Guest Post by Willis Eschenbach
This is the third in a series ( Part 1, Part 2 ) of occasional posts regarding my somewhat peripatetic analysis of the data from the TAO moored buoys in the Western Pacific. I’m doing construction work these days, and so in between pounding nails into the frame of a building I continue to pound on the TAO dataset. I noticed that a few of the buoys collect data on both shortwave (solar) radiation and longwave (infrared or greenhouse) radiation at two-minute intervals. For a data junkie like myself, two-minute intervals is heaven. I decided to look at the data from one of those buoys, one located on the Equator. at 165° East.
Figure 1. Location of the buoy (red square) which recorded the data used in this study. Solid blue squares show which of all the buoys have the two-minute data. DATA SOURCE
It was a fascinating wander through the data, and I found that it strongly supports my contention, which is that the net effect of clouds in the tropics is one of strong cooling (negative feedback).
To start with, I looked (as always) at a number of the individual records. I began with the shortwave records. Here is a typical day’s record of the sun hitting the buoy, taken at two-minute intervals:
Figure 2. A typical day showing the effect of clouds on the incoming solar (shortwave) radiation.
In Figure 2 we can see that when clouds come over the sun, there is an immediate and large reduction in the incoming solar energy. On the other hand, Figure 3 shows that clouds have the opposite effect on the downwelling longwave radiation (DLR, also called downwelling infrared or “greenhouse” radiation). Clouds increase the DLR. Clouds are black-body absorbers for longwave radiation. After they absorb the radiation coming up from the ground, they radiate about half of it back towards the ground, while the other half is radiated upwards The effect is very perceptible on a cold winter night. Clear nights are the coldest, the radiation from the ground is freer to escape to space. With clouds the nights are warmer, because clouds increase the DLR. Figure 3 shows a typical 24 hour record, showing periods of increased DLR when clouds pass over the buoy sensors.
Figure 3. A typical day showing the effect of clouds on the downwelling longwave radiation (DLR).
Once again we see the sudden changes in the radiation when the clouds pass overhead. In the longwave case, however, the changes are in the other direction. Clouds cause an increase in the DLR.
So, here was my plan of attack. Consider the solar (shortwave) data, a typical day of which is shown in Figure 2. I averaged the data for every 2-minute interval over the 24 hours, to give me the average changes in solar radiation on a typical day, clouds and all. This is shown in gray in Figure 4.
Then, in addition to averaging the data for each time of day, I also took the highest value for that time of day. This maximum value gives me the strength of the solar radiation when the sky is as clear as it gets. Figure 4 shows those two curves, one for the maximum solar clear-sky conditions, and the second one the all-sky values.
Figure 4. The clear-sky (blue line) and all-sky (gray line) solar radiation for all days of the record (2214 days).
As expected, the clouds cut down the amount of solar radiation by a large amount. On a 24-hour basis, the reduction in solar radiation is about 210 watts per square metre.
However, that’s just the shortwave radiation. Figure 5 shows the comparable figures for the longwave radiation at the same scale, with the difference discussed above that the clear-sky numbers are the minimum rather than the maximum values.
Figure 5. The clear-sky (blue line) and all-sky (gray line) downwelling longwave radiation (DLR) for all days of the record.
As you can see, the longwave doesn’t vary much from clouds. Looking at Figure 3, there’s only about a 40 W/m2 difference between cloud and no cloud conditions, and we find the same in the averages, a difference of 36 W/m2 on a 24-hour basis between the clear-sky and all-sky conditions.
DISCUSSION
At this location, clouds strongly cool the surface via reflection of solar radiation (- 210 W/m2) and only weakly warm the surface through increased downwelling longwave radiation (+ 36 W/m2). The net effect of clouds on radiation at this location, therefore, is a strong cooling of – 174 W/m2.
This likely slightly overstates the radiation contribution of the clouds. This is because, although unraveling the effect on shortwave is simple, the effect on longwave is more complex. In addition to the clouds, the water vapor itself affects the downwelling longwave radiation. However, we can get an idea of the size of this effect by looking at the daily variation of longwave with and without clouds in more detail. Figure 6 shows the same data as in Figure 5, except the scale is different.
Figure 6. As in Figure 5 but with a different scale, the clear-sky (blue line) and all-sky (gray line) solar radiation for all days of the record.
