The CERES Calculated Surface Datasets

Guest Post by Willis Eschenbach

The CERES dataset is satellite data that is based on radiation measurements made from low earth orbit. The CERES data has two parts. The first part is observational data, measurements of downwelling and upwelling solar radiation and of upwelling longwave radiation. It is usually referred as the CERES “top-of-atmosphere” data. The official name is “CERES EBAF-TOA”, and it is available here.

However, the second part of the CERES is not top-of-atmosphere observations from the satellite. Instead, it is calculated surface data based on the CERES TOA observations along with other satellite observations. It’s called the “CERES EBAF-Surface” dataset, and is available from the same location.

As a result, I’ve always been concerned about the accuracy of the CERES surface data. After all, it’s just calculations, it’s not actual observations. So I got to thinking that I could “ground-truth” the CERES surface observations by using the TAO buoy data. It’s not a comprehensive test by any means, but the TAO buoys cover a region of great interest to me, the tropical Pacific. The TAO buoy data is available here.

I started out by seeing how well the CERES surface longwave radiation data agreed with the TAO sea surface temperature (SST) data. Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship. First I looked at a string of TAO buoys that run along the Equator. I used the location of each TAO buoy, and compared it with the CERES surface calculated result for that location. Figure 1 shows that comparison for the eight TAO buoys along the Equator which have SST data.

tao and ceres sst equatorFigure 1. Sea surface temperatures (SST) from the TAO buoys (red) and from the CERES surface data calculations (blue).

I was pleasantly surprised by this result. The greatest bias is ± two tenths of a degree, and the correlation is very high, 0.97 to 0.99.

Having looked at an east-west line of buoys, I then looked at a north-south line of buoys. These are all at 165°E, in the warmest area in the Pacific.

tao and ceres sst 165EFigure 2. Sea surface temperatures (SST) from the TAO buoys (red) and from the CERES surface data calculations (blue).

Again the correlations are good, although there is one of the seven down at a correlation of 0.92. And the bias is slightly larger, -0.3 to -0.4°C. In this region all of the CERES data is slightly below the TAO buoy data.

Overall, however, if the bias errors are only on the order of a few tenths of a degree and the correlation is on the order of 0.97 or better, I’m more than happy to say that the sea surface temperature is extremely well represented by the CERES surface calculations.

However, that’s the easiest of the variables. Next I looked at something much harder to estimate—the available solar radiation at the surface after atmospheric reflection, absorption, and scattering. Figure 3 shows the available solar measurements from buoys along the Equator.

tao and ceres available solar equatorFigure 3. Available surface downwelling solar after atmospheric reflection, absorption, and scattering from the TAO buoys (red) and from the CERES surface data calculations (blue).

This one surprised me quite a bit. I wouldn’t have guessed that the satellite calculations would come this close. Not only do they get the annual cycles right, but they also get the occasional departures from the annual cycles. Yes, the correlation of some of them is lower, but they still do a good job. And the bias in all cases is less than 2%, a respectable showing.

I then looked at the same group of north-south buoys I’d used above. Here are those results.

tao and ceres available solar 165eFigure 4. Available surface downwelling solar after atmospheric reflection, absorption, and scattering from the TAO buoys (red) and from the CERES surface data calculations (blue).

Again, a very good showing, with correlations from 0.87 to 0.97, and bias of less than 2%.

There is one more overlapping dataset between CERES and TAO, that of downwelling longwave radiation (DLR). Unfortunately, there are only five TAO buoys with DLR data, and one record is very short … but we use what we have. Here is that group of buoys.

tao and ceres sst downwelling longwave equatorFigure 5. Downwelling longwave radiation (DLR) from the TAO buoys (red) and from the CERES surface data calculations (blue).

Of all of the results, I was most surprised by this one. I would say that this one would be the hardest to calculate from the satellite data. But despite that, if we set aside the very short (5-month) dataset in the first panel of Figure 5, the other four have good correlations (0.82 to 0.97), and the three longer datasets (panels 2, 3, and 4) have a bias of well under 1%.

Conclusions? Well, as I said, this is far from a comprehensive test … but I am greatly encouraged nonetheless. The CERES surface dataset, despite being calculated rather than observed, is a very good match to the TAO buoy data in all available respects. Makes me feel much better about using it.

My regards to you all,

w.

PS-If you disagree with someone please have the courtesy to quote the exact words you disagree with. This lets all of us understand the exact nature of what you think is incorrect.

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121 thoughts on “The CERES Calculated Surface Datasets

  1. Looks convincing to a lay-person like me too. Nice work. So now its time (for you) to start using it I guess. I look forward to some useful solar energy balance facts in the (near?) future. Thanks Willis

  2. Not bad.
    But their data is for near-equatorial conditions.
    I have not found any Sereze-approved calc’s for the far north (or far south areas past 55 north or south) accurate against actual ocean albedo’s, sea ice albedo’s, air masses, attenuation factors, incident angles, or solar elevation angles.
    but, neat the equator? Looks like they are right.
    Good.

    • That was my first thought – but surely the additional calculation is just Euclidian geometry, which isn’t hard to do.
      The poles themselves aren’t calculated are they?

    • I’m a bit surprised to find that measured SS W/m^2; solar is not around 1 kW/m^2 which is what all earth bound solar panel designs are based on (measured normal to the sun vector).
      So what gives Willis, that you only find 240 W/m^2; and that is supposed to be a measured number; not a calculated number.
      I’m puzzled. I assume that the solar flux measurements includes at least the 0.25 to 4.0 micron wavelengths.
      g

      • george e. smith (asking willis e)

        I’m a bit surprised to find that measured SS W/m^2; solar is not around 1 kW/m^2 which is what all earth bound solar panel designs are based on (measured normal to the sun vector).
        So what gives Willis, that you only find 240 W/m^2; and that is supposed to be a measured number; not a calculated number.

        Willis is playing the “total radiation over 24 hours”/24 hour (at 3600 second/hr) game. It doesn’t really work that way. For example, during the daylight hours, the world at sea level near the tropics received 1000 watt/sec (as you indicate) for a period of 6 hours. Then the rest of the systems (evaporation, LW radiation loss and gain, convection to the atmosphere, etc) spend the next 18 hours losing that 6 hours of heat, plus the original 6 hours when both heat gain and heat loss are going on at the same time.

      • george e. smith February 24, 2015 at 3:47 pm

        I’m a bit surprised to find that measured SS W/m^2; solar is not around 1 kW/m^2 which is what all earth bound solar panel designs are based on (measured normal to the sun vector).

        What I’m showing is the average solar over the month, not the instantaneous solar at high noon.
        RACookPE1978 February 24, 2015 at 7:03 pm

        Willis is playing the “total radiation over 24 hours”/24 hour (at 3600 second/hr) game. It doesn’t really work that way.

        Oh, piss off. I don’t play games. I give the results as best I understand them. I’ve given a comparison of the monthly averages from CERES and the monthly averages of the TAO data. If you wish to make some other comparison, that’s your business. But it doesn’t give you leave to falsely accuse me of playing games.
        In any case, RA, if you don’t like monthly averages, how do you propose that we compare the TAO data and the CERES data?
        Regards to all,
        w.

        • Willis Eschenbach (in reply to RACookPE1978 February 24, 2015 at 7:03 pm )
          Submitted on 2015/02/25 at 1:19 am | In reply to george e. smith (original)

          Willis is playing the “total radiation over 24 hours”/24 hour (at 3600 second/hr) game. It doesn’t really work that way.

          I don’t play games. I give the results as best I understand them. I’ve given a comparison of the monthly averages from CERES and the monthly averages of the TAO data. If you wish to make some other comparison, that’s your business. But it doesn’t give you leave to falsely accuse me of playing games.
          In any case, RA, if you don’t like monthly averages, how do you propose that we compare the TAO data and the CERES data?

          Ah, but I regret you misunderstand my use of “games” there; the world is but a stage, is it not? And we but simple players upon its fractally infinite beach toying with pretty pebbles – just to mix a few inappropriate quotes there.
          More seriously, listen to what Dr Roy Spencer wrote in Climate Confusion (hardback version, pg 65-66) about these satellite measured differences.

          One might wonder, how do we know that this small radiation imbalance at the top of atmosphere from the extra carbon dioxide really exists? Well, we don’t really know. It is (sigh), once again, a theoretical calculation.
          A series of NASA satellites have been flown in recent decades to measure the amount of sunlight being absorbed by the earth, and the amount of infrared energy being lost by the Earth to outer space. But the expected imbalance between them is still very small as of this writing – a little less than 1 watt out of the 235 watt average. The satellite instruments are not quite accurate enough to measure such a small imbalance with confidence. It would be like trying to see the difference in room brightness when your ceiling is covered by 234-watt light bulbs spaced three feet apart, instead of 235-watt light bulbs.
          Another measurement difficulty is that the satellites cannot measure the whole earth at once. Even though one half of the earth is absorbing sunlight, and the entire earth is emitting infrared radiation, the satellite can only measure one small area at a time as it orbit over different geographic regions. For any given place and time, the imbalance between incoming sunlight and outgoing infrared energy is usually very large: many tens, if not hundreds, of watts per square meter. So the satellites measure many, many large imbalances at different locations allover the earth, and the average of all of these large number together is expected to approach zero (or the very small one-watt imbalance) over a sufficiently long period of time.

      • RACookPE1978 February 26, 2015 at 8:43 am

        Willis Eschenbach (in reply to RACookPE1978 February 24, 2015 at 7:03 pm )

        Willis is playing the “total radiation over 24 hours”/24 hour (at 3600 second/hr) game. It doesn’t really work that way.

        I don’t play games. I give the results as best I understand them. I’ve given a comparison of the monthly averages from CERES and the monthly averages of the TAO data. If you wish to make some other comparison, that’s your business. But it doesn’t give you leave to falsely accuse me of playing games.
        In any case, RA, if you don’t like monthly averages, how do you propose that we compare the TAO data and the CERES data?

        Ah, but I regret you misunderstand my use of “games” there; the world is but a stage, is it not? And we but simple players upon its fractally infinite beach toying with pretty pebbles – just to mix a few inappropriate quotes there.

        RA, you say you weren’t accusing me of “playing games”, you were simply misquoting poetry?
        Well, OK … but your intention was far from clear. Let me suggest that in future you purge “playing games” from your list of playful allegorical accusations.

        More seriously, listen to what Dr Roy Spencer wrote in Climate Confusion (hardback version, pg 65-66) about these satellite measured differences.

        One might wonder, how do we know that this small radiation imbalance at the top of atmosphere from the extra carbon dioxide really exists? Well, we don’t really know. It is (sigh), once again, a theoretical calculation. …[more good stuff from Dr. Roy snipped]]

        Thanks, RA. I agree completely with Dr. Roy.
        w.
        PS— I note that in your reply you didn’t answer my scientific question, so let me ask it again …

        In any case, RA, if you don’t like monthly averages, how do you propose that we compare the TAO data and the CERES data?

