Do Satellite Temperature Trends Have a Spurious Cooling from Clouds?

October 30th, 2014 by Roy W. Spencer, Ph. D.

The validity of the satellite record of global temperature is sometimes questioned; especially since it shows only about 50% of the warming trend as do surface thermometers over the 36+ year period of satellite record.

The satellite measurements are based upon thermal microwave emissions by oxygen in the atmosphere. But like any remote sensing technique, the measurements include small contaminating effects, in this case cloud water, precipitation systems, and variations in surface emissivity.

A new paper by Weng et al. has been published in Climate Dynamics, entitled Uncertainty of AMSU-A derived temperature trends in relationship with clouds and precipitation over ocean, which examines the influence of clouds on the satellite measurements.

To see how clouds and precipitation can affect the satellite temperatures, heres an example of one day (August 6, 1998) of AMSU ch. 5 data (which is used in both our mid-tropospheric and lower-tropospheric temperature products), and the corresponding SSM/I-derived cloud water for the same day:

Fig. 1. One day of AMSU limb-corrected ch. 5 brightness temperatures (top), and the corresponding SSM/I cloud water retrievals centered on the same day (August 6, 1998).

Fig. 1. One day of AMSU limb-corrected ch. 5 brightness temperatures (top), and the corresponding SSM/I cloud water retrievals centered on the same day (August 6, 1998).

As can be seen, the contamination of AMSU5 by cloud and precipitation systems is small, with slight cooling in deep convective areas, and no obvious cloud water contamination elsewhere (cirrus clouds are essentially transparent at this microwave frequency).

And even if there is contamination, what matters for tropospheric temperature trends isnt the average level of contamination, but whether there are trends in that contamination. Below I will discuss new estimates of both the average contamination, as well as the effect on tropospheric temperature trends.

The fact that our monthly gridpoint radiosonde validation shows an extremely high level of agreement with the satellite further supports our assumption that such contamination is small. Nevertheless, it is probably worth revisiting the cloud-contamination issue, since the satellite temperature trends are significantly lower than the surface temperature trends, and any potential source of error is worth investigating.

What Weng et al. add to the discussion is the potential for spurious warming effects in AMSU ch. 5 of cloud water not associated with heavy precipitation, something which we did not address 18 years ago. While these warming influences are much weaker than the cooling effects of precipitation systems (as can be seen in the above imagery), cloud water is much more widespread, and so its influence on global averages might not be negligible.

The Weng et al Results Versus Ours (UAH)

Im going to go ahead and give the final result up front for those who dont want to wade through the details.

Weng et al. restrict their analysis to 13 years (1998-2010) of data from one satellite, NOAA-15, and find a spurious cooling effect from cloud contamination in the middle latitudes, with little effect in the tropics. (They dont state how they assume their result based upon 13 years, even if it was correct, can be applied to 35+ years of satellite data.) Ive digitized the data in their Fig. 8, so that I can compare to our results (click image for full size):

Oceanic trends by latitude band in AMSU5 during late 1998 to mid-2010 in the Weng et al. study (top) and our own calculations (bottom), for "all-weather" and "clear-sky" conditions.

Fig. 2. Oceanic trends by latitude band in AMSU5 during late 1998 to mid-2010 in the Weng et al. study (top) and our own calculations (bottom), for “all-weather” and “clear-sky” conditions.

There are two main points to take away from this figure. First, the temperature trends they get at different latitudes for 1998-2010 are VERY different from what we get, even in the all-weather case, which is simply including all ocean data whether cloud-contaminated or not. The large warming signal we get in the tropics is fully expected for this limited period, which starts during a very cool La Nina event, and ends during a very warm El Nino event.

I have spent most of this week slicing and dicing the data different ways, and I simply do not see how they could have gotten the near-zero trends they did in the tropics and subtropics. I suspect some sort of data processing error.

The second point (which was the main point of their paper) is the difference in clear-sky versus all-weather trends they got in the middle latitudes, which is almost non-existent in our (UAH) results. While they estimate up to a 30% spurious cooling of warming trends from cloud contamination, we estimate a global ocean average spurious cooling of only -0.006 deg. C/decade for 1998-2010 from not adjusting for cloud-contaminated data in our operational product. Most of this signal is probably related to the large change in cloud conditions going from La Nina to El Nino, and so it would likely be even less for the 36+ year satellite record.

