Climate Physics

Preprint #3C: Carbon cycle model shows nature controls CO2 level

Final update on March 8, 2021

I took the above photo of Flathead Lake from the Montana State Park in Bigfork, a 15 minute drive from my home. – Ed

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Comments by scientists:

Ed’s paper “quantifies the anthropogenic and natural contributions to changes in atmospheric CO2 concentration without need for knowledge of rate constants for individual mechanisms. This is a breakthrough in understanding which [other scientists] including myself all failed to make.” – Dr. Richard Courtney

“A proper model must address all CO2 in the atmosphere at once, without discrimination. You do that magnificently from first principles.” – Dr. Gordon Fulks

“Ed does not make mathematical mistakes in solving his rate equations.” – Dr. William Happer

“Dear Ed, Congratulations – a wonderful piece of work.” – Dr. Nils-Axel Morner


Ed Berry

  • Edwin X Berry, PhD, Atmospheric Physics, CCM
  • 439 Grand Dr #147
  • Bigfork, Montana 59911, USA
  • Climate Physics, LLC

The author retains sole right to publish the contents of the preprint.

Copyright © 2020 by Edwin X Berry, Ph.D.


  1. This Preprint derives a complete carbon cycle model based upon the Physics model that I described in my Preprints #1 and #2.

    This derivation is fundamental to all climate research. Yet, the USA government and the IPCC spent hundreds of billions of taxpayer dollars on their climate research without ever properly deriving a true carbon cycle model.

    This Preprint proves the IPCC core hypothesis – that human emissions have caused all the CO2 rise above 280 ppm – is wrong. As a result, ALL climate publications that claim or assume the IPCC core hypothesis is true, are wrong. The claimed “97 percent support” for the alarmist climate agenda disappears.

    The political implications of IPCC’s scientific fraud are significant. IPCC told the world its human carbon cycle was valid. The world trusted IPCC and changed the world economy. The world proposed climate treaties based upon IPCC’s fraud.

    Media and government promote the fraud. Schools and universities promote the fraud. Social media “fact checking” promote the fraud. Government funds research that promotes the fraud. Non-profit corporations promote the fraud.

    It is time to promote climate truth.

    1. Quantum Activist, Amit Gotswami, in the everything Answer Book, nails the limits of classical Newtonian physics manifested by the Science of Governance.

      Limits of Growth, Supremacy, Nuclear Winter, Peak Oil hoax, the Mickey Mouse IPCC Climate Science Models, Green New Deal Brown-energy and Pandemic Lockdowns are last remnants of Medieval to Classical Science of Governance.

      The Genesis of Deep Ecologists Paul Ehrlich and Mechanical Engineer Stephen Schneider’s Single-Parameter CO2 Global Warming Model in 1972 was astrophysicists acceptance of the Malinkovitch Theory, the End of the Modern Interglacial and geological record of Mass Extinctions.

      The 1973 Arab Oil Embargo was a Black Swan that threatened the US Petrodollar and International Monetary System.

      The Arab League’s Oil Producing States had organized plans to create the first Arab hard currency before the West unified in the First Iraq Gulf War.
      Cheap-Fossil Energy remained the primary threat to the Limits of Growth and New World Order.

      Sen. Tim Wirth’s Subcommittee was first to hold Government Science Hearings on Global Warming, but only after V.P. Al Gore had reorganized and reset priority of key Federal Agencies.

      Sen. Wirth resigned to lead the $1 Billion Ted Turner UN Foundation, one-third was dedicated to UN IPCC Lobbying over ten years.

      The UN IPPC is a Science Governance Lobby where Stephen Schneider was the UN IPPC Director of Modeling until death in 2010.

      New York City, London and EU Bankers and Financiers members are vested in selling hundreds of Trillions in Bonds to Sovereign Wealth Funds for the Mining and Manufacture of Infrastructure on the obsolete Renewables Tech.

      The Greatest Ponzi Scheme the World has seen since the Dutch Tulip Bulbs.

    2. Dr. Ed,
      The one hypothesis that the entire model rests on: “outflow is proportional to level” (2) on page 9/10 … are you sure it’s true? Is it a fundamental law in physics that applies to all systems where something is flowing in and out of reservoirs?
      I’d be grateful if you gave me a reference that supports this hypothesis.
      Thanks a lot

  2. Thank you for this effort. It is clear, reasonable, and soundly based. I look forward to your suggestions to “show you what we can do to restore truth to climate science”.

  3. The material balance is always fulfilled for the system:

    Inlets + Produced = Outlets + Accumulated

    For the atmosphere there are CO2 inlets mainly natural (land and oceans) and anthropogenic (from fossil fuel combustion, industrial production and land use), so that:

    Inlets = Nature_in + Anthrop_in

    Produced = 0 (CH4 & CO concentration is ~0)

    Outlets = Nature_out + Anthrop_out

    Anthrop_out = 0 ppm.

    Resulting in:

    Nature_in + Anthrop_in = Nature_out+ Accumulated


    Nature_out – Nature_in = Anthrop_in – Accumulated

    The right hand part of the equation is bigger than zero due to that the two terms are well known from e.g. atmospheric analysis (Mauna Loa site) and CO2 emission statistics.

    Then the left hand part of the equation also is bigger than zero, i.e. atmosphere’s CO2 flow is net to the nature.
    Even if the nature’s flow into the atmosphere is very big and not fully known, the flow out from the atmosphere, into the nature is bigger.

    Kind regards
    Anders Rasmusson

    1. Dear Anders,
      Thank you for your comment. I believe my derivation of the Physics model in Section 3.1 is more accurate and complete than what you present in your comment.

    2. This balance argument is well known. It rests on circular reasoning: By assuming that the natural balance of input and output does not change, the net growth of CO2 must be due to the additional input from humans, which upsets the balance.

      The fallacy has been undressed by Professor Salby. He shows from observed changes that the additional human input of CO2 is mostly cancelled by additional removal of CO2 that it causes. The net growth of CO2 therefore follows from changes in the natural balance, changes which this argument ignores.

  4. Hi. I am not a scientist, but find this article very interesting. When discussing with other people in climate related discussion forums it often comes out that the arguments against any article comes based on the journal it has been published in. So why is this not published in better journals then? Or what does it tell if the paper has not been good enough to be accepted in other journals?

    1. Dear Pertti,
      I have not yet submitted Preprint #3 to a journal. I am still improving it and readers, like DMA, still find some of my composition errors.

      However, this Preprint #3 already has been reviewed extensively by top climate scientists. They approve it. No one has found a fundamental scientific error in Preprint #3. All climate alarmists have had the opportunity to challenge Preprint #3 but no opposing scientists has reported any error. So, it is fair to say that this Preprint #3 is as reliable as any peer-reviewed climate paper in any journal.

      The field of climate science has become so politicalized that peer review means little. It amounts to pal review. If the reviewers for a journal are too stupid to understand why the IPCC core theory is wrong, then they will approve papers that support the theory and reject papers that prove the theory is wrong. That is not how science is supposed to work but that is how it works today in climate science.

      In science, the message is important, the messenger is not. Many alarmists attack me, the messenger, but such attacks have no bearing on the truth of what Preprint #3 contains. You may wish to read my recent post because it explains the results of Preprint #3 in simpler language.

      Preprint #3 is not just one more general paper. Preprint #3 PROVES the UN IPCC human carbon cycle is a fraud. That simultaneously proves all IPCC peer-reviewed scientific publications that claim or assume IPCC’s core theory is true, are wrong. That shows how reliable peer-reviewed publication are. They will collapse as soon as someone finds an error in their logic, as Preprint #3 has done.

  5. Dr. Ed
    The last sentence in the abstract says “IPCC’s “real” human carbon cycle shows there is no climate emergency”
    I’m being a bit picky but really your paper only shows there is no human caused emergency. There are lots of reasons not to accept the proclamation of “climate emergency” which is postulated on a human cause which implies a human solution but is based on the rising CO2 being dangerous. however,the point of your work and all the others that support yours is that humans aren’t causing CO2 to rise enough to make any difference so we cannot stop the rise.

  6. Hey Ed, we spoke over email earlier and I am commenting now after reading. I was just wondering why would these organisations lie? What would they gain from spreading miss information? And why do so many of them agree that we’re in the sixth mass extinction.
    I’m really scared for my future and my family. I appreciate your efforts

    Thank you

    1. “And why do so many of them agree that we’re in the sixth mass extinction”.

      Hi Elan, I looked into that. Greta Thunberg says 73,000 extinctions per year (200/day) and would like to answer that. The list provides some historical context. The real number of known extinctions is 1.7 per year (IUCN) and none from climate change, instead the crush of humanity. Due to 150 extra new people on earth each minute, hunting, expanding farmlands, new dams for power, pollution, pesticides etc.
      From all I’ve been able to gather, it seems like the wild numbers boil down to flawed models that made blanket assumptions about fossil records, number of existing species, Amazon (and other) destruction applying worldwide and the like, all the while keeping their work hidden (I haven’t been able to find one of their formulas laid out clearly including their inputs, if anyone can, please let me know), plus the deliberate desire to motivate the public using large lies to short-circuit the reasoning portion of the brain, engaging fear.

      Scientists Fangliang He and Stephen Hubbell wrote a model, and even they, later, realized there were flaws: “No proven direct methods or reliable data exist for verifying extinctions,” they noted in a paper published to the journal Nature in 2011.
      “Hubbell’s point is that if you increase a habitat by, say, five hectares, and your calculations show that you expect there to be five new species in those five hectares, it is wrong to assume that reversing the model, and shrinking your habitat, eliminates five species.” –BBC

      In the attempt to find a scientific paper backing the 200 per day claim, these are the bread crumbs. Earliest “200” is 1995:

      2020, Greta Thunberg, Full Speech | Extinction Rebellion,
      … “about 200 species going extinct every single day” (73,000 per year)
      2009, IUCN,
      … “There are 869 recorded extinctions” … “since the year 1500”
      … That’s 1.7 extinct species per YEAR.
      2004, UN Environment Programme, TUNZA for YOUTH,
      … “It is estimated that between 150 and 200 species become extinct every day”
      … No citation or reference. Page removed in 2009.
      1997, Encyclopedia of World Problems & Human Potential, Decreasing diversity of biological species,
      … “150 to 200 species”
      … “World Bank and Worldwatch Institute, and reported to the Rio+5 conference in 1997, estimated 150 to 200 species of life become extinct every 24 hours”
      1997, J. John Sepkoski Jr., Biodiversity: Past Present and Future,
      … “range to 150 species etinctions per day (Ehrlich and Wilson, 1991)” [extinctions typo in paper],
      … although Sepkoski adds “[total species] figure is misleading, however, because no official list of described species exists”
      1995, Adam Rogers of United Nations, [Book] Taking action: An environmental guide for you and your community,
      … “every 24 hours, an estimated 150 to 200 species of life become extinct” (in the preface)
      … No citation or reference to any scientific paper.
      1991, Paul R. Ehrlich and Edward O. Wilson, Biodiversity Studies: Science and Policy,
      … no mention of extinctions per day as Sepkoski said.
      1989, WV Reid and K Miller, Keeping options alive: the scientific basis for conserving biodiversity,
      … “potential loss of” … “50 to 150 species per day”. Contains “climate change” 27 times.
      1989, Walter V. Reid, How many species will there be?,
      … “potential loss of” … “50 to 150 species per day”. Included in a larger IUCN report containing “climate change” 11 times.
      … “An estimated 25 percent of the world’s species present in the mid-1980s may be extinct by the year 2015”.
      1988, Edward O. Wilson Harvard University, Biodiversity,
      … “By the end of this century [year 2000], our planet could lose anywhere from 20 to 50% of its species”.
      … Ok, so up to all species extinct by 2012, got it.
      1979, Norman Myers, The sinking ark : a new look at the problem of disappearing species,
      … “at least 1 million by the end of the century”, contradicting himself.
      … That’s 137 per day starting in 1980.
      1979, Norman Myers, Conserving our Global Stock,
      … “present century, about one species per year”

      Sometimes they are honest about their goal to be dishonest … “To capture the public imagination, we have to offer up some scary scenarios, make simplified dramatic statements and little mention of any doubts one might have. Each of us has to decide the right balance between being effective, and being honest.” –-Stephen Schneider, Discover Magazine Oct, 1989

      As to why they lie, it took 60 years for it to sink in with me there are people for whom truth means nothing, they think this life is all there is, all they know is the game, a thrill from controlling others for fun and profit and power.