  3. “The CERES dataset is satellite data that is based on radiation measurements made from low earth orbit.”
    The Ceres data is known to suffer from calibration problems.
    Some comments appear in Loeb et al. Toward Optimal Closure of the Earth’s Top-of-Atmosphere Radiation Budget. J.of Climate, AMS, V.22, p.748.)
    URL: http://www.nsstc.uah.edu/~naeger/references/journals/Sundar_Journal_Papers/2008_JC_Loeb.pdf
    In 2012 an update was published in Nature Geoscience on the subject of uncertainties in the observations of solar and terrestrial energy flows (radiative flux). The authors stated:
    “The net energy balance is the sum of individual fluxes. The current uncertainty in this net surface energy balance is large, and amounts to approximately 17 Wm–2. This uncertainty is an order of magnitude larger than the changes to the net surface fluxes associated with increasing greenhouse gases in the atmosphere (Fig. 2b). The uncertainty is also approximately an order of magnitude larger than the current estimates of the net surface energy imbalance of 0.6 ±0.4 Wm–2 inferred from the rise in OHC. The uncertainty in the TOA net energy fluxes, although smaller, is also much larger than the imbalance inferred from OHC.”
    Regarding the estimate of ocean heat content, they stated,
    “For the decade considered, the average imbalance is 0.6 = 340.2 – 239.7 – 99.9 Wm-2 when these TOA fluxes are constrained to the best estimate ocean heat content (OHC) observations since 2005 (refs). This small imbalance is over two orders of magnitude smaller than the individual components that define it and smaller than the error of each individual flux. The combined uncertainty on the net TOA flux determined from CERES is ±4 Wm-2 (95% confidence) due largely to instrument calibration errors (refs). Thus the sum of current satellite-derived fluxes cannot determine the net TOA radiation imbalance with the accuracy needed to track such small imbalances associated with forced climate change.”
    Graeme L. Stephens et al, An update on Earth’s energy balance in light of the latest global observations. Nature Geoscience Vol. 5 October 2012
    URL: http://www.aos.wisc.edu/~tristan/publications/2012_EBupdate_stephens_ngeo1580.pdf
    The estimate of 0.6 Wm-2 was updated by Loeb and others in 2012 to 0.5 Wm-2.
    Reference: Norman G. Loeb, John M. Lyman, Gregory C. Johnson, Richard P. Allan, David R. Doelling,Takmeng Wong, Brian J. Soden and Graeme L. Stephens. Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty. (Nature Geoscience Vol 5 February 2012)
    URL: http://www.met.reading.ac.uk/~sgs02rpa/PAPERS/Loeb12NG.pdf
    My detailed comments here:
    https://geoscienceenvironment.wordpress.com/2014/09/04/the-emperors-of-climate-alarmism-wear-no-clothes/

    • Given the calibration errors are so large, what is the explanation for the close correlation between TAO and CERES? Could CERES have been actively calibrated against TAO, or a closely related data set?

      • Neither of the two satellite metrics calibrate against surface data. It’s straight MW conversion. A few years back, Dr. Christy was very vehement on that, and I trust him implicitly in this.

    • That energy varies with the 4th power of temperature,
      E = σT^4,
      is another way of stating that temperature varies with the fourth root of energy,
      T = (E^¼)/&#963,
      a very small number when compared with the CERES noise, as you have pointed out.

    • Thanks, Katio. It’s the first time I’ve done it, and I did it to see what’s what vis-a-vis the TAO data.
      w.

  4. Two comments, Willis:
    First, please can you consider Eric Worrall’s question carefully? It is one that would not have occurred to me.
    Second, do you think that CO2 is supposed to increase downwelling LW over time and do you think the CERES graphs refute that?
    Thanks – nice article.
    Rich.

  5. “Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship.”
    How do you convert the radiation data into tempature in detail? Most of the IR thermal radiation of the oceans is absorbed by the atmosphere. It is true that there are some atmospheric windows in the IR, which you can use to reconstruct the Stefan-Boltzmann spectrum emitted by the surface. But you have to assume that the albedo is constant for these windows. It would be nice if satellites could measure the surface temperature directly, for instance by inelastic light scattering (Brillouin, Raman scattering). But unfortunately these techniques can only be used in the lab.

    • It can be measured directly. They just don’t know how because they are so focused on the details . Can’t see the forest for the trees.

    • Thanks, Paul. I converted using the standard S-B relationship, which is that
      Radiation = S-B_constant * emissivity * temperature^4
      For the surface radiation I used the CERES calculated upwelling surface radiation, the EBAF-SURFACE dataset called “surf_lw_up_all”.
      w.

      • Well this of course takes as gospel the assumption that the ocean surfaces are indeed black body radiators, which one might conjecture should be true for the 5.0 – 80 micron wavelengths characteristic of a 288k BB radiator.
        Of course Konrad insists that the ocean is anything but a BB emitter.
        Well that’s his opinion. I’ve never measured it, but would assume its a fairly good BB at its surface Temperature.
        G

  6. I’m always embarrassed to admit my ignorance, which is profound in many areas. Nevertheless, rather than persist in my ignorance, I’ll ask for help.
    Google tells me TAO stands for Tropical Atmosphere ocean, so I’m further advanced than I was before. But what does the term ‘bias’ mean when you are using it in these graphs?

    • The word “bias” has many meanings in the dictionary, most of them related to conveying a judgment. When applied to human judgment it implies the existence of prejudice or subjectivity, usually in a derogatory sense.
      But “bias” is also used mathematically, to describe the output of statistical estimators, and simply means that on average the consistently misses the ‘ground truth’ value by a constant offset, i.e. it consistently overestimates or underestimates. In this sense it usually carries no judgmental stigma, as in the human-judgment sense of the word. It is a simply a way to measure the reliability and usefulness of a statistical estimator.
      When the measured bias of an estimator equals zero, we say the estimator is “unbiased”.
      Be careful not to confuse “bias” with “variance”, which is a random offset observed in virtually all estimators, which is distinct from “bias” because in the long run it averages out to zero. Bias and variance of components of the total squared error: SE=bias^2 + variance

      • Thanks, Johanus. Your comments from the second paragraph forward are of course what I was looking for.
        Yet even with your help, there’s much I don’t understand.
        Sure, Willis could fairly say ‘he’s using the term in a perfectly ordinary statistical sense’, and I have no doubt that’s exactly what he’s doing. Still, he is writing for a lay audience. That’s me and people with even less stats education than me, so I don’t think I’m unreasonable to continue to pursue the matter.
        Are the graphs simply reporting the difference between the calculated values for the Pacific and the measured values from the TAO buoys, and calling the difference ‘bias’? [Whether that is or isn’t it, what do both systems do about ‘time of measurement’? That would surely create differences much greater than the fractional degree Willis is reporting.]
        If my inference above is wrong, then I need lots more explanatory help. In this particular example, what thing is the statistical estimator? If the measurements of the TAO are not the ‘Ground Truth’, then how do we know what the Ground Truth is? Why would there be a bias rather than variance?
        I’ve now read the Wikipedia article on Bias (Statistics), and it lists 12 Categories of Bias excluding sub-categories. What type is this and how do we know? And how do we calculate its value?
        My ‘take home’ message from Willis’s article is that the temperature figures of TAO and CERES EBAF – Surface are very similar. That’s good to know. The calculated result is biased in some fashion. Which set of figures is biased, or is he simply using the term to refer to the amount of difference between the two sets? When I go to explain his work to others, what exactly do I tell them? Don’t worry about insulting my intelligence, just give clear explanations.

      • Taking a set of model outputs projecting the temperature for the past fifteen years or so, and comparing them to the measurements on the ground, what sort of ‘bias’ number is seen?
        Based on the explanation above, it must be a pretty big number. Any model run will have bias and variance too. To me, the models look biased towards heating. When evaluated as ‘worthy or not’ models using ordinary criteria, how do they stand up?
        The calculated Ceres numbers are the output of a set of calculations that are a ‘model’ too. With a bias of one or two per cent the Ceres model looks good. It seems to me the bias of the GCMs is, on average, far, far larger.

    • TAO and TOA were both correctly used in the article. The latter is Top of Atmosphere the former is Tropical Atmosphere Ocean program which posted a series of buoys across the tropical Pacific.

  7. I have yet to see data about the increasing LWIR, being a sign of increased “GH effect”. It is an unquestioned assumption all models work with, but has it ever been really observed? There was a study of LWIR observations at clear sky conditions somewhere from US Midwest, which shown even decrease of LWIR.

    • Stephen 4:52am: Yes. Dr. Spencer has explained how at his site. If I recall correctly, they use the atm. O2 signature calibrated to radiosonde. This top post should be useful for you to start to add intuitive radiative energy transfer lacking in your limited intuitive KE+PE transfer to reach better meteorological conclusions especially at the surface.

      • Dr Spencer’s method is not the be all and end all method for measuring temperature. There are other ways, even using the data from ‘his’ satellites. I’m not taking anything away from his work. It is quite complicated.
        His focus is on temperatures up and down the atmosphere. His work is not focused on near to earth stuff.

    • Just everything from the ground to the satellite. You can probably calculate the reading cone from the NASA website for individual readings.

      • My reason for asking is that I’m sure that if radiation to space from within an atmosphere changes then radiation from the surface to space varies in an equal but opposite direction.
        The regulating mechanism is then variations in the amount of potential energy returning as heat to the surface in adiabatic descent.
        The more radiation to space there is from within an atmosphere the less energy as heat that can be returned to the surface in adiabatic descent and the less the surface can radiate to space and vice versa.
        It is a neat self adjusting process but unless we can distinguish the two separate sources for outgoing IR we cannot check it out.

      • Stephen
        I know your ‘bag’ is adiabatic stuff. I don’t disagree with it. I just know the principle of spectrometers and that kind of instrumentation. Dr Spencer’s stuff seems to be in regard to upper troposphere and all the various levels of the atmosphere. I suggest you look at the raw data at his work site and kinda do calculations from that.

      • Dr Spencer deals with multiple levels within the atmosphere but doesn’t seem able to sum up everything from within the atmosphere and then distinguish it from that which comes from the solid surface.

      • Stephen
        That is the problem and I agree with you. There are other ways to look at things but people just do their job and don’t go there. Such is life. Look at his data , the actual satellite stuff raw. Pain in the arse for me too. I have to work out the software and data to do my own thing.

  8. Can that be right, the buoys around the equator are 15 degrees apart? That is 900 miles, and that is a proxy for water temps? Realistically that may be the way its done, it only tells me that satellites should be the gold standard for earth temps.

  9. Well, if the Ceres measurements for the surface are that good, then one can proceed to checking what the entire land surface and ocean SSTs are really doing.
    The TOA is not really important since we live at the surface. Ceres is just showing us that not much is really happening at the TOA (a few ups and downs but the imbalance/balance and individual components are not really changing. The Ceres 0.5-0.6 W/m2 energy imbalance is NOT really what the satellite is measuring. It IS what the Argo floats are measuring. They use Argo’s numbers as a proxy since Ceres’ components don’t add up. The imbalance is the OHC numbers from the Argo floats.
    It is also very interesting that the Stefan-Boltzmann equation works so well here. I note that it works everywhere in the universe it is tried and if it works so well in this example, I think that gives one the go-ahead to convert Ceres radiation data to temperature and be confident about it.

    • Why would it be interesting that the Stefan-Boltzman equation works in this case? It would be more interesting if it didn’t.

    • I hate to pile in Bill Illis but even I (as hard-core a sceptic as you find) didn’t have reason to doubt the Stefan-Boltzmann equation.
      What reason would you have for questioning its applicability? Was it the assumptions around what counts as a “black body”?
      You seem to be sceptical about something I took as reasonable and that perturbs me.