While I used a different method for identifying and removing cloud contamination (I use localized warm spots in AMSU ch. 3, they use a retrieval scheme using AMSU ch. 1 & 2), I get about the same number of data screened out (40%) as they do (20%-50%), and the geographic distribution of my identified cloud and precip. systems match known regional distributions. So I don’t see how different cloud identification methodologies can explain the differences. I used AMSU prints 10-21 (like our operation processing), as well as their restricted use of just prints 15 & 16, and got nearly the same results, so that can’t explain the discrepancy, either.

I have many more plots Im not showing relating to how cloud systems in general: (1) do indeed cause a small average warming of the AMSU5 measurements (by up to 0.1 deg. C); (2) less frequent precipitation systems cause localized cooling of about 1 deg. C; (3) how these effects average out to much smaller influences when averaged with non-contaminated data; and most importantly (4) the trends in these effects are near zero anyway, which is what matters for climate monitoring.

We are considering adding an adjustment for cloud contaminated data to a later version of the satellite data. Ive found that a simple data replacement scheme can eliminate an average of 50% of the trend contamination (you shouldn’t simply throw away all cloud-influenced data…we don’t do that for thermometer data, and it could cause serious sampling problems); the question we are struggling with is whether the small level of contamination is even worth adjusting for.

66 Responses to “Do Satellite Temperature Trends Have a Spurious Cooling from Clouds?”

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  1. Cunningham says:

    Dr. Spencer, why is it that RSS is showing no warming for nearly two decades? (In your opinion, what are they doing wrong?)

  2. Stephen Richards says:

    When I first saw this paper I thought it was an attempt by the climate gestapo to discredit the satelite data so that their modified surface data could become pre-eminent

  3. DougCo t t o n says:


    Of course their temperature trends are different – they have to fudge them, just as they have to fudge past data and totally ignore natural climate cycles – all in order to fool the world into believing they are right with their greenhouse conjecture.

    And it’s about time you realised, Roy, that water vapour cools in the real world, as real world temperature data confirms. You could do your own study in less than a day.

    As you add more water vapour more of it congregates below the “radiating altitude” (as does more carbon dioxide) because of the density gradient. So that altitude is lowered (not raised) and furthermore we all know that water vapour reduces the temperature gradient and thus the supported surface temperature.

    You Roy have produced no empirical evidence to support the GH conjecture. You have not proved water vapour warms or produced any valid SBL calculations that gel with the observed surface temperatures on Earth or Venus and so you don’t come anywhere near qualifying for the $5,000 reward I’ve offered, because the first requirement is a study with similar methodology to mine but showing water vapour warms, and warms to the huge extent that would be necessary if it were in fact causing most of the claimed “33 degrees” of warming as in IPCC documentation on their website.

    Critical to the IPCC “explanation” is the addition of back radiative flux to solar flux when doing SBL calculations for Earth’s surface temperature. The combined requirement for 288K (using emissivity 0.95) would be a mean of 370W/m^2 of thermal energy transferring out of the base of the atmosphere and into the surface. But, after 30% of solar radiation is reflected by the atmosphere, the mean solar radiation entering the atmosphere is about (0.7 x 1360)/4 = 238W/m^2. So how does the atmosphere add 55% to the incident energy and deliver more into the surface?

    Roy, Earth’s climate cycles correlate compellingly with the 934-year and superimposed 60-year cycles in the inverted plot of the scalar sum of the angular momentum of the Sun and all the planets.

    There is no measurable net trapping of thermal energy at TOA, where the difference in flux rarely varies 0.5%. Carbon dioxide does not act like a blanket, and nor does water vapour which keeps the world cooler.

  4. Locke says:

    Oh dear, Roy has been under-cooking his data by 30% ? This has been my fear for some time – that the respective RSS and UAH groups either don’t fully understand the limitations of their data or even if they do will not correct it due to fear of embarrassment.

    Roy has been extolling the virtues of the satellite data more recently but the more we learn about the data cleaning and sins of omission going on in the background the uglier it looks. As the great Richard Lindzen once said:

    “The technical details of satellite measurements are really sort of grotesque”

    We have the absurd situation where Roy is presenting global temperatures with no error bars even though he knows the process that goes into making the final sausage is a complete and utter mess.

