (hPa)] The data is from the NOAA Earth System Research Laboratory here. – See more at: http://www.friendsofscience.org/index.php?id=710#sthash.fPaeblG0.dpuf
I, neither, can’t find Figure1. Could we have link to it, and, also, the data that it was made from.
The reanalysis is not a ‘prediction’, it is a model interpolation driven by observational inputs. ie it is not climate “data” but a gridded dataset which tries to fill in the gaps using climate models rather than straight lines.
Someone calling this a ‘prediction’ probably has not researched the material being used.
sorry, that says “depicted”.
“The graphs show that the peak reduction estimate can be regarded a correct estimate.”
?w=842
That is not what I see. The NCEP line shows about four times the dip of the Soden GCM data. The NCEP semi-observational data also shows a strong rebound in 1993 that is not in the models. Clearly models are failing to capture this part of the story too.
Models are trending up ( as a reaction to CO2 warming ) climate is going the other way. Showing, despite a recovery, a net downward offset following Mt P.
This is in accordance with :
and this:
https://climategrog.wordpress.com/uah_tls_365d/
This significant warming effect is currently being spuriously attributed to GHG and other human induced changes and goes a long way to explaining the increasing divergence between models and observational data.
Greg, if you compare the Lower Stratosphere image above with that shown on the WUWT ref page from RSS:
ftp://ftp.ssmi.com/msu/graphics/tls/plots/rss_ts_channel_tls_global_land_and_sea_v03_3.png
there seems some agreement and might to the untutored eye suggest that there is a step down in local temperature at altitude following each of the 2 significant volcanic events , followed by a long period of stability since 1995 to present . The lower temperature presumably means less radiative tranmission to space and thus surface warming following the 2 events , and the absence of major stratospheric aerosol related disturbances since then is contributing to the “Pause” . Is this a conclusion too far?
“The main eruption began on the island of Luton in the Philippines on the 3rd of June, 1991 and concluded on the next day.”
FWIW, the main island of the Philippines is named Luzon.
Mods: for clarity, the typo DB identified above is in the third paragraph below Figure 1. “Luton” should be “Luzon.”
The above assumes that visible light and long wave infrared (LWIR) have the same effect. I have seen people insist that they are not.
The theory seems to be that visible light penetrates into the water column and its energy goes mostly into heating the oceans. LWIR, on the other hand doesn’t penetrate the water column. Its effect is to increase evaporation and heat the air.
Do I have this right? Am I missing anything? Does this have any effect on Dr. Ollila’s work?
Edit: I have seen people insist that they
aredo not.Well light by definition is visible, so no need to say visible light.
And solar radiation penetrates ordinary sea water, with about the same ease, as it stimulates the human eye. That is the blue green wavelengths near 500 nm wavelength penetrate deepest, (1/e absorption depth is 100 meters) while red and UV peel off earlier. Strongest water absorption is at 3 microns, where the 1/e absorption depth is just 1.25 microns. At 288 K BB LWIR radiation peak of 10.1 microns wavelength the 1/e absorption depth is about 10 microns, so only 1% survives for more than 50 microns below the surface (2 mils) .
G
The question remains; does it matter to the findings of Dr. Ollila’s paper?
I think it is a common practice to assume that both the SW radiation from the Sun warms up the Earth’s surface as well as the LW radiation radiating downwards from the sky. The big difference is that the incoming SW irradiation can travel through the atmosphere mainly without absorption: 71 W/m2 by the atmosphere and 167 W/m2 by the surface, together 238 W/m2. The surface emits LW radiation with the rate of 396 W/m2 but only 238 W/m2 is emitted by the atmosphere into the space. Why there is the difference of 396-238 = 158 W/m2? That is the famous GH phenomenon. A part of the LW radiation upwards has been absorbed by GH gases: water 82 %, CO2 11 %, O3 5 % and CH4 & N2O 2 %. The energy does not disappear but it changes its form. In this case it warms the lower part of the atmosphere from -18 C to +15 C (33 C difference), if we make it simple.
It is important to understand that this is not merely a failed prediction, it is a core failure. A non-core failure might be something like “more hurricanes”. It is a failure, but could be explained by various confounding factors.
However a core failure concerns the very mechanism by which the theory proposes the effect occurs. No extra water, no magnified heating, no problem. The theory is wrong.
“No extra water”
It dosn’t say no extra water. That would require non-increasing specific humidity.
I couldn’t find the first plot (RH) at the link given. It doesn’t have the NOAA logo.
The assumption of constant relative humidity is not correct. Here is a graph of global average annual relative humidity at various elevations in the atmosphere expressed in millibars (mb) from 300 mb to 700 mb for the period 1948 to 2013. [Standard atmospheric pressure = 1013 mb. 1 mb = 1 hectopascal (hPa)] The data is from the NOAA Earth System Research Laboratory here. – See more at: http://www.friendsofscience.org/index.php?id=710#sthash.fPaeblG0.dpuf
“The assumption of constant relative humidity is not correct.”
It is not made.
“It is not made.” I guess this depends on the meaning of the word “Is,” to you anyway…
When all governments of the World have their Carbon Tax in place, we will then institute the RH Tax.
When the RH Tax has been universally instituted, we will introduce the Gravitational Force Tax.
Good idea. The obese are consuming too much of our common gravity resources.
That would suck, I think….
For your amusement:
http://www.morningticker.com/2016/03/a-huge-crisis-is-looming-over-africa/
“The study, led by Julian Ramirez-Villegas of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), examined nine crops which make up half of the food production in the region. It came to the alarming conclusion that up to 60 percent of areas that produce beans will become unviable by 2100, as will 30 percent of areas where maize and bananas is grown, according to a University of Leeds statement.”
So, there still remains very little, if any, observational evidence that water vapor is a positive feedback.
