New Santer et al. Paper on Satellites vs. Models: Even Cherry Picking Ends with Model Failure

by Roy W. Spencer, Ph. D.

(the following is mostly based upon information provided by Dr. John Christy)

Dr. John Christy’s congressional testimonies on 8 Dec 2015 and 2 Feb 2016 in which he stated that climate models over-forecast climate warming by a factor of 2.5 to 3, apparently struck a nerve in Climate Consensus land.

In a recently published paper in J. Climate entitled Comparing Tropospheric Warming in Climate Models and Satellite Data, Santer et al. use a combination of lesser-known satellite datasets and neglect of radiosonde data to reduce the model bias to only 1.7 times too much warming.

Wow. Stop the presses.

Part of the new paper’s obfuscation is a supposed stratospheric correction to the mid-tropospheric temperature channel the satellite datasets use. Of course, Christy’s comparisons between models and satellite data are always apples-to-apples, so the small influence of the stratosphere on the MT channel is included in both satellite and climate model data. The stratospheric correction really isn’t needed in the tropics, where the model-observation bias is the largest, because there is virtually no stratospheric influence on the MT channel there.

Another obfuscation is the reference the authors make to previously-published radiosonde comparisons:

“we do not compare model results with radiosonde-based atmospheric temperature measurements, as has been done in a number of previous studies (Gaffen et al. 2000; Hegerl and Wallace 2002; Thorne et al. 2007, 2011; Santer et al. 2008; Lott et al. 2013).”

Conveniently omitted from the list are the most extensive radiosonde comparisons published (Christy, J.R., R.W. Spencer and W.B Norris, 2011:The role of remote sensing in monitoring global bulk tropospheric temperatures. Int. J. Remote Sens. 32, 671-685, and references therein). This is the same kind of marginalization I have experienced in my previous research life in satellite rainfall estimation. By publishing a paper and ignoring the published work of others, they can marginalize your influence on the research community at large. They also keep people from finding information that might undermine the case they are trying to build in their paper.

John Christy provides this additional input:

My testimony in Dec 2015 and Feb 2016 included all observational datasets in their latest versions at that time. Santer et al. neglected the independent datasets generated from balloon measurements. The brand new “hot” satellite dataset (NOAAv4.0) used by Santer et al. to my knowledge has no documentation.

Here is my testimony of 2 Feb 2016 (pg 5):

I’ve shown here that for the global bulk atmosphere, the models overwarm the atmosphere by a factor of about 2.5. As a further note, if one focuses on the tropics, the models show an even stronger greenhouse warming in this layer … the models over-warm the tropical atmosphere by a factor of approximately 3.

Even when we use the latest satellite datasets used by Santer, these are the results which back up my testimony.

Global MT trends (1979-2015, C/decade) & magnification factor models vs. dataset:
102ModelAvg +0.214
___UWein(2) +0.090 2.38x radiosonde
_____RATPAC +0.087 2.47x radiosonde
_______UNSW +0.092 2.33x radiosonde
____UAHv6.0 +0.072 2.97x satellite
____RSSv4.0 +0.129 1.66x satellite
___NOAAv4.0 +0.136 1.57x satellite
________ERA +0.082 2.25x reanalysis

The range of model warming rate magnification versus observational datasets goes from 1.6x (NOAAv4.0) to 3.0x with median value of 2.3x for models warming faster than the observations.

Tropical MT trends (1979-2015, C/decade) & magnification factor models vs. dataset:
102ModelAvg +0.271
___UWein(2) +0.095 2.85x radiosonde
_____RATPAC +0.068 3.96x radiosonde
_______UNSW +0.073 3.69x radiosonde
____UAHv6.0 +0.065 4.14x satellite
____RSSv4.0 +0.137 1.98x satellite
___NOAAv4.0 +0.160 1.69x satellite
________ERA +0.082 3.31x reanalysis

Range goes from 1.7 (NOAAv4.0) to 4.1 with a median value of 3.3 for the models warming faster than the observations.

Therefore, the testimony of 2 Feb 2016 is corroborated by the evidence.

Overall, it looks to me like Santer et al. twist themselves into a pretzel by cherry picking data, using a new hot satellite dataset that appears to be undocumented, ignores independent (radiosonde) evidence (since it does not support their desired conclusion), and still arrives at a substantial 1.7x average bias in the climate models warming rates.

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85 thoughts on “New Santer et al. Paper on Satellites vs. Models: Even Cherry Picking Ends with Model Failure

  1. channel the satellite datasets

    All becomes clear. This isn’t science, its sceance!

    Channelling the Datasets
    “Knock knock!”
    “Whose there?”
    “Only a poor disembodied dataset. Please help me!”
    “What’s in it for me?”
    “Only Ectoplasm.”

    • “Who’s there?” [not “Whose”]

      When I was a teenager and first heard of ectoplasm, I envisioned it as a shapeless blob of ghostly shimmering purple stuff, glowing in the dark and breathing softly, just at the edge of audibility.

      What is the current description of ectoplasm?

  2. Don’t worry. They will use the (Christy, Spencer, Norris 2011) data posthumously. When your skeleton can’t say “I told your so”,

  3. If you twist and torture the data sufficiently, you will finally get something that fits your hypothesis. This process can hardly be called “science” since it bears no resemblance to the scientific method. It amazes me how Santer and his ilk can sleep at night.

    Instead of perverting the scientific method to attempt to show that obviously failing models are not as bad as Dr. John Christy presented, why don’t Santer et al not admit that there are significant problems with climate models and spend their time finding out what is wrong with the models so that they can be fixed. By assuming that the models are correct and trying to twist empirical data to conform with their assumptions, Santer et all are reinforcing the opinion of people who have been saying that climate science has much more to do with politics than with either science or the climate.