Note that the minimum (clear-sky) DLR varies by about 10 W/m2 during the 24 hours of the day. Presumably, this variation is from changes in water vapor. (The data is there in the TAO dataset to confirm or falsify that presumption, another challenge for the endless list. So many musicians … so little time …). Curiously, the effect of the clouds is to reduce the underlying variations in the DLR.
This warming due to water vapor, of course, reduces the warming effect of the clouds by about half the swings, or 5 W/m2, to something on the order of 30 W/m2.
Finally, to the perplexing question of the so-called “cloud feedback”. Here’s the problem, a long-time issue of mine, the question of averages. Averages conceal as much as they reveal. For example, suppose we know that the average cloud cover for one 24 hour period was forty percent, and for the next 24 hours it was fifty percent. Since there were more clouds, would we expect less net radiation?
The difficulty is, the value and even the sign of the change in radiation is determined by the time of day when the clouds are present. At night, increasing clouds warm the planet, while during the day, increasing clouds have the opposite effect. Unfortunately, when we take a daily average of cloud cover, that information is lost. This means that averages, even daily averages, must be treated with great caution. For example, the average cloud cover could stay exactly the same, say 40%, but if the timing of the clouds shifts, the net radiation can vary greatly. How greatly? Figure 7 show the change in net radiation caused by clouds.
Figure 7. Net cloud forcing (all-sky minus clear-sky). Net night-time forcing is positive (average 36 W/m2), showing the warming effect.
In this location, the clouds are most common at the time they reduce the net radiation the most (mid-day to evening). At night, when they have a warming effect, the clouds die away. This temporal dependence is lost if we use a daily average.
So I’m not sure that some kind of 24-hour average feedback value is going to tell us a lot. I need to think about this question some more. I’ll likely look next at splitting the dataset in two, warm dawns versus cool dawns, as I did before. This should reveal something about the cloud feedback question … although I’m not sure what.
In any case, the net cloud radiative forcing in this area is strongly negative, and we know that increasing cloud coverage and earlier time of cloud onset are functions of temperature. So my expectation is that I’ll find that the average cloud feedback (whatever that means) to be strongly negative as well … but in the meantime, my day job is calling.
A final note. This is a calculation of the variation in incoming radiation. As such, we are looking at the throttle of the huge heat engine which is the climate. This throttle controls the incoming energy that enters the system. As shown in Figure 7, in the tropics it routinely varies the incoming energy by up to half a kilowatt … but it’s just the throttle. It cools the surface by cutting down incoming fuel.
The other parts of the system are the tropical thunderstorms, which further cool the surface in a host of other ways detailed elsewhere. So the analysis above, which is strictly about radiation, actually underestimates the cooling effect of tropical clouds on surface temperature.
All the best, please don’t bother questioning my motives, I sometimes bite back when bitten, or I’ll simply ignore your post. I’m just a fool like you, trying to figure this all out. I don’t have time to respond to every question and statement. Your odds of getting a reply go way up if you are supportive, on topic, provide citations, and stick to the science. And yes, I know I don’t always practice that, I’m learning too …
w.
PS — Here’s a final bonus chart and digression. Figure 8 shows the average of the actual, observed, measured variation in total downwelling radiation of both types, solar (also called shortwave) radiation and longwave (also called infrared or “greenhouse”) radiation.
Figure 8. Changes in average total forcing (solar plus longwave) over the 24 hours of the day.
Here’s the digression. I find it useful to divide forcings into three kinds, “first order”, “second order”, and “third order”. Variations in first order forcings have an effect greater than 10% of the average forcing of the system. For the system above, this would be something with an effect greater than about seventy W/m2. Figure 7 shows that the cooling from clouds is a first order forcing during the daytime.
Variations in second order forcings have an effect between 1% and 10% of the average. For Figure 8 that would be between say seven and seventy W/m2. They are smaller, but too big to be ignored in a serious analysis. With an average value of 36 W/m2, the warming from night-time clouds is an example of a second order forcing.
Finally, variations from third order forcings are less than 1%, or less than about seven W/m2 for this system. These can often be ignored. As an example of why a third order forcing can be ignored in an overall analysis, I have overlaid the Total Radiation (red line in Figure 8) with what total radiation would look like with an additional 7 W/m2 of radiation from some hypothetical CO2 increase (black line in Figure 8). This seven watts is about 1% of the 670 W/m2 average energy flowing through the system. The lines are one pixel wide, and you can scarcely see the difference.
