Guest Post by Willis Eschenbach
I discussed the role of tropical albedo in regulating the temperature in two previous posts entitled Albedic Meanderings and An Inherently Stable System. This post builds on that foundation. I said in the latter post that I would discuss the diurnal changes in tropical cloud albedo. For this I use a marvelous dataset called the TAO dataset. It is measurements from a number of moored buoys in the tropical Pacific.
Figure 1. Locations of all of the TAO buoys ever in operation. Background shows the sea surface temperature.
Sadly, despite the billions spent on “global warming”, the TAO buoys don’t have funds for maintenance. As a result, the records from some have ceased entirely. But I digress … the great thing about the TAO buoy records is that they are either hourly, or every ten minutes, or even every two minutes in some cases. This lets us accurately reconstruct the daily cycles.
To refresh your memory, my hypothesis is that variations in the timing and strength of the emergence of tropical cumulus and tropical thunderstorms act to regulate both the amount of incoming energy and the tropical surface temperature. I say that whenever there is a hot day or a hot area, we get earlier and more dense cumulus and thunderstorms. The cumulus clouds act solely by reflecting the sunlight. Thunderstorms, on the other hand, cool the surface in dozens of ways. This prevents the surface temperature from overheating.
So with that hypothesis in mind, let me start by looking at the daily air temperature cycles. Because of availability of data, I’ve used data from a string of buoys along the Equator. The buoys I used stretch from 95°W (buoy just to the left of the “E” in “Equator”) to 165°E (on the Equator northeast of Australia). Conveniently, the average temperature increases steadily along the line. Figure 2 shows the daily variations in surface air temperature for those Equatorial buoys:
Figure 2. Average daily air temperatures measured at ten minute intervals at eight different buoys. Colors represent temperatures.
Using just locations along the Equator gives me a peculiar advantage. All of the locations receive exactly, precisely, the same amount of top-of-atmosphere solar energy every single day. This means that the differences between them can’t be from different solar forcing. It eliminates a variable from the equation.
Now, there is an oddity about these records, which no doubt you’ve noticed. The temperature doesn’t warm steadily during the day. Let me show you what I mean. Here’s a chart I made a while back showing temperatures at Santa Rosa, California, the met station nearest to where I live.
Figure 3. Hourly temperatures averaged over a year in Santa Rosa, CA. About 20 miles (30 km) from the ocean. The photo shows wine grape trellises.
As you might expect in a generally marine climate that usually doesn’t get much in the way of afternoon clouds or thunderstorms, the graph is simple. As the solar energy increases the earth warms. It continues to warm until around 2:00 and then starts to drop. It cools rapidly at first, then more slowly towards early morning.
However, that’s not the pattern we saw in Figure 2. Instead of a steady straight rise from dawn to noon, there is a bend or a “dip” in the rate of temperature rise. This can be seen more clearly when we look at the same records shown in Figure 2 as anomalies (variations about their individual averages). Figure 4 shows the same data as in Figure 2, but with each individual average subtracted from its respective record.
Figure 4. Same data as in Figure 2, but expressed as anomalies about the individual means (averages). Colors indicate buoy average temperature as shown in Figure 2.
Here we see a most interesting progression. The cyan (light blue) colored trace of 95°W, the coolest buoy, shows only a slight bend in temperatures from 6 am to the afternoon peak. It’s nearly straight. But as we look at warmer and warmer buoy locations, the bend becomes more and more pronounced. In the warmest five locations, there is an actual “dip”, a reduction in temperature as the day progresses.
In addition, the peak temperature anomalies start decreasing with warmer temperatures. Since there is identical solar input to all of the buoys, this must reflect some local phenomenon.
To me, the “dip” in the morning records is the clear sign of the phenomenon I described in my last post—the emergence of the cumulus clouds starting in mid-to-late morning. Through variations in their emergence time, as soon as a certain temperature threshold is surpassed these clouds “throttle” the incoming solar energy by reflecting some of it back to space. This cloud throttling effect is so strong and comes on so suddenly that in the warmer locations, the temperature actually drops despite the continually increasing morning sunshine.
However, in no case is the throttling effect of the morning albedo change sufficient to overcome the full strength of the tropical sun. This is because there is no way for these cumulus to cover the entire sky—there needs to be clear descending air around each cumulus cloud to maintain circulation. As a result, there is only so much the cumulus reflections can do … and so past noon the day continues to warm. The later reduction of the peak afternoon temperature values is due not to increased albedo but to the emergence of afternoon thunderstorms. These “chop the top” off of the temperatures, imposing a high temperature limit and preventing further surface temperature rise.
Having seen that, let me move on to another way that we can see the effect of the morning-time cloud albedo. Note that the clouds that create the reflective albedo which helps regulate the tropical temperature only emerge in response to the surpassing of a temperature threshold. Once that threshold is passed and the increased cloud albedo has come into existence, it acts to reduce the high temperatures by cutting way back on the incoming solar energy.
Given the nature of the regulation, which depends on reflecting the sun’s rays, we can make the following predictions.
• The regulation of the temperature will be stronger in the day than in the night. No sun, no reflection …
• The regulation of the temperature will be greater in the morning than the afternoon. This is because the early morning is often clear and the late morning is cloudy, whereas there are generally clouds throughout the afternoon. As a result, controlling the onset time of the cloud formation will provide powerful regulation, and generally that happens in the morning.
• The regulation of the temperature will be greater up at the warm end of the scale than down at the cool end. This is because the emergent phenomena act to reduce peak temperatures.
With those predictions in mind, I cast around for some way to visualize the effects of the thermal regulation due to clouds and thunderstorms. Figure 5 shows my solution. It is the record of the hourly air temperature from the TAO buoy on the Equator at 165 East. This is the warmest of the buoys in the graphs above (red line in those graphs).
Figure 5. Boxplots of the hourly air temperatures at 0N165E. There are 59,429 observations, or about 2,500 for each hour of the day.
A “boxplot” gives various information about the distribution of the data, including outliers. The green boxes show the range that contains half of the data (the “interquartile range” or IQR). The heavy black line is the median of the data, which is the point with half the data above it and half below. The dotted “whiskers” show a distance from each green box of 1.5 times the IQR for that data. Black crosses show “outliers”, which are data points that are further from the boxes than the extent of the whiskers.
An examination of Figure 5 shows that the predictions of the distributions are borne out by the data. First, daytime regulation, from 6 AM to 6 PM (18:00 hours), is much stronger than night-time regulation. Daytime temperature regulation is so strong that there is not one single outlier on the warm side from dawn until noon, and only one (or in one instance two) outliers in each hour from noon to sunset. In fact, daytime regulation is so strong that there are many night-time temperatures that are greater than the record noon-time temperature … go figure.
Second, the regulation is stronger in the morning than the afternoon. The variations in the timing of the albedo changes are able to oppose the sun successfully until about noon (see Figure 4). After that, the continued solar input starts driving the temperature higher, and the regulation is not as certain.
Third, it is clear from the number and distribution of the outliers above and below the row of boxes that there is extensive downward pressure on any warm temperatures. This shows the cloud/thunderstorm control system is pushing back at the hot spots, cooling them down. Nor does this downward pressure only exist on the warmest temperatures. A close examination of the location of the median line shows that the median is in the middle of the green box from midnight to dawn. But during the day, the median is high up in the green box, showing that downwards pressure from the regulatory mechanisms extends well down into the body of the data.
My conclusion is that this downward pressure is the combination of cumulus clouds throttling back solar input in the morning, and thunderstorms and squall lines moving heat from the surface to up near the tropopause in the afternoon. It is this regulation of each day’s maximum tropical temperature via a host of inter-related mechanisms that keeps the earth from overheating on a daily basis.
And as I mentioned in my previous post, my insight was that if there are mechanisms that reliably keep the earth from overheating for a single day, they would keep the earth from overheating for a million years …
I may return to these topics in a future post, I’ve only scratched the surface of the TAO data.
My best wishes to each of you,
w.
My Customary Request: If you disagree with someone, please quote the exact words you disagree with. That way, everyone can understand your objection.
Data and Code: I’ve been wrestling this for too long, I’m burnt. I’ll post up the code when I get time if someone wants it. This code a dog’s breakfast, no order, functions used before they’re defined, sections of dead code exploring blind alleys. The data, on the other hand, is from the TAO website.
Couldn’t the variations be reduced by proper averaging? Not forgetting the sqrt 2 factor?
Minor “typo”
“Figure 4 shows my solution. It is the record of the hourly air temperature from the Argo buoy on the Equator at 165 East. This is the warmest of the buoys in the graphs above (red line in those graphs).”
I think you mean TAO instead of Argo here.
How many TAOs remain on active duty?
Thanks, George, fixed. And I don’t know the answer to your question.
w.
probable typo; ‘continually increasing morning sunshine’ implies fits and starts. ‘Continuous’ doesn’t.
Find the status of the Global Tropical Moored Buoy Array system here
http://www.pmel.noaa.gov/tao/global/status/
According to this information the global system seems to be ailing but OK.
mebbe one is an adverb, and the other is an adjective.
Yes, george, and you could quibble with any editing comment if you were determined to miss the point.
‘continuous’ and ‘continual’ are not synonyms, whether they’re adjectives or adverbs.
Well here at WUWT, most of us guests do not quibble about pedantic grammar issues. The purpose here is to communicate information and ideas. If you want a forum to quibble about grammar well I can’t think of a better place than twitter, where you can tinkle to your heart’s content.
george, you’re the twit.
adjectives and adverbs are grammar and you introduced that quibble.
My point was one of lexical semantics, which is not grammar; it’s the meaning of words.
Stick to Nyquist sampling comments if you don’t want to come across as an irascible old petard.
Actually, that might not work. So, do what you want.
Petard: “An explosive device used to break down a gate or wall.”
Huh?
It is a given that GCM’s will never be able to model mechanisms at this time scale, to improve overall long-term climate modeling. But what is the possibility that they can use parameterized versions of mechanisms like these inside a GCM grid cell to better model the climate. For example, average daily regulation onset time, average density of thunderstorms, etc…
You have two figures labeled “Figure 3” and refer to them multiple times. Makes it kinda hard to follow your argument.
Otherwise, another excellent write-up.
Thanks, fixed.
w.
Willis, don’t forget that the radiant emittance of the surface increases as T^4 and the spectral radiant emittance as T^5.
