Sunday, June 8, 2014
Compelling evidence CO2 does not cause significant climate change and the identity of what does are at

Mistakes made by the Consensus
(Updated 10/28/15, 10/21/16)
CO2 increase from 1800 to 2001 was 89.5 ppmv (parts per million by volume). The atmospheric carbon dioxide level has now (through September, 2016) increased since 2001 by 33.29 ppmv (an amount equal to 37.2% of the increase that took place from 1800 to 2001) (1800, 281.6 ppmv; 2001, 371.13 ppmv; Sept, 2016, 404.42 ppmv) while the average global temperature trend has been flat [1]. This is outside of the ‘limits’ asserted by the ‘Consensus’ of the Climate Science Community [2].

So how did the Consensus get it so wrong?

The scientists in the Consensus apparently don’t understand some of the science very well, stubbornly refuse to acknowledge some science or may not even be aware of some relevant engineering science.

Here are some of the issues:

1. Global Climate Models
Climate Scientists use huge mathematic models that are intended to simulate climate over the entire globe. The mathematic models are very computationally intensive and are run on powerful computers. These so-called Global Climate Models (GCMs) divide the atmosphere into about 100,000 or more contiguous blocks which may also be called elements. For example, the Hadley Center model named HadAM3 is a 73 by 96 grid with 19 levels for a total of 133,152 elements. HadGEM1 has four times as many. The number of elements is limited by the practical consideration of computer run time. The programs are somewhat compromised because they necessarily use strategies such as parameterization of some phenomena and also use algorithms to suppress numerical computational artifacts such as aliasing and computational instability.

The known laws of physics and some approximations are applied to calculate energy interchange between the elements. Once everything balances at a particular time, the program advances by a specific time interval and repeats the process. This works great if you know exactly where you started (initial conditions) and have perfectly determined what causes change. Neither of these is true for the GCMs.

To be true for initial conditions, all properties at every point in the atmosphere would need to be specified which is clearly impractical. Instead, properties must be interpolated and extrapolated from the comparatively few known measurements and then smeared over the elements. Wikipedia has an extensive discussion of climate models at . Caution is advised when consulting Wikipedia on controversial subjects because article content can be controlled by administrators and might exhibit their biases.

To perfectly determine how things change, requires exact application of the physical laws to each of the elements. Again this is impractical (e.g. some of the phenomena take place in less volume than an element) so some of the phenomena, such as convection and cloud behavior, are approximated using human-determined parameterization. One of the acknowledged sources of greatest uncertainty in GCMs is the parameterization of cloud behavior. The high sensitivity of average global temperature (AGT) to tiny cloud changes is readily demonstrated [10].

Climate Scientists are apparently undeterred by the inherent limitations of the climate models that they use. Inherent in this type of modeling (approximation of initial conditions and time-step progression with approximate application of physical laws) is that the longer the program runs, the greater the uncertainty in the results. Although the GCMs are pretty good at predicting weather for up to a few days they are useless for predicting climate for years. This has been demonstrated in the total failure of GCMs to predict the AGT trend since about 2001. [14]

Thus the so-called global climate models are effectively global weather models. It is woefully naïve to assume that all that is needed to turn a global weather model into a global climate model is to run it longer.

The GCMs were expanded in an attempt to account for the influence of oceans in Atmospheric/Oceanic Global Climate Models (AOGCM). However, these models have suffered from poor definition of initial conditions especially temperature distribution in the oceans and a paucity of attention to the various natural ocean oscillations. To add to the confusion, AOGCMs are sometimes called GCMs, short for General Circulation Models.

Both the GCMs and AOGCMs fail to incorporate thermalization or the rudimentary fact of the physical world that water has partial pressure irrespective of the presence of CO2.. Thermalization explains why CO2 has no significant effect on climate. As of September, 2016 there are more than 100 of these models.

2. Thermalization
An observed characteristic of gases is that significant absorption of electromagnetic radiation (EMR) takes place only at certain discreet wavelengths. Emission of EMR takes place only at these same discreet wavelengths. (Theory and extremely fine measurements have revealed that the absorption and emission ‘lines’ are actually narrow statistical distributions resulting from pressure broadening and other factors)

When a molecule of ghg absorbs a photon of EMR (EMR can be considered to be in packets called photons) it experiences a step increase in energy. If the molecule then bumps in to another molecule before it has emitted a photon, its energy changes to a lower level and the probability that it will emit another photon is greatly reduced. According to the kinetic theory of gases, molecules bouncing off each other causes pressure, temperature, viscosity and thermal conduction in the gas mixture.