TonyL says: 750 times more greenhouse effect from W/V than from CO2. The warming effects of GH gases cannot be summarized in the way you describe, because the absorbing bands overlap with each other and especially with water. The only way is to carry out a separate spectral analysis for each concentration profile combination and to find out the effects by changing the concentrations. That is how I have calculated the relationship 15:1 between the H2O and CO2 in the present atmosphere. By the way, this method gives that the portion of CO2 in the GH phenomenon is 11 %. The percentage of 26 by Kiehl & Trenberth have been used commonly but they have used the wrong atmosphere US Standard Atmosphere 76 and even reduced the water content by 12 %. Because of this the actual water content 1.25 prcm.was only 50 % about the real average global atmosphere value of 2.6 prcm. Water again.
My feeling is that overlapping spectra interfering is not a problem. It is the point. Of course the spectra overlap, if they did not, the species could be considered independently.
To add spectra, I simply rely on the Beer-Lambert Law. At a given wavelength, Absorbance is linear with concentration, and the Absorbances of multiple absorbing species are additive in a simple summing.
I can go ahead and integrate the areas under the absorbance peaks and compare the various compounds of interest.
Question:
What wavelength range do you consider to be the most important for the Greenhouse Effect, and what range do you consider to be the most troublesome?
Thanks in advance.
I can do the integrations and let everybody know what I come up with.
Beer’s Law (for dilute solutions of absorbing species) refers to the ” Absorption coefficient.” It does NOT relate to the radiant energy TRANSMISSION coefficient. It presumes that the photons once absorbed stay dead.
So Beer’s Law is NOT VALID for absorbing species that fluoresce, or in any other way re-radiate at some spectrally shifted wavelength. And the problem with re-radiation of a shifted spectrum, is that such radiation is inherently isotropic, so a Lambertian radiation distribution, such as that emitted form any real earth surface, that is confined to a cosine 2 pi steradian forward transmission path (hemisphere) is converted to a 4 pi UNIFORM isotropic radiation pattern.
So GHG absorption in the atmosphere does not obey Beer’s Law, nor does it obey any simple one dimensional beam propagation model. The intercepted LWIR energy finds a way to continue to propagate, and eventually escape from the earth; it was never trapped.
G
Beer-Lambert law applies for CO2 up to the concentration of 25 ppm. It means that up to this concentration the absorption is linear. Thereafter the absorption curve starts to bend strongly downward and in the present concentration it is already pretty flat. I give here the numerical values in order to show how nonlinear are the warming effects of CO2. The concentration of 280 ppm has raised the Earth’s temperature with about 3.5 C (about 9-11 % of the GH effect of 33 C). Thereafter the increasing temperature effects are as follows: 379 ppm = 0.2 C, 560 ppm = 0.46 C, 800 ppm = 0.71 C and 1200 ppm = 1.0 C. In other words: the portion of CO2 is in maximum about 0.2-0,25 C about the observed 0.85 C in 2011 assuming the constant absolute water profile in the atmosphere.
More information in the slideshows: http://www.climatexam.com
Here is a pretty good illustration in my paper about the overlapping frequencies or wavelengths actually in my presentation: http://www.seipub.org/des/paperInfo.aspx?ID=17162
The overlap of spectra in the CO2 region is minor (see below), you can’t use the Beer-Lambert law in that region either that only applies for very low concentrations of CO2. The current atmosphere has an approximately linear response for CO2.
http://i302.photobucket.com/albums/nn107/Sprintstar400/H2OCO2.gif
The absorption band of CO2 overlaps with the water very badly. That is why the increased concentration of CO2 can increase in reality the absorption only in the wavelength zone from 10 to 14 micrometers. Here is an image where you can see that the absorption area increase from 280 to 379 is about the same as from 379 to 560 ppm
The increased concentrations of GH gases have very different effects. The very low concentrations of CH4 and N2O are still in the linear response of Beeer-Lambert law, CO2 has a logarithmic response with a very low effect bu water has a very strong (and linear) effect without any saturation. You have to read the figure below carefully, because the red horizontal line represents the present atmosphere.
http://www.climatexam.com/#!Dia37.JPG/zoom/c1vmg/image_k3z
The current atmosphere has an approximately
linearlogarithmic response for CO2.aveollila March 8, 2016 at 11:08 pm
The absorption band of CO2 overlaps with the water very badly. That is why the increased concentration of CO2 can increase in reality the absorption only in the wavelength zone from 10 to 14 micrometers. Here is an image where you can see that the absorption area increase from 280 to 379 is about the same as from 379 to 560 ppm
The CO2 absorption peaks at about 15 microns why haven’t you included the center and upper wing of the absorption peak?
Greg says: “The graphs show that the peak reduction estimate can be regarded a correct estimate.”
That is not what I see. The NCEP line shows about four times the dip of the Soden GCM data. The NCEP semi-observational data also shows a strong rebound in 1993 that is not in the models. Clearly models are failing to capture this part of the story too”
You are right, if you select NCEP data set but Soden et al. selected NVAP data set (blue graph). As I wrote, we do not know which of these data sets is correct and therefore, they cannot be used as an evidence about water content changes during the eruption.
Sorry, the figure did not appear. Another trial:
What happens is that additional GHGs in the vertical column distort the lapse rate slope to the warm side.
See here:
http://joannenova.com.au/2015/10/for-discussion-can-convection-neutralize-the-effect-of-greenhouse-gases/
Since there is a reduced temperature gradient with height in the troposphere, convection from the surface slows down so that RH increases at the surface and just above but reduces at higher levels because less water vapour is carried upwards when convection is less powerful
That is what we see in the above charts.
With a higher surface RH, water vapour condenses out at a warmer lower temperature so clouds form at lower warmer levels and those clouds then radiate out to space at that warmer temperature.
That phenomenon provides a re-routing mechanism for radiating to space more energy from water vapour condensate when non-condensing GHGs increase.
David Evans has utilised that scenario in connection with his concept of multiple radiating ‘pipes’ to space which switch radiation to space between pipes so as to cancel any thermal effect from the radiative capabilities of GHGs.
Convective changes thus neutralise radiative imbalances by altering the height from which water vapour condensate radiates to space.
Should be:
“With a higher surface RH, water vapour condenses out at a warmer temperature at a lower height so clouds form at lower, warmer levels.”