Both lead to faster cooling while Temperatures are higher, as in your daytime heating slowdown, and also the night time cool slowdown.
And the higher Temperature periods, tend to move the LWIR emission spectral peak to shorter wavelengths, where lies the “atmospheric window”.
g
That should be ‘peak’ spectral radiant emittance, and of course assuming some semblance of black/gray/colored body behavior.
Your diurnal Temperature graphs also point out why the twice a day (min / max) Temperature reporting regime, doesn’t satisfy the Nyquist sampling criterion, so those sorts of daily Temperature reports don’t give a correct average Temperature without aliasing noise.
g
The distribution of warmer and cooler buoy locations seems odd to me. Why does the daily temperature fall off steadily towards the eastern Pacific?
The North and South Pacific currents bring cold water down/up the East Pacific coastlines to the equator, where it is warmed and pushed west, only to flow toward the poles along Australia/NZ (in the south) and the Philippines and Japan (in the north).
This should be obvious from Figure 1.
Colder water = lower night time temperatures = lower day time temperatures.
I’ll say. Cold water is pulled up along the California coast It is about 45 F here. As that heads toward Indonesia, it takes time to warm… Surface still has cycles at the surface, but the layer a few feet down mixes up by wind and waves tending back to cool, until enough depth is warmed.
http://thejunkwave.com/wp-content/uploads/2011/07/world16-gyre-from-seafriends.org_.gif
The tradewinds more water from East to West and it is warmed along the way. The East pulls cooler water from the South and there is often upwelling of cooler water from below.
Move not more above.
What a joke !.
It would be great talking about daily temperature fluctuations if the academics could manage to understand the fact that the Earth turns 365 1/4 times within the confines of an annual circuit instead of the horror notion of 366 1/4 times –
“During one orbit around the Sun, Earth rotates about its own axis 366.26 times” Main ‘Earth’ article, Wikipedia
http://en.wikipedia.org/wiki/Earth
The Earth turns 1461 times within the confines of 4 annual circuits to a close approximation therefore turns 365 1/4 times per annual orbital circuit. The ridiculous 366 1/4 rotations is a consequence of the ‘solar vs sidereal’ fiction yet it is left to stand as though it was the greatest fact ever.
” It is a fact not generally known that,owing to the difference between solar and sidereal time,the Earth rotates upon its axis once more often than there are days in the year” NASA /Harvard
http://adsabs.harvard.edu/full/1904PA…..12..649B
It is not that academics can believe that nonsense, it is that the extension of that stupidity really surfaces in the lack of an explanation for the purpose of the extra 24 hour day and the extra rotation (with all the daily effects) that closes out 4 annual circuits on February 29th.
The most astonishing thing about this is that nobody else is astonished.
Copied an pasted your link, http://adsabs.harvard.edu/full/1904PA…..12..649B, into my browser.
Produces an Invalid bibliographic code message.
Also, no one will mind if you were to correct the Wikipedia reference.
It is an open source document, and you did find the error.
You fail to appreciate that the abominable 366 1/4 rotations value is a result of dubious reasoning based on the ‘solar vs sidereal’ fiction. The ‘fact’ in Wikipedia is not presented as an error but rather a result of a failure to appreciate the juncture where timekeeping merges with the daily and orbital cyclical dynamics of the Earth. The external references which defines the Earth’s position in space and the number of times the planet turns within an orbital circuit is absent from all descriptions and everywhere.
Through a generational error, most schoolboys learn that the Earth is into the next full rotation after 23 hours 56 minutes 04 seconds hence the accumulative 3 minute 56 seconds difference to 24 hours is supposed to build up into an extra rotation than there are 24 hour days. Even though the appearance of the Sun followed by the appearance of the stars within each 24 hour day is meant to satisfy any intelligent person as to the underlying cause of a single rotation, we live in an era where it is common practice to ignore the most basic of all facts where days and rotations keep in step.
It may be fine for Willis here to wax lyrical about daily temperatures and how they pick up over the course of a day but he is doing it in a world that is unable to untangle timekeeping from planetary dynamics with the result that the most inviolate facts known to humanity are challenged such as the correspondence between a single day and all the effects within a 24 hour and extended out to a mismatch between rotations and orbital circuits.
Off the Topic of Willis’ blog, and also wrong. This was explained in elementary astronomy class. The earth moves along its orbit around the sun slightly less than 1 degree each day. So after a complete rotation on its axis relative to distant stars, it must rotate that additional 1 degree for the sun to appear in the same position as the day before. This takes aout 4 minutes. If the earth were rotating in the reverse direction from its orbital direction around the sun, we would have 367.22 days per year instead of 365.22 (that is, one more day than the 366.22 in a sidereal year, instead of the one less day we have in the real world.
Well,well ,well Mayor of Venus.
The dumb idea is that the Earth is into the next full rotation after 23 hours 56 minutes 04 seconds and therefore 24 hour days and rotations fall out of step within an orbital cycle given the hideous 366 1/4 rotations per orbital circuit . It doesn’t matter that the 24 hour system and the Lat/Long system work in tandem within the confines of 4 annual circuits where the average 24 hour hour days substitutes for constant rotation at a rate of 15 degrees per hour, academics contrive an alternative explanation to suit a conclusion made way back in the late 17th century .
Not being able to match the daily 24 hour temperature fluctuations with the single rotation behind it, and this is exactly how that dumb ‘solar vs sidereal’ fiction does introduces the spectre of pandemic incompetence and that is where the real catastrophe is.
Personally I enjoy the Sun coming up in the morning as the Earth turns and brings it into view followed by the stars as the Earth turns away from the central Sun. If any of you find yourselves believing there is one more rotation than there are 24 hour days (as implied by the ‘solar vs then I suggest you go out walking in the early morning or at twilight and get all the ‘solar vs sidereal’ nonsense out of your heads. Common sense is a wonderful thing .
[Personally, I enjoy threads that stay on topic, and I’m forcing that point today – Anthony]
The Wikipedia statement is correct. Imagine the Earth would rotate around the Sun in a year’s time with the same side of the Earth always facing the Sun (like the Moon revolves around the Earth). Then by completing one full rotation around the Sun the Earth would also have rotated about its own axis once – in the same direction as it normally does. However, we would not see a sunrise or sunset and as such won’t experience this extra rotation as an additional day. Yet, the additional rotation of the Earth has meanwhile happened.
[snip -OK you are done here, your theories aren’t pertinent to the discussuion, and are wildly off-topic. You’ve been put into the troll bin before for thread bombing, and back you go -Anthony]
“Then by completing one full rotation around the Sun the Earth would also have rotated about its own axis once”. How so? If you spin a globe it rotates around its axis, meaning it spins similarly to a wheel on an axle. The axle itself is not spinning with the wheel. In your example the globe and its axis orbit the Solar System’s gravitational center without Earth rotating on the axis at all. Earth and its axis could be glued together as Earth is not spinning relative to its axis. That’s not “rotation” on its axis when the “rotation” of Earth you describe as seen from anywhere off Earth is due to the axis itself orbiting the Sun. Notice you said “like the Moon revolves around the Earth”. Revolves is correct. The Moon doesn’t rotate around its axis by always keeping one side to Earth.
BobM
In my thought experiment, consider an observer sitting on the North Pole who keeps his nose pointing at a distant star in the plane of Earth’s orbit around the Sun. When looking down at Earth, the observer would see the Earth rotating about its own axis in a year’s time.
(If you would think of the axle being fixed to the wheel, the axle would run in imaginary outer bearings.)
Similarly, an observer sitting on top of the Moon keeping his nose pointed at the Sun will see the Moon making a full rotation below him in about a month’s time.
I’m aware it’s off-topic, hope to get into Willis’s revelations when time allows.
Frans – I don’t disagree. It’s what I get for swooping into WUWT while working and not paying close enough attention. Its all way OT anyway… I didn’t think your example was great, and I don’t think my response was great either… Best example I’ve heard of is a diagram of the Sun and Earth with an arrow through Earth pointing at the Sun, indicating noon, with the feathers of the arrow at midnight. Six months later, say 183 days, if Earth has rotated exactly 183 times on its axis, the arrow is pointing in the same direction, but with Earth on the other side of the Sun, it is the feathers that would be sunlit, not the point. But we know that 183 days later the arrow WILL BE pointing at the sun, so Earth has rotated 183 complete times, plus another 180 degrees (1/2 rotation) for the arrow to point to the Sun each day at noon. Hence, 183 1/2 rotations in 183 days, with each day completing one full rotation plus just under another degree of rotation to accommodate Earth’s orbital movement around the Sun, about 1.6 M miles a day. Repeat another six months and Earth has to have rotated another 1/2 rotation more than the number of days. Hence, 366 rotations in a 365 day year.
OK, done with this.
So when is Willis going to submit his great stuff to be published?
Gkell1
And again I say to one of your posts… wait, what?
Or to put it more clearly, what does this have to do with the article?
Thanks Frans and the Mayor of Venus, I was never aware of that.
Hi mr Eschenbach
I am wondering about the “plateau” in the cooling ? do you have a theory there as well?
Like all great ideas, this one seems obvious when looked at through the retrospectoscope. I guess it doesn’t fit the narrative of the “made to order” science that is so common in the climate arena so no one wants to look at it.
As usual, an edifying and fascinating (and fantastically succinct) analysis from the always enlightening Mr. Eschenbach!
+1. Great, and in retrospect obvious, analysis. Sorry AJ, you seem to have said that already.
Thanks Willis.
As usual, excellent and clear. The one thing that bothers me is those warm outliers prior to sunrise. What sort of phenomenon can account for the appearance of the morning sun’s cooling things by several degrees C? Fog? Temperature inversion? Maybe if I had spent more time in the tropics (too bloody hot for me) the answer would be obvious. Anyway, I’d like to see a plausible explanation just for reassurance that they don’t signal some sort of a data collection/analysis artifact that also somehow affects the daytime data.
The temperature would continue to sink until the sunshine became strong enough (high enough in the sky) to overcome the natural cooling from no sun.
Isn’t this the time when “green house gases” would have most effect?
The thought then arises that someone (not me – I’ve tried playing with R and I don’t have enough years left ;-)) might be able to see if there is any detectable signal with increasing CO2 and other gases over time?
Tisdale and Eschenbach (and of course Watts will go down in history as Climate heroes – that’s my prediction.