    • You are perfectly right, of course, that this is not proper science.

      It should be trivially easy to “fix” the models so as to follow the observed trend more closely; there must be a plethora of tunable input parameters to play with, and a much better fit to the data can probably be obtained just tweaking these parameters, without rewriting any actual code.

      However, doing so would highlight that the prognostications are based on arbitrarily chosen numbers, not on exact science, and it would amount to a public admission of error. To them, it is about them, not about science.

      • @Michael Palmer

        “It should be trivially easy to “fix” the models …”

        My ignorance may be showing here, but if we’re talking CMIP models, as “selected” by the IPCC, isn’t an acceptance criterion that they have to follow the IPCC script: that a doubling of CO2 will cause a temperature rise of …?

        Maybe that’s the trivial fix required – remove that obviously incorrect “hallowed” input and see if they come anywhere near matching reality.

      • “It should be trivially easy to “fix” the models …”

        “fixing” the models so they will match trends doesn’t mean the models will be right, or be able to predict future trends.

  4. I’ve never seen a Susan Solomon paper I can stomach.

    Benjamin D. Santer* and Susan Solomon
    Massachusetts Institute of Technology, Earth, Atmospheric, and Planetary Sciences, Cambridge, MA 02139, USA.

    Giuliana Pallotta
    Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.

    Carl Mears
    Remote Sensing Systems, Santa Rosa, CA 95401, USA

    Stephen Po-Chedley and Qiang Fu
    Dept. of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA.

    Frank Wentz
    Remote Sensing Systems, Santa Rosa, CA 95401, USA.

    Cheng-Zhi Zou
    Center for Satellite Applications and Research, NOAA/NESDIS, Camp Springs, Maryland 20746, USA.

    Jeffrey Painter, Ivana Cvijanovic, and Céline Bonfils
    Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.

  5. It appears that Santer is auditioning for a job in the new Clinton Administration. You would figure his rewrite of the technical report from 20 years ago would give him the inside track.

    • Yes. CoP1 was 20 years ago in July. Christy challenged Santer’s data set back then but to no avail. The Clinton admin came on board with binding commitment on the basis of Santer’s work towards IPCC detection finding. Now possibly a new Clinton and still Santer and still Christy. Plus ça change, plus c’est la même chose.

  6. And the global warmists never mentioned global warming during this entire ‘election’ mess. Nor has the media asked about it.

    • Hillary made a mention a few weeks ago, something about “we can’t allow a climate denier into the white house, ever”. But she wants to bring people together. Another lie, apparently.

    • Yup. After fiddles, about as wrong on the tropical troposphere hotspot as on ECS in CMIP5: observed ~1.65 (e.g. Lewis and Curry 2014) vs. model median 3.2.

      • ristvan,

        Lewis & Curry, 2014, start out by assuming that all the reported warming between their base and final periods is caused by us. That’s how they get their climate response/sensitivity values.

      • Kristian

        I don’t understand what you say. If all warming between their preferred1859-1882 base period and 1995-2011 final period is attributed to AGHG then that would maximise the sensitivity surely? Having said that I don’t see what you say having anything to do with what they did. Are you sure you aren’t confusing this with the steps taken to find base and final years where the volcanic, SOI and AMO influences are basically similar?

      • HAS, you say:

        “If all warming between their preferred 1859-1882 base period and 1995-2011 final period is attributed to AGHG then that would maximise the sensitivity surely?”

        Yes, exactly. But they have no way of knowing that all warming between those two periods was caused by “AGHG”. So what they do is simply assume it was. Which is pretty unscientific …

        In order to credibly discuss a positive “climate sensitivity” to the atmospheric concentration of CO2 in the first place, you NEED to have it empirically established that some “global warming” was/is caused specifically as a result of the rise in the atmospheric concentration of CO2. Otherwise you’re just guessing based on cherry-picked “All-Else-Being-Equal” theoretical musings …

        No such empirical evidence exist.

  7. Since the warmer tropics demonstrate the biggest difference between models and reality it supports the views of Dr. William Gray that convection and water vapor provide negative feedback. As one moves away from the tropics there is less heat and weaker convection except at frontal boundaries and therefore lower feedback.

    Now all these folks need to do is add this negative feedback to their models and they might actually be able to model our atmosphere. As if ….

  8. Dr Spencer & Christy,
    The main shortcoming with your comparisons between observations and models, is that the TMT and TLT layer are wide and a mix of troposphere and stratosphere. Radiosondes do have vertical resolution but you destroy that by emulating TMT etc. The satellite era is also too short and start with a warm period around 1980, when temperatures had made a big leap up from the cool mid-seventies.
    With radiosonde datasets it is possible to separate the atmosphere in distinct layers (unlike TMT) and also extend the model/obs comparison to a slightly longer period. Here is my attempt:

    It shows that the observed warming in the free troposphere follow the models relatively well. As measured by the trend, the warming is 80% of the model mean trend. Right now the observed temperature is way over the model mean due to the el Nino.
    The trend in the tropopause is flat unlike the models, and the lower stratosphere is cooling much faster than the model mean. The main discrepancy between models and observations is in the stratosphere, not in the troposphere. The models may have the wrong prescription of stratospheric ozone, but stratospheric cooling can also be a “fingerprint” of increased greenhouse effect.

    Please don’t exaggerate:
    No way that the tropospheric warming is 3 times larger in the models..
    Not even 1.7 times as suggested by Santer et al..
    More likely 1.25 times..
    Go out and find the reason why models are bad in the stratosphere instead..

    • Your post begs the question regarding the validity of the CMIP5
      ensemble and average. Please demonstrate that the average
      has any statistical significance whatsoever.