    We had Roy saying for a while that UAH was superior to RSS as UAH used AQUA instead of NOAA-15 which was suffering from diurnal drift. Then Roy dumped AQUA and is now using NOAA-15 (amongst others). Data is being stitched together from multiple satellites, all drifting and decaying. We’ve got instrument heating problems, we’ve got cloud problems, we’ve got variable oxygen concentration problems, we’ve got algorithms galore that nobody has seen. The UAH and RSS teams can’t even agree why their data is different.

    Roy, you are to be commended for engaging with the public. A bit of debate strengthens us all. I’m a great believer in thesis, antithesis, synthesis. However, it only works if everyone agrees to be intellectually honest.

    PS. Peabody Coal cares for poor people.

  5. Alan says:

    OK, Climate Dynamics has published a paper. You, Dr. Spencer, have examined the paper, and based on the same supporting data sources have concluded the paper’s results are in error.

    For those of us who are engineers rather than research scientists, it would be interesting to hear how this discrepancy will be resolved…

  6. Truthseeker says:

    “especially since it shows only about 50% of the warming trend as do surface thermometers over the 36+ year period of satellite record”

    It is probably more due to data tampering of the land based record rather than any genuine measurement difference.

  7. Mark Luhman says:

    It may be data tampering or just poor data gathering, I have seen number they infill due to missing data some time it over 30%, how one would expect to get something useful out of such a mess is beyond me but hell it seems to support their theory of AGW so the go for it full speed, and God forbid someone question there methods or data after all the see and hear what they want to see and hear. Deliberate or not there is no excuse for such shoddy methods, all though that seem to be the trend in this modern world in almost all endeavors. Outcome based education in spades.

  8. Chris Schoneveld says:

    Roy, why didn’t they ask you as a reviewer of the paper?

  9. Alick says:

    Dr. Spencer, how can satellite information determine the origin (altitude) from where radiation is finally emitted from the atmosphere. Perhaps this doesn’t matter to you because of how you are using the satellite data.

  10. jimc says:

    We have a new re-definition of terms I havent seen before.

    The comments to The Weather Channel statement immediately devolved into an argument between climate change realists and skeptics.

    RWS is unrealistic.

  11. Aaron S says:

    As an outsider to the satellite data… I sincerely appreciate that you share counter arguments. I would not even hear these topics otherwise and i think it adds credibility.

  12. Andrew_FL says:

    Roy-Allow me to repeat a point I made last year when in an unpleasant conversation with Robert Way, he cited this very paper as evidence that there is still a significant cool bias in the UAH product:

    “It seems to me that to the extent there is significant cloud feedback/forcing, *of course* the temperature trends in clear sky regions would not be the same as those in cloudy regions. This would certainly confound any attempt to measure a bias in trends due to cloudiness: part of the signal would actually be *real*.”

    Am I wrong in thinking this?

    Much of what you say here confirms my suspicions then that this issue was not a priori reason to think UAH has a long term cooling bias. At least not one of any significant size.

    So much for Way’s “fairly strong evidence that TMT trends are biased low due to cloud and precipitation effects over the oceans.”

  13. DougCo t t o n says:

    however you look at it, the impact of 0.04% of carbon dioxide being doubled to 0.08% is infinitesimal, probably being less than 0.1 degree and maybe less than 0.01 degree of warming or cooling. You can put your own figures into this calculation:

    Start with the real world and assume there is 2% water vapour and 0.04% carbon dioxide. Assume the radiating altitude is 4.5Km and temperature gradient 7C/Km. Imagine replacing the 98% of other air molecules with CO2. The troposphere is a mean of 11Km high. It is unlikely that the radiating altitude would rise above 7Km. So multiplying the CO2 concentration by about 2,500 raises the radiating altitude 2.5Km. So just doubling it raises that altitude a mere 1 metre. Applying the temperature gradient, that 1 metre represents 0.007 degree of warming. But there is a cooling effect because carbon dioxide absorbs some incident solar radiation in which the 2.1 micron photons have about 5 times the energy of the 10 micron ones coming up from the surface. There is also a cooling effect due to the gradient being reduced by inter-molecular radiation. And there is a cooling effect due to greater expanse of vegetation which, in general has higher emissivity than soil and rock.

  14. KevinK says:

    Dr. Spencer wrote;

    “The satellite measurements are based upon thermal microwave emissions by oxygen in the atmosphere.”

