TAO Buoys Go Hot And Cold

Guest Post by Willis Eschenbach

I got to thinking about how I could gain more understanding of the daily air temperature cycles in the tropics. I decided to look at what happens when the early morning (midnight to 5:00 AM) of a given day is cooler than usual, versus what happens when the early morning is warmer than usual. So what was I expecting to find?

Well, my hypothesis is that due to the emergence of clouds and thunderstorms, when the morning is cooler than usual, there will be less clouds and thunderstorms. As a result the day will tend to warm up, and by the following midnight it will end up warmer than where it started. And when the morning is warmer than usual, increased clouds and thunderstorms will cool the day down, and by the following midnight it will end up cooler than when it started. In other words, the emergent thermoregulatory phenomena will cause the temperature to tend to revert to some mean, not over months or years, but on a daily basis.

Now, this is the third post in a series discussing the effects of albedo and thunderstorms on the tropical temperatures. In order they were Albedic Meanderings, An Inherently Stable System, and The Daily Albedo Cycle. This post will make more sense if you’ve read those three first and seen the Figures.

So to investigate warm and cold days what I did was to take the air temperature data from some sixty-seven TAO buoys. I sorted them by average temperature, and I started to look at them. Figure 1 shows the temperature data from one of the coolest TAO buoys, where the mean temperature is 24°C. I split the data into “warm” and “cool” days, based on the average early morning temperature from midnight to 5 AM, and then took an hourly average of the warm and cool datasets individually.

 

TAO average warm and cool days coolest buoyFigure 1.Cool TAO buoy, averages of the days with warmer early mornings (Midnight-5AM) and the days with cooler early mornings. Straight lines connect the temperature at midnight at the start of the day with the midnight temperature 24 hours later. “Mean” is the mean temperature of all days. “Recovery” is how much the following midnight averages have moved towards the mean compared to the opening midnight averages. “Recovery Percentage” is the same as “Recovery”, expressed as a percentage of the distance from the beginning temperature to the mean.“Warm Recovery” is how much the warm temperatures have moved towards the mean, and “Cool Recovery” is how much the cool temperatures have moved to the mean. Horizontal black line shows the mean (average) temperature of all midnights. Red and blue straight lines connect the starting and ending midnight temperatures.

My hypothesis says that the temperatures should move towards the mean. That is to say, the temperatures at midnight of the end of the day (hour twenty-four in Figure 1) should be closer to each other than the temperatures at midnight at the start of the day (hour zero in Figure 1). So I have measured the difference between the opening distance (warm-to-cool  temperature difference at opening midnight), and the closing distance (warm-to-cool  temperature difference at closing midnight ). This I have called the “recovery” in Figure 1. This movement towards the mean is reported both in °C and as a percentage of the opening warm-to-cool difference. I’ve also noted how much the ending midnight temperatures of the warm and cool days separately have moved towards the mean midnight temperature.

However, there’s not a lot happening in Figure 1. The temperatures are barely moving towards the mean. When the day starts out cold it seems that it stays cold, and when it starts out warm, it stays warm. There is very little difference over the 25 hour period shown (0-24). Looking at other buoys I found that at the coolest end of the TAO buoy locations, there is little indication of my hypothesized thermoregulatory mechanisms. None of the TAO buoys in the cooler locations show any significant thermoregulated recovery to the mean.

But then I looked at the records from a TAO buoy at one of the warmest locations, where the mean temperature is over 28°C. There, the situation is totally different.

 

TAO average warm and cool days warmest buoyFigure 2. Warm TAO buoy, averages of the days with warmer early mornings (Midnight-5AM) and the days with cooler early mornings. Straight lines connect midnight at the start of the day with midnight 24 hours later. “Mean” is the mean temperature of all days. “Recovery” is how much the following midnight averages have moved towards the mean. “Warm Recovery” is how much the warm temperatures have moved towards the mean, and the same for “Cool Recovery”. 

Now, this is quite different. At the warm end of the TAO buoy locations, the warm days end up cooler, and the cool days end up warmer, exactly as my hypothesis predicts.

One of the most interesting things about Figure 2 is how rapidly the restorative forces are able to move the temperature back towards the mean. In only one day, on average the temperature at midnight moves sixty percent of the way back to the mean midnight temperature … that’s a very rapid and rigid temperature control compared to what is happening in the cooler TAO buoy locations.

To close out this part, here’s a typical record from an intermediate temperature TAO buoy, with average temperatures of 27°C:

 

TAO average warm and cool days intermediate buoyFigure 3. Intermediate TAO buoy, averages of the days with warmer early mornings (Midnight-5AM) and the days with cooler early mornings. Straight lines connect midnight at the start of the day with midnight 24 hours later. “Mean” is the mean temperature of all days. “Recovery” is how much the following midnight averages have moved towards the mean. “Warm Recovery” is how much the warm temperatures have moved towards the mean, and the same for “Cool Recovery”. 

As you can see, the recovery towards the mean in this medium-temperature TAO buoy is somewhere in between the coolest and warmest buoys. In a single day the midnight temperature moves about a quarter of the way back to the mean.

One oddity that I noted was that although in absolute terms (°C) the recovery was different between the cold and warm days, in percentage terms (for the buoys shown above at least) the recovery is about the same.

This led me to ask, what is the overall dependence of the restorative thermoregulatory forces on the temperature? To see this, I took a scatterplot. Since I wanted to also see if the warm/cold recovery percentages were different, I used a scatterplot of the warm recovery percentages and the cool recovery percentages separately as a function of temperature. Figure 4 shows how the recovery percentage is related to temperature. I have again used the average temperature from midnight to 5 AM as the dividing factor for warm and cool days.

 

daily recovery to mean warm and cold daysFigure 4. Scatterplot, daily thermoregulatory response to warmer (red) and cooler cooler (blue) days versus annual mean temperature. “Recovery Percentage” is how much closer to the mean the temperature of the midnight at the end of the day is, compared to midnight at the start of the day. If it moved all the way back to the mean it would be 100%.

First, it’s clear that the strength of the thermoregulatory response is a function of temperature. There is almost no thermoregulation at the low end of the temperature scale, while at the high end the midnight temperature moves halfway back to the mean or more in the course of a single day.

Next, it’s kind of hard to see the red and the blue because there is so little difference between them. I’ve printed them transparent so when they overlap they make purple … but in no case is there any significant difference between the warm and cold recoveries when expressed as percentages. This is despite the fact that often they are different in absolute terms (°C), as is shown in Figure 5 below. I have no explanation of why this should be so. Always more puzzles …

 

TAO daily recovery to mean warm and cold days absoluteFigure 5. Scatterplot, absolute daily thermoregulatory response to warmer (red) and cooler (blue) days versus annual mean temperature in degrees C. “Recovery Amount” is how much closer to the mean the midnight temperature at the end of the day is, in degrees C, compared to the midnight temperature at the start of the day. 

Here, we see that the thermal regulatory mechanisms at the upper end of the ocean temperature range can warm or cool a single day by a third to half of a degree C, midnight to midnight …

CONCLUSIONS: Well, I can say that this result is certainly consistent with my hypothesis that there are emergent thermoregulatory mechanisms that warm up the cool days and cool down the warm days in the wet tropics.

Now, scientists have previously proposed temperature mechanisms which they thought were involved in holding the temperature down in the Pacific Warm Pool (PWP), where we find the warmest of the TAO buoys. Sea temperatures in that area are the warmest in the open ocean … but despite that, the sea temperatures rarely exceed 30°C. Ramanathan proposed a “Super-greenhouse” effect to explain this temperature limit, and Lindzen proposed an “Iris Effect”, in order to explain the strong downward pressure on the temperature in the PWP. And those proposed mechanisms may indeed exist, they are not in opposition to my hypothesis.

What I have not seen mentioned previously, however, is that in addition to there being the strong downward pressure on the temperature of the warm days in the PWP noted by previous researchers, there is also a strong upward pressure on the cool days in the PWP … and as far as I know, mine is the only one of those three hypotheses that predicts such an effect.

However, it’s a big world out there, and I certainly could have either missed or misinterpreted previous art …

Finally, my hypothesis is that the temperatures displayed above are regulated by the emergence of cumulus, thunderstorms, and organized squall lines. HOWEVER, this analysis can say little about whether my hypothesis is the actual reason for the remarkably strong daily recovery towards the mean of warm tropical ocean temperatures. All it can say is that such a powerful thermoregulative effect certainly exists, that it operates on both the cool and the warm days, and it is consistent with my hypothesis.

It does not provide evidence that the mechanism is cloud-based. That’s hard to establish with the TAO buoys because they don’t contain information on the cloud coverage. But I think there’s a way to do it, which will be the subject of an upcoming post.

w.

You May Have Heard This Before: If you disagree with someone’s words, please have the courtesy to quote the exact words you disagree with. That way we can all understand your objection.

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157 thoughts on “TAO Buoys Go Hot And Cold

  1. Another interesting article. Willis says:

    …in addition to there being the strong downward pressure on the temperature of the warm days in the PWP noted by previous researchers, there is also a strong upward pressure on the cool days in the PWP… such a powerful thermoregulative effect certainly exists, that it operates on both the cool and the warm days, and it is consistent with my hypothesis.

    That seems pretty clear from the results. Prof. Richard Lindzen wrote:

    “There is ample evidence that the Earth’s temperature as measured at the equator has remained within ±1°C for more than the past billion years. Those temperatures have not changed over the past century.”

    Something in the tropics obviously regulates the planet’s temperature. Explaining it to the extent that he is able to make repeated, accurate predictions would place Willis Eschenbach at the very pinnacle of the climate scientist community. I sincerely hope he is able to do that. He’s certainly capable.

    • Lindzen must have made that statement without knowledge of the effects on the Earth’s climate by the K/T extinction event 66 million years ago. We have hard evidence of the effect of massive volcanic eruptions on our climate, I’m sure that a 10 km asteroid impact that left a 112 mile wide crater seriously affected global temperatures….

    • Water vapor pressure rises with temperature. Hotter runs faster, and colder stops transporting heat (snow doesn’t evaporate as well as hot water). The physics is well enderstood in Engineering circles. It is Willis’ Thunderstorm thermostat or what I called Heat Pipe Earth.

      https://chiefio.wordpress.com/2011/07/11/spherical-heat-pipe-earth/

      They are also known to oscillate rather like weather does

      https://chiefio.wordpress.com/2011/08/17/pulsating-heat-pipes/

      Same physics, just a LOT larger.

      Heat pipes have working ranges, as does the interglacial Earth. Too cold, they freeze up. For the Earth, that is called an Ice Age Glacial.

      • The atmospheric temperature varies from up to 30 C at the sea surface to -50 C high in the stratosphere. The physics of clouds may be becoming understood, but for sure not in Engineering circles.

        I like the simplicity of your statement, Water vapor pressure rises with temperature. True. Where is that water? Is it liquid or solid? Gaseous ..no; your statement refers to a two-phase boundary.

    • Relative to the earth surface, the tropics are the source of heat and the poles (arctic, antarctic) are the sinks of heat. The tropic band radiates less solar heat than it receives, and the poles radiate more heat than they receive. The heat engine of the atmosphere, water vapor and winds, moves heat from the equator to the poles. (Heat evaporates water in the tropics; water vapor condenses and precipitates rain and snow at high latitudes, radiating heat away from the earth.

      Prof Lindzen has explained exactly that.

      The earth’s surface has \water in three phases, ice water and vapor. The energy in the phase changes is very large. The heat conveyor from the equator to the poles has very large capacity. The equatorial temperature variation can not be large. The energy imbalances can only be small.

      • Nevertheless, the tropics radiate away most of their own heat. The poles and high latitudes are left to deal with the leftovers.

    • So, who to believe? A climatologist and author of twenty dozen peer reviewed papers, who was M.I.T’s head of atmospheric sciences, and Lecturer in Meteorology at UCLA, and Professor of Meteorology at the University of Chicago and NCAR, and Professor of Meteorology at Harvard?

      Or… J. Jackson, who has no science background, and who gets his misinformation from alarmist blogs?

      Take your pick.

      • Sorry Dbstealey, but when you cite the twenty dozen pal reviewed papers, etc. …..you commit the fallacy of appeal to authority.

        Not only did Lindzen ignore the effects K/T impact, he’s ignored the fact that in a billion years, a main sequence G2V type star does not have constant output. He doesn’t address “Snowball Earth” either In other words, a lot can happen in a billion years.

        Can you find the data and or graph Lindzen uses to discern the equatorial temperatures over the past billion years?
        ..
        Try discussing the facts instead of committing the fallacy of an appeal to authority.

  2. Interesting. Positive feedback when temperatures are cooler, switching to negative feedback when temperatures are warmer. Could this also explain the missing hotspot? The models assume positive feedback. However in the real world this changes to negative feedback as ocean temps increased, damping out the predicted hotspot.

    • I don’t really see a positive feedback. Rather, a negative feedback strengthening and weakening.

      • I see further the difficulty of incorporating into models how seawater must also shed 35 ions of sodium per thousand total molecules when it evaporates to water vapor from the sea surface, which further raises the salinity which further requires more energy to overcome the entropy barrier. the heavy salty water despite being warm sinks. Wind spray of sea salt can also further encourage nucleation of water molecules at the vapor saturation pt.
        Honestly, as bad as the GCMs are, its a wonder and a tribute to their tuning that they are even in the ballpark. Of course, the GCM runs that go off the rails never see the the light of day past the cutting room floor of the CGI factories.

      • Joseph Murphy , correct. Both are manifestations of the same NEGATIVE feedback. ferdberple does not know what the term means.

        A negative feedback is one which opposes diviation. The idea being the negation of the change , not whether the result is up/down; in/out; more negative/less negative, etc. Negative feedback stabalises a system.

        A positive feedback is one which acts to increase any deviation. This leads to instability , “tipping points” etc.

    • Positive feedback mechanism are not likely – as positive feedback mechanisms tend to produce exponential growth. You may be familiar with the effect of positive feedback from what occasionally happens in sound systems with microphone and a speakers. From Wikipedia:

      “Positive feedback is a process that occurs in a feedback loop in which the effects of a small disturbance on a system include an increase in the magnitude of the perturbation. That is, A produces more of B which in turn produces more of A. In contrast, a system in which the results of a change act to reduce or counteract it has negative feedback.

      Mathematically, positive feedback is defined as a positive loop gain around a closed loop of cause and effect. That is, positive feedback is in phase with the input, in the sense that it adds to make the input larger. Positive feedback tends to cause system instability. When the loop gain is positive and above 1, there will typically be exponential growth, increasing oscillations or divergences from equilibrium. System parameters will typically accelerate towards extreme values, which may damage or destroy the system, or may end with the system latched into a new stable state.”

      Please don´t be scared about the effect of positive feedback. It there was a risk of such dangerous effects in the climate system we would have known. Or rather – we would not be around to know.

  3. By seeing the individual trees you explain the behavior of the forest–brilliant. Thank you!

  4. That’s very interesting.

    Is there a way to eliminate any mathematical bias that an extreme is likely to return to the average for most periodic functions? I’m sure there’s a proper way to say that, but it doesn’t come to mind.

    • Good question, George. I’d thought of that, but I’d say the fact that the cooler TAO buoys show no such tendency to “revert to the mean” on any daily basis indicates that if such an effect exists it is very weak.

      w.

      • Hi Willis, It could be that in general regression to the mean is more evident in the hot bouys if daily temperature is dependant on short term randomness and less evident in cold bouys where daily temp might be more a function of multiday weather patterns. This would be an alternative explanation for the different behaviour of the hot and cold bouys. Is there a way to determine whether or not this is the case?

      • Willis,

        But temperature is auto-correlative, so the amount of regression to the mean on any given time scale depends on the correlation time. So it might be that the correlation is controlled by a different process in the eastern Pacific (lower T’s in Figures 4 and 5) and western Pacific (higher T’s). The latter appear to have correlation times of a couple of days and the former have correlation times of weeks at least. So atmospheric control in the western Pacific and oceanic control in the eastern Pacific? Seems plausible since the lower T’s in the east are due to upwelling.

    • It should be remembered that temperature is a cumulative integral. Any “random” variations are likely to be seen in dT/dt and temps will thus display a red noise profile, one that decreases with frequency. ould better be applied to dT/dt .

      The cumulative result of random changes is called a random walk and does not display regression toward the mean. It can wander off in either direction for an indeterminate length of time.

      If it does return towards the mean it is evidence of a negative feedback.

      Good work Willis. Good digging.

      • Hi Mike- clearly they are restraints on termperature- days of -50 or + 100 degrees Celsius are very unusual in most locations. All other things being equal a day with an unusual temperature is likely to be followed by a more moderate day thus exhibiting regressive behaviour.

      • Mike wrote: “If it does return towards the mean it is evidence of a negative feedback.”
        Anyone not living in an isolated environment should be aware that temperature does regress to the mean. That is indeed evidence of a negative feedback: heat transfer (radiative, conductive, and convective) to/from places that are colder/hotter than where the temperature is being measured.

        For the planet as a whole, only radiative heat transfer matters. That is accounted for in the models by the “Planck feedback” which is negative and dominates all others. But the Planck feedback is not always classified as a feedback.

      • “If it does return towards the mean it is evidence of a negative feedback. ”

        There’s always the SB law which already provides a neg feedback via blackbody/greybody radiation.

  5. I think you are neglecting the thickness of the warm layer just under the surface. My measurements indicate that its temperature stays very consistent, but its thickness varies considerably from literally nothing to several feet thick and it can be extremely persistent. On sunny days the warm layer gets thicker and on overcast days the warm layer gets thinner.

    It seems to me that it is a regulatory mechanism itself.

      • Maybe observations is a better term. I have surface measurements and just below the surface measurements and engine inlet measurements but the thickness observation is from snorkeling which I do almost every day.

        The expanding, contracting ‘warm’ layer clearly acts like a buffer.

  6. On a macro scale, warmer west Pacific SSTs -> more convection -> stronger and deeper trade winds-> increased humidity, clouds, and rain -> cooling effect?

  7. Put another way, WE’s clouds/thunderstorms hardly kick in at all on cool starts, and work all day on warm starts.

    Humidity differences could be the reason. Temperatures are lower at night with low humidity, and allow more sun the following day since clouds are less.

    What drives humidity?

    • “Humidity differences could be the reason. Temperatures are lower at night with low humidity, and allow more sun the following day since clouds are less.”
      Night time cooling increases rel humidity(and slows the rate of cooling ), but that also removes water vapor.

  8. Willis:

    … but despite that, the sea temperatures rarely exceed 30°C. Ramanathan proposed a “Super-greenhouse” effect to explain this temperature limit, and Lindzen proposed an “Iris Effect”, in order to explain the strong downward pressure on the temperature in the PWP. And those proposed mechanisms may indeed exist, they are not in opposition to my hypothesis.

    A better and much simpler hypothesis is gut simple. Don’t use climatologist divide by four of the irradiance entering and leaving the Earth system since Earth does have a day and a night side. The TOA energy balance in and out during actual daytime is not 237.5 W/m² but 237.5 W/m² times two, or 475 W/m². Pass that through Stefan-Boltzmann with adequate assumptions as emissivity one and you get the 30°C that you see near the equator. That is assuming also 0.30 albedo but you can adjust if that is not correct for a certain region of limited time when it can go over or under that 30°C but I do agree with you Willis that this 30°C is the approximate mean.

    So I do not see the need for some “Super-greenhouse” or even some “Iris Effect”. it is 30°C because the irradience says it should be 30°C.

    • A great idea Wayne.

      To extend your ‘gut simple’ idea ad absurdum: At night there is no solar radiation coming in and, by your misunderstanding of the Stefan-Boltzmann Law, the temperature should be absolute zero.

      By the way, the Stefan-Boltzmann Law says nothing about irradiance (i.e. energy coming in) but only about radiation going out. The intensity of the radiation going out depends only on the body’s own temperature and emissivity (irrespective of any energy coming in).

      That’s what’s wrong with gut reactions.

    • Wayne

      Where do you get your 237.5 W/m² figure from?

      Solar irradiance over the equatorial and tropical oceans whilst the sun is shinning on the oceans (ie., during the mainstay of the day) is far higher than 475 W/m², more like double that figure.

      There is enough solar irradiance to drive the equatorial/tropical oceans well above 40degC.

      Indeed, even in the Med, where there are shallow lagoons, the water temperature is often over 38degC. These shallow lagoons are just like hot tubs.

      Infact, you only have to look at the salt lakes, around the Med, to realise how much heat the solar insolation received at these mid latitudes can generate (notwithstanding evaporation). In the equatorial/tropical regions, it is considerably more.

      • Most global heat balances I see have 340 W/m^2? What does the “consensus” say?

        If the solar constant is 1,366 +/- 0.5 W/m^2 why is ToA 340 (+10.7/- 11.2)1 W/m^2 as shown on the plethora of popular heat balances/budgets? Collect an assortment of these global energy budgets/balances graphics. The variations between some of these is unsettling. Some use W/m^2, some use calories/m^2, some show simple %s, some a combination. So much for consensus. What they all seem to have in common is some kind of perpetual motion heat loop with back radiation ranging from 333 to 340.3 W/m^2 without a defined source. BTW additional RF due to CO2 1750-2011, about 2 W/m^2 spherical, 0.6%.

        Consider the earth/atmosphere as a disc.
        Radius of earth is 6,371 km, effective height of atmosphere 15.8 km, total radius 6,387 km.
        Area of 6,387 km disc: PI()*r^2 = 1.28E14 m^2
        Solar Constant……………1,366 W/m^2
        Total power delivered: 1,366 W/m^2 * 1.28E14 m^2 = 1.74E17 W

        Consider the earth/atmosphere as a sphere.
        Surface area of 6,387 km sphere: 4*PI()*r^2 = 5.13E14 m^2
        Total power above spread over spherical surface: 1.74E17/5.13E14 = 339.8 W/m^2

        One fourth. How about that! What a coincidence! However, the total power remains the same.
        1,366 * 1.28E14 = 339.8 * 5.13E14 = 1.74E17 W
        Big power flow times small area = lesser power flow over bigger area. Same same.

      • Yes, of course, but cosine weighted due to the geometry, it divides the top of atmosphere TSI minus the albedo mean by two to get the average over the lit hemisphere. Directly underneath the sun it would be much higher, ie. twice.

      • Richard:
        “There is enough solar irradiance to drive the equatorial/tropical oceans well above 40degC.