Which is why I say that the natural governing mechanisms that have controlled the tropical temperatures for millions of years will have no problem adjusting for a change in CO2 forcing. Compared to the temperature-controlled cloud forcing, which averages more than one hundred and fifty W/m2, the CO2 change is trivial.
TimTheToolMan says:
The problem is that warming doesn’t have a very specific meaning in common parlance. You say “raising the temperature” but warming can equally mean warming by putting on a jumper or warming by standing in front of the fire.
I’ll give you that — which is yet one more reason to avoid “warming”, “reducing the cooling”, etc and stick to statements about energy.
Warming by standing in front of the fire is precisely not what GHGs do even though a simplistic energy flow consideration, mathematically, amounts to the same thing. Its only when you properly consider conservation of energy or in a general sense that the energy that comes from the clouds came from the ocean in the first place that an appreciation for the effect can be made.
This confuses me. I could say that ALL the energy came from the sun — including the energy from the burning logs. So now we have the energy coming from the same source AND being the “same mathematically”. What other reason can there be to call the energy different? Does a 3 um photon from a cloud add energy to you in any different way than a photon from the fire would? How does a “proper consideration of conservation of energy” differentiate a photon from a GHG molecule vs a photon from a fire vs a photon from the sun?
At a more fundamental level, I would say that the source of the energy is irrelevant. Some of the energy in the cloud came from the ocean; some came directly from the sun; some came from radioactive decay; some from kinetic energy of in-falling asteroids stored as thermal energy since the earth was formed. This doesn’t make an iota of difference. Once the energy is in the cloud, it is the cloud’s energy, pure and simple. There is no little tag attached to a bit of energy saying “I came from convection from the ocean” or “I came from a photon produced by a GHG molecule”. The cloud doesn’t “re-radiate” IR energy it received, it simply radiates ITS OWN energy.
cba says
There is NO altitude which allows radiation to escape. This is a function of wavelength and on strong line centers, it never happens. Elsewhere in the spectrum, emissions from the surface go straight through. As one goes up in the atmosphere, line widths narrow, increasing the liklihood of capture, but over narrower and narrower bandwidths – hence allowing more energy through. WHen dealing with smaller areas and lower temperature differences, the liklihood of absorption for strong lines tends to approach the liklihood of emission and so there is very little net radiative transfer between these areas. Given two areas of the same temperature, there is no net thermal transfer of any kind. This doesn’t and can’t happen in the atmosphere because of the geometry of the system and we can use the plane radiative transfer approximation for this.
—————-
It does escape even at the central C02 line near 670 cm-1 , at a sufficiently high altitude. If the absorption length is 10 meter, then at altitudes where the pressure is 1/1000 of ground atmospheric pressure, the absorption length becomes comparable to the atmospheric thickness constant. z0 (pressure dependence p =p0 exp(-z/z0)), even allowing for line narrowing.This is why the central CO2 line appears as a strong peak in satellite top of the atmosphere radiation spectra, corresponding to the high temperatures in the high stratosphere.
Your consideration of pressure dependence of the spectral width is the reason I like to use the following heuristic.
Compute the absorption length of a cylinder of atmosphere of length z0, under the conditions (pressure and temperature) of the tropopause. Any wavelength that is strongly absorbed, e.g. 30% transmission or less, has to correspond to an atmospheric radiation effective altitude in the stratosphere. Any wavelength that is weakly absorbed e.g. 90% transmission or more , corresponds to radiation from below, mostly close to the ground. All the others yield the “normal” greenhouse effect dependent of concentration through the troposphere lapse rate.
This exchange being somewhat out of topic in this post on cloud effects, with multiple comments, it is probably advisable to continue in another setting.
TimTheToolMan says:
September 18, 2011 at 7:01 pm
Its only when you properly consider conservation of energy or in a general sense that the energy that comes from the clouds came from the ocean in the first place that an appreciation for the effect can be made.
This is another source of confusion. Most of the DLR came from the ocean before it came back down from the clouds. But according to the Trenberth-Keihl cartoon, around 66W/m^2 is ‘new’ LR derived from the solar energy absorbed in the atmosphere. Coincidentally this is around the same as the ~66W/m^2 net radiative loss from the ocean. 33 of this will come downwards, but it seems the amount of solar energy absorbed by clouds has been underestimated by around 30W/m^2 according to measurements taken by planes simultaneously flying above and below cloud decks. This is likely due to a models being based on imperfect physics around the issue of Mie scattering and forward propogation.
http://tallbloke.wordpress.com/2010/11/14/alistairmcd-aerosols-cause-warming/#comment-7645
Tim F says:
The sunspot numbers are odd. SSN drops very close to zero at the end of every cycle, yet your plot shows large variations for the minima.