      It appears there are over 130,000 web pages putting the myth of 200 species extinct per day in a blender with climate change as if known fact, even though they can’t name a single species definitively extinct from climate change ever. Believers.

      IUCN is the International Union for Conservation of Nature, the authority on species extinctions.
      “… over 1400 … organizations. Some 16,000 scientists and experts … 1000 full-time staff in more than 50 countries. Its headquarters are in Gland, Switzerland.”

      I want Greta to publicly apologize for buying into that fairy tale and switch her message over to the real, living, IUCN “32,441 species threatened with extinction.”

      Then let groups do gofundme’s for example, each campaign to save a specific single species, one at a time. We would learn a lot in the process, improve management of our burgeoning world population, save many species, and it would rescue Greta’s future reputation looking back, as she is currently being ridiculed a lot, her wacky claim is harming team climate awareness.

      1. “… all they know is the game, a thrill from controlling others for fun and profit and power.”
        Love it!
        For a few years, I’ve been saying this…
        “It’s NOT ‘follow the money,’ it’s really ‘Follow the Money, The Power and The Control Over People.”

        Nailed it.

    2. Why would they lie? What is a lie? To say something you know to be untrue. In my opinion, these organizations believe their theories describe how the world works. Therefore, they are not lying, but they may be wrong.

      Continental mobility, until the evidence was discovered on the floor of the Atlantic Ocean.
      For a long time, the germ theory of duodenal ulcers was rejected.
      For a long time, humans were reported to have 48 chromosomes.

      I think it worthwhile to read Thomas Kuhn’s, The Structure of Scientific Revolutions. I do not regard Kuhn as a philosopher, but rather as an historian of science. Some of his concepts are vague and variable. But he makes a lot of good points on the politics of science, the role of the leaders in a field as gatekeepers who ensure that a prevailing paradigm is defended and promoted. He defines this as “normal” science, which prevails until another paradigm has sufficient support to be accepted as a new paradigm. That switch is a scientific revolution.

      A point often made is that before a paradigm is overturned there must be phenomena that the paradigm cannot explain. (Such as an aberration in the orbit of Mercury.)

      In climate there are plenty of problems with the accepted paradigm. I name one.

      Tiny variations in Bond albedo could account for global warming estimates based on ocean heat content. A series of estimates of energy imbalance at the top of the atmosphere between 2005 and 2012 put the figure at 0.5 Watt per square meter (Wm-2). Source: Loeb et al, 2012. Simple arithmetic gives solar energy of 340 Wm-2 at the top of the atmosphere, of which about 102 Wm-2 is reflected back to space, based on an albedo of 0.30, (30%) and 238 W-m2 enters the troposphere. A 0.5 percent decline in albedo would decrease sunlight reflected back to space by 0.5 Wm-2 and increase the energy imbalance at the top of the atmosphere (TOA) from equilibrium to 0.5 Wm-2. Substantial research by many scientists estimates this is equal to the energy imbalance at TOA.

      The dominant controls for albedo are clouds (high albedo). As the amount of cloud increases, albedo rises. Can albedo be measured to within 0.5 per cent of 0.30 over the period 1960-2020, 0.30 plus or minus 0.0015? In my opinion, based on the literature, the answer is no.

      This does not prove anything, but it does show that the following statement is unsupported, “The observed climate change cannot be explained by natural variation.” I claim that the amount of climate change observed since 1960 can be explained by tiny variations in Bond albedo.

      This justifies testing other paradigms based on variations in cloud cover.

      Hansen, J. et al. 2005: Earth’s energy imbalance: Confirmation and implications. Science, 308, 1431-1435
      Hansen, James, et al. “Earth’s energy imbalance and implications.”Atmospheric Chemistry and Physics 11.24 (2011)
      Loeb, Norman G., et al. “Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty.” Nature Geoscience 5.2 (2012): 110-113.
      Stephens, Graeme L., et al. “An update on Earth’s energy balance in light of the latest global observations.” Nature Geoscience 5.10 (2012): 691-696.

  7. I found pre-print 1 the best of the three and pre print 3 the worst.

    It is far harder to ready and seems messy and erratic.

    It also has a bunch of minor mistakes in it which make it a bit of a chore to read. Also can you post a PDF link, that reader is annoying and makes cut and pasting from it remove spaces.

    For example,

    “.IPCCmerely inserteditscoretheoryintoits human carbon cyclewhichcircular reasoning”

    This should say ” which is circular reasoning”.

    Also whenever you mention IPCC it does not have the word the in front of it which makes reading it feels wrong. It should be proceeded with the word the in almost every instance.

    There is a few other minor errors to do with missing words etc.

    The first section doesnt feel like you have enough evidence. You just quote a paper but don’t elaborate enough.

    Honestly I wish this was a bit more like pre print 1.

    I still think the physics model is great and your points are valid it just doesn’t seem to be explained as simply and clearly as the pre print 1.

  8. Have you performed a sanity check on your model? Your model suggests that more CO2 has made its way into the deep oceans than into the atmosphere, land, and ocean surface combined.

    This suggests that your coefficients are incorrect, or that neglecting the fact that the coefficients are temperature and concentration dependent is a fatal flaw for your toy model.

    You also have no explanation for where the extra 100ppm in the atmosphere comes from. Have you considered the fact that your model is wrong?

    One last comment. Do you know that there is a closed form analytical solution for your model? I’ll provide it to you if you like.

    1. Dear Immortal600,
      Have you performed a sanity check on your comment?

      My calculation of IPCC’s true human carbon cycle uses the same time constants that IPCC uses in its natural carbon cycle. So, there is no basis to claim I used the wrong coefficients.

      If you claim my time constants are wrong, then you also claim IPCC’s time constants are wrong. And if IPCC’s time constants are wrong then you help me prove IPCC’s core theory is wrong.

      IPCC used vastly different time constants for its human carbon cycle than it used for its natural carbon cycle. That proves IPCC’s core theory is wrong.

      I don’t need to explain where the 100 ppm supplied by nature comes from. I address that issue in section 4.6. Did you read that?

      Yes, I would like to see a “closed form solution” of my carbon cycle model.

      1. Of course I have done a check on my comment. I solved your model.

        Your model is flawed because you do not get the time constants correct. The IPCC’s time constants are not wrong. If you bothered to read the report and understand it then you would have seen that the time scale for sequestration into the deep oceans is at least on the order of 10,000 years. They also discuss the other time scales. You can’t calculate time scales for non-equilibrium processes based on the equilibrium exchanges as you have naively done. Do you understand that across a surface in a metal wire with zero voltage drop across it, there are countless electrons flying back and forth across that surface? However, the current flowing through that surface is zero. Given that information do you think you can calculate the resistance? The fact is that you can’t. You have confused the content of the CO2 in each reservoir with the generalized chemical potential of that content. At equilibrium the chemical potential in each of the reservoirs is equal. Away from equilibrium, the net flux between each reservoir is related to the difference in the chemical potential. The mobility coefficient describing that flux then can be used to set a time scale for non-equilibrium processes. You cannot determine those mobility coefficients by looking at what is happening at equilibrium, just like you cannot determine the resistance of a wire by looking at the electrons flying back and forth when there is no potential drop.

        So, it is not the IPCC that is wrong, but it is you who has made a fundamental error in interpreting the information that was given by the IPCC.

        You do need to explain where the extra CO2 comes from if you want to be taken seriously. The ocean and land sinks have been measured. Look up Global Carbon Budget 2019. Given that both the oceans and the land have taken more CO2 out from the atmosphere than they have put into it, that means that they cannot be the source of the atmospheric increase.

        I generated the following coefficients for your model based on ~10, ~100, and ~10000 year time scales for the land to atmosphere, ocean surface to atmosphere, and ocean surface to deep ocean exchanges respectively. They yield far more reasonable results than your faulty procedure.


        The closed form solution looks as follows:

        L1 = L1eq + C11 Exp[-a1 t] + C21 Exp[-a2 t] + C31 Exp[-a3 t] + C01 Exp[a0 t]
        L2 = L2eq + C12 Exp[-a1 t] + C22 Exp[-a2 t] + C32 Exp[-a3 t] + C02 Exp[a0 t]
        L3 = …
        L4 = …

        Where a1, a2, and a3 are the eigenvalues of a matrix that depends on your coefficients, and the C’s are the associated eigenvectors. The C0 terms are the particular solution for an exponential fit to the human source term. I can provide more detail if necessary, but if you understand math well enough then this should be enough for you to generate it yourself.

  9. Dear Immortal600,
    Thank you for your comment. I appreciate critiques.

    First, let’s dispense with your “closed form solution.” I purposely wrote my equations to readily be imported into matrix algebra. From there, we can to a relaxation calculation. It turns out the this relaxation calculation produces identical results to the numerical calculations I do in my Excel spreadsheet.

    Second, do you agree that IPCC’s numbers for its natural carbon cycle (as shown in my Figure 3) represent an equilibrium situation?

    I think IPCC makes it quite clear that its natural carbon cycle is at equilibrium and represents IPCC’s claimed conditions in the absence of human CO2.

    If that is true, then any valid e-times must keep IPCC’s levels constant in its 4 reservoirs. However, using your e-times, IPCC’s levels quickly fall out of equilibrium. In fact, your e-times move most of the carbon into the atmosphere. Not very realistic. So, you have a whole lot of explaining to do to justify your e-times.

