NOAA, NASA manipulates data to support the political agenda of the myth of manmade climate change otherwise known as Anthropogenic Climate change. And to keep their jobs the employees in the various agencies of the federal government have all been infected with the desire to keep their jobs i.e. publish data, tables and charts that purport to show that we are in the hottest year ever and that if we don’t tax carbon immediately that we are all going to die. The national media dutifully promotes this cause and those that believe in the cause of more taxes attack anyone that disputes the narrative calling them names such as a Flat Earther or Non Believer and other nastier names as suits them at the time. However there is a building problem in that the citizens of the country don’t see what the propaganda claims to be happening and as the disparity gets larger and larger every year the government and their minions, the national media, get more and more desperate.

Over the past several years I have been downloading a table of global temperatures that NASA publishes each month to use in my research. This table is identified as the Land Ocean Temperature Index (LOTI) which consists of a number which is generated by a very complex computer program. To calculate this table NASA first set an arbitrary global temperature by calculating a base global temperature from period from1951 to 1980 of 14.0 degrees Celsius (57.2 degrees Fahrenheit). Then they determine an anomaly by taking the temperature that they calculated subtracting 14.0 from it then they divide multiply the result by 100. This than gives a plus or minus value from base 0.0 which represents 14.0 degrees Celsius (C). This creates a whole number which is apparently easier for the scientists to work with. Example 14.5 would be an anomaly of 50 (.5 * 100). The only problem with this method is that the base is strictly arbitrary and can be any number one wants to use; but that doesn’t matter for what we’re going to talk about here.

As the federal agencies try to support what the Obama administration wants to promote, they have had to resort to data manipulation that has become so blatant that even non technical people are able to see that something is very wrong. One of the tricks that these agencies use is to change history. They do this in how they calculate their data and in the form of what they show, for example we have the following Chart of anomalies from three different plots of the LOTI monthly tables for the indicated years. The first is from December 1998 (blue line), the second from October 2009 (green line) and the third from December 2014 (red line) which is the lasted one available at the time this paper was written.

This plot was generated by break each indicated year into a ten year blocks of values and then creating an average for each block. By doing this we take out large changes in the monthly numbers; for example for the month of January 1980 from the LOTI issued in December 1998 the value was 30 and the LOTI value for the same month, January 1980, was 24 on the December 2014 report, which one was right? To my way of thinking some variances could be expected but they would cancel out with looking at blocks of numbers; this is not the case here. There is one other issue of note and that is when looking at this subject for the first time around 2005 the LOTI table went back to January 1980. Unfortunately at the time the methodology used by NASA was not understood by me, at the time, and the earlier tables were not saved. Each month as new data was published the current value was added to the table that had been developed. It never occurred to me that the published data was itself a variable. Why would numbers be changed constantly for if they are, of what value are they? Now that we understand how the numbers were derived lets analyze the Chart.

At this scale all three plot should be one on top the other, which they are not. Next it’s curious as to why NASA stopped publishing the anomalies prior to 1980. Also we can see that the plots prior to 1950 have major swings in them; and that the plots after 1980 do as well. Lastly why would the base temperature be calculated using the temperatures from 1951 to 1980 since there is a clear and large upward trend to the data?

The first things we’ll look at are the Blue and Green plots. Which follow each other reasonably with the only difference being dropping the numbers prior to 1980. What comes to mind is that those promoting anthropogenic climate changes did not want to show a decline in temperatures while carbon emissions were growing from 1860 through 1890. It would be interesting to see when this change was made; it wouldn’t be a surprise if it was in the period when James E. Hansen’s was put in charge of the Goddard Institute for Space Studies (GISS) section of NASA.

Next, what happened before 2014 that made such a large change in the red plot? Could it be that if we look at the plot from the periods from 1910 to 2000 there would be close to a full degree upward movement in temperature? Actually that change occurred sometime between October 2011and September 2012 but LOTI tables for that period have not been found yet so it is somewhere in those eleven months. If we go back to 1860 values that almost one degree increase drops by 1/3, is this intentional?