The sunspot numbers are averaged over 96 months.
Measuring DLR on a global scale would be very challenging, since there are only limited pyrgeometers around the world collecting. And a quick look around the web suggests they are a bit challenging to keep in calibration
Douglas Hoyt (the worlds foremost expert in pyrgeometry) shows they don’t need to be calibrated against each other, and that optical depth hasn’t changed in seventy years at various locations.
Willis
I hope that you have read my first post even if you did not comment on what seems a very important result.
Indeed do you realize that the Figure 4 falsifies your favorite “thermostat” theory based on the daily asymmetrical tropical cloud cycle (e.g clear mornings and cloudy afternoons) ?
Figure 4 (all skies) shows exactly the contrary – there are (in average !) as many clouds in the morning as in the afternoon, at sunrise as at sunset.
Did you understand my suggestion to show the curve of the minimal SW radiation which corresponds to fully clouded skies?
You can then count how often the skies were fully cloudy at every hour and see if it is still symmetrical.
Based on the Figure 4 you must now either abandon idea of asymmetrical daily cycles of clouds because they are contradicted by the data or if you want to maintain the “thermostat” theory and the existence of daily cloud cycles then you must explain why the all sky curve of Figure 4 is symmetrical and shows no trace of a daily cloud assymmetry.
Otherwise the Figures show there is less SW during cloudy skies than during clear skies but everybody will agree that this is a very trivial observation. Producing from this data saisonal averages of cloudiness f.ex 3 months (cloudiness definition ; SW all skies/SW clear skies) and looking if there are either global or temporally localised trends would be obviously less trivial and certainly more interesting.
Tallbloke says:
“Douglas Hoyt (the worlds foremost expert in pyrgeometry) shows they don’t need to be calibrated against each other, and that optical depth hasn’t changed in seventy years at various locations.”
I find it fascinating how people (on both sides) accept information that agrees with their views, and are skeptical only of information that contradicts their views.
* Douglas Hoyt is THE foremost expert? Even his own bio says nothing about prygeometry (although he has a couple papers on phyheliometry). http://www.warwickhughes.com/hoyt/bio.htm
* Instruments don’t need to be calibrated??? Honestly, would you be so generous if Mann claimed such a thing? In many cases, only relative change is important and uncalibrated instruments work pretty well. But for long-term studies, involving small changes in difficult to measure numbers, I would think calibration would be quite important. Do you have a reference for this claim?
* Typically optical depth for the atmosphere refers specifically at visible light, which would be immaterial for measurements of thermal IR from the atmosphere. Do you have a reference for your claim about optical depth, specifically as it relates to thermal IR?
Tim F
Sorry, my mistake. I was getting mixed up with pyrheliometry. See the paper Hoyt co-wrote with Frohlich on pyrheliometry measurements between 1920-90 at Davos. Changes in DLR due to co2 change should be smaller than those due to aerosols absorbing/ reflecting sunlight. Not that the Team ever seems to be able to make up it’s mind which it is or what the overall effect is…
TomVonk says:
September 19, 2011 at 4:06 am
I saw it, and it got lost in the flood. Thanks for your thoughts.
The morning/afternoon cloud shortwave forcing is indeed asymmetrical. It is lost in the graph, because the maximum is not smoothed. In fact, the average SW forcing from 6AM to Noon is -339 W/m2, while the Noon to 6 PM average forcing is -361 W/m2.
It is important to note that this underestimates the actual forcing, because this is an average. Remember that on a hot day, the clouds form earlier, and on a cold day they form later. When you average them, it temporally smears out (and thus diminishes the amplitude of) the actual on-the-ground effect because the timing and amount of clouds is temperature dependent.
Which is another example of why averages need to be interpreted with great caution.
w.
Just a couple other comments/questions, Tallbloke
“The sunspot numbers are averaged over 96 months.”
If that is the case and you are averaging last 48 months and the next 48 months (as it appears you are doing), then you are correlating today’s humidity to the solar cycle over the next 4 years. It seems very odd to try to predict current humidity using data you will not have for 4 more years. Or perhaps you aer saying you can reverse the process and use humidity to predict the upcoming solar cycle?
“Most of the DLR came from the ocean before it came back down from the clouds.”