    I put the tabular summary of the results of the calculation using your e-times at the top of these comments. Looks to me like your e-times totally disagree with IPCC’s numbers. Please explain.

    1. First) You are free to not provide readers with an analytical solution to your model. Doing so would make it more accessible to anyone that would want to play around with it. You could probably construct an Excel spreadsheet that anyone can download and play with to see how the coefficients affect the solution.

      Second) I’m not an expert on the topic. You are claiming that it is an equilibrium situation with respect to your model and I am happy to go with that terminology for now.

      You have ASSUMED that the forward flux from reservoir A to reservoir B is INDEPENDENT of the chemical potential of the species in reservoir B. That is incorrect. That flux can be approximated with a Taylor series expansion that includes a constant term associated with zero chemical potential difference which can be taken from the “equilibrium” IPCCs numbers, and a linear term associated with the difference in chemical potential. Those terms CANNOT be determined from the “equilibrium” numbers that are given, and it is those terms that determine the non-equilibrium rates.

      3) “However, using your e-times, IPCC’s levels quickly fall out of equilibrium.”

      Indeed, my workbook inverted one of your definitions and I forgot to put it back into the form you use. The corrected numbers for the T’s are:

      T12 = 42.4448
      T21 = 10
      T23 = 100
      T32 = 152.801
      T34 = 15280.1
      T43 = 629881

      My apologies for the error, and for causing you to waste time on that.

      In any case, you should see that those corrected numbers do not lead to as much CO2 in the deep ocean. If you change the atmosphere to land time scale to ~50 years, then it starts to look even better:

      T12 = 212.224
      T21 = 50
      T23 = 100
      T32 = 152.801
      T34 = 15280.1
      T43 = 629881

    2. Again, my apologies for that prior inversion error. So, here is what happens if I make the atmosphere to land and atmosphere to ocean surface times scales both at ~100.


      For the simple exponential fit to the human emissions that I used, I get the following ppm changes in the land, atmosphere, ocean surface, and deep ocean:

      Land: 1179 to ~1220 -> ~21%
      Atmosphere: 278 to ~400 -> ~62%
      Surface: 425 to ~460 -> ~18% (roundoff errors evident)
      Deep: 17500 to ~17500 -> ~0%

      Total input was ~ 196

      1. Dear Immortal600,
        Your e-times have my interest. Are the e-times above (5:57 AM) your latest, so I can ignore your previous ones?

        Please explain how you calculated these e-times. Provide references if applicable.
        I want to follow your derivation.


        1. Yes, those are the latest. I think you could play with the numbers more, but I don’t see the point. These do a reasonable job for such a simple model.

          Also, my apologies for not looking into your Excel workbook more thoroughly. I now see that folks can play with these numbers and see what happens. In any case, I wanted to generate the solution for myself and we get basically the same story. It’s up to you if you think it is worth your while to generate the analytical solution. It is a 3×3 matrix (since L4 is not independent) and so the algebraic formulas are a bit messy.

          My times are very rough estimates to mimic the time scales stated on page 472 Ch. 6 of the IPCC report.

          Take these “time scales” for land to atmosphere to be S12, atmosphere to ocean surface to be S23, and ocean surface to ocean depths to be S34. I take the equilibrium concentration in the atmosphere, L2eq, to set the baseline for chemical potential. Then the T’s are calculated as follows:

          T12 = L1eq/L2eq * S12
          T21 = L2eq/L2eq * S12
          T23 = L2eq/L2eq * S23
          T32 = L3eq/L2eq * S23
          T34 = L3eq/L2eq * S34
          T43 = L4eq/L2eq * S34

          That first prefactor of L?eq/L2eq ensures that the chemical potentials at equilibrium are each the same and that the equilibrium solution does not change for no human forcing. Then the S12, S23, and S34 scales can be adjusted accordingly (100, 100, and 10000 above).

        2. Dear Immortal600,

          Thank you. I will look at that IPCC page and get back to you.

          By the way, I understand that for equilibrium, we need (where F = flows):

          F12 = F21
          F23 = F32
          F34 = F43

          Both your values for Te and my values for Te satisfy those constraints. If we assume we agree on IPCC’s reservoir levels, then our key disagreement is in the equilibrium flows between the reservoirs. My flows equal the IPCC flows in Figure 3. Your flows do not equal the IPCC flows.

          Please explain why your flows do not equal the IPCC flows.

  10. I have tried to explain this already. The forward flow from reservoir a to reservoir b can be expanded into a Taylor series as:

    Fab = Fab0 + kab (mu_a – mu_b)

    the forward flow from b to a is then

    Fba = Fab0 + kba (mu_b – mu_a)

    Fab0 is the equilibrium forward flux (and must be the same for Fab and Fba) and does not enter into a proper thermodynamic interpretation of your model. It is Fab0 that is essentially given in the IPCC report, but what is needed for the model are the kab and kba terms.

    The chemical potentials can be linearized about the equilibrium state. So, your formulation has all that is needed for such a linearized model, but your interpretation of Fab0 is incorrect.

    The point is that the forward fluxes from the equilibrium state shown in the IPCC report DO NOT set the time scales for non-equilibrium processes. The k’s do this, and those are discussed qualitatively in Ch. 6 of the IPCC report.

    1. Dear Immortal600,

      Thank you for your explanation of how you calculated your e-times.
      Here is my interpretation of IPCC’s Chapter 6, pages 467-472.

      IPCC explains its Figure 6.1 (my Figure 3) as follows:

      (1) “Numbers represent reservoir mass, also called ‘carbon stocks’ in PgC (1 PgC = 1015 gC) and annual carbon exchange fluxes (in PgC yr–1).”

      (2) “Black numbers and arrows indicate reservoir mass and exchange fluxes estimated for the time prior to the Industrial Era, about 1750.”

      Your numbers come from:
      (3) “Box 6.1, Table 1. The main natural processes that remove CO2 consecutive to a large emission pulse to the atmosphere, their atmospheric CO2 adjustment time scales, and main (bio)chemical reactions involved.”

      Items (1) and (2) are very clear. The numbers in IPCC’s Figure 6.1 represent IPCC’s best estimates of the reservoir levels and the annual flows between the levels at equilibrium. IPCC’s core theory says its natural carbon cycle data is valid after 1750. This means its flows keep its levels constant, which they do after I make very small adjustments to IPCC’s flows.

      Item (3) does not override items (1) and (2). Item (3) is about how a fictitious large pulse of CO2 would flow out of the atmosphere. It is based upon the assumption that IPCC’s core theory is true. This assumption invalidates the papers that made these calculations.

      Not even IPCC claims these (3) numbers apply to its natural carbon cycle.
      IPCC applies these numbers only to its human carbon cycle. This, of course, contradicts the Equivalence Principle.

      I conclude your e-times apply only to IPCC’s model for a theoretical carbon pulse that first assumed IPCC’s core theory is true.

      Nevertheless, I thank you very much for your very useful comments.

  11. “Items (1) and (2) are very clear. The numbers in IPCC’s Figure 6.1 represent IPCC’s best estimates of the reservoir levels and the annual flows between the levels at equilibrium. IPCC’s core theory says its natural carbon cycle data is valid after 1750. This means its flows keep its levels constant, which they do after I make very small adjustments to IPCC’s flows.”

    I have no problem with your adjustments. Again, these flows are the Fab0’s that I explained in my prior comment.

    You will note that the Fab0’s do not enter into your model because your model always has Fab – Fba.

    Fab – Fba = [Fab0 + kab (mu_a – mu_b)] – [Fab0 + kba (mu_b – mu_a)] = (kab + kba) (mu_a – mu_b)

    Hence, it is the (kab + kba) that sets the time scales for non-equilibrium processes in your model. The equilibrium flows, Fab0, cancel one another out.

    “Item (3) does not override items (1) and (2). Item (3) is about how a fictitious large pulse of CO2 would flow out of the atmosphere.”

    No, it does not override (1) and (2), it supplements them. Item (3) explains what the time scales are for non-equilibrium processes, which is exactly what is needed in your model.

    “So, in summary, I stand by my e-times derived from IPCC’s natural carbon cycle.”

    That is your error. Your “e-times” come from Fab0, where they need to come from (kab+kba). Your thermodynamics is wrong.

    “I conclude your e-times apply only to IPCC’s model for a theoretical carbon pulse”

    They apply to ALL non-equilibrium situations for your model.

    1. I see there may be some confusion on my response to:

      “Not even IPCC claims these (3) numbers apply to its natural carbon cycle.”

      To clarify, the numbers in (3) apply to all situations when the system is out of equilibrium, and those numbers do not play a role when the system is in equilibrium. I read ‘natural carbon cycle” in two different ways. I think a less confusing terminology is equilibrium and non-equilibrium, as the natural effects are occurring is both scenarios.

  12. Ed,

    To summarize, the point of contention is on the kinetic relationship between the flows, F12 …, and the L’s (which I will refer to as concentrations).

    You ASSUME that the form is as follows:

    Fab = La/Tab

    I make NO assumptions, but I expand about the equilibrium state. I also invoke the thermodynamic restriction that the flow must depend on the difference in the chemical potential. I’m not sure if you are aware of this or not. This means that

    Fab = Fab0 + kab (mu_a – mu_b) + 1/2 m_ab (mu_a – mu_b)^2 + …

    I then linearize by taking the first two terms. Furthermore, I can expand the chemical potentials about the equilibrium state as well in terms of the concentration in reservoir a, as follows:

    mu_a = mu_a0 + ca La + 1/2 da La^2

    Again, I linearize and keep only the first two terms. Note that at equilibrium mu_a = mu_b, and so we have after linearization:

    mu_a0 + ca Laeq = mu_b0 + cb Lbeq

    Plugging back into the linearized expansion for the flow we have:

    Fab = Fab0 + kab (mu_a – mu_b) = Fab0 + kab (mu_a0 + ca La – mu_b0 – cb Lb)
    = Fab0 + kab [ ca (La-Laeq) – cb (Lb-Lbeq) ]

    This is the most general form linearized about the equilibrium state.

    Your form does not even respect the thermodynamic restriction that the flow from one reservoir to the other must depend on the chemical potential difference between the two reservoirs.

    1. Dear Immortal600,

      See Section 4.3. Preprint #3 proves (3) is wrong before you even get to use (3).

      (3) is not only wrong, it does not apply to the natural carbon cycle. IPCC does not apply (3) to its natural carbon cycle. IPCC applies (3) only to its human carbon cycle.

      IPCC (1, 2) says its flows are valid to 20 percent. Yet you use IPCC’s (3) to multiply IPCC’s (1, 2) flows by 0.0546 and 0.0006, way outside IPCC’s error bounds.

      If IPCC (1, 2) were that far off, don’t you think IPCC would have put different numbers (1, 2)? Of course, IPCC would have changed its numbers in its Figure 6.1.