      • The S-B “balance” assumptions include superconductivity, matte black emitter, zero specific heat, zero thickness, no changes of form or state (melting, evaporation), and no other sinks. Equilibrium is treated as instantaneous, radioactivity is ignored as an energy source. The planet is treated as an ideal point source. The indicator of heat used, temperature, is intensive and cannot be dealt with arithmetically (adding, averaging).
        Treating the whole surface as an undifferentiated black body uses “averaging” to handwave such quibbles away. Enthalpy is just too hard to figger, don’cha know?

      • Brian H February 27, 2015 at 4:53 pm

        The S-B “balance” assumptions include superconductivity, matte black emitter, zero specific heat, zero thickness, no changes of form or state (melting, evaporation), and no other sinks. Equilibrium is treated as instantaneous, radioactivity is ignored as an energy source. The planet is treated as an ideal point source. The indicator of heat used, temperature, is intensive and cannot be dealt with arithmetically (adding, averaging).
        Treating the whole surface as an undifferentiated black body uses “averaging” to handwave such quibbles away. Enthalpy is just too hard to figger, don’cha know?

        And yet, the S-B equation gives an answer that has about a 95%+ correlation with the ground data from the TAO buoys … “too hard to figger”??? I’d say the scientists “figgered” it just about exactly.
        I’m sorry, but your sarcasm and your faux folksiness don’t work when the equation does work, and works very well.
        I’d advise you save your snark for an equation that doesn’t work …
        w.

        • Willis!
          Yet, putting aside the problems in his rejoinder, what is the actual S-B constants (and factors) for long wave heat loss from a horizontal flat “real surface” (a gray body) at sea level radiating “up” into the T_air?
          If so, what is the correct correction for air temperature at 2 meters (T_air) at a given relative humidity?
          Or is it radiation into a “T_sky at 15,000 meters (40,000 ft) at ???? cloud conditions?
          Or is it the “total condition” of T_ground into T_Space? can’t be => Else the FL fruit growers would not spray water onto orange grows and use foggers to protect their trees on clear nights in sub-freezing weather!
          I’ve worked outside on clear nights at 22 – 20 deg F. It’s d***ed cold! But “How cold is cold is it?” has never been clear. ANd the more “papers” and “pdf’s” I read, the less I am convinced the “clima-astrologists” know either. Other than, the classic T_ground and T_space = 0.0 K problem that the original S-B equations approximate.

    • Yes, Willis says the following (in the top post):
      “Now, the CERES dataset doesn’t have SST data, but we can convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship.”
      Fine, even though we know already that the ‘CERES surface radiation data’ is itself computed using inputs from other sources. These sources provide specific information on clouds, temperature and humidity in the air column above the surface. This information then goes into a radiative heat transfer model.
      Pretty complex work in the end. But it all seems to function quite well. At least for the region checked here by Willis …
      Here is NASA (by Seiji Kato) on the data and its origin:
      “Surface irradiances included in this dataset are from the CERES Energy Balanced and Filled (EBAF)-Surface Ed2.8 data product (Kato et al. 2013). They are computed using MODIS-derived cloud properties (Minnis et al. 2011) and atmospheric properties (temperature and humidity profiles) given by the Goddard Earth Observing System (GEOS-4 and 5) Data Assimilation System reanalysis (Bloom et al. 2005; Rienecker et al. 2008). To account for the diurnal cycle of cloud properties between 60°N and 60°S latitude, cloud fraction and cloud top height derived from five geostationary satellites (Minnis et al. 1995) are also used. Geostationary satellites are calibrated against MODIS (Doelling et al. 2013). Other inputs for irradiance computations include ozone amount (Yang et al. 2000), ocean spectral surface albedo from Jin et al. (2004), and broadband land surface albedos that are inferred from the clear-sky CERES measurements (Rutan et al. 2009). Because computed TOA irradiances do not necessarily agree with CERES-derived TOA irradiances, computed TOA irradiances are adjusted to be consistent with CERES-derived TOA outgoing shortwave radiation (rsut, rsutcs for clear-sky) and outgoing longwave radiation (rlut, rlutcs for clear-sky) from EBAF-TOA Ed2.8 (Loeb et al. 2009; Loeb et al. 2012). TOA irradiance adjustments are made by adjusting inputs (surface, atmospheric, and cloud properties). In the adjustment process, CALIPSO, CloudSat, and AIRS observations are used to constrain cloud and atmospheric properties (Kato et al. 2013).”
      http://ceres.larc.nasa.gov/documents/cmip5-data/Tech-Note_CERES-EBAF-Surface_L3B_Ed2-8.pdf

  10. Willis
    ALL satellite data is calculated and not observed. Why are you surprised? Because it is accurate and correlates with other readings? Those effing things are up there for a reason.

    • Alex, 97% correlation with any independent thing surprises me.
      That’s seems to provide evidence that the two methods are referring to something independent of their own workings.
      In short – it provides evidence that they reflect an independent reality.
      In the land of complex climate science that is unusual.

      • MCourtney
        You could be right. Perhaps there was ‘calibration’ that we aren ‘t aware of. I know from my experience in the engineering/scientific world that the correlation would not be unusual. Dealing with climate science? God knows. Maybe I’m just a dreamer with rose coloured glasses. Stop being horrible and leave me with my hallucinogenic dream.

      • Alex, I’d love to leave you in your hallucinogenic dream. But you said those satellites were up there for a reason… and then that some effective calibration may have happened without any acknowledgment.
        Yet satellites are expensive. It wouldn’t be an accident that they are up there. That would mean forethought in dishonesty.
        Nah.
        These satellites were put in space to seek reality.
        And I think they found it.

    • Alex February 22, 2015 at 6:16 am

      Willis
      ALL satellite data is calculated and not observed. Why are you surprised? Because it is accurate and correlates with other readings? Those effing things are up there for a reason.

      Thanks, Alex. While you are correct, you are overlooking an important distinction. The CERES TOA radiation datasets are based on CERES satellite observations. The CERES Surface product is not. The surface product is a “constrained” product, meaning that it is the best estimate of a physical system given that the estimate has to satisfy a variety of constraints. These constraints are based mostly on the CERES TOA radiation datasets, along with other datasets.
      This makes the CERES Surface radiation datasets a different kind of creature than the TOA datasets. Among other significant differences, the errors of the surface dataset come from a much wider variety of sources. This means that the errors in the surface dataset are going to be larger than those of the TOA dataset.
      That’s why I was so interested in looking at how well the surface datasets match the TAO buoy data, so I could know how much trust to place in the surface results.
      Regards,
      w.

  11. Looking particularly at 2010, equatorial 165e/170w. There is an inverse correlation between down welling (440 spike ) and available solar at the surface (150 valley).
    What would cause this and why such a major extreme during that time period?

  12. Mr. Eschenbach,
    What albedo did you use for your S-B calculation? You really need a full spectral measurement of radiation from the surface to get a good measure of temperature. An albedo of 1 would give you the lowest possible temperature. Lower albedos would give higher surface temperatures.

    • Albedo is irrelevant if you know the peak wavelength of emission. Peak wavelength determiunes temperature and not intensity. I actually have no idea as to how Willis applied Sand B in this case.

      • Albedo can be a strong function of wavelength so the peak of the emission spectrum may not be at the peak of a Planckian (it usually is however). Regardless, the Stephan-Boltzmann relation is a power balance equation using a mean albedo while the Planckian spectrum has wavelength info. Which one is being used? The article said S-B. No wavelength info there.

      • rbspielman
        I was only referring to albedo. Blackbody, greybody peak (wavelength) emission is the same, just a different intensity. If you are referring to ‘non gray bodies’ then I am out of here

    • So far as I know “albedo” is exclusively reserved for the reflectance of the incoming solar spectrum energy. If the spectrum is not solar it is NOT a component of albedo.
      Useful solar spectrum is 0.25 to 4.0 microns containing 98% of the total solar energy.
      At ocean surface Temperatures, the operational BB (Planckian) spectrum is 5.0 to 80 microns which is mutually exclusive with the albedo spectrum.
      So surface emitted LWIR has no association with earth’s albedo.
      g
      Funded by a grant of the Government of New Zealand.

    • But there is a sharp downturn this last week in the Arctic sea ice , according to the reference Sea-Ice page .
      Almost looks as if maximum ice has been reached a month or 3 weeks ahead of “schedule”.

      • Could be. Note that short term changes in sea ice are driven more by winds and currents than by temperature, so not much can be inferred from them (except re winds and currents).

      • But there is a sharp downturn this last week in the Arctic sea ice , according to the reference Sea-Ice page .
        Almost looks as if maximum ice has been reached a month or 3 weeks ahead of “schedule”.

        No, not really. The Arctic sea ice is just bouncing along right at the -2 std deviation curve like it has the past two years.
        http://nsidc.org/data/seaice_index/images/daily_images/N_stddev_timeseries.png
        The Arctic sea ice area, and sea ice extents will peak near the end of March, first week in April. Now, we are near the top of the total area curve – and, like all cyclical curves, the top represents a long “flattish” period of almost no net growth, but almost no net loss either. So we will not see any large increase in Arctic sea ice extents either.
        But, do you see that the entire Arctic sea ice area (less the extreme south tip of Bering Sea and Hudson Bay is still in the “dark” right now? There is no sunlight energy up there yet!

      • Making all that ice dumps lots of sensible heat into the atmosphere as the water changes state. Does it also spike OLR?

      • Ren:
        The Great Lakes “sea ice” behaves much more like Antarctic sea ice (because the Great Lakes at 42, 43, 44, 45, 46 degrees) are at latitudes much more comparable in reflecting solar energy than the Arctic sea ice up between 81 north to 71 north latitudes. BUT! The Great Lakes are NOT included in the “Arctic sea ice” totals by any of the many different national labs that track sea ice. (Neither is the permanent Antarctic shelf ice grounded near the Antarctic continent. )
        So, any increased ice on the Great Lakes or around Antarctica from normal levels DOES reflect significant amounts of solar energy from the planet, thus cooling the planet immediately. (The energy is reflected away in seconds, never available to be absorbed into the dark lake waters to slowly heat the region later.)
        Decreased sea ice in the Arctic any months of the year from mid-August through mid-April COOLS the planet because the “missing” sea ice increases heat losses to space from increased conduction, LW radiation, evaporation, and convection. May-June-July? Different story obviously. Decreased Arctic sea ice in those three months does heat the Arctic Ocean because more solar energy is absorbed into the sea than is lost from the exposed ocean surface. But only during those three months.