    • O R
      Thanks for that. I believe that the stratosphere was where we saw those cloverleaf type jet streamers patterns in the sky last summer. Maybe they are ignoring it because it is a telling tale.

      • Rather, O R, I’m suggesting that models are predictively useless, that consensus climate modelers are engaged in nonsense, and that your recourse to climate models as proof or validation of anything is hopelessly wrong.

        All the rest is your diversionary invention.

    • O R, it’s easy enough to tune CMIP5 models to reproduce whatever observable one likes. Tuning parameters to reproduce observables produces lines that have no explanatory value

      Not one of your CMIP5 projections includes uncertainty bars. Including propagated uncertainty would show that not one of your CMIP5 lines has any physical meaning at all. Your lines prove nothing whatever about consonance of models with physical reality.

      • Pat Frank,
        If it is easy to tune the CMIP5 output to whatever observable, why then have the model makers failed to tune their models to fit UAH TLT?

        If you want the spaghetti, it is easy to project it over my graph. TLT is about the same as 850-300 mbar, at least in trend. I’ll stick with the model mean (taz mean of 37 models from Knmi climate explorer). When using ensembles for prediction, the mean or median represents the most likely outcome.
        BTW, the 1979-1983 base period used in the S&C chart above, give observations a handicap of about 0.2 C (push them down) vs the models (at least in 850-300 mbar).

      • O R, “the spaghetti is not a measure of physical uncertainty. It only indicates model variability. Your temperature projections range across 36 years. The immediate physical uncertainty of your projections, due to propagated CMIP5 long-wave average cloud forcing error alone, will be about ±2 C in 1971, and by 36 years will be about ±10 C.

        Your lines are physically meaningless.

      • I’ll let other people deal with the complex physics. This is simple validation. Can the models predict the climate change or not? The models cannot predict UAH v6 TLT, most certainly not after year 2000, but they can decently predict the warming in the free troposphere as measured by radiosonde datasets.

      • O R, that plot is not physical validation at all. It merely shows that models can approximately reproduce themselves.

        I’m not talking “complex physics.” I’m talking physical error analysis; something no climate modeler seems to understand at all.

        Every single one of those individual projections should have physical uncertainty bars. However, they do not.

        The uncertainty bars of each individual projection from tropospheric thermal cloud forcing error would be about ±2 C at 1970, and about ±10 C at 2030. The uncertainty about the mean projection would be the r.m.s. of the uncertainties about each projection; also about ±2 C and ±10 C, respectively.

        The uncertainty bars, in other words, go right off the page.

        Here’s a video of my recent conference talk about uncertainty in model air temperature projections:

        They’re physically meaningless. Your plots are physically meaningless.

      • I suggest that you contact Spencer & Christy and urge them not to use comparisons between observations and models, because the physical uncertainties of the latter are so large that the comparisons are meaningless.
        What you are suggesting is essentially that Christy’s testimony before congress is meaningless and unprofessional..

      • Rather, O R, I’m suggesting that models are predictively useless, that consensus climate modelers are engaged in nonsense, and that your recourse to climate models as proof or validation of anything is hopelessly wrong.

        All the rest is your diversionary invention.

    • The satellite era is also too short

      But starting in 1970 is fine, apparently!

      ROFL

      Since 1979, UAH 6.0 TLT trend is 0.12C/decade and RSS is 0.13C, both well below the CMIP5 figure of 0.25C

      • RSS TLT 3.3 is no longer endorsed by RSS due to drifts, and UAH 6 beta is even lower. A RSS TLT made with the UAH v6 TLT formula have a trend of more than 0.20 C/decade. Ratpac A is 0.19 C/ decade in the satellite era.
        1970 is a good starting point. The warming started in the late seventies, do you want to cherrypick away that? I could go back to 1958 but it doesnt add anything, no warming, a volcanoe, no difference between models and observations..

      • O R: once again, you are in the wrong area, I’m afraid. All is about the t r o p i c a l hotspot in the upper troposphere. When you can’t switch to this, please stop the red herrings…

      • Please read the blog post again and try harder. It’s about both global and tropical troposphere temperatures. I have only focused on global so far..

      • So please stay focused on the right think:

        This was the figure in question from the testimony of John Christy. See the headline! Lost in reality?

      • Please read Christy’s latest testimony:
        http://docs.house.gov/meetings/SY/SY00/20160202/104399/HHRG-114-SY00-Wstate-ChristyJ-20160202.pdf

        First figure is global TMT. Using the broad unphysical TMT layer is the cheap “trick”. Mixing cool stratosphere with warm troposphere, and use this mix to suggest that the troposphere warming is only one third of the modelled, that is not correct and not a sign of competence.
        The right answer, as I pointed out in my first comment with the chart, is that the stratosphere is cooling much faster than the models..

    • As far as I saw the comparison of Christy refered to the tropics, not to the globals as you show it in your figure. Please try once again and select “tropics” for Ratpac and CMIP5.

      • O R: It seems to me the data are against you:

        In the tropics the slope of the trend of the lower troposphere ( 850 mb…400 mb, red) is much lower then the slope of the upper troposphere ( 300…100 mb, blue). It’s the opposite of what is expected by models?

      • frankclimate,
        If you want to find the elusive tropical hotspot, compare upper troposphere 400-300 mbar with lower troposphere 850-700 mbar. A more pronounced tropical hotspot can be found in RAOBCORE and IUKv2, or the ERA-interim and Merra2 reanalyses

    • These are model runs of the atmospheric warming profile expected due to a doubling of CO2 and feedbacks alone:

      It’s not happening.
      The explanation can be found at Climate4you — global temperature (for non-scientists like me).

      • The elusive ‘hotspot’ is a cornerstone of the dangerous AGW theory and if they can’t find it in the direct temperature data it’s only to be expected that the believers will go to extraordinary lengths the manufacture it somehow, using roundabout techniques, wind sheer etc. in Sherwood’s case (above).
        The expected warming at the 9km – 12km level 20N – 20S, two to three times that at the surface, is not happening according to millions of radiosonde direct temperature measurements:

        (climate4you).

      • Chris H,

        That’s correct. As Prof McKitrick showed, there is no ‘hotspot’:

        So Toneb is once again in error. The ‘hotspot’ was just another prediction that never happened, despite the one-third rise in (harmless and beneficial) CO2.

      • “The elusive ‘hotspot’ is a cornerstone of the dangerous AGW theory and if they can’t find it in the direct temperature data it’s only to be expected that the believers will go to extraordinary lengths the manufacture it somehow, using roundabout techniques, wind sheer etc. in Sherwood’s case (above).”

        First of all it is not a “cornerstone” of AGW theory. Warming in the upper trop would occur in the tropics with any causation of GW. What is a “cornerstone” is stratospheric cooling – that can only happen via GHG reducing in cooling rate of climate to space.

        And do you see that on the image I posted?

        Also allusion to deceit and fraud from climate scientists says more of you than any other comment you may make.
        Well done.

      • Toneb, you say:
        “What is a “cornerstone” [of “AGW theory”] is stratospheric cooling – that can only happen via GHG reducing in cooling rate of climate to space.”

        Perfect! That means that “AGW theory” is falsified in more ways than one. According to YOUR interpretation of “AGW theory”. But what it also means is that you do not understand what “AGW theory” is saying about “stratospheric cooling”. It ALSO means that you don’t have a clue about what might cool the stratosphere.

        Three in one! Well done.

      • “Perfect! That means that “AGW theory” is falsified in more ways than one. According to YOUR interpretation of “AGW theory”. But what it also means is that you do not understand what “AGW theory” is saying about “stratospheric cooling”. It ALSO means that you don’t have a clue about what might cool the stratosphere.

        Three in one! Well done.”

        Ah, another Sky-Dragon slayer.
        Splendid hand-waving my friend.
        Signifying nothing.
        (Macbeth Act 5, Scene 5)

        Would you care to point to some science that says AGW theory does not induce stratospheric cooling?
        Would you care to link to science that says that a hot-spot would NOT occur under any means of climate warming?
        (you do know why it should occur – Google if not).

        And what was the 3rd?

        The 2 above can be seen on the image I posted … but of course you’re another that wears bottle-bottomed glasses.

      • > That means that “AGW theory” is falsified in more ways than one.

        Here’s warming for a doubling of CO2 according to GISS ModelE:

        And here’s warming for a 2% increase according to GISS ModelE:

        Clearly, the “missing” hotspot means that the Sun cannot possibly warm the planet.

      • Toneb, you say:

        Would you care to point to some science that says AGW theory does not induce stratospheric cooling?

        Uhm, where exactly did I claim that “AGW theory” doesn’t say more CO2 in the atmosphere should induce stratospheric cooling? What I wrote was this:
        “(…) you do not understand what “AGW theory” is saying about “stratospheric cooling”.

        A direct response to your claim: “(…) stratospheric cooling (…) can only happen via GHG reducing in cooling rate of climate to space.”

        This is NOT how the “AGW theory” explains stratospheric cooling as a result of more atmospheric CO2, Toneb.

        I also wrote: “(…) you don’t have a clue about what might cool the stratosphere.”

        A direct response to the very same claim: “(…) stratospheric cooling (…) can only happen via GHG reducing in cooling rate of climate to space.”

        No. This ISN’T the only way that stratospheric cooling may occur, Toneb. In fact, as already pointed out to you, it isn’t even the “AGW theory” way …

        Would you care to link to science that says that a hot-spot would NOT occur under any means of climate warming?

        Where exactly did I even mention the “Hot Spot”?

        And what was the 3rd?

        First of all, the Hot Spot wasn’t the second, as I didn’t even mention it.

        Go through my comment again, and you will see.
        The 1st one: “Perfect! That means that “AGW theory” is falsified in more ways than one. According to YOUR interpretation of “AGW theory”.”
        The 2nd one: “But what it also means is that you do not understand what “AGW theory” is saying about “stratospheric cooling”.”
        And the 3rd one: “It ALSO means that you don’t have a clue about what might cool the stratosphere.”

        Pretty straightforward, really.

      • I am pretty sure that Toneb understands what may cause stratospheric cooling. Ozone depletion is one such thing. However, stratospheric ozone has not declined since the late nineties, but is rather recovering slowly. Anyway, the stratosphere is still cooling, what may cause that?? May increased greenhouse effect serve with some explanation…?

      • O R, you say:

        I am pretty sure that Toneb understands what may cause stratospheric cooling.

        Well, apparently, he doesn’t. Because what he says is: “What is a “cornerstone” [of “AGW theory”] is stratospheric cooling – that can only happen via GHG reducing in cooling rate of climate to space.”

        Stratospheric cooling isn’t happening because “GHGs” reduce Earth’s cooling rate to space.

        Ozone depletion is one such thing.

        Yup. Primarily in the lower stratosphere, though.

        However, stratospheric ozone has not declined since the late nineties (…)

        And neither has the temperature in the lower stratosphere (since about 1994-95):

        Anyway, the stratosphere is still cooling (…)

        Not in the lower part. But, yes, higher up it seems to be.

        May increased greenhouse effect serve with some explanation…?

        No. An increase in the stratospheric content of CO2, however? Yes. Likely so.

        Why do you think that is, O R? And how would this circumstance be completely detached from what’s going on in the troposphere below?