      IPCC’s (1,2) is an equilibrium scenario. Even the addition of human carbon to IPCC’s (1,2) is not enough carbon to make any significant difference to this equilibrium. A Taylor expansion will change its primary number by those factors, even when the system is close to equilibrium.

      You have not shown the carbon cycle system is far enough from equilibrium to justify your numbers. Given that IPCC’s natural carbon cycle (2) is at equilibrium, your Taylor series is negligible.

      Physics does not justify adding additional terms to equation (2). Physics and chemistry show outflow is proportional to level to the first power. If you add additional terms then the perfect gas law fails, standard pharmaceutical models fail, Dalton’s law of partial pressure fails, etc.

      Occam’s Razor favors the simplest solution to a problem. You present a more complicated solution.

      Preprint #3 proves IPCC’s core theory is wrong by showing its human carbon cycle contradicts its natural carbon cycle.

      Thank you again for your comments.

  13. Yes, I do get that (3) is not data.

    Do you understand what a Taylor series expansion about equilibrium is?

    Do you understand that the equilibrium flows do not tell you anything about the non-equilibrium rates?

    “Preprint #3 proves (3) is wrong”

    It does no such thing. Preprint #3 makes an invalid interpretation of the information provided by the IPCC. This has now been explained to you with equations and you still do not understand it.

    Here it is again.

    Fab = Fab0 + kab (mu_a – mu_b)

    Fab0 comes from the IPCC’s (1) and (2).

    kab comes from the IPCC’s (3).

    Both apply to ALL scenarios including equilibrium and non-equilibrium.

    All qualified physicists would understand what chemical potential is, and would understand how to carry out a Taylor series expansion about equilibrium. Qualified physicists would reject the numbers that you have gotten for the deep oceans and question why. I have explained to you why.

    Your ASSUMED equation (2) is incorrect as I have explained.

    You have created a toy model and interpreted its terms in a physically incorrect manner. Furthermore, you are ignoring the data analyzed and published in the Global Carbon Budget 2019 that shows that both the land and oceans have taken more CO2 out from the atmosphere than they have put in over the last 100 years.
    Those facts alone show that the land and oceans are not the source for the atmospheric increase. Those facts alone show that humans are responsible for the increases in each of these reservoirs. Even your faulty model shows that each of the reservoirs INCREASES in CO2 content due to human emissions.

    The kinetic equation in question is an approximation for a highly complex system. The oceans emit CO2 in the tropics and absorb CO2 near the poles. The kinetic equations in this toy model are lumping all of those processes into one equation. The most general analysis of that lumped system is what I have described for you by using a Taylor series expansion about equilibrium. That is how dynamical systems are analyzed.

  14. Dear Immortal600,

    Thank you for your final comment.

    Figure 8 explains how IPCC’s slow processes affect the outflow of CO2. Figure 8 assumes all human CO2 emissions stop in 2020. Once stopped, the scenario is like a pulse of human CO2 of 33 ppm was added to the atmosphere.

    The curve after 2020 shows how fast human CO2 in the atmosphere flows to the other reservoirs according to IPCC’s fast processes as shown in Figure 3. But the human-caused increase will never return to zero in the Physics model. That is because the fast processes do not remove carbon from the carbon cycle. They only redistribute carbon among the reservoirs.

    Only IPCC’s slow processes remove carbon from the carbon cycle and the Physics carbon cycle model does not include IPCC’s slow processes. The Physics carbon cycle model leaves more carbon in the carbon cycle than the IPCC model does.

    Figure 8 says if we allow the fast processes to distribute the human carbon added as of 2020 without calculating how IPCC’s slow processes would remove the carbon, the long-term effect is to add about 5 ppm to atmospheric CO2.

    I think you incorrectly revised IPCC’s fast flows to become very small flows according to IPCC’s slow processes. IPCC’s fast and slow processes are independent.

  15. I want everyone on this site know that I AM the REAL ‘Immortal600’ who posts elsewhere using that moniker. I am mostly on cfact but do post elsewhere. I don’t want to be associated with that clown above who stole my handle so he could post here. He posts as ‘Straight Flush’ and ‘evenminded’ elsewhere.

    Don’t be confused! I agree with Dr. Berry’s model and tout it everywhere I go. It is logical and clear. I admit I do not understand the deep math (calculus) but I know others do. If there were errors in the formulas someone would have pointed that out.

    The Taylor Series explanations used by the imposter ‘Immortal600’ are incorrect usage and give results, as Dr. Berry has pointed out, out of the range of IPCC figures. I am told this by other math majors whose expertise far outshines my own.

  16. To be fair on mathematics, Taylor polynomials are an excellent tool if used correctly to tweak or finite your math or verify your work. However, as an infinite series it can be used to misinterpret the work. Like everything in science, it’s not the math tool that’s wrong it’s the tool using that math that can be wrong. Using any infinite series with a slightly wrong calculation or deliberate change can create an exponentially incorrect value.

    Just as an example if you input a single temperature data for a 12 month year, use the coolest temp and average that out for the year you can make older years look cooler than newer warmer years. You can manipulate values to coerce a desired outcome and by using any infinite series you can hide those values more easily. The best way to hide a lie is to cover it with more data.

    I’d love to crack open these “climate models” and see how older temperature data has been treated in them. I did it once and the code -37268 showed up about 90% of the time on older temperature data. That code was for a null set. I did inquire about the data I did not receive a response other than a generalized nothing to see here move along.

    I am not an expert on climate models and would have been willing to hear an explanation, they were not want to give one. You see for an infinite series like climate models you can cheat by using that code and bury it in over 3,624,768 entries and some neurotic individual like myself would find the pattern and wonder why they were there.

  17. I am just a computer scientist and a mechanical engineer so I am not an expert in this field but I find your observations and analysis very interesting. This worldwide economy slowdown because of covid has provided us with a significant worldwide reduction in CO2 emission but still the level of CO2 in the atmosphere continues to rise at the same speed as before. That seems to support your analysis.

  18. I am not a scientist either. Just an interested observer.
    Dr Ed, have you seen this?
    David Evans Andrews. Correcting an Error in Some Interpretations of Atmospheric 14C Data. Earth Sciences. Vol. 9, No. 4, 2020, pp. 126-129.
    doi: 10.11648/

    1. Dear John,

      Yes, I am aware of it. Thank you for adding the reference for the readers.

      Even if Andrews is correct, his paper has no bearing on this Preprint #3 because Preprint #3 does not use any argument that depends upon 14C data. Also, his paper has no bearing on the conclusions of my 2019 paper as Andrews claims because I can remove, or even revise, the 14C discussion without having to change the paper’s conclusions.

      1. Dr Ed,
        Your response is much appreciated.

        I am not an American but I pray for all Americans and Presidents Donald’s Trumps success for a second term.
        I think he has identified the evil intent of the NWO

  19. Dear Dr. Berry,

    Now that your book is out, I wonder if you have had time to address this post from a while ago (reproduced here with minor edits):

    The following simple model explains the apparent different behavior of natural and anthropogenic carbon. It is not meant to be an actual model of the oceanic carbon cycle, but it will demonstrate the relevant mathematics. Also this model will show, at least in principle, how the lifetime of CO2 concentration perturbations can differ from the lifetime of isotopic tracers like carbon-14. For both of these questions, the key is nonlinearity.

    Consider a system containing a mass m of some substance (maybe CO2). There is a constant inflow of 1 kg/s. The outflow is O=-C m^2 (we will just write C=1, but really C=1 kg^-1 s^-1). Then

    dm/dt = 1-m^2 (1)

    Clearly an equilibrium is reached when 1-m^2=0. This occurs at the value m=meq=1 kg. Also, the outflow is equal to 1 kg/s. Thus at equilibrium the e-time for a given molecule to leave is (1 kg)/(1 kg/s)=1 s.

    What happens when a small amount of mass x is added? We could solve the full nonlinear equation (1), but nonlinear equations are difficult and unintuitive. Instead we write m=meq+x and examine the outflow term, m^2. The outflow becomes O=-(meq+x)^2=-meq^2-2 meq x-x^2. We can ignore the term in x^2 because x is small — of course this is just a Taylor expansion. Then O~-meq^2-2 meq x. The differential equation becomes

    d(meq+x)/dt = 1-meq^2-2 meq x
    d(meq+x)/dt = 0-2 meq x
    dx/dt = -2 meq x
    dx/dt = -2 x

    Notice that the equilibrium inflows and outflows canceled out, leaving just the added mass x. Now, this equation looks like a decay of x with e-time 0.5 s. Here is the key point: we already determined that the e-time for a given molecule to leave is 1 s. However, if a small perturbation from equilibrium is added, that perturbation decays with a different e-time of 0.5 s. There are two different sorts of e-times at play here. This only occurs in a nonlinear system. In a linear system, the two e-times are the same.

    This already gives intuition for why natural and anthropogenic carbon may appear to be treated differently in the Bern model. Natural carbon dominates the total flows of carbon, and the total flows set the e-time for individual molecules to move between reservoirs. These are the e-times you have calculated from Figure 3 in your preprint 3. The equilibrium is perturbed only when new carbon is added, which is done by humans. Such a perturbation decays back to equilibrium with a different e-time.

    The point of this was to show that, for nonlinear flows, there are two types of e-times. The story becomes slightly more complicated when moving from this simple one-reservoir model to the full, 4-reservoir model. Then there are also the decay times in the Green’s function, which are different still.

    But sticking with the simple model, there is one more interesting conclusion. If a few molecules of isotopic tracer like carbon-14 are added, the total mass will decay back to equilibrium with an e-time of 0.5 s. But if we keep track of a given tracer molecule, it will leave with an e-time of 1 s. That is why the lifetime of an isotopic perturbation can differ from the lifetime of the mass perturbation. I have thought of a nice way to formalize this, but the post is already quite long.

    This is far from a realistic model of the carbon cycle — I don’t pretend to know exactly what the flow rates are, or to have modeled the nonlinearities well. But I believe this shows the important effects which are added by any nonlinearity, and cannot be captured by a fully linear model like the one in your Preprint 3.

    1. Dear Tim,

      Thank you very much for your comment. I apologize for my delay to reply.

      I agree with your equations that show a Taylor expansion of your assumed nonlinear equation for outflow. So, we have no issue with your math. That narrows our discussion to whether the components of the carbon cycle system are best described by linear or nonlinear equations.

      My equation (2) assumes a linear system. By contrast, you have assumed a nonlinear system. You agree that your specific nonlinear equation is not realistic. I understand that you use your example to illustrate how a nonlinear system would behave.

      Physics is also decided by Occam’s Razor, or the simplest solution that fits the data wins.

      Arguably, the best data we have on the carbon cycle are in the IPCC natural carbon cycle. These data, remarkably, perfectly fit the linear model. Until data prove it is necessary to use a nonlinear model, Occam’s Razor requires us to use the linear model.

      You wrote, “And due to the buffer chemistry of CO2 in seawater, the outflow to the atmosphere is nonlinear.”

