NASA publishes values representing the global surface temperature of the planet supposedly based on actual measurements processed in a complex algorithm they call homogenization. The resulting values are published each month in a table called the Land Ocean Temperature Index (LOTI) which runs from January 1880 to the current month, May in this case. The process they use is explained on their web site for those that are interested. However the values shown in their work seem to show very large temperature swings on a month to month basis and that did not seem reasonable to me, given this was Global temperatures. This prompted me to do a review of the process in June 2015 and that led to a previous draft paper which was modified to create this finished work.

A small sample from NASA’s table is provided below running from January 2001 to May 2015. A good example of this large swing in values can be found in the value shown in February 2014 of 44 compared to March 2014 of 71 (both shown in red) a difference of 27 anomalies, a NASA measure of temperatures in hundredths of a degree Celsius, represents a lot of energy on a global scale.

What we are going to do now is reverse engineer the NASA Temperature values in the full LOTI table and then calculate the energy flows required to make those changes. If the “required” energy flows are not reasonable, then the NASA temperatures are not reasonable. They must be in synchronization with each other as energy can neither be created nor destroyed. The first step was to place all 1925 LOTI values in a spreadsheet and then turn the NASA anomalies (a deviation from a base of 14.0 degrees Celsius) back into temperatures by dividing by 100 then adding that value back to the base 14.0 degrees Celsius and lastly adding that result to 273.15 to convert to degrees Kelvin. Kelvin must be used to calculate total heat when working on these kinds of projects.

Next we needed to calculate the total heat value of the NASA temperatures and their changes and so from Wikipedia we find that the Earth’s dry atmosphere is 5.1352E+18 kg and the water in the atmosphere is 1.27E+16 kg for a total of 5.1479E+18 kg. From these values we can calculate that water is on average .247% of the atmosphere. We also find that on Wikipedia the specific heat of the Earth’s atmosphere is 1006 Joules per degree Kelvin (J/kg/K) without water and so we need to add 4.6 J/kg/K for water and 9.8 J/kg/K for latent heat to the 1006 J/kg/K giving us a total of 1020.4 J/kg/K for the earth’s atmosphere with .0247% water at standard air.

There is one last step since the NASA values are “surface” temperatures, we need an adjustment for altitude cooling if we are looking for the total energy in the atmosphere. To accomplish this we’ll subtract 28.5 degrees Celsius making the answer the theoretical temperature at 5 km above sea level which is about where 50% of the atmosphere is above 5 km and 50% below; so this makes for a reasonable estimate for calculating total energy. Using this logic we subtract the 28.5 degrees Celsius from the NASA LOTI values that we converted to degree Celsius, which are surface values which then gives a ballpark value to calculate the total heat in the atmosphere.

With the monthly NASA temperatures in a spreadsheet it was only a few hours work to set up the equations and plot a few charts. We calculated the heat value of each month’s anomaly for example for January 1880 the value was 1.3572E+24 Joules and for June 2015 the value was 1.36266E+24 Joules. Those values are a result of energy coming in from the sun minus what leaves the planet as infrared energy assuming no large change in the temperature of the land or oceans. To my knowledge these kinds of temperature changes (energy flows) have not been observed on the surface of the planet.

This review shows that the magnitude of the “required” energy flows is not reasonable indicating to me that the NASA temperatures is not reasonable as can be seen in Chart 1 on the next page. This shows two plots, the monthly change in the NASA anomalies in blue (required energy out) and the sun’s input in red (energy in). The sun’s input is adjusted for the orbital distance to the sun and the number of days in the month which is required to match the time periods shown in the NASA LOTI table. Since the sun is the energy input, the NASA temperatures minus the input must equal the input with the opposite sign, or negative. In other words, the sum of the two must be zero.

, David Pristash

It’s clear when looking at Chart 1 that there have to be extremely large monthly energy flows involved here if the NASA numbers are actually valid. To put this in perspective three, lines were added to Chart 1, as shown in Chart 2. These lines are for the incoming solar radiation using 1414.44 Wm² for solar radiation at aphelion (January) and 1322.97 Wm² for solar radiation at perihelion (July) in the earth’s orbit using the following albedo percentages; 20.0% dark red plot, 30.0% (Actual) red plot and 40.0% a yellow plot. The red plot is also shown on Chart 1. We also changed the time frame from 1880 to the present to 2000 to the present so that more detail could be seen when making Chart 2.

The choppy lines in the dark red, red and yellow Sun radiation plots are a result of using monthly values and the months