      • No, the stratosphere is still cooling on all levels, despite a slow ozone recovery the last twenty years. Watch STAR: s Amsu-only dataset and remember that channel 9 ( and possibly 10) has a considerable amount of tropospheric warming contamination:

        ftp://ftp.star.nesdis.noaa.gov/pub/smcd/emb/mscat/data/AMSU/AMSU_v2.0/AMSUA_only_Monthly_Layer_Temperature/AMSU_L3_Inter-Bias_vs_Merged_Trend_Ch9-15.jpg

        The stratospheric cooling can be understood in two ways. There is a AGW- caused energy imbalance, trapping heat in the system below the tropopause at a rate of about 1 W/m2. There is also a kind of inverse greenhouse effect in the stratosphere.
        rogertaguchi once wrote a good explanation on this:

        “The first thing to understand is that the MODTRAN spectrum available at https://en.wikipedia.org/wiki/Radiative_forcing very closely models an actual spectrum taken by a satellite looking down near Guam [see the third Fig. at http://climateaudit.org/?p=2572 . The models in molecular spectroscopy are really “settled science” (unlike those of the IPCC predicting climate change).
        The next thing to understand is that these are “net absorption” spectra [ask any competent chemist], not “emission spectra”. This is the difference between the Fraunhofer lines in the Solar spectrum and the bright line emission spectra of a hydrogen discharge tube (or the bright mercury lines seen over diffuse phosphor emission from a fluorescent light – use any small hand spectroscope to see these).
        I used the adjective “net” for absorption because there is a CO2 emission spectrum (at 220 K) at central frequencies superimposed on a CO2 absorption ditch that would otherwise go all the way down to zero transmission in the troposphere. This 220 K CO2 emission is powered by incoming Solar UV and visible radiation absorbed by ozone in the stratosphere and then transferred during inelastic molecular collisions to the main molecules N2, O2 and Ar that make up more than 99.9% of the atmosphere. A tiny part of that total energy excites CO2 molecules which can emit infrared (IR) frequencies around 667 cm^-1, and these are registered in the spectrum.
        Doubling CO2 will increase absorption in the troposphere, and this occurs in the wings of the spectrum, centered at 618 and 721 cm^-1, since the main increase is in sidebands where the absorbing molecules are in the first excited state (about 3% of all CO2 molecules), and not in the ground (lowest energy) state, which is involved in the 667 cm^-1 absorption. 3% relative concentration means that these sideband frequencies are not “saturated”, so doubling CO2 will have a significant effect on absorption. You can see this extra absorption in the MODTRAN spectrum (it is the area between the green and blue curves that represent absorption at 300 ppmv CO2 and 600 ppmv). Most of the absorbed energy is transferred to the main molecules of the air (N2, O2, Ar) that are non-polar, with zero electric dipole moment, and therefore cannot and do not emit or absorb any significant IR photons. Because the heat capacity at constant pressure for linear molecules like N2, O2 and CO2 is Cp = 7k/2 per molecule, where k is Boltzmann’s constant, most of the heat content (enthalpy) is stored in non-radiating molecules that outnumber CO2 by 2500:1 (at 400 ppmv CO2). This is the molecular explanation for the greenhouse effect. This extra absorption would mean an energy imbalance: a decreased TOA (Top Of the Atmosphere) flux would no longer balance the net incoming Solar flux (after reflection or the albedo has been taken into account), so the same incoming flux would warm up the surface until the TOA flux again balanced the net incoming. The principle of adding equal amounts of energy to all molecules in the same energy state means that all molecules in a column of the troposphere (which have the same total U + H, where U is the gravitational potential energy and H is the enthalpy) will on average increase by the same temperature T [ since “delta H” = Cp .(“delta T”) ]. Therefore the new temperature profile will have the same slope as previously [the lapse rate remains at -6.8 K/km], but will be offset by the same temperature at each altitude. Extra absorption means an increased temperature.
        The stratosphere is a different story. The heating by incoming Solar UV and visible radiation by ozone produces a temperature inversion: the temperature increases with increasing altitude. Central CO2 frequencies around 667 cm^-1 are essentially 100% saturated in the troposphere. Kirchhoff’s law says that a good absorber is also a good emitter, so those CO2 frequencies are 100% re-emitted, as per the usual theory of the greenhouse effect. This is mathematically handled with the Schwarzschild Equation, which adds an emission term to a Beer-Lambert absorption term. Doubling CO2 means that the region of 100% absorption is extended to higher altitudes, where the temperature is higher. So the final escape of IR photons to outer space occurs at higher temperatures, which means higher emission (using the Stefan-Boltzmann law for an effective Planck black body equivalent). This does not show up in the MODTRAN spectrum, which was calculated only to 20 km altitude. Jack Barrett has run the program to 70 km altitude [see the section “The hard bit” at his website http://www.barrettbellamyclimate.com/ ], which shows increasing emission around 667 cm^-1 on increasing CO2. Increasing emission at these frequencies means that the energy imbalance is now the other way: if more escapes per unit time while the incoming radiation (which excites ozone and heats the stratosphere) stays the same, then the stratosphere will cool with time.
        The tropopause is the inflection point, where the lapse rate switches from negative in the troposphere to positive in the stratosphere. The net effect on temperature should be between the two cases, i.e. zero or very little change with time as CO2 increases.
        QED”

      • Toneb tap dances:

        First of all it is not a “cornerstone” of AGW theory. Warming in the upper trop would occur in the tropics with any causation of GW……&etc.

        …while moving the goal posts:

        What is a “cornerstone” is stratospheric cooling…

        And:

        “Would you care to point to some science that says AGW theory <– ("theory", heh) does not induce stratospheric cooling? Would you care to link to science that says that a hot-spot would NOT occur under any means of climate warming?”

