Why is the Carnot Cycle the most efficient heat engine?

Desmond Sander asks:

You say: “There is no other heat engine that can convert heat to work more efficiently than the Carnot Cycle. It is the perfect heat engine.”

I ask: How about Rafa Nadal? Does he not convert the kinetic energy of the oxygen molecules he breathes (and other molecules in food) to the motions of his body which make him a great tennis player? Is that not a local increase in entropy, similar to the local increase in entropy that other individuals like you/me achieve so long as they are alive?

 

 

On Consciousness

How might artificial intelligence achieve consciousness?

It has been said: “Machines will become conscious when they start to set their own goals and act according to these goals rather than do what they were programmed to do”. Setting its own goal instead of following a program would be seen as a bug, a flaw. Perhaps in order for a machine to be conscious it must be flawed. Evolution happens because of flaws in DNA. Mathematics requires Gödel.

In order to be conscious, intelligence must be flawed; without flaws it is just a program. Without flaws in nucleic acids, no life more complex than a virus could ever have evolved. Gödel’s theorem states that any self-consistent system of mathematics must be finite. Without the flaw of original sin, we would be God’s robots. Without random errors there could be no life – the Universe would be a lifeless, deterministic machine. Attempts to create a society which is flawless always fail because such a society can never renew itself.

References:

A Return to Empiricism

Chapter 16 of The Fluid Catastrophe by John Reid

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Science or Astrology?

Fig 7 from John Christy’s paper showing model predictions of tropospheric equatorial temperature and actual measurements. (Image: Global Warming Policy Foundation)

Global average temperature has risen by about  1oC over the last century. But it has not risen steadily. There have been ups and downs. The record is noisy. When the data is analysed its variance spectrum is “red”, i.e. there is a concentration of variance at low frequencies. This gives rise to “spurious regression”  which is sufficient to account for the observed variation, that is, there is no statistically significant trend in global average temperature. The presumed correlation with atmospheric CO2 concentration is also spurious for the same reason.

In 1962 philosopher Karl Popper set out seven principles defining the Scientific Method, e.g. A theory which is not refutable by any conceivable event is non-scientific. Climate models are certainly refutable and so are indeed scientific theories. Prof John Christy of the University of Alabama has spent decades collating model predictions of global average temperature and testing them against observations. All but one of 102 models failed the test. Clearly the models don’t work. They don’t work because the equations on which they are based do not satisfy the Second Law of Thermodynamics. If climate “science” really were a science this sort of fluid dynamic modelling would have been abandoned decades ago.

Instead millions of dollars in research funding is being wasted on projects that are no better than Astrology.

 
Reference:

The Fluid Catastrophe by John Reid

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Deniers and Charlatans

Fig 7 from John Chrity’s paper showing model predictions of tropospheric equatorial temperature and actual measurements.

In the last couple of weeks, the intensity of pandemic climate change hysteria went up another notch when the UN Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) announced that a million species now face extinction. Twenty seven Australian City Councils immediately declared a Climate Emergency and we have seen the birth of a new movement, Extinction Rebellion. Extinction Rebellion is “a socio-political movement which uses nonviolent resistance to protest against climate breakdown, biodiversity loss, and the risk of human extinction and ecological collapse”. Clearly the UN is now an active agent of social unrest in the West.

There is no factual basis for any of this. The IPBES provided no evidence for its outrageous claim, no link to a world species database, for example. Any rational individual who may harbour lingering doubts about the paucity of evidence supporting the man-made climate change hypothesis need only spend half an hour viewing Prof. John Christy’s Congressional Testimony (May 2015, https://www.youtube.com/watch?v=Cz45fETw078). A more recent written version of Christy’s arguments can be found at https://www.thegwpf.org/climate-models-have-been-predicting-too-much-warming/ , the centrepiece of which is the graph at the top of this page showing how all but one of 102 climate models failed to predict equatorial tropospheric temperatures over a period of 20 years. There is no evidence of climate change other than these models and they are clearly wrong. There is no evidence at all.