David Evans pipe scenario sounds rather like that of Ferenc Miscolczi. It follows from nonlinear thermodynamics (Prigogine) that the dissipative atmospheric system would adapt to increased CO2 to keep overall heat fluxes the same. CAGW is simply wilful ignorance of nonlinear-chaotic systems and processes.
Quantitative Radiative Forcing with Relative Humidity
Ferenc Miskolczi does a quantitative Line By Line (LBL) radiative forcing calculation using the available balloon humidity measurements with numerous latitude/longitude blocks and elevation sections. e.g., see:
The greenhouse effect and the infrared radiative structure of the Earth’s Atmosphere
No, he doesn’t. He says the TIGR data are too unreliable. He says:
“In this article we use the GAT atmosphere as the representative temperature and humidity structures of the global average climate. For studying possible long term changes in the global average optical thickness (due to changes in GHG content of the atmosphere) the TIGR2 archive is not suitable. “
He’s just using a standard atmosphere.
Thanks for clarifying Nick. I was thinking of previous graphs/analyses i had seen where he uses the more detailed data, (NOT constant over time) :
Compare: Greenhouse Effect and the IR Radiative Structure of the Earth’s Atmosphere
(One substantial issue are the adjustments from TIGR 2 to 2000.)
Summary fig. H2O vs CO2: “Former NASA scientist defends theory refuting global warming doctrin
Here’s another graph of NOAA humidity vs time for 3 elevations
Michel Moon realized that I am the disciple of Miscolczi, because we have found the same kind of results about the GH gas effects. It is true that the results about the GH effects calculated by me and by Miskolczi are close to each other. They are independent calculations but they have been calculated by different spectral analysis tools. I have used Spectral Calculator and the water absorption of this tool is little bit weaker (no continuum absorption/emission included). It means that my results are a little bit more “conservative” than those of Miskolczi: for example 11 % versus 9 % concerning the portion of CO2 in the GH phenomenon).
If you are able to get Nick Stokes to back down it will be a huge first. You have him on the run, keep it up. The NASA NVAP-M study results from satellite seem to have been suppressed.
“The truth shall set us free!!!”
Why would YOU use ANY tool that does not compute the real effects. Water droplets in clouds of just a few mils (0.1 mm) are near perfect black body (isotropic) radiators at the cloud Temperature. Spectral Calculator calculates one dimensional beam absorption coefficient.
It does not correctly predict radiant energy transmission in a three dimensional atmosphere.
G
Well, maybe I got too exited, when I learned by trial and error how to add an image on the comments. I like to show an image, which shows in the form of table, that my spectral analyses give the same results as by Kiehl & Trenberth, when using the same wrong atmosphere. There are also the results carried out in the correct average global atmosphere. The difference is in the amount of water. Water is on the driving seat, when we think about the GH effects.
To David L. Hagen. It is true that Miskolczi has used in his latest studies more detailed atmospheric models than me. I have used a single column calculations. Anyway, the results are pretty close to each other. The question of water content is not quite sure yet. If we use the balloon measurements since 1948, the absolute water content has decreased and compensated the warming effects of CO2. I would be cautious and wait another 10 years. The accurate RH measurements started around 1980 with the new Humicap technology from Vaisala, and now the accuracy and reliability is much better.
Water content depends on latitude and season. It might complement your present work to study dependence of sensitivity on latitude. Would such a study be able to definitively separate the effects of CO2 from those of water vapor?
Separation of warming effects of water and other GH gases is not a problem. I have carried out tens of such spectral analysis calculations. These calculation do not solve the problem here: in which way the water in the atmosphere behaves as the GH gases increase the temperature. Stephen Wilde offers one explanation and I think that Miskolczi has introduced a pretty complicated theory with numerical calculations. This theory shows that (with simple terms) the GH effect of the average global clear sky is constant. It means that water eliminates the warming effects of GH gases. I have no scientific skills to judge Miskolzci’s theory. I have noticed that it has been ignored but I have seen only one trial to explain, why it cannot be true.
So far I keep it clear the the assumption of constant RH is not correct.
The RH graphs at different altitudes. I am sorry that the url address is not to the direct address of the data page of NOAA.The data base, what I have used in creating the graphs in my story are here: . Hopefully it went right.
So, something went wrong. I write it here. http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl
Miskolczi’s observations appear to be correct but as far as I know he offers no explanation.
An explanation arising from the fact that higher humidity allows condensation out at a lower height and warmer temperature (so as to radiate more to space) is simple, neat and complies with basic physics.
A powerful and thought-provoking thread. Thanks to all.
Regarding:
“There is only one question remaining, is the RF value of 3.7 W/m2 correct. According to my analysis this value is calculated in the atmosphere, where there is constant RH and therefore positive water feedback.”
I read Dr. Roy Spencer’s blog, and there he does not dispute the 3.7 W/m^2 per 2xCO2 figure or claim it includes any feedbacks. He uses it as a pre-feedback figure. Given his views and expertise, I expect him to say it includes a positive feedback if it does.
I have calculated the RF value of CO2 in the same way as Myhre et al. and I got the formula RF = 3.12*ln(C/280), where C is the concentration of CO2 in ppm. (Myhre: RF = 5.35*ln(C/280). There are three papers referred by IPCC and the other two papers are those of Hansen et al. and Shi. These three papers give different formulas but the results are very close to each other. Strange enough, one of these papers namely Shi, says this way (exact quote): “Water feedback is treated by assuming a fixed relative humidity (FRH) in the model…”. I draw a conclusion that also Myhre’s and Hansen’s calculations have been carried out in the fixed RH conditions, which means doubling the RF value. That is the only explanation I can find.
I have noticed that Myhre’s equation has been commonly used in various analyses as expressing the right RF of CO2 but I have not found anybody carrying his/hers own calculations. Those who say that Myhre’s formula is correct, I would ask: have you calculated by yourself and what are the results of your calculations?
There is a special paper of mine about this issue: http://www.seipub.org/des/paperInfo.aspx?ID=17162
Regarding:
‘Strange enough, one of these papers namely Shi, says this way (exact quote): “Water feedback is treated by assuming a fixed relative humidity (FRH) in the model…”. I draw a conclusion that also Myhre’s and Hansen’s calculations have been carried out in the fixed RH conditions, which means doubling the RF value. That is the only explanation I can find.’