        Indeed, even in the Med, where there are shallow lagoons, the water temperature is often over 38degC. These shallow lagoons are just like hot tubs.”

        Yes, that is what I said of regions with strings of days with minimal albedo (cloudless). Plug that in and you will get your 38°C or very close. Here where I am we have strings of cloudless days hitting 104°F (40°C) also. Plug that in at 1050 W/m² peak, I’ve seen those actual measurements, divide by two, 525 W/m², and you get 310 K (37°C, 99°F) and will shallow water bodies reach that, close but not quite. To get deeper into this to see why you have to look into what the radiosondes are doing over nighttime (creating the local diurnal range) allowing for the columnar mass, heat capacity for the radiative loss at night is not much lower that daytime (see ESRL). The bulk of the tropo cools but about 1.25 K between the pressure levels of 250 – 800 hPa, above the boundary level.

        BTW, thanks for the reply.

  9. Willis, this is fascinating. I am not surprised at the temperature reduction; but, I am surprised at the warming effect. There are a number of chemical reactions in the ocean that are not well understood. I will list some of the pieces that I have noticed, but I cannot put them together and make sense of the total picture.
    1. The temperature that carbon dioxide cannot remain a liquid regardless of the pressure is between 30 and 31C. A gas in solution loses some of it’s energy because its degrees of freedom are reduced. Around 26C, carbon dioxide becomes more active; I am not sure if this means it will enter into chemical reactions or outgas.
    2. Calcium carbonate has two reactions, one the familiar reaction of photosynthesis and the second a direct reaction. The direct reaction is acknowledged in the literature, but no one knows how it works. The reaction is inhibited by magnesium and trace amounts of fulvic acid. This reaction appears to be the primary reaction for the calcium carbonate deposits in the warm latitudes away from the equator because of the absence of nutrients in these latitudes. The floor of the ocean down to the CCD, the depth at which calcium carbonate is dissolved, is coved like snow with calcium carbonate, so there is an active process at work.
    3. When calcium carbonate is “dissolved”, it either goes into its individual ions and reforms as calcium carbonate hexahydrate or it forms calcium carbonate hexahydrate directly. Calcium carbonate hexahydrate being a hydrate does the usual thing that hydrates such as calcium chloride hydrate does, it stores energy. The important thing about this reaction is it is not inhibited by magnesium or fulvic acid.
    I suspect that somewhere between the absorption and release of carbon dioxide, these reactions are reversible, i.e., they absorb and release heat. The calcium carbonate reaction is endothermic and absorbs about 1400 joules per mole of calcium carbonate. The calcium carbonate hexahydrate reaction has about 5 phases and can absorb 75 to 90 kilojoules per mole if it goes all the way to Ikaite, The Ikaite decomposes into water and calcium carbonate at 4C and releases its heat. I suspect the calcium carbonate hexahydrate release of heat is present in Kelvin Waves and the cold anomaly that flows the wave is calcium carbonate hexahydrate reforming. The problem with this scenario is the temperatures do not fit; however, I do not know how these temperatures might be modified by the water pressures.
    Sorry that I cannot give the answers; maybe some of the others on WUWT that have a chemical background can add some more pieces.

  10. This also increases the probability of life on other planets in the universe. It means the zone that supports life is much larger than would otherwise be the case. Planets closer to their sun would have more clouds and planets further away would have less clouds. The mean temperatures would be close to that optimal for life.

    • So where does this bring the probability of life on other planets up to? Still between 0% and 100%? ;)

  11. Man, I hate to admit ignorance. I scanned your post looking for the meaning of TAO. Not finding it (always a chance I missed it, of course), I turned to my trusty Climate Audit Acronyms link. Alas, it is not there. Somebody help me out here….

      • Well, I kind of figured that out by looking at the post. But one does assume that the letters stand for something, n’est-ce pas? In this case ‘allacronyms’ gives 152 meanings for TAO.

        http://www.allacronyms.com/TAO

        And if you think about it, Tropical Atmosphere Ocean doesn’t make a whole lot of sense for a buoy system that is presumably in the water and not in the atmosphere. There is a lot to be said for the convention of using an entire expression initially, before using its acronym.

        Do try not to lap the competition.
        : > )

      • Well, nut, I’m going to have to eat crow on this one. The TAO home site describes the buoys capabilities as: TAO/TRITON moorings measure surface meteorological parameters, upper ocean temperatures and, at some locations, ocean currents.. I (correctly) assumed ocean temperature measurement, and (incorrectly) assumed no atmospheric measurement. Which, of course, wouldn’t make any sense, given the text of Willis’s post.

        As I said I really hate to admit ignorance. But I’ll stand by my remarks on acronyms and sportsmanship.

      • J S … kudos to you for making the effort to follow the conversation closely by searching for something you were not familiar with. Stay with WUWT, it will be an enlightening experience.

  12. My number for calcium carbonate formation was wrong. Zumdahl lists the delta Hf as 1207 KJ per mol.

  13. Interesting as always.

    Usually looking into the things you dont expect gives you the greatest insight. So why is the thermostatic effect small to non existent for cooler areas of the ocean?

    • Regression to the mean has no meaning unless you can explain why it regresses. We also know that for larger changes – coming into and going out of deeper segments of the ice age that there are tipping points. When it happens in an electronic circuit we call it a Schmitt Trigger circuit. The part of the cycle we are in now is a negative feedback system.

    • Bill 2 June 16, 2015 at 8:36 pm

      Pretty sure you see this at all latitudes. Regression to the mean.

      Look at the last two Figures—you don’t even see this at all temperatures, so it can’t be “regression to the mean”. Remember, we’re looking at daily changes. As I pointed out in the head post, at a number of the TAO buoy sites when a day starts out cold it ends cold, and when it starts out warm it ends warm … no regression to the mean at all.

      w.

  14. The time of minimum and maximum temperatures vary with the day length. The day length vary with latitude and season — tan pie x tan delta where in pie is the declination of the Sun and delta is the latitude of the place.

    Dr. S. Jeevananda Reddy

  15. Nice work Willis. But shouldn’t you be using “adjusted” ship intake temperature data. LOL

  16. Willis,
    You mention thunderstorms. Can you indicate your view on the role played by lightening? Is this a rapid form of heat dissipation or..? in your suggested process.

    • I’ve actually looked at the total energy released worldwide by lightning … it’s not large on a global 24/7 basis. But on a local level it is indeed a form of energy transformation that does move significant energy. It’s an odd one, because a good chunk of the light that is emitted by lightning must go straight to space. Other than aurorae I don’t know how often that happens …

      w.

    • Just did a quick calculation. I think all lightning world wide represents an amount of energy which is 1/36,000 of the energy of the atmosphere. Like Willis says, it doesn’t appear to be significant overall, but maybe locally.

      By shedding electrons to build up a charge, I believe kinetic energy in the air/water is being transformed into both heat energy and electrical energy. If/when lightning discharges to the ground, a typical strike will transfer about 500 MJ. A typical thunderstorm can produce 3 CG strikes per minute, and a storm typically lasts 30 minutes.

      90% of the electrical energy of lightning is released in the form of heat, which is quickly dissipated into the atmosphere. Less than 1% of lightning’s energy is converted into sound and the rest is released in the form of light.

      In a thunderstorm, water vapor is lifted up, and when this condenses, the amount of energy released is about 10^15 Joules. This is 22,000 times the energy released by the lightning of the storm.

      So, it appears that lightning results in a transfer of kinetic energy (caused by sun) into heat, warming the atmosphere slightly. However, 85% to 90% of lightning occurs over land because solar radiation heats land faster.

  17. “Elements of Physical Oceanography”, McLellan, 1977 although dated, covers heat budget of the ocean in Chapter 18. This link offers a download which I downloaded and compared with my paper copy:
    http://bookzz.org/g/%27physical+oceanography.%27

    Two of several other links offer paywalled copies at about $30 per chapter.
    http://www.sciencedirect.com/science/book/9780080113203
    http://store.elsevier.com/Elements-of-Physical-Oceanography/Hugh-J_-McLellan/isbn-9781483151939/
    My text price of $9.50 for the whole book in 1970 looks like a good investment.

    To the problem at hand, several commenters mentioned humidity. McLellan Chapter 18 Section 18.2 “Back Radiation” caught my attention and might offer some insight. I captured part of the text, copied below (caution on the “greenhouse effect”):
    18.2 BACK RADIATION
    The sea surface, by virtue of its temperature, emits long wave radiation to the atmosphere. The emissivity* is very close to unity, so that the rate of back radiation Q& approximates that from a black body as given by the Stephan-Boltzmann law,
    Qb = oT^4 (18.5) [equation not fully captured]
    where T is the temperature in degrees Kelvin and σ, the Stephan-Boltzmann constant, has a
    value 5.735 X 10^-5 ergs/sec cm^2 degree^4. The radiated energy is distributed over a wide band of wavelengths with the wavelength of maximum emission (Am) given by Wien’s displacement law,
    [equation not captured]
    K has the value 2880(micro symbol) degrees. Thus, for a surface at 20°C (293°K),
    lambdam = 2880/293 = 9.859(microns). [equation not fully captured]

    Over most of its spectrum this radiation is absorbed efficiently by carbon dioxide and water
    vapor in the atmosphere. Since the air, with its water vapor, itself radiates by virtue of its temperature, the loss of heat by back radiation is reduced by the humidity of the atmosphere over the sea surface. Sverdrup et al. (1942) have presented (Fig. 18.2) a graphical relationship of effective back radiation to a clear sky as related to sea surface temperature and relative humidity measured a few meters above the sea surface. This shows that, for a constant relative humidity, effective back radiation decreases with increasing temperature. This relationship may at first appear strange but it should be noted that, for constant relative humidity, the concentration of water vapor in the atmosphere is greater at the higher temperatures. Also the radiation efficiency of the air itself increases with temperature.

    * A “black body” is defined as one that completely absorbs all incident radiation. Such a body is also the most efficient radiator. Radiation from a body with emissivity e is given by
    Qb = €sΤ^4, where € has a maximum value of unity for a black body.

    Air and water vapor are almost transparent to radiation in a band of wavelengths from about 8 micron to 14 micron which embraces the wavelength of maximum emission from the sea surface. This band of high transparency is sometimes known as “Simpson’s window”. The long wavelength cut-off in this window is accomplished by a strong absorption band due to CO2. Water vapor gives almost complete absorption at the still longer wavelengths.

    The earth is heated by short wave solar radiation which passes efficiently through the atmosphere and, because of atmospheric absorption of the longer wavelengths, the surface temperature rises to where the wavelengths of maximum emission falls within the window. At these surface temperatures a balance of incoming and outgoing radiant energy can be effected, and the skin temperature of the earth is stabilized in this range. Because of the similarity to the effect created by horticulturists with glass roofed enclosures this is called the “greenhouse effect”.

  18. Now, this is quite different. At the warm end of the TAO buoy locations, the warm days end up cooler, and the cool days end up warmer, exactly as my hypothesis predicts.

    I’m trying to think what happened if opposite was true.

    Warm days ended up warmer and cold ended up colder. Wouldn’t that necessarily mean the system were completely unstable? So how could it be otherwise?