Evidently Christy’s impeccably empirical approach is inaccessable to some people. They can’t handle facts, they need explanations. Rep. Alan Lowenthal in the YouTube video is an example. Well, Congressman,  here is my explanation: as my book points out, the models cannot predict the climate because they are based on equations which cannot describe turbulence. The atmosphere is clearly turbulent, look at any weather map. Therefore the equations and the models fail. The models don’t work. They are not evidence of anything. But even if they were true, they would show that the contribution to global temperature due to US emissions is negligible.

Ironically the YouTube video in question was distributed by the Democrats in order to discredit Christy and is entitled “John Christy Climate Change Denial Testimony Highlights”. The words denial, and denier are used by Climate Change Believers in the same way that some Christians use the words sin and sinner. They are not intended to enlighten, they are intended to smear.

Another good smear word is charlatan (Charlatan: noun – a person falsely claiming to have a special knowledge or skill). Surely this is an accurate description of the climate modellers who purport to understand and predict climate. Nevertheless it is never used by climate change sceptics. Real scientists don’t resort to such tactics.

Reference:

Chapter 11 of The Fluid Catastrophe by John Reid

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The CO2 Hockey Stick

Willis Eshenbach’s graph of Mauna Loa and Ice Core CO2 data.

The above graph is certainly convincing evidence of a remarkably rapid increase of atmospheric CO2 since 1800. Note how there is a very good match between the most recent ice core data and the actual measurements made at Mount Mauna Loa in Hawaii. Note also that Mauna Loa measurements have been confirmed at other observatories around the world, such as Cape Grim in Tasmania. There can certainly be little doubt about the accuracy of the data after about 1950.

About ten years ago I saw the Law Dome data, now included in the above graph, which all but convinced me that something very serious and unprecedented was happening to CO2 concentrations in the atmosphere so I started looking further afield to find other data and other arguments which would either support or cast doubt on this view.

The data prior to about 1700 looks almost too good to be true because it is so very flat and smooth. Perhaps something else is going on. It has been pointed out (notably by Murray Salby, the guy who was fired by Macquarie University) that, maybe, over time, the CO2 trapped in bubbles in ice cores can diffuse between different layers, so smoothing any ups and down of its variation over time.

Then I found out about stomata at  (https://www.geocraft.com/WVFossils/stomata.html).

Recent stomata studies show that CO2 was variable and the average CO2 concentrations have been significantly higher during the Holocene Interglacial Period than are indicated by the ice core record.

Stomata are the tiny “mouths” in leaves through which a plant absorbs its “food”, CO2. When concentrations of CO2 are high the plant needs fewer stomata to obtain the required amount of CO2 and when low the opposite is the case. Hence fossil leaves provide an alternative proxy to ice cores for ancient CO2 concentrations. As we can see in the diagram, the two do not match. The stomata densities indicate that CO2 levels were both higher and more variable during the last 1000 years than indicated in the upper diagram. There are two conflicting stories. It’s a “he said, she said” situation.

A further piece of information is the Bomb Test Curve:

The Bomb Test Curve shows the injection and subsequent decay of radioactive CO2 in the atmosphere caused by the atomic bomb tests of the1960s (image: Hakanomono).

There is a mathematical description in TFC, Chapter 13. Suffice to say here that we can conclude that residence time of CO2 in the atmosphere is only 10 years and that less than 20 percent of recent increases in atmospheric CO2 are anthropogenic in origin, the rest comes out of the deep ocean in regions of upwelling. It follows that the ice core graph indicates that either there has been a dramatic recent change in deep ocean circulation or there is something wrong with the ice core proxy CO2 methodology and the stomata data is correct.

References:

https://www.geocraft.com/WVFossils/stomata.html

Reid, J. (2019) The Fluid Catastrophe, Cambridge Scholars Publishing, Newcastle upon Tyne.