      However, the IPCC carbon cycle data do not reveal this nonlinearity. Further, chemical reaction models use linear equations. Pharmacology models use linear equations that assume the reaction is proportional to level.

      You wrote, “The equilibrium is perturbed only when new carbon is added, which is done by humans. Such a perturbation decays back to equilibrium with a different e-time.”

      Well, it decays back with a different e-time ONLY if the system is nonlinear. IPCC data do not support a nonlinear assumption.

      Humans have added only about one percent to the carbon in the natural carbon cycle. Stomata data and chemical data show that nature changes the amount of carbon in the carbon cycle much more than human carbon has added to the carbon in the carbon cycle.

      Even if the system were slightly nonlinear, we would not expect an additional one percent to provide a measurable signal of nonlinearity.

      You wrote, “This already gives intuition for why natural and anthropogenic carbon may appear to be treated differently in the Bern model.”

      No, the IPCC treats human carbon differently than it treats natural carbon because it assumes – contrary to its own data – that human carbon has caused all the increase in atmospheric CO2 above 280 ppm. That incorrect assumption is IPCC’s major error.

      You wrote, “That is why the lifetime of an isotopic perturbation can differ from the lifetime of the mass perturbation.”

      The 14C in the atmosphere does not contribute enough additional carbon to the carbon cycle to change the e-time under any reasonable assumption of nonlinearity. The much larger error in using 14C to track 12C flows is in the slower chemical reaction time of 14C compared to 12C.

      The following is a digression from my main argument:

      Consider a real nonlinear system of a tall beaker with a faucet at the bottom. Fill the beaker with water and open the faucet. Measure how fast the level decreases. This system is nonlinear because it changes potential energy into the kinetic energy to cause water to flow out of the spout. So,

      Outflow = SQR(2g * Level)

      Its square-root is the reverse of your square. The e-time changes with level. But we understand why the e-time changes because we have the equation to express the nonlinearity. If the level remained within a few percent of its original level, we would need accurate measurements to detect its nonlinearity. We could approximate it reasonably well with a linear equation.

      [end digression]

      In conclusion, to support your argument that the flows in the natural carbon cycle are nonlinear, you must develop a nonlinear carbon cycle model that replicates the IPCC carbon cycle data better than the linear carbon cycle of my equation (2). That will be difficult because the IPCC says its data are accurate to only about 20 percent and my equation (2) replicates IPCC’s mean data to a fraction of one percent.

      Thank you again for your comment.


  20. I agree with your conclusions, Berry. I am no expert and certainly no authority, but below is a small article I put together explaining why I think the CO2 increase could be natural. It’s only an armchair skeptic’s view of the situation and I am sure I have left out important points, but I feel some of the points I bring up are worth consideration.

  21. Sorry, Dr. Ed and everyone else… I lost interest when the First Immortal600 made this statement..

    “Do you understand that across a surface in a metal wire with zero voltage drop across it, there are countless electrons flying back and forth across that surface? However, the current flowing through that surface is zero. Given that information do you think you can calculate the resistance? The fact is that you can’t. ”

    As a person with a degree in Electrical Engineering, I considered that, while there might be “countless electrons flying back and forth across that surface,” the point is irrelevant to their assertion. If there is no current flowing down the length of the wire, yes, it IS impossible to measure the wire’s resistance directly, as the Resistance (R) == The voltage difference from one end of the wire to the other end (E), divided by the RESULTING Current Flow (I). [R=E/I].

    So, with not current flowing through a path external to the wire, its resistance is indeterminate, and the electrons scurrying across its surface are irrelevant to any and all ‘issues at hand.’

    … barely even a ‘red herring’… an irrelevant and unnecessary sentence added to an insulting paragraph.

    But it hit my “EE” button. 🙂

    1. Alan Falk,

      The First Immortal600 turns up in many places and uses many false names. His/her/them/it is easily identified by the distinctive ‘style’ and always displays the purpose of casting doubt on valid information which does not support climate alarmism.

      I have had several interactions with him/her/them/it. All were unpleasant and as example I cite one on WUWT where he/she/they/it used the name “Rich Davis” while attempting to disrupt discussion of evidence concerning anthropogenic and natural contributions to the recent rise in atmospheric CO2 concentration. In that discussion he/she/they/it attempted the same erroneous .mass balance closure’ argument which he/she/they/it puts to Ed Berry above.

      The cited example I cite is in the thread at

      That example begins with “Rich Davis” replying to a post of John Shotsky at November 29, 2020 12:03 pm, and ends with these final comments from him/her/them/it and me

      “Rich Davis
      December 1, 2020 4:45 pm

      This is all very basic engineering that I learned more than 40 years ago. And for you to call me rude is quite rich, given your continuous stream of abuse and condescension.

      Do you have any education whatsoever? It is not apparent.

      Richard S Courtney
      Reply to
      Rich Davis
      December 1, 2020 10:20 pm


      You have ignored everything I have told you of our published work.
      I have refuted with evidence each of your attempts to make a point.

      You have accosted me with words and phrases such as “bloviating” and “redundant verbiage”.
      I have patiently explained your errors.

      You said to me, “Kindly address the two points at the top of this comment if you wish to continue the discussion.”
      I replied to you by addressing those points yet again and adding,
      “As for you being willing “to continue the discussion” with me,
      I enjoy sensible debate with those who disagree with me because I learn nothing from debating with a mirror, but so far your only contribution to this discussion has been to demonstrate you have meagre understanding of the subject. So, I suggest that if you want to learn then read what I have written for you and try to be polite instead of trying to hide your ignorance and bias behind rudeness. I am willing to try to answer any sensible questions and to debate any reasonable points.”

      I leave it to others to decide for themselves which of us is “condescending” and which of us knows what we are talking about.



      1. Richard, you make an excellent comment on that fraud who stole my name. My only wish is that you referred to him as the fraudulent ‘Immortal600’ as I am the FIRST and ORIGINAL ‘Immortal600’.

        I want to take this opportunity to thank you for all that you do in combating this AGW madness. May God bless you and your family always!

  22. I posted this update on January 15, 2021.

    The math part is the same. But I improved the rest of the paper based on how I organized my book Climate Miracle.

    Now is your chance to add your review so you can be on my Acknowledgements list.

    I plan to submit this for publication on January 18.

  23. A typo (missing “cause”):
    “The Equivalence Principle requires human and natural CO2 to behave the same. If natural were to ____ CO2 stick in the atmosphere,”

  24. In section 2.5, in addition to Munshi, Chaamjamal (I presume he is not Jamal Munshi?) also published detrended statistical analysis revealing NO correlation between:
    — rate of atmospheric CO2 increase and rate of fossil fuel CO2 emissions;
    — ocean CO2 levels and fossil fuel CO2 emissions;
    — rate of global warming and rate of CO2 emissions;
    — rate of sea level rise and rate of CO2 emissions; and
    — rate of Arctic sea ice melt and rate of global warming.

  25. Loved the entire paper. It presents an entirely logical contradiction of the IPCC CO2 models upon which all of the CAGW alarmist hypothesis is based.

    I would like to see somewhat more detailed discussion of the C12/C13 subject as it relates to alarmists’ fallacious use of the differences to identify anthropogenic versus natural sources of CO2.

    Salby has a limited discussion of it in this youtube, but his presentation is less than optimal IMHO:

    I know this is a scientific paper, but I think the non-scientist readers would also benefit from a short discussion of the many natural causes of CO2, since so much of the public has been indoctrinated to believe that industrial emissions are not only the primary source, but the only source of increasing total atmospheric CO2:

  26. Dr. Berry,
    You say that IPCC’s argument is invalid because it assumes all human CO2 sticks in the atmosphere. I thought they believed only about 50% of human CO2 sticks in the atmosphere which is still invalid?

    1. Dear Stephen,
      The IPCC assumes human CO2 stays in the atmosphere much longer than natural CO2. This does not mean that no human CO2 gets out of the atmosphere.

      When we sum all human emissions up to a specific year after about 1970, the sum is about two times greater than the increase in CO2 above 280 ppm. So, the IPCC simply says that half of the human CO2 moved out of the atmosphere.

      1. I suppose that is what is confusing in your preprint with the statement, “IPCC’s argument is invalid because it assumes all human CO2 sticks in the atmosphere.” Wouldn’t it be better to say IPCC’s argument is invalid because it treats human CO2 differently than natural CO2? IPCC doesn’t assume all human CO2 sticks in the atmosphere; it assumes about half moves out. It assumes all the natural CO2 moves out of the atmosphere but only about half of the human.

  27. Dear Ed:
    Am I glad you came back from politics to science.
    While I agree with you that climate Change is not due to manmade factors but to mother nature, whether it is polar vortex, (See: or solar flares , or volcanic eruptions, (both terrestrial and sub – marine) I am of the belief that since the “manmade hypothesis” is based on GHG (i.e IR spectrum) the whole argument of CO2 being the culprit is wrong.

    While I appreciate your derivation of mathematical equations to support your theory of Equivalence principle, I still simply maintain that H2O is the real culprit.

    Look, there once was a gay poet who was born in Dublin and died in Paris (Oscar Wilde). He said, and I quote: “With age comes wisdom, but sometimes age comes alone”.
    While this is true for too many American voters, the exception is Greta Thunberg of Sweden. This high school dropout kid figured out that the game is not whether the climate changes or not, but rather that fame brings riches to its owner of fame.

    I tip my hat to her, in spite of my vehement disagreement with her.

    As to your book: I recommend you start with the definition of climate, as opposed to weather. Climate is a combination of temperature and precipitation. You might even comment how Global Warming slowly morphed into Climate Change as election day drew near.

    Any way, while your theory spins around CO2 as the culprit, I would proceed with the fact that the claim that it’s due to manmade actions (a “fact” which may be true to between 5 and 10%) cannot be proven, and therefore it’s an “extraordinary claim”.

    Any way, posting to the real problem is only half the issue. Proposing a solution is the other half. Sequestering CO2 has been proposed in many ways and that’s good. But what is the solution if you believe that H2O is the real culprit?

    Here is my theory:

    As the world population continues to grow (in spite of COVID 19 pandemic) water shortages around the world are saved by building more and more desalination plants. To save money, the concentrated brine is dumped back into the ocean, in most cases. This causes less evaporation which “translates” to less precipitation.
    Solution: spend some money to build evaporation ponds, and ultimately sell the salt to states that need salt to melt snow.

    The year 2020, according to NOAA, was the second warmest year since 2016, which was the warmest year. Now, if it is man made and not due to mother nature, 2020 should be warmer than 2016, since the world population grew and the demand for fossil fuels grew also.

    I hope my comments prove helpful in spite of any disagreements we may have. My kudos to you and your wife for your efforts.



  28. Dr. Berry,

    Elon Musk just announced that he is going to give 100,000,000 to the best carbon capture invention. I think you could win 😉

  29. Dr. Ed,
    I think you are right on both counts, Joe biden and his advisors are scientific morons and want to destroy America. Just like Justin Trudeau and his advisors are morons and want to destroy Canada.