When a photon is absorbed but not emitted, the energy of the absorbed photon has been thermalized which warms the atmosphere. The warmed air rises. The rising air is exploited by soaring birds and sailplanes. Air falls elsewhere, recognized by pilots and passengers as air pockets and micro-bursts. The common observation of the existence of thermalization is a greater temperature range night-to-day with lower absolute humidity.

Thermalized energy carries no identity of the molecule that absorbed the photon. That is, thermalized energy from water vapor, CO2, or any other ghg warms the atmosphere according to the energy in the absorbed photon, irrespective of the molecule that absorbed it.

Some gases are called greenhouse gases (ghg) because absorption and emission of EMR occur at wavelengths of significant terrestrial EMR. EMR absorption/emission for CO2 at very low total pressure is at 15 microns. At sea level, pressure broadening increases this to mostly within 14-16 microns. EMR from the planet is mostly in the range 6-100 microns. Thus CO2 can absorb photons in only a small portion of terrestrial EMR. [All EMR energy in a microwave oven appears as heat but the physical process (which involves liquids and solids) is entirely different from that described here for gases.]

By far the most important ghg is water vapor. In the wavelength range of significant terrestrial radiation, water vapor at approximately 15,000 ppmv has more than 400 absorption lines (absorption opportunities) per molecule in the wave length range 18-100 microns compared to only one at 15 microns for CO2. At low to medium altitude, some of the thermalized energy causes convection. The rest is reverse-thermalized to water vapor molecules which emit photons essentially at wavelengths that only other water vapor molecules can absorb. The tiny increase in absorption opportunities due to a 100 ppmv CO2 increase, about 1 in 60,000, contributes to the  reason CO2 has no significant effect on climate.

It should be apparent that a time interval must pass between absorption and emission by any molecule. If that time interval were zero there would be no evidence that the photon had been absorbed and no ghg effect. The amount of time that passes between absorption and emission is very short but it must be more than zero.

The average amount of time that passes between when a molecule of CO2 in the atmosphere absorbs the energy and momentum of a photon until it emits one (the relaxation time) is about 6 µsec (values from 6 to 10 µsec are reported) Heat is conducted in the atmosphere by elastic collisions between molecules. The average time between collisions of molecules in the atmosphere at sea level conditions is less than 0.0002 µsec [12]

Thus, at sea level conditions, it is at least 30,000 times more likely that a collision will occur (thermal conduction) than a photon will be emitted by CO2. The process of a molecule absorbing the energy in a photon and conducting the energy to other molecules is thermalization. Thermalized energy carries no identity of the molecule that absorbed it.

Reverse thermalization, where the warmed jostling molecules excite some molecules to emit a photon is almost entirely to water vapor molecules at sea level conditions. The reason is relaxation time of some water vapor molecule rotational emission lines is about 0.5 µsec compared to 6 µsec for CO2.

The fact that nitrogen and oxygen do not radiate at terrestrial wavelengths demonstrates that reverse-thermalization, back to the ghg, must occur at high altitudes. In reverse-thermalization the jostling from non-ghg molecules imparts energy to ghg molecules. The higher energy increases the probability that the ghg molecules can emit photons.

The population gradient of ghg molecules (declining with increased altitude) and increased molecule spacing at extremely high altitudes results in all absorbed EMR being radiated to space.

The TOA radiation distribution includes radiation from ghg (some that got excited by reverse-thermalization and some directly by radiation from other ghg or the surface) and some directly from the surface through the ‘window’ or between the absorption lines of ghg. TOA measured radiation profiles differ according to the underlying location and absolute humidity [13].

Clouds are another source of EMR escaping the planet. Approximately 66% of the planet is covered by clouds all the time. The liquid or solid water in clouds approximates ‘black body’ (Plank spectrum) subject to Stephan-Boltzmann (proportional to T4) radiation with an emissivity of approximately 0.5. Water vapor is greatly diminished above clouds so much of cloud radiation goes directly to space.

Failure to identify and account for thermalization is a major deficiency of the 1997 Kiehl & Trenberth chart which has been relied on heavily by the Intergovernmental Panel on Climate Change (IPCC). This chart is shown in the fourth IPCC report at AR4WG1, Chapter 1, page 96. A 2008 update to this chart can be seen at . It also fails to indicate thermalization. None of the IPCC reports (including the 5th) mention thermalization (sometimes spelled thermalisation).

The Kiehl and Trenberth (K & T) charts erroneously imply that all radiation, which was absorbed close to the ground and re-radiated, penetrates substantially to high altitude and also that all radiation from high altitude gets all the way to the ground. Both of these implications are misleading. With thermalization and convection, EMR flux initially declines logarithmically with distance from the emitting surface.

At intermediate altitudes the combination of thermalization, reverse-thermalization (effectively all to water vapor) and vertical convection results in a net effective thermalization of approximately 12%.