OK, but I could just as well say “Most of the ULR came from the atmosphere before it came back up from the oceans.” (After all, the ocean received 325 W/m^2 from the atmosphere, but only 168 W/m^2 from the sun) What relevance does either have on the physics? The ocean radiates according to the energy it CONTAINS (as expressed in its temperature); the atmosphere radiates according to the energy it CONTAINS (as expressed in its temperature). Neither the atmosphere nor the surface knows nor cares where that energy may have been earlier.
“Coincidentally this is around the same as the ~66W/m^2 net radiative loss from the ocean. 33 of this will come downwards…”
In the trenberth diagram, the atmosphere radiates about ~ 325 W/m^downward (to the surface), and ~ 200 W/m^2 upward (to space), so ~ 62% of the energy goes down and 38% goes upward. If you really want to break it down by “sources” you could claim:
62% of ~ 350 W/m^2 (IR energy received from the ocean) goes down
62% of ~ 80 W/m^2 (evaporative energy from the ocean) goes down
62% of ~ 25 W/m^2 (convective energy from the ocean) goes down
62% of ~ 65 W/m^2 (SW photon energy from the sun) goes down
NET: ~ 325 W/m^2 goes down. If you re going to treat the atmosphere as one object (a la Trenberths diagram), then you have to treat all the energy as going to/from the atmosphere as a whole.
I really don’t see how you can talk about where “net loss” goes.
TomVonk says:
September 19, 2011 at 4:06 am
There’s lots and lots of things to do with the TAO dataset that would be interesting, Tom … but I’m one guy with no associates and no graduate assistants and no funding and no supercomputer. It’s just me with a day job, my trusty Mac, and my imagination … and all of that can only do so much in a given time.
I’m sorry if my ongoing series of reports of my preliminary results aren’t up to your standards, and you find them trivial and less than interesting … so how about you produce some non-trivial results from the TAO dataset that you think are more interesting and report back to us?
What’s that you say? You’re busy and that kind of analysis would take a while? Yes, I understand … and I hope you will as well.
I’m doing my best with the time I have available, following the avenues I see and reporting on what I find. As I mentioned above, my next move will likely be to split the data into the warm dawns and the cool dawns and re-analyze it to see what happens in the ensuing days. As far as I know, I’m the only person doing a “warm dawn vs. cool dawn” type of analysis, and it provided fascinating results when I last used it on the TAO dataset, so I hope you will find it more interesting …
w.
TimTheToolMan says:
September 18, 2011 at 7:01 pm
Mathematically, it’s the same thing as warming, but it’s not warming because of where the energy came from?
That is a most curious claim. I’ve never heard that whether something warmed something else depended on where the energy came from … particularly since in this case, all of the energy came from the sun.
w.
Willis wrote: There’s lots and lots of things to do with the TAO dataset that would be interesting
I have created a directory called “Eschenbach”, and I have started downloading the TAO data into it. I hope to expand upon your work in the coming weeks. I think, as I wrote, that you had a good idea. There’s wind speed data, rainfall data, and so forth. It’s a magnificent data set, apparently neglected before you.
http://modis.gsfc.nasa.gov/data/atbd/atbd_mod05.pdf details galore
well, if the sea’s skin is cooler than what’s above and below – obviously it’s not because of conduction and obviously not by radiation or obviously it can’t be convection.
that means it’s by phase change – evaporation.
that means there is a saturated layer of water vapor over the skin.
the layer of dense water vapor has optical thickness, doesn’t it?
it’s not ‘net releasing’ heat – it’s evaporating – it’s is sequestering heat – and the thermometers don’t measure the quantity of heat.
Willis writes “Mathematically, it’s the same thing as warming, but it’s not warming because of where the energy came from? That is a most curious claim. I’ve never heard that whether something warmed something else depended on where the energy came from … particularly since in this case, all of the energy came from the sun.”
If the sun increased its average output by 3.7W then there aren’t too many people in the world who would believe the earth wouldn’t heat up. Thats the fire analogy. However adding a thicker jumper isn’t necessarily going to heat you up if say you went from a thinner white jumper to a thicker black jumper which radiates better.
This is essentially your argument (and my belief too) that the climatic processes will tend to arrange themselves to maximise energy loss. Its much harder to escape heating from an actual energy increase from the sun.