    Very interesting, the satellites function by measuring microwave energy emissions (very smart and impressive, I do admire all the folks that made these measurements possible, Dr. Spencer, Dr. Christy, the engineers that built the “bird”, etc.). That would be energy being emitted to the energy free vacuum of space by the atmosphere of the Earth. I though one of the basic premises of the “GHE” was that the ONLY way for the Earth to “shed” energy to space was via “GHGs”? And that increases in “GHGs” reduced the “shedding” (loss/rate of cooling/etc) of energy away from the surface. BUT you are inferring the temperature of the surface of the Earth by intercepting some (a wee tee tiny little bit) of that energy flowing away as microwaves….

    Seems like some of that “trapped” heat figured out how to escape as microwaves… Really tricky stuff that heat/energy is, it always seems to find a way to escape to someplace where less energy is present, who knew….

    X-Rays, UV, Visible, NIR, MWIR, FIR, microwaves, all of those wavelength sub-specta always find a way to escape. Delayed a bit, for sure, but trapped ??? does not seem likely.

    Cheers, Kevin.

    • DougCo t t o n says:

      Yes Kevin, what really “traps heat” is gravity. If you visualised the graph of temperature v. altitude its gradient is induced by the effect of gravity acting on each individual molecule whilst in free path motion between collisions. The gravitationally induced temperature gradient is the very same state of thermodynamic equilibrium which the Second Law of Thermodynamics says will evolve. So the area under that graph represents the thermal energy that is permanently trapped by gravity in every planet’s troposphere, and even in its surface, crust, mantle and core. That is why it’s hotter than Earth’s surface at the base of the nominal troposphere of Uranus where there’s no direct solar radiation or any surface down there, 30 times further from the Sun than we are. Planetary surface temperatures are not primarily determined by direct incident radiation. There’s more in “Why It’s Not Carbon Dioxide After All” of course.

      • Phil R says:

        We did trick-or-treating tonight. You are spamming websites. d*ckh*ad.

      • DougCo t t o n says:

        And, Phil R greatly improving the level of scientific discussion thereon, steering people to a better understanding of thermodynamic equilibrium and its relevance to the greenhouse hoax. If you are incapable of entering into such discussions (because of a lack of understanding of relevant physics) then how about you keep your opinions to yourself? Read the discussion on The Air Vent for example.

        • Phil R says:

          I did, and I didn’t see a “discussion.” all I saw was more of your ranting. I don’t know why you can’t provide a concise, direct answer to a simple question. but then, I guess we’re all in the presence of unprecedented genius. The last person who went against the consensus and revolutionized physics was Einstein. I’m flabbergasted that science and society has muddled along for so long with such a “lack of understanding of relevant physics.” Then here you come along, the next Einstein, and can’t even provide a simple, non-aggressive explanation of your hypotheses or answer simple questions. When Einstein was wrong, he went back to the drawing board. Maybe you should back off the arrogance practice a little more humility.

  15. DougCo t t o n says:

    So are you going to report on this speech about fudged climate records addressed to the Australian Parliament?

    • Locke says:

      Dear Doug,

      I have it on good authority that Mr Christensen is as thick as a brick. However, if you insist, I will allow you to use the unhomogenised data. I hope you know that it shows a greater warming trend than the homogenised data……..Oops!

  16. Robert Way says:

    Aren’t the trends calculated from:
    October 26, 1998 to August 7, 2010 ?

  17. Bert Walker says:

    Dr Spencer,
    Is it possible for the satellite date to give regional surface or lower tropospheric temperature data? If so could that dat be used to aid “correction” surface temp data trends and help solve the problem on how do best do area weighting?

    There seems to be a paradigm that the satellite record should be corrected against terrestrial surface records in some of the comments above. Of course it is always wise to consider possibilities of bias in any data set, but it seems somewhat unreasonable to deny the stability, and quality of the satellite data which is inclusive of +/-85 deg.. such reasoning seems like the tail wagging the dog.

    In the press and on the internet there are reports that there has been much effort by your collogues to adjust various surface data sets to account for area weighted sampling, station location changes etc.. Possibly there have been attempts to bias the surface record to show an exaggerated trend. If one could use the lower troposphere satellite record to be the standard by which the data for land temperatures are “adjusted” in a uniform rational manor error could be minimized. Of course I know this would be limited from 1979 onward, and the satellite data sets would have to have sufficient resolution of the land area in question.
    If possible UAH data may provide a reasonable standard by which to make the adjustments to the sparse surface temp data set at least in regard to the problem of area weighting. What is your opinion?
    My apologies if you have covered this elsewhere.