  30. Your conclusions are surely correct – but in my eyes primarily for economic reasons. We don´t need to solve all the intricate problems natural scientists are dealing with, because the market provides much better solutions, as far as the decisive matter, POLICY, is concerned.

    For two reasons. 1) Things not broken don´t need to be fixed. 2) If broken, the actions to take are definitely NOT the ones suggested by the UN, IPCC, and most western governments. Because the only effective prescription is a GLOBAL climate tax on CO2 emissions, the same (roughly) in all countries.

    Kyoto – or Paris agreements only ends up with a REDISTRIBUTION of emissions. No global reductions and therefore no climate impact at all.

    A key problem is that even the most respected expert in this field, professor William D Nordhaus, the Nobel laureate rewarded for his writings on climate change, has been silent about this solution. I have personally, as a retired Civil Servant interested in these matters, contacted him about these facts, but he never responded, except for a first polite reply indicating a willingness to consider my questions, but then nothing more.

  31. Let me add that your graph separating human and natural causes is also quite convincing.

    But old estimates, derived from statistics or formulas of unknown quality, are more likely to be questioned than very basic price theori. Wellknown terms like demand and supply are shortcuts to insight, while few voters will ever grasp the rules guiding universe.

    By combining these two approaches, natural science and economics, end of the intellectual disaster called “climate change” is in sight. The sceptics have contributed to the delay, by making natural science their only weapon, when sharper ones are available, especially in the most relevant field, climate policy.

  32. Dr. Berry,
    I’ve read quite a few and have been drilled with quite a few attempts at the discredit of Beck’s excellent work.

    One common claim is that the readings weren’t atmospheric but locale and lower to the ground as if that makes any difference seeing how if it was read it existed? I’ve always been suspicious of the current atmospheric stable levels of CO2 claims, since all older papers I’ve read showed a regional seasonal flux that is never shown in the “official volume” which conveniently never lowers as it would on any standard model.

    This is a link to one of the crits and I’d imagine a standard template, as I am not a scientist I have no idea how legit the processes claimed in the paper are according to scientific experimentation. I have a hard time believing advanced chemists of the age would make those acclaimed errors.


  33. Ed,
    I have a few comments on your preprint. But first, thank you for correcting the mistake you made in your 2019 paper, where you mistakenly took “Delta 14C” to be C14 concentration. And thank you for posting my paper on your blog.

    Your Figure 17 summarizes your model. Reading from the curve, you assert that the concentration of a pulse of carbon injected into the atmosphere will fall by about 90% after 20 years. Harde and Salby’s yet to be published paper which you reference make similar predictions. These predictions are testable with carbon 14.

    The thing you call “14C ratio” in Section 4.5 is the fractional deviation of the 14C concentration from its value in 1970, in parts per thousand, with the 1970 value forced to about 510 parts per thousand, the value of Delta 14C in that year. Your prescription for calculating that quantity is correct. Yours is perhaps an awkward definition, but never mind. It will give the correct shape of the concentration curve over time.

    While you only show the 14C concentration from 1970 on, there is no good reason not to compute C14 concentration all the way back to 1950, or to 1920 as I did in my paper. (I copied you on my recent note to Harde, pointing out that early delta C14 measurements, using specific activity (Becquerels/gm) instead of isotope ratios measured by mass spectrometry, also depend on the 12C concentration at the time of the measurement.)

    With your definition, you would find negative but stable values of “14C ratio” between 1920-1950, in the vicinity of -150 parts per thousand. The Delta C14 curve decreases only slightly with time in this period due to the Suess effect, and the “14C ratio” (C14 concentration) is even flatter.

    Look at the whole range of 14C concentration data. You can save yourself the trouble of converting the years before 1970 to “14C ratio” by looking at the curve in Figure 2 of my paper, the shape of which agrees with your calculation after 1970, the only place you show calculations of it. (My plot is in ppmv instead of being a fractional deviation. I think ppmv is a more easily understood measure of concentration.)

    You see that what you call the “balance level” of 14C concentration around 1995 is about 50% above the quite stable 1920-1950 baseline. In your Figure 17, you predicted that the “bomb pulse” should be almost all the way back to its original baseline after all these years. It is not. In fact, the way that C14 decreased after the “bomb pulse” as displayed in my Figure 2 looks nothing like your Figure 17 plot. My plot is not a model. It is carbon 14 data, properly interpreted. As I said in my paper, the C14 concentration data refute your model.

    Harde and Salby try to explain their higher “balance level” (1995 vs 1950) by speculating that cosmic ray fluxes have dramatically increased since 1950. Their model does not fit the data either unless they make such unwarranted hypotheses. Radiocarbon daters indeed need to invoke small variations in atmospheric C14/C12 concentrations over the millennia, to reconcile their time scale with historical dates, but these variations are at the 1% level, not the 50% level.

    There is no mystery why the C14 concentration changed the way it did. Bomb testing put a lot of C14 into the atmosphere, not into the ocean or biosphere. This created an isotopic imbalance between the sinks. The rapid decrease of atmospheric C14 concentration in the 1970’s (which you were able to fit with an exponential) was accompanied by a corresponding increase in land and sea C14, as carbon in the different sinks mixed.

    That mixing was completed on the time scale that you measured. But the new carbon from the bomb test is not safely sequestered away, as shown by the baseline shift that you, Harde and Salby needed for your fits. It is now added to the cycling carbon. Similarly, the emissions from a gas-guzzling ’55 Chevy moved sequestered fossil fuel carbon into the carbon cycle, raising levels in the atmosphere and oceans in particular, and probably in land sinks as well.

    1. Dear David,

      Thank you for your comment.

      Your 2020 paper does a very good job of calculating the 14C data from the D14C and CO2 data. As you may recall, when you first introduced this subject in a comment on one of my posts, I agreed that ratios do not flow, only quantities flow. So, your physics is good.

      But your 2020 paper does not recognize that I and Harde used 14C data only to derive an upper bound for the 12CO2 e-time. And while it is true that my 2019 paper should have converted D14C data to 14C data, the consequences of this omission turn out to be zero because the 14C e-time is less than the D14C e-time, which strengthens the conclusions of my and Harde’s papers rather than refutes them. You did not calculate the 14C e-time to check this. So, your climate physics was not so good.

      If your paper had focused on your 14C calculation rather than as a hyper-focus (invalid) attack on the papers by me and Harde, AGU would have published it. Since I sent a rebuttal to your AGU paper, the AGU editor emailed me that he rejected your paper, and therefore my rebuttal, because you wrote it as a comment on the papers by me and Harde, rather than as an independent article.

      As an independent paper separated from its attack on the papers by me and Harde, your paper would have been a valuable and highly referenced paper.

      There are few scientific papers that do not have errors. Every time I rewrite my preprint, I find an error. Science, like technology, always moves forward after finding new truth but that does not mean the Wright Brothers’ airplanes were mistakes that negate the value of their flights.

      My preprint also updates my review of the Bern model because Tom C. politely showed in his comments that the Bern model coefficients were Green’s function coefficients. Of course, I understand Green’s functions, as do you, but I never found that connection in my review of Bern model papers. So, that may be the most critical error in my 2019 paper, now updated. But it does not negate the value of my 2019 paper because the rest of the paper stands alone.

      Regarding your specific items in your comment above:

      Yes, your Figure 2 is very good.

      Your conclusion that the Suess effect was the cause should be a hypothesis rather than a conclusion.

      Your comment on how I calculated my 14C ratio is valid. Remember, we have different goals. Your goal was to properly calculate the 14C data, and you did it well. Meanwhile, my focus was on my preprint #3, where my interest in 14C data is to derive a 14C e-time without adding another figure and more discussion to my already long paper. So, I chose the short way to do it, which you have kindly approved.

      My use of the balance level in Figure 19 is merely an easy mathematical way to find the e-time for the 14C data from 1970 to about 1990. It is not necessary that I fit the 14C curve beyond even 1980 because the curve will tend to assume longer e-times as the level moves closer to its equilibrium level, as described in Figure 18.

      I agree with your last two paragraphs that describe the physics of the flows. So, we can continue to discuss flows without conflicting our physics.

      Finally, your comment, “As I said in my paper, the C14 concentration data refute your model,” is not valid because I have not used my model to make a C14 prediction that can be tested.

      In fact, such a test is impossible because we do not know the 14C e-times of all six nodes. We do not know the 14C levels in all four reservoirs. And we do not know what changes may have occurred in the 14C inflows to each reservoir.

      If we make assumptions about these unknowns and assume the inflows have not changed since 1950, we could run my model to simulate the 14C pulse beginning 1970. The result might be a curve lying between the 12C and Bern curves in Figure 18.

      But the fact that the 14C data seem to be rising after, say, 1980, is not a contradiction of the model. It is a contradiction of our knowledge of 14C inflow.

  34. Ed,
    You say that you agree with my last two paragraphs. So evidently you agree with my last sentence: “Similarly, the emissions from a gas guzzling ’55 Chevy moved sequestered fossil fuel carbon into the carbon cycle, raising levels in the atmosphere and oceans in particular, and probably in land sinks as well.” Why then have you been saying for a few years that we humans are not responsible for the atmospheric CO2 increase? If you don’t agree with this last sentence, tell me why C14 added to the atmosphere with bomb tests is still with us, but C12 added by fossil fuel burning is not.

    For the third time, read Caldiera, et. al. The 14C data does NOT “contradict our knowledge of 14C inflow.” It confirms a prediction made in 1998, using a conventional carbon cycle model. It is only an anomaly in fringe models such as yours, Harde’s, and Salby’s which are, as you almost admit, contradicted by 14C data.

    1. Dear David,

      Human carbon emissions, whether from a 1955 Chevy or from the manufacture and installation of wind turbines, add carbon to the carbon cycle. The issue in this post, however, is how much the human carbon addition has increased the level of atmospheric CO2.

      I invite you to defend your sentence:

      “The 14C data does NOT ‘contradict our knowledge of 14C inflow.’ It confirms a prediction made in 1998, using a conventional carbon cycle model. It is only an anomaly in fringe models such as yours, Harde’s, and Salby’s which are, as you almost admit, contradicted by 14C data.”

      Please describe the important features of the “conventional carbon cycle model” and tell how it differs from the carbon cycle model described in this preprint, which you call a “fringe model.”

      Since you apparently still assume the Core Theory is true, please tell us how it can be true given the data plotted in Figure 1.