Thanks Willis, up in the great white north we have a similar “control” . The forecast is for very high temps but as soon as temps go up in late morning clouds form (with occasional t-storms) from evaporating late spring mountain snow and moisture from our spring rains and voila the temps are generally 3-5 degrees colder than what was predicted. I have really like these reports, fascinating.
The same thing happens in Arctic coastal areas in summer. The land warms until it creates an onshore sea breeze that cools the air for several mile inland by tens of degrees.
Passes the smell test. Only thing now is to wed it to some cloud data; if such a thing exists.
Another fascinating read thank you. You make it easier to understand what is going on both in the ocean and in your head as you work through the data. Talking of data that is probably why the buoys are not being looked after who wants data when it doesn’t follow the party line or the money can go on the gravy train as Dr Tim Ball wrote in his post,
To cover these diversions they took money from other programs. There are fewer weather stations in Canada now than in 1960, many replaced with unreliable Automatic Weather Observing Stations (AWOS). Many important activities and data collection practices were abandoned. While I was chair of the Assiniboine River Management Advisory Board (ARMAB) in Manitoba the worst flood on record occurred. We asked Water Resources why they didn’t forecast the event. They said they had no data on the amount of water in the snow in the valley. We learned EC canceled flights that used special radar to determine water content. Savings, as I recall, were $26,000. The cost of unexpected flood damage was $7 million to one level of government alone. Loss of weather data means long continuous records, essential to any climate studies, are impossible.
And who wants to hear that the earth can and does look after itself and has been and will keep doing it.
James Bull
The fact that our planet Earth has to have its own self-regulating thermostat system seems to me to be self-evident, otherwise life as we know it today simply would not exist.
Cumulus cloud formation and their resultant thunderstorms appear to be a major part of this thermostat process, doubtless overlooked or underestimated (deliberately?) in most/all IPCC climate models.
Climate models don’t have the resolution (grid size) to see a Thunderstorm. Or the physics to properly simulate convection.
The diurnal wake up processes that Willis describes here, with his thundercloud development, in the afternoon, reminds me of summer life in Saint Louis Mo. County region in the mid 1960s.
It seemed that every Sunday afternoon at around 4PM, there was a thunderstorm front passing through, and one of my colleagues and I, took that as an occasion to get out of our apartment complex swimming pool, and head out into the county farmland to set up our cameras in the cornfields to take lightning pictures. It was our regular entertainment.
Well we stopped doing that after one day, watching a huge tornado sweep through our favorite cornfield, and sending all those corn cobs to heaven. Our camera gear never went back in the car so fast before or since.
But fun aside, Willis’s essay gives voice to one of the reasons why I detest the Kevin Trenberth et al global energy budget cartoon, with its 342 W/m^2 ho hum nothing ever happens static planet earth model.
So as I recall, the 390 W/m^2 number, corresponds to a black body Temperature of 288 K. Well you can all check that with your BB IR Applet
So taking that as a base number, we can take (342 / 390)^0.25 x 288 and come up with 278.7 kelvin, instead of 288.
So Trenberth’s magic number cannot get the planet up to beyond 4.5 deg. C no matter how long that steady state persists.
But noting Willis’s assertion that the sun always shines 24 hours per day straight down on the “subsolar” point, where it is always noon, and at a TSI of circa 1362 W/m^2; if that all survived the atmospheric transport, it could send the surface heading towards (1362 / 390)^0.25 x 288 K which is 394 K or about 121 deg. C
Luckily, even with CAVU morning weather, it seems that on the surface it is only a mere 1,000 W/m^2 so we have (1,000 / 390)^0.25 x 288 which is now a tolerable 364.4 K or 91.25 deg. C
Now that is more like something we can live with. In fact I do believe that some actual blacktop Temperatures of that order have indeed been measured.
So how does that grab you ?? Imagine that Willis’s thunderstorm regulator decided to take a vacation. If something wasn’t shutting off that solar blow torch each and every day, with processes that happen in as short as atto-seconds as far as we know, then we would indeed be cooking on planet earth.
Now in the dry arid tropical deserts of North Africa and the Middle East, then the daily afternoon surface Temperatures can get to around +60 deg. C or 333K. which corresponds to (333 / 288)^4 x 390, or 697 W/m^2 BB total radiant emittance or about 1.8 times Trenberth’s assumed value.
So look to those hot deserts for earth’s maxi cooling; not to the ice masses of Antarctica or Greenland, which are puny radiators.
So while Willis’s thunderheads are building during the day, the radiative cooling engine is also operating in top gear, to help keep planet earth livable.
You should bookmark this essay of Willis, and send it to all of your friends.
Maybe copy in Kevin Trenberth, and tell him that there is nothing in the entire universe, that can sense, observe, measure, evade, react to, warn against, or take any sort of action with regard to ANY average of ANYTHING !
Physics takes place instantly in the shortest time units we know how to measure or take data in, and in our models, we can explain things down to 10^-43 seconds or thereabouts. …(some people can; not me)…
Averages and other statistical paraphernalia, are somewhat akin to Origami.
If you take a suitable square table napkin, and you apply some 4,000 year old algorithm to that napkin, you can actually turn it into a frog, that can hop; as did an elderly Chinese lady who gave that frog to me last Sunday ,morning at a local MacDonalds restaurant. I now have it on my car passenger seat, to remind me, that there are all sorts of algorithms that can turn real weather data, into frogs, that lead you to believe things, that simply are not real.
I’m almost embarrassed to have to share the same land of birth, that gave us Kevin Trenberth.
g
Hey Willis,
Great article once again. Off the subject, it seems that plants have an adaptability which is most probably genetic in function. They adapt very quickly to changes in atmospheric co2 levels. This adaptation would indicate that plant life in the past has had to adjust itself to changes in various levels of co2, which means that, most probably, co2 has been at lower and higher levels of co2 in the past, which, it seems, has been hard to determine. If plants have the ability to adapt to higher levels of co2 in the atmosphere and also have the ability to decrease water consumption by decreasing the exposure to the atmosphere, it would indicate that there has been higher levels of co2 in the atmosphere and probably at many times in the past. Adaptation comes from exposure to variation in climate.
Just a thought.
R.
Well, of course plants have the ability to adapt to higher levels of CO2. They came into existence when CO2 levels were 10 times higher than they are today. Plants like CO2. This is what they photosynthesise to make food. And that food is also the base of our own food chain. Without the Plants and the CO2 all life on this planet would perish.
From a geological perspective, CO2 levels today are at an all-time low.
http://www.catholica.com.au/misc/images2013/AJB-Global-Temp-Atmospheric-CO2-over-Geologic-Time_640x513.gif
MikeB.
See http://WWW.geocraft.com/WVFossils/stomata.html. Plant respiration adjusts to levels of co2 and proves atmospheric co2 levels have been much higher and lower during more recent times…A few million years rather than hundreds of million years.
This helps argue against the theories that co2 levels have remained at or near 280 ppm over the last few million years. Per plant fossil study, the atmospheric volume of co2 has been much higher than current levels within leat few million years and life survived.
R
The drop in temperature of the North Atlantic is already visible in Greenland.
http://www.dmi.dk/uploads/tx_dmidatastore/webservice/e/n/i/b/m/Melt_combine.png
Left: Maps showing areas where melting has taken place within the last two days. Right: The percentage of the total area of the ice where the melting occurred from January 1 until today (in blue). For comparison the average for the period 1990-2011 is shown in the dark grey curve. The variation from year to year for each of the days during the melt season are shown as the gray shaded area.
The increase in ionization of air over the polar circle increases albedo.
http://sol.spacenvironment.net/raps_ops/current_files/rtimg/dose.15km.png
And in the fact that I am still wearing my winter woolies in the UK midlands.
Nice work Willis. It looks like a lot of cold outliers in fig5. What % of the data are they? It suggests a quite assymetric distribution of temperatures.
This is good stuff Willis. Climate model “parameters” for all these processes are largely guesswork and make a nonsense of all the claims about them being built on basic, known physical laws. Here you have something concrete.
.
Morning cooling caused by afternoon clouds ? I don’t think that came out quite the way you intended. 😉
The ERBE reflected SW needs to account for differing flyover times at each location. It has a near polar orbit with a period of about 93 min. ( it does about 15 orbits per day ) . This calculation requires an estimation of cloud cover. For some obscure reason they decided to assume ( as one does ) constant meteorology through out the day. The tropical equivalent of a spherical cow.
This wonderful pattern is an alias of the daily cycle reflected out to 36 days. ( The total orbit repeat is 72 days but each orbit passes equator twice : up and down , so the tropical pattern is 36d. ) In fact this is two 72d cycles superimposed. Each has a 12h bump and a 12h flat: night time: no reflected SW. So the bump pattern close to 6h-18h cycle.
Now it looks like we can see the daily anomaly profile with the mid-day dip reflected in this data.
By making the spurious assumption of constant cloud cover in processing the actual SW measurements they have created a record of the averaged daily cloud cover.
Another interesting feature is the 1991 red line. It sets out from the pack in the latter half of 1991 and shows the effects of Mt Pinatubo.
Checking back on my notes, this alias should be a good indication of the daily SW albedo changes. The calculation is done taking into account zenith angle at flyover time and assuming constant SW meteo throughout the day. So an increase in reflected SW should be a reasonably good indication of changes in SW albedo.
What surprises me is the fact that the diurnal temperature cycle is fine tuned to plus or minus 0.4 deg C (Anomalies fig. 4) while the average temperature can vary from 23 to 28 deg C (Averages fig. 2) – without much influence on the diurnal pattern.
In other words: why do the same cloud patterns form in the eastern pacific around 23 deg C and in the western pacific around 28 deg C?
Should’t we expect thunderstorms already at sunrise near australia?
I understand Willis’ argument regarding the existence of a governor as being dependent on absolute temperature and not relative temperature. What am I missing?
Apparently, temperature is only half of the cause of clouds. Try biological dust for the other half of cloud formation.
…or Influence of Cosmic Rays on Earth’s Climate by Henrik Svensmark shows another contributor to cloud formation. CERN’s CLOUD project discovered another….
dependent on absolute temperature
============
that cannot be the whole story, because warm air rises relative to cold air, not relative to absolute temperature.
what changes however is the amount of moisture in the rising air, which is a function of absolute temperature.
so while you get rising air during the day regardless, the warmer the underlying ocean the greater the chance of thunderstorms.
so while you get rising air during the day regardless, the warmer the underlying ocean the greater the chance of thunderstorms.
