Dehumidifying the Tropics

Guest Post by Willis Eschenbach

I once had the good fortune to fly over an amazing spectacle, where I saw all of the various stages of emergent phenomena involving thunderstorms. It happened on a flight over the Coral Sea from the Solomon Islands, which are near the Equator, south to Brisbane. Brisbane is at 27° South, and as a result, it is much colder than the Solomons.

It was overcast when we took off that early afternoon from Honiara, the capital of the Solomons. When we got up to altitude we crossed over the mountainous spine of the island and started south over the ocean. My attention was immediately drawn to the scene below me. I could see that for mile after mile over the ocean, the thunderstorms were all arranged in the long serried rows called “squall lines”.

ge HIR to BNEFigure 1. Honiara to Brisbane. Honiara, the capital of the Solomon Islands, is on the north side of the island of Guadalcanal. Distance is about 2,000 km (1,200 miles).

Squall lines arranged in row after row are the final emergent circulation pattern in the chain of events involving the formation and subsequent intensification of thunderstorms. At the start of the process, the first emergent phenomena to appear are cumulus clouds and a change in circulation patterns. Rather than random movements in the lowest atmosphere, the cumulus have Rayleigh-Benard circulation associated with them.

tropical diurnal late morningFigure 2. The first stage in the evolution of thunderstorms. The cumulus clouds could be thought of as flags marking the upwelling section of the Rayleigh-Benard circulation. SOURCE

Of course, the increased albedo due to the clouds initially cools the surface. However, over the next hours as the surface continues to heat up despite the reduced incoming energy due to the formation of the cumulus, above a certain temperature threshold a scattered few of these cumulus clouds develop into thunderstorms. If surface temperatures continue to rise, the number of thunderstorms continue to rise, and quite rapidly. The circulation pattern changes, with surface air being lifted to condensation level. There, the moisture falls as rain, and the heat of condensation drives the deep circulation to the upper troposphere. From there, dry air descends again to the surface.

tropical diurnal early afternoonFigure 3. Further circulation changes as thunderstorms develop.

The next emergent pattern in this process is that the thunderstorms begin to line up in a row, shoulder to shoulder. This allows for a more dense packing of thunderstorms into any given area, basically doubling the possible areal density of thunderstorms and greatly increasing their power. Here’s a really big example of that:

radar image squall lineFigure 4. A radar observation of a long squall line, with few breaks, stretching a thousand kilometres (600 miles) from Oklahoma to Indiana. SOURCE

Until the day I took that flight, however, I had never seen or even imagined that there was a further possible emergent circulation pattern.  I’d seen plenty of squall lines during my time sailing and motoring over the tropical ocean. But I never guessed that the squall lines could stack up, one after the other, in relatively straight lines, for as far as the eye could see. And curiously, even now I can’t find a single clear photo showing the phenomenon, I can only report what I saw. I was shocked, it was a totally new cloud formation that I’d never witnessed or at least never noticed, endless rows of walled thunderstorms reaching well up towards flight altitude, with clear air canyons  to the surface between the towering sides. It was awe-inspiring.

And flying that afternoon from Honiara to Brisbane, going over the Coral Sea and slowly moving southwards from warm ocean to cool ocean, I saw the whole process leading from cumulus clouds up to those endless stacked squall lines, only I saw it in reverse because I was flying from warm to cold. It started with flying for a few hundred miles over row after row after row of thunderstorms. These rows stretched from horizon to horizon, which from jet elevation is a long ways.

One of the clear advantages of this physical arrangement is that it is more efficient, with less turbulence than individual storms. There are huge long areas, canyons between the squall lines, where all of the air is smoothly descending. From the plane I could see the long cirrus anvils spilling downwind from the tops of each of the squall lines. The air flowed out there at the top and began the long descent into the canyon below. This long rolling cylinder of air allows the efficient movement of huge amounts of air containing both latent and sensible energy into the base of the thunderstorms, up through cumulonimbus towers making up the the squall lines to the upper troposphere, and then rolling out at the anvils and downwards again, turning the waterwheel over and over.

As we flew south, the squall lines weakened. First there started to be gaps in the squall lines, narrow breaks in what had been continuous sections of thunderstorm after thunderstorm to the horizon. After that, the breaks got wider. Then areas of squall lines began to be interspersed with areas of dense, closely packed thunderstorms. Beyond a certain clear surface temperature threshold, there were no more squall lines, just dense thunderstorms. From altitude I could see the two separate regimes. To the north, squall line after squall line, with fewer and fewer breaks the further north I looked.

And to the south, not one squall line in sight, just masses and masses of densely packed individual thunderstorms.

As we continued flying south over cooler and cooler water, the number of thunderstorms in sight decreased. Eventually, there was another clear line, another temperature threshold beyond which there were no further thunderstorms, just cumulus clouds. It was fascinating to see the towering thunderstorm clouds suddenly come to an end at a definite line. Out my window I could see dozens and dozens of thunderstorms in view north of the line, and not one thunderstorm in the slightly cooler area south of the line. And finally, by the time we got to Brisbane, there were only scattered cumulus.

Now, I bring all of this up because in the comments to a previous thread I’d said I would write a post about humidity. And when you write about humidity, you have to write about thunderstorms. I wrote before about how thunderstorms function as natural refrigerators, springing into existence as needed to cool off the hot surface spots around the planet. In addition to acting as refrigerators, however, they also function as immense natural solar-powered dehumidifiers. And as I saw, they are capable of covering huge areas and removing an almost unimaginable amount of moisture from the air.

Thunderstorms do this in the same manner as one class of human-made dehumidifiers. They cool the air until the water condenses out, and then re-warm the dehumidified air. Here’s a graphic from my post on thunderstorms as refrigerators, which also shows how they dehumidify the air.

thunderstorm refrigerator

Figure 5. Thunderstorm acting as a de-humidifier. Moist air rises under the base of the thunderstorm until it starts to condense. At a certain point it begins to fall as rain. More moisture is removed, as both ice and water, within the tower. Finally, the now-dry air descends between the thunderstorms to repeat the cycle. SOURCE

Note that after the moisture has been wrung out of the air and has fallen as rain, the resulting dry air then returns to the surface, warming as it descends. So paradoxically, although the thunderstorm greatly increases local evaporation under and near the base, it actually decreases the overall bulk average local humidity. When the thunderstorm regime is fully established, most of the bulk atmosphere is composed of dry downwelling (descending) air. In other words, the thunderstorm is a natural dehumidifier that is constantly stripping the moisture out of the lowest troposphere.

========================

Now, why is this important to the climate? Well, it has to do with the amount and nature of the water vapor feedback, which is said to amplify the warming from any source.

The Earth intercepts about three hundred and forty watts of solar energy for every square metre of its surface averaged on a 24/7 basis.

The upwards radiation from the surface, on the other hand, averages more than that, about three hundred and ninety watts per square metre, again on a 24/7 basis.

This implies a net gain of about 15% (390 / 340 – 1) from the intercepted radiation to the surface radiation, including all systems—clouds, evaporation, winds, surface albedo, parasitic losses from sensible heat transport, radiation “window” to space, everything. In large measure this elevation of the surface temperature is due to the absorption and radiation of infrared (longwave) radiation by the poorly-named “greenhouse gases” in the atmosphere. First among these greenhouse gases, of course, is water vapor.

Now me, I don’t think the climate works linearly. I don’t think that a change in forcing will necessarily result in a proportional change in surface temperature. However, that’s the current paradigm, so let me run with their assumption and see where it goes. The doubling of CO2 in the atmosphere is stated to bring a change of 3.7 W/m2 at the top-of-atmosphere (TOA). Other things being equal (which they never are, but we’re assuming here in order to get rough numbers), this should result in a surface change on the order of 15% larger than the TOA change of 3.7 W/m2, or about four and a quarter watts per square metre.