A rough analysis [3] using an improved Kiehl and Trenberth type graphic and assuming effective 12% thermalization produces the results shown in the following table.

The three assessments of energy flow are presented below; all are in units of watts/m2.

Symbol [3]
K & T 1997
K & T 2008 & 9
With thermalization
Incoming solar radiation (insolation)
Reflected solar radiation
Energy radiated from earth’s surface
Surface radiation absorbed by the atmosphere


Back radiation from absorbed radiation near surface
Absorbed IR that is thermalized

IR from surface directly to space
IR emitted by atmosphere to space
IR emitted from clouds to space
Energy transported to atmosphere via convection
Energy transported to atmosphere via latent heat
Solar radiation directly absorbed by atmosphere


Solar radiation directly absorbed by clouds and atmosphere

Back radiation from clouds that reaches the ground

Solar radiation absorbed by surface

At extremely high altitudes, reverse-thermalization to CO2 and ozone produces the spike centered at the characteristic absorption/emission lines that are observed in graphs of TOA radiation.

3. Feedback
A feature of GCM (and AOGCM) applications is feedback factor. In the phenomenon referred to as the ‘enhanced greenhouse effect’ increased temperature causes increased water vapor in the atmosphere which further increases temperature. In Feedback Control Theory as used by engineers, feedback factor relates to the ratio of temperature with feedback to temperature with no feedback. The result with positive feedback is a greater increase (or decrease) than would have occurred if there were no feedback. Feedback as used by Climate Scientists is defined differently.

Positive feedback is a part of the Global Warming Theory which posits that a small temperature increase from increased carbon dioxide is amplified by the increase in water vapor that the small temperature rise causes. The existence of life on this planet demonstrates that net feedback is less than forcing.

Proxy data from ice cores show temperature trend direction changes. Apparently some climate scientists do not fully understand Feedback Control Theory. It dictates that temperature trend direction changes are not possible if NET feedback from average global temperature is significantly positive. GCMs do not predict significant Global Warming unless feedback is assumed to be strongly positive.

Without human-caused global warming there can be no significant human-caused global climate change.

4. Safe Carbon Dioxide Level
Included in the erroneous scary stories that have been circulated (and not refuted by Climate Scientists) are concerns about health and also about fears of the atmospheric carbon dioxide level reaching a ‘tipping point’ leading to runaway warming. The federal standard for the allowable level of carbon dioxide in the air that we breathe is that it should not be more than 5000 parts per million by volume (ppmv). Another study, found using the Google search link corroborates this as a safe conservative level. Still another reference reports that performance of normal healthy males (e.g. in a submarine) is not degraded at levels up to 20,000 ppmv. Some greenhouses artificially increase the carbon dioxide level to about 1500 ppmv to enhance plant growth. The seasonally corrected atmospheric level in September 2016 was 404.42 ppmv [4].

Runaway warming at elevated atmospheric carbon dioxide levels is also refuted by the determination that during the late Ordovician period the planet plunged into and warmed up from the Andean-Saharan ice age when the atmospheric carbon dioxide level was over ten times the present [5].

5. Lack of Correlation
The complete lack of correlation between temperature and CO2 level for over 500 million years is evident in a graph available on the web [5]. Note also from this graph that, for nearly all of the past, the atmospheric carbon dioxide level has been higher, usually several times higher, than it is at present.

Many Climate Scientists have not noticed, ignored or bizarrely rationalized climate determinations from the past and even measurements made since the thermometer was invented. During the last and previous glaciations, atmospheric CO2 increase often lagged temperature increase by hundreds of years. CO2 decrease also often lagged temperature decrease by hundreds of years. The lag is apparent in data determined from ice cores. Graphs of the reported data are shown in a March, 2008 paper [6]. An event can not have been caused by another event that followed it.

As shown on the first graph in [6], average global temperatures for over a century have trended down, then up then down, then up then down, while average annual atmospheric CO2 levels have always risen since 1800.

Lack of correlation implies lack of causation. (Not proven because unidentified modulating factors might exist.)

6. Measured Data.
Thermometer measurements of average global temperature are reported as far back as 1850 by four agencies. Reported values are the differences between some fixed value, usually an average between predetermined dates, and the measured value. The differences are called anomalies. The actual temperature is the anomaly added to the fixed reference value. Numerical data and graphs of the average global temperature anomalies are widely available on the web.

The normalized average of four reporting agencies is graphed in Figure 2 of a paper made public 9/16/13 [7]. Billions of dollars have been wasted in failed attempts to write GCMs and train them to calculate the measured data for extended time periods.