============
Of course. I just don’t remember Willis talking much about the amount of moisture in the rising air with respect to his proposed governor mechanism. As far as I understand it it’s an absolute temperature threshold that supposedly triggers the onset times of the emergent phenomena – clouds, thunderstorms, squall lines – and not just a temperature difference that results in a variation of the amount of moisture rising. I’m afraid figure 2 is not supporting his idea. From Willis’ earlier posts I would have expected rather different diurnal temp profiles at different longitudes, converging at the onset times of cloud and thunderstorm formation.
Fascinating…
I hope that is clear enough. I’m familiar with this so may be is clear to me and not others.
Behind the bumps there is double dip annual cycle of the tropics. There is a regular 2-3-2-3 monthly pattern in the deeper dips. I do not know where that comes from. Very likely also an alias.
This data was further processed into circa 30 day monthly averages which produces another alias ! The 36d and 30d periods combine to produce an alias of about 6 months ( 198 days IIRC ). Since the annual cycle is two six month bumps this aliased-aliased daily signal was a significant distortion of the annual cycle. This was picked up by Kevin Trenberth on one of his better days.
This is a beautiful example what aliasing does and why it is essential to do proper anti-alias filtering before resampling data.
Had they filter out the 36 day cycle with a well behaved low pass filter they would have got a reliable monthly resampling.
Professor Humlum discusses the apparent relationship between tropical cloud cover and global temperature at his climate4you site:
http://climate4you.com/images/HadCRUT3 and TropicalCloudCoverISCCP.gif
http://climate4you.com/images/HadCRUT3 and TropicalCloudCoverHIGH-MEDIUM-LOW ISCCP.gif
http://www.climate4you.com/images/HadCRUT3%20and%20TropicalCloudCoverISCCP.gif
Oh no, is it just me or do I detect a distinct “pause” in both of those temperature plots? And by a professor of all, tsk tsk. The Obama administration’s data scrubbers should be notified for an adjustment session immediately.
No, it’s just you Wayne, there is only one temperature plot.
Here’s another pause: TLS:
Looks like the only thing that is not pausing is Karl et al’s latest attempt at gerry-rigging that surface record.
The above graph: the data ends in 2011 and 2009. Is there an updated graph? I could be wrong but doesn’t the graph show a negative cloud forcing from 1983 to 1997 then the “pause”?
yes indeed, I was a bit too brief. The stratosphere works the other way around: volacanoes initially cause warming , not cooling.
More detailed explanation here and updated graph:
https://climategrog.wordpress.com/?attachment_id=902
In figure 3, the late night reduction of cooling corsponds to a rise in rel humidity, there a big change in the cooling rate in the middle of the night in figure 4, does it too corspond to high rel humidity (temp dropping down to near dew point )?
In figure 3, the late night reduction of cooling corsponds to a rise in rel humidity, there a big change in the cooling rate in the middle of the night in figure 4, does it too corspond to high rel humidity (temp dropping down to near dew point )?
Dew points do tend to put a floor on temperature change. Only really dry air can have large downward temperature swings.
It continues to cool until sunrise, just at a lower rate.
Hi Willis, there’s something here I don’t quite understand.
Looking at figure 4 you see approximately the same temperature profile for each of the buoy lines, with a clear different between the warmer and cooler records.
But if the mid-morning “kink” is an emergent phenomenon triggered by temperature, why does the same thing happen at below 24C in some regions but above 28C in others? Why are thunderstorms triggered at approx 4pm despite the absolute temps being several degrees apart?
I would expect the cooler regions to continue increasing to well after 4pm since they are still many degrees cooler than the regions where the storms started at 28C+ ?
Not Absolute Temp, but maybe Temperature differential?
Don’t see how that would work – a kettle boils at 100C whether in a hot or a cold room.
Maybe the length of time it takes a thunderstorm to develop is unrelated to the surface temperature. After all, water vapor, in large quantities, has to meander up to >30,000ft.
I had the good fortune to spend some three years in Singapore long ago, well before people worried about global temperatures. I do remember the nights didn’t offer much relief from the days and if you complained the cry would come back “It’s not the heat. It’s the humidity.” The afternoon rain showers were so normal they got no comment and could be avoided by walking on the other side of the street. If you were unfortunate and it was raining on both sides there was always a street vendor who would sell you a varnished paper umbrella for a dollar. If you didn’t have a dollar, no problem, the rain was pleasantly warm and never lasted long.
Seems like a reasonable explanation of limiting maximum temperatures. However, the global warming doom mongers are all about mean temperatures.
My layman’s experience with cloud cover is generally, cooler in the day warmer at night. That generally goes for air humidity too. This leads me to suspect that the so called greenhouse gasses are more a function of basic two way insulation than “back radiation”. I suspect if one adjusts for changing atmospheric pressure, the difference in mean temperature at any particular location checked over the years on the same date, with different weather conditions, will show very little variation, regardless of the massive swings in overhead “greenhouse” water vapour or clouds.
I will leave it for a scientist with funding to check this out properly. Don’t forget to adjust for the differing barometric pressure readings!
Mind you, thinking about this further, clear non humid days followed by a cloudy night would produce the opposite to the reverse situation. Then there is wind transferring heat horrizontally to consider. Still, I’m sure a budding scientist could find ways to negate these other variables…. Given enough funding 😀
With you there wickedwenchfan. I have noticed many times over the years how during a clear sunny and low humidity day temperature climbs. With no change in conditions temperature drops quite sharply after sunset. If a bank of low cloud moves over, temperature starts to climb, but never exceeds daytime maximum. My layman interpretation of these events is ‘radiation’ from the bottom of the cloud layer is reducing the rate of radiative cooling of the surface allowing the more deeply embedded heat energy to warm the air above. But as you say, we will have to leave this to the budding scientists if there are any.
Richard111 commented on The Daily Albedo Cycle.
in response to wickedwenchfan:
I’ve spent the last 5 or 6 years following this.
65 some million Surface station records from 1950 show slightly more cooling at night than warming the prior day.
Then and IR thermometer when pointed to a clear sky when the humidity is low is quite cold, 80F to over 100F colder than the ground. Cloud bottoms can be as warm as 20F or 30F colder than the surface, thin high clouds are 50F-60F colder than the ground. On hot high humidity days, clear sky is much warmer 50F-60F colder than the ground.
I started doing astrophotography, and noticed how quickly it cooled once the sun went down, got me thinking, got me to get some data and look at it.
In the tropics, the clouds tend to dissipate right after the thunder squalls. You get these really tremendous late afternoon squalls followed by clear blue sunsets. Great viewing of the constellations unless a marine layer haze sets in. So the clouds have no night time impact. This is one of the many asymmetrical phenomena that occur in climate that do not make it into the numerical models.
wwf
I have been plotting the barometric pressure since December 2014 on a daily basis. I am using a weather station that you can find almost anywhere. I plot each change of the digital digits which is .01 inch of mercury. I gave up trying to use time as a cadence because sometimes the pressure does not change for several hours. I have established a set of “opinion” plots that represent the shape of the wave itself. The one I am using presently is a “low opinion” because the barometric pressure is at a low state and has remained constant since the solar activity has basically dissappeared from its interferrence of the diurnal shape.
I recently found that between high noon and eight pm it doesn’t change its shape (during the period using the opinion as a reference). The AM portion can be referenced using the high noon point as a reference and aligning backwards until it fits the pattern. If the midnight point is used, nothing correlates.
Like you, I am a layman looking for data. I gave up on the published data and started using my Christmas present (to myself). I suggest you do the same. I would love to start comparing the daily cycle as it happens with other people in different parts of the world to see if the cycle looks the same. I have confirmed many times this ESR cycle. My ranch name El Starvo Rancho.
If you do attempt this, I could lead you through the process of seeing the data.
LeeO
Obscurity is personal security.
Besides cumulus clouds the other thing that starts in the morning is local wind driven waves, which will also help to cool the surface by mixing the surface heat with deeper cooler water.
Willis, Willis, Willis. You poor naive fool you. This sort of stuff is way, way too close to actual climate mechanisms to be considered climate science. I mean if the models don’t do this sort of mechanism then it can’t be real!
Sarc off.
What a refreshing articulation of what is probably a critical mechanism in the actual global climate. The point you make about the small size of the material cloud formations is probably the very reason the ‘models’ don’t bother with them.
Willis, with respect to Karl et.al I tried to find a difference between the TAO-SST data and the HadSST3 -SST in the same area of Pacific… Without great success, the trend between 1992 and April 2015 is very, very similar: almost zero. If Karl et.al are right there should be a difference because the buoys have a negative offset?
Excellent!
Willis, here is another piece of the puzzle.
When the clouds form they block the suns shortwave radiation which is absorbed into the ocean, but they increase the long wave radiation which is not absorbed by the ocean.
What the long wave radiation does is cause evaporation at the surface which causes the surface and the air to cool. That is why you get the temperature dip during the day.
As the atmosphere warms, the cloud bases move higher. Would be interesting to see how much of an impact this has if any.
Let’s see clouds over the North Atlantic.
http://www.sat24.com/
Hey Willis,
My father was a meteorologist during WWII in the South Pacific, stationed at airfields on several islands. This phenomenon you describe was very familiar to him — so much so that he could look up at the sky in the early morning and predict within 15 minutes when it was going to rain that day just by how the clouds were starting to build up. The cook would always ask him when to serve lunch so that it wouldn’t rain on the food!
See the book, Weather Knight http://bit.ly/1dt5Swt
Reinforcement for something I had noted myself, and thought all the while Willis was discoursing. The normal summer pattern of South Florida weather – when there is not some system affecting it – was SO regular you could essentially set your clock by it. Early mornings would be clear, sometimes hazy but few real clouds; mid to late morning they built; and if you didn’t hear thunder by mid-afternoon it was very unusual. I see the exact same pattern in what Willis is describing, and the same for your father’s experience. I also noted the cooling effect of nature’s “air conditioners” through that process, as well. Just one vast heat pump …
I worked as a geologist on Bougainville Island in the later 1960’s and noticed the predictability of afternoon storms even though mornings started with clear skies.
I t always amazed me how little weight was given to albedo . . . . I wonder when the schmodellers will get around to factoring in this variable (high altitude air traffic / contrail impacts): http://markosun.files.wordpress.com/2014/01/land5-global-air-traffic-routes.jpg?w=1000&h=666
Well, contrails would only make a difference if they occurred and spread widely and there was no lower cloud; ie not very often.