And this, by Stefan-Boltzmann’s relationship and assuming blackbody for convenience, should give us about eight-tenths of a degree (C) of warming for a doubling of CO2.

How do we get from that basic calculation to the dread range of three degrees or so from a doubling of CO2 that the global warming enthusiasts talk about? Ah, that’s where the handwaving comes in. It is supposed to be from two main sources, which they call “cloud feedback” and “water vapor feedback”. The modelers say that both of these are positive, i.e., they both act to amplify the amount of warming from a given change in TOA radiation.

There is a terminology problem to start with. Only one of the two, the effect of water vapor, is a simple linear or semi-linear feedback. Clouds are not just simple feedback, they act as governors, applying both positive and negative feedback in response to different situations. However, let’s set that question aside as well to follow the main point, that of water vapor.

Using the TAO buoy dataset, I have demonstrated how at times in the tropics cloud feedback actually reverses the effects of increasing amounts of incoming energy, so that the surface air temperature cools despite an increase in total downwelling energy. (See One , Two , and Three .) And that’s just the net energy (albedo minus longwave) change in total downwelling energy, it doesn’t include the effect of emergent homeostatic climate phenomena like thunderstorms …

And other research of mine has shown that in general clouds cool the earth in the summer and warm it in the winter. Again, the clouds are not a feedback but act as a governor, tending towards a homeostatic state. Despite that, the climate models show a positive cloud feedback … go figure.

In any case, while I was writing the above story about thunderstorms and humidity as I had said I would do, I got to musing the other day about the second leg of the modelers’ claim, water vapor. The reasonable idea put forward by the climate modelers is that as temperatures warm, the amount of water vapor in the air goes up in some quasi-linear fashion. Since water vapor is the main greenhouse gas, this of course increases the downwelling infrared (longwave) radiation. This positive feedback is claimed to greatly enhance the surface warming, as a result of increased radiation-trapping water vapor.

The problem is, given my understanding of the tropical ocean and the weather therein, I thought that when the thunderstorms kicked in, the humidity would drop.

So after I had written the description above, about how thunderstorms constantly dehumidify the tropical atmosphere, I realized that I had the data I needed to actually see if my hypothesis held water, so to speak. I could see if my understanding of thunderstorms was correct.

You see, my understanding of thunderstorms and their actions comes from what I might term “first principles”—but not the first principles of physics usually referred to by that term. Nor are the first principles what I learned in a class or from a book.

I say I know thunderstorms from first principles because I lived for seventeen years in the tropical Pacific, and I was either in view of or being rained on by thunderstorms most of those days. So I know they dry the air around them because you can feel it. When the thunderstorms kick in, usually sometime during the afternoon, the air in the neighborhood gets much fresher and less sticky. I don’t mean the downwelling cold wind that comes with the rain, that’s different. I mean when the circulation changed and the dry air starts descending, the atmosphere in the whole area feels drier … but I’d never actually looked at the data to verify my experience. So, trapped by my own writing, I set out to see if I was right.

For this I turned again to the trusty TAO buoy dataset, which has thousands of hourly observations. For no other reasons than that it is in an interesting region, the “Pacific Warm Pool”, and because I used to live on this map, on a tiny island above and to the right of the “a’ in “Sea”, and so I’m very familiar with the weather there, I looked at a TAO buoy I’d considered previously. It’s on the Equator up north of the Solomon Islands. Among the information that is measured and recorded there, hour by hour, are the surface air temperature and the relative humidity.

ge tao 0n156e solomonsFigure 6. Location of the TAO buoy, moored to the abyssal plain in water of about 2,200 metres (1.3 miles) depth. Nearest land is ~ 600 km away, no urban warming there.

I started by looking at the correlation between the actual measured variables, the surface air temperature and the relative humidity. It’s not the comparison I’m looking for, we’ll get to that, but I can use relative humidity for verification, because I expect it to show a negative correlation (an inverse relationship) between relative humidity (RH) and temperature. This is because if a parcel of air warms, it can hold more moisture. If there is the same amount of moisture in the parcel, when the parcel warms the relative humidity drops. So I’d expect the RH to drop with increasing temperature. Figure 7 shows those results from the TAO buoy at 0°N, 156°E.

rel humidity vs sat tao 0n156eFigure 7. Relative humidity versus air temperature, from the TAO buoy located as shown in Figure 6. N =119,359.

As expected, the RH drops with increasing temperature. So I would say the dataset is valid and acting as expected.

However, I wasn’t interested in relative humidity. Relative humidity is the relative amount of water vapor in the air, expressed as a percentage of what the air could potentially hold if it were fully saturated.

But the amount of radiation absorbed by water vapor doesn’t vary with the relative amount of water in the air (relative humidity). Instead, absorption varies with the actual amount of water vapor in the air, which is called the “absolute humidity” or AH. The amount of outgoing radiation intercepted by water vapor depends on the actual amount of water vapor in the air (AH), not the relative amount of water (RH). However, you can calculate the absolute humidity from the temperature and the relative humidity, so I did that.

Figure 8 shows a scatterplot of the temperature (bottom scale) versus the absolute humidity (AH, vertical scale). The AH for each hourly observation is calculated from the hourly temperature and relative humidity (RH) using the method shown here. (The pressure adjustment is too small to be of interest at the earth’s surface, it can be assumed to be constant.)

abs humidity vs sat tao 0n156eFigure 8. Temperature (°C) versus absolute humidity (kg/m^3). The individual gold lines show the trend for each degree celsius` interval. As an aside, the maximum air temperature of ~ 30°C reflects the general global oceanic temperature maximum, with few values over that in open oceans anywhere. In this case, only 0.5% of the data is above 30°C, and only a tenth of that is above 30.5°C (0.05%, five hundredths of a percent).However, although only 0.04% of the observations are below 24°C, there is no hard lower limit visible in the data.

Given the results shown in Figure 8, I’m gonna have to say that my experience is vindicated. As you can see, at cooler temperatures around 24 or 25°C the amount of water vapor in the air goes up fairly rapidly with increasing temperature, just as people claim.

However, as the temperature continues to rise, the rate of water vapor increase slows down, then levels off from 26 to 27 C. Then, between 27 and 28 C, the amount of water vapor in the air actually decreases with increasing temperature.

Above that temperature, water vapor resumes increasing with temperature, but quite slowly.

My interpretation is that the overall leveling off of the trend curve shown in gold, and the decrease in absolute humidity from 27° to 28°, are clear signs of the dehumidifying action of the thunderstorms. The thunderstorms form as a response to surface hot spots, and when they form, they wring the water out of the air.

What can we draw as more general conclusions from this? Well, not a whole lot, it’s only one buoy in one location, we need to look much further … but it does support the dehumidifying nature of thunderstorms. Assuming that the finding is general, the first conclusion would be that in the wet tropics, where most of the energy enters the climate system, the amount of water vapor in the air doesn’t vary a whole lot with temperature. At this location, as temperatures rise, thunderstorms start dehumidifying the air and the resulting curve is pretty flat, with little change in the region from 26°C to 29°C

And that, of course, means that the amount of amplification of any warming due to water vapor feedback will be smaller than would be calculated under the assumption of a relatively linear or constant rise in absolute humidity with temperature.

Of course, more study is required, and there is lots more to learn, both using the TAO dataset and elsewhere. All conclusions are provisional and subject to future falsification, void where prohibited or taxed, you know the drill. I was just happy to have my understanding confirmed by this preliminary look at the data.

Regards to all,

w.