Lastly we look at the period from 2000 to the present. Interestingly it shows that the plot for October 2009 is higher than the plot for December 2014. The period from January 2000 to December 2009 was 62 on the October 2010 report. The same period was 55 on the December 2014 report which is enough to make 2014 hotter. Was this done so the Obama administration could say that 2014 was the hottest years ever?

For reference the following table is what was used to make the plot.

The analysis and plots shown here are based on the following: first NASA-GISS temperature anomalies (converted to degrees Celsius so non-scientists will understand the plots) as shown in their table LOTI, second James E. Hansen’s Scenario B data, which is the very core of the IPCC Global Climate models (GCM’s) and which was based on a CO2 sensitivity value of 3.0O Celsius, lastly, a plot based on an alternative climate model designated ‘PCM’ and based on a sensitively value of .65O Celsius.

The next three paragraphs have been added to this monthly temperature plot to clear up confusion regarding the methods used in this work. That confusion is my fault for not properly explaining what is shown here.

An explanation of the alternative model designated PCM is in order since many have interpreted this PCM model as a statistical least squares projection of some kind and nothing could be further from the truth. A decade ago when I started this work the first thing I did was look at geological temperature changes since it is well know that the climate is not a constant; I learned that in my undergrad climatology course in 1964. One quickly finds that there is a clear movement in global temperatures with a 1,000 some year cycle going back at least 3,000 to 4,000 years. There are also 60 to 70 year cycles in the Pacific and the Atlantic oceans that are well documented. We also know that there are greenhouse gases such as Carbon Dioxide and the National Academy of Sciences (NAS) estimated that Carbon Dioxide had a doubling rate of 3.0O Celsius plus or minus 1.5O Celsius in 1979

The IPCC still uses the NAS 3.0O Celsius as the sensitivity value of Carbon Dioxide and a number in that range is required to make the IPCC GCM’s work. The problem with using this value is it leaves no room for other factors and hence the need of the infamous Hockey Stick plots of the IPCC from Mann, Bradley & Hughes in 1999. The PCM model is based on a much lower value for Carbon Dioxide consistent with current research which places the value between 0.65O and 1.5O Celsius per doubling of Carbon Dioxide. If the long and short movement in temperatures and a lower value for Carbon Dioxide are properly analyzed and combined a plot that matched historical and current NASA temperature estimates very well can be constructed. This is not curve fitting.

The PCM model is such a construct and it is not based on statistical analyses of raw data. It is based on creating curves that match observations (which is real science) and those observations appear to be related to the movement of water in the world’s oceans. The movements of ocean currents is well documented in the literature all that was done here was properly combine the separate variables into one curve which had not been previously done. Since this combined curve is an excellent predictor of global temperatures unlike the IPCC GCM’s it appears to reflect reality a bit better than the convoluted IPCC GCM’s which after the past 19 years of no statistical warming have been shown to be in error.

Now, continuing from the first paragraph, to smooth out monthly variations a 12 month running average is used in all the plots. This information will be shown in four tables and updated each month as the new data comes in about the middle of the month. Since no model or simulation that cannot reasonably predict that which it was design to do is worth anything the information presented here definitively proves that NASA, NOAA and the IPCC just don’t have a clue.

The first plot, UL is a plot of the NASA temperature anomaly converted to degrees Celsius and shown in red with a black trend line added. There has been a very clear reversal in the upward movement of global temperatures since about 2001 and neither the UN IPCC nor anyone else has an explanation for this 13 years later. Since CO2 has continued to increase at what could be argued an increasing rate this raises serious doubts about the logic programmed into all the IPCC global climate models.

The next plot UR, also in red, shows the IPCC estimates of what the Global temperature should be, based on Hansen’s Scenario B, with the NASA actual temperatures’ subtracted from them. Therefore this plot represents a deviation from what the Climate “believers” KNOW what the temperature should be; with a positive value indicating the IPCC values are higher than actual and a negative value indicating the IPCC values are lower than actual, as measured by NASA. A black trend line is added and we can clearly see that the deviation from expected is increasing at an increasing rate. This makes sense since the IPCC models project increased temperatures based primarily on the increasing level of CO2 in the earth’s atmosphere. Unfortunately, for them, the actual temperatures from NASA are trending down (even as they try to hide the down ward movement with data manipulation) since other factors are in play, therefore each year the gap between them widens. Since we have 13 years of observations’ showing this pattern it becomes hard to justify a continuing belief in the IPCC climate models, there is obviously something very wrong here.