  18. phi says:

    Dr Spencer,
    It seems that the divergence with RSS comes only from the land fraction. On the chart below, it would appear that the issue could come from a problem with UAH since 2005. What do you think?

    • Kristian says:

      Thanks, phi.

      Yes, this should make it even clearer to Roy that there is definitely something spurious happening suddenly in the latter half of 2005 (which needs to be investigated and corrected for):

      RSS has the same (only opposite) problem:

      There is no ‘gradual drift’. There is only the abrupt artificial step in 2005 …

      • Fonzarelli says:

        Kristian, above I only wanted to make sure that you understood where Dr. Spencer was coming from. Now, I’d like to get into the “meat and potatoes” of who is right and who is wrong here. I assume that you saw the graph that Dr. Spencer linked to in his comment above (UAH minus RSS). That graph CLEARLY shows a ‘gradual drift’ starting in the years immediately following 1998. What issue do you have with his graph?

        • Kristian says:

          Sorry Fonzarelli, but you’re seemingly not reading what I’m writing (yearly averages/smoothing of data vs. the actual data – what is it that you don’t get?), dismisses actual data (looks “suspicious” because it fits too well) and basically seems to be a Spencer fanboy (whatever he says is true and infallible and nothing can change that), so I find you an utterly uninteresting person to discuss this topic with. People can clearly see the data that is presented for themselves, drawing their own conclusions about what’s going on, without you flying around trying your best to divert their attention away from it. Bye.

          • Fonzarelli says:

            Kristian, Dr Spencer’s data is MONTHLY not yearly averages… Look, I’m not here to give you a hard time, and as “uninteresting” as I am, I really want to get your side of the story. I don’t “clearly see the data that” you present, but I do see what Dr Spencer is getting at. If your going to give a counter argument to what Dr Spencer has to say, than can you make it understandable as he has? So as it stands now, you’ve made the mistake that Dr Spencer’s data is yearly. It’s NOT, it’s monthly… So I’ll ask you the question once again: What issue do you have with his graph?

          • Fonzarelli says:

            So, kristian has apparently decided to ride off on his high horse thereby leaving questions unanswered and people unswayed. (no time for the uninteresting spencer fanboys) So I guess I’ll have to go with what I’ve got. And what have I got? He gives us a graph supposedly of UAH and RSS “actual” data superimposed. The two data sets look virtually the same. (so similar that I can’t even see kristian’s alleged shift circa 2005) He doesn’t explain where he got the data from nor what the data actually represents. Is this “actual” data available through either UAH or RSS? Is this data raw unadjusted data or is the only adjustment lacking that of monthly averaging? Until I get answers to these (and perhaps more) questions then how can I be swayed by what kristian has to say? Kristian, of what little I know about your comments, I DO like them. You think out side the box in what I think is a unique way. However, you don’t seem to argue your (very valid) points very well. You come across with all the eloquence of a teenager on pot. (i know, i used to be one) I recommend that you slow down and focus on making your arguments as clear as possible to all who may inquire. If your arguments are as good as you believe them to be, then you should have no fear in having people thoroughly inspect them. Unless you do that, your going to remain being a “kristian fanboy” marching to the beat of your own drum…

  19. Kristian says:

    What people like Fonzarelli seem to be completely oblivious to is how averaging and smoothing of data distorts and obscures what reality is trying to tell us, meaning, the information held by the actual data behind.

    You need to actually look at the data itself in order to be able to see what in fact it’s doing. The last thing you should do is smearing or corrupting the data into something that it’s not before you attempt to read anything from it, by first applying various statistical methods to it. You do not remove, change or average data if you don’t absolutely have to. Well, you can, but don’t expect, then, to be able to say anything meaningful about reality from it. What you in effect are looking at, are statistical artefacts.

    The exact same rule applies when looking at linear trends. Producing linear trend lines across a set of data doesn’t tell you anything about what’s really going on. Why? Because the statistical computation of the trend line is highly affected by what the data might do along the way, from start to end date. A low before the middle and/or a high after the middle, but start and end sections at the exact same level, and what do you get? An upward trend line purporting to show that temps have gone up. If you don’t see the data behind, then there is no way of telling why the trend might go up. What caused the dip in the first half of the time series? Some natural process? A short-term, transient effect? Similarly, what caused the peak in the latter half? You need to find out about these things before you can be certain that the trend line speaks the truth.