Correct Conclusion, Wrong Argument

Recently an argument has been going around the sceptic community that CO2 does not trap heat because there is too little of it in the atmosphere. CO2 comprises only 400 parts per million of the atmosphere, that is only 0.04%. Only about 4 atoms in every 10,000 are absorbing heat so their effect must surely be negligible.

This argument is quite wrong because it ignores the radiation cross-section of CO2 which is huge in the infrared range, as it is for other tri-atomic molecules such as ozone (O3) and water vapour (H2O). Think of three balls (the atoms) connected by two springs (the chemical bonds). There are a large number of ways that these springy, bouncy things can vibrate and their frequencies of vibration are in the infrared range of wavelengths. They act like antennas sucking in radiation as it goes past and converting it to mechanical vibration (i.e. heat). By comparison the di-atomic molecules of N2 and O2 which make up the bulk of the atmosphere don’t vibrate in the infra-red because there are no vibrational modes to take up the energy. For infrared radiation the tri-atomic molecules look like soccer balls in a background of sand grains: not many of them absorb a lot of radiation.

The issue with CO2 is the opposite: there is so much CO2 in the atmosphere that the absorption band is already saturated; adding more CO2 makes very little difference. The climate modelers get around this problem of making CO2 the bogeyman with a gigantic fudge. It is called “water vapour positive feedback” whereby extra H2O is arbitrarily added to the model to do the heavy lifting when it comes to changes in radiation absorption.

Here are some valid arguments in refutation of the Climate Change meme:

  1. Met balloons measure the temperature gradient of the atmosphere all over the world many times a day. The observed temperature gradients fit a thermodynamic model. They do not fit a radiation transport model.
  2. The bomb test curve shows that CO2 in the atmosphere is in approximate equilibrium with the ocean. 98 percent of CO2 is in the deep ocean. It comes out of the ocean in regions of upwelling currents and is absorbed back again by diffusion. Of recent increases more than 80 percent are due to this upwelling and human activity less than 20 percent.  Since the beginning of the Industrial Revolution we have only contributed one percent of the total CO2 in the ocean-atmosphere system.
  3. Variations in upwelling currents cause variations in both atmospheric CO2 and global temperature over time. Some of these variations are most likely caused by changes in volcanic activity on the ocean floor. More than 80 percent of the world’s volcanoes lie beneath the ocean. These effects are unacknowledged by climate scientists and ignored in their models.
  4. Climate models have no predictive power. They don’t work.

Reference: Reid, J. (2019) The Fluid Catastrophe, Cambridge Scholars Publishing, Newcastle upon Tyne.

 

The North Atlantic “Cold Spot”.

NEWS | February 6, 2019. 2018 fourth warmest year in continued warming trend, according to NASA, NOAA

The latest scary map from NOAA and NASA showing the earth glowing red hot from Climate Change. You can click here to see it as a movie and read the blurb.

The trouble is the North Atlantic cooled considerably over this four year period. No reason is given for this weird behaviour. Perhaps there was a lack of CO2 in this vicinity in 2018, which is strange because weather patterns usually ensure atmospheric gases are well mixed.

There is another explanation: this part of the ocean was warmer in 2014 than in 2018.  Ocean temperature here must be highly variable  for reasons unrelated to CO2 concentration.

The World Ocean Circulation Experiment (WOCE), collected hydrographic data from the world’s oceans between 1990 and 1998. The following map shows the WOCE sections for the North Atlantic:

WOCE Hydrographic Sections of the North Atlantic (© 2011 International WOCE Office)

Section A25 from the tip of Greenland to Portugal crosses the cool region in the NASA-NOAA map. Here is a plot showing potential temperature along this section. (Potential temperature is measured temperature corrected for pressure. Black shows the ocean floor. It looks spiky because the horizontal scale is so contracted.)