  19. There are TAO sensors measuring downwelling shortwave radiation, which is related to cloudiness, if it is defined as the attenuation factor relative to incoming shortwave flux at ToA. The latter quantity is independent of weather and only depends on time and location.

    More importantly, they also measure wind speed. Your albedo-related regulatory process clearly depends on rate of evaporation, which is indeed a strong monotonic function of sea surface temperature. However, it also proportional to area of water-air interface, which is very small over calm seas. However, as soon as wind speed exceeds the limit when sea spray starts to form, it suddenly increases by many orders of magnitude.

    Therefore thermoregulation is expected to kick in at a lower temperature if wind speed is high enough. Is that so?

    It would also explain the apparently explosive nature of storminess. As soon as the first deep convective cell form over an area, wind speed exceeds this threshold, which in turn speeds up evaporation tremendously. A strong positive feedback loop, a sure recipe for an explosion.

  20. Brilliant work as usual!
    Is the scale of importance?
    Can a maximum temperature also exist in lakes and swimming pools?

    • It’s 105 F all week in Phoenix. How come I still have to heat the pool to keep 80 F? Why doesn’t the pool heat up to 105 F? Because evaporation from the pool drives the water temperature towards the ambient wet bulb. Water evaporates because the air is dry, not because it is hot.

      • Because unless you have a cover at night, the sky temp is probably 0F to -20F, Which would be ~600 to 800 BTU’s per hour lost to space.
        What sized heater do you have and how long does it have to run to maintain the temp.
        BTW it will do this most of the day, it will lose a little bit less during the day, plus the amount that the Sun adds.

        This is actually a really good daily energy balance experiment, the mass of water makes a good thermometer.

  21. You plot the “mean temperature at midnight”, but I am more interested in the mean temperature each day. Currently we get this calculated, globally, through just two reference points, minimum and maximum temperatures. How stable is the temperature at the equator, I wonder? If we measured the temperature every 15 minutes to get 96 data points each day and took the mean of this, how stable or variant would the temperature be each day? Would cloud cover have any impact at all? Would humidity? Bearing in mind the assertion that the Greenhouse Effect is supposed to add 33C of heat to the surface and that water vapour is supposed to be by far the biggest part of that increase, do the changes in its concentration day to day, bare this out?
    There is so much basic testing, in Climate science in general, that should have been done, that hasn’t been done. So many assumptions made without testing the basics.
    The equator is a good place to do a lot of this. Equal amounts of day and night, with only the distance from the sun throughout the year to consider (at first, though solar activity can be added in later).
    As interesting as I find these investigations into cloud cover and weather patterns, it seems to be jumping ahead of the process.
    Perhaps you could also check the mean temperature for the entire day on your two separate starting scenarios and comparing that (if there aren’t 96 equal intervals of temperature checks each day go with however many there are (hopefully there will be more than two!!)) Checking for the mean temperature the following midnight, leaves me feeling I am looking at an incomplete picture.

  22. Hi Willis

    Do you have enough data to see if there are any changes in the outcome if the data is sliced by day of year (or week, or month) ?

    I would be interested to see whether the recovery percentage varies with the seasons.

  23. “Strong wind shear—a large change in wind speed and/or direction going up through the atmosphere—can destroy a hurricane or even prevent one from forming. The top map shows the difference from average (1981-2010) in the strength of the vertical wind shear during August-October 2013, measured between 200 and 850 millibars of pressure (roughly 4,500 feet and 38,000 feet altitude). The vertical wind shear across much of the western half of the main development region and the Gulf of Mexico was stronger than normal.”
    https://www.climate.gov/sites/default/files/styles/featured-image/public/2013HurricanSeason_Composite_620.jpg?itok=80TABy5a
    http://www.sat24.com/image2.ashx?region=am&time=false&index=7

  24. I may be missing something:

    Figure 1 has both end of the day, beginning of the day, data the same (midnight avg is midnight avg, says so in the text) Trendline is flat.
    Figure 2 midnight avg end, is not same a midnight avg beginning, so you get a trend line.

    Why are the 2 midnight avgs not the same? The hypothesis is seemingly proved by using a different “midnight avg” calculation.

    BTW – TAO? as per Juan Slayton June 16, 2015 at 8:01 pm

    And if you think about it, Tropical Atmosphere Ocean doesn’t make a whole lot of sense for a buoy system that is presumably in the water and not in the atmosphere.

    Thanks.

    • Thanks, Rocky. The time shown at zero is the midnight at the start of the day. The time at 24 is NOT the repeat of the time at zero. It is the midnight at the end of the day.

      w.

  25. We live in a water world, most of it is covered in water, we live on a blue planet, not a green one. Without water, and the amount that is on earth and its unique properties the world would not be a place where life could flourish. I live most of my life in a cold climate, and when I learned in high school that water freeze on the surface because it get lighter at 4C I realized if not for that simple property, earth would be a giant snow ball, since without it lakes and oceans would freeze from the bottom up, and once froze not likely to ever thaw out, but since water gets lighter a 4 C and ice forms on the surface and ice itself is and insulator lake and oceans do not often if ever freeze solid. Water keeps things from getting to hot or to cold, add on the heat conveyor, that the thunder storms present water even more wondrous. Water is the control knob of climate, not CO2, to bad the morons of the world have not figured that out. Even worst some of the same moron are trying to set limits on CO2 production thinking their fools errand might make a difference, I only have contempt for such morons. Oh as a disclaimer those who are born with limited intelligence please do not take offense, my derogatory comments about morons are only for the self made morons.

  26. This is despite the fact that often they are different in absolute terms (°C), as is shown in Figure 5 below. I have no explanation of why this should be so. Always more puzzles …

    Reconsidering my earlier comments about regression to the mean, I realise that your “recovery” is a temp diff over 24h, ie it is dT/dt. That maybe tested against a null hypothesis of a gaussian distribution.

    It has to be fairly symmetric since what you’re doing is defined relative to the mean. However, abs vs proportional change is probably informative.

    If it was gaussian distributed data they would be equally distributed either side of the mean in degree units.

    Proportional change is what you would get from a negative feedback. NB I’m not talking about the non-linear processes inside the emergent phenomena, but the resulting daily averaged effect that you are considering.

    I think that what you have shown is further evidence that this is feedback not regression to the mean.

    Figure 4 may give some indication as to whether it is a linear or non-linear -ve f/b. It seems fairly flat <26 deg C above that there is upward curvature indicating non-linear ( stronger than linear ) feedback, with a very strong rate of change at the top end.

    I'm inclined to see a very nice power law curve at the bottom of the envelop, and a more linear rise in the rest but that could be just in the eye of the beholder. It may be interesting to see whether that is due to some geographical variation. Are there two groups of data behaving somewhat differently here?

  27. It seems to me that there is two cut off points on the graphs and three sets of data in figure 5?

    Looking at figure 4&5 there is cut of points in behaviour at 26 degree c. And one in figure 5 at 27.5 degree c.

    The three sets of data in figure 5: There seems one set of results the (base line) looking like a, dare I say it hockey stick!!! Another one I would call offset 26 to 27.5 degrees raised above the base line. And one above 27.5 which seems reactive.

    Could the difference be in the position of the buoys with say a under currents or prevailing winds or another factor? I am curious as to what’s going on. Any one tell me the answers please.
    Thanks.

  28. Willis, This is way out of the domain of anything I know even the slightest bit amount, so just ignore it if it is mindless. But it seems to me that you assume that all temperature changes seen by the TAO buoys are local and are the result of insolation, clouds, convection, precipitation,etc at or near the buoy. But I should think that at any given time, some of the buoys will be outside the intertropical convergence zone and in the domain of the trade winds with air from elsewhere constantly replacing the local air. I would also think that even very modest changes in temperature caused by air mass transport will affect your arithmetic.

  29. The variable ‘control’ at the higher t locations suggests something from control theory. You need two things for control: forward response with gain (energy), and neg feedback for stability. Most systems rely on constant gain. In this case, gain is a variable because energy in system is increasing before onset of violent convection. So it’s a control system that can’t work until gain passes some threshold

  30. Willis,

    I wonder if you’re not looking at something caused by how you split the data. Statistically, most of the colder days must get warmer, while most of the warmer days must get colder. I guess this is what other posters are calling regression to the mean.

    I did a quick test in R to see what completely random data would look like. It turned out that the random data also shows the two trends, so you’d probably need to add something to take out any trend effects caused by your choice of warm and cold. Then again, maybe I’m missing something, I see your code.

    Here’s my code, should be possible to run it as is (sorry, I’m new to R)

    # Generate random data
    meas = runif( 1000, 22, 27 )

    # Moving average to get something resembling a random walk
    f10 <- rep(1/10, 10)
    mavg <- filter( meas, f10, sides=1)

    # Split in "days" of 10 hours
    mavg <- t(matrix( mavg, 10, 100 ))

    # Split in hot and cold, find average
    num_cold <- 0
    num_hot <- 0
    cold <- vector( length = 10 )
    hot <- vector( length = 10 )
    for( day in (2:99) )
    {
    if( mavg[day,1] < (22+27)/2 ) {
    cold[ 1:10 ] <- cold[ 1:10 ] + mavg[day,]
    num_cold <- num_cold + 1
    }
    else {
    hot[ 1:10 ] <- hot[ 1:10 ] + mavg[day,]
    num_hot <- num_hot + 1
    }
    }
    hot[ 1:10 ] <- hot[ 1:10 ] / num_hot
    cold[ 1:10 ] <- cold[ 1:10 ] / num_cold

    plot( 1:10, hot, col = 1, ylim=c(22,27),xlim=c(1,10),type="l" )
    lines( 1:10, cold, col = 2 )

    • > Then again, maybe I’m missing something, I see your code.
      Err, I *didn’t* see your code.

    • Frank says : “# Moving average to get something resembling a random walk”

      You’re heading in the right direction.

      Don’t use running mean ( it’s crap ) , besides what you need to do to get a random walk is integrate. Random temps would be random walk.

      What is needed is to fit the parameters of your random model to the data, not just choose any random series. See my comments above. Willis’ 24h dT is rate of change so that could be modelled as AR1 ( ARIMA or some other may be better )

      It looks like when scaled to the data the 24h regression would be negligible but this needs to be tested and would firm up the result.

      • oops, more proof reading reqd. Temps could be modelled as AR1, 24h dT should be gaussian random series, as a basic test.

      • Thanks Mike.
        The point I was trying to make was to show that even a random set of values, when split into “hot” and “cold” intervals will always show two trends towards to average. The running average was just to get something quickly that goes up and down somewhat smoothly in the 22-27 degree range. I don’t think it matters much to the point I was trying to make. I don’t want to model anything.
        F

    • Frank de Jong June 17, 2015 at 5:01 am

      Willis,

      I wonder if you’re not looking at something caused by how you split the data. Statistically, most of the colder days must get warmer, while most of the warmer days must get colder. I guess this is what other posters are calling regression to the mean.

      Don’t know how many times I have to say this, but I guess it’s at least one more …

      IF this were regression to the mean we’d see it at both low and high temperatures. But at lower temperatures, we don’t see this at all. No significant reversion to the mean occurs at lower temperatures.

      THEREFORE … I’m sure you can fill in the rest.

      Nor would we really expect to see any sizable “regression to the mean”. Remember, we’re looking on a daily basis. A summer’s day doesn’t revert to the annual mean in the course of a day.