============

DATA AND CODE: Well, the code is a mess. By a mess I mean it’s in my usual form, in that I write in bits and chunks, and in general I only run selected lines. So while the code contains all the information and calculations needed to do the analysis above, they are not necessarily in order. Plus there’s a lot of other code that isn’t used, or didn’t work, or worked but wasn’t needed for the post. And far from being user-friendly, code I write might be described as “user-agressive”, I wrestle with it constantly.

In any case, there are two R files and a data file, zipped, downloadable here. The data file contains (as an R “save” file) the two NetCDF (ncdf) files, one for humidity called “rh” and one for temperature called “nc”, for the given buoy 0N156E. The ncdf files are the 4-bit files available here. The two R programs are “buoy temperatures” and “buoy humidity”. The “buoy humidity” file contains the calculations for the graphics shown above. The temperature data is calculated in the “buoy temperature” file, and then utilized by the “buoy humidity” file. So good luck, and as the poet said, “Lasciate ogni speranza voi ch’entrate” …

Advertisements

73 thoughts on “Dehumidifying the Tropics

  1. The hottest places in the world are deserts, places where rising humidity can’t form thunderstorms.
    The maximum temperature in humid tropical regions is far more constrained – its humid, but the temperature never reaches 120F on a tropical island.
    If climate models were right, then the hottest parts of the world would also be the most humid – the towering blanket of water vapour sitting above tropical islands would trap more heat than the dry air above deserts, causing the surface temperature of wet tropical places to be unimaginably hot.

  2. Willis:
    That is elegant.
    As you say, the data is only from “one buoy in one location” but IF it is typical then your finding is fundamentally important information for both meteorological theory and to understanding of climate mechanisms.
    The best research indicates clear need for additional study. Your above study is ‘best research’.
    Please try to get funding for a full study of data from a representative sample of all the available data from the buoys. And get it fast before someone else takes your idea, runs with it, and gets the credit.
    Richard

  3. Willis, you explore a version of Lindzen’s adaptive iris hypothesis.
    The significance of your post is greater than you stated. From a GCM warming perspective, the most important water vapor (absolute humidity) is in the upper troposphere. The models all have this emergent property as roughly constant UTrH. AR4 went to great lengths to maintain this fiction by discounting radiosonde and satellite studies that showed it is not correct. UTrH decreases with increasing temperature both inter seasonally and trend wise from 1979 to about 2003. This is why the tropical upper troposphere ‘hot spot’ predicted by GCMs is missing.
    You describe the physical mechanism. Thunderstorms wash humidity out of the air as precipitation before it is convected into the upper troposphere. The hotter it is, the more this happens.
    In addition to observed UTrH, there are two other ‘observations’ that support this. GCMs significantly underestimate tropical precipitation, so miss the washout. That is because they have no ability to actually model convective thunderstorm cells, which happen at much finer scales of resolution than the GCM grids. When a cloud resolving superparameterization is overlaid, precipitation increases and UTrH decreases with increased CO2, and equilibrium climate sensitivity decreases by about half owing to the reduction in the water vapor feedback. An ECS of between 1.5 and 1.9, as most of the post AR4 studies are now showing (e.g. Nic Lewis), fits all of this rather nicely.
    Long way of saying nice post that also explains one of the main things the models have got wrong. And from this section of AR5 SOD, will continue to get wrong in the next IPCC report

  4. Willis
    Here is a not that good but identifiable version of what you are talking about. This was taken on a flight between San Francisco and Hawaii in 2011. The cloud lines are fairly identifiable.
    http://www.panoramio.com/photo/89146527
    [REPLY: Thanks, Dennis. Those are actually cumulus in rows with breaks between them. I saw that kind of thing, but with cumulonimbus (thunderstorm) instead of cumulus. -w.]

  5. Let me have a few words on the “Evaporator” part of the dehumidifier engine. On calm seas with an upper layer of hot water floating on top, ratio of surface to volume is very small. Therefore evaporation is inefficient, due to lack of water-air interface area. Still, evaporation goes up sharply with increasing water temperature and eventually Rayleigh-Bernard cells are formed, with associated horizontal winds at the bottom. As soon as wind over surface gets strong enough to generate spray at wave crests, the system explodes, so to speak.
    For two things happen in parallel at this point
    1. area of water-air interface increases by many orders of magnitude in a short time
    2. it becomes possible to push relative humidity above 100% close to the surface
    The second proposition begs explanation. Now, RH is 100% when evaporation and condensation is in equilibrium over a flat surface. However, sea spray is made of tiny droplets, whose surface is not flat any more, but spherical. If the droplet is small enough (therefore curvature of its surface is high), it is much easier for a water molecule to escape from it than from a flat surface and it is less likely to get captured if bounces to the surface from the outside. So a higher concentration of water molecules is needed in the gas phase to keep equilibrium, which means RH over 100%.
    These two processes push rate of evaporation up in a hyper-exponential manner at first, which makes the entire system switch into another mode fast, the thunderstorm mode, of course. Which, as Willis says, removes this extra moisture (in the “Condenser” compartment), but before that, sucks all extra heat out of the upper hot water layer (by evaporative cooling).

  6. Figure 4 lacks context: what was the synoptic reality -air masses, pressure etc…- behind this line? It does not just appear because the ground gets hot.
    [REPLY: Thanks, Tom, you’re correct. This is a frontal squall line, which is singular in nature. w.]

  7. Willis, you danced all around, but missed probably the most important fact about tropical thunderstorms: the vast amount of heat transported from the surface to the top of the troposphere, completely bypassing any greenhouse effect in that portion of the troposphere. The “blanket” has holes in it. When water vaporizes, the latent heat is an enormous figure, on the order of 1000 btu/lb. Every lb of water that rises to the top as vapor and then condenses leaves 1000 btu behind up there that can’t be stopped by greenhouse gases.

  8. Thanks, Willis. Clouds will take you far above the fray, from where the big picture can be seen.
    This article shows me another confirmation that your thermostat theory is robust.

  9. then levels off from 26 to 17 C. ????
    26°C to 27°C ??? Like your reasoning Willis.
    [Thanks, fixed. -w.]

  10. “And other research of mine has shown that in general clouds cool the earth in the summer and warm it in the winter.”
    This is most people’s experience, too. I love the tropics but I’m not a sun worshipper by any means. I’m the guy sitting in the shade at the beach, sipping a good rum and smoking a cigar. In winter for most decades, I have lived under a Canadian winter, the first few decades in Manitoba where clear nights, the chimney smokes rose in vertial columns into very frigid air. When clouds covered the sky, it was warmer and commonly it snowed – hopefully without too much wind.
    Willis, you always put across a very understandable, unambiguous (eminently readable) case and then follow it up with clincher graphics. Man, I would run out and buy a climatology text written by you before the ink dried (I didn’t even know it was an interesting area of study a half dozen years ago). It would be a great first course in the subject. I’m sure you could handle the whole set of topics if you wanted to. How about taking a crack at the paleoclimate proxy stuff. I know you have written some critiques but I think the wide subject could benefit from your “first principles” style of investigation. I love this stuff.

  11. If I understood you correctly you are saying that you saw line after line of thunderstorms across the Coral Sea. I have seen things like that before, but only on my aircraft radar. Developing TDs and TSs have that pattern, only curved to reflect the rotation of the system.
    Picking my throught those systems involved staying in the clear bands with no or few radar echoes, finding a weak spot in the TSTM band, punching through, and prodeeding on. Sometimes they fell apart as I watched.

  12. Willis, you and Mcintyre have taken a chunk out of my afternoon household-cleanup efforts that my wife will not forgive.