Nasa’s models thought differently.
http://www.nasa.gov/centers/langley/news/releases/2004/04-140.html
After 9/11 they claimed it wasn’t anywhere near as large, but then what does that say about NASA’s GCM?
Some time back Willis E wrote a post discussing the natural stability of our atmosphere. The gist was that our atmosphere returns to equilibrium after perturbations from volcanic eruption changed, temporarily, the climate. Then Anthony had a meeting with Bill McKibben where Mckibben said our atmosphere was “finely tuned”. I took that to mean that any perturbations would disrupt this “tuning” and cause instability. Baloney!
The Earth’s atmosphere is a stable system.
There are no tipping points for temperature run-away. What Mckibben calls fine tuning, I call stability.
It would be interesting to view rainfall patterns and amounts over the last 40 years on land throughout the pacific at the equator. Wouldn’t they see increased rainfall if increased clouds were a negative CO2 forcing?
@ Willis E
Great commentary, enjoyed reading it this morning (Tuesday, 6-09-15). And concerning this statement of yours, to wit”
If I replace the word “tropical” with “temperate” (I live in central WV), that is exactly what I experienced late yesterday afternoon.
The air temperature in my local area was hovering around 90 F and the humidity was increasing when kinda suddenly like “WHOOSH”, …. in rolled a thunderstorm with high winds and massive hurricane-like rainfall …. which only lasted for 15 minutes or so. The wife’s daughter who lives about 25 miles SE of us ….. called to tell us “they heard the thunder but didn’t get any wind or rainfall”.
Cheers
Willis
I notice you are using time zones to separate the graphs. For a year of plotting temperatures from different locations here in north america, I was having problems with correlations. My sniff test was telling me something was wrong so to give myself a second source of data, I mounted a solar cell on my roof connected to a volt meter. Trying to get a clear picture of what it was representing took awhile. Because of clouds, the readings were very irratic, but managed to have quite a few days without clouds that allowed me to see what what was going on.
Just like I see in your charts, the voltage peaks at about 9 am and then dropped and flattened out for the rest of the day. I assumed it was wrong because of the common sense approach, it should peak at high noon.
While I was also plotting temperature as a comparison, noticed it peaked around 2 to 3 pm (just like your second peak). Again, this made no sense why nothing correlated. When I added a barometer to the mix, It gave me another pattern that appeared to be a floating di-urnal that appeared to pass through the same point at high noon.
So I began using the solar noon as my reference to see if it would clear up the correlation problem. After wrestling with plotting for a long time, I almost gave up and switch my research to killing fire ants…
But, in January this year, things started changing. I was able to get a clear voltage plot that showed the 9am peak. It wasn’t until the middle of March that the pressure waves started clearing up. That is when I began using GOES data comparisons to put some sense into the pressure waves. I found correlation of the noise on the pressure wave to incoming solar activity. That has now cleared up, the solar wind became my next topic to study since everything else had dissappeared.
Just recently, 6/3/15 at 1700gmt, there was a sharp spike in the solar wind that lasted about 2 hours of which only abut 10 minutes it exceeded 500 and peaked at 1136 and dropped instantly back to the 300 mark. It made the barometric pressure rise about .03″hg.
And today the K wing showes two periods in the red. The wind is now rising starting sharply rising at midnight. As I wait for data to catch up I read your blog on WUWT. I believe this exercise is way beyond my basic knowledge of how things work.
But, I believe that the voltage peak at 9am is real. That going through the atmosphere almost horrizonal to the earth is the way light travels through the layers. And the 3pm temperature peaks are because the warming of the sun does not reach earth at the same time but 2 to 3 hours later.
This time factor I have been seeing when there has been a reported solar flare (they see the light) and when I see it on the barometer. Ive timed it to be 2hr 40minutes.
So maybe an adjustment to the recorded times should be set to the sun daily cycle at high noon instead of the normal time zones.
If I had a way to send pictures of my plots, it would be easier to explain what I see.
LeeO
I guess this string will work. (I would never use thread to tie two tin cans together it is just too weak when we streach it to talk) Iphones work alot better.
Update
Willis, the storm is continuing this morning with wind around 600. We had a M1flare at 0855gmt and coincidently the satelite stopped sending data for 13 minutes. The time for transit time to the satelite from the sun is 2hr35min. Previously I estimated the time for flares to reach earth 2hr40minutes. Because the sat is between us and it (about 30min transit from goes to us) totals 3hr10min. Not sure yet if this delay varies but I expect it does.
LeeO
w.
It is 10:15 and my voltmeter on my second solar panel overloaded and had to change the scale. Looks like its gonna be a hot day.
lo
Lee, the voltage across silicon solar cells is not a good measure of incoming insolation energy. These cells are current sources, not voltage sources (I’m sure someone here can do the whole physics explanation if you like..:-) If you want to measure insolation, you will need to measure total power being generated, not just voltage.
Hartley
Hartley
My voltmeter is not terminated. I am only using it as a TOOL to watch solar energy. Physics seems to be about a Solar panel that is being used as a charger.
lo
Lee, the way a silicon solar panel works, the open-circuit voltage will rise with increasing solar flux until the maximum voltage of the panel is reached. You will then see little or no additional voltage rise with additional flux, though MUCH more power would be available if you were drawing current from it. What you reported – that voltage rises until about 0900, then shows little change until evening is exactly what we would expect. If you want to measure approximate solar flux with a silicon solar cell, you have to measure the power (current X voltage), not just the voltage.
Hartley
But, I would like to know what it is measuring. Maybe the frequency that I assume is sublight
No I said that it rises (to a peak) about 9am. Then drops back down where it flattens out until the evening when the sun goes down.
Lee, I’m not sure, never having closely examined the open-circuit behavior of solar cells, but my suspicion is that your panel is heating up, which would reduce the voltage (slightly), beginning after the 9 am peak you report.
Hartley
I have bought six 12v arrays and set them up to see what was the most sensitive. I use it to record the reflections from the Moon. I have just glanced at them but looking back at midnight on a non-moon nite it measures .2mv. That is really dark.. During lightning storms it records the brightness of the flashes. I can’t wait to have time to plot them!
The peak voltage for the Sun around 9am is around 17volts. On 3/28 and 3/29 it was peaking at 8:30am at 17.12v. My last check on 5/1-2 showed it peaking at 7:15am. This makes it take on a longer “bite” pattern that slowly drifts down until noon (16v) when it rises back up to 16.25 at 5pm and drops gradually drops off at dusk.
No, dont think they are heating up, just doing their job.
lo
[What latitude is your array? What total area and how are they oriented or controlled? .mod]
Mod,
I am using a solar charger used in feeders on ranches. Like I said, its just a tool. I plot the readings and compare to various sensors I use. All graphic comparisons.
Hartley,
I am not looking for insolation energy. Only a signal like a phonograph needle, a barometer, thermometer, and all the usual tools needed to monitor the atmosphere here in the hill country of Texas. I have yet to see where these tools are being used so I am doing it. The problems with collection, saving, and plotting so much data has been worked out. But, I guess no one wants to see the results. At least no questions as to what they are showing me.
Mod
For instance, on 6/15/15 0100gmt, a M2 solar flare was detected on the sun. It was located on the west limb. I received the resulting change of the diurnal cycle 2-1/2 hours later using my barometer. How could that be? It was beyond geo effective positions. The same thing happens on the ones we see on the east limb. It seems to me that the light and the uv component is being reflected by the magnetic bubble above the “hole” as if it was a mirror….
Hartley
I have other devices that are set up in a mini-studio
You realize that this “string” is obscure.
BTW, I saw some communicating going on couple of nights ago in an obscure location like this…..hackers….this is their tool.
While another blog is going on and everybody is following an encounter, they are doing their thing. I cannot find it now so guess it was deleted….? mod delete this…
4:30 PM, like clockwork, a downpour and thunder.
Bair Polaire June 9, 2015 at 12:56 am
The answer in my opinion is that temperature thresholds are thresholds in ∆T, a temperature difference. In this case the relevant temperature difference is between the ground and the lower atmosphere.
We can verify that these phenomena are triggered by ∆T by looking at a closely related phenomenon, dust devils. You usually see them in the desert … but you also find them in the snow. They, like cumulus clouds and thunderstorms, are driven by the difference in temperature between the surface and aloft.
Now, the puzzle to me is why the ∆T between the atmosphere and the ground would be such that all across the temperature range from East to West Pacific, the ∆T gets strong enough at about the same time of day (late morning) to drive the emergence of the cumulus clouds regardless of the ground temperature.
w.
http://en.wikipedia.org/wiki/Lifted_index
This suggests however that you have more work to do before you can say this mechanism will regulate climate. The basic problem is that if temperature differences are the trigger then uniformly raising all temperatures will not trigger earlier thunderstorms.
What I take away from this is the massive amounts of energy involved in the daily temperature regulation cycle and the huge size of the effect caused by clouds and changes in albedo throughout the day. The posited effect from CO2 in the global warming hypothesis is so miniscule by comparison that only a very subtle and tiny change in the daily cycle would be needed to completely overwhelm it.
As I see it your main problem is going to be finding such a subtle and tiny effect in the midst of these massive chaotic daily exchanges of energy. You may need to settle for simply pointing out that worrying about a couple of Watts per square metre from CO2 while all this is going on is rather like worrying about the draft from a fan in the middle of a hurricane.
Ian H June 9, 2015 at 3:35 pm
Thanks, Ian, but that’s not true at all. Look again at Figure 4. The warmer the buoy location, the greater the response. This is visible in a variety of other plots as well.
w.
The temperature differences are the “trigger” …… but the H2O vapor (humidity) ppm is the “powder charge”.
Ahah – I get you now. The greater the response but not the earlier the response. So what you are saying is that timing is triggered by temperature differences, but the amplitude of the response is determined by absolute temperature. Gotcha.
That is a modification of the model as you first presented it where you suggested variations in the time of initiation as being the main controlling mechanism.
Ian H June 15, 2015 at 3:11 pm
Sorry for my lack of clarity, I haven’t modified the model. The control is done by varying the time of emergence, but the strength of the time-varying emergent phenomena seems to be stronger at higher average underlying temperature.
w.
Thank you for elaborating. I understand that thresholds for emergent phenomena can be triggered by ∆T – but with regard to a governor mechanism I thought (and still think) absolute temperature being relevant, at least for the strength of the response.