  35. Ed,
    I don’t think it is my responsibility to explain to you the paper: Caldeira, K., Raul, G. H., and Duffy, P. B. “Predicted net efflux of radiocarbon from the ocean and increase in atmospheric radiocarbon content.” Geophysical Research Letters, 25 (20), 3811-3814 (1998). They explain it clearly enough themselves. Here is a link for the convenience of you and your readers:
    By calling theirs a “conventional model”, I mean that it is a model that acknowledges the dominant human contribution to atmospheric CO2 increases during the last century. It is a model put together by physicists at the Lawrence Livermore Laboratory, not, as you would like to think, at some liberal think tank or university. As you know LLNL is the premier US nuclear weapons laboratory, and they know a thing or two about modeling fallout from nuclear testing. As you requested, here are some of the differences between the LLNL model and what I will call the BHS (Berry/Harde/Salby) model:
    1. The LLNL model (1998) predicted that atmospheric C14 concentration would rise beginning around 2000, because of the ongoing introduction of fossil fuel carbon into the atmosphere. This is not an obvious result since the fossil fuel carbon contains no C14, but the addition of fossil fuel carbon to the atmosphere has consequences that they explain, and which I echoed in my paper. This prediction is verified in recent data. Meanwhile the BHS modelers cannot fit the C14 concentration the same way they did when the authors misinterpreted DeltaC14 as a concentration. Harde and Salby hypothesize an increase in cosmic ray produced C14 to explain the discrepancy, even though the success of C14 dating verifies the stability of C14 production. You talk of unknown C14 inputs, another way of saying your model doesn’t fit the data as it stands either.

    2. The LLNL model utilizes conservation of carbon, not counting of course the creation of C14 from N14 neutrons from cosmic rays. BHS does not, and before discovering your Delta14C error, that was the focus of my criticisms. If once sequestered fossil fuel carbon is burned, the carbon released from sequestration must be accounted for somewhere. Harde’s earlier papers considered the oceans to be an infinite sink. If the C14 concentration really behaved like DeltaC14, that would be a defensible position. It is not defensible with his new and correct interpretation of DeltaC14. You have always been vague about where most of the fossil fuel carbon ends up, even while you have been adamant that little has ended up in the atmosphere. I guess you think it mostly goes into the ocean, at the same time that “natural carbon” is moving from the oceans to the atmosphere. It appears to me that it is your model, not the IPCC model, that violates what you call the equivalence principle!

    3. The LLNL model was published in Geophysical Research Letters, a peer reviewed journal. The BHS model was published by (or submitted to) Science Publishing Group, known to put out “predatory”, “pay to self-publish” articles without rigorous peer review. The original DeltaC14 error would never have gotten through a peer review process. I would not be the only one criticizing the earlier papers had they been published in more visible journals.
    In defense of you, Harde, and Essenhigh, I think the C14 community was negligent to allow misleading graphs of DeltaC14 to be a proxy for C14 concentration, a practice that continues. I may send my paper to their journal Radiocarbon and ask how they think this issue should be addressed, perhaps as a letter or comment in that journal.
    Let me now address your assertion that your Figure 1, which plots the history of carbon emissions along with the history of atmospheric CO2 concentration, somehow negates the idea that those emissions are the cause of the atmospheric CO2 increase. The two curves are strongly correlated, but not identical, and I suppose that is your point. The fact that in recent decades more carbon has been emitted than remains in the atmosphere is part of every competent model. The increase in carbon in the oceans, making them more acidic, is established. The IPCC has also documented an increase in land carbon, as the higher atmospheric CO2 concentration stimulates some forest growth. I don’t know for sure, but I would guess that CO2 concentration increasing faster than emissions early in the 20th century is related to land use changes. I do not believe that CO2 created by burning down a forest to make room for agriculture would be counted as human emissions in your plot. If I have correctly understood your point about Figure 1, it is similar to one Salby has talked about elsewhere: the lack of “detrended correlations” between CO2 concentrations and emissions. That Salby claims to reach a statistical conclusion on this point is remarkable, since nowhere does he consider data uncertainties! Surely he knows much more about atmospheric science than I do, but he does not appear to be experienced in handling data.
    I hope I have answered your questions. Now I have one for you. You assert that Harde and Salby’s unpublished paper “prove Andrews wrong.” Can you be more specific? It has taken nearly a year, but I am glad we now agree that I was correct on the DeltaC14 definition. I don’t know where you think I am wrong now.

    1. Dear David,

      You have not explained Figure 1 because IPCC’s estimates of carbon emissions from land-use are too small to have significantly changed the data used to plot Figure 1.

      You wrote, “You have always been vague about where most of the fossil fuel carbon ends up, even while you have been adamant that little has ended up in the atmosphere.”

      – Your claim is preposterous because Preprint #3 fully describes the flow of human carbon, which neither Caldeira et al. nor LLL have done.

      Caldeira et al. is invalid because their model incorrectly assumes the Core Theory is true, a fact you acknowledge when you say their model “acknowledges the dominant human contribution to atmospheric CO2 increases during the last century.”

      The Caldeira-LLL 14C model does not have or use a valid human carbon cycle model. LLL made a serious scientific error when it assumed the Core Theory is true.

      The LLL model predicted that 14C would increase around 2000, but a valid prediction is not evidence that the model is valid because other possible causes have not been eliminated.

      Caldeira et al. say this increase will happen because “fossil‐fuel carbon diminishes the net flux of 14C from the atmosphere to the oceans and land biosphere, forcing 14C to accumulate in the atmosphere.”
      – But they present no evidence or even physics to support that conclusion.
      – Figure 17 shows how a pulse of 14C in the atmosphere would flow to the land and oceans, according to IPCC 12C data.
      – The conclusion that human carbon “diminishes the net flux of 14C” means the LLL model includes invalid assumptions.

      You say the LLL model conserves carbon. Preprint #3’s carbon cycle model conserves carbon.
      Caldeira et al. do not describe their model, except to say it comes from:

      Hesshaimer, V., M. Heimann, and I. Levin, Radiocarbon evidence for a smaller oceanic carbon dioxide sink than previously believed, Nature, 370, 201-203, 1994.

      The Hesshaimer et al. paper does not describe their model and they openly admit they had to make adjustments to curve fit the data.

      By contrast, the Physics carbon cycle model is the only model that replicates IPCC’s natural carbon cycle data. Then it uses IPCC’s natural carbon cycle data to prove IPCC’s human carbon cycle is a fraud.

      Your attempt to claim the LLL model done two decades ago shows the Physics carbon cycle model is incorrect fails data and logic.

      You wrote, “The increase in carbon in the oceans, making them more acidic, is established. The IPCC has also documented an increase in land carbon, as the higher atmospheric CO2 concentration stimulates some forest growth.” – Preprint #3 fully explains these observations that are consistent with the physics carbon cycle model.

      Your “authority” arguments that refer to LLL and journals are invalid. All arguments in this discussion must be logical scientific arguments.

      Your criticism that the Physics carbon cycle model does not model the 14C carbon cycle is a strawman. I have not modeled the 14C carbon cycle.

      In summary, you have not shown there is an error in the Physics carbon cycle model. And we are long past your D14C argument that has no relevance to Preprint #3.

      (I do not represent the Harde-Salby model. You will have to address that issue with them when they publish their paper or its preprint.)

  36. (Note: To organize this discussion, I bolded Dave’s sentences that are relevant. – Ed)

    The Lawrence Livermore National Lab paper did not assume that human activities caused CO2 to increase. That conclusion followed from the data.

    For you to suggest that any argument which contradicts your theory is invalid, simply because it contradicts your theory, would imply that your field is religion, not science.
    Every scientist I have ever met (myself included) takes very seriously a model with demonstrated predictive ability.

    The LLNL model passes that test, making a non-trivial prediction verified by measurements.

    Every scientist I have ever met asks those whose theories DON’T fit the data “What modifications can you make to fix that?”

    Your present model of C12 transport was, I believe, motivated by your wrong interpretation of DeltaC14. (You may argue that point if you wish, but you once called your WRONG graph of C14 concentration after the bomb tests “the most important graph in climate science.”)

    As far as I know, you made no modifications to your model after I pointed out your mistake, you just avoided mentioning C14. Therefore it is no surprise at all that when your model is applied to C14, IT DOES NOT FIT THE DATA.

    What are you going to do about that Ed? You distance yourself from Harde, whose solution to the same difficulty was to invoke increased C14 production from cosmic rays. Your response so far has been “unknown C14 inputs.” You pay lip service to Feynman’s dictum: “It doesn’t matter how beautiful your theory is. It doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s WRONG.” Apply that dictum here.

    The contest is not between your model and the LLNL model. It is between your model and DATA.

    You forgot to tell me how the Harde and Salby draft paper, which Science Publishing Group tell me has yet to be submitted to Earth Sciences, proves my paper wrong.

    1. Dear Dave,

      Sorry, I had to bold some of your sentences in your comment above to identify the parts of your comment that were worth a reply.

      You claim the LLL paper determined from data that human CO2 caused all the CO2 increase (above 280 ppm). PROVE IT!

      You claim “The LLNL model passes that test, making a non-trivial prediction verified by measurements.” – You have reversed the scientific method by claiming a good prediction verifies a model.

      You think my Physics model was “motivated by [my] wrong interpretation of DeltaC14.” If you could understand my (2019) paper and my Preprint #3, you would see that my derivation of the Physics model stands alone and has nothing to do with 14C or D14C data.

      You say, “As far as I know, you made no modifications to your model after I pointed out your mistake, you just avoided mentioning C14.” This proves you do not understand Preprint #3, which is a very significant advance over my (2019) paper.

      You say, “The contest is not between your model and the LLNL model. It is between your model and DATA.” No, the contest is between the LLL model and data.

      Please show, in your next comment, how the LLL model uses data that show human CO2 caused all the CO2 increase above 280 ppm.

      Also, please show how the LLL model replicates the IPCC natural carbon cycle data.

      (And to answer your last question, the reason your paper is wrong is that it makes incorrect conclusions about my and Harde’s papers. These incorrect conclusions destroyed the value of your paper.)

  37. Ed,
    Nice try, but I will not be distracted by your highlighted requests for discussion of side topics. There is one and only one issue on the table that you failed to highlight and which you continually duck. That is the issue of the clear conflict between your model and the behavior of atmospheric carbon 14 concentration after the bomb tests. That is the issue which I asserted in my paper refutes your model, and I stand by that claim. The question is: is your model salvageable? I think it is not. Ralph Alexander says basically the same thing in his Oct 19, 2020 post on his scienceunderattack blog.

    I will accept, with considerable skepticism, your assertion that misinterpreted C14 data did not motivate your model. But however you arrived at it, you certainly did proudly show that your model nicely fit the misinterpreted C14 data, and was strong evidence in favor of it. That is why it should be no surprise to you that your model does not fit correctly interpreted data with substantially different features. When the data changes, whether in reality or because of a correction, models which previously fit the data must change or be discarded. Your challenge is not just to explain the small uptick in C14 after about 2000. You must also explain the higher “balance level” in your new fit. Where did all that C14 come from if carbon from whatever source is removed from the atmosphere on a time scale of a decade or two? Harde’s answer is maybe more cosmic rays. What is yours? (Interestingly, the current issue of Science discusses an event about 42,000 years ago during which the earth’s magnetic field reversed. While that was happening and the field was weak for a while, the earth was not so well protected from cosmic rays, and there was a temporary spike in C14 production. Maybe you can argue that is what is happening now.)