However, water vapor feedback is a feedback. Assumption of constant relative humidity is a simplistic way of evaluating this feedback. The 3.7 W/m^2 per 2xCO2 is a pre-feedback figure that even Dr. Roy Spencer goes along with in his blog.
I noticed your paper stating water vapor presence in terms of Average Global Atmosphere – but representative water vapor presence is less because water vapor’s effect (like all greenhouse gases) is sublinear, and most of the world’s atmosphere has below-average atmospheric concentration of water vapor (which has a superlinear function of temperature (at any specific relative humidity).
If relative humidity is decreasing as a result of warming, then the atmosphere should be getting less cloudy. That would make the cloud albedo feedback positive.
That is s good point. I think that there are two competing theories for AGW theory and they are the Sun theory (Svensmark) and the Astronomical Harmonic Climate Model (Ermakov et al.). In both theories the clouds have an important role in amplifying the effects of the original changes. It is a general understanding the the clouds provide the last resort against the overheating of the Earth. The higher temperatures should mean more clouds. The cooling effect of cloudiness is about -0.1 C per 1 % increase in cloudiness.
The last resort is the Planck feedback
I have added an image above illustrating the absorption bands of GH gases in the average global atmosphere. There is also another image showing the effects of increased concentrations of GH gases. According to my calculations, the effects of water are very close to linear showing now decreasing in the elevated concentrations. I add here an image showing the absorption bands of water and CO2 in the tropical climate. Because there is so much water, the portion of CO2 about the total absorption (=GH effect) is only 5.9%, when in the average atmosphere it is about 11 % and in the polar cap area (above 60 latitude) it is about 24 %.
Relative humidity can be decreasing while absolute humidity remains constant. I believe that is more nearly the case. If so, then, the tonnage of water in the atmosphere remains constant. Any excess precipitates out. There is no a priori reason to believe cloud albedo is anything but constant overall.
Why not ?? Earths ‘steady state’ Temperature depends on the total earth albedo. There is NO cloud albedo. Albedo refers to the total earth rejection of incoming solar spectrum radiant energy. It is not some localized reflection coefficient.
Clouds do more than simply reflect some solar spectrum radiant energy, as part of earth’s albedo. Clouds also radiate efficiently at LWIR thermal radiation wavelengths.
Albedo by definition is solar spectrum ‘reflected’ radiant energy only.
I put ‘reflected’ in apostrophes just so you know that it is not really reflected by clouds; it is strongly refracted by ordinary optical processes in near spherical water droplets, so it is scattered by multiple refractions, which results in much back scattering. The original solar photons exit the earth as part of the albedo. If the leaving photons did not arrive from the sun and exit, instead of remaining on earth, they are NOT part of albedo.
G
Relative humidity determines cloud presence more than absolute humidity does. Note cloudiness in tropical and polar regions, where the temperature difference at any given relative humidity means the absolute humidity is different by an order of magnitude or more.
Lower RH, means fewer clouds and more SW absorption by the ocean, which means more warming.
http://www.climate4you.com/images/HadCRUT3%20and%20TropicalCloudCoverISCCP.gif
Interesting. Vaguely complementary.
Why are you plotting global HadCRUT, land+sea “average” temps against tropical cloud. Wouldn’t it be a better examination of the effect to look at tropical SST ?
The problem with Tropical SST is that it is very constant, held constant by evaporation. Temperature is the wrong metric to use for the energy transfer, for the Tropical SST at least.
Measuring temperature and radiation losses is more appropriate for the higher latitudes. Also Clouds increase the albedo in the Tropics but decrease the albedo in the higher latitudes, simply because of the incident angle.
Increasing cloud coverage in the Tropics decreases the amount of energy entering the system and decreases the cloud coverage in the upper latitudes increasing the energy loss (less albedo).
Whereas Decreasing cloud coverage in the Tropics increases the energy absorption and increases the amount of clouds in the upper latitudes slowing the energy loss.
The location and amount of clouds are the Climatic controllers.
That’s all sounding to get rather contorted and hand-wavey. That tropical SST is fairly constant was my point. You suggestion that tropical cloud kinda casts a shadow on higher latitudes but does not affect tropical SST .. Hmmm. I’d want some solid data to convince me of that.
Greg “That’s all sounding to get rather contorted and hand-wavey. That tropical SST is fairly constant was my point. You suggestion that tropical cloud kinda casts a shadow on higher latitudes but does not affect tropical SST .. Hmmm. I’d want some solid data to convince me of that.
No, what I am saying is that tropical clouds are perpendicular to the sun for maximum reflection. High latitude clouds see a ‘lower’ sun and as a result trap a portion of surface reflected radiation. And the extra water vapor from the tropics increases the amount of clouds in the upper latitudes.
Dr Ollila, thank you for your essay, and link to the published paper.
I have carried out a dynamic analysis of the temperature effects caused by the eruption. I wanted to test two options for the climate sensitivity parameter (CSP). The radiative forcing (RF) at the top of the atmosphere has a linear relationship to the global mean surface temperature change dT:
Have you tested your model against “out-of-sample” data?
Sorry but because I am not a native English speaker, I could not understand your question. Could you try other wording?
Have you used the model to predict the outcomes of events that had not happened when you wrote and parameterized the model?
Hello matthewrmarler, I think that now I understood your question. In this Pinatubo study the model is very simple indeed concerning the temperature effects caused by the radiation flux changes. It is mainly a dynamic model, because the input varies along the time.
I have two papers, which you might be interested in, because there are future projections. The first paper I have a model describing the fluxes between the atmosphere, the biosphere and the ocean and there are also are two projections of the CO2 concentration trends for the future:
http://sciencedomain.org/issue/1288
Another paper introduces two competing theories for AGW and the future forecasts of these models:
http://www.scienpress.com/journal_focus.asp?main_id=59&Sub_id=IV&Issue=1564
Dr Ollila. I have had a look at your paper “Cosmic theories of Greenhouse gases…” You say this includes future forecasts for different models – am I correct in thinking that Figure 8, where it says “The black curve is the combined effect of SDI, the Sun and GH gases.”, that this is the future forecast for the model you describe here?