It’s even more puzzling to me that not only the onset times for the temperature changes (and subsequent emergent phenomena) but also the diurnal temperature patterns are so similar. What else goes in sync with the slowly increasing SST from East to West: cloud height, air temperature at certain pressure levels, air pressure near the surface, humidity, biogenic atmospheric ice nuclei,…?
Where is the leeway coming from…?
b.
Great post as always. Don’t take this as criticism, just a (maybe) different viewpoint.
Small bone to pick. You say:
The regulation of the temperature will be greater up at the warm end of the scale than down at the cool end. This is because the emergent phenomena act to reduce peak temperatures.
My ‘bone’ is ‘act to.’ They don’t act to (ie intention), they merely have the effect of… semantics but also reflects how one thinks about it. It’s just a reproducible response by air/water/water vapor to temps.
Related: You also said early on ‘This prevents the surface temperature from overheating.’ What the heck is ‘overheating’? The earth doesn’t have a temperature that is ‘normal’ or ‘supposed’ to be. Again, it’s just water vapor acting as water vapor acts
Again, I agree with nearly everything you say about the system; it limits temperatures by feedback. I see it as natural responses to threshhold events. In the west pacific you start at higher T (higher humidity?), closer to a threshhold to form clouds, so this system of cloud formation snap into gear faster than it does in the east where it’s cooler, clouds probably form less fast. Another possibility it seems is that the eastern feedback is less consistently at the same time of day (is it some days a sharp effect like the west and some days not at all so the average looks different?). Can you ‘predict’ by the starting temp of the day (or the water) how strong that 9am dip is?
How to test this? is there seasonality to the temps at the equator buoys? Do individual cool days (or cool seasons) in the west look like the same temperature days/seasons in the east?
Thanks again, yet another enjoyable and thought-provoking post.
ME
It would be cool to quantify the ‘dip’ T9-T12 is a nearly perfect measure it seems, and see what that correlates to (seasonally, daily).
Thanks, Willis. It is good to see your Thermostat Hypothesis is advancing.
“Planet Ocean” (Earth) has emergent phenomena that prevent it from frying under the Sun. On the other hand, humans, seem to have only reason, and it is a scarce commodity, have we gone past “Peak Reason”?
Dear Mr. Eschenbach,
Can I talk you into using a code-sharing service? I’m not a big fan of Github, but it is the most popular. Alternatives off the top of my head are Bitbucket and Gitorious.
The immediate advantage to you is that you could crowd-source your code cleanup. I could “fork” your repository and send you pull requests with fixes. You can merge the fixes you approve of, and reject the ones you don’t with or without comment.
I would be happy to help with setup.
Willis;
When you say:
All of the locations receive exactly, precisely, the same amount of top-of-atmosphere solar energy every single day.
do you mean within the calendar day, or for every day of the year? If the later, I’m confused.
Sorry for the lack of clarity. I meant that on any given day the locations receive exactly the same amount of sunlight. It changes from day to day, but they all get the same amount whatever it might be.
w.
Willis, I don’t know whether you missed it or just weren’t interested because there’s not code supplied 😉
I think the graph I supplied provided empirical evidence of what you have been saying for the last few years.
http://wattsupwiththat.com/2015/06/08/the-daily-albedo-cycle/#comment-1958222
Extracting the ERBE data at this level is a bit complicated but I can provide details if you are interested.
The earth is always trying to reach equilibrium with all of its thermodynamic processes. As a consequence of an infinite number of variables, your never going to predict its weather or climate. All you can hope to do is call out trends, based upon limited information, or data and previous history ( undoctored of course ). For my $$$ Weather Bell is best, followed by the Farmer’s Almanac.
That’s a few bold statements. I would love to know what the Earth is trying to achieve.
What’s she doing? Nothing much, just messing with our heads. Sort of things deities find amusing.
Reblogged this on Climate Collections and commented:
Fascinating analysis. Consistent with my tropical met training. Saturated boundary layer at dawn; weak inversion; AM insolation/heating overturns the boundary layer mixing drier/cooler air from aloft; random CU form; low/medium sun angle reflects off sides of CU casting medium/long shadows; late morning sun angle increases reducing CU shadow footprint; surface heating increases; random CU organize into TCU; max insolation/heating in early afternoon; CB and rainfall mid-late afternoon; surface insolation/heating reduced by CB-induced CS footprint; surface also cooled by rainfall and subsidence/downdraft of cooler drier air aloft. Rinse, repeat.
Willis
Compliments on your graphs and results.
You show the temperatures increase westwards along the equator. (“The buoys I used stretch from 95°W (buoy just to the left of the “E” in “Equator”) to 165°E (on the Equator northeast of Australia). Conveniently, the average temperature increases steadily along the line.”)
Similarly your graph of daily temperatures shows corresponding increasing trends about 9:00 hours. (“To me, the “dip” in the morning records is the clear sign of the phenomenon I described in my last post—the emergence of the cumulus clouds starting in mid-to-late morning.”)
However there is the inverse trend about 17:00 hours. (“The later reduction of the peak afternoon temperature values is due not to increased albedo but to the emergence of afternoon thunderstorms.”)
The ocean temperature provides the integrated effect of net heat heating. E.g., See Shaviv’s Blog “The Oceans as a Calorimeter.”
May I suggest plotting the derivative of temperature vs time, and the difference between non-cloudy integrated insolation (such as your land temperature Fig. 3) and the ocean temperature (Fig. 4). I think that should be insightful when compared against the cloud cover (albedo) and consequent change in net heating.
Best regards, David
Willis
Your hypothesis seems compelling – how much does it have in common with the “Iris hypothesis” of Richard Lindzen?
http://www-eaps.mit.edu/faculty/lindzen/adinfriris.pdf
Could your work be a refinement of the Iris hypothesis? Lindzen saw a role for cirrus cloud in relation to cumulus. From Lindzen’s abstract:
Motivated by the observed relation between cloudiness (above the trade wind boundary layer) and high
humidity, cloud data for the eastern part of the western Pacific from the Japanese Geostationary Meteorological Satellite-5 (which provides high spatial and temporal resolution) have been analyzed, and it has been found that the area of cirrus cloud coverage normalized by a measure of the area of cumulus coverage decreases about 22% per degree Celsius increase in the surface temperature of the cloudy region. A number of possible interpretations of this result are examined and a plausible one is found to be that cirrus detrainment from cumulus convection diminishes with increasing temperature. The implications of such an effect for climate are examined using a simple two-dimensional radiative–convective model. The calculations show that such a change in the Tropics could lead to a negative feedback in the global climate, with a feedback factor of about -1.1, which if correct, would more than cancel all the positive feedbacks in the more sensitive current climate models.
What are your thoughts on cirrus cloud?
“Could your work be a refinement of the Iris hypothesis? ”
Not in my opinion. I wouldn’t use the word “refinement”. Perhaps “paling in comparison” might be a better phrase. This post reads like Lindzen never existed.
What we see here is a depiction of the average diurnal cycle not of albedo, but of surface temperature based upon TAO buoy data. The former would require satellite measurements of radiance. Meanwhile, the general characteristics of the latter and the underlying physical mechanisms have been well-known since at least WWII (see Hamilton & Archbold, 1945), and the particular features of TAO data have been studied in depth by various authors for over a decade. Sadler and Schroll (1997) present a reasonable analytic model for the diurnal cycle. What’s new in Willis’ work is the terminology of “emergent phenomena” and the splendid graphics.
George E. Smith:
Avoidance of aliasing is why WMO calls for 4 daily observations of temperature at periodic standard times. The question of using Tmax and Tmin to obtain the mid-range temperature (often mistakenly called the daily mean) is quite separate from that of aliasing, because the extremal times are NOT periodically spaced.
Well samples of continuous functions, don’t have to be periodically spaced; they merely have to occur at least once in any half cycle of the highest frequency component of the band limited continuous function. And they need to occur at least once in ever full cycle of that frequency in order for an extracted “average” to not have aliasing errors.
Willis’s diurnal Temperature plots clearly go beyond a second harmonic frequency component limit, so even four samples per day, is not above reproach.
I’m not a fan of combining different data taken at different times and different places, and trying to somehow claim that you are adding information to just what the raw data records.
When they can synchronize their instrumentation so that all spatial data samples are taken simultaneously, at all spatial locations, then they might start to have some idea of what is going on.
Physical thermal processes, such as “heat” transport or propagation, depend on what Temperature difference there is at a specific moment in that region, so measuring the Temperature of two different places at two different times tells you nothing about what thermal processes will happen in that region. You are just recording anecdotal events, that are unrelated to each other.
g
Aliasing is an artifact EXCLUSIVELY of periodically sampled continuous-time signals. Shannon’s Sampling Theorem and band-limited interpolation depend critically upon the STRICT periodicity of the sampling. Granted, spectrum analysis of actual (not just averages of diurnal data) much-more-finely-sampled records typically show significant spectral content only at the fundamental (24hrs) and the second and fourth harmonics. While the WMO standard is indeed not beyond all reproach, the fourth-harmonic content nevertheless pales in relation to the lower-frequency content. It serves the practical function of providing SYNOPTIC (simultaneous) data, as well as the best basis available for determining the true daily mean temperature, rather than the daily mid-range value.
Unfortunately, the mid-range temperature is all we have historically throughout the English-speaking world when it comes to century-long records. I’ve never been a fan of a variety of ad hoc methods to bring the mid-range value into closer conformity with the true daily mean, upon which the monthly “average” temperature is based. Your stated criteria for avoiding “aliasing” in NON-periodically sampled series are patently off the mark in every respect.
“””””…..
1sky1
June 10, 2015 at 3:29 pm
Aliasing is an artifact EXCLUSIVELY of periodically sampled continuous-time signals. …..”””””
Well that would be useful to know for those people who put weather stations, to sample weather parameters, at totally random locations on the planet.
Obviously their strategy, being anything but periodic in space (rather than time) must be quite immune to aliasing noise,
This is wonderful new knowledge that you give us, that aliasing noise occurs only in time sampled data systems; well according to Shannon’s Sampling Theorem, you say that is.
Also you might point out to Tektronix, that they shouldn’t be selling sampling oscilloscopes, that use random sampling, to achieve results that can’t otherwise be obtained without difficulty.
I believe they have been doing that since I was working there in the early 1960s.
I’ll have to point out the error to some of my old colleagues when we next cross paths.
In any case, your new information explains why Dr. Mann, was able to succeed with his sampling of just a single Charlie Brown Christmas tree on the Yamal peninsula.