  13. Willis,
    Are the DLR figures that the TAO buoys provide based on measuring incoming thermal infrared in the spectrum of (4 – 100 µm) or is it “calculated” using temperature and humidity?
    After all, “DLR or back radiation from the atmosphere to earth is a fundamental pillar of CO2 alarmism.”
    http://claesjohnson.blogspot.com/2011/08/who-invented-downwelling-longwave.html
    From Poster:
    The DLR is derived from several sensors (METEOSAT, MSG) using various approaches, in the framework of the projects.
    From Geoland:
    However Radiative Transfer Models (RTM) may be used to estimate DLR from atmospheric profiles (temperature and humidity).
    Then there is this:
    http://claesjohnson.blogspot.com/search/label/myth%20of%20backradiation

    • Most all ground-based measurements of that so-called “sky radiance” presumably welling down to the surface are done either by pyrgeometers or by spectroradiometers. The former don’t measure (as in ‘detect’) such radiation at all. They are so-called ‘thermal detectors’. They register only the ‘net’ radiative flux (that is, the radiative HEAT flux) at the sensor, expressed as a certain voltage signal (positive or negative, depending on what way the heat goes). Knowing, then, the sensor temperature as well, the instrument computes a hypothetical “sky radiance” flux for you, and you are free to believe that this calculated output constitutes a real, thermodynamically working flux (transfer) of energy down to the warm surface from the cold sky.
      The latter instrument needs for its detector to be colder than the air layers above it for it to “experience” any incoming radiation from the sky at all. As in all such cases, you need a heat transfer to detect. It is ALWAYS the heat transfer that is actually detected. The cold detector of a passive spectroradiometer (like the AERI, for instance) is not the warm surface of the Earth. The surface of the Earth can never “experience” any incoming radiation from the sky like this detector does. Not until it becomes colder than the sky. Like the detector. These so-called ‘photonic’ (or ‘quantum’) detectors are held at cryogenic temperatures, normally around 77 K. At this temperature their ‘self-radiation’ would be so weak that they could safely be neglected facing any incoming EM wavetrain from even a pretty cold point or region in the sky. This point/region could therefore be regarded as a ‘pure emitter’ to the detector, meaning, there would be a practically pure radiative heat transfer from the sky to the detector. In the available spectral bands.
      This can easily be shown through the Stefan-Boltzmann equation.
      Let’s say a certain atmospheric layer whose thermal radiation is able to reach our instrument detector, holds a temperature of 250 K. That’s pretty cold. -23°C. If this layer faced a perfect vacuum at 0 K and could be approximated as a blackbody, it would emit a clean radiative heat flux to the vacuum at absolute zero like this:
      q = σ * 250^4 = 221.5 W/m^2
      If it were rather faced with our detector at 77 K, how much would this radiative heat flux (q) be reduced?
      q = σ (250^4 – 77^4) = 219.5 W/m^2
      By 0.9%. That’s not a lot.
      In reality, each single layer of atmosphere could not function as a full blackbody radiator to the detector. Only certain wavelengths of radiation would be able to pass through the intervening layers, wavelengths that weren’t already ‘covered’ by those closer layers. The detector receives the total, cumulative radiance from all the layers above it, as far as it can see (normally a few kilometers up, or to some impenetrable cloud layer).

  14. A quiet thread, a good thread to ask about actual longwave radiation losses from (real) surfaces into (real) atmospheres.
    Yes. An isolated perfect gray body of emissivity “e” at a perfectly uniform temperature of T degrees K sitting in a perfect vacuum inside a black body of space at 0.0 deg K will emit from all surfaces
    LW = S-B * e * (T^4)
    But.
    That is not where we are. There is a LOT of disagreement about “real” LW radiation losses – once you get away from a perfect gray body sitting in space. But I have not seen the actual calculations presented thoroughly, when they are presented at all. And none have used “measured” data of humidity, winds, and air temperatures – as if nothing existed between ground (or ice, or water) and the cold nothing of interstellar space.
    Space is essentially “black”, at 3 deg K. That doesn’t change with weather.
    The stratosphere? Not too much of a change: T_sky = -40 deg C almost all of the time at 15,000 meters (40,000 + feet ASL).
    Mid-level and low-level air? Well, that IS weather. And it controls radiation loss, right? I’ve worked outside overnight in calm, clear cold nights: It’s bitter. Worked outside in foggy, humid nights with low cloud cover. But I don’t see the climate community organizers actually calculate the respective radiation losses. They “talk” about the two cases frequently, if not all the time. They just don’t calculate them. (They don’t calculate daylight LW radiation losses either.)
    So, what is the actual LW radiation loss from a flat surface at sea level of T_surf, E_surf, into a real atmosphere of:
    1. Hot weather, cloudy. Air temp = 35 deg C dry bulb, 30 deg C dew point (or wet bulb if you prefer), 1000 pressure, cloudy sky, winds = 3 m/sec?
    2. Very cold weather, absolutely “clear”, low humidity. Air temp = -10 deg C dry bulb, 15% relative humidity. No clouds, 1020 pressure, winds = 0.25 meter/sec.
    3. Cold weather, higher humidity, overcast with low clouds at 1500 meters. Air temp = 5 deg C, relative humidity = 60%, 980 barr pressure, winds = 2 m/sec?

      • If those questions are to be dealt with, the article should also deal with the fundamental point made by Kristian at February 22, 2015 at 10:29 am.
        It could be a very interesting article.

    • Since detectors cannot routinely be chilled to a cryogenic low point, de facto the ambient temperature is the set point. If the pyro gains no heat, the sources around it and its target are at ambient. If it loses heat, it is emitting more than receiving, and the target is cooler, etc. Calculating that temperature would be a non-linear transform and conversion depending on ambient. “It’s all relative.” But AFAIK no such compensation is attempted.

  15. I understand that you are inherently skeptical of a TOA calculation that produces an effect that you disagree with. However, claiming that you are attempting to find a new TOA calculation result that uses a significantly smaller monitoring area (Equatorial region) than the CERES-EBAF (global series) is hardly a convincing argument!

    • I’m sorry, but I don’t understand your post at all. Willis is doing a comparison of the CERES-EBAF-Surface data (which is acknowledged as calculated, not measured) against the TAO bouy set of data. Where does that mean he’s attempting to find a new TOA calculation result? I would say he’s doing a verification of the accuracy of that calculation, not trying to find a new calculation.
      I would personally think that, assuming the two data sets are completely independent, it’s a useful confirmation that both sets of data agree with each other and therefore can be (subject to evidence that they aren’t independent) trusted to be reasonable reflections of the ‘truth’. At least with respect to equatorial ocean data.

    • “you” in your comment is presumably Willis. But I cannot relate your comment to Willis’ article. If I understand him correctly, Willis is not disagreeing with anything, he is using an opportunity to test the surface calculations from CERES against surface data from TAO. Since TAO operates in the tropics, that’s where the test takes place – and Willis acknowledges the incompleteness of the test. The really interesting thing about the test is that it shows remarkably good agreement between CERES and TAO. Assuming that there isn’t some factor that Willis has missed that makes this an artificial result (eg, if CERES had been calibrated against those same TAO measurements) then Willis has IMHO come up with a very valuable finding, namely that the CERES surface calculations are remarkably accurate over the tropical ocean.
      For my part, and subject to the above assumption, I would like to congratulate Willis for conducting the test and publishing its result regardless of whether it was what he was expecting. I would also like to congratulate the CERES team for a job well done. I also note that all of the satellite teams appear to produce work very high quality – a quality which is unfortunately not always matched in some other areas of climate science.

  16. Hello Willis.
    Congratulation for your amassing approach in this matter and issue.
    Before I go any further I have to say that I am in a Mosher like attitude, having one too many drinks, but never the less I will try to drive my point through.
    From where I stand, you seem to have the ability and the .skill to bring up very interesting points.
    So Cutting it short, as far as this posting of yours goes, from my point of view is in the same great approach as the previous one.
    Believe me, I say this because I have learned a great deal, because of your expertise and the intellectual approach you show.
    Now as far as this matter goes per relevance to the point you try to brink up, one thing or few do seem to raise a confusion.
    Simply put, whether your approach simply showing a very weird and odd coincidence or not, it means for as far as I can tell that, if by some chance that is not an weird and odd coincidence than some how you have nailed further into AGW by showing that the tropics and global are at the same pattern.
    If the expected measurable impact of AGW not seem to be happening in tropics, your very close and exact calculation when compared to the CERES, MEANS THAT THE SAME HOLDS TRUE.for the globe.
    But never the less if this not a figment of imagination, due to some weird coincidence, then it also means that the hypothesis that CO2 in not increasing RF is a bollocks too.
    You see, these both require that in the short term data you relied up on,, is shown much more deference.
    Only in a CO2 causing increment of RF you get the result you have got at the end, regardless how accurate the CERES or you are in your calculation of the surface radiation.
    Only when Co2 emission cause an increment of RF you get such a close match between the CERES and your calculation, otherwise that very close match means that is only an odd coincidence or if not than your believe of CO2 emission not increasing the RF is bollocks.
    Is up to you to choose what the case is.
    cheers

    • Denis, the CERES instruments are quite precise but not extremely accurate. So while they can accurately measure a small CHANGE in a value like say upwelling longwave (good precision), the absolute size of the longwave radiation might be off (bad accuracy)
      Now the basic equation at the top of the atmosphere is that at the mythical equilibrium, or say averaged over the course of the year, energy gains will be very close to energy losses. Otherwise the planet would be radically warming or cooling. The gains are the total incoming solar. The losses are the outgoing reflected solar and the upwelling longwave infrared radiation (ULR) which is the thermal radiation emitted by a combination of the earth and the atmosphere. They should equal each other.
      The problem is … in the CERES dataset the gains don’t equal the losses. Instead, they’re off by about 5 W/m2 or so. And if that were actually the case, we’d see it as a change in temperature.
      So … they adjusted the TOA average imbalance. Which makes sense to me. Unfortunately, they adjusted it to James Hansen’s best guess at the imbalance, which as a warming imbalance of +0.85 W/m2.
      In any case, whether it’s adjusted to zero or to 0.85, the absolute values can’t be trusted. To deal with this I simply avoid depending on absolute values, and I stick to examining things like geographic or annual and decadal trends and variations.
      w.

      • Willis said:
        “The gains are the total incoming solar. The losses are the outgoing reflected solar and the upwelling longwave infrared radiation (ULR) which is the thermal radiation emitted by a combination of the earth and the atmosphere. They should equal each other.”
        Good point. They MUST equal one another if an atmosphere is to be retained at all.
        Incoming solar must stay the same and be matched by outgoing longwave plus reflected solar over time so the only variables are the thermal radiation emitted from each of earth and atmosphere and reflection.
        It must follow that if one variable rises then the others must fall and vice versa.
        What enables that equal and opposite adjustment in the thermal radiation from earth and atmosphere?
        I have told you that the adjustment mechanism is variations in the amount of kinetic energy returning back to the surface from the potential energy in the atmosphere during adiabatic descent.
        With water vapour in the atmosphere the albedo can also vary which provides another adjustment mechanism but in the absence of water vapour it would still work via changes in adiabatic descent.

    • Steven Mosher: the physics that skeptics deny or question.
      My “or question” is that too little is known about changes in non-radiative transfer of energy from surface to troposphere; and a few other ways that the “physics” of radiative transfer models are incomplete. Good efforts to fill the gap include the studies surveyed in:
      “Energetic Constraints on Precipitation Under Climate Change” by O’Gorman, Allan, Byrne, and Previdi: Surveys in Geophysics, DOI 10/1007/s10712-011-9159-6.
      They report estimates of 2% – 7% increase in rainfall in response to a 1C increase in temperature. With surface evapotranspirrative cooling estimated at 80 W/m^2 (Trenberth et al), those estimates indicate a non-ignorable amount of increased surface cooling to be caused by a 1C increase in surface temp. The lower estimates are produced by GCM-based analyses, the upper estimates based on regressions of rainfall vs temp in diverse parts of the Earth.

      • My “or question” is that too little is known about changes in non-radiative transfer of energy from surface to troposphere; and a few other ways that the “physics” of radiative transfer models are incomplete.
        I wait for your publications.

      • Steven Mosher: I wait for your publications.
        Me too.
        Meanwhile, assume for the sake of argument that the rate of heat loss due to evaporation will increase 5% per 1C increase in surface temp. Assume Stefan-Boltzmann law is reasonably accurate. Assume that DWLWIR increases 4 W/m^2 and that the temperature warms up. When it has warmed 0.5C, evapotranspiration heat loss will have increased by 2W/m^2, and radiative heat loss by about 2.8W/m^2 — implying that the DWLWIR increase of 4 W/m^2 can not raise the Earth surface temp by 0.5C. Obviously these are approximations (based on flow rates by Trenberth), but there is no justification for ignoring the change in the evapotranspirative heat loss rate.
        Anybody can easily repeat these calculations with different published values of the estimated constants and estimated changes. Do you need the imprimatur of a journal reviewer to think about them for a while?