  13. Willis, any guestimate of the distance between the thunderstorm squall lines?
    (Crusing speed of a 737-x is about 8 miles / minute). Do you recall if you were flying over the anvils or between them?
    The Radar picture gives hints of a second squall line about 40-80 miles NW of the main line and another weak one 20-100 miles south-east of the main. (Tennessee is 120 miles N-S).

  14. Stephen Rasey says:
    April 21, 2013 at 1:10 pm

    Willis, any guestimate of the distance between the thunderstorm squall lines?
    (Crusing speed of a 737-x is about 8 miles / minute). Do you recall if you were flying over the anvils or between them?

    Good thought, Stephen. Sadly, I didn’t even consider that question at the time, I was just watching in wonder.
    From memory, which is notoriously unreliable, there were about four or five rows between me and the horizon to the north, and the same to the south. Distance to horizon in miles is about 1.25 times the square root of the eye height in feet (30,000 ft. for a jet). That makes horizon distance about two hundred miles, And that would make the rows maybe forty or fifty miles apart, horizon to horizon. From memory. Which is notoriously et cetera …
    w.

  15. Hmm. I’d sure like to see error bars on Figure 8. And I wonder how models treat the 100+% relative humidity in the boundary layer above the sea surface. Seems like it would stop any infrared heating of the water, even at moderate surface temperatures.

  16. “My attention was immediately drawn to the scene below me. I could see that for mile after mile over the ocean, the thunderstorms were all arranged in the long serried rows called “squall lines.”
    I’m not sure those are squall lines, which I recall are lines that form out ahead of a rapidly moving front.
    Figure 4 looks like a big front, not a squall line, but it has a small squall line formed southeast of it.
    Perhaps weatherman Anthony could enlighten us.

  17. As OldWeirdHarold points out, surely convective transport of latent heat is by far the dominant heat tranfer mechanism under the huge cloud mass in Fig 4 ? Isn’t the sun blocked out under thunderstorms, preventing any greenhouse effect and making the effect of humidity stabilization irrelevant in this area ?

  18. ‘However, as the temperature continues to rise, the rate of water vapor increase slows down, then levels off from 26 to 17 C.’
    Pretty sure you meant 26 to 27 C.
    Interesting as usual.

  19. I think your observations may reveal more on water-vapour effects than you present above.
    If I understand you (here & elswhere on this blog) –
    > the response of the tropics to insolation is thunderstorms in a “close-packed” arrangement (no free space);
    > T/S per area per day will on average match the insolation/area/day;
    > the response to more heat (AGW?) is likely to be more T/S per area per day rather than bigger ones;
    > if so, the descending air humidity will be independent of AGW;
    > the “canyons” you describe are then IR “windows” bypassing the T/S zone, so dominating local OLR behaviour;
    > any additional (AGW) water-vapour in the T/S zone is irrelevant as the cloud is opaque;
    So there can be no tropical water-vapour “feedback” unless the T/S-zone:canyon area ratio increases significantly in the most intense regions.
    Can you recall this ratio?
    (there will be a CO2 effect on the downwelling air, but you’re discussing H2O only)

  20. Thanks, Willis.
    As I recall, the models create a “hot spot” in the upper troposphere of the tropics. In theory this is like a lid, keeping tropical thunderstorms from occurring. In reality such a “hot spot” is yet to be seen, over moist areas.
    The closest thing to such a “lid” is seen over our Great Plains in times of drought, (such as during the Dust Bowl.) A “Heat High” hundreds of miles wide, and sometimes over a thousand miles wide, gets going, which is a sort of vicious cycle where lack of moisture creates lack of clouds which creates baking heat and lack of moisture. However even when such droughts get going, all around the edge of the “Heat High” is a sort of ring-of-fire, made up of thunderstorms.
    The only way the Global Warming models can work is if you create a “hot spot” which allows you to pretend thunderstorms can’t happen. For those models, thunderstorms are a real “inconvenient truth.”

  21. Isn’t the basic argument this idea: thermal conductivity under convective flow is always MUCH great than for laminar conditions. If you begin convective flow of the atmosphere, then you are bound to have greater thermal conductivity to cold space, and thus get some kind of negative feedback effect and/or governing behavior? Why do the standard atmospheric models not take this into account?

  22. Willis,
    In addition to a surface temperature change between the Solomon’s and Brisbane, there is also a significant change in Coriolis acceleration. I wonder what effect this might have had on your observations of change in thunderstorm distribution? Maybe none, but in the temperate regions long frontal lines often terminate in an occlusion. Does this describe some part of your observations?
    I lived in the Pacific NW for a long time. It rains for 9 months on end in western Washington, but despite the rain, the air is not all that humid. I would tell people, to their disbelief, the rain dries out the air; so your observation probably applies equally to colder rain too.

  23. ” And far from being user-friendly, code I write might be described as “user-agressive””

    I love that term.

  24. Dr Burns says:
    April 21, 2013 at 2:06 pm

    As OldWeirdHarold points out, surely convective transport of latent heat is by far the dominant heat tranfer mechanism under the huge cloud mass in Fig 4 ? Isn’t the sun blocked out under thunderstorms, preventing any greenhouse effect and making the effect of humidity stabilization irrelevant in this area ?

    Thanks, Doc. You (and Harold) are correct that the main transport is of latent heat. However, usually the sun is not blocked out under the direction the thunderstorm is moving.
    Underneath the base of the thunderstorm, you can also have direct sunshine. However, you have what is basically a perfect blackbody for IR in the form of the cloud overhead. As a result, I don’t think the change in water vapor under the cloud blackbody changes the downwelling IR a whole lot … but that’s theory. I haven’t done an analysis that is fine-grained enough to differentiate between the cloud moving overhead, and the concomitant increase in the absolute humidity directly under the thunderstorm base due to increased wind. The analysis is likely doable, using some combination of wind and rain to identify the timing of thunderstorm regime … so many interesting avenues to investigate, so little time. I need some sharp graduate students to start looking at this stuff, I’m just a guy with a day job, I’m back to work tomorrow morning … but I digress.
    In addition, the upwards transport `is fast. A parcel of air can easily go from the surface to inside the thunderstorm in under a minute, giving it very little time to move energy radiatively.
    So overall, because of the difference in area between a thunderstorm and the area of the downwelling dry air, I’d say that thunderstorms increase the ability of the surface to radiate to space, by reducing the absolute humidity in their surroundings.
    w.

  25. Ellis, a few things. I loved your description of the serried ranks of storms in squall lines across the Coral Sea,evenly spread. It seems to be different over land? The multiple squall lines I’ve seen have been linear and pushed along by cold fronts.
    I once had the joy of flying through such a frontal system on a flight from Brisbane to Mt. Isa. Too high to go over and too dangerous to go under. Our captain told us to strap in and enjoy the ride then proceeded to swerve that Boeing 737 on one wing tip, then the other, threading our way through about 5 lines. Amazing walls going straight up and down and being ripped by stunning discharges of lightning. At one point, captain said not to worry, that bolt ( a blinder) was 5 km away so I would guess that the distance between cells was about 10 km.
    Also, in N. Queensland, when we have those hot sultry days that culminate in general storm activity quite often the process stops when the spreading anvils meet and cut off the supply of sunlight. It sure remains humid.
    About the “dehumidifier” effect. I’d like you to explain better just what you mean. Condensation droplets (fog, cloud. rain) form when relative humidity reaches 100%. I can see that rain removes heaps of water from the atmosphere, but does that decrease the relative humidity?
    When I was a youth, I constructed my own wet-and-dry bulb thermometer set so that I could measure rel. hum. in caves. And yes, they were boringly humid. As a rabid Thunder Storm watcher, I turned it to measurements before and after storms. The typical description was: Hot humid,T about 34C, rel hum. about 80%, storm coming, hotter and rel.hum. rising a bit; storm passed , T about 20C rel. hum. 99%,local stream flooding.
    So, are these processes different to what you have described over the coral sea?