To seaice1. Yes in Fig. 8 there is a future forecast up tio 2050. Why it is ending there? The available data of two major cosmic forces was available only up to 2050.
Dr. Ollila,
Thank you for more information about “Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model” by Hansen et el, Journal of Geophysical Research, 20 August 1988. It is perhaps the most frequently cited example of a successful test of climate models.
Its skill is evaluated more or less in “Skill and uncertainty in climate models” by Julia C. Hargreaves, WIREs: Climate Change, July/Aug 2010 (ungated copy).
What might we find from a rerun of Hansen’s model using your suggestions? We’ll never know! Hargreaves reported that “efforts to reproduce the original model runs have not yet been successful”. The dog ate the model, so it can’t be rerun with updated observations or different assumptions.
Very sloppy archiving for the project to save the world.
“The dog ate the model”
There is no reason to believing archiving is the problem. Complex codes need maintenance as hardware, software libraries etc change. The original program evolved into GISS Model E, so it was maintained in that sense, but reviving a 30yo version would be a major task. It probably used something like SCSS for code management, and IMSL libraries etc. Getting old versions of those working would be a challenge. And the original people probably won’t be available.
Nick Stokes
Certainly. But how do you solve this part of the “running old code, getting BAD solutions” problem?
In 1986, they thought TSI = 1371 watts/m^2,
In 1988 ACRIM1 had 1367
Then in 1996, the calculation had to be based on TSI = 1365 watts/m^2,
Then in 2010, the calculations had to be based on TSI = 1362 watts/m^2
Now, it the same “robust” calculations keep coming up with the same forcing from a theoretical, fundamental physics basis but while chasing a input heat energy that has dropped by more than 3 times the “net forcing” that has been calculated for a doubling in CO2 by man, how accurate the robust fundamental calculations?
Should they now not be predicting massive cooling of -6 watts/m^2 forcing, since the input energy has dropped by that much during their season of running GCM?
“Should they now not be predicting massive cooling of -6 watts/m^2 forcing”
No. For a start, the forcings are per unit area of Earth surface. So all those numbers need to be divided by four. But solar is part of the forcing scenario. Hansen said in the 1988 paper that there was no evidence to that time to base a forecast variation, so they took it i to be constant. The variations you cite are not actual changes in TSI, but mostly changes in measurement value with the instruments of the time. TSI itself didn’t change from 1371 to 1362 W/m2. The historic variation they now use for CMIP 5 is:
http://data.giss.nasa.gov/modelforce/solar.irradiance/tsi_CMIP5.png
That is a variation of range about 1.5 W/m2, which after dividing by 4 gives a forcing oscillation of about 0.4 W/m2.
Nick,
Thanks for the additional color on this. I’ve twice had IT run old code (once for an audit, once for an arbitration), the latter about 30 years old. Neither was a big project, but the context was in a large corp — not a science institution.
I’ll ask my one of my cyber co-authors for an opinion on this.
Nick,
I got an answer.
The team I worked with were skilled, had little turnover, and a consistent systems environment.
Still, if we’re talking about saving the world this looks like an important project with trivial costs. What’s the cost of allowing the current gridlock to continue for another 28 years?
A common attitude seems to be trillions for prevention and mitigation but not a cent for testing. Penny wise and all that.
As I described earlier, there are three studies on the RF effect of CO2. Hansen et al. applied a model but Myhre et al. calculated the RF effects for three different atmospheric profiles (tropical, NH, SH) for the RF effects for the change from 280 ppm upwards. Shi applied broad band calculations. My method is actually the same as used by Myhre et al.
I’ve just plotted the NCEP monthly area weighted data with a 12mo low-pass filter.
It looks a bit different to figure 1.
http://climategrog.files.wordpress.com/2016/03/ncep_rh1.png
Higher more rarified altitudes show marked drop in RH until 1977 ( the end of cooling ) , then rise to about 1998. Mid troposphere seems to generally counter this.
The lowest level in this graph : 600, 700, 850mb show a slight increase in the last 15-20 years. Beginning of cooling ? Maybe this data has not been ‘corrected’ yet.
Actually this looks very different from figure 1. Is that the area weighting or partly the fact that I low-pass filtered the monthly data instead of using their ‘seasonal averages’.
Perhaps Dr. Ollila could clarify what he plotted.
850 and 925 mb levels of NCEP data
Sorry to coming so late to comment this issue. Partially the delay is due to my different time zone.
I did not check the properly the latest version of Figure 1, because I did not used these values anywhere in my calculations otherwise than the other water content graph. Figure 1 was used only to show that even by eye it is possible to see that the assumption of the constant RH is not correct. I created this figure first time for my paper published in 2013. Now after your comments I noticed that the data has been updated. The original data set can be found in this address:
http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl
The data set is NCEP Reanalysis published by NOAA. I have used the global values with seasonal average and area weight grids. The version in my story was based on the earlier version. The newest version is from 13th of May 2014. The climatology in the newest version is 1981-2010, when it was in the older version 1971-2000. The main difference seems to be that the new values are about 2 % on the higher level. Anyway there are the same downward trends as in the older version. Here is a figure with older and newer graphs:
The earlier data in that sequence, particularly, is to be taken with scepticism. Not the fault of NCEP – there just isn’t much reliable data. Here is the note that goes with that data:
“The humidity analysis is believed to be the weakest of the primary atmospheric analyses; i.e., Z, T, U, V, and Q. The other primary variables (Z, T, U and V) and their gradients have to be internally consistent. One can not change T without changing U, V, and Z. As a result, the internal consistency provides a check and constraints on these fields. The humidity analysis, however, is unconstrained (except for q <= q-sat) and is effectively produced by a univariate analysis with no dynamical constraint on the gradients. Then there is the sampling problem. The humidity has many small-scale features and a single measurement may not be representative of a grid box average.