    • Steven Mosher February 22, 2015 at 10:39 am
      The key physics to getting the answer correct is radiative transfer models.

      This presumes that:
      a) the radiative transfer models are themselves correct, and;
      b) there are no other significant processes outside radiative transfer that are significant
      Given that the IPCC in AR5 chose to substitute “expert opinion” over output model in regard to sensitivity, it seems that your complaint that:
      the physics that skeptics deny or question.
      should not be constrained to skeptics alone.

      • davidmhoffer, at the risk of repeating myself, let me support your point.
        Meanwhile, assume for the sake of argument that the rate of heat loss due to evaporation will increase 5% per 1C increase in surface temp. Assume Stefan-Boltzmann law is reasonably accurate. Assume that DWLWIR increases 4 W/m^2 and that the temperature warms up. When it has warmed 0.5C, evapotranspiration heat loss will have increased by 2W/m^2, and radiative heat loss by about 2.8W/m^2 — implying that the DWLWIR increase of 4 W/m^2 can not raise the Earth surface temp by 0.5C. Obviously these are approximations (based on flow rates by Trenberth), but there is no justification for ignoring the change in the evapotranspirative heat loss rate.
        Anybody can easily repeat these calculations with different published values of the estimated constants and estimated changes. Does anyone need the imprimatur of a journal reviewer to think about them for a while?

      • If the models have if right they would do a better job of predicting the temperature of the globe. As per my question above, what is the bias and variance of these ‘correct’ calculations?

  17. I am thinking circular reasoning. The satellite does not measure LW radiation.. it measures voltage or current, not photons directly. To figure out what the ‘reading’ really means, one can calibrate in a lab, but that assumes that one has a perfect test chamber to mimic the world OLR frequencies and thus the CERES input. No way.
    I would suggest one would use the very TAO buoy data set that Willis used. Some other data set would be used for say an area of ice. Thus the instrument ‘readings’ can be translated back to worldwide temperatures.
    Of course one would get a 99% correlation with the buoy data set if it was used to calibrate CERES. Circular, yes or no?

    • ECB,

      Of course one would get a 99% correlation with the buoy data set if it was used to calibrate CERES. Circular, yes or no?

      Only if the argument is: the buoy data are accurate because CERES agrees with them.

    • Brandon
      The CERES data comes from the top of the atmosphere. Read:
      ” It is usually referred as the CERES “top-of-atmosphere” data. The official name is “CERES EBAF-TOA”, and it is available here.
      However, the second part of the CERES is not top-of-atmosphere observations from the satellite. Instead, it is calculated surface data based on the CERES TOA observations along with other satellite observations. It’s called the “CERES EBAF-Surface” dataset, and is available from the same location.”

  18. “convert the CERES surface radiation data into temperature by using the Stefan-Boltzmann relationship.”
    What was the emissivity used; 1?

    • DocMartyn,

      What was the emissivity used; 1?

      This came up on Willis’ SURFRAD article a few months back, and IIRC using an emissivity of unity worked rather well.

    • Emissivity includes a “time” component. If you don’t know the lag between when the energy came in and when it was subsequently emitted, and if you don’t have several days of all these measurements timed to the trillionith of a second, then what is the emissivity?
      Heat up an iron bar in a room at room temperature. The iron bar will absorb the energy for quite some time before its starts to emit that energy back. The emissivity is therefore Zero.
      After you stop adding energy to that iron bar, it continues to emit energy until it reaches room temperature. Emissivity is therefore infinite and is actually an undefined quantity.
      Emissivity has been used as a redirection for far too long. We are talking about objects that absorb energy and re-emit virtually all of that energy within picoseconds. At most, it is a few minutes to an hour. Emissivity can be assumed to be 1.0 unless you can measure all those “time elements” to a pico-second level.
      Measure the emissivity of soil throughout a 24 hour day and then come back and tell us assuming 1.0 is not correct. If one actually did so, one would find that the soil is emitting back virtually 99.999992% (0.008 joules/second divided by 1000 joules/second) of the energy it is receiving in any one second. That difference is enough to allow the soil to slowly warm up throughout the day by 15C or so and then slowly release that energy throughout the night so that it is about the same temperature the next morning. I call that close enough to 1.0.

      • Bill Illis, Willis E.

        Measure the emissivity of soil throughout a 24 hour day and then come back and tell us assuming 1.0 is not correct. If one actually did so, one would find that the soil is emitting back virtually 99.999992% (0.008 joules/second divided by 1000 joules/second) of the energy it is receiving in any one second. That difference is enough to allow the soil to slowly warm up throughout the day by 15C or so and then slowly release that energy throughout the night so that it is about the same temperature the next morning. I call that close enough to 1.0.

        True, very true. These calc’s “assume” that temperatures are static, are in equilibrium.
        But they are not: You’ve made a good assumption for the static (stays in place) soil mass exposed to solar radiation. The steel bat heats up to a static temperature within 15 minutes (1 x 1 x 48 inch, heated at one end by an oxy-acetelyne torch will get that hot. then stay at the same temperature as long s the heat continues to be applied.
        BUT.
        The heat into the bar (the end being heated) is not “all” going out as radiation. (Which, for an isolated planet in space, or an isolated/insulated/insolated iceberg sitting in space radiated by the sun on only one side, you can “sort of” make that assumption. But the steel bar I heat up with the torch is losing heat by conduction down the bar, by conduction to the clamp and the vise it is held up by, by convection of the air around the bar, and (where it like the iceberg sitting the Arctic Ocean, by evaporation and air flow by the wind across the top and by convection into the water below.
        ALL of those heat transfer mechanism go on simultaneously. So, you CANNOT p”calibrate nor even compare the radiated heat out of an iceberg/ice cap to the radiation received. Too much other heat transfer mechanisms are going on.
        Reflected thermal SW and IR radiation occurs instantaneously. Conducted heat is lost more slowly. Convection (by definition) is lost to the other moving liquid or gas. That gas must be removed from the surface to be replaced by fresh fluid.
        Radiation thermal loss is “instantaneous” but the energy lost is only that which can get transported (usually by convection and conduction) from another area to the radiating area. (Power supply gets hot, power supply heats a radiator, radiator fin starts to get hot and begins radiating. But that fin is not yet as hot as the original power supply was. And it will never get as hot as the original power supply. )

      • RA Cooke said
        “ALL of those heat transfer mechanism go on simultaneously. So, you CANNOT p”calibrate nor even compare the radiated heat out of an iceberg/ice cap to the radiation received. Too much other heat transfer mechanisms are going on. ”
        Absolutely right and that goes to the heart of a point I put to Willis and others elsewhere, namely, that if energy is involved in conduction/convection it cannot also radiate at the same time.
        That is why I propsed a separate adiabatic energy exchange between surface and atmosphere which is maintained as long as insolation continues whilst new radiative energy coming in flows straight out again through a discrete diabatic energy exchange between surface/atmosphere and space.
        The global thermostat can then seen to be the adiabatic energy exchange which varies precisely and oppositely with variations in the diabatic energy exchange.
        Convection acts as the regulator between radiation and conduction and duly reapportions energy between those two processes as necessary to maintain thermal equilibrium at any given level of incoming radiation.
        .

      • Stephen Wilde says, February 23, 2015 at 12:32 am:
        “(…) if energy is involved in conduction/convection it cannot also radiate at the same time.”
        The ‘radiationers’ are seemingly completely blind to this fact. And they have been blinded by invariably looking at cases where such other heat transfer mechanisms for various reasons are not operating, that is, where the heat transfer is purely radiative. So they interpret all the radiation laws as if they were universal. But they are only universal in … purely radiative situations.

      • Stephen 12:32am, Kristian 4:39am: “..if energy is involved in conduction/convection it cannot also radiate at the same time….The ‘radiationers’ are seemingly completely blind to this fact.”
        Radiationers? LOL, please now explain who they would be. Note that CERES only measures radiative energy data. As Stephen notes CERES is blind to energy transport in surface conduction/convection (thermals) or evapo-transpiration at the same time – yet Willis work shows the surface temperature data is reasonably calculable from CERES radiative only data. No knowledge of the energy in thermals or evapo-transpiration is necessary to get the surface temperature from CERES EBAF. Maybe Kristian’s blind ‘radiationers’ are on to something. Is Willis thus a radiationer?

      • Trick says, February 23, 2015 at 6:03 am:
        “Radiationers? LOL, please now explain who they would be.”
        People like you, Trick. Thanks for presenting yourself 🙂
        “Note that CERES only measures radiative energy data.”
        CERES only measures radiances from the ToA to space, Trick. It doesn’t ‘measure’ any UWLWIR flux at the surface, if that’s what you think.

      • Kristian 8:00am: CERES measures incident radiation at its orbit so if you read top post again understand EBAF calculated reasonable surface temperature from that radiation data as Willis shows. Call it what you will.

      • Trick says, February 23, 2015 at 8:56 am:
        “CERES measures incident radiation at its orbit so if you read top post again understand EBAF calculated reasonable surface temperature from that radiation data as Willis shows. Call it what you will.”
        You don’t get it, do you? CERES couldn’t possibly calculate surface temps from its own IR flux readings from space alone. It could only possibly ever do so by determining peak wavelength of the atmospheric window radiation.
        Did you notice the part about CERES needing lots of additional input from other sources to its heat transfer model in order to be able to calculate anything at all at the surface?
        You can find out about it upthread. Or you can check this out:
        http://ceres.larc.nasa.gov/documents/cmip5-data/Tech-Note_CERES-EBAF-Surface_L3B_Ed2-8.pdf

      • Kristian 9:35am – I know that Kristian, that’s why they call it CERES EBAF-Surface. You should read your own link to learn about the EBAF “radiationer” (Kristian term) processing that Willis writes about in the top post – which does a reasonably “good showing” (Willis term) calculating surface temperature using remote sensing methods when Willis compared to TAO buoy in situ measured sea surface temperature (SST). There are whole books written on remote sensing, recommend Kristian brush up on one.

      • Trick says, February 23, 2015 at 10:56 am:
        “You should read your own link to learn about the EBAF “radiationer” (Kristian term) processing that Willis writes about in the top post – which does a reasonably “good showing” (Willis term) calculating surface temperature using remote sensing methods when Willis compared to TAO buoy in situ measured sea surface temperature (SST).”
        Yes, and this has exactly what to do with my original comment about the ‘radiationers’ that you replied to? In none of your responses here have you addressed at all what I actually pointed to. Only performing good ol’ misdirection.