      As to the code, well … you’re more than welcome to it, it is here, but I’m not sure it will do too much good. Far from being user-friendly, It’s kinda user-aggressive …

      w.

  31. Frank. One key error you have is that your rand series is the full range of the TOA data , not the range for one site.

    If you look at Willis’ fig 1 etc the range of data are much narrower. You need to scale your integrated random walk to fit the data. Ultimately this needs to be done by matching the statistical model to the actual data, but your idea is a good first hit.

  32. I would like to see the rate of change in SST on calm cloudless nights. SST closely correlates with dew point at the surface and the rate of change in dewpoint is a measure of the energy being radiated to space.

  33. Wish I could make a constructive comment, but you can see what the scatter plots say as well as I can. The only way you could do better is by adding dimensions using more data, for example if the buoys were equipped with a simple full-spectrum (all the way down into the LWIR so that it includes “back radiation”, even better a split that records separately SWV and LWIR split at the midpoint between incoming solar and downwelling LWIR) photocell that gave you “top of buoy” insolation as a function of time. This is the thing that would really help you, because it would let you connect what is actually happening with incoming radiation as a function of time/temperature and vice versa. Humidity/precip as well, as I’m guessing getting actually rained on might affect temperatures, or else the peak in temperature might correspond to achieving saturated humidity near the surface.

    In the meantime, ascribing causes is going to be basically impossible, because all of the causes discussed are in hidden dimensions and because the regression effect you record is a fraction of a degree and hence is associated with some comparatively weak (on average) phenomenon.

    To some extent you may just be seeing the emergence of a seasonal split (it would be interesting to correlate e.g. location of the cool buoys with their interaction with e.g. a jet stream, or the dates over which they return cool behavior vs warm behavior in a scatter plot as your “split” may be purely seasonal). The warm buoys might regress to a mean because there is only one stable mean with little seasonal behavior. The cool buoys clearly have a variable mean with a temporal persistence greater than a day, which suggests seasonal or at least weather cycle persistence.

    I’ve read elsewhere about the apparent clipping of open ocean temperatures around 30C. The one thing that is immediately apparent is that that energy doesn’t stop coming down at the TOA just because SSTs reach 30C. It must therefore be a critical point of some sort for a mechanism that either blocks incoming radiation, increases sensible loss via e.g. latent heat, or increases sensible loss via some sort of active transport (or all of these together). It also has to be one that has a rather sharp onset because your scatter plot is clearly the flipping of some sort of climate “switch” (or switches) in higher dimensions. It is reminiscent of the clipping of temperature in water at the boiling point until you add enough energy to break latent heat bonds and start a boil. The energy isn’t going into temperature any more, it is going into something else (but obviously not Hansen’s “boiling oceans”:-) or going somewhere else.

    I like going somewhere else, but where? Does this temperature correspond to one that triggers advective rolls in the salinity downward transport cycle, so that any extra heat just speeds up the transport? That could even be the missing mechanism for the missing heat — an entire equatorial band that simply speeds up downward transport of high density warmed water directly proportional to any increase in net downward flux to maintain a constant surface temperature of 30C. More heat equals faster, not warmer.

    This sort of thing wouldn’t function alone. It would have to regulate the rate of surface evaporation to match, cope with the extra water vapor produced and increase sensible heat transport laterally in that form poleward, and might actually alter albedo several thousand miles away, several weeks later to further implement your feedback mechanism. That is, the mechanism doesn’t need to be local to affect global average temperatures — increasing water vapor production in the tropics and transporting it poleward could push temperatures down (on average) in the temperature zone three weeks later by increasing the cloud albedo there by a tiny amount.

    This is why climate models suck. One would love to be able to build a model for this. But how can one build a model for this? It’s not even a hypothesis. One is postulating an alteration of a probability connected to a purely turbulent phenomenon in the coupled Earth-Ocean system, one involving density not of water but of highly saline ocean water in a way that depends on the local details of its density/depth/thermal/saline profile. The turbulent rolls involved are going to be completely invisible on a scale of 100km square cells. They might have a characteristic length scale of 50 meters! The entire phenomenon I described above might involve them growing to 51 meters when the surface is receiving more energy than it loses to the atmosphere! There might be a whole spectrum of these rolls that varies with surface wind speed and direction and past history, and the entire regulatory mechanism could be a tiny shift in the spectrum.

    The only way to build it into climate models is by fiat. Assert that it exists, make up some semi-empirical function that affect tropical 100 km square cells, implement it in a model, and then run the model. At which point voila! The model will produce what you built in as that function! But does this reflect reality? It is literally Impossible with caps, boldface, and italics all intended, to tell. Climate models produce an insensible shotgun blast of future climates. To even detect the phenomenon might require real time detectors in an array the same order of magnitude as the advective rolls themselves place in the open ocean, and one would expect that the existence/presence of the detector might be more than enough to disrupt the phenomenon so that they are literally not observable except with extremely sophisticated techniques, perhaps a doppler sonar, perhaps collecting signals from a few million tiny (oversized bobber sized, too small to affect the evolution of the rolls) research buoys that ride the local currents and return some sort of picture of the local flow of energy in the ocean where temperatures appear to be clipped.

    We are decades away from having the data needed to solve mini-problems like this, and centuries away from having enough compute power to solve the larger problem (the coupled Navier-Stokes equations for the Earth-Ocean-Atmosphere-Sun system) that dictates the evolution of the climate at adequate spatiotemporal resolution to be able to actually model the emergence of emergent negative feedback phenomena.

    This is where GCMs utterly fail. 100km square cells basically mean that they can only develop self-regulatory nonlinear phenomena — emergent dissipative structures — at that scale. 5 minute timesteps and enormous amounts of compute time mean that they cannot with any plausibility function well enough to capture (predict) the known, named long period emergent phenomena, the decadal oscillations, that clearly have an enormous impact on global climate. Yet much shorter length scales are almost certainly critical (literally) in the heat transport they are trying to model. Thunderstorms have length scales dictated by their height — a cell with an anvil that reaches the top of the troposphere has a length scale order of 10 km, and there can be a lot of variability on scales down to a km laterally by kms vertically. Thunderstorms represent a huge local transport of heat latent and otherwise straight up through the greenhouse gas barrier.

    The ocean no doubt has many similar transport mechanisms that exist on length scales from meters (size of surface waves) to a few hundred meters, pretty much clipped at 700 m if not before at the thermocline. But within the first 700 meters there can be entire encapsulated rivers transporting heat coherently and spinning it off in turbulent chaotic featherings to mix with surrounding water at different temperatures. This process is almost certainly fractal down to very small scales indeed — one can see the featherings in any surface temperature representation of e.g. the gulf stream, but only at a horrendously poor resolution, and of course a lot of what happens is beneath the surface, where the thickening of a layer by a factor of 2 might not affect the surface temperatures at all but which might represent a doubling of the energy being transported at constant temperature.

    One hates to plead ignorance as an excuse, but I do so plead on behalf of the human species. We are cosmically ignorant about the climate. We are decades away from enlightenment, decades that are not well-served by a research climate rife with confirmation bias and contaminated by a “religious” desire to save the world from an unconfirmable hypothesis “predicted” only by GCMs that were built for the sole purpose of predicting it.

    AGW is a plausible hypothesis that is directly supported by evidence that increased CO_2 is largely anthropogenic and a single, comparatively simple theory of radiative heat transport that, as a mean field theory, predicts a logarithmic warming that is reasonably well-supported by data with a thoroughly unalarming empirical climate sensitivity. Catastrophic AGW is (so far) purely a pipe-dream of a few individual people, amplified beyond all reason and outside of all actual evidence into a trillion-dollar public trough from which the very energy companies that are supposed to be “the bad guys” gobble down billion dollar chunks, money that if otherwise invested might have (by now) brought about an end to global poverty (instead of its perpetuation), a stable and healthy national economy (instead of a fragile energy economy that at this point would collapse if the public trough were to suddenly be emptied), and hey, who knows, World Peace.

    Me, I’d be content if we simply invested it in making energy cheap. Energy is the fundamental scarce resource. Given enough, cheap enough, energy, all of the world’s problems can be solved. With energy we can (if necessary) desalinate the oceans and make deserts bloom, we can make fertilizers and run tractors and combines and grow food to feed a hungry world, we can build sewage treatment systems and bring the miracle of flushable toilets and the consequent reduction in misery and disease to the third of the world’s population that uses the nearest open field or the side of a handy street as a bathroom. We could provide energy to heat food without burning charcoal or dried dung and break a cycle of dung-based contamination of food and respiratory illnesses that claim several million lives a year in the third world, most of them children.

    Personally, I could care less about where the energy comes from as long as it is cheap. Cheap solar is just fine. Cheap nuclear is peachy. Cheap coal is lovely, as long as coal remains cheap. Cheap fusion is my dream — that is the technology that would allow us to run civilization for so long that we would no longer be recognizably human long before it runs out (if then — by then we can probably mine Jupiter or its moons and never run out in the lifetime of the Sun). Sure, we might die off in the meantime, or be wiped out by an asteroid or gamma ray burst or war or an engineered super-virus built by a crazy person, but at least we wouldn’t do any of the above because of a lack of the fundamental resource.

    At heart, all poverty is energy poverty. The units of energy are the units of work, and work, one way or another, is wealth.

    rgb

    • One hates to plead ignorance as an excuse, but I do so plead on behalf of the human species. We are cosmically ignorant about the climate. We are decades away from enlightenment, decades that are not well-served by a research climate rife with confirmation bias and contaminated by a “religious” desire to save the world from an unconfirmable hypothesis “predicted” only by GCMs that were built for the sole purpose of predicting it.
      AGW is a plausible hypothesis that is directly supported by evidence that increased CO_2 is largely anthropogenic and a single, comparatively simple theory of radiative heat transport that, as a mean field theory, predicts a logarithmic warming that is reasonably well-supported by data with a thoroughly unalarming empirical climate sensitivity.

      This is what got me interested in Climate.

      But I have one nit

      predicts a logarithmic warming that is reasonably well-supported by data

      The problem is that the data is infilled based on the same hypothesis, and none of the temp series are based on actual measurement alone, so you have GCM’s being compared to temp series that are augmented by the very same hypothesis they are used to confirm.
      Turtles all the way down, turtles, inside of turtles, inside yet more turtles….

      • “The problem is that the data is infilled based on the same hypothesis, and none of the temp series are based on actual measurement alone, so you have GCM’s being compared to temp series that are augmented by the very same hypothesis they are used to confirm.”

        wrong

        [for a man who professes that we all need to show our work (raw data, code, procedure, etc.) you sure have a lot of one-word responses without providing the slightest portion of what you preach -Anthony]

      • wrong

        So you infill based on lat and elevation, and a fudge factor for weather from stations up to 1,200km away, you do exactly the same thing for 1880 as you do for 1980, and you do it before you adjust the hell out of the 1880 data right?

      • The problem is that the data is infilled based on the same hypothesis, and none of the temp series are based on actual measurement alone, so you have GCM’s being compared to temp series that are augmented by the very same hypothesis they are used to confirm.
        Turtles all the way down, turtles, inside of turtles, inside yet more turtles….

