## B. How is a Projection Formula Generated?

The easiest way to find the formula used by the IPCC would be to look in the Assessment Report that displayed the data.  But, no such formula, analysis, or equations were presented or disclosed.  The Assessment reports are silent on the identities of variables considered other than temperature and CO2.

Another way to generate a projection formula is to look at observational data.  There are published records showing temperatures and carbon dioxide concentrations going back 570 million years.  That data was plotted and is shown in Quorvita’s Figure 2. The Historical Observations are shown in the blue curve.  The R squared value of 33% is extremely poor illustrating many missing major variables.  It indicates that CO2 is not a significant factor, if at all.  To illustrate what a low R squared value means the following example is provided.  A plot of the win record of the top 12 baseball teams (Yankees to Angles) verses the same CO2 historical observations and using a logarithmic equation yielded an R squared of 54%.   Although that percent (54%) was better than what is shown in Figure 2 (33%), both indicate major missing variables.

There are many, many variables that must be considered to understand historical temperature fluctuations and historical CO2 content fluctuations.  Trying to connect CO2 as the main cause or even a cause (baseball example) is far too simplistic to be credible.

However, the above Figure indicates that the world is not in a run-away environment.  A run-away environment would show a sharply accelerating temperature for each increase in CO2 content.  The curve would become almost vertical at the right hand side.  But the opposite is shown.  The curve becomes flatter and flatter.  This indicates a self-regulating environment.  That is, as the CO2 continues to rise, the temperature change becomes less and less.

The Temperature and CO2 data going back 570 million years are based on proxies from ancient sea beds and ice cores.  Proxies are less reliable than actual temperature measurements—assuming that proper temperature measurement methods are used.  As shown in Question 2 Item B, there are significant errors in the current handling of the temperature data skewing the actual temperature anomaly by 26% higher than actual.

Figure 3 is a plot taken at Mauna Loa of the ocean temperature and CO2 concentration between 1980 and 2014.  This is far too short of a time span.  At least one thousand years would be minimal and at least 1 million years would yield more accurate results.  There are many processes that occur over long time periods and using a short time period is unreliable. The above plot shows a 4.03 slope for the curve with an R squared of 73.86%.  The low R squared value indicates that there are many major variables not taken into account.  The slope on the IPCC formula was about 50% higher at 5.99, indicating that the IPCC formula is not supported by either the long term Historical Observations or the short-term MLO data.  In fact, both the Historical Observations and the MLO data suggest that CO2 by itself may not be a material factor as it relates to temperature.

It is difficult to prove that the undisclosed IPCC formula represents an accurate projection of future temperatures and CO2 concentrations without waiting 200 years and comparing the projection to the actual measurements.  However, it is easier to disprove something than to prove it.  For example the IPCC formula excludes many obvious variables.  Some of these variables include orbital deviations.  Orbital deviations are what causes ice ages.  Another variable is water vapor.  Water vapor constitutes 99 percent of all greenhouse gases.  To exclude water vapor in the equation is without credible justification. Biology is probably the largest variable that controls temperature and CO2.  There is no biology component in the equation.  Albedo, or reflections, is a major component of what regulates temperature.  This is discussed in detail at Question X item X.  As shown the standard deviation in variations in albedo is 4.4 times larger than the effect of the greenhouse gases.  Albedo is not in the equation.  There are so many known variables that appears to be excluded from consideration that it renders the IPCC projections highly suspect.