  19. This is a very nice piece of analysis. However, the surface temperature is estimated by observing the LWIR emission through the atmospheric transmission window. There is no connection between the atmospheric LWIR emission from the water and CO2 bands at the top of the atmosphere and the surface temperature. The atmospheric emission to space is rate limited by the water vapor concentration. The water band emission changes in altitude as the heat stored in the troposphere changes.
    The troposphere is an open cycle heat engine, not an IR spectrometer. The temperatures in the troposphere are determined by the lapse rate, not the LWIR emission. The LWIR flux is fully coupled to the heat capacity of the troposphere. It cannot be treated independently. The radiative change in temperature is the time integrated change in LWIR flux divided by the heat capacity. Almost of the LWIR flux exchange between the troposphere and the surface takes place within the first 2 km layer of the troposphere and a third to a half of this is within the first 100 m of the surface. The LWIR emission to space is from the middle to upper troposphere. This is the cold reservoir of the atmospheric heat engine. Energy conservation only requires that the net long term emission to space from the cold reservoir and the transmission window balance the absorbed solar flux. Heat is stored and released by the climate thermal reservoirs, and by water evaporation and condensation.
    Ocean surface temperatures are determined by the energy balance between the solar heating, the net LWIR emission and the wind driven evaporation. All of the cooling and LWIR absorption/emission occurs within an ocean surface layer less than 1 mm thick. The cooler surface water then sinks and cools the ocean below. Approximately half of the solar flux is absorbed within the first 1 m layer of the ocean and about 90% total is absorbed within the first 10 m layer.
    In good round numbers, in the Pacific warm pool, under full tropical sun illumination at a surface temperature near 30 C, the average solar flux of 250 W m^-2 is balanced by 50 W m^2 net LWIR cooling and 200 W m^2 of wind driven evaporation at an average wind speed near 5 m s^-1. A change of 1 m s^-1 in wind speed changes the evaporative cooling by 40 W m^-1. The total increase in net LWIR from CO2 over the last 200 years is approximately 2 W m^-2. In the warm pool this corresponds to a change in wind speed of 5 cm s^-1. This change in CO2 flux is far too small to have any effect on surface temperatures.
    The ocean evaporation depends on the difference in ocean and air humidity and the wind speed. This has been investigated in detail by Lisan Yu and coworkers at Woods Hole, http://oaflux.whoi.edu/heatflux.html.
    How much heat is removed from the oceans by wind driven evaporation? This is real source of weather and climate change.

    • Ah, but you use “average” numbers there.
      On the water surface near the equator, the ocean actually receives over 1000 watts/m^2 at noon, and 900+ watts/m^2 from 9:00 to 15:00 (pm) .. and near-zero at other times. So, your evaporation rate, and heat up rates for that square meter need to reflect not the average heat received, but the instantaneous heat gain and heat loss.

      DOY = 	53		LAT Deg =	-4	-0.06981317	= LAT Rad
      Hour	Tau 	 Decl 	 HRA 	 SEA	SEA	Air	DIR	DIR     DIR    Cos(SZA) Ocean   Watts   Watts
                               radian  radian degree  Mass    atten.  perp    horiz   radian  albedo  absorb  refl
      0.00	0.895	-0.1829	-3.1416	-1.3180	-75.5	0.000	0.000	0	0	-0.968	0.000	0	0
      1.00	0.896	-0.1827	-2.8798	-1.2079	-69.2	0.000	0.000	0	0	-0.935	0.000	0	0
      3.00	0.897	-0.1822	-2.3562	-0.7492	-42.9	0.000	0.000	0	0	-0.681	0.000	0	0
      5.00	0.899	-0.1816	-1.8326	-0.2437	-14.0	0.000	0.000	0	0	-0.241	0.000	0	0
      7.00	0.900	-0.1811	-1.3090	 0.2698	 15.5	3.706	0.344	479	128	0.267	0.201	102	26
      9.00	0.902	-0.1806	-0.7854	 0.7845	 44.9	1.414	0.666	926	654	0.706	0.066	611	43
      11.00	0.903	-0.1800	-0.2618	 1.2888	 73.8	1.041	0.741	1031	990	0.960	0.066	925	65
      12.00	0.904	-0.1798	 0.0000	 1.4608	 83.7	1.006	0.749	1041	1035	0.994	0.066	966	68
      13.00	0.904	-0.1795	 0.2618	 1.2890	 73.9	1.041	0.741	1031	990	0.961	0.066	925	65
      15.00	0.906	-0.1790	 0.7854	 0.7846	 45.0	1.414	0.666	926	654	0.707	0.066	611	43
      17.00	0.907	-0.1784	 1.3090	 0.2697	 15.5	3.706	0.344	479	128	0.266	0.201	102	26
      19.00	0.909	-0.1779	 1.8326	-0.2442	-14.0	0.000	0.000	0	0	-0.242	0.000	0	0
      21.00	0.910	-0.1774	 2.3562	-0.7505	-43.0	0.000	0.000	0	0	-0.682	0.000	0	0
      23.00	0.912	-0.1769	 2.8798	-1.2119	-69.4	0.000	0.000	0	0	-0.936	0.000	0	0
      									7088			6577	511
      Note: Every other hour shown, all 24 used in totals.                    total                   total   total
                                                                              watt-hr                 watt-hr watt-hr
      

      This calculation displays direct radiation only, today (22 Feb) for lat -5 south.
      Atmosphere attenuation = 0.75 per measurements (Bason, Accra, Ghana 2006. Clear days, no clouds, 5.5 degree Lat N.)

    • Regarding the emissivity of soil – the description above is of the soil slowly changing temperature with the sun besting down and thus the E value is high, nearly One. A counter argument is that there is conduction of heat into the ground.
      Soil has an emissivity of about 0.93, is a poor conductor and the difference in heat gain is probably loss of moisture. Obviously soil is different in colour from place to place, but 0.93-0.95 is a pretty good start for making calculations. Not very many ordinary objects are 0.99. A fresh, untouched, sooty pot bottom is a possibility.
      Dry soil heats up Far more rapidly than damp soil. And conducts less. Water and water vapour have a higher emissivity than soil (and most things).

    • “Approximately half of the solar flux is absorbed within the first 1 m layer of the ocean and about 90% total is absorbed within the first 10 m layer. ”
      From the article http://wattsupwiththat.com/2013/10/28/solar-spectral-irradiance-uv-and-declining-solar-activity/ the graphic below indicates his estimate, which varies from yours, where the integrated solar spectral energy ocean penetration looks to equal 50% at about 0.1 meter, not 1 meter. Please correct me if that’s wrong.
      http://wattsupwiththat.files.wordpress.com/2013/10/ocean-penetration-by-solar-spectrum1.png

  20. There was a lot of “ground truthing” of this data both before and during the era of the current satellites. We participated in an exercise at the NASA Marshall Spaceflight Center (MSFC) where our satellite would carry narrowband filters at the knee of the curve (3db point for you EE’s), of the absorption features in the visible spectrum. These were the same filters (bandwidth wise [5,7,10 nanometers]) as would have been carried on the Terra and Aqua satellites.
    At MSFC they were going to have a spectral radiometer that would have the same filters, thus enabling the establishment of the bi direction extinction coefficients for the principle absorption features in the visible band. While our satellite was never able to do this due to a malfunction in the receiver. This has been done for well over a decade at MSFC and as Steve Mosher pointed out, at LARC as well. NASA JPL also has the AVRISS program which is a high altitude version of the space based sensors.
    Thus, there is considerable validation of these measurements.
    The problem is that they have not gone back and taken the historical data from the USAF from the 1950’s where this was first measured down to the individual wavelengths to then to a qualitative comparison at the individual absorption/emission line level (especially in the IR), so that we could get the proper calculations done.
    Most on the AGW community use Plass’s measurements from the late 50’s and early sixties. (Gavin Schmidt specifically references his papers). However, Kaplan showed that Plass’s measurements were more than a factor of 2 off (exaggerating the effect of CO2) over the actual measurements done by the USAF at the time.
    Part of the problem is that we have lost a lot of this old data (technoarchaeology again), and thus this allows FUD to be spread by the pro AGW community that may not be justified.

  21. SOO … you have some nice correlations … but where is the “surface data graph” calculated from this wonderful correlation??
    Maybe the woodfortrees guys could add the CERES calculated surface temperature to the mix on their site …. so as to allow comparisons with the other products, … um .. like GISS!! We might just find that NASA has conflicting data within its own offices!!

  22. Eric Worrall February 22, 2015 at 12:49 am

    Given the calibration errors are so large, what is the explanation for the close correlation between TAO and CERES? Could CERES have been actively calibrated against TAO, or a closely related data set?

    Reply
    evanmjones February 22, 2015 at 6:15 am

    Neither of the two satellite metrics calibrate against surface data. It’s straight MW conversion. A few years back, Dr. Christy was very vehement on that, and I trust him implicitly in this.

    Thanks, Evan. Those “two satellite metrics” don’t include CERES. They are the UAH MSU satellite temperature data product and the RSS MSU satellite temperature data product.
    Reply
    See – owe to Rich February 22, 2015 at 2:47 am

    Two comments, Willis:
    First, please can you consider Eric Worrall’s question carefully? It is one that would not have occurred to me.

    And a good question it is. As I said in the head post, the datasets I’m using are the “EBAF” datasets. This stands for “energy balanced and filled”. This means that the datasets are internally consistent and consistent with the actual TOA satellite observations. There’s a flowchart here showing the path from the raw spectrally-resolved radiance data to the 1° gridded EBAF calculated surface output. There’s also an excellent surface data quality summary here.
    Now, Eric’s question was

    … what is the explanation for the close correlation between TAO and CERES?

    I’d say the answer is that the scientists involved did a good job with the energy balancing and filling. In addition, although the CERES data is not super accurate, it is very precise.

    Second, do you think that CO2 is supposed to increase downwelling LW over time and do you think the CERES graphs refute that?

    Well … that’s a bit hard to say. The problem with looking just at downwelling LW is that if the planet warms or cools, the atmosphere warms and cools, and so we’d expect the corresponding up/down changes in the downwelling LW radiation.
    Lemme take a look … well, that’s interesting. There’s no increase in surface downwelling longwave over the 14 years of the CERES dataset. In fact, it’s gone down by 0.5 ± 0.15 W/m2 per decade, p-value 0.00, over the period March 2000 to February 2014.
    However, that may or may not mean that CO2 is not absorbing more upwelling CO2. The measure for that is how much upwelling radiation is absorbed by the atmosphere … hang on …
    OK, atmospheric absorption has increased by 0.7 ± 0.1 W/m2 per decade, p-value = 0.00. So there’s another oddity for you … atmospheric absorption of upwelling longwave has gone up, but downwelling surface radiation has gone down.
    I would add that both of these represent “porpoising values” that have gone both up and down over the period, and that the data is very short. So I wouldn’t put too much weight on the very slight trends of about half a W/m2 change over ten years … other than to note that half a W/m2 change in ten years is pretty dang stable.
    Nothing like settled science …
    w.

    • Willis, thank you for your replies, especially those new trends you calculated. I was beginning to think you had gone away and left us, but looking at the time stamps and considering your time zone, I am presuming that sleep was a good reason for part of it.
      Cheers,
      Rich.

    • Willis, very interesting. However, you say:
      “OK, atmospheric absorption has increased by 0.7 ± 0.1 W/m2 per decade, p-value = 0.00.”
      Where exactly did you get this information from?
      I thought it was the oceans that were supposed to hold back the energy, accounting for the (postulated) ToA radiative imbalance over the last decade and a half …

      • Good question, Kristian. The atmospheric absorption is from the CERES dataset. It’s calculated as the difference between two datasets, as the surface upwelling longwave minus the TOA upwelling longwave.
        Best regards,
        w.

  23. Willis: What about the consumption of energy via net primary productivity – like plant growth?
    In the paper,
    Loeb, Norman G., et al. “Toward optimal closure of the Earth’s top-of-atmosphere radiation budget.” Journal of Climate 22.3 (2009): 748-766.
    http://www.nsstc.uah.edu/~naeger/references/journals/Sundar_Journal_Papers/2008_JC_Loeb.pdf
    Loeb states ”In an equilibrium climate state, the global net radiation at the TOA is zero.”
    … yet I find no mention of energy stored by photosynthesis.