        Which makes the value of the TCS more uncertain, but probably doesn’t change its sign or make it particularly likely to be zero. Personally I think it is somewhere between 0.5 and 2 C, most likely around or a bit over 1 C, and one reason for the size of this range is that it is very difficult to know how much of the warming post 1850 in HadCRUT4 is an artifact of the sort you describe or lost in what should be much larger error bars than HadCRUT acknowledges in the 19th century. Almost certainly more than 0.1 C, possibly (IMO) as much as 0.3 C. That would knock my own “best fit” TCS of 1.8 C down by almost a factor of 2, which would put it — perhaps unsurprisingly — at the low end of the range of the central theoretical estimates for TCS, which run from 0.9 C to around 1.5 C. The low end would simply suggest that feedbacks, if any, are on average slightly negative, not positive.

        But even 0.1 C would knock it down pretty easily to the high end of the no-feedback range, around 1.5 C. This is what at least one climate model that uses the newly measured lack of any significant climate response to aerosols obtains — TCS around 1.45 C. I don’t think it would surprise anyone that even if every single adjustment made to HadCRUT has been made with the very best of will, the simple fact that nearly all of them have had the effect of cooling the past and/or warming the present has perhaps overshot the mark by 0.1 C. Not that there isn’t an acknowledged uncertainty in HadCRUT4 greater than that anyway, nearly 3x that much (and still not enough) on the early end of things.

        The fundamental problem is this. What the heck, accept HadCRUT4 at face value. Fit the predicted log increase in temperature as a function of CO_2 concentration historically with no lag and no additional assumptions. It is a simple two parameter nonlinear least squares fit, a child could do it with R (and I have). One of the two parameters is irrelevant as it just matches the floating scale of the “anomaly” to the equally floating scale of the log. The money parameter is then only the no-lag equilibrium sensitivity.

        When one does this, one gets a really excellent fit with a log factor that implies ECS equals 1.8 C, a bit over 1/2 of the IPCC’s central estimate. One also gets a fit that is good enough that it leaves little room for “uncommitted warming”, although of course long relaxation times wouldn’t necessarily show up in this sort of stationary fit as long as everything is smooth enough.

        Given this, what is the motivation for spending a fortune on GCMs that obviously don’t work as well as the essentially one parameter fit? How much of the climate’s observed variation over the last 165 years remains “unexplained” by this fit? The answer is:

        Not much.

        rgb

      • I’m going with 0.8C +/- 0.4C (per doubling), From a little above Co2 alone (1.1C) to about half that.

        I would even buy that during the day max temps are a bit higher*, but it’s completely lost at night.

        * though the more I look at surface data the harder it is for me to believe what I just wrote.

      • rgbatduke wrote: “one gets a really excellent fit with a log factor that implies ECS equals 1.8 C”
        Unless I misunderstand what you wrote, that gives a Transient Climate Response of 1.8 C. Smack dab in the middle of the IPCC range of 1.0 to 2.5 C. To get ECS, you need to account for net heat transfer into the ocean. But your response is high since it does not account for other greenhouse gases. Careful analyses of this type (such as those by Nic Lewis) do give ECS around 1.8 K.

      • micro6500: I’m going with 0.8C +/- 0.4C (per doubling), From a little above Co2 alone (1.1C) to about half that.

        Looking only at surface energy fluxes, I calculated a surface climate sensitivity to a doubling of CO2 of about 0.3C-0.9C. I put the calculations up at RealClimate and ClimateEtc. A part can be downloaded from my web page at ResearchGate.

    • “At heart, all poverty is energy poverty. The units of energy are the units of work, and work, one way or another, is wealth.”

      Thumbs up.

    • rgbatduke: The only way you could do better is by adding dimensions using more data, for example if the buoys were equipped with a simple full-spectrum (all the way down into the LWIR so that it includes “back radiation”, even better a split that records separately SWV and LWIR split at the midpoint between incoming solar and downwelling LWIR) photocell that gave you “top of buoy” insolation as a function of time. This is the thing that would really help you, because it would let you connect what is actually happening with incoming radiation as a function of time/temperature and vice versa. Humidity/precip as well, as I’m guessing getting actually rained on might affect temperatures, or else the peak in temperature might correspond to achieving saturated humidity near the surface.

      Rainfall and humidity are available, but downwelling lwir is generally not, except on a few buoys for a few years.

  34. Clearly the tropics buffer the planet.
    One need not look further than the satellite surface temperature record, which is flat as a board since 1979.

  35. The electromagnetic spectrum goes like this from short wave high energy to long wave low energy:
    Gamma rays, X-rays, UV, visible, SWIR, LWIR, microwave, radio wave.
    Step 1: UV, visible, SWIR from the sun heats the earth.
    Step 2: The earth heats and per S-B emits LWIR.
    Step 3: GHGs absorb LWIR.
    Step 4: GHGs emit an equal amount of down welling LWIR that over heats the earth.
    Step 5: I don’t think so.
    Per S-B and Einstein’s award winning photoelectric equation balance GHGs cannot emit LWIR. Objects/molecules absorb some of the incident energy through heating, vibration, oscillation, etc. and emit at a lower energy, longer wave.
    The down welling back radiation from GHGs cannot be LWIR, but microwaves, good for heating water, not much else.
    And the upwelling and down welling fluxes shown as equal on so many of the popular global heat balances cannot be correct.

    • Really Nick?
      Greenhouse gases emit radiation at the same wavelengths they absorb radiation. This is Kirchoff’s Law.
      Besides, down-welling radiation is measured; it is not guessed at. Spectral plots show that down- radiation is in the long wave infrared. It is not the result of guessing, assuming or modelling – it is measured.

      • Greenhouse gases emit radiation at the same wavelengths they absorb radiation. This is Kirchoff’s Law.
        Besides, down-welling radiation is measured; it is not guessed at. Spectral plots show that down- radiation is in the long wave infrared. It is not the result of guessing, assuming or modelling – it is measured.

        And yet actual surface temps don’t match the models.

      • And yet actual surface temps don’t match the models.

        Sure they do. Just not General Circulation Models, not ill-tuned weather models run out to a few thousand times their useful time span. They match the simple model of CO_2 driven average warming extremely well:

        Better, on average, than all of the climate models (literally) put together.

        Seriously, the physics for the GHE is pretty sound, and as you can see, explains almost all (all except for a 0.1 amplitude, 67 year period sinusoid for which I have no explanation) of the observed warming of the past 165 years (I’m only displaying the last century plus, but it works over all of HadCRUT4 back to 1850 well within reason).

        rgb

      • Oh, Kirchoff’s radiation law! Which applies to an ideal black body in an isolated system at thermodynamic equilibrium. Just exactly like the atmosphere!

        NNNNNNOOOOOOTTTTTTT!

      • Kirchoff’s law applies to electric circuits

        https://en.wikipedia.org/wiki/Kirchhoff%27s_law_of_thermal_radiation

        Gosh, I guess Kirchoff had more than one law in more than one context. Kind of like Newton, and Gauss, and a few other early physicists and mathematicians.

        Aside from Kirchoff’s Law, molecules absorb radiation according to its radiatively coupled quantum structure, and emit radiation according to its radiatively coupled quantum structure. There’s a bit of slop (from broadening and multi-molecule events), but on average the slop works out to be nearly zero.

        The funny thing is that people have a problem with this even after MikeB points out — quite correctly — that the downwelling spectrum is not the result of guessing, assuming, modeling, or applying a theoretical law because it is MEASURED! Let me see if I can isolate that word for you again:

        MEASURED!

        Do you understand what that means? It means that denying its reality is literally as insane as denying that the sun is lighting up the earth, or denying that my weight is slightly in excess of 1000 Newtons. It isn’t badly measured, or measured with bleeding edge equipment. Measuring it is cheap and easy and several methods for measuring it have been around for a very long time. You could measure it yourself if you invested a comparatively small amount in a piece of equipment to do the measurement with.

        rgb

    • I can only repeat what I said yesterday to ren under similar circumstances. As a physics professor and with the greatest of good will, you should never, ever post again on the subject of radiation or physics in general, certainly not unless you are going to take the time to learn some of both.

      If you want to be educated — instead of just posting a short diatribe that proves that you don’t have the foggiest idea of what you are talking about — you could read Ira Glickstein’s nice article on the greenhouse effect on WUWT (I can find the link if you are interested and can’t manage Google). Or better yet, you can buy a copy of Grant Petty’s book “A first course in atmospheric radiation”, which isn’t horribly expensive. You will without question struggle with the physics if you are so confused as to state that downwelling radiation is “microwaves” and not “LWIR” and that there is some difference in what they do, or that CO_2 can interact with one and not the other, but if you get a textbook on introductory physics (I have a free one online if you can’t afford one of the paper ones) and perhaps continue on to learn a bit of modern physics and a smattering of more advanced electrodynamics and quantum theory you can manage it.

      In the meantime, please — if you post as “fact” exactly the kind of articles that give skeptics a bad name, things that are so obviously erroneous that (logical fallacy that it is) makes it easy for warmists to assert that all skeptics are equally erroneous, you do science no service.

      rgb

      • APS IPCC Workshop 1/8/14
        Dr Koonin’s opening remarks

        “While not all or even most of the APS membership are experienced in climate, it’s important to realize that physicists do bring a body of knowledge and set of skills that are directly relevant to assessing the physical basis for climate science. Radiation transfer, including the underlying atomic and molecular processes, fluid dynamics, phase transitions, all the underpinnings of climate science are smack in the middle of physics.”

        In a similar vein:

        In order to earn, emphasis on “earn”, my BSME I had to demonstrate competence in chemistry, physics, heat transfer, thermodynamics, statistics, calculus, algebra, etc. Got the picture? And engineering is more that models, it actually has to work.

        The notion that these “climatologists” have some kind of special knowledge or scientific insight the rest of us haven’t got is just snake oil BS. We all recognize a used car salesman when we hear one.

        All of this esoteric academic chatter about LWIR up/down is all beside the point. These next three points are all that matter.

        According to IPCC AR5 industrialized mankind’s share of the increase in atmospheric CO2 between 1750 and 2011 is somewhere between 10% and 200%, i.e. IPCC hasn’t got a clue. IPCC “adjusted” the assumptions, estimates and wags until they got the desired result. Ta dah! It’s all about man!

        At 2 W/m^2 CO2’s contribution to the global heat balance is insignificant compared to the heat handling power of the oceans and clouds. CO2s nothing but a bee fart in a hurricane.

        The hiatus/pause/lull (IPPC acknowledges as fact) makes it pretty clear that IPCC’s GCM’s are useless trash.

      • rgb you are hand picking data to make the case that somehow global temperatures are agreeing with the models which is so not true. In addition the correlation between CO2 and temperature does not exist.

      • http://hockeyschtick.blogspot.com/2014/09/new-paper-finds-natural-ocean.html

        Here is what correlates to all of the temperature changes to the highest degree.

        Also if one plots radiosonde and satellite temperature data versus CO2 /model temperature projections one can easily see how wrong they both are.

        In addition if one goes back to the Holocene Optimum some 8000 years ago the overall temperature trend has been in a gradual down trend from then — present punctuated by periods of warmth due to solar variability being superimposed upon the slow gradual moving Milankovitch cycles which were more favorable for warmth 8000 years ago as opposed to now.

        .

        Further refinement of the temperature trends from the Holocene Optimum to present fit very well if the PDO,AMO and ENSO phases are put into the mix and for even a further refinement can be brought about if volcanic activity during this period is accounted for. The correlation being very high as evidenced by the data I sent over.