By the way, did I mention instrument errors?"
Thanks for some very informed input on this discussion. A rarity here. ( As on most blogs )
There has been a lot on RH recently and when I read that at NCEP, I realised the whole thing was pretty hopeless. I posted those graphs because they seem at odds with the starting point of this post : figure 1 “sight test”.
Dr. Ollila initially gave a bad link for the origin of what he plotted and he still has not said what he actually plotted and it was not marked on his graph. This is rather unsatisfactory.
It seems that he could have plotted a non area weighted average and thus heavity skewed the data towards changes in the polar regions.
Can we can hope that the data is not complete garbage or the result of model assumptions in the NCEP reanalysis ( which is not to be ruled out )?
I
1. Re quantitative importance of water vapor for the Greenhouse Effect: From infrared (IR) spectra of outgoing radiation as seen by satellites looking down on a cloudless Earth, water vapor is roughly twice as important as CO2. Sample spectra are found in Grant W. Petty’s excellent book “A First Course in Atmospheric Radiation, Second Edition” and Fig. 3 at http://climateaudit.org/?p=2572 .
2. However, water vapor does not provide a 200% positive feedback because doubling CO2 does not double water vapor. Increasing temperature from 15.0 to 15.6 Celsius increases saturated water vapour from 12.788 to 13.290 mm Hg [Handbook of Chemistry and Physics], an increase by a factor of 1.039, or by 3.9%. Multiplying by a weighting factor of 2 would increase this only to 8%, not 200% (the main absorption lines of both CO2 and water vapor are highly saturated). This factor of 8% increase would also apply at 50% relative humidity instead of 100%. For any starting temperature from 40.0 to -10.0 Celsius, an increase by 0.6 Celsius increases water vapor by only 3.2% to 5%. This relatively constant % increase results from the fact that saturated water vapor is roughly an exponential function of absolute temperature, and exp[K(T+0.6)] = exp(KT).exp(0.6K) = constant.exp(KT) for any T, since K and therefore 0.6K and exp(0.6K) would both be constants.
3. I have used 0.6 K instead of 1 K for the climate sensitivity on doubling CO2 (not including feedbacks) because the main gases of the atmosphere (N2, O2, Ar) are nonpolar molecules that cannot and do not emit any significant infrared (IR) radiation. Therefore the outgoing TOA (Top Of the Atmosphere) IR is not radiated from a black body surface at 10 km (or 5.5 km) altitude, but is better understood as that part of the black body IR emitted from the 15.0 C (288.2 K) solid and liquid surface of the Earth which is NOT absorbed by greenhouse gases such as CO2, water vapor, ozone, etc. The Stefan-Boltzmann law says that at 288.2 K and emissivity 0.98, the surface emits 383.34 W/m^2. Adding a radiative forcing of 3.7 W/m^2 which must be emitted to compensate at steady state for increased absorption on doubling CO2, the warmer Earth must emit 387.04 W/m^2. Using the Stefan-Boltzmann law backwards, this corresponds at emissivity 0.98 to a new temperature of 288.893 K. This gives 288.893 – 288.2 = 0.693 degrees for the temperature sensitivity not including feedbacks. However, Jack Barrett at his excellent website http://www.barrettbellamyclimate.com/ (see the section “The hard bit”) has rerun the MODTRAN simulated IR spectrum to 70 km altitude (not the 20 km assumed to be the TOA). The results show slightly increasing CO2 emission from the stratosphere on doubling CO2 (because of the temperature inversion caused by the absorption of incoming UV and visible Solar radiation by ozone, the photons escaping at central CO2 frequencies come from a higher altitude, i.e. at a higher temperature), equivalent to about 0.11 degrees. So I have rounded off the climate sensitivity not including feedbacks to 0.693 – 0.11 = 0.6 degrees.
4. In addition, increasing water vapor is likely to increase cloud cover, which provides a net negative feedback. Assuming this negative feedback only just cancels (not overwhelms) the 8% positive feedback due to increased water vapor absorption, the climate sensitivity INCLUDING WATER VAPOR AND CLOUD FEEDBACKS is likely to be only about 0.6 degrees, not the 3 degrees assumed in the literature and by the IPCC. This explains why there has been an 18 year hiatus/pause in global warming, even as CO2 continued to increase recently. Increasing CO2, manmade or natural, is not anywhere the danger as previously thought, and limited financial and manpower resources ought to be used for other problems.
5. The literature also got the mechanism of the greenhouse effect wrong. The troposphere does not consist of spherical shells of decreasing temperature at increasing altitude, each emitting a Planck black body spectrum until finally “the IR photons escape to outer space at 10 km”. At 10 km, the Stefan-Boltzmann law at 220 K predicts an emission of only 130 W/m^2, nowhere near the observed 240 W/m^2. Calculating an altitude of 5.5 km, where the temperature is 256 K which would correspond to emission of 240 W/m^2, assumes emission from a Planck black body shell, and the observed spectra simply do not follow Planck curves. Instead, the observed spectra are net ABSORPTION spectra (NOT EMISSION spectra), where some of the photons emitted by the 288.2 K black body surface are absorbed at CO2, water vapor and ozone frequencies. That energy is not simply re-emitted as photons to the next layer higher up, but is transferred during non-radiative collisions to the main molecules of the troposphere (N2, O2, Ar) which make up 99.9% of dry air and do not emit any significant IR. The energy ends up increasing the translational and rotational energies of these molecules which outnumber CO2 by 2500:1. I.e. the troposphere warms up, the greenhouse effect. Even Petty’s book title betrays lack of understanding, since it includes “Atmospheric Radiation” [i.e. Emission, not Absorption].
If the result and theory is correct, there are usually more than one way to get the same results. In my original paper I have used two tools (Spectral Calculator and MODTRAN) and two different methods plus the traditional energy balance equation with a pen and paper. All these methods come to the CS of 0.27….0.3 K.