  26. GCMs are known to deliberately underestimate the cooling effect of thunderstorm as using the correct input would prevent them from telling scary stories!
    It is already established that Convective cooling increases exponentially with increasing temp, yet computer modellers are allowed to program this as only a linear relationship.
    nuf said!

  27. “and the heat of condensation drives the deep circulation to the upper troposphere. From there, dry air descends again to the surface.”
    How does the air lose energy and buoyancy and descend? IR radiation to space?

  28. Pedantic old Fart says:
    April 21, 2013 at 4:20 pm

    Ellis, a few things. I loved your description of the serried ranks of storms in squall lines across the Coral Sea,evenly spread. It seems to be different over land? The multiple squall lines I’ve seen have been linear and pushed along by cold fronts.

    Thanks, Pedantic. In terms of pedantry, name is Willis.
    I don’t think the difference is land versus not land. I think it’s tropics versus temperate zone.

    Also, in N. Queensland, when we have those hot sultry days that culminate in general storm activity quite often the process stops when the spreading anvils meet and cut off the supply of sunlight. It sure remains humid.

    If the thunderstorm process stops for any reason, the de-humidification stops, so yes, it can get humid in that condition.

    About the “dehumidifier” effect. I’d like you to explain better just what you mean. Condensation droplets (fog, cloud. rain) form when relative humidity reaches 100%. I can see that rain removes heaps of water from the atmosphere, but does that decrease the relative humidity?
    When I was a youth, I constructed my own wet-and-dry bulb thermometer set so that I could measure rel. hum. in caves. And yes, they were boringly humid. As a rabid Thunder Storm watcher, I turned it to measurements before and after storms. The typical description was: Hot humid,T about 34C, rel hum. about 80%, storm coming, hotter and rel.hum. rising a bit; storm passed , T about 20C rel. hum. 99%,local stream flooding.
    So, are these processes different to what you have described over the coral sea?

    Dunno … what I have shown in Figure 7 sounds a lot like what you measured. The highest relative humidities are at the coldest times, which are the times of rain or in the immediate aftermath … which is what you’re describing.
    Best regards,
    w.

  29. Thanks for the interesting post, WIllis,
    Every year, I get to experience tropical cloud formation twice (once there, once back) and have mused about what is going on in the atmosphere, often using thermal convection cells in a boiling pot of water as a mental analog. The thunderstorm diagram is very enlightening.
    Your graph of AH v. sea surface temp suggests that AH remains constant above 26C (as per previouis article). Well, we all know positive feedback in the atmosphere is clearly not occuring (we would all have fried or frozen billions of years ago) so this explains a lot.
    Of course, the Warmista’s invented the magical positive feedback to pursue their paymasters’ agenda, hoping that no engineers or historians or geologists would notice.
    Ha! Fat chance.

  30. Outstanding Willis. I would say you have found something of fundamental importance here.
    The lower temp range where there is a notable slope (justification of feedback) is a very sparse proportion of the data. It would be worth stating the percentage of the total data that is in each segment you fit to.
    The bulk of the data is nearly flat, though it clearly does have a significantly non-zero trend.
    The other thing is the max temp you have posted on before. The right hand side of the scatter plot is nearly straight. Your governor again. How will a feedback work when it runs into that wall?
    If we were to hypothesise another degree of warming that graph would simply get condensed. It would not get shifted bodily to the right.
    Finally I would suggest that you also invert the axes and check the slopes the other way around.
    This is one of things that many scientists of all areas of study get wrong because they don’t know the maths, they just click on the button: fit trend.
    It is fundamental to the validity of least squares fitting that the independent variable ( x axis to be less technical) has minimal errors compared to the dependant variable. If this is not true you get the wrong answer. That simple. The slope will be lower.
    Now in the case of this kind of data, it is not the actual measurement error that is relevant but whatever other processes are present that causing this widely spread cloud of points rather than neat line of data that reflects the relationship you are seeking to quantify, ie there is very significant ‘noise’ on both variables.
    There’s not short answer or “correct” method in this case but if you do the same thing the other way around the error will be in the other sense and you will have at least put upper and lower bounds on it.
    You can then take the reciprocal of those slopes and plot them on the original graph as an uncertainty range bounding the true slope.
    What you currently have is the lower bound, so it’s probably quite important to test the upper bound to avoid thinking it’s flatter than it is.
    Published studies (eg Dessler 2010) attempting to measure climate sensitivity contain this same error. Since the ratio they are measuring is then inverted to get the climate sensitivity, the incorrectly lower slope produces a higher value for CS. Oops.

  31. Hi Willis,
    Thanks for another very interesting article. I have liked your physical model of thunderstorms as a temperature regulator, from the first post you made of it. And this is a very nice addition.
    I’d just like to add to a generalisation that you made:
    “And other research of mine has shown that in general clouds cool the earth in the summer and warm it in the winter.”
    I agree with this, but would add that in general, daytime clouds always cool in summer and generally cool in winter, night time clouds always seem to warm both summer and winter. In my subject experience.
    Its a pity that one of the Universities with a sceptic Head of Department wouldn’t fund you as a visiting researcher so that you could work on this full time with out needing a day job.
    Thanks again for an interesting post
    Regards
    /ikh

  32. Another gem from Mike MacCracken the Climate Institute Director:
    “So, moist Gulf Coast air made it all the way up to Minnesota? Really–Mike”
    I guess Mikey has never heard of MPHs advecting warm air from the Gulf of Mexico…

  33. ‘Dehumidifier versus Heat Engine.’ ‘Frictional Dissipation in Falling Precipitation.’
    Refer:
    Chapter 9: Water vapor and Entropy Production in the Earth’s Atmosphere by Olivier M. Pauluis
    in:
    Non-equilibrium Thermodynamics and the Production of Entropy; Life, Earth and Beyond.
    Axel Kleidon and Ralph D. Lorenz (Eds)
    Springer, 2005

  34. Willis: I am not surprised at your discovery of ranked thunderstorms (although I never tumbled to it, either). Just take the two-dimensional picture shown in Figure 2, and give it a third dimension. So long as conditions exist to create the Figure 2 X-Y dynamic, it should extend as far into Z as those conditions pertain. Same for your late-night ocean overturning concept. Same for rising salt diapirs when an evaporite bed is uniformly compressed. Same for the mounds and depressions on the bottom of an egg carton. The termini of these areas marks a step change of some sort in temperature, geography, pressure, or material availability (in relation to the examples I gave above).

  35. I think you’ll see more if you simply plot humidity, temperature, SW and LW vs time. You’ll see a signature like a heartbeat across each day, and you will be able to see the phenomena you’ve described, and be able to detect the storms by change in signature. If you smear it all together, I don’t think you’ll see as much. In fact, if you simply connected the dots in your charts by time (rather than just dots), you will see events emerge. Once you can verify a few big storms went through by radar or other reports, you can see what changed during the duration of the storms, analyze slopes, etc. I’m not sure whether the buoy you picked has LW, but some do. It seems like that is really what you’re wanting to see, which is the main reason I suggest that method. I’ve started to play around with this but have been too busy to do the detection algorithms like I wanted. Seems like I’ll have time 2 weeks out no matter when it is. Now I’m busy working on my Classic Range Rover (head gaskets, ugh).