        Co2 having nothing to do with anything. A trace gas with a trace increase which probably has a negative feedback with water vapor as evidenced by STILL no tropical hot spot. This trace gas is not going to run the climatic system of the earth. In addition all data shows CO2 concentrations are in response to the climate /temperature which is why it always follows the temperature never leads it.

        That is not to say there is not a GHG effect, but that GHG effect is a result of the climate not the cause
        of it.

        One last note is the weakening earth magnetic field is being trivialized in all of this which is a mistake. This field acts to enhance solar effects primary and secondary effects.

        It ceases to amaze how a non energy source in trace amounts (co2)can be thought to have more influence upon the climate then the sun which is not only the source of energy for the climate system to begin with, but what drives the climate system.

        Yet the scam has legs thus far ,despite every major atmospheric process it has predicted to be verified as false but I think time is running short.

      • rgb you are hand picking data to make the case that somehow global temperatures are agreeing with the models which is so not true. In addition the correlation between CO2 and temperature does not exist.

        I’m doing no such thing. In the graph above, I’m fitting all of HadCRUT4, an accepted temperature series, using the raw data they publish on their website. If that’s “hand picking data” to you, all I can say is that we have very different definitions of hand picking.

        In addition, I have to say I’m a bit flabbergasted that, when I publish a graph above that shows a truly excellent — according to R — relationship between the unpicked data (HadCRUT4) and the standard log model for CO_2 driven warming, you would assert that the correlation I’ve plotted “does not exist”. That puzzles me. You might assert that the correlation is accidental. You might assert that the data I’m fitting is corrupt (several people have, and I don’t argue with them but as I clearly state, I’m taking HadCRUT4 at face value and suggest that the buyer beware, especially with regards to error bars and the possibility of biased overcorrection). But to assert that something I plot doesn’t exist seems to me to be some sort of state of pretty serious denial.

        I plot the precise functions I use to fit HadCRUT4. You too can download its data, punch the function I obtained into R, and either fit it yourself or verify that the fit I plot really does match the data as well as I portray, but to claim “it does not” when clearly it does is silly.

        You go on to plot various other timeseries for CO_2 and temperature, most of them geological low resolution even higher error data, and assert that this somehow “proves” that the greenhouse effect doesn’t exist or that CO_2 concentration has no effect on temperature. I would take issue with the former, just as I would take issue with the assertion that the good fit I plot above “proves” that it does exist, and the latter is almost certainly not true, although there is a great deal of uncertainty as to the magnitude of the “average” effect it has in a complex system that can behave quite perversely with respect to any single “cause”.

        As I go to some pains to point out, the plot above is certainly not good evidence against the assertion that CO_2 causes a logarithmic warming of the planet, on average. The fit permits one to estimate an ECS, and the ECS is very much in line with theoretical expectations. I should emphasize again that the fit also does not imply that we are on the brink of any sort of catastrophe — quite the contrary, it suggests that what the majority of surveyed climate scientists in at least the Georgetown survey apparently believe is correct — that the planet is warming, the anthropogenic greenhouse effect is real, and that future warming caused by it will probably not be catastrophic. I think this view is shared by our host, by Christopher Monckton, by Dick Lindzen, by myself, and by a whole lot of other folks who have gone to the trouble to work through a paper or two describing the details of the greenhouse effect, or read through e.g. Grant Petty’s book.

        On to Nick:

        The notion that these “climatologists” have some kind of special knowledge or scientific insight the rest of us haven’t got is just snake oil BS. We all recognize a used car salesman when we hear one.

        All of this esoteric academic chatter about LWIR up/down is all beside the point. These next three points are all that matter.

        According to IPCC AR5 industrialized mankind’s share of the increase in atmospheric CO2 between 1750 and 2011 is somewhere between 10% and 200%, i.e. IPCC hasn’t got a clue. IPCC “adjusted” the assumptions, estimates and wags until they got the desired result. Ta dah! It’s all about man!

        At 2 W/m^2 CO2’s contribution to the global heat balance is insignificant compared to the heat handling power of the oceans and clouds. CO2s nothing but a bee fart in a hurricane.

        The hiatus/pause/lull (IPPC acknowledges as fact) makes it pretty clear that IPCC’s GCM’s are useless trash.

        Nick, I try not to judge somebody’s scientific knowledge on the basis of their degrees or lack thereof but on what they say and the arguments they make. My comments above were very specifically aimed at some absolute nonsense about downwelling LWIR not really being LWIR but being “microwaves” followed by the assertion that microwaves are somehow different. As I’m sure you know given your own understanding of E&M, this is pure piffle, nonsense, balderdash. The downwelling radiation is indeed (partly) LWIR, its spectrograph can be and has been made at many sites and portrayed on this website and elsewhere, and for that matter, there is no substantive difference between LWIR and “microwaves” except for their wavelengths — both are either absorbed or reflected by anything they fall on depending on that something’s particular properties.

        I fail to understand why “academic chatter” about LWIR is beside any point. If downwelling LWIR exists — and I think you truly have to be a bit crazy to assert that it doesn’t, especially when you can feel it and measure it and do a full spectral decomposition of its intensity, all of which suggest reality one would think — then that fraction of it that hits the surface of the Earth or Ocean is part of its overall energy budget. True, it is order of 1% of the total energy budget. OTOH, the greenhouse warming we are talking about is order of 1% of the total absolute temperature. It isn’t unreasonable.

        As for your other points. I personally respectfully disagree with the assertion that humans haven’t caused all or most of the CO_2 increase. Note well that I did not arrive at this position casually — you can look back a few years at comments I’ve made in the WUWT archives (if you can find them) and for a rather long time I was unsure myself because it was clear that multiple models all of which predict rising CO_2 “could” have been correct, but over the last few years I’ve learned more about the data and its consistency with the various alternatives, and at this point I’m fairly certain that humans have contributed all or most of the current CO_2 increase — around 100 ppm over the last 100 to 150 years. Ferdinand Englebeen, a frequent WUWT contributor who is if anything a climate skeptic or lukewarmist himself AFAIK, has built a lovely website where he exhaustively tallies the evidence and multiple consistent lines of support and IMO his conclusions are very difficult to challenge.

        Regarding 2 W/m^2, recall that this is 2 W/m^2 all the time, very nearly everywhere on the planet. It is interesting that you compare this, unfavorably, to the awesome power of hurricanes. Consider a year of downwelling radiation. A year being around 3 x 10^7 seconds, that’s 60 million joules per square meter — just about enough energy to shoot a kilogram sized mass to infinity from the surface of the planet for every square meter of the planet — times 510 x 10^6 x 10^6 = 5 x 10^14 square meters. That’s 3×10^22 Joules, which is, actually, a lot of joules, around 1% of the total solar energy budget.

        An average hurricane releases (depending on how you estimate it) just about half of the 10^15 watts of global power downwelling from those 2 lousy watts. If there were over 700 additional “hurricane days” a year, the earth would break even compared to its energy budget without the additional forcing of those 2 watts. That would roughly triple the number of hurricanes. I don’t think you can count on hurricanes to help much with balancing it.

        If you were trying to argue instead that the 2 watts is irrelevantly small compared to e.g. the heat capacity of the ocean-earth system, I’d have to say that you are getting your units mixed up. Power is the rate at which the planet receives energy. Its temperature is related to its heat capacity and energy/enthalpy content, but then you can’t use “the planet” because temperature and heat storage are local, not global averages. As I pointed out above and will point out again, 2 watts is a bit less than 1% of the Earth’s current average solar power budget and adding it to the open system can perfectly reasonably be expected to raise the absolute temperature of the Earth-Ocean system by an amount on the order of 1%, although of course it could be half this, or even a tenth of this, or (less likely) more than this (always possible in a nonlinear system). If we assume the average temperature is around 300 K, 1% is 3 C (same degree size) and half of this is — gasp — the ballpark of the climate sensitivity expected of CO_2.

        But this isn’t entirely fair, as the actual computation of a response is a bit more work than that. Again, I’m not asserting that I can solve the climate problem in my head, only pointing out that the assertion that increasing CO_2 will cause warming is more than “plausible”, more than just “reasonable”, it is probable. The issue isn’t whether the world will warm, it is “how much”.

        Finally, we are in complete agreement that the IPCC’s GCMs are complete trash, as they don’t even do as well as my trivial one-effective-parameter model above head to head on the same data. True, I’m just fitting the data, but the fit is completely consistent with the theoretical prediction if one really assumes that all things remain equal in the climate but the total downwelling radiation increases by 2 measely watts.

        The main thing to remember, however, is that while the IPCC’s computers cannot solve the problem of the climate, neither you nor I can solve it in our heads, either! The IPCC’s predictions of doom and gloom could be true, or could be false. The question is one of probabilities based on observation and evidence. I would say that it is probably true that humans are largely responsible for the last 100 ppm of CO_2 in our atmosphere. I would say that it is almost certainly true that this CO_2 has been enormously beneficial to the planet so far, so much so that if we soberly assessed it we would probably have chosen to raise planetary CO_2 to at least 400 ppm, maybe even (as we learn more) 500 to 600 ppm. I would say that one of the many benefits of the CO_2 so far is its probable contribution (however large or small it might be) to the warming that lifted us out of the Little Ice Age. The real problem we face isn’t that the IPCC is right or wrong to worry — it is that we don’t know enough to predict the results of continuing to increase CO_2 in the atmosphere.

        This puts humanity on the horns of a dilemma. There are obvious, enormous, overwhelming benefits to all of mankind right now from generating electricity burning coal. Without coal generated electricity, the world would enter a depression the likes of which it has never seen, a loss of around a century of steady rise in global average standard of living, a return to abject poverty in all of the energy starved economies of the world. That is the immediate risk of catastrophe that we are playing with right now, not eighty years in a murky future. There are other risks — huge political power shifts, risks to personal and political freedom. Yet there is an undeniable risk of a climate catastrophe — we certainly don’t know enough to be certain one won’t occur if we push planetary CO_2 over 850 ppm up towards 1000 ppm.

        I just don’t like both sides exaggerating the certainty of their knowledge that a catastrophe will definitely occur or that it will definitely not occur, that the greenhouse effect is real and catastrophic, real and harmless, or not real at all when nobody can solve the climate problem in their heads or using the world’s best computers. The real political debate is best served by Feynman’s brutal utter honesty about what we do not know, and how little we can reliably predict, not about what might happen in some imagined worst-case scenario that might actually be rather improbable. We needn’t turn this into the modern version of Pascal’s Wager in the Green Church of the Climate Apolcalypse, which is the way it is currently presented.

        rgb

  36. Just like to say this is one of the best and most informative threads for a long time. Willis, as usual, is posting really well reasoned and thought-provoking stuff, nicely presented: no surprise there. But also the quality of the responding comments is brilliant. Something from so many disciplines. Much sensible caution and counter-argument. Much right on the money, some perhaps not so relevant, but all really constructive stuff. Wonderful.

    Many thanks, folks.

  37. one of the most interesting article series with a very valid set of hypothesis and supported by data sinca a long time. digging this out does not show a lot of other scientists that try to explain these mechanisms.

    thanks a lot for this!

