Nakamura Mototaka’s Book, “Confessions of a climate scientist”

Confessions of a climate scientist:
The global warming hypothesis is an unproven hypothesis
– by Nakamura Mototaka

“From 1990 to 2014 he worked on cloud dynamics and forces mixing atmospheric and ocean flows on medium to planetary scales. His bases were MIT (for a Doctor of Science in meteorology), Georgia Institute of Technology, Goddard Space Flight Centre, Jet Propulsion Laboratory, Duke and Hawaii Universities and the Japan Agency for Marine-Earth Science and Technology. He’s published about 20 climate papers on fluid dynamics.”

A Climate Modeller Spills the Beans

This was a fast but very interesting read which reinforced many of my understandings about the relevance of the climate models, given the observational data. But he also clarified several important issues I haven’t explored. (Bold emphasis in quotes added by me.)

“… 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, … 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.”

A sample of factors before any feedback loops. Not from the book.

The most obvious and egregious problem is the treatment of incoming solar energy — it is treated as a constant, that is, as a “never changing quantity”. It should not require an expert to explain how absurd this is if “climate forecasting” is the aim of the model use. It has been only several decades since we acquired an ability to accurately monitor the incoming solar energy. In these several decades only, it has varied by 1 to 2 Watts per square meters.”

I’m not sure I’ve ever been aware that solar energy was treated as a constant in the models. This information would’ve ended the debate for me much more quickly. I learned it within days of reading this book/essay, overshadowed by a global climate strike.

I’ve long been skeptical that even the world’s best can sufficiently understand the countless chaotic nonlinear systems which interact to create climates. I still believe it is hubris to believe we can know these things with any actionable certainty. He discusses this in more detail…

“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 … appear to firmly believe in the validity of using these models for climate forecasting.

“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.”

“Climate researchers used to downplay the significance of interactions between the large-scale atmosphere and oceans in the middle and high latitudes, based on many experiments using coarse-resolution climate simulation models that are hopeless in capturing the atmospheric response to the underlying oceanic temperature structures and analyses of these experiments with mostly linear statistical methods in simple frameworks. They had missed important factors in the large-scale atmosphere-ocean interactions in the extra-tropics (middle and high latitudes) — importance of the spatial position of the westerly jet stream with respect to the areas of large horizontal temperature gradient (contrast) in the oceans and high horizontal resolutions required for capturing effects of the oceanic temperature structures — and grossly underestimated the oceanic impacts on the large-scale atmospheric states.

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. So, small- to medium-scale motions exert ensemble effects on the larger-scale state in such a way that they “tighten” the larger-scale fields of flows, temperature, and salinity when and where the larger-scale flows tend to “loosen” the larger-scale fields. I found this situation occurring roughly half of the time in realistic ocean simulation output.”

“Not only is the strictly-diffusive qualitative aspect of the representations wrong, but also the quantitative aspect of the representations, the strength of mixing and transport, is an ad hoc “model tuning tool”. Parameters that determine the strength of mixing and transport by the smaller-scale flows are selected to “tune” the model without adhering to numbers estimated from observations or high-resolution model output. That is, the selection of the parameter values is an engineering process to “make the model work” rather than a scientific process. 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.”

“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. This positive feedback itself is not fictitious. But, in climate models, it is artificially enforced to operate without interference by other feedbacks that exist in the real climate system, and is very likely to be exaggerated. It is this feedback that generates major increases in the surface temperature when the atmospheric carbon dioxide is increased in climate simulation models.”

“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.”

“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 1mm. So, clouds are represented with parametric methods in climate models. Are those methods reasonably accurate? No. If one seriously studies properties of clouds and processes involved in cloud formation and dissipation, and compare them with the cloud treatment in climate models, one would most likely be flabbergasted by the perfunctory treatment of clouds in the models. 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.”

“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.

So it continues to be my position that there are far better reasons — and less divisive reasons — to hasten the inevitable shift to renewable energies. Meanwhile, more outlets and activists might be more attracted to trying to prevent this alleged catastrophe with even scarier science. And a global movement of environmentalists will help build the next big energy ownership consolidation, keeping it in the big oil family.


Here is a very related video created by one of the few voices that let me know this book was published:

More Significant Details

These points were originally included in my essays, but removed to keep those arguments as focused as possible. But I do still think these are important points to be aware of…

CO2 Lags Temperature

One of the specific points I find more important is the historical correlation of carbon and temperature. I’m not sure how often this perspective finds the mainstream discussion, but Al Gore’s Inconvenient Truth strongly implies that there is causality on the side of carbon driving increases in global temperatures. However there is wide agreement that based on Antarctic ice core data, changes in CO2 have followed changes in temperatures by about 600 to 1000 years.

This is consistent with carbon being one of the smaller temperature feedbacks, which seem to be dominated by water vapor and clouds. This “carbon lag” is accepted by both sides, and creates a opportunity for AGW proponents to confirm that CO2 has not been a dominant driver of climate and the real debate is focused on the feedback loops.

Some critics of this “lag” argument cite our current century as the one counter-example when temperature changes have lagged behind carbon changes (Al Gore’s side of causality). But in order to consider this modern counter-example as evidence of carbon being a significant driver of temperature, you must first presume the certainty of the above AGW models. So again, this counter-argument begs the question.

Changes in CO2 have lagged behind changes in temperature, so if there is causality within their correlation, the historical record demonstrates the opposite of popular opinion.

While this correlation is not inconsistent with basic carbon-temperature feedback concepts, many assumptions are necessary to count it as solid evidence for the large multiplying feedbacks in the models. Increases in carbon, one of the weaker greenhouse gasses, have never caused temperature increases before this century, so the burden of proof remains on the AGW models and the correlation cannot support the theory of catastrophic man-made global warming.

For more than five years I have been asking carbon-related questions, and I am more concerned about man-made elements added to the periodic table. Novel elements we have invented for the first time earth’s known history, which may affect the environment (and us) but not necessarily the climate.


The graph above with temperature and carbon over the past 400,000 years shows us in our current higher temperature ballpark every 100,000 years or so. Had we modernized 20,000 years earlier, there would be zero concern on rising temperatures because we would be debating at a low-point in the 10 degree Celsius fluctuations within this time-scale.

The following chart is the most common perspective in the mainstream discussion of this debate. It goes back until only 1880, and is very short-sighted but helpful for encouraging alarm:

It should be noted that in this graph above does not have the scope of the current century, where atmospheric carbon levels approach 400 ppm. This rise of carbon before temperature is certainly an anomaly without historical precedent. But also keep in mind that each doubling of CO2 concentration, temperature increases by a constant value.

Anatomically modern humans had thousands of years on an earth more than 2.5 degrees Celsius warmer than this century (almost 5 degrees Fahrenheit warmer):

And our great ape ancestors lived on an earth more than 7 degrees Celsius warmer than this century (around 13 degrees Fahrenheit warmer). It was definitely very different, and might not be preferable, and a rapid rate of temperate change may be another issue, but those temperatures alone were clearly not catastrophic enough to prevent our evolution or complete destruction of ecosystems.

And of course, the concern is really about maintaining our human status quo, life on earth itself will go on with or without us, and is not threatened.

Links embedded in this essay: (Inconvenient Truth) (Peter Sinclair)

Videos Worth Entertaining

Possibly the only debate on the topic without a single ad hominem attack:

Why the models matter:

Issues with the IPCC itself, Donna Laframboise Interview: