Book review: Confessions of a Climate Scientist — Global Warming is an unproven hypothesis

Gastao Taveira
Oct 1 · 13 min read

A top-level climate scientist shows why the predictions of climate models are not reliable for dictating public action and energy policy despite being useful for weather and climate research.

This is a remarkable book that describes the major features of climate models and their limitations to reflect the termodynamics of the oceans and the atmosphere. It explains how the Earth’s Climate is modelled for computer simulations and how these models, though being useful for climate research, cannot be used to predict climate. They cannot even predict the sense or direction of the climate change correctly. This book is concise and easy to grasp if you have just a basic knowledge of physics.

Dr. Mototaka Nakamura is a top-level scientist who worked on cloud dynamics, and on atmospheric and ocean flows for almost 25 years at world class institutions. He has a ScD in meteorology from MIT and has an impressive curriculum in the area of climate science and modelling: Georgia Institute of Technology, NASA (Goddard Space Flight Centre, Jet Propulsion Laboratory), Duke and Hawaii Universities and the Japan Agency for Marine-Earth Science and Technology. He published about 20 climate papers on fluid dynamics

A few months ago he published a book in Japanese explaining the flaws of the current Climate Science “with an aim to inform the Japanese public of the reality behind the rampant “global warming” references in the Japanese society, because of the absence of accurate description of the state of climate science revealed by climate experts in the Japanese language”.

In mid September, just a few weeks ago, he published a short English version in Kindle eBook format. Despite being a concise version it covers essentially the same topics.

Summary and excerpts

Dr. Nakamura says:

… my skepticism on the “global warming hypothesis” is targeted on the “catastrophic” part of the hypothesis and not on the “global warming” per se. That is, there is no doubt that increased carbon dioxide concentration in the atmosphere does have some warming effect on the lower troposphere (about 0. 5 degrees Kelvin for a doubling from the pre-industrial revolution era, according to true experts), although it has not been proven that the warming effect actually results in a rise in the global mean surface temperature, because of the extremely complex processes operating in the real climate system, many of which are represented in perfunctory manner at best or ignored altogether in climate simulation models. I also want to emphasize that I am not denying the possibility of a major climate change as a result of the human activity, either catastrophic global warming or a return of severe glacial period (the real climate system that has myriad of physical and biogeochemical processes is highly nonlinear, much more so than the toys used for climate predictions). I am simply pointing out the fact that it is impossible to predict with any degree of accuracy how the climate of this planet will change in the future.

I want to emphasize here that climate simulation models are fine tools to study the climate system, so long as the users are aware of the limitations of the models and exercise caution in designing experiments and interpreting their output. In this sense, experiments to study the response of simplified climate systems, such as those generated by the “state-of-the-art” climate simulation models, to major increases in atmospheric carbon dioxide or other greenhouse gases are also interesting and meaningful academic projects that are certainly worth pursuing. So long as the results of such projects are presented with disclaimers that unambiguously state the extent to which the results can be compared with the real world, I would not have any problem with such projects. The models just become useless pieces of junk or worse (worse, in a sense that they can produce gravely misleading output) only when they are used for climate forecasting.

Dr. Nakamura focuses on “two serious flaws in climate simulation models used for climate change predictions” that he knows as an expert:

1. A fatally serious flaw in the oceanic component of the models.

2. Grossly oversimplified and problematic representations of the atmospheric water vapor.

Let’s go through the main topics addressed in the book. After finalising this review and summary I realised I had reproduced a lot of the book’s content. This book is so full of information that virtually every period contains relevant explanations or descriptions of the climate or modelling processes. It was dfficult to select some and leave others out.

Global temperature measurement

Only in the past 50 years, with the use of satellite observations has it been possible to measure surface temperatures on a global scale. Until then observations were limited to a very small portion of the earth’s surface. Temperature trends before that time have a narrow coverage, therefore limiting the assessment of global means.

Other simplifications in the models no adressed in this book

There are many other gross simplifications employed in climate prediction models that are likely to be fatal for making any meaningful climate prediction. One of them is, for example, a complete lack of meaningful representation for changes in aerosols that act as cloud condensation nuclei. I do not touch on these biogeochemical topics even in the Japanese version either, since I am not an expert on them.

Besides, the solar energy is treated as a constant by the models (its has changed by 1 to 2 Watts per m2 since a few decades ago since when we had the means to measure it) which limits their ability to predict long term climate.

Serious flaws in climate “forecasting” models

All climate simulation models have many details that become fatal flaws when they are used as climate forecasting tools, especially for mid- to long-term (several years and longer) climate variations and changes. These models completely lack some of critically important climate processes and feedbacks, and represent some other critically important climate processes and feedbacks in grossly distorted manners to the extent that makes these models totally useless for any meaningful climate prediction. I myself used to use climate simulation models for scientific studies, not for predictions, and learned about their problems and limitations in the process. I, with help of some of my former colleagues, even modified some details of these models in attempts to improve them by making some of grossly simplified expressions of physical processes in the models less grossly simplified, based on physical theories. So, I know the internal workings of these models very well. I find it rather bewildering that so many climate researchers, many of whom are only “so-called climate researchers” in my not-so-humble opinion, appear to firmly believe in the validity of using these models for climate forecasting. I have observed that many of those climate researchers who firmly believe in the global warming hypothesis view the climate system in a grotesquely simplified fashion: many of them view the climate system as a horizontally homogeneous (no variations in the north-south and east-west directions) or zonally homogeneous (no variations in the east-west direction) system whose dynamics are dominated by the radiative-chemical-convective processes, smooth vertical-north-south motions in the atmosphere, and stationary oceans, and completely neglect the geophysical fluid dynamics, an extremely important and strong factor in the maintenance of the climate and generation of climate variations and changes.