  36. Thanks Willis, more interesting observations expressed in plain language.
    I want to provide links to your other posts regarding the earth thermostat principles of thunderstorms to a local weather blog in my area. If you could provide links it would be a great help as my time now is quite limited. It may also help other readers here who may have missed your earlier posts. A couple of those posts were just too important not to be viewed by all.
    Sorry to sound too lazy to look back in the WUWT archives, just short on time. Thanks.

  37. eyesonu says:
    April 21, 2013 at 7:57 pm

    Thanks Willis, more interesting observations expressed in plain language.
    I want to provide links to your other posts regarding the earth thermostat principles of thunderstorms to a local weather blog in my area. If you could provide links it would be a great help as my time now is quite limited. It may also help other readers here who may have missed your earlier posts. A couple of those posts were just too important not to be viewed by all.
    Sorry to sound too lazy to look back in the WUWT archives, just short on time. Thanks.

    Thanks for the vote of confidence, eyesore. Here are some links. There’s a very out-dated index here.
    My first paper on the subject was the Thunderstorm Thermostat Hypothesis. It was followed by Further Evidence for my Thunderstorm Thermostat Hypothesis.
    I provided links to three papers on the TAO buoy data, and the refrigeration paper in the head post. I also linked to the paper on the winter/summer aspect of clouds.
    Another important paper was It’s Not About Feedback.
    Regarding the human cost of increasing energy prices, see We Have Met The 1%, And He Is Us.
    Regarding supposed loss of atolls and river delta lands, see “Floating Islands“, and “The Irony, It Burns“.
    There are a couple of posts on emergent climate phenomena, including Emergent Climate Phenomena, and Slow Drift in Thermoregulated Emergent Systems.
    That’s a good start, I have lots more, There’s a full list, page after page, from the most recent backwards, located here. At twenty posts per page, there’s about 17 pages of them.
    Finally, my autobiography is online here as short stories, most recent on top. There are several pages.
    All the best,
    w.

  38. Michael D Smith says:
    April 21, 2013 at 7:57 pm

    I think you’ll see more if you simply plot humidity, temperature, SW and LW vs time. You’ll see a signature like a heartbeat across each day, and you will be able to see the phenomena you’ve described, and be able to detect the storms by change in signature. If you smear it all together, I don’t think you’ll see as much. In fact, if you simply connected the dots in your charts by time (rather than just dots), you will see events emerge. Once you can verify a few big storms went through by radar or other reports, you can see what changed during the duration of the storms, analyze slopes, etc. I’m not sure whether the buoy you picked has LW, but some do. It seems like that is really what you’re wanting to see, which is the main reason I suggest that method.

    Thanks, Michael. As usual, and as I said above, more good ideas than time to explore them.
    Yes, splitting them by various things (time, SW, LW, and the like is interesting. Did you see my links to One, Two, and Three in the head post? These cover some of those subjects. As always, of course, there’s more to do than time to do it.

    I’ve started to play around with this but have been too busy to do the detection algorithms like I wanted. Seems like I’ll have time 2 weeks out no matter when it is. Now I’m busy working on my Classic Range Rover (head gaskets, ugh).

    Ah, yes, the joys of the torque wrench. I wish you well, from a fellow practitioner.
    w.

  39. Thanks Willis.
    As far as being “eyesore” I’ll shave and comb my hair just for you! 😉

  40. Great post, Willis. I’ll admit being lazy–now I just click “thumbs-up” on a bunch of comments in favor of your observations and expanding the scope. Aren’t these digital nuances grand?

  41. Why can’t climate scientists actually go down to the tropics and do some measurements on a wider scale. After all AGW rests of the whole idea of water feedback. Maybe they did and did not find what they were expecting and put such a study under the carpet.

  42. Willis to M. Smith: Did you see my links to One, Two, and Three in the head post? These cover some of those subjects. As always, of course, there’s more to do than time to do it.
    No, I hadn’t seen those and didn’t follow the links the first time. Thanks, I’ll read those a few times… There’s a lot going on in those waveforms.

  43. Fantastic idea Willis. The “consensus” assumes that RH is constant but the bouy suggests it is AH that tends to be constant. I am not familiar with the argument for the RH-constant assumption. Is it just an argument, without supporting data, or is there some context in which the data supports the RH-constant assumption?

  44. The planet does not receive 340W/m2 over the whole surface since the sun only radiates on a 12/24 basis. ie. we have day and night. You cannot model as you have but you must follow reality. this is how we have got into the GHE mess we are in at the moment.
    TOA insolation is ~1370W/m2. surface radiation is ~1000W/m2 which is a measured quantity in the zenith position, roughly the tropics. average hemispheric radiation is 500W/m2 which gives a radiative equilibrium temperature of about 34C. the planet has more than enough incoming heat to attain the +14C calculated average. What you observed was the excess heat loss due to convection, the most efficient way for surface heat to dissipate and a well underestimated loss by Trenberth who does not really consider what you observed. It might be better if he got out more.

  45. Thank you for your reply, Willis and apologies for getting your name wrong. I do actually have a file of your posts—-correctly named!

  46. Willis,
    You provide this disclaimer about the data and your code at the end of an otherwise excellent article:
    “DATA AND CODE: Well, the code is a mess. By a mess I mean it’s in my usual form, in that I write in bits and chunks, and in general I only run selected lines. So while the code contains all the information and calculations needed to do the analysis above, they are not necessarily in order. Plus there’s a lot of other code that isn’t used, or didn’t work, or worked but wasn’t needed for the post. And far from being user-friendly, code I write might be described as “user-agressive”, I wrestle with it constantly.”
    Were I a rabid critic I would jump on this as evidence that you are deliberately trying to obscure your methodology. You technically meet the requirement to provide your data and code – but as you say “the code is a mess.”
    I am not a rabid critic, rather a big fan, who hates to see you tee yourself up for criticism from those more interested in form than substance.
    All the best,
    Andy Wehrle
    Stafford, VA

  47. Willis. Cool idea sharing the code. If all climate science was done like that !
    However, there seem to be some glitched loading R files. (tab file was fine).
    buoy temperatures.R , R reports unexpecte closing brace in line 221 , if I remove it, it then finds an empty block in a for loop. Looks like something got chopped out by accident.
    for (i in whicharehot){
    for (j in 1:24)
    }
    Could you check your files?
    Thanks.

  48. Great stuff as usual, Willis.
    Have you read “Song of the Sky” by Guy Murchie, incidentally?

  49. Greg Goodman says:
    April 22, 2013 at 6:40 am

    Willis. Cool idea sharing the code. If all climate science was done like that !
    However, there seem to be some glitched loading R files. (tab file was fine).
    buoy temperatures.R , R reports unexpecte closing brace in line 221 , if I remove it, it then finds an empty block in a for loop. Looks like something got chopped out by accident.
    for (i in whicharehot){
    for (j in 1:24)
    }
    Could you check your files?
    Thanks.

    Like I said, Greg, there’s lots of unused sections left over from previous stuff and dead code and who knows what in there.
    All the best,
    w.

  50. Andy Wehrle says:
    April 22, 2013 at 4:37 am

    Willis,
    You provide this disclaimer about the data and your code at the end of an otherwise excellent article:
    “DATA AND CODE: Well, the code is a mess. By a mess I mean it’s in my usual form, in that I write in bits and chunks, and in general I only run selected lines. So while the code contains all the information and calculations needed to do the analysis above, they are not necessarily in order. Plus there’s a lot of other code that isn’t used, or didn’t work, or worked but wasn’t needed for the post. And far from being user-friendly, code I write might be described as “user-agressive”, I wrestle with it constantly.”
    Were I a rabid critic I would jump on this as evidence that you are deliberately trying to obscure your methodology. You technically meet the requirement to provide your data and code – but as you say “the code is a mess.”
    I am not a rabid critic, rather a big fan, who hates to see you tee yourself up for criticism from those more interested in form than substance.
    All the best,
    Andy Wehrle
    Stafford, VA

    Thanks, Andy. For my more coherent and finished posts I’ve provided much more coherent code. This was another of my peripatetic peregrinations around the TAO dataset, so I don’t put much time into cleaning up the code.
    However, all of the details are there, and you can check the math, and it does run.
    w.