So why does it matter that its cooling not heating? Well because its the jumper analogy that we’re looking at and not the fire analogy. A slower rate of cooling due to GHGs can be trumped (or at least offset) by a higher rate of cooling from other processes.
gnomish says:
September 19, 2011 at 4:22 pm
“well, if the sea’s skin is cooler than what’s above and below …
The clouds above and much of the atmosphere above and outer space above are colder than the surface. So this statement is wrong.
– obviously it’s not because of conduction and obviously not by radiation or obviously it can’t be convection.
Since the original hypothesis was false, this conclusion is false. Radiation can and does contribute to the cooling of the surface of the ocean. As does evaporation.
that means it’s by phase change – evaporation.
that means there is a saturated layer of water vapor over the skin.
There is only a saturated layer if the relative humidity is 100%. (And at that point there is no more net evaporation, since the saturated vapor is returning to the liquid as fast as the liquid is evaporating into the gas phase. That is pretty much the definition of “saturated”.)
the layer of dense water vapor has optical thickness, doesn’t it?
Sure, any layer of gas has an optical thickness. What does this relate to?
it’s not ‘net releasing’ heat – it’s evaporating – it’s is sequestering heat – and the thermometers don’t measure the quantity of heat.
Evaporation only sequesters (isolates and/or stores) energy to the extent that there is a NET evaporation of water. Since water cycles from evaporation (sequestering energy) thru condensation (releasing the stored energy), the net change is basically zero. (When there is a net warming of the atmosphere & oceans, then could be a slight increase in global humidity, resulting in a slight sequestration of energy, but I am sure this is a tiny number and not important on a global level. )
All that evaporation really accomplishes is a net transfer of energy from the oceans to the atmosphere (~ 80 W/m^2).
It is true that thermometers do not measure this energy, but since this energy it is pretty much constant on a global, long-term basis (since humidity is pretty much constant on a global, long-term basis), it doesn’t really matter.
i meant that ‘that which is in contact and immediate proximity’ with that surface layer, of course – not outer space or clouds a mile above it- you know- the saturated air near in contact – the interface.
experiment i just conducted:
heat cup of water in microwave. leave cup 1 inch underfilled.
take reading with IR thermometer: 149-159F (don’t fog the thermometer!)
cross ventilate to remove saturated vapor layer
take reading with IR thermometer: 135-141F
do it several times with the same cup to make sure it’s not a fluke.
so – what material object is actually being detected?
NOTE: ir thermometer can not ‘see’ water below the surface.
NOTE: ir thermometer can not ‘see’ water beneath vapor.
and of course there is a net evaporation of the water from that surface – that’s how we get rain, right? it doesn’t stay on the surface, either, as it rises, being the least dense gas in the atmosphere by a significant margin – that’s how we get rain clouds, right?
and when it rises, it’s replace by other, dryer air that moves in along the lowest surface, sweeping along those water molecules that randomly acquired enough energy to evaporate- thus cooling the ‘skin’ which provided the calories and becoming saturated again.
care to try again with these constraints clarified? i tried to reduce the quibbling quotient.
heh- but you knew that there was net evaporation, for you say:
“All that evaporation really accomplishes is a net transfer of energy from the oceans to the atmosphere (~ 80 W/m^2).”
and so your remark about
“Evaporation only sequesters (isolates and/or stores) energy to the extent that there is a NET evaporation of water. Since water cycles from evaporation (sequestering energy) thru condensation (releasing the stored energy), the net change is basically zero.”
is not a refutation of anything.
no rhetorical roulette, plz, if that’s what it was.
“humidity is pretty much constant on a global, long-term basis”
of course. but every single day/night cyle it varies hugely – definitely not constant.
this is an example of how ‘averaging’ simply destroys information and an illustration of the faulty conclusions that proceed from relying on data homogenized beyond recognition.
@Tim Folkerts,
“All that evaporation really accomplishes is a net transfer of energy from the oceans to the atmosphere (~ 80 W/m^2).
It is true that thermometers do not measure this energy, but since this energy it is pretty much constant on a global, long-term basis (since humidity is pretty much constant on a global, long-term basis), it doesn’t really matter.”
You might be thinking of relative humidity rather than absolute humidity. Negative feedback from a couple extra turns of the water cycle might well matter for both the actual climate sensitivity and the model projections. Models which couple CO2 forcing to the whole mixing layer of the ocean rather than properly representing the shallow skin coupling and resulting differences in climate feedback vis’a’vis solar and other forcings are arguably not yet skillful in projection of either warming or precipitation. Consider the issues Wentz raised in the journal Science.
“Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. However, the climate models predict that global precipitation will increase at a much slower rate of 1 to 3% per kelvin. A recent analysis of satellite observations does not support this prediction of a muted response of precipitation to global warming. Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.”
“There is a pronounced difference between the precipitation time series from the climate models and that from the satellite observations. The amplitude of the interannual variability, the response to the El Niños, and the decadal trends are all smaller by a factor of 2 to 3 in the climate model results, as compared with the observations.”
“The difference between a subdued increase in rainfall and a C-C increase has enormous impact,
with respect to the consequences of global warming. Can the total water in the atmosphere
increase by 15% with CO2 doubling but precipitation only increase by 4% (1)?Will warming
really bring a decrease in global winds? The observations reported here suggest otherwise, but
clearly these questions are far from being settled.”
How Much More Rain Will Global Warming Bring? Frank J. Wentz,* Lucrezia Ricciardulli, Kyle Hilburn, Carl Mears
Published online 31 May 2007; 10.1126/science.1140746
I heard a talk by Lindzen in which he claimed that results for latent heat flux are consistent with the observed increase in precipitation rather than with the models, but I didn’t get the reference. Hopefully, someone will supply that.
Gnomish,
Certainly variations in water evaporation from day to night or from summer to winter are important. More water evaporates during the day and less water evaporated during the night. This is one of the key reasons oceans moderate temperatures, which is well know to amateurs and professionals alike.
I have not personally worked with climate models, but I have to assume that one way or anther they build in this moderating effect of oceans.
“i meant that ‘that which is in contact and immediate proximity’ with that surface layer, of course – not outer space or clouds a mile above it- you know- the saturated air near in contact – the interface.”
I also meant ‘in contact and immediate proximity’ with that surface layer. Radiation easily passes back and forth from the surface layer to the clouds, upper atmosphere, and space. This puts the surface in thermal contact with these regions. The large amounts of thermal energy involved suggest rather good thermal contact.
Willis
The morning/afternoon cloud shortwave forcing is indeed asymmetrical. It is lost in the graph, because the maximum is not smoothed. In fact, the average SW forcing from 6AM to Noon is -339 W/m2, while the Noon to 6 PM average forcing is -361 W/m2.
It is important to note that this underestimates the actual forcing, because this is an average. Remember that on a hot day, the clouds form earlier, and on a cold day they form later. When you average them, it temporally smears out (and thus diminishes the amplitude of) the actual on-the-ground effect because the timing and amount of clouds is temperature dependent.
This is a great result and exactly what I was going after in my post !
Of course as I had not the actual data, by eyeballing only the Figure 4 it seemed that your asymmetry hypothesis was in trouble.
So, actually this analysis supports your hypothesis instead of falsifying it.
Your remark about a different answer of the system at “cold” and “hot” days is also interesting.
To avoid misunderstandings.
There was no criticism intended when I was speaking about “trivial” and “non trivial” results.
If I don’t do the work you did, it is not that I lack time. I lack the skills and energy.
In science there have always been theorists and experimenters. I am a theorist and my skills are elsewhere. I would certainly be slower and less efficient than you in manipulating numerical data and writing computer programs.
That’s why my comments regarding your results were always guided by a genuine interest and what I tried was to provide you with possible theoretical interpretations of your data as well as showing possible research directions which could show interesting results.
I find that what I call “Willis’ asymmetrical system answer” makes sense and seems to be supported by the data you showed. I find it also highly interesting because you explore here the least understood aspects of the dynamics – the clouds. Admittedly only tropical clouds but it is already something.
Now obviously if the asymmetrical mechanism was established beyond any reasonable doubt, the second and more ambitious stage would be to analyse the temperature dependence of the mechanism.
Indeed if the mechanism was stronger with increasing temperatures, then you would have discovered a real negative feedback.
If it was only slightly dependent on temperature or even independent then the mechanism would play no important role in the energy management of the system.
Btw you should not call the negative number you find “forcing”. The – 339 W/m² number is just saying that there are sometimes clouds instead of clear sky 100% of the time. It tells us how many clouds in average there are but this is no “forcing”. You could call it “cloud albedo effect” if you want.