    Same with averages. WHY is the annual average higher in one dataset than in another for a particular year? What specifically happened during the year in question? Is it all down to noise? How to find out? LOOK AT THE ACTUAL DATA BEHIND!

    In conclusion, it is all too easy (and tempting) to get blinded by averages/smoothed data and trend lines and to think that these somehow portray the real world situation, when in fact they only obscure it. Why? Because it LOOKS so neat and orderly, so visually appealing and simple, but ends up HIDING actual data.

    I have to repeat the words of William M. Briggs:

    “If we want to know if there has been a change from the start to the end dates, all we have to do is look! Im tempted to add a dozen more exclamation points to that sentence, it is that important. We do not have to model what we can see. No statistical test is needed to say whether the data has changed. We can just look.”

    “Again, if you want to claim that the data has gone up, down, did a swirl, or any other damn thing, just look at it!


    “The various black lines are the actual data! The red-line is a 10-year running mean smoother! I will call the black data the real data, and I will call the smoothed data the fictional data. Mann used a low pass filter different than the running mean to produce his fictional data, but a smoother is a smoother and what Im about to say changes not one whit depending on what smoother you use.

    Now Im going to tell you the great truth of time series analysis. Ready? Unless the data is measured with error, you never, ever, for no reason, under no threat, SMOOTH the series! And if for some bizarre reason you do smooth it, you absolutely on pain of death do NOT use the smoothed series as input for other analyses! If the data is measured with error, you might attempt to model it (which means smooth it) in an attempt to estimate the measurement error, but even in these rare cases you have to have an outside (the learned word is exogenous) estimate of that error, that is, one not based on your current data.

    If, in a moment of insanity, you do smooth time series data and you do use it as input to other analyses, you dramatically increase the probability of fooling yourself! This is because smoothing induces spurious signalssignals that look real to other analytical methods. No matter what you will be too certain of your final results!

    Take heed, climate ‘scientists’.

  20. DougCo t t o n says:

    Clouds and water vapour all lead to cooler surface temperatures, not warmer ones as the IPCC would like you to be gullible enough to believe.

    The emissivity of water and water vapour are a next-to-useless figures when trying to calculate the temperature of any thin layer of a cloud or the atmosphere through which most of the solar radiation passes, just as we can’t determine easily what temperature solar radiation mostly passing through the thin surface layer of the ocean would affect its temperature. (These layers do not act like black or grey bodies.) Yet the IPCC authors think they can do so, and not only that, they add the back radiation which, as is well known, does not penetrate more than a few nanometres into the ocean. Then they fudge the back radiation figure so they get a total that gives them 288K with emissivity 0.95 and hence a total solar and back radiation flux of 370W/m^2 of which solar flux is only 163W/m^2. That’s laughable, because their atmosphere is supposedly somehow delivering 370W/m^2 when, after albedo considerations (say, 30%) is 55% more than the total solar flux of 238W/m^2 entering at the top. So the atmosphere is a good energy generator is it?

    • Gordon Robertson says:

      @Doug…”…back radiation which, as is well known, does not penetrate more than a few nanometres into the ocean”.

      I doubt if any of the BR is effective beyond a few centimetres from the radiation source. Wood claimed circa 1909 that surface radiation is ineffective more than a few feet above the surface.

      If you take the ring on an electric stove and turn it up till it’s cherry red and radiating 1500 watts, then you touch it, the heat will cook the flesh on your finger via conduction. Almost the same if you hold your finger a centimetre above the red hot ring where IR will cook it by exciting the atoms in your flesh.

      Pull your hand back a foot and you can still sense the radiation as it excites the atoms in your skin. Pull it back 5 feet and I doubt if you can feel it at all. That’s how quickly intense radiation drops off over a short distance.

      What is the intensity of surface radiation? Is it 260 watts/m^2? What would that be power-wise in a circle the size of a stove ring on the surface? I know one thing, you can stand on the surface barefoot and it feels cool, or cold, depending on the time of year.

      How is such a low energy source able to warm GHGs more than a few feet above the surface? And how can energy absorbed by GHGs back-radiate enough energy to be effective more than a few centimetres from the GHG source?

      Alarmists seem to think there is a one to one relationship between photons of IR emitted from the surface and the same photons absorbed by a GHG molecule. That is science fiction. No one has a clue how radiation from a surface atom reaches a molecule of GHG in the atmosphere.