        Toneb still can’t understand how the scientific method works: Skeptics of a hypothesis like ‘dangerous AGW’ have nothing to prove.

        So the stratosphere strawman now replaces the troposphere…

        Only in climate science™.

        Next, a reply to ‘O R’ (who’s not fooling many folks here):

        Cutting and pasting a Wiki article is questionable. Why not post each subsequent change in that cut ‘n’ paste job — along with the dates that each edit was done? Then we could see all the backing and filling that’s gone on ever since Gaia falsified that particular prediction.

        I recommend using the WUWT search box to find all the articles on the ‘hot spot’, on ‘tropospheric’, etc. Then you will see that it was just another failed alarmist prediction (the so-called ‘fingerprint of man-made global warming’).

        Yes, the stratosphere was occasionally mentioned here and there. But the big AGW scare was based on a ‘tropospheric hot spot’ appearing — and that prediction was flat wrong.

        Half right = wrong.

      • > while moving the goal posts

        Sorry db, you’ve got it wrong from the beginning. Stratospheric cooling is the GHG fingerprint. The hotspot would be expected to evolve due in any warming regime due to external forcing, natural or not.

      • O R says, October 22, 2016 at 8:08 am:

        The stratospheric cooling can be understood in two ways. There is a AGW- caused energy imbalance, trapping heat in the system below the tropopause at a rate of about 1 W/m2.

        No. It can not be understood in this way.

        First, there is no such “AGW-caused energy imbalance” observed. The ToA energy imbalance is evidently (from the available data, ERBE+CERES, ISCCP FD, HIRS) caused by an increase in ASR (heat in), NOT by a reduction in OLR (heat out).

        Second, this is not how stratospheric cooling is supposed to come about with an increase in atmospheric CO2 content in the first place. As I tried to point out to Toneb.

        There is also a kind of inverse greenhouse effect in the stratosphere.

        There’s a positive lapse rate in the stratosphere, meaning, the temps rise as you move up. If you were then to put more CO2 into the atmosphere, this should naturally make the cooling of the stratosphere more effective. But this is only because, for all intents and purposes, there is no convection going on in the stratosphere. No turbulent mixing of air masses. The stratospheric heat budget is basically governed by radiation. This is a very different regime from the one further down, in the troposphere. So the two cannot be directly compared. There is no inherent connection between a cooling stratosphere and a warming troposphere. The causative processes are simply completely different …

  9. Maybe one reason models are so high is they under count energy loss to space from El Nino events when the earth burps a huge amount of heat high into atmosphere with processes complete unimpeded by CO2.

      • When will you ever learn to read, kim?

        Although the El Nin˜os and La Nin˜ as are often referred to as ‘events’ which last a year or so, ENSO is oscillatory in nature. The ocean is a source of moisture and its enormous heat capacity acts as the flywheel that drives the system through its memory of the past, resulting in an essentially self-sustained sequence in which the ocean is never in equilibrium with the atmosphere. The amount of warm water in the tropics builds up prior to and is then depleted during El Nin˜o. During the cold phase with relatively clear skies, solar radiation heats up the tropical Pacific Ocean, the heat is redistributed by currents, with most of it being stored in the deep warm pool in the west or off the equator such as at about 10 or 20N. During El Nin˜o, heat is transported out of the tropics within the ocean toward higher latitudes in response to the changing currents, and increased heat is released into the atmosphere mainly in the form of increased evaporation, thereby cooling the ocean.

    • … earth burps a huge amount of heat high into atmosphere

      presuming you are referring to deep moist convection, it becomes a small amount of heat once it reaches high into the atmosphere after adiabatic cooling…

      … with processes complete unimpeded by CO2

      Which is a trace gas which has a trace effect on the atmosphere…unless you actually believe the AGW models.

      Please present a link to a satellite imagery showing all this “energy loss to space from El Nino events” because if energy is being lost to space, meteorological satellites will see it. BTW, satellites show *much* more energy being lost to space from the Earths surface under clear skies than from the top of a cold cloud.

      • All energy lost to deep space is by radiation. At 4 Kelvin deep space is a deep sink. Any time water vapor condenses and falls, whether rain at lower elevations or virga at higher elevations, it leaves heat at the high elevation. This increases radiant heat flux in all directions including out to space.

      • it leaves heat at the high elevation

        I’m still waiting for you to back up your claim & show where all this heat is in an IR satellite image…

    • NS, models run hot for a very simple reason. Gridscales that woild start to model convection realistically are computationally intractable by 6-7 orders of magnitude. See mynprevious guest post here on models. Therefore they have to be parameterized. Dor CMIP5′ the parameterization is tuned to best hindcast from YE2005 back to 1975 per the official ‘experimental design’. That introduces the attribution problem, because the warming from ~1975-2000 is essentially indistinguishable from the warming from ~1920-1945. The earlier warming is mostly natural per IPCC AR4 SPM fig. 8.2. Yet the 1975-2005 tuning attributed the warming to GHE. There is certainly a natural component also (because natural variation did not magically stop in 1975), hence the models run hot as tuned. The inescapable and fundamentally fatal to CAGW attribution problem.

      • There is yet another warming event in the 19th Century, again with approximately the same slope; all three on an approximately 60 year cycle. That we’ve again followed the flat to cooling slope in the last 20 years suggests that sensitivity to CO2 is low.