Potential temperature along WOCE Section A25. © 2011 International WOCE Office

Salinity shows an even more confused picture:

Salinity along WOCE section A25. © 2011 International WOCE Office

Compared with most oceanographic sections these sections are poorly stratified particularly at the left-hand side, south of Greenland. The perturbations occur down to the ocean floor and near the Mid-Atlantic Ridge (the double black spike on the left) implying they are of volcanic, hydrothermal origin. The MAR is particularly active at its northern end.

The “cold spot” in the North Atlantic cannot be accounted for in terms of the greenhouse effect. It can be readily accounted for in terms of variable volcanic heating of the ocean. Why is this ignored by NOAA and NASA?

By the same argument the “hot spot” to the north of Greenland can be accounted for by more recent hydrothermal activity on the Gakkel Ridge. In both cases the temperature difference is 4 deg C – the difference between the temperature of ice formation and the temperature of the deep ocean. Volcanic heating does not itself cause the observed temperature variations. It acts indirectly by changing the pattern of circulation and intermittently bringing deep ocean water to the surface.

The Fallacy of Steady-State

The central idea of The Fluid Catastrophe (henceforth TFC) is that, in all but a few special cases, deterministic models do not provide a realistic picture of reality; stochastic models are more powerful. Determinism works well for the motions of the planets but not for fluid dynamics

A closely related idea is the idea of the steady-state whereby the equations describing quantities are assumed to be independent of time. The more sophisticated idea is that of stationarity whereby the statistics of a system are assumed independent of time; values of measured quantities may vary over time and it is only the statistics and model parameters which are assumed to be static. This is one step removed from steady-state; it is a higher level of abstraction.

We assume steady-state in order to come to grips with reality, in order to make reality conceivable and manageable. It is only ever a working hypothesis. We can never be sure that a system is steady-state but we can be sure when it isn’t. There is a natural tendency to assume that those processes which are long compared with a human lifetime are steady-state: wilderness, undisturbed ecosystems, ocean circulation. Events which disturb such systems are then sufficiently rare to be regarded as accidents or aberrations, outside the cosy delusion we have constructed for ourselves. It then follows that someone or something must be to blame: the gods, God, capitalism, humanity. Non-indigenous Australians seem to believe this of bushfires and talk of the “devastation” wrought by bushfires in wilderness areas. We could equally well talk of “renewal” or “regeneration” following such fires. Even qualified ecologists go along with this hand-wringing, while well aware that numerous native species could only have evolved in a regime of regular burning. This is the human lifetime fallacy.

Most people have an intuitive grasp of the Law of Large Numbers: that the average of a sample gets closer and closer to the true value as the sample size gets bigger.

But this is only true of the average! It is not true of the sum! 

The average converges only because the sum is divided by the number in the sample, N. The sum of a number of zero mean, random fluctuations becomes larger as N becomes larger. Its standard deviation is the the square root of N even though the mean tends to zero. The belief that the variance of the sum of random quantities tends to zero is the Law of Large Numbers fallacy.

For a physical system in which a large number of small rapid fluctuations are added, the outcome will not be a steady state, it will be a variation which is both larger and slower than that of the input fluctuations. This sort of slow variation is called red noise because there is more variance at lower frequencies compared to white noise. An example is the temperature of a body of water heated and cooled by radiation and evaporation in the course of a year (TFC pp 64-65).

Another example is ocean circulation. At short time scales we see the surface currents driven by wind and tides. At longer time scales we see the big warm core eddies which spin off promontories like the Cape of Good Hope and Cape Horn. At even longer time scales we see the great ocean gyres and ocean currents such as the Gulf Stream, the Kurashio and the Aghulas. It would be comforting to assume, because these large gyres are the sum of component smaller currents and eddies, that they are steady-state and not subject to variation over time. This would be wrong. It is an example of the human lifetime fallacy and the law of large numbers fallacy. Large scale ocean currents are not the average of smaller variations, they are more like their sum and most likely have a red-noise frequency spectrum with significant variability at low frequencies.

Ocean currents are not steady-state. Concerns about variations in the Gulf Stream are unwarranted.