  51. Observation + curiosity + observation + …. = intelligent apprehension => science.
    Well brought to life. It will be interesting to see where this goes.

  52. johnmarshall says:
    April 22, 2013 at 3:18 am

    The planet does not receive 340W/m2 over the whole surface since the sun only radiates on a 12/24 basis. ie. we have day and night.

    That’s true … and I generally only eat during the day.

    You cannot model as you have but you must follow reality. this is how we have got into the GHE mess we are in at the moment.
    TOA insolation is ~1370W/m2. surface radiation is ~1000W/m2 which is a measured quantity in the zenith position, roughly the tropics. average hemispheric radiation is 500W/m2 which gives a radiative equilibrium temperature of about 34C. the planet has more than enough incoming heat to attain the +14C calculated average.

    You can’t just use peak heating to determine the incoming energy, any more than I can use peak eating to determine whether I’ll gain or lose weight. Instead, in both cases you need to average what’s happening over a full day.
    I’ve discussed this issue at length both here and here.

    What you observed was the excess heat loss due to convection, the most efficient way for surface heat to dissipate …

    The surface loses heat by radiation (~ 390 W/m2), evapo-transpiration (~ 80 W/m2) and sensible heat (~ 80 W/m2). I’m not sure what you mean by “most efficient way for surface heat to dissipate”.

    … and a well underestimated loss by Trenberth who does not really consider what you observed. It might be better if he got out more.

    If you have a problem with one of Trenberth’s estimates, you’ll need to show where he is wrong. The basis of his estimates is well explained in his papers (here and here), come back and tell us what he’s done wrong.
    Thanks,
    w.

  53. Another evidence for the dehumidification effect is how much clearer the air is after a thunderstorm.

  54. However, all of the details are there, and you can check the math, and it does run.
    w.
    Nope.
    Loading required package: stringr
    Error in R_nc_inq_varndims: NetCDF: Not a valid ID
    Error in varndims.ncdf(nc, varid) : error returned from C call
    Sure if I wanted to spend the time debugging someone else code that probably runs on their machine but not elsewhere without modification. But I contest the claim “it does run” as it stands.
    All the best.

  55. Greg Goodman says:
    April 22, 2013 at 11:54 am

    However, all of the details are there, and you can check the math, and it does run.
    w.

    Nope.
    Loading required package: stringr
    Error in R_nc_inq_varndims: NetCDF: Not a valid ID
    Error in varndims.ncdf(nc, varid) : error returned from C call
    Sure if I wanted to spend the time debugging someone else code that probably runs on their machine but not elsewhere without modification. But I contest the claim “it does run” as it stands.
    All the best.

    I told you, it doesn’t run as a whole entire program. To be exact, I said:

    I write in bits and chunks, and in general I only run selected lines. So while the code contains all the information and calculations needed to do the analysis above, they are not necessarily in order. Plus there’s a lot of other code that isn’t used, or didn’t work, or worked but wasn’t needed for the post. And far from being user-friendly, code I write might be described as “user-agressive”, I wrestle with it constantly.

    Since it did all that I asked it to do, and it successfully generated the results and drew the graphics for this paper, I say it does run. Sorry it’s not up to commercial quality code, but I am doing exploratory work, not writing up a paper for publication in the journals. If you are interested in the subject, it’s not all that hard to analyze the TAO data yourself.
    In this case, it doesn’t matter, the program doesn’t use anything from that package. Remark out the “require(“stringr”)” line and keep going.
    Although why I should assist someone as demanding as you is a bit of a mystery … next time, just ask for assistance or explanation and leave out the attack mode, you’ll get further in life that way.
    w.

  56. Hey, Willis that’s not attack mode.
    I did ask earlier that you check the code and you basically said “your on your own bud, good luck”.
    There’s no obligation and no-one’s expecting fully debugged ,error trapped, commercial quality code. However, it’s you who knows what bits are needed, it seems a pointless waste of effort for me (or multiple others) wasting time sorting chaff from the wheat.
    Sure I could do it from scratch, but I could do whole stack of more interesting things with that time too.
    Since you know the code, it would probably take you 5 minutes to cut and paste the relevant bits and post something such that source (“buoy temperatures.R”) would produce the graph.
    Now I think you have hit on something important and I was willing to do the inverse OLS that I suggested above that is needed to make the result more thorough and resistant to attack.
    However, if I have to go and get the data, reinvent the wheel or re-spoke your wheel, I can think of more useful ways to spend the time, like picking the fluff out of Dessler’s clock, rather than one buoy near the Solomons.
    I would have thought that the idea of sharing code was to save each other work not to make each other work. At least that would be my motivation.
    Please don’t regard it as an attack. I thought I may be able to chip in a bit of effort to strengthen what you’d done but I’m not interesting in climbing a hill before I start the job.
    I’m working on other stuff and don’t want to get diverted into spending loads of time parsing all that to sort what is relevant and what is chaff. I’ll go back to what I was doing.
    Anyway, I think you have something important here, I suggest you take it further.
    All the best.

  57. Willis, a couple of years ago, I spent some time looking at SST data and used the Honiara gridcell as a type case. See http://climateaudit.org/2010/08/30/a-first-look-at-icoads/
    I looked at this gridcell at WIlliam Kininmonth’s suggestion – I wanted to look at a cell where the weather changed as little possible on an annual basis, figuring that this would be the best sort of spot to look for secular changes, as distinct from fluctuations.
    I did a related post on Hawaii as well. http://climateaudit.org/2010/09/01/icoads-hawaii/ which had a pretty graphic illustrating the impact of different fleets on SST measurement.

  58. Konrad says:
    April 21, 2013 at 4:59 pm
    “and the heat of condensation drives the deep circulation to the upper troposphere. From there, dry air descends again to the surface.”
    How does the air lose energy and buoyancy and descend? IR radiation to space?

    The Warmers assert it is a radiative transfer. They treat the tropopause as some kind of ‘lid’ and the implication of ‘pause’ is that mass flow stops, so it just must be radiative.
    That is a misunderstanding. The tropo”pause” has a Cat 2 Hurricane force wind level, just blowing sidways instead of convecting upward. That wind heads off toward the ‘cold pole’ where most of the heat loss happens in the arctic (or antarctic) winter night. So there is both radiative and conductive heat loss across the tropo”pause”. As you might guess, there is also some mass flow across the “pause” too. That cold descending polar vortex air had to get up into the stratosphere somewhere… and it’s not doing it at the descending polar area…
    http://chiefio.wordpress.com/2012/12/12/tropopause-rules/
    goes over it some, and has a couple of nice pictures showing how there IS mixing such as this one:
    http://chiefio.wordpress.com/2012/12/12/tropopause-rules/tropobands-cell1/
    This one that shows water radiating at the top of the troposphere and CO2 radiating way high in the stratosphere:
    http://chiefio.wordpress.com/2012/12/12/tropopause-rules/stratosphere-radiation-by-species-1460/
    so more CO2 just makes for better radiation way up high and any added heat down low just makes more thunderstorms so more water radiating at the top of the troposphere.
    http://chiefio.wordpress.com/2012/12/12/tropopause-rules/wind-speed-alt-1090/
    gives wind speed by altitude. Note the 80 knts+ at the tropo”pause” height… Think what it does to the top of the troposphere to have an 80 knt wind blowing over those radiative water laden areas and heading off to the ‘cold pole’ to become the Night Jets… and the descending polar vortex…
    http://chiefio.wordpress.com/2012/12/13/snow-polar-night-jets-and-cold/
    The notion that it’s all radiative all the time is just another of the very broken ides of AGW advocates… It’s mass driven. Mass of water. Mass of air. Mass of evaporated water transport and condensation and mass of frozen water returning to the surface. Convection and Enthalpy rule, not radiation.