        I’ve called attributing the warming of the last quarter of the last century to CO2 the grandest example yet of the ‘Post Hoc, Ergo Propter Hoc’ logical fallacy. As you say, it is a fundamental and fatal flaw.
        ==================

  10. Science died the day “peer review” was established. You make only enemies by proving other wrong, so nobody does that, so BS just pile up, and you end with “Most Published Research Findings Are False” (just google that). Another segment of published BS is “captain obvious” things, that pile up, too.
    Bottom line:science is all about proving others wrong, or not replicable, or pretty obvious (consequence of known result, for instance) so irrelevant. That’s the first criterion that should be used to grant money, not publishing .
    “Consensus” and “97%” wouldn’t live long…

    • Most manuscripts submitted to higher quality journals get rejected, and almost all of those eventually accepted are initially returned for revisions and corrections. Not all of the rejections are really justified; peer review is quite frequently abused to stall competitors. Because of this, authors are typically given the option to request that their immediate competitors not be chosen as peer reviewers, but unwarranted rejections happen nevertheless.

      On the other hand, peer review can never be as rigorous as an actual replication of the data. If an author lies plausibly, one cannot expect peer reviewers to catch him. Similarly, within a research group, PhD candidates or postdocs feeling the pressure may be tempted to present doctored data to their bosses.

      Peer review is not perfect, but overall it is useful. I find that I can learn something about a third to half of the peer reviews I receive. I strive to be evenhanded and constructive in the peer reviews I write, but can only hope that they are perceived as such by their recipients.

  11. It is amazing how these climate scientists, again and again, fail to meet the ethical standard for science.

    “it is still impossible, for various reasons, that any theoretical system should ever be conclusively falsified. For it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition. It is even possible without logical inconsistency to adopt the position of simply refusing to acknowledge any falsifying experience whatsoever. Admittedly, scientists do not usually proceed in this way, but logically such procedure is possible»
    – Karl Popper; The logic of scientific discovery

  12. Santer is well known for trying to torture the radiosonde data by “adjustments” to support the case for finding the hot spot in the troposphere. Looks like he gave up and tried it another way.

  13. Matt Ridley – Lecture on >Global Warming Versus Global Greening< at the Royal Society 17 October 2016

  14. I wonder if Ben Santer will now want to “beat up” John Christie. Mr.Santer is such a class act. Memo to Mr.Santer: If you still want to “beat up” someone who disagrees with you, try “beating up” me. Good luck with that. It is a standing offer.

  15. In part to provide some sort of evidence to support the AGW conjecture, the IPCC sponsored development of a plethora of climate models. The fact that there are so many models supports that idea that a lot of guess work was involved. The plethora of models have predicted a wide range of values for today’s global temperatures but apparently they all have one thing in common. They are all wrong and have predicted global warming that has not happened. If they are evidence of anything it is that there is something very seriously wrong with the AGW conjecture. All the wrong models need to be discarded and all papers that make use of such wrong models need to be withdrawn.

    CO2 does not create heat so it can cause global warming only by adding to the insulation effect of the atmosphere. One measure of that insulation effect is how adding CO2 to the atmosphere causes the dry lapse rate in the troposphere to increase. If adding CO2 to the atmosphere really caused global warming then the increase in CO2 over the past 30 years should have caused a noticeable increase in the dry lapse rate in the troposphere but that has not happened.

    In their first report the IPCC published a very wide range for the possible value of the climate sensitivity of CO2. Only one value can be correct. In their most recent report the IPCC published the exact same range of values. So after more than two decades of study the IPCC has learned nothing that would allow them to decrease the range of values one iota. Yet their simulation results when compared to real data indicates that the climate sensitivity of CO2 is really much lower then the range of values in the IPCC’s previous reports. The IPCC needs to correct their previous mistakes. They need to throw out all of their bad models. They need to publish much more realistic values for the climate sensitivity of CO2.

  16. I don’t know why John Christy is complaining about the new STAR 4.0 dataset.
    “The brand new “hot” satellite dataset (NOAAv4.0) used by Santer et al. to my knowledge has no documentation.”

    The documentation can be found here:

    ftp://ftp.star.nesdis.noaa.gov/pub/smcd/emb/mscat/data/MSU_AMSU_v4.0/Monthly_Atmospheric_Layer_Mean_Temperature/readme.txt

    It is essentially a global Po Chedley et al (2015), which means it has practically passed peer review.
    Afaik the “cool” UAH v6 dataset is still beta, not published, hence of a lower status than STAR 4.0.

    • If you accept that as documentation, after my having looked at it, you will accept the documentation of my Mayflower ancestry.

      Actually, my ancestors met the Mayflower. My attitude always pissed off my wife’s family. Too crude, by far.

    • “hot” satellite dataset (NOAAv4.0) Documentation, as claimed by O R:
      I formatted the block writing to try and differentiate and clarify. If you prefer, refer to the original.

      “This directory contains the monthly averaged time series and their anomaly time series for
      • STAR V4.0 TMT (MSU channel 2 and
      • AMSU-A channel 5),
      • TTS (TUT, MSU channel 3 and A
      • MSU-A channel 7),
      • TLS (MSU channel 4 and
      • AMSU-A channel 9)
      – o derived from NOAA TIROS-N through NOAA-18,
      – o MetOp-A, and
      – o NASA EOS Aqua.

      The grid resolution for these datasets is 2.5 degree latitude x 2.5 degree longitude.

      The datasets were generated using the
      • IMICA (Integrated Microwave Inter-Calibration Approach, Zou and Wang 2011, 2013) calibrated L1C radiance.

      Main difference of STAR V4.0 from previous versions is
      • that a new scheme for correcting diurnal drift effect is applied in V4.0.
      – o In this scheme, diurnal drift effect in TMT was corrected using a combination of RSS model-based diurnal anomaly datasets (Mears et al. 2003, ftp://ftp.ssmi.com/msu/data/diurnal_cycle/)
      – o plus a regression scheme developed by the University of Washington (UW) group (Po-Chedley et al., 2015).