  38. I can’t help feeling that plotting this same temperature recovery data, from pole to pole as opposed to equatorially, that the seasonal changes due length of day and sun angle would some how reflect variation in polar sea ice formation/melting from year to year. What could influence the recovery from year to year? The ENSO and other events don’t always jibe with sea ice levels.

  39. As mentioned in previous articles in this series, 30C seems to be the magic temperature at which things really start to happen. This just appears to confirm that.

    If the data were available, it might be interesting to look at the spread (N-S) over which this effect occurs. I suspect that as temperatures N-S increase towards 30C the band of clouds expands, and as temperatures N-S decrease, the band narrows.

    So a global increase in temperature would see the normal equator thunderstorm pattern spread out towards the tropics.

    • Philip,

      “As mentioned in previous articles in this series, 30C seems to be the magic temperature at which things really start to happen.”
      It never actually gets to 30C, it looks like things start to happen at 27 +/1 C. That happens to be the critical T for forming hurricanes. So the mechanism might involve triggering some sort of strong convection.

      “So a global increase in temperature would see the normal equator thunderstorm pattern spread out towards the tropics.”
      That would be in agreement with what is in the paleo record. Tropical T’s don’t change much as the planet gets warmer of colder. To a large extent, what changes is how much of the planet experiences tropical T’s.

  40. The addition of water vapor to air (making the air humid) reduces the density of the air, which may at first appear counter-intuitive. This occurs because the molar mass of water (18 g/mol) is less than the molar mass of dry air (around 29 g/mol). For any gas, at a given temperature and pressure, the number of molecules present is constant for a particular volume (see Avogadro’s Law). So when water molecules (water vapor) are added to a given volume of air, the dry air molecules must decrease by the same number, to keep the pressure or temperature from increasing. Hence the mass per unit volume of the gas (its density) decreases.

    The density of humid air may be calculated as a mixture of ideal gases. In this case, the partial pressure of water vapor is known as the vapor pressure. Using this method, error in the density calculation is less than 0.2% in the range of −10 °C to 50 °C. The density of humid air is found by:

    http://en.wikipedia.org/wiki/Density_of_air

  41. Those popular greenhouse and blanket analogies are both totally bogus because they are woefully incomplete.

    As JoNova (maybe Curry) observed in some thread, the popular GHE is exclusively about radiation, LWIR, in, out, trapped, etc. Without water vapor a greenhouse is an oven. Water absorbs heat when it evaporates and releases heat when it condenses. And a little bit can carry mega-KJ of energy without changing the surrounding temperature. Water vapor is the only GHG that matters because it runs the entire show.

    The blanket analogy also ignores the power of water vapor. When you blanket your house with more insulation it doesn’t get hotter inside because the furnace thermostat cuts back the firing rate just as oceans and clouds moderate the atmosphere. Chop wood on a cold day while wearing a heavy “blanket” coat. What happens to the trapped heat? You sweat! And cool off! Your own personal water vapor thermostat. Powerful stuff, that H2O.

  42. Good work Willis Eschenbach, please do more.

    So, the planet is self regulating and clouds are important for weather. I’m glad that those lectures I had decades ago were correct all the time. Now, if only Environmental Terrorists, erm, I mean global warming enthusiasts could go back to school.

  43. Interesting as allways.
    I have only one problem Willis: How did the difference between cold and warm days started? Somehow the temperature must have been spreading at some time before it can narrow in. What goes up must come down.
    I hope for some explanation.

  44. 7.2.1.2 Effects of Clouds on the Earth’s Radiation Budget
    The effect of clouds on the Earth’s present-day top of the atmosphere (TOA) radiation budget, or cloud radiative effect (CRE), can be inferred from satellite data by comparing upwelling radiation in cloudy and non-cloudy conditions (Ramanathan et al., 1989). By enhancing the planetary albedo, cloudy conditions exert a global and annual short¬wave cloud radiative effect (SWCRE) of approximately –50 W m–2 and, by contributing to the greenhouse effect, exert a mean longwave effect (LWCRE) of approximately +30 W m–2, with a range of 10% or less between published satellite estimates (Loeb et al., 2009). Some of the apparent LWCRE comes from the enhanced water vapour coinciding with the natural cloud fluctuations used to measure the effect, so the true cloud LWCRE is about 10% smaller (Sohn et al., 2010). The net global mean CRE of approximately –20 W m–2 implies a net cooling.

    Clouds -20 W/m^2.

    CO2 2 W/m^2

    Hmmmmm.

  45. Great article Willis! It also made my mind wander back to a funny detail about K15. Is it still believed that higher CO2 concentrations influence night temperatures disproportionately and pre-dawn temps the most? Might that be one reason why K15 used pre-dawn temperature readings exclusively, to maximize possible temperature increases concurrent with increasing CO2?

    “To avoid complications from diurnal heating, only observations taken close to local dawn were
    used.” – from Karl et al. 2015 Part 2

  46. It does not provide evidence that the mechanism is cloud-based. That’s hard to establish with the TAO buoys because they don’t contain information on the cloud coverage.

    I tried to get that by comparing actual daily measured insolation to maximum measured insolation (per time of day and day of year, per buoy), but I do not think it worked well. Trying to tease out one mechanism in a setting where “regression to the mean” will almost certainly prevail as a result of many mechanisms isn’t a promising course.

    In a previous analysis, you showed that lower (higher) early am temperatures produced higher (lower) afternoon maximum temperatures. There, regression to the mean was not a problem to contend with.

    Good essay. Thank you again.

    It’s a big data set. I am glad that you are sticking with it.

  47. Willis, a letter to the editor of my newspaper in Australia (The Australian)
    gives you the thumbs up today.

    “Fred Cehak (Letters, 17/6), it would be a grave mistake to assert that people who do not hold formal science degrees (your armchair experts) are not capable of making valuable contributions to the global warming debate. As an example, go to the Watts Up With That? website and read the essays by Willis Eschenbach, a holder of no academic qualifications. I have five science degrees, and would not be able to hold a candle to the way that this chap can analyse data.

    G. Gillman, Townsville, Qld”

    I used to work with this guy. I only hold one science degree though, and was his Librarian.

  48. Space shuttle view of cloud systems forming by convection of air masses over the Pacific Ocean. Evaporation consumes heat and leads to surface cooling. Higher up condensation of the water
    vapour releases heat, which leads to warming of the atmosphere. By convection both heat and water vapour is removed from the surface and are transported up into the atmosphere. The picture covers an horizontal distance of about 40 km from left to right.
    Cloud albedo is a measure of the reflectivity of a cloud. High values mean that the cloud can reflect more solar radiation. Cloud albedo varies from less than 10% to more than 90% and depends on drop sizes, liquid water or ice content, thickness of the cloud, and the sun’s zenith angle. The smaller the drops and the greater the liquid water content, the greater the cloud albedo, all other factors the same.
    http://www.climate4you.com/index.htm

  49. Willis: Very interesting data, but it tells only part of the story. If a mechanism exists in the warmer part of the Equatorial Pacific that returns temperature to average, then how does the temperature ever move away from average? Your discussion starts at midnight on days when it is colder or warmer than average and follows the return towards average the next day. But what happened on the previous day that led to anomalous temperature at midnight? Why didn’t your mechanism prevent the anomaly from developing in the first place?

    One factor that might vary and produce anomalous temperatures is wind speed. The rate of evaporation depends on both surface temperature and surface wind speed.

  50. rgb, can not break away from presenting data when contrasted to other data sources does not hold up as far as showing CO2 is governing the recent temperature trends of the globe from 1850-present..

    The data sources I subscribe to all show a strong temperature correlation to solar variability with ENSO,PDO-AMO phase and volcanic activity superimposed upon the solar variability independent of CO2 .

    It is quite clear that CO2 when taken alone and plotted against the temperature does not correlate. This fact is further evidenced by this recent pause 1998- still going and when reviewing past recent warm periods such as the Minoan, Roman ,Medieval warm periods which were as warm or warmer then today with less CO2 in contrast to present day. This is quite clear when looked at objectively..

    If this present pause turns into a decline (which I expect will happen before this decade is out) then maybe finally some reality might come into the climate arena but in the mean time wishful thinking of a CO2/TEMPERATURE correlation with CO2 leading the way is going to persist.

    One last note is, one can say CO2 is correlated to temperature but not that temperature is correlated to CO2.

  51. This is rank amateur stuff. Where’s the customary statistical hand-waving; the “adjusted, gridded, homogenized, extrapolation” of measured data? Where’s the engine-manifold/ bucket thermometer bias taken into account? Properly analyzed, an alarming temperature hockey-stick must emerge from these buoys. That’s how you’ll know when you’ve “got it right”.

  52. Reblogged this on gottadobetterthanthis and commented:

    Willis’ article is well presented and insightful. The comments, particularly those of RGB, are quite valuable. Some of the comments are good examples of what not to do. Some are educational and valuable.

    Willis and RGB contribute greatly to WUWT, and they are among the greatest minds of our time. If you research the site, with the built-in search or your favorite search engine, you will find a wealth of knowledge and insight.

    You will understand the global climate better if you read this article and the comments. The time spent reading will prove worthwhile.

    While RGB points out that CO2 physically acts to increase global average surface temperature, Willis shows (in this and prior articles) that CO2 is not the only factor, and as RGB points out, more heat doesn’t necessarily mean hotter; it can instead mean faster, or slightly larger dissipative emergent phenomena.

    Carbon dioxide is an essential ingredient in life. We must have it, and it has been deficient in the environment throughout human existence. It is likely still deficient. CO2 is no more a pollutant than O2 and H2O. Oxygen is a killer. Water, even more so. We humans suffer more expense and direct tragedy already, directly due to these other two essential ingredients of life than any plausible scenario associated with CO2.

    We will burn all of the fossil fuels unless a genius breakthrough occurs. We will run out of all of it before CO2 even begins to become a true concern to the well being of humans and the biosphere.

    Mostly, I agree with RGB (and Willis routinely expresses full solidarity with this sentiment) when he says that climate related policies, and even the vast sums spent on climate research are harmful to the least among us. The Pope wants us to respect the poor. That starts not with only small kindnesses, but with cheap energy by every means available.

    RGB is correct when he says:
    “At heart, all poverty is energy poverty. The units of energy are the units of work, and work, one way or another, is wealth.”

    http://www.phy.duke.edu/~rgb/

  53. Using W.E.’s cloud forming mechanism as a governor, if it is too cool to form clouds, the governor has reached a limit of its range to control temperature. Without cloud, the sun has its maximum warming effect. In the case of Milankovic cycles, it would presumably not achieve a cloud-raising temperature at the greatest distance from the sun. On the warm end of the cycle, the formation of clouds to cool is a certain proposition. The governor, therefore is most effective at the warm end of the range and limited at the cool.

  54. Please use the comments to demonstrate your own ignorance, unfamiliarity with empirical data and lack of respect for scientific knowledge. Be sure to create straw men and argue against things I have neither said nor implied. If you could repeat previously discredited memes or steer the conversation into irrelevant, off topic discussions, it would be appreciated. Lastly, kindly forgo all civility in your discourse . . . you are, after all, anonymous. – Barry Ritholtz

    http://www.ritholtz.com/blog/2014/02/how-does-the-u-s-power-grid-work/

  55. Emergent excellency! More good work.

    There are those who have never held a hammer nor lived a real life who are going to continue to squirm over your posts!

    I simply smile! ;-)

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