Martin Lewitt says:
September 20, 2011 at 2:46 am
You might be thinking of relative humidity rather than absolute humidity. Negative feedback from a couple extra turns of the water cycle might well matter for both the actual climate sensitivity and the model projections. …
“Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. “
That is a good point. The total humidity would almost certainly increase as temperatures increase. While that will almost certainly have a major impact on energy balances by affecting radiation balances and cloud cover, I don’t think it will specifically have a significant “energy sequestration” affect, as Gnomish seemed to suggest. A quick calculations supports my contention:
The following are estimates from the internet:
1.30E+16 kg = mass of water vapor
18 = molar mass water
7.22E+14 = moles of water
0.01 % = increase of water
7.22E+12 = Extra moles of water evaporated
44000 J to evaporate 1 mole of water @ur momisugly 290 K
3.18E+17J to evaporate 1% more water vapor
5.10E+14 m^2 = area of earth
6.2E+02 J/m^2
31557600 sec/year
0.00002 W/m^2
In other words, to raise the total humidity in the air by 1% over the course of a year would require about 0.00002 W/m^2 extra input. Using your numbers, even if a warming of 1 K occurred in only 7 years, the system would only require would require about 0.00002 W/m^2 each year to account for the evaporation. This could easily be off a little bit, but it is pretty clear to me that it is a drop in the bucket (pun intended) compared to other energies and other changes.
let’s examine of the surface of the sea is ‘in contact and immediate proximity’ with the skin of the sea surface where evaporation takes place…
the experiment i reported demonstrates that:
ir thermometer can not ‘see’ water below the surface. ir is blocked by absorption in the first microns.
ir thermometer can not ‘see’ water beneath vapor. ir is blocked by absorption, again.
That means that a layer of vapor or water blocks LW transmission because it absorbs it, right?
That means that the surface of the sea is NOT in direct ‘radiative contact’ with the clouds or outer space because it has an IR absorbing layer between, right?
My experiment can’t really be interpreted any other way- it proves the existence of a layer of water gas blocks the reading of the surface.
It also means that DLR, in such a situation, can NOT reach the surface but is absorved by a vapor layer.
That’s how come DLR doesn’t directly heat the ocean.
It’s been stated that the skin is cooler than the air above or the water below because of evaporation – that’s empirical, right?
if that is so, then there is no net conduction of heat from cold to hot, right? conduction would convey heat from the warmer bodies and raise the temperature, right?
if there were convection, it would have cooler gas rising thru warmer gas – that’s not the definition of convection.
and my experiment demonstrated that a layer of vapor BLOCKS ir radiation, so there’s no direct radiation from atmosphere to skin- DLR doesn’t warm it – it’s not warm; it’s the coolest layer at that interface.
oh, i need a do.over-
let the first sentence of my previous post read:
let’s examine if the skin of the sea surface, where evaporation takes place, is ‘in contact and immediate proximity’ with clouds or outer space …
ima dock the pay of my proof reader…
Gnomish,
The experiment you described is interesting, but you will have to forgive me if “blowing on a cup of coffee” doesn’t 100% convince me. There are too many details missing. For one thing, water vapor only emits at certain frequencies, so you will always be seeing partly thru the water vapor to the liquid water behind. There will always be some wavelengths that can transmit from the “cup of coffee” far up thru the atmosphere, connecting it thermally with these colder areas. What wavelengths does your IR thermometer use?
“cross ventilate to remove saturated vapor layer”
This could be doing several things. For instance, it could be inducing evaporation/conduction at the surface, cooling the top layer of water.
I can think of lots of other variations to try and variables to try.
Let me leave you with one final thought. If less than 1″ of “saturated water vapor” is the main material being measured (before you blow on the hot water), then partly saturated water vapor a few times thicker should have the same effect. That means that your thermometer would not work on a humid day if it was more than a few inches from the item being measured, since it would read the temperature of the water vapor in the air instead. Is that indeed the case?
well, it’s just about useless for measuring water temperature because of that, unless the water is at ambient anyhow- readings can be all over the place-
the temps read from the coffee cup are consistent with that – for the vapor may not be hotter than the water, but you can only read hot vapor or evaporatively cooled skin (lower temp than the vapor)
in normal use it’s not a noticeable problem. usually there isn’t a fog of dense vapor in the way. often the object to be measured is at ambient anyway- same as the air. usually one puts it very close to the object, too
i don’t know for certain what is the band of ir the device is reading but it’s probably the same as other ir ‘thermometers’, IR spectrum sensor w/ sensitivity 4μm – 8μm with a log circuit to mimic the boltzman formula and an a/d to make it numeric, all on one chip.