The next plot LL shown in blue is based on the equations in the PCM climate model described in previous papers and posts here and since it is generated by “equations” a trend line is not needed. As can be seen the PCM, LL, and the NASA, UL, trend plots are very similar the reason being that in the PCM model there is a 68.2 year cycle that moves the trend line up and then down a total of .30O Celsius (currently negative .0070O Celsius per year); and we are now in the downward portion of that trend which will continue until around 2035. This short cycle is clearly observed in the raw NASA data in the LOTI table going back to 1868. Then there is a long trend, 1052.6 years with an up and down of 1.36O Celsius (currently plus .0029O Celsius per year) also observed in the NASA data. Lastly there is CO2 adding about .005O Celsius per year so they basically wash out which matches the current holding pattern we are experiencing. However within a few years the increasing downward trend of the short cycle will overpower the other two and we will see drop of about .002O Celsius per year and that will be increasing until till around 2025 or so. After about 2035 the short cycle will have bottomed and turn up and all three will be on the upswing again. These are all round numbers shown here as representative values.

The last plot LR in blue uses the same logic as used in the UR plot, here we use the PCM estimates of what the Global temperature should be with the NASA actual temperatures’ subtracted from them. A positive value indicates the PCM values are higher than actual and a negative value indicates the PCM values are lower than expected. A black trend line was added and it clearly shows that the PCM model is tracking the NASA actual values very closely. In, fact since 1970 the PCM model has rarely been off by more than +/- .1 degrees Celsius and has an average trend of almost zero error, while the IPCC models are erratic and are now approaching an error rate of +.5O above expected.

In summary, the IPCC models were designed before a true picture of the world’s climate was understood. During the 1980’s and 1990’s CO2 levels were going up and the world temperature was also going up so there appeared to be correlation and causation. The mistake that was made was looking at only a ~20 year period when the real variations in climate move in much longer cycles. Those other cycles can be observed in the NASA data but they were ignored for some reason. By ignoring those trends and focusing only on CO2 the models will be unable to correctly plot global temperatures until they are fixed.

Lastly the next Chart shows what a plot of the PCM model would look like from the year 1000 to the year 2200. The plot matches reasonably well with history and fits the current NASA-GISS table LOTI date very closely. Again this plot is a combination of three factors a long cycle probably in ocean currents, a short cycle probably related more to atmospheric effect from the ocean and a factor for CO2 using a much smaller sensitivity value than the IPCC. I understand that this model is not based on physics but it is also not curve fitting. It’s based on observed reoccurring patterns in the climate. These patterns can be modeled and when they are you get a plot that works better than the IPCC’s GCM. If the conditions that create these patterns do not change and CO2 continues to increase to 800 ppm or even 1000 ppm than this model will work into the foreseeable future. Two hundred years from now global temperatures will peak at around 15.5 to 15.7 degrees C and then will be on the downside of the long cycle for the next 500 years. The overall effect of CO2 reaching levels of 1000 ppm or higher will be between 1.0 and 1.5 degrees C which is about the same as that of the long cycle.

Carbon Dioxide is not capable of doing what Hansen and Gore claim!

The purpose of this post is to make people aware of the errors inherent in the IPCC models so that they can be corrected.

Sir Karl Raimund Popper (28 July 1902 – 17 September 1994) was an Austrian and British philosopher and a professor at the London School of Economics. He is considered one of the most influential philosophers of science of the 20th century, and he also wrote extensively on social and political philosophy. The following quotes of his apply to this subject.

If we are uncritical we shall always find what we want: we shall look for, and find, confirmations, and we shall look away from, and not see, whatever might be dangerous to our pet theories.

Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve.

… (S)cience is one of the very few human activities — perhaps the only one — in which errors are systematically criticized and fairly often, in time, corrected