    • Brian February 23, 2015 at 7:29 am

      Willis: What about the consumption of energy via net primary productivity – like plant growth?

      Interesting question, Brian. While there is energy stored by plants, it’s basically a zero-sum game due to the energy released when the plants die and decay. Overall the two balance each other out.
      w.

  24. Readers might first want to familiarize themselves with
    http://ceres.larc.nasa.gov/documents/STM/2006-10/0610260830Doelling.pdf
    to catch a few definitions.
    While browsing that document, I was able to lift these bullet points:
    There are 4 main CERES product groups

    ERBE-like
    • Uses ERBE algorithms to derive fluxes

    SRBAVG Non-GEO
    • Uses the CERES ADMs to derive fluxes

    SRBAVG GEO
    • Adds geostationary fluxes to improve temporal sampling
    Appropriate Usage:
    The CERES SRBAVG GEO product is the most robust CERES TOA monthly mean flux product, and of climate quality.
    • Most regions sampled twice a day with either Terra or Aqua
    • Terra & Aqua sample the poles up to 14 times/day
    • Even after combining Terra and Aqua, 8 hour gaps exist
    • PM-AM differences can be ~ 30 W/m^2
    • Regional instantaneous differences can be ~ 100 W/m^2
    • 3-hourly GEO fluxes adequately samples the diurnal cycle between ±60° latitude
    • ERBE temporal interpolation assumes constant meteorology (cloud properties) through out the day
    • Over land a half-sine fit is used to model diurnal heating if night time observations exist (Sine fit does not capture peak daytime heating)
    Boldface added by me.
    I was astonished to note that most regions are sampled twice a day, yet morning and afternoon differences can be 30W/m^2 and instantaneous differences can be 100W/m^2 … and gaps between passes of satellites are 8 hours! How many ” instantaneous differences” of 100W/m^2 get ignored? There is a graph of a half-sine wave model-fit, which states that it does not capture peak daytime heating, and the graphic depicts a mismatch on the lower half, too.
    I’m a believer that the earth heats up at the equator, and vents heat to space at the poles (a gross approximation, I’m sure…) so I find the depictions that have equator-centered images, a little lacking. That other part of the bullet point – 3-hourly GEO fluxes “adequately samples” between ±60° latitude … what is missed between N60° to N90° and S60° to S90° latitude?
    … saving the best for last, they assume “constant meteorology” throughout the day? As little as a 5% increase in clouds would be able to deflect all the “global warming” flux:
    Apr 2014: “… a 5% increase of [Stratocumulus clouds’] coverage would be sufficient to offset the global warming induced by doubling CO2”, a conclusion that is also stated by the studies conducted by Randall et al. (1984), Slingo (1990), Bretherton et al. (2004) and Wood (2012).
    Lin, Jia-Lin, Taotao Qian, and Toshiaki Shinoda. “Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models.” Journal of Climate 27.8 (2014): 3000-3022.
    http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00376.1
    To anyone interested, read my long rant, models can’t do clouds at http://wattsupwiththat.com/2014/12/11/mixed-signals-from-the-noaa-enso-blog-about-climate-models/#comment-1811783

  25. Willis replied: “While there is energy stored by plants, it’s basically a zero-sum game due to the energy released when the plants die and decay. Overall the two balance each other out.”
    I understand the concept, but we’re not in a steady-state condition. Increased CO2 is causing a 9% to 200% increase in Net Primary Production (1) and I wonder what amount of energy is consumed.
    CERES will end up counting every erg, joule, and BTU of “fossil fuel” burned, as waste heat. Maybe that is what is cancelled by Net Primary Production.
    Wills, this really isn’t for you, but it seems a good time to post my notes on Net Primary Production as my footnote #1. Folks seem to like the links and brief summary…
    2009: ”… both gross, and net, primary productivity has likely increased over recent decades, as have tree growth, recruitment, … and forest biomass. … potentially from rising atmospheric CO2 concentrations, is the most likely cause.”
    Lewis, Simon L., et al. “Changing ecology of tropical forests: evidence and drivers.” Annual Review of Ecology, Evolution, and Systematics 40 (2009): 529-549.
    http://www.planta.cn/forum/files_planta/changing_ecology_of_tropical_forests_evidence_and_drivers_133.pdf
    2014 Dec NASA NCAR Press Release: ”… add more carbon dioxide to the atmosphere, forests worldwide are using it to grow faster, reducing the amount that stays airborne. This effect is called carbon dioxide fertilization.” Also known as the β effect.
    https://www2.ucar.edu/atmosnews/news/13659/tropical-forests-have-large-appetite-carbon-dioxide
    2015: ”Feedbacks from terrestrial ecosystems to atmospheric CO2 concentrations contribute the second-largest uncertainty to projections of future climate. These feedbacks, acting over huge regions and long periods of time, are extraordinarily difficult to observe and quantify directly. ”
    ”the carbon cycle is second only to physical climate sensitivity itself in contributing uncertainty”
    ”Our results, however, show significant tropical uptake and, combining tropical and extratropical fluxes, suggest that up to 60% of the present-day terrestrial sink is caused by increasing atmospheric CO2. ”
    ”Photosynthesis increases with increasing CO2 following a Michaelis−Menton curve, and this effect grows stronger at higher temperatures”
    Schimel, David, Britton B. Stephens, and Joshua B. Fisher. “Effect of increasing CO2 on the terrestrial carbon cycle.” Proceedings of the National Academy of Sciences 112.2 (2015): 436-441.
    http://reddcommunity.org/sites/default/files/field/publications/increased_CO2_Schimel.pdf
    ”Rising atmospheric [CO2] … fertilizes plants (Liebig, 1843; Arrhenius, 1896; Ainsworth & Long, 2005).”
    Zaehle, Sönke, et al. “Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate Free‐Air CO2 Enrichment studies.” New Phytologist 202.3 (2014): 803-822.
    http://c-h2oecology.env.duke.edu/pdf/np12697-14.pdf
    2012: Plants grown under controlled conditions of 700 ppmv CO2 “increased both root length (35.6%) and root dry weight (39.1%) densities.”
    “Fine root length density in the top two depths increased by 64.5 and 57.2%.”
    “Fine root dry weight density in the top two depths increased by 80.3 and 82.8%.”
    Prior, S. A., et al. “Sour orange fine root distribution after seventeen years of atmospheric CO2 enrichment.” Agricultural and forest meteorology 162 (2012): 85-90.
    http://www.sciencedirect.com/science/article/pii/S016819231200144X
    “…CO2-enriched trees to have consistently sequestered approximately 2.8 times more carbon than the control trees over a period of three full years.”
    Idso, Sherwood B., and Bruce A. Kimball. “Downward regulation of photosynthesis and growth at high CO2 levels No evidence for either phenomenon in three-year study of sour orange trees.” Plant Physiology 96.3 (1991): 990-992.
    http://www.plantphysiol.org/content/96/3/990.short
    “… plant growth and yield have typically increased more than 30% with a doubling of CO2 concentration …may decrease evapotranspiration… if the climate warms, the average growth response to doubled CO2 could be consistently higher than the 30% mentioned above … in nutrient-poor soil, the growth response to elevated CO2 has been large … under [conditions of] water-stress, the CO2 growth stimulation is as large or large than under well-wateredconditions … plant growth and crop yields will probably be significantly higher in the future high-CO2 world.”
    Kimball, B. A., et al. “Effects of increasing atmospheric CO2 on vegetation.” Vegetation 104.1 (1993): 65-75.
    http://link.springer.com/article/10.1007/BF00048145#page-1
    Carrot and Radish plant productivity “significantly increased by a 300 ppm increase in the CO2 content of the air at all temperatures encountered, but with progressively greater effects being registered at higher and higher temperatures. At 25°C, the productivity enhancement factor for radish was about 1.5, while for carrot it was approximately 2.0.” Plants were grown in a 700 ppmv CO2 environment.
    Idso, S. B., and B. A. Kimball. “Growth response of carrot and radish to atmospheric CO2 enrichment.” Environmental and Experimental Botany 29.2 (1989): 135-139.
    http://www.sciencedirect.com/science/article/pii/0098847289900452
    Doubling of atmospheric CO2 concentration “increased agricultural weight yields by [33% – 36%. Doubling of CO2 likely will]reduce transpiration by 34% … water-use efficiency may double.”
    Greater CO2 concentrations will probably boost agricultural production with less water consumption, which will be a boon to Earth’s ever-expanding population.”
    “… the most comprehensive review of CO2 effects on ultimate harvestable yield has been presented by Kimball (1982) who examined more than 70 reports about effects of CO2 enrichment on the economic yields and growth of 24 crops and 14 other species, and extracted more than 430 observations.”
    Elevated CO2 concentrations have had an overwhelmingly positive effect on yield (Kimball, 1982). Of 437 separate enriched samples, only 39 yielded less than their respective controls. Of this group, 20 were flower crops, whose yields were measured by number of flowers rather than by weight.”
    Kimball, B. A., and S. B. Idso. “Increasing atmospheric CO2: effects on crop yield, water use and climate.” Agricultural Water Management 7.1 (1983): 55-72.
    http://www.uu.nl/faculty/science/EN/contact/depts/biology/research/chairs/Palaeoecology/projects/AzollaProject/intranet/literature/AzollaandCO2/Documents/Kimball1983.pdf
    Trees grown in 700 ppmv CO2 concentrations had grown 2.8 times larger than the ambient-treated trees; and they have maintained that productivity differential…”
    Idso, Sherwood B., and Bruce A. Kimball. “Tree growth in carbon dioxide enriched air and its implications for global carbon cycling and maximum levels of atmospheric CO22.” Global Biogeochemical Cycles 7.3 (1993): 537-555.
    http://onlinelibrary.wiley.com/doi/10.1029/93GB01164/abstract
    “… cassava will respond with increased biomass accumulation in response to raising atmospheric CO2 levels …”
    Further experiments with nitrogen fertilizer showed the toxic effects of the form of nitrogen, but that doesn’t change the conclusions of enhanced growth from CO2.
    ”The challenge is to determine how to manage NH4 + fertilization so that the photosynthetic benefit observed in the initial phase may persist throughout the crop cycle.”
    Cruz, Jailson L., et al. “Effect of elevated CO2 concentration and nitrate: ammonium ratios on gas exchange and growth of cassava (Manihot esculenta Crantz).” Plant and Soil 374.1-2 (2014): 33-43.
    http://link.springer.com/article/10.1007/s11104-013-1869-8#page-1
    Elevated CO2 stimulated plant growth by 10.8% [to as much as] 41.7% for a C3 leguminous shrub, Caragana microphylla, and by 33.2% [to as much as] 52.3%for a C3 grass, Stipa grandis, across all temperature and watering treatments … C4 grass, Cleistogenes squarrosa, 20.0% [to as much as] 69.7% stimulation of growth occurred with elevated CO2 under drought conditions.”
    Xu, Zhenzhu, et al. “Effects of elevated CO2, warming and precipitation change on plant growth, photosynthesis and peroxidation in dominant species from North China grassland.” Planta 239.2 (2014): 421-435.
    http://link.springer.com/article/10.1007/s00425-013-1987-9#page-1
    Enhanced growth of spring wheat (Triticum aestivum L.) under 550 ppmv CO2 were found to be “cultivar dependent” with an increase in productivity of 42% to as much as 53% for the cultivar called Yitpi, but less for the H45 variety.
    Thilakarathne, Chamindathee, et al. “Intraspecific variation in leaf growth of wheat (Triticum aestivum L) under Australian Grain Free Air CO2 Enrichment (AGFACE): Is it regulated through carbon and/or nitrogen supply?” Functional Plant Biology (2014).
    http://www.publish.csiro.au/view/journals/dsp_journals_pip_abstract_scholar1.cfm?nid=102&pip=FP14125
    “…current carbon-cycle models underestimate the long-term responsiveness of global terrestrial productivity to CO2 fertilization. This underestimation of CO2 fertilization is caused by an inherent model structural deficiency…”
    “Global carbon cycle models have not explicitly represented this … and underestimate photosynthetic responsiveness to atmospheric CO2.”
    “This increase represents a 16% correction, which is large enough to explain the persistent overestimation of growth rates of historical atmospheric CO2 by Earth system models. Without this correction, the CFE for global GPP is underestimated by 0.05 PgC/y/ppm. This finding implies that the contemporary terrestrial biosphere is more CO2 limited that previously thought
    Ying Sun et al. 2014
    “Impact of mesophyll diffusion on estimated global land CO2 fertilization”
    Ying Sun, Lianhong Gu, Robert E. Dickinson, Richard J Norby, Stephen G Pallardy, Forrest M Hoffman
    doi: 10.1073/pnas.1418075111
    http://www.pnas.org/content/early/2014/10/10/1418075111.short
    http://www.pnas.org/content/early/2014/10/10/1418075111.accessible-long
    A special note, the authors comment about model deficiencies: “In C3 plants, CO2 concentrations drop considerably along mesophyll diffusion pathways from substomatal cavities to chloroplasts where CO2 assimilation occurs. Global carbon cycle models have not explicitly represented this internal drawdown and therefore overestimate CO2 available for carboxylation and underestimate photosynthetic responsiveness to atmospheric CO2.”
    Jun 2013: “Satellite observations reveal a greening of the globe over recent decades. The role in this greening of the “CO2 fertilization” effect—the enhancement of photosynthesis due to rising CO2 levels—is yet to be established. The direct CO2 effect on vegetation should be most clearly expressed in warm, arid environments where water is the dominant limit to vegetation growth. Using gas exchange theory, we predict that the 14% increase in atmospheric CO2 (1982–2010) led to a 5 to 10% increase in green foliage cover in warm, arid environments. Satellite observations, analyzed to remove the effect of variations in precipitation, show that [green vegitation] cover across these environments has increased by 11%. Our results confirm that the anticipated CO2 fertilization effect is occurring alongside ongoing anthropogenic perturbations to the carbon cycle and that the fertilization effect is now a significant land surface process.”
    [Note, others have published results in humid areas, like the Amazon rain forest.] “Satellite observations, analyzed to remove the effect of variations in precipitation, show that [green vegitation] cover across these environments has increased by 11%. Our results confirm that the anticipated CO2 fertilization effect is occurring alongside ongoing anthropogenic perturbations to the carbon cycle, and that the fertilization effect is now a significant land surface process.” “…it has proven difficult to isolate the direct biochemical role of[increases in atmospheric CO2 concentrations] in these trends, from variations in other key resources (such as light, water, nutrients [Field et al., 1992]) and from socioeconomic factors, such as land use change [Houghton, 2003].”
    Donohue, Randall J., et al. “Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments.” Geophysical Research Letters 40.12 (2013): 3031-3035.
    http://xa.yimg.com/kq/groups/18383638/1708677228/name/grl50563.pdf
    PDF link in article: https://groups.yahoo.com/neo/groups/26thIAE/conversations/topics/3529
    http://onlinelibrary.wiley.com/doi/10.1002/grl.50563/abstract
    …So, while global temperatures have not risen since the turn of the millennium, noticeable changes in vegetation are evident. As stated, the results were not limited to Australia, the researchers found that arid areas all over the globe were reaping the carbon dioxide bounty, as shown in the map below.
    “On the face of it, elevated CO2 boosting the foliage in dry country is good news and could assist forestry and agriculture in such areas; however there will be secondary effects that are likely to influence water availability, the carbon cycle, fire regimes and biodiversity, for example,” Dr Donohue said.
    This research does not mean that all the world’s deserts are suddenly springing into bloom, but in the affected areas an 11% increase in plant cover was found…”
    “we predict that the 14% increase in atmospheric CO2 (1982–2010) led to a 5 to 10% increase in green foliage cover in warm, arid environments. Satellite observations, analyzed to remove the effect of variations in precipitation, show that [green vegitation] cover across these environments has increased by 11%.”
    Donohue, Randall J., et al. “Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments.” Geophysical Research Letters 40.12 (2013): 3031-3035.
    [PDF] from yimg.com
    Rather than attribute the greening observation to CO2-influenced fertilization of plant growth, Ranga attributes the greening to “… warmer temperatures [that] have promoted increases in plant growth during summer” “…the global carbon cycle has responded to interannual fluctuations in surface air temperature…” Oh wait, is he saying that the warmer temperature produced more CO2? Like from ocean outgassing? Anyway, he presents the point that accelerated plant growth has sequestered carbon from the atmosphere: “plant growth … net primary production increased 6% (3.4 petagrams of carbon over 18 years)” “Amazon rain forests accounted for 42% of the global increase in net primary production, owing mainly to decreased cloud cover and the resulting increase in solar radiation.” Note, Ranga is taking about increases in plant productivity in the Amazon rain forest, while others have emphasized plant growth in arid areas.
    Myneni, Ranga B., et al. “Increased plant growth in the northern high latitudes from 1981 to 1991.” Nature 386.6626 (1997): 698-702.
    http://ecocast.arc.nasa.gov/pubs/pdfs/1997/Myneni_Nature.pdf
    http://www.ias.sdsmt.edu/STAFF/INDOFLUX/Presentations/14.07.06/session1/myneni-talk.pdf
    These scientists study “…a hyper-arid land- locked region in northwest China” and observe that the
    “…mean growing season vegetation cover has increased from 3.4% in 2000 to 4.5% in 2012.” They think the increased plant productivity is “…associated with increases in regional precipitation.” “We found that the regional fractional vegetation cover fV in the downstream parts of the greater Heihe River basin increased by 25% from 2000 to 2012.”
    So much for dry regions getting drier, a mantra of the “Global Warming” crowd.
    Wang, Y., et al. “Attribution of satellite-observed vegetation trends in a hyper-arid region of the Heihe River basin, Western China.” Hydrology and Earth System Sciences 18.9 (2014): 3499-3509.
    http://www.hydrol-earth-syst-sci.net/18/3499/2014/hess-18-3499-2014.pdf
    “Norway spruce and European beech exhibit significantly faster tree growth (+32 to 77%), stand volume growth (+10 to 30%) and standing stock accumulation (+6 to 7%) than in 1960. … mainly the rise in temperature and extended growing seasons contribute to increased growth acceleration …” The 14% increase in atmospheric CO2 (1982–2010) world-wide was not a controlled variable in this study, and its effect was ignored. This study attributes all of the increased productivity to the rise in temperature, and the resultant increase in the growing season.Pretzsch, Hans, et al. “Forest stand growth dynamics in Central Europe have accelerated since 1870.” Nature communications 5 (2014).
    http://www.nature.com/ncomms/2014/140912/ncomms5967/full/ncomms5967.html
    “… stimulatory effect of atmospheric CO2 enrichment is strongly temperature dependent. … for a 3°C increase in mean surface air temperature … the growth enhancement factor … rises from 1.30to 1.56.” That is a 30% increase, rising up to a 56% increase for a 3°C warmer environment.
    Idso, S. B., et al. “Effects of atmospheric CO2 enrichment on plant growth: the interactive role of air temperature.” Agriculture, ecosystems & environment 20.1 (1987): 1-10.
    http://www.sciencedirect.com/science/article/pii/0167880987900235