    1. Dear David,

      Correction: The issue under discussion in this post is whether Preprint #3 is correct in its conclusion that the Core Theory is false. You have provided NO evidence that the Core Theory is true.

      You wish to test the Physics carbon cycle model with 14C data. Such a test must assume a 14C pulse is added to the atmosphere in 1970, and the natural 14C level, inflow, and outflow all stay constant at their pre-1950 level and flows after 1970 and there are no other inflows. Your desired model test is impossible because you cannot guarantee that these assumptions are valid.

      You claim the observed increase in the 14C level after 1970 proves the Physics model is incorrect. Indeed, under the above assumptions, the Physics model would not predict this 14C increase, nor would any acceptable model. This would not be a test of the Physics model. This would be a test of your assumptions.

      You claim the LLL model predicted the increase based upon the theory that human CO2 somehow jammed up the outflow whereby 14CO2 escapes from the atmosphere. Sorry, that irrational explanation does not fly.

      Therefore, you are not talking about a test of the Physics model. You are talking about a test of the above theory that you cannot explain.

      You claim the LLL model is valid when it (a) cannot simulate IPCC’s natural carbon cycle and (b) assumes the Core Theory is true.

      In your previous comment, you claimed the LLL paper shows data that prove the Core Theory is correct. But now, you refuse to show such data. Why?

      So, you lied! There are no such data. If there were such data, the IPCC would use the data to support its Core Theory but it has not.

      I reject your opinions of my “motives” in developing my Physics model. No wonder you can’t do climate physics. You can’t focus on physics.

      I reject your referrals to opinions of people who will not put their opinions in a comment in this post. Your referrals show you lack confidence in your climate physics and you need emotional support for your opinion. After all, you did blow your climate physics in your paper.

      You want me to explain the observed increase in the 14C level after 1970, but even you cannot explain it.

      In summary, you so dearly believe the Core Theory is true even though you cannot produce any data or present any valid argument to support your belief. That, David, is called religion, not science.

    2. I assume people are pointing to the above ground atomic weapons tests as a source of C14.

      I also assume people think there were no more above ground atomic weapons detonated in the atmosphere, since 1970.

      But, what if I were to report there were more atmospheric detonations of atomic weapons, since that year? Would such detonations effect the C14 data people are using in attempting to track the reduction of atmospheric C14 levels?

      Has anyone calculated the amount of C14 created by a single device, of any specific yield?

      No need to puzzle about C14 levels not being predictable, or increasing, as it seems your data does not include all the input sources.

  38. Ed,
    I will choose a religion that explains data and anticipates trends, over one that is falsified by data, every time. The LLNL group did not need to make a lot of assumptions about C14 sources to explain the data. They simply assumed C14 production by cosmic rays since 1960 was unchanged from what it had been the last 1000 years, and that isotopic ratios in the various sinks were identical, before the bomb tests put C14 in the atmosphere. It is yours, Harde, and Salby’s models that cannot fit the data without making a lot of unjustified assumptions about changing C14 sources. I take your comments above as acknowledging that fact. The LLNL model wins by Occam’s razor.

    Of course, C14 is only about a trillionth of the atmospheric carbon. What we really care about is what it says about the fate of fossil fuel generated C12. The initial rapid change in atmospheric DeltaC14 and in C14 concentration after the bomb tests was caused by the initial isotopic imbalance between atmospheric and land and sea carbon. We do not expect C12 concentrations to track C14 concentrations during that period, which has a time scale some call the “residence time”. But after a couple of residence times when the bomb carbon and the carbon cycle carbon are thoroughly mixed, the only difference in C14 and C12 behavior are the small fractionation differences. (As you note, lighter C12 diffuses a little more quickly than C12. Those differences are in the LLNL model.) Thus the situation AFTER about 1990 is key in telling you what has become of carbon injected into the atmosphere much earlier. A model that gets C14 wrong in that period certainly gets C12 wrong.

    But I fear our posts are getting repetitious, and I will sign off with this one, and go enjoy a nice spring day.

    Best regards,

  39. Dear Reader,

    Now, it is up to you to review the arguments presented by Dave and my replies.

    Has Dave presented any argument that makes you believe the Core Theory is true?

    Has Dave presented any argument that makes you believe the conclusions of Preprint #3 are incorrect?

    In the next few weeks, we will review how Dave’s arguments reject physics and logic.

    Here is a start:

    Dave cannot find any fault in Preprint #3. So, he argues that another theory is true, namely, that somehow human CO2 emissions jammed up the outflow of 14C from the atmosphere, causing more 14C to accumulate in the atmosphere.

    Of course, if that happened, it would also slow the outflow of natural and human 12CO2. Reference [31] says that did not happen.

    Dave misses these key points:
    (a) you cannot prove a theory is wrong by proposing another theory,
    (b) Dave’s theory has no replacement for the Physics model hypothesis (2),
    (c) Dave’s theory is not a real theory because it cannot make a prediction that can be falsified,
    (d) Dave’s theory violates physics because it assumes the Core Theory is true, and
    (e) Dave’s theory assumes human CO2, but not variations in natural CO2, blocks the outflow of 14C.

    Dave has a Ph.D. in physics and is an expert climate alarmist. So, Dave has proved that climate alarmism is a scientific scam.


  40. Dr. Ed,
    The one hypothesis that the entire model rests on: “outflow is proportional to level” (2) on page 9/10 … are you sure it’s true? Is it a fundamental law in physics that applies to all systems where something is flowing in and out of reservoirs?
    I’d be grateful if you gave me a reference that supports this hypothesis.
    Thanks a lot

  41. Dear Renate,
    You are correct, my hypothesis (2) is the basis of my model, as I state. This is the same hypothesis IPCC uses for its natural carbon cycle model. IPCC’s “turnover time” is the same as my Te. My model using (2) exactly replicates IPCC’s natural carbon cycle data.

    What are the alternatives? IPCC offers none. There are no data that support any other hypothesis. Until there are data to support that outflow is some nonlinear function of level, then we should use the simplest hypothesis, which is (2).

    The units of outflow are mass / time, which in the model translates to level / time, which supports (2).

    Pharmacology models use (2) because chemical reactions are linear functions of level. Dalton’s law of partial pressures is linear.

    In addition, suppose outflow is a nonlinear function of level that we do not know. Then it is still proper to use the linear function in models because a nonlinear function will be near “linear” when the level is near its balance level. Human CO2 has added only about one percent to the carbon in the carbon cycle, meaning human carbon will not change the linear behavior of IPCC’s carbon cycle.

    Most important is that the IPCC uses the linear model and I use IPCC’s own data to prove my point. In other words, I do not need to do the research to prove outflow is linear. That is IPCC’s job. My job is only to show that IPCC’s linear natural carbon cycle data prove IPCC’s claimed human carbon cycle is wrong.

  42. Dear Dr. Ed,

    thanks a lot for the reply! I understand your approach. You were more concerned in proving the IPCC wrong than in discovering the truth. That’s fine.

    Assuming that the hypothesis is true, it’s clear that one of the the conclusions – the IPCC’s or yours – must be wrong because they are very different. But what if the hypothesis isn’t true? Then both conclusions may be wrong. Do you agree?

    I found a hint that the hypothesis is NOT a universal law in physics. Here’s a counter-example:

    In this circumstance, the outflow is proportional to the square root of the level (provided that the tank holding the fluid has a constant cross-section). The speed at which the fluid escapes may be expressed in the unit [mass/time] which translates to [level/time], so the consideration of the units you gave does neither support nor reject the hypothesis.

    What do you think about the hypothesis now after learning about a counter-example? Should the IPCC consider a different relationship between flow and level?

    1. Dear Renate,

      First, there are many examples in physics where outflow is not linear in level. Torricelli’s well-known law is only one of them. It is based on the transfer of potential energy (mgh) into kinetic energy (1/2 mv^2). Also, irrigation engineers design weirs to produce a desired relationship of outflow to level. But these are not chemical reactions or reactions that transfer molecules between states, like from vapor to liquid. So, these examples are unrelated to our subject.

      Second, and most important, is your comment: “You were more concerned in proving the IPCC wrong than in discovering the truth.”

      The philosophy of science says the way we learn truth is to prove a hypothesis is wrong. So, my proof that the IPCC human carbon cycle is wrong is a discovery of the truth. When we prove a hypothesis is wrong, we identify what is fiction. Then the truth is lies outside that fiction.

      My paper shows that IPCC’s human carbon cycle does not use the same physics as IPCC’s natural carbon cycle. IPCC’s natural carbon cycle is based on data but IPCC’s human carbon cycle is based only on the (incorrect) assumption that human CO2 has caused all the increase in atmospheric CO2. Therefore, we must reject IPCC’s human carbon cycle.

      Torricelli’s law will not to replicate IPCC’s natural carbon cycle, so we must reject Torricelli’s law for this application. But suppose it did. Then, we would still find that IPCC’s human carbon cycle uses different physics that its natural carbon cycle.

      If we follow the scientific method, we must reject IPCC’s human carbon cycle. If anyone wishes to support IPCC’s human carbon cycle, the only way is to postulate another hypothesis that replicates the data in IPCC’s natural carbon cycle, and then recalculate the new IPCC human carbon cycle. No one has done this. So there is no alternative hypothesis to test.

      Therefore, your argument does not prove my paper is wrong.

  43. Dear Ed,

    You say “my hypothesis (2) is the basis of my model, as I state. This is the same hypothesis IPCC uses for its natural carbon cycle model. IPCC’s ‘turnover time’ is the same as my Te.”

    However, the IPCC does not specify the dependence of outflow versus level. They only specify a single point: outflow at the current level. Graphically, this looks like this: . The turnover time is just the outflow divided by the level, regardless of the full dependence — it is specified by a single point.

    Now, there are an infinite number of possible functions for outflow versus level that go through this point. Again, graphically, here are a few examples: . You have chosen to make outflow proportional to level, which is the red curve. This is the simplest choice, and Occam’s razor is often useful, but there is no good reason to believe the oceanic carbon cycle follows the simplest possible dynamics.

    You also say this: “In addition, suppose outflow is a nonlinear function of level that we do not know. Then it is still proper to use the linear function in models because a nonlinear function will be near “linear” when the level is near its balance level.”

    I agree that it is right to approximate the full outflow v level dependence with a linear function. This is equivalent to approximating the full function by its derivative, as shown by the green lines here: . But there are still an infinite number of choices, and your choice of the red line is arbitrary.

    To summarize: you say that you have shown that the IPCC’s carbon cycle model can’t explain the CO2 rise. But really, you have only shown that the “red curve” model can’t explain the CO2 rise. The IPCC numbers you used specify the one starred point, but the IPCC never endorsed the red curve model. In fact, other papers cited by the IPCC specifically calculate a different dependence — see, for example, the Revelle factor.

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