  59. Willis, please re-read what I posted.
    Max. surface radiation is ~100W/m2 on HALF the planet makes #500W/m2 on average for a hemisphere. In fact the sun heats about 10% of the turning surface at its maximum figure of 1000W/m2 and I repeat convection removes a large portion of this heat, radiation much less, as a look at zenith surface temperatures will show. Deserts approach 60C max. whilst the rainforest areas get to 30-40C and this is because of the water vapour and latent heat in those areas. The temperature at radiative equilibrium of 1000W/m2 is 88C. You can measure ~1000W/m2 at the surface in the zenith position so it seems ridiculous to me to use 167W/m2 as Trenberth does. If he does this then his explanations are wrong as I am concerned.
    The whole planet’s surface radiates, on average, ~250W/m2 day and night. Heating at an average 500W/m2 over the day hemisphere will ballance the 250W/m2 from the whole planet day and night. We so comply with the 1st law.
    It is obvious that heating on a sphere will be at maximum directly below the source of heat and diminishing to zero at the edges. This needs no scientific explanation since it is observably obvious and can be shown on a spherical model, football, and a tourch. Terberth’s model not only uses the wrong inputs to his model but even this is flat with 24/7 sunlight, (which is where he gets his TOA figure but dividing total flux by 4, for total insolation coverage, then reducing this for albedo and atmospheric adsorption to get his too low 167W/m2.).
    Trenberth figure for latent heat, 78(?)W/m2 is a pure guess by someone who has never observed tropical Cb formation as we both have. This figure has to be much higher because latent heat removes a lot of heat from the surface to high in the troposphere and higher as I have observed flying at just below 65,000ft with Cb still building above me and very violent they were too.
    The whole AR4 graphic as wrong from the inputs to the unneeded GHE to the right and the flat earth. Reality is a pill sometimes a little bitter and climate science has yet to get to grips with reality. If their version of reality is a flat earth then what hope for all the rest of their theories.

  60. johnmarshall:
    re your post at April 23, 2013 at 2:58 am.
    I write in hope of helping.
    Trenberth’s cartoon diagram shows average heat fluxes of the Earth. The average fluxes are (a) to and from space and (b) to and from the atmosphere and surface.
    The averages are for all the Earth’s surface and for all time (day, night and seasons) throughout a year.
    The diagram does NOT assume, state or imply “a flat earth”.
    It provides average values for the whole of the Earth’s spherical surface throughout a year in which the Earth rotates to provide days and orbits the Sun to provide seasons.
    Please note that I am not defending Trenberth’s cartoon: I think there is much wrong with it. I am writing to correct your stated misunderstanding of it.
    Richard

  61. Where Mosher telling us that all this complex convection/clouds is already taken care of in the models?

  62. Greg Goodman says:
    April 22, 2013 at 2:31 pm

    Hey, Willis that’s not attack mode.
    I did ask earlier that you check the code and you basically said “your on your own bud, good luck”.
    There’s no obligation and no-one’s expecting fully debugged ,error trapped, commercial quality code. However, it’s you who knows what bits are needed, it seems a pointless waste of effort for me (or multiple others) wasting time sorting chaff from the wheat.

    Thanks, Greg. I actually did cut out and simplify the code before I posted it. And I just went to check it, it even runs passably straight from the top.
    I’m sorry it’s not in turnkey shape, Greg, but I’m typing this on my break. I have a day job, and my own house and land require attention when I’m not doing that. I don’t have an infinite time left in this world, and there’s loads of things I’d still like to do, and lots of other scientific research waiting for my hand.
    As a result, I’m glad to answer questions about the code, but I’m not going to re-write it. Not enough time.
    Best regards,
    w.

  63. Steve McIntyre says:
    April 22, 2013 at 9:16 pm

    Willis, a couple of years ago, I spent some time looking at SST data and used the Honiara gridcell as a type case. See http://climateaudit.org/2010/08/30/a-first-look-at-icoads/
    I looked at this gridcell at WIlliam Kininmonth’s suggestion – I wanted to look at a cell where the weather changed as little possible on an annual basis, figuring that this would be the best sort of spot to look for secular changes, as distinct from fluctuations.
    I did a related post on Hawaii as well. http://climateaudit.org/2010/09/01/icoads-hawaii/ which had a pretty graphic illustrating the impact of different fleets on SST measurement.

    Thanks, Steve. Your analysis of the Honiara and Honolulu gridcells was eye-opening. I followed your lead and downloaded a bit of the ICOADS data. Another veritable pit of snakes, despite the best efforts of the collators to include every even possibly relevant bit of metadata. We’re still left with the usual problems of instrument location and type and calibration, and observation time, and the usual land-bound problems. Then you add in the issues with the moving platform—a location that may give representative air temperatures going upwind may by hopelessly polluted by the exhaust fan from the galley when going downwind, to pick just one.
    I like the TAO buoy data because it’s just one single spot on the globe, so I know that (absent the inevitable sensor drift) we have an internally consistent dataset. Plus the observations are hourly, and I’m not fond of averages.
    In any case, the beat goes on. I want to look at the 24-hour cycle of AH, never looked at that before. Many thanks for the tip, and for all of the good work that you continue to do.
    w.

  64. johnmarshall says:
    April 23, 2013 at 2:58 am

    Willis, please re-read what I posted.
    Max. surface radiation is ~100W/m2 on HALF the planet makes #500W/m2 on average for a hemisphere.

    John, I’ve re-read that statement above about six times. I fear that there are too many wrong things in that statement to even start to correct them. Nor is that unusual in your claims to date.
    It doesn’t help your case to just toss out un-supported figures and claims, particularly when they make no sense. For example, you claim average surface radiation is 250 W/m2 … based on what? That converts to a temperature (assuming blackbody) of -15°C, well below freezing. As an average radiation level for the planet, 250 W/m2 doesn’t even pass the laugh test.
    Trenberth has provided documentation on the basis of his estimates. I have given you links to both of his papers, and invited you to tell us where he is wrong.
    Instead of doing that, you’re just repeating your un-substantiated prior claims.
    Fail.
    w.

  65. 250W/m2 is the average based on 500W/m2 on the sunlit hemisphere and 1st law. Satellite measurements show average radiation at 247W/m2. Radiation is from high in the atmosphere where -15C is common.
    I repeat why I find Trenberth wrong with his energy graphic in AR4. If you cannot see the clear energy input error given measured energy, sorry. If you cannot see that he is generating energy from nothing then I am sorry. If you cannot see that using a flat earth 24hour sunlit model is wrong then you live on a different planet to me. My argument has always been that if yopur model does not follow reality then your version of reality is wrong. All your arguments seem to be to follow the leader, and quote model outputs from models shown to be wrong by empirical data. Models proving the GHE that have the GHE as a basis for answers cannot be used as proof of the GHE.
    Empirical data shows that it is temperature that drives atmospheric CO2 levels not the reverse. Empirical data shows that the GHE predicted temperature anomaly in the mid to high troposphere not to exist. there are other failed predictions but you seem to ignore data and believe Trenberth modeled output.
    Fail.

Comments are closed.