… erroneous representation of actions of oceanic motions that have spatial scales of a few hundred kilometers or smaller. I use the word “erroneous” here to convey a message of “doing something wrong” to the readers, but emphasize that there is nothing anyone can do about it intellectually and that it can be remedied only by increasing the resolution of climate simulation models from the typical 1 ˚ x 1 ˚ or lower to 0. 1 ˚ x 0. 1 ˚ or higher in longitude and latitude. It is simply an issue of limited computer resources and is not an issue of our limited knowledge of the ocean dynamics and thermodynamics…

Oceanic flows play extremely important roles in climate. They are much slower than atmospheric flows, but transport extremely large amount of heat due to the large heat storing capacity of water. The oceanic heat storing capacity is so much greater than that of the atmosphere to the extent that one can say that the atmosphere does not store any heat at all in comparison to the ocean…

Needless to say, it is absolutely vital for any meaningful climate prediction to be made with a reasonably accurate representation of the state and actions of the oceans. In particular, oceanic flows that play important roles in poleward transports of heat and salt and generation of the so-called thermohaline circulation must be represented reasonably accurately because of very long time scales (tens to hundreds of years) associated with the thermohaline circulation…

Albedo is a fancy term for the planetary reflectivity of the solar radiation… This process plays the dominant role in the major warming in high-latitude regions produced by climate simulation models in scenarios of increasing atmospheric carbon dioxide. Without a reasonably accurate representation of the ice-albedo feedback, it is impossible to make any meaningful prediction of climate variations and changes in the middle- and high-latitudes and, thus, the entire planet. One might argue that it wouldn’ t matter in a very long run, if the carbon dioxide emission continues to increase. It does matter, because the terrestrial and oceanic biogeochemical processes that control the atmospheric carbon dioxide concentration are dependent on the temperature, among other factors, and are highly nonlinear…

I hate to say this, because I know well how much of serious efforts have been put into improving these parametric representations (I spent hundreds of hours in vain myself), but all of these parametric representations, even the best of them, are Mickey Mouse mockeries when compared with the reality. In the real oceans, just like in the atmosphere, the smaller-scale flows often tend to counteract the effects of the larger-scale flows…

… The models are “tuned” by tinkering around with values of various parameters until the best compromise is obtained. I used to do it myself. It is a necessary and unavoidable procedure and is not a problem so long as the user is aware of its ramifications and is honest about it. But it is a serious and fatal flaw if it is used for climate forecasting/ prediction purposes…

…Thus, changes and variations in climate predicted by those models are completely meaningless even if they were tuned to reproduce the current climate very accurately. By the way, none of the climate simulation models used for predictions can reproduce the current climate accurately despite the heavy tuning and engineering efforts by climate researchers. The models are tuned to produce the “best compromise” and used for various experiments.

Ad hoc treatment of water in the atmosphere

Water vapor is the most important greenhouse gas in the Earth’ s atmosphere. Actually, a large portion of the major global warming predicted by those climate prediction toys is attributed to increases in the atmospheric water vapor concentration, not the increased atmospheric carbon dioxide…

Most of the people who have studied the global warming issue probably know about its strong greenhouse effect, that is, its role as a radiation absorber/ emitter. Its radiative forcing in the present climate dwarfs that of the atmospheric carbon dioxide. The enhanced warming effect of its changes predicted by the climate simulation models also dwarfs that of the projected carbon dioxide increase. So, predicting changes in the radiative forcing associated with the atmospheric water vapor accurately is essential for any meaningful prediction of climate changes. But the fact is this: all climate simulation models perform poorly in reproducing the atmospheric water vapor and its radiative forcing observed in the current climate.

This difficulty stems from, among several major factors, large spatial and temporal variations in the water vapor concentration. Unlike other trace greenhouse gases in the atmosphere, water vapor plays a critical and active role in atmospheric motions of all scales and directions and readily changes its phase from gas to liquid (water) or solid (ice), and vice versa. Energy release/ absorption associated with these phase changes is one of the most important factors that drive the climate system. Since water and ice can be removed from the atmosphere by precipitation, accurately simulating atmospheric motions that bring these phase changes is a prerequisite for reasonably accurate simulation of climate…

… The models use various parametric representations that estimate the water vapor profiles from the large-scale atmospheric state that can be calculated by the models. All but one of these parametric representations are ad hoc and rely on major simplifying assumptions that are not justifiable when scrutinized against the reality…