      This was done by first applying scaled RSS diurnal anomaly dataset to minimize intersatellite differences over land for a best merging.
      • The scaling factors were 0.875 for MSU and 0.917 for AMSU-A (Zou and Wang 2009).
      • After that, a regression scheme was applied in STAR V4.0 based on an assumed relationship between inter-satellite temperature differences and satelliate[sic] local equatorial crossing time,
      • following Po-Chedley et al. (2015). This process provided the best results in correcting the diurnal drift effects, particularly for AMSU-A observations.

      Both STAR V3.0 and V4.0 are put on the STAR website for downloading.
      • Note that STAR V3.0 is also archived and distributed by the NCEI CDR website: https://www.ncdc.noaa.gov/cdr/fundamental,
      • o with a dataset name: “Mean Layer Temperature – NOAA”.
      • The STAR V4.0 is the latest version which has not been delivered to NCEI CDR for archiving and distribution.

      Other information on these time series are:

      1) Time range for individual product:
      • TMT and TLS: November 1978 – present
      • TTS (TUT): January 1981 – present.

      2) Base priod[sic] for calculating anomalies: Jan 2000-Dec 2010.

      3) A sample_read_monthly.f is provided to read and use the data.
      • Please refer to comments in the source code for information on the data format.

      References:

      1. Zou, C.-Z. and W. Wang (2009), Diurnal drift correction in the NESDIS/STAR MSU/AMSU atmospheric temperature climate data record, Proc. SPIE, Vol. *7456*, 745616.
      2. Zou, C.-Z. and W. Wang (2011), Inter-satellite calibration of AMSU-A observations for weather and climate applications, J. Geophys. Res., Vol. 116, D23113, DOI:10.1029/2011JD016205
      3. Zou, C.-Z., W. Wang, (2013), MSU/AMSU Radiance Fundamental Climate Data Record Calibrated Using Integrated Microwave Inter-Calibration Approach, Climate Algorithm Theoretical Basis Document (C-ATBD), NOAA/NESDIS
      4. Po-Chedley, S, T.J. Thorsen, and Q. Fu, (2015), Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies. J. Clim., 28, 2274 – 2290, doi:10.1175/JCLI-D-13-00767.1.
      5. Mears, C. A., M. C. Schabel, and F. J. Wentz (2003), A reanalysis of the MSU channel 2 tropospheric temperature record, J. Clim., 16(22), 36503664, doi:10.1175/1520-0442(2003)0162.0. CO;2.”

      Some documentation huh!?
      Note the 2.5 X 2.5 (latitude X longitude) degree grid.

      The sample code for reading and using the data? ‘sample_read_monthly.f’

      “ccccccccccc Data format
      c The data being read are stored in the array with a dimension 144 X 72 X NT
      c (longitude by latitude by monthly number)

      ccccccccccc Longitude and Latitude
      c The data grid resolution is 2.5 longitude by 2.5 latitude. Therefore, there are 144
      c grid boxes in the first latitude zone near the South Pole,then 144 boxes in the next
      c latitude zone right above it, all the way to the North Pole. There are 72 latitude
      c zones in all, so the first month contains 144×72 = 10,368 temperatures, then on to
      c the next month, and so forth. Longitude starts from 180W to 180E, which means the
      c first longitude index (nx=1) represents the grid box centered at 178.75W (-178.75), and
      c so fourth; and the last longitude index (nx=144) represents the box centered at 178.75E.
      c Please also use “lat.txt” and “lon.txt” files for specific values for the lad/lon definition.

      ccccccccccc Time
      c Use extra caution when handling time dimesion because TMT(ch2) and TLS(ch4) start from Nov.1978,
      c while TUT(ch3) from Jan.1981.
      c

      ccc compile with option : f77 -ffixed-line-length-150 -ff77 sample_read_monthly.f

      PARAMETER ( missing = -9999.0 )
      PARAMETER ( nx=144, ny=72, nt=446)

      c nx is the longitude(nx =1 for -178.75, nx=2 for -178.75+2.5….,and nx=144 for 178.25)
      c ny is the latitude (ny=1 for 88.75S, ny=2 for 88.75S+2.5,…, and ny=72 for 88.75N)
      c nt is time (see the explanation above)

      real tmsu_am(nx,ny,nt)
      CHARACTER*150 filename

      filename=’NESDIS-STAR_TCDR_TMT_merged_msu_ch2_amsua_ch5_monthly_1978-Dec2015_v3.0.dat’
      OPEN ( 88, file=filename, status=’old’ )
      PRINT*,”reading! TMT …………”
      do k=1,nt
      do j=1,ny
      READ ( 88,'(144(f10.3,1x))’)(tmsu_am(i,j,k),i=1,nx)
      enddo
      enddo

      c you are ready to go !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

      This is documentation? and code? And ‘0 r’ claims this is ‘practically’ past pal review?
      Yup, ranks up there in quality with so many other ‘pal reviewed’ papers; not even usable in the john.

      • A skilled person could probably reproduce STAR 4.0 by use of this note, references therein, with supplementary online material, etc.
        I guess your are not among them. Instead you choose to spam the discussion, and is strangely enough allowed to do that by the (absent) moderation.

        No one can reproduce UAH v6, it is not enough info out there.
        However, even a layman can reproduce the “Cadillac calibration choice”, the anectdotal method whereby the true scientist Spencer and Christy merge MSU and AMSU data. It is simple, a 50/50 flip of the coin choice, which also can be done with gut feeling or ideological bias..
        However, validation with radiosondes may question if the choice is right. (Of course, the choice is right if you want a pause):

        The STAR and RSS team don’t do important 50/50 choices based on anectdotes or wishes. If they are uncertain they choose both an take the middle road. Hence, they are never more than 50% wrong..

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