My library text books on sampled data systems, seem to assert that sampling works with ANY continuous function of any variable, or sometimes combination of variables.
So what is the point of spatially sampling weather data, if “Shannon’s sampling theorem” is not applicable to such sampling.
Sampling, and reconstruction from such samples, is a purely mathematical construct, and works even with no linkage at all to any physical system, so if I replace (t) for time, with (s) for space, or (lambda) for wavelength the mathematics derives exactly the same result. so sampling is not “exclusively” restricted to continuous time functions.
But evidently, people who are doing that are unaware of your new information on the subject.
g
Well, George, the very fact that you think that discrete-time sampling produces “aliasing noise” reveals a fundamental miscomprehension of what aliasing really means. As the name implies, it refers to the mathematical artifact of high-frequency sinusoids above the Nyquist frequency (N = 1/(2 delta t)) appearing as the frequency alias of a baseband frequency due to under-sampling with a FIXED sampling rate delta t. It is not the same as signal distortion or noise! For any baseband frequency f, the potential alias frequencies are specified by 2kN +/- f, for all integer k. You’ll find this explicated in any competent introductory text on discrete time systems (e.g., Freeman, 1965).
No doubt, t need not be the time variable; it can be any variable which supports a continuous process. Weather stations are, of course, NOT distributed on any spatially periodic grid, but their measurements, aside from Tmax and Tmin thermometers, are are all sampled PERIODICALLY in time, according to the WMO standard. BTW, the lack of a periodic station grid is what makes BEST’s resort to global kriging wholly inadequate, because there is no spatially-periodic data for estimating the spatial covariance function or its spatial stationarity, aka homogeneity.
Hope this helps.
Not convinced Willis. Take the 165 E bouy, do a temperature plot for days when there is little or no cloud and you still get the rapid rise from 6.00 am to about 8.00 am then the dip around midday followed by a slight afternoon rise. As the buoy also measures SW radiation averaged over 2 minutes it is easy to see when a day has little cloud.
Not sure what is going on but the diurnal temperature difference isn’t much 2m above the ocean.
I do think your hypothesis has merit over larger areas of warm ocean forming convective cloud over longer time periods.
Can’t see your objection. What happens one cm above the surface Temperature wise, is as little concern as what happens 2m above the surface.
It is the very surface itself (couple of molecule layers) that determines the thermal (BB like) radiant emittance, and also the evaporation with its latent heat content, and also the conduction from the surface to the atmosphere.
The atmosphere is such a poor thermal spectrum radiator, compared to the ocean surface or the land, that the Temperature fluctuations of the lower atmosphere, are only of interest to the local thermal (heat related) processes.
The surface drives the atmosphere; the atmosphere is not driving the surface.
g
“To refresh your memory, my hypothesis….”
So Lindzen’s work is now your hypothesis? Just because you don’t read the scholarly works doesn’t mean you are the first to come up with something.
From Lindzen’s MIT page, “His research involves studies of the role of the tropics in mid-latitude weather and global heat transport, the moisture budget and its role in global change,…..”
So go read his research. Like this for instance: D. Stevens, R.S. Lindzen and L. Shapiro (1977). A new model of tropical waves incorporating momentum mixing by cumulus convection. Dyn. Atmos. and Oc., 1, 365-425. [pdf]
Or maybe this, R.S. Lindzen and S. Nigam (1987). On the role of sea surface temperature gradients in forcing low level winds and convergence in the tropics. J. Atmos. Sci., 44, 2418-2436. [pdf]
No, Lindzen’s work is nothing like my hypothesis, and the fact that you can’t seem to tell the difference disqualifies you from trying to judge either one. Lindzen is a brilliant man in my opinion … but his “iris hypothesis” doesn’t have a lot to do with my hypothesis other than that it is another part of the complex system that keeps earth’s temperatures within fairly narrow limits.
w.
So… You haven’t read all his papers on the tropics… Thought not.
Dinostratus, you are 100% correct. I haven’t read each and every one of Lindzen’s papers on the tropics, just as I suspect you haven’t read each and every one of my posts on the tropics … so what? There is no man alive who could possibly read every scientific paper on the climate. So sue me …
If you had any actual objections to my scientific statements, you’d have raised them. My work is either correct or incorrect, no matter what I have or haven’t read.
Instead of raising scientific objections, first you falsely accuse me of stealing Lindzen’s work [ when a) his is nothing like mine and b) you can’t give a single example of what I’m supposed to have stolen ], and now you want to criticize my reading list … my reading list? Get a grip!
Please come back when you actually have something scientific to contribute to the discussion. You see, Dino, I have a rule of thumb that covers people like you:
And as a result, when some random internet popup like yourself decides to start heaving muck at the walls as a way to demonstrate his infantile frustration, I just bow out until they come to their senses and return to the science. It’s simpler that way.
Regards,
w.
“I suspect you haven’t read each and every one of my posts on the tropics … so what?”
Because you could LEARN from it. That’s what. You don’t have to reinvent the wheel. Original research takes so much longer than study. If you want to see farther, stand on the shoulders of giants. Having the ability to recognize that while you are intelligent, you are not as intelligent as everyone who has come before you COMBINED, is the beginning of adding to the world instead of duplicating what already exists.
Dinostratus June 10, 2015 at 10:08 am
Dinostratus, I’ve come into science in a curious manner. I have no formal training in science beyond a year of introductory college physics and one of introductory college chemistry. That’s it. Period. That’s my formal scientific education.
Everything else that I know, every scrap of it, I’ve had to learn from the works of others, the work that you accuse me of ignoring. Over the years I’ve laboriously taught myself enough to have a peer-reviewed “Communications Arising” of mine published in Nature magazine, along with peer-reviewed articles in several other scientific journals. So I’d say I’ve done quite well considering where I started.
Now, one thing about educating myself is that in addition to a huge mountain of past studies and papers on climate science, there is also an unending river of publications coming out of the journals on a daily basis. In all of this, it’s easy to get lost. So I have to pick and choose, admittedly based on my own rather eclectic method, just what is worth spending my precious and limited time reading.
So I read things like Bejan’s work on the application of Constructal Law to climate … have you read it? I read Ramanathan’s hypothesis about the “supergreenhouse effect”. I read Dick Lindzen’s work on the Iris Hypothesis … but there are plenty of things that I haven’t read, even by those three men. However, that doesn’t mean that I don’t want to “stand on the shoulders of giants”, for goodness sake, how do you think I got here?
So I’m sorry, Dino. I’m not objecting to learning from the past, I do that all the time, whenever I can. I’ve had to do so to get where I am.
I’m objecting to you thinking that I should follow your reading list in the matter, and that if I don’t I’m neglecting the giants of the past. I’m sorry, but I’ll follow my own reading list … and if you haven’t read Bejan or if you haven’t heard of the Constructal Law, then let me recommend that part of my reading list to you.
The only difference is, I won’t diss you if you decide to read something else …
w.
“So I read things like Bejan’s work on the application of Constructal Law to climate … have you read it?”
Hell no. Anti-entropy theories are like rear end holes. Next time my sink is stopped up I’ll yell at it, “For a finite-size system to persist in time (to live), it must evolve in such a way that it provides easier access to the imposed currents that flow through it.” We’ll see what good it does.
Okay fine. I’ll give you a gold star for self directed curiosity (really, I do) but let’s be serious. You are reinventing the wheel. Also, a little humility would go a long way with me.
I just looked up this Bejan guy. Not the anti entropy stuff but just the regular what’s he published stuff. Never heard of him before. Odd as he works in an area that is similar to mine. Moreover he has some of the same academic lineage I have. Weird.
After scanning some of his stuff, I’d recommend moving on. He seems to have recast theory thoroughly covered by BSL (the case of Le=1 stuff) as his own. He currently publishes in at least some journals that don’t have a strong reputation.
Dinostratus June 12, 2015 at 9:56 pm Edit
Well, since “this Bejan guy” was listed by ISI as one of the top 100 cited engineers in the world in all engineering disciplines, and since he has published over 600 peer-reviewed papers and 28 books, and since he has not one but two physical constants named after him (the “Bejan numbers” in both thermodynamics and fluid flow), and since he occupies the J. A. Jones Distinguished Professor of Mechanical Engineering chair at MIT, I fear that your ignorance of his work says much, much more about you than about him … but sure, go ahead and tell us he’s a non-entity.
After all, that’s why we have random anonymous internet popups, isn’t it, to give us the benefit of their lack of experience in these questions?
w.
It’s not the “…Distinguished Professor of Mechanical Engineering chair at MIT”. It’s the “…Jones Distinguished Professor of Mechanical Engineering chair at Duke”. Duke’s not even the best school in NC when it comes to heat transfer. NC State is Duke’s better.
Combining known non-dimensional numbers in the case of Le=1 isn’t new science. It’s redundant and confusing.
GoreSat just reached station. When they have the Earth-facing camera working, maybe we’ll get to watch the clouds repeat the albedo pattern from its “noon” viewpoint.
http://www.nasa.gov/feature/goddard/nation-s-first-operational-satellite-in-deep-space-reaches-final-orbit
Personal observation: In Florida, as seasons progressed from winter to summer, at first there were no thunderstorms (only occasional frontal storms from cold northern air). Then late afternoon storms near leaving work time. In mid seasons, it would rain conveniently between lunch and going home. Then, at the hottest of summer, rain at lunch was an issue.
My desk had a partial window view, and “Is it raining?” was the daily question at lunch and leaving… I ended up with 3 umbrellas so one was always near. Home, work, car. Eventually I got skill at predicting and only used one of them…
Thanks, Chiefio. That’s exactly the temperature pattern I’m pointing to. The warmer the day, the earlier the clouds and thunderstorms form.
w.
https://medium.com/the-physics-arxiv-blog/cause-and-effect-the-revolutionary-new-statistical-test-that-can-tease-them-apart-ed84a988e
Mosh, that’s absolutely fascinating, thanks immensely. If I understand their brilliant insight, it’s like this, correct me if I’m wrong.
We have a cause C with noise NC.
We have an effect E with noise NE.
Their insight was, if we look carefully, under certain conditions we can partition the noise in the effect, NE, into two parts.
One part is the noise in E.
But the other part is the original noise from C, NC, transformed by whatever process it is that connects the cause C with the effect E. So if you find that in one but not the other, you’ve separated cause and effect.