      For one, a photon is a fictitious particle of EM that was defined as a particle with momentum but no mass. Eh? What kind of particle has no mass?

      The anthropogenic theory relies on a whole lot of naive assumptions. One of them is that radiation is the main mode of heat transfer in the atmosphere.

      • DougCo t t o n says:

        Gordon, don’t make too much of the radiation falling off as the square of the distance, as it indeed does from a point source. However, from an extended planar source at some given altitude the radiation to the extended Earth’s surface falls off only with the distance, not the square thereof. That said, the back radiation can only slow the portion of surface cooling that is by radiation.

        Back radiation cannot …

        (a) slow non-radiative and evaporative surface cooling
        (b) assist the Sun to raise the temperature to a higher daily maximum
        (c) affect the temperature at the base of the troposphere which is supported by the gravitationally induced temperature gradient and which slows and even stops the surface cooling in the early pre-dawn hours on a calm night.

        Low frequency radiation is not absorbed in a warmer source by the normal atomic absorption process. Its electro-magnetic energy is not converted to thermal energy in the target. All this was in my March 2012 paper. We can see evidence when a plastic container is not warmed in a microwave oven, though it would be in solar radiation. Water is not an exception as it is not warmed by atomic absorption, but by whole molecules flipping in synchronisation with each passing (micro) wave in a resonance process.

    • Gordon Robertson says:

      @Doug…The paper by Gerlich and Tscheuschner debunks both greenhouse theory and the AGW theory. G&T are experts in thermodynamics and their paper very clearly lays out the math and physics behind their arguments.

      Page 16…Heat is the kinetic energy of molecules and atoms and will be transferred by contact or radiation.

      P32 – describes the experiment by Wood (1909) which Roy referenced in a recent article.

      p78 Rahmstorf and 2nd law…the quotation from Rahmstorf is pretty well what Roy is claiming.

      Reply from G&T…”Obviously, the authors are confusing energy with heat”.

      p59 – with regard to radiative balance diagrams a la Kiehle-Trenberth…”…in the literature on global climatology it is not explained, what the arrows in “radiation balance” diagrams mean physically”.

      That’s probably because Trenberth admitted they have no evidence to back it. It’s all based on theory.

      • DougCo t t o n says:

        I agree with much of what Gerlich and Tscheuschner say, and their conclusion is “Already the natural greenhouse effect is a myth beyond physical reality. The CO2-greenhouse effect, however is a mirage …” which is not what Roy agrees with.

        In any event, whereas they only got as far as saying planetary temperatures cannot by determined from radiation levels (with which I agree but Roy mocked me when I wrote this) they have not taken it as far as I have in my book, from which hypothesis it is indeed possible to calculate planetary tropospheric and surface temperatures.

  21. Gordon Robertson says:

    Weng…the author of the article…works for NOAA. NOAA launched the satellites from which Roy and John Christy get the data for their data sets.

    NOAA is in denial about their own satellite data. They represent the IPCC POV on anthropogenic warming and they have worked with NCDC to seriously cut back the number of reporting surface stations.

    The author of the site claims in bold face, “NOAA / NCDC have Fudged and Corrupted the Input Data Series”

    It is little wonder to me that they are attacking their own satellite temperature data that contradicts their fudged surface station data.

    The author of chiefio goes on:

    The GHCN input data to GIStemp has issues (they -NOAA/NCDC- deleted 90% or so of the thermometers between about 1990 and 2009) with those deletions focused on cold places. This is the second set of reports most folks ought to read. We explore that here:

  22. Roderic Fabian says:

    Considering all the serious problems there are with the surface data, especially limited coverage and falling numbers of stations, you would expect satellite data to be the gold standard for global temperatures. Instead they are trying to discredit it with spurious analyses. Why? Because, like paper ballots in an election, there is a lot more room for low tech monkey business with surface data. We can watch them fudging the data year by year. Every year they have made early temperatures cooler and so the warming trend seems greater. Has there ever been any detailed explantion published for how they extrapolate station data to grid squares with no stations? I only know of a few cases in which that sort of extrapolation has been tested for validity, and it can be badly off, as was the case in Antarctica.

    The surface station numbers are in the hands of people who are more advocates than scientists. “Scientists” who chain themselves to the gate at the White House to protest the coal industry. As we have seen in the news, such people think nothing of lying to get the policies they want. They can make the mean surface temperature out to be anything they want.