Contrary to the ‘Consensus’ approach, an analysis was started with the measured data. An equation was derived using the first law of thermodynamics and some logic. A seminal discovery was that the time-integral of sunspot numbers, properly reduced by radiation from the planet, and modulated by an approximation of ocean cycles, resulted in a graph with a shape very similar to the observed temperature run-up trend that has been called Global Warming.

Analysis of the PDO and ENSO combined with effective thermal capacitance calculations showed that the energy stored in the oceans is approximately 20 times that stored in the atmosphere. This revealed that the oceans must be accounted for in any rational assessment. The up-trends and down-trends are each about 32 years long. The net effect of all up-trends and down-trends of all the ocean cycles are included in a factor called ESSTA, for Effective Sea Surface Temperature Anomaly, with 32-year-long trends and amplitude to be determined. The amplitude (peak to valley) of ESSTA has turned out to be approximately 0.36 C°.

Sunspots have been regularly recorded since 1610. In 2015 historical (V1) SSN were reevaluated in light of current perceptions and more sensitive instruments and are designated as V2. The V2 SSN data set is shown in Figure 8 of [11].

Using the first law of thermodynamics (conservation of energy), the sunspot number anomaly time-integral, ESSTA, atmospheric water vapor (quantified by Total Precipitable Water, TPW), and the change in terrestrial radiation due to AGT change, an equation was derived that calculates the AGT anomaly. Equation (1) in [11] calculates measured temperatures with an excellent Coefficient of Determination, R2, of 0.90 irrespective of whether the influence of atmospheric CO2 is included or not. The paper includes a possible extension of the calculations back to 1610. Also shown is comparison to 5-year moving average smoothed measurements which gives R2=0.98.

7. Sunspot number effect
Total Solar Irradiation, TSI, varies slightly with sunspot number. The amount of variation is tiny (only about 0.1%) which has caused many climate researchers, who have mistakenly only looked at TSI, to erroneously reject sunspots as having anything significant to do with earth’s climate.

Various papers have been written which indicate how the solar magnetic field associated with sunspots can influence climate on earth. Decreased sunspots are associated with decreased solar magnetic field which decreases the deflection of and therefore increases the flow of galactic cosmic rays on earth [8].

Henrik Svensmark, a Danish physicist, found that increased galactic cosmic rays caused increased low altitude (<3 km) clouds. An abstract of his 2000 paper is at . Marsden and Lingenfelter also report this in the summary of their 2003 paper where they make the statement “…solar activity increases…providing more shielding…less low-level cloud cover… increase surface air temperature.” [9]. This has been further corroborated by the CLOUD experiments at CERN.

These papers associated the increased low-level clouds with increased albedo leading to lower temperatures. Increased low clouds would also result in lower average cloud altitude and therefore higher average cloud temperature. Although clouds are commonly acknowledged to increase albedo, they also radiate energy to space so increasing their temperature increases radiation to space which would cause the planet to cool. Increased albedo reduces the energy received by the planet and increased radiation to space reduces the energy of the planet. Thus the effects work together to change the AGT of the planet.

Simple analyses indicate that either an increase of approximately 186 meters in average cloud altitude or a decrease of average albedo from 0.3 to the very slightly reduced value of 0.2928 would account for all of the 20th century increase in AGT of 0.74 °C [10].

The mechanism sequence for the influence of sunspots on earth’s AGT appears to be: Fewer sunspots; reduced solar magnetic shielding; increased galactic cosmic rays penetrating the atmosphere; increased low-level clouds. Increased low-level clouds result in increased albedo and lower average cloud altitude; higher average cloud temperature; increased cloud-to-space radiation. Increased albedo and higher average cloud temperature both cause planet cooling. The opposite, more sunspots, produces higher AGT. TSI is complementary but is a much smaller contributor.

Others have looked at just amplitude or just time factors for sunspots and got poor correlations with AGT. The good correlation comes by combining the two, which is what the time-integral does. Note that a low but broad solar cycle may have just as much cumulative influence on AGT as a high but brief one. Both magnitude and duration are accounted for by using the time-integral of sunspot numbers.

The sunspot number anomaly is defined as the difference between the sunspot number in a specific year and an average sunspot number for several years. Because AGT has not changed much over the millennia, it is clear there must be an ‘average’ SSN above which AGT increases and below which AGT decreases. For V2 SSN, the averae SSN appears to be approximately 60.

9. Marsden & Lingenfelter 2003, Journal of the Atmospheric Sciences 60: 626-636
12. Mean time between molecule collisions

13. Barrett, ‘Greenhouse molecules, their spectra and function in the atmosphere’, Energy & Environment, Vol. 16, No. 6, 2005.  
14. GCM vs measured thru 2015