Brilliant.
However, as clever as their method is and as useful as it is likely to be, I fear that for the most part it won’t be too useful in climate studies. This is because in climate we don’t often see simple cause and effect.
Instead, the usual situation is not just what I call a “chain of effects”, a sequence of events wherein one event leads to the next with no obvious “first cause”. No, it’s worse than that.
The usual situation is what I call a “circular chain of effects”. As an example, consider the relationship between the daily temperature and the albedo in the tropics. Clearly, changes in temperature are followed closely by changes in albedo … but just as clearly, changes in albedo are followed by changes in temperature. That’s a circular chain of effects.
And this feedback in the circular chain of effects will wreak havoc on their lovely method. Consider my previous example. Any noise in the temperature will cause corresponding transformed noise in the albedo … which then will feed that transformed temperature noise plus some more purely albedo noise back into the temperature.
They do use climate variables in their example dataset, but they are only where a “circular chain of effects” is not possible. Here’s their list:
Obviously, no matter how much it rains it won’t change the longitude … but for most interesting climate relationships there is no such simple one-way causality.
Their description of their pairs data does contain the following curious claim:
The “Haigh 2007” turns out to be a book called “The Sun and Earth’s Climate” … sorry, not buying that claimed cause and effect. I wonder what their method said about it … so much to investigate, so little time.
In any case, Steven, my great appreciation for pointing that out. Do you know if there is R code available? I found the location of their CauseEffectPairs data in their paper, it’s here.
Regards,
w.
There is also one problem with their notion.
In the real physical world, that we inhabit, cause and effect are simultaneous.
That is true down to the shortest time intervals that we are able to observe, and that is some where in or beyond the atto-second region.
I don’t see how one observes “noise” or noisiness, in two different things that happen simultaneously.
g
Meanwhile, SOI increases.
Recent (preliminary) Southern Oscillation Index (SOI) values.
https://www.longpaddock.qld.gov.au/seasonalclimateoutlook/southernoscillationindex/30daysoivalues/
The ITCZ snuffed my heat wave. ITCZ birthed a hurricane, which became a TS. TS turned into TD as it came up from Baja. Then just a barely organized moisture blob. Blob got caught in mid latitude circulation and fed a cut off low. The subsequent clouds and rain took us from a heat wave Monday, to an overcast barely warm day yesterday to a rainy coolish day today.
Good essay. Thanks again.
“All of the locations receive exactly, precisely, the same amount of top-of-atmosphere solar energy every single day.”
I’m not sure the equator is all that special. From one day to another, every latitude receives almost exactly the same amount of TOA insolation. The orientation of the earth with respect to the sun doesn’t change that much in the span of a day. In that respect, the equator is no different from any other latitude. It is around the days of the equinoxes that the equatorial insolation is most steady, since the equator is in the plane of the ecliptic.
It isn’t that special, MfK. I picked those because they were on the same line of latitude.
w.
w.
I will continue posting with my thread with updates until i hear from someone.
lo
Willis wrote: “My conclusion is that this downward pressure is the combination of cumulus clouds throttling back solar input in the morning, and thunderstorms and squall lines moving heat from the surface to up near the tropopause in the afternoon. It is this regulation of each day’s maximum tropical temperature via a host of inter-related mechanisms that keeps the earth from overheating on a daily basis.”
The TAO buoys provide hourly surface air temperature, but you haven’t cited any direct information linking changes in surface temperature to changes in clouds or thunderstorms. You are inferring what “must be happening” in the sky above the surface based on your personal experiences in the tropics and your “thermostat” hypothesis. Only real climate scientists are allowed to claim that their inability to conceive of an alternative explanation for some data provides strong evidence their preconceived notions are correct. Since neither of us are real climate scientists, let me point out a phenomenon that could account to some of your observations.
Most of the time, the “skin layer” of the ocean (the top 10 um) is colder than the water immediately below because all OLR and evaporation comes from this thin layer and DLR isn’t enough to compensate. Most SWR passes through the skin and is absorbed in the top 1 m. For most of the 24-hour day, the skin layer is getting heat from the water below by conduction and convection. As SWR weakens, the surface water gets cold and dense enough to sink and initiate convection. Around mid-day, however, enough SWR may be absorbed by the skin layer that it becomes warmer than the water below and upward conduction and convection cease. The air temperature measured by the TAO buoys probably closely follows the skin temperature of the ocean.
In Figure 4, the rapid fall in temperature around 17:00-18:00 followed by a slower cooling through at least midnight could represent cooling of the skin layer from 17:00-18:00 followed by the onset of convection and a dramatic increase in the heat capacity of the ocean in rapid equilibrium with the air above. In this case, convection should cease sometime in the morning.
In Figure 4, the rapid rise in temperature around 6:00 could be due to the fact that incoming SWR is entering the skin layer of the ocean at a very shallow angle, providing a long path length through the skin layer (or the top of the ocean in equilibrium with the air). However, the same phenomena should happen near sunset.
Perhaps the TAO buoys are collecting other data that will allow one to distinguish between changes in heat transport near the surface of the ocean, clouds, thunderstorms, and alternative hypotheses.
(Infrared thermometers measure the average temperature of roughly the top 10 um of the ocean, the microwave detectors used in satellites measure the average temperature of the top 1 mm and thermometers the bulk of the ocean below this.)
True in part, because I’m laying this story out in sections. You’ll just have to wait. However, I will note that my first graphic shows the timing of the emergence of the clouds in the Pacific, which coincides exactly with the timing of the changes I showed in the TAO buoy data.
False in root and false in branch. The fact that I haven’t written up all of the studies I’ve done, or presented all of the evidence I have, doesn’t mean I haven’t done them or don’t have them.
As to the idea that it is the ocean temperatures that are making the changes, I do love how people jump on stuff without doing the actual work to find out what’s happening. The variations in sea temperatures are almost totally disconnected from the air temperatures ,,, which you’d know if you gotten the data yourself and actually taken a look.
w.
Willis wrote: “The fact that I haven’t written up all of the studies I’ve done, or presented all of the evidence I have, doesn’t mean I haven’t done them or don’t have them.”
Thank you for the reply. My apologies for not guessing that you have undisclosed direct evidence that changes in clouds cover and the development of thunderstorms limit surface warming. I should have stock to the facts and not speculate about your thinking.
I’m very interested in any data that might explain what phenomena produced Figure 4 (or often limits SSTs to a maximum of about 30 degC). I wrote above: “Perhaps the TAO buoys are collecting other data that will allow one to distinguish between changes in heat transport near the surface of the ocean, clouds, thunderstorms, and alternative hypotheses.”
You can find more information about daily changes that occur at and near the surface of the ocean here:
http://ghrsst-pp.metoffice.com/pages/sst_definitions/
http://www.researchgate.net/profile/Akiyoshi_Wada/publication/225649603_Diurnal_sea_surface_temperature_variation_and_its_impact_on_the_atmosphere_and_ocean_A_review/links/0a85e539f0d1e1c144000000.pdf
Willis wrote: As to the idea that it is the ocean temperatures that are making the changes, I do love how people jump on stuff without doing the actual work to find out what’s happening. The variations in sea temperatures are almost totally disconnected from the air temperatures…”
Ouch! When I first commented, it seemed obvious that SST and SAT were tightly linked in the middle of the ocean. I tried (and mostly failed) to find some useful information about the relationship between SST and SAT. In terms of monthly averages, the difference is usually less than 0.5 degC in the Indian Ocean. The difference is larger (1 degC) near land, when the prevailing wind comes from land.
http://www.academia.edu/5322744/Relationship_between_sea_surface_temperature_and_surface_air_temperature_over_Arabian_Sea_Bay_of_Bengal_and_Indian_Ocean
The problem is that the annual range of SSTs in tropical oceans is only a few degC. So the correlation between SST and SAT in the Indian Ocean is usually, but not always, greater than 0.5 and sometimes greater than 0.75.
Even worse, I need information about the hourly, not monthly, relationship between SST and SAT. Since all of the heat exchange between the surface and the atmosphere occurs from the skin layer, the most relevant SST will be that of the “skin layer” (measured by IR thermometer). I believe satellite sensors record SST for the top 1 mm of the ocean (the depth from which microwaves escape) and traditional thermometers record the bulk temperature at various depths below the surface (where temperature varies less between day and night). The difference between these different measures of SST (up to 2 degC) is bigger than the daily warming of the air above the surface! See the graph at http://ghrsst-pp.metoffice.com/pages/sst_definitions/.
The rate of heat and humidity transfer from the surface of the ocean to the air depends on wind speed as well as the temperature difference between the air and surface and the relative humidity of the air. With turbulent mixing in the boundary layer, you are correct to disdain speculation in the absence of data. Unfortunately, ignorance of the diurnal changes at the surface of the ocean (where heat is exchanged) might lead one to miss any relationship that does exist.
Willis wrote: “And as I mentioned in my previous post, my insight was that if there are mechanisms that reliably keep the earth from overheating for a single day, they would keep the earth from overheating for a million years …”
That’s a bit of a stretch. Figure 4 suggests that the same mechanisms are influencing the daily cycle of temperature no matter what the average local temperature is: At 95W, where the average SST is 23 degC, the average daily warming is 0.8 degC. At 165E, where the average SST is 28.5 degC, the average daily warming is about 0.7 degC. IF global warming ever raised SST at 95W to 28.5 degC, I’m not going to feel any better if the average daily warming is limited by clouds and thunderstorms to 0.7 degC.
Your interesting post showing the SSTs are rarely above 30 degC suggested that some mechanism limits warming above that threshold. The development of hurricanes apparently requires a threshold SST of 26.5 degC. The data in this post PROVES that there is NO threshold SST where daily warming is significantly limited. Perhaps you will find a limit to daily warming around 30 degC. That would be exciting.
Areas of rising air that produce clouds require other areas of descending air that almost certainly will be sunny – even in the warmest regions of the tropics. The relative proportion of cloudy and clear sky is determined by the relative rate air rises and falls. Perhaps that proportion changes with warming. Perhaps convective cumulus clouds or thunderstorms are different above 23 degC topical oceans than they are above 28 degC tropical oceans. That difference could limit warming in the tropics.
Thanks Willis. Here at 12 N in South India on the coastline I see the same thing: the hotter, the more and faster clouds develop. Hot meaning above 36 C. Thunder storms come from the strongest and longest heating and when they drop their load they cool the ground by at least 5 C or more.