  26. Willis replied: “While there is energy stored by plants, it’s basically a zero-sum game due to the energy released when the plants die and decay. Overall the two balance each other out.”
    ///////////////////
    How can it possibly be a zero sum game? Is Willis seriously suggesting that growing a tree requires no net energy?
    During the life cycle of a tree, it has to overcome gravity. Not only does it have to build a vertical structure may be 25 or more metres high, but it also has to continally ‘pump’ water from below groud level up to the top of its canopy. This must take a lot of energy.
    At most, all one receives back when the tree dies, is the mass of material in its structure. One does not get back the energy that was used in the organisation of that structure and its maintenance over the years.
    A considerable amount of energy from sunlight must surely be ‘lost’ in the bioshpere.

    • richard verney February 23, 2015 at 9:59 pm

      Willis replied:

      “While there is energy stored by plants, it’s basically a zero-sum game due to the energy released when the plants die and decay. Overall the two balance each other out.”

      How can it possibly be a zero sum game? Is Willis seriously suggesting that growing a tree requires no net energy?
      During the life cycle of a tree, it has to overcome gravity. Not only does it have to build a vertical structure may be 25 or more metres high, but it also has to continally ‘pump’ water from below groud level up to the top of its canopy. This must take a lot of energy.
      At most, all one receives back when the tree dies, is the mass of material in its structure. One does not get back the energy that was used in the organisation of that structure and its maintenance over the years.
      A considerable amount of energy from sunlight must surely be ‘lost’ in the biosphere.

      “Lost” in the biosphere? One of the first things we learn in science is that energy is neither created nor destroyed. So it’s not “lost” in any sense of the world. It just gets transformed into a different form of energy.
      The energy utilized by the tree goes into a couple of forms. One, as you point out, is mechanical motion—pumping water up from the ground is a good example. However, that energy is not “lost” somewhere. It’s transformed into both potential energy (water up high has more potential energy than water at ground level) and also into heat (since all mechanical processes are less than 100% efficient).
      So while you are right that there is energy expended in “the organisation of that structure and its maintenance over the years”, at the end of the day all of that energy will inevitably turn into heat and be returned to the environment. It won’t get “lost in the biosphere”. By the time that the tree dies and rots back into its elementary constituents, exactly as much energy as was put in during the lifetime of the tree will have come back out again as heat.
      Best regards,
      w.

  27. Willis, I really learned a lot from your article and the thoughtful responses made by so many familiar names here.
    My take on this stems from not eyeballing an increase in trend from 2000-2014 in any of the datasets you plotted, that correspond to the 8% CO2 concentration increase from 2000 to now. Do any of the data you plotted have an upward trend for that period?
    I used co2now.org/images/stories/data/co2-mlo-monthly-noaa-esrl.xls, where for 2000 CO2 was 369.52 and for 2014 it ended at 398.55 (annual data).
    What does that mean to you or anyone else if there isn’t a corresponding trend in these energy fluxes wrt the CO2 trend? Thanks and that is all.

  28. The answer to my question was covered here last year: http://wattsupwiththat.com/2014/01/13/co2-and-ceres/ where you said “There is no trend (0.01 W/m2 per decade) in the surface downwelling radiation.” Thanks.
    Your figure 2 there clearly shows the dropoff in TOA solar after SC23 max in 2003, bottoming out during the minimum in 2008-9, and thereafter increasing again as SC24 reached maximum.
    I realize this post is a different subject, so please forgive for going off thread. At this time it’s pretty obvious to me anyway that surface downwelling radiation had nothing to do with the coincident 8% CO2 increase.

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