… Most of these parametric representations employ procedures that adjust the atmospheric water vapor content in a vertical column by using as references certain smooth profiles derived from averaging relative humidity profiles over the globe or over very large areas and over very long periods of time, and have nothing to do with instantaneous physical processes… In the case of increasing atmospheric carbon dioxide, the use of relative humidity as the variable of control target creates artificially forced extra warming arising from the increase in the maximum water vapor content in the atmosphere, as the maximum water vapor that can be contained in the atmosphere increases exponentially with temperature… So, if a model were to have the same relative humidity regardless of changes in other aspects of the atmosphere, then, for a minor warming caused by an increased amount of carbon dioxide, the artificially imposed condition on the relative humidity would generate some extra warming due to an increase in the water vapor amount, which would tend to further raise the atmospheric temperature and water vapor content, creating a vicious cycle between the atmospheric water vapor and temperature…

One might think that the parametric schemes work fine for climate simulation, if such averages compare well with the observation, since the target of the simulation is not the daily forecasts. They do not, because of the nonlinear relationship between the water vapor concentration and its warming effect…

The ad hoc treatment of the vertical water vapor distribution is not the only major problem associated with this most important greenhouse gas. Methods to calculate its horizontal distribution are laced with a grave problem also. It is rooted in the treatment of effects of sub-grid (too small to be calculated explicitly in climate models) motions on the water vapor…

… The diffusion in the models results in artificial spatial smoothing of the water vapor field by artificially moving some water vapor from areas of greater amount to smaller amount. This procedure is designed to conserve the total amount of water vapor, but produces artificial net warming effect via the nonlinear characteristic of greenhouse effect…


Clouds, consisting of immeasurable numbers of very, very small liquid water droplets, also have the greenhouse effect, but have significant cooling effects due to their light scattering properties as well. Clouds’ role in the global climate is extremely important and extremely complex, to say the least. Ad hoc representations of clouds in climate models may be the greatest source of uncertainty in climate prediction. A profound fact is that only a very small change, so small that it cannot be measured accurately with the currently available observational devices, in the global cloud characteristics can completely offset the warming effect of the doubled atmospheric carbon dioxide…

Reasonably accurate representation of cloud is one of the most difficult and important tasks in climate simulations. Accurate simulation of cloud is simply impossible in climate models, since it requires calculations of processes at scales smaller than 1 mm. So, clouds are represented with parametric methods in climate models. Are those methods reasonably accurate? No…

The parametric representations of clouds are ad hoc and are tuned to produce the average cloud cover that somewhat resembles that seen in the current climate. Can we, or should we, expect them to simulate the cloud coverage and properties in the “doubled atmospheric carbon dioxide” scenario with reasonable accuracy? No. I am aware that some sophisticated cloud models have been developed in recent years. Unfortunately, however, regardless of the degree of sophistication they achieve, the net effect of clouds in the future climate cannot be predicted meaningfully without knowing how the presence of super tiny particles in the atmosphere that are essential to cloud formation changes in the future, which is practically impossible.

Nakamura concludes:

The take-home message from the above discussion is this: all climate simulation models, even those with the best parametric representation scheme for convective motions and cloud, suffer from a very large degree of arbitrariness in the representation of processes that determine the atmospheric water vapor and cloud fields. Since the climate models are tuned arbitrarily to produce the time-averaged atmospheric water vapor field and cloud coverage that best resemble the observed climatological ones, but still fail to reproduce the observed fields (especially miserably when the instantaneous field and temporal variability are examined), there is no reason to trust their predictions/ forecasts. With values of parameters that are supposed to represent many complex processes being held constant, many nonlinear processes in the real climate system are absent or grossly distorted in the models. It is a delusion to believe that simulation models that lack important nonlinear processes in the real climate system can predict at least the sense or direction of the climate change correctly.

On his motivation for writing this book

For better or worse, I have more-or-less lost interest in the climate science and am not thrilled to spend so much of my time and energy in this kind of writing beyond the point that satisfies my own sense of obligation to the US and Japanese tax payers who financially supported my higher education and spontaneous and free research activity. So, please expect this to be the only writing of this sort coming from me. I am confident that some honest and courageous true climate scientists will continue to publicly point out the fraudulent claims made by the “mainstream climate science community”…

Before concluding the introduction, let me state unambiguously that I am all for environmental conservation, contrary to what some people might think about me. I do support the idea of reducing oil and gas consumption, based on a simple fact that there are limits to those resources (unless the rate of generation is greater than the rate of consumption) and also on a fact that there are human health problems caused by the use of those resources, not based on the unproven hypothesis of the global warming. Let’ s reduce the oil and gas consumption by globally declaring eternal zero tax on any activity related to renewable or sustainable energy resources, rather than imposing nonsensical and immoral carbon tax on harmless carbon dioxide, shan’ t we? I would happily support a positive and productive approach of that kind.


Links to the Kindle version on Amazon where it can be purchased for $1 (don’t be scared by the title, the main part is in Japanese, but it contains the English version too)

The book has become a best seller in Sciences & Technology in Japanese on Amazon.

A review on Quadrant (Australia):

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