Relevant links:
Richard Telford – The Peer Review of Ollila (2016
Scholarly Open Access – Finnish Man Uses Easy Open-Access Journals to Publish Junk Climate Science
ScienceDomain Reviewer 1st round comment
cienceDomain Reviewer Final Evaluation
Predatory journal. $500 bucks and you too can be a peer-reviewed published scientist.
It might be useless to start the show my replies to every comment of reviewers. I would rather ask, what do you think about those two papers, which have been referred to be solid evidence about positive water feedback during the Pinatubo eruption? There are two points, which make the analysis of positive water feedback to work: 1) selection of a lower solar irradiation decrease -4.5 W/m2 instead of -6.0 W/m2 used by any other researchers, 2) using the humidity decrease in a very “creative” way, which has turned the trend upside down. As usually this review process included relevant questions but also some, which were not so relevant. For example the main reviewer wanted to disapprove the paper, because I had used also UAH MSU temperature as a reference beside the average temperate of 4 temperature data sets. According to the reviewer, UAH MSU is not a surface temperature. If we are accurate as the Sun, it is a correct comment. But the authors of the paper of Soden et al. had also used UAH MSU temperature and only it.This happened during those days, when there was no pause in the temperature and trends of UAH MSU were close to other data sets. This is of course my personal opinion but I would be ready to give my paper for a re-review together with the paper of Soden et al. It would be interesting to see the results.
It should be noted that the revieweer who did not want to show his name seems to be John Abraham
He is frequent contributor at the “unreliable” alarmist web site SkS
https://www.skepticalscience.com/posts.php?u=2502
and frequent contributor to the fact-distorting, alarmist newspaper web site of The Guardian, where every climate article now seems to carry the subtitle : ” Climate Consensus – the 97%”
http://www.theguardian.com/profile/john-abraham
He is qualified to raise pertinent criticisms but seems to be an activist as much as scientist.
The UAH issue seems to be a key plank in the SkS and warmist agenda to discredit datasets that don’t show the “right” message. I guess RSS is now OK, now that they don’t correct for diurnal drift any more.
I have sent the following reply to the web page of Telford:
Yes, in the open peer review system the possible weaknesses are readily available. I admit that three of the reviewers gave only formal comments. The first reviewer was very detailed in his/her comments trying to turn every stone to find out reasons to reject the paper. It was very obvious what is the attitude of the reviewer based on this comment: “On line 175 the author(s) claim that prior researchers included a positive water vapor feedback. There really is no doubt about this.” In the section “Results and discussion” I have a summary showing that a former paper of Soden et al. (it is called a solid evidence about the positive water feedback) is based on the proper selection of flux changes not used by the other researchers. Soden et al. have used in a very “creative” way the humidity trends in order to turn upside down the trend. I am ready to give the paper of mine to any review process together with the paper of Soden et al. It would be interesting to see the results.
Yes, I admit that I visit sauna three times a week. But you are wrong about the money. I did not pay $500 but only $50 from my own pockets. What we should think about those papers published with the fee of $2000 – $3000?
My original profession is not a civil engineer. I used to be a process and automation engineer. You may say that I have no idea about the climatology. At least I know what is the water content of the average global atmosphere. Kiehl & Trenberth used the US Standard Atmosphere 76 in calculating the portion of CO2 in the GH phenomenon and getting the result of 26 %. Have you any idea what is wrong with this atmosphere?
Dr. Antero Ollila
http://multi-science.atypon.com/doi/pdf/10.1260/0958-305X.25.8.1439
Each method shows that, on average, water vapour contributes approximately 96% of current greenhouse gas warming. Thus, the factors controlling the amount of water vapour in the air also control the earth’s temperature.
TOTAL BACK RADIATION OF ALL GHG Figure 7 is FAQ 1.1 Figure 1 from page 96 of AR4. It shows the radiation balance for the earth and that the back radiation of all of the greenhouse gases is 324 W m-2. This is the value used to calculate the RF [radiative forcing] of CO2 at 378 ppmv as (8.67/324)/100 = 2.7% back radiation of the total of all of the greenhouse gases.
From Table 1, CO2 accounts for 2.7% of the global warming while all of the other gases account for approximately 0.7% for a total of approximately 3.4%. It becomes evident that, on average, water vapour accounts for approximately 96% of the current global [greenhouse effect] warming. This is an important finding because it leads to the conclusion that the factors controlling the average level of water vapour in the atmosphere also control atmospheric temperature.
[O]n average, each molecule of CO2 is surrounded by approximately 23 molecules of water vapour at ground level. … If the warming effect of water molecules and CO2 molecules were the same, then the contribution of CO2 would be (1/22.7) = 4.4% of that of water vapour. But from the previous section, water molecules are 1.6 times more effective at warming than CO2 molecules. Using this value and the ratio of 22.7:1, the contribution of CO2 to warming of the atmosphere is approximately (1/22.7)/1.6 = 2.8% of that of water vapour. As water vapour is approximately 96% of the total RF of all of the GHG, the contribution of CO2 is approximately 4% less than this, i.e., 2.69%. If the average RH were 60%, the contribution of CO2 would be ((1/27.4)/1.32) x 0.96 = 2.65%. For practical purposes, these values are the same as the 2.7% obtained by the quadratic model.
The increased absorption band areas are directly related to the warming effects of each GH gas. As far as I know the spectral analysis is the only way to find out the small changes of the absorption bands. The absorption / emission processes at the molecular level are so complicated that they cannot be calculated accurately enough with no other methods. I think that many people do not know that GCM’s do not apply spectral analyses in their calculations but they utilize results of real spectral analyses. By the way the absorption spectra in HITRAN database has been checked in the real climate conditions and the error is less than 1 %.
Yes, that’s the real physics part. The rest fluff and frig-factors typically misrepresented as “known, basic physics” .
Lower RH at higher altitudes could be a sign that CO2 causes cooling, not warming.
I wrote a tongue-in-cheek post about CO2 causing global cooling at http://wattsupwiththat.com/2016/01/08/how-thunderstorms-beat-the-heat/ and everybody scoffed. It predicted cooling caused by a greater cloud cover. Cloud cover is increased because more CO2 in the lower levels reduces the IR flux to the higher levels. That means less absorption by water at higher levels, cooler water and more condensation (clouds).
What I didn’t mention was that it predicts lower cloud levels. If the enthalpy of the atmosphere is greater very near the surface and lesser above then it will lower cloud levels and increase condensation. Lower cloud levels mean less absolute humidity at higher levels. There are a number of possible explanations why this would mean less relative humidity too.
I’m stickin’ by my guns. CO2 causes cooling and it’s because water condenses at lower temperatures than CO2. More CO2 absorbing the IR below, less IR reaching the water vapor above. Using the climatist assumptions about IR radiation, that means more evaporation of water below and more condensation of water above. That in turn means higher albedo and more insolation reflected back to space. That means global cooling.
“I’m stickin’ by my guns. CO2 causes cooling and it’s because water condenses at lower temperatures than CO2. ”
That sounds like negative feedback , which will reduce or negate GHG effect of CO”, it will not produce actual cooling.
http://www.sdiarticle2.org/prh/PSIJ_33/2016/Rev_PSIJ_23242_Joh_ANON_v1.pdf
Many serious criticisms of this paper by the main reviewer seem to have gone unaddressed.
University of St Thomas? John Abraham?
see above, warmist activist:
https://www.skepticalscience.com/posts.php?u=2502
http://www.theguardian.com/profile/john-abraham
It is not necessary to have the LW component explicitly . Just use ERBE total flux in both directions. The difference is the energy budget anomaly which comprises both the aerosol effect and the climate feedback.
That was the method suggested Dr Roy Spencer which I used in my study ( link to Spencer’s blog included.).
I have replied to each comment of every reviewer but it looks like that the magazine does not publish the author’s comments.
That is certainly not the impression that we get from review documents posted . Maybe you should ask for a refund 😉
True, it is misleading if you made full replies.
If there is a lag of six months in the aerosol spreading , I don’t see how you can take that is a globally valid figure. Most of the energy comes into the system in the tropics. There the spread happened within a month or two.
There is detailed gridded AOD data for four different atmospheric heights available here:
http://data.giss.nasa.gov/modelforce/strataer
That had peaked already and dropped to about 50% within 6mo.
Using just the tropics, I found ( as did Spencer et al ) a lag of about 12-13mo in the radiative effects ( reflecting the surrface climate reaction ) . That corresponds to a time constant of about 8 mo.
If you are effectively subtracting 6 months from that as the time it takes to reach high latitudes that will not represent the majority of the disruption to the energy budget and will seriously skew any estimation of time constant.
It is unclear from figure 1 in the paper when the minimum on UAH happens since there is still a strong 6 monthly residual in your anomaly data, though I would estimate 1992.8 by eye, you need to determine this better.
That would also agree my and Spencers lag correlation for the tropics of 12 to 13 mo.
AOD and ERBE data outside the tropics are patchy. Aerosol spreading involves notable delays and global data sets averaging land and SST are or questionable validity for energy budget calculations and will in any case bias towards the land of NH .
https://judithcurry.com/2016/02/10/are-land-sea-temperature-averages-meaningful/
I would suggest focussing on tropics where data is more continuous, physically consistent and where the ‘action’ is in terms of energy budget.
https://climategrog.wordpress.com/2015/01/17/on-determination-of-tropical-feedbacks/
I have defined the dead time from the global UAH MSU monthly temperature, and it is quite easy to find out, when the global temperature starts to decline; that delay is 1.6 months. If you look at the measured temperature and the simulated temperatures, they follow pretty well each other.
[Oops. Misplaced this comment above]
It is not necessary to have the LW component explicitly . Just use ERBE total flux in both directions. The difference is the energy budget anomaly which comprises both the aerosol effect and the climate feedback.
That was the method suggested Dr Roy Spencer which I used in my study ( link to Spencer’s blog included.).
This is a quote from my study: “There has been a special GEWEX project to assess the surface radiation budget data sets based on the available data at the top of the atmosphere (TOA). By studying the GEWEX results, the author’s conclusion is that the LWDN fluxes could not be estimated reliably in this project based on the other existing flux data.” The ERBE flux is the easiest substitute for the real LWDN flux.
Thanks for the reply. I saw that.
You may like to look at the ERBE in more detail. There was some very silly assumptions made about there being constant meteorology throughout the day in the tropics ! Obviously by someone who’d never been there.
This led to a massive alias of the diurnal cycle that comes out at 36d in the tropics ( 72d outside that ). This affects the upward SW : hence the derivative LW flux.
https://climategrog.files.wordpress.com/2015/02
Pretty ain’t it ?
It was pointed out by Trenberth that taking the usual monthly averages would result is a circa 6mo alias in the data. ( 198d I think is more accurate ). This is
why ERBE only provide 36d and 72d datasets now. That avoids the alias but there may be some residual oddities. At some stage they provided monthly so be careful to avoid that.
It will probably be necessary to fit a spline of do a Cat-Mull interpolation if you need monthly data.
I got the pretty picture by extracting the daily data. It took a fair bit of effort adapting some FORTRAN code but it was informative.
BTW the red line you can just see popping above the others is the Pinatubo event.
Regarding climate sensitivity to the Pinatubo eruption, and Earth’s climate sensitivity: The Pinatubo eruption’s cooling and the warming after its effects faded occurred over only a few years, which is period much too short to get the atmosphere in equilibrium with the part of the ocean that is above the thermocline. To do that requires decades. The .27 degree per W/m^2 that is indicated above sounds to me like somewhat over half the equilibrium climate sensitivity, which I think is around .35-.4 degree per W/m^2.
(I expect a lower figure than IPCC does because positive cloud albedo feedback requires water vapor feedback less than that of constant relative humidity. The zero-feedback except Planck figure is about .33 degree per W/cm^2.)
I have used in this paper the time constant of 2.74 months for the surface ocean (=mixing layer of 75 m in depth). The temperature below this depth has not time to react for this kind of a rapid change. The model calculated temperature response of the dynamic model follows very well the real temperature change proving that the time constants of land and sea are correct. The differences in using CSP 0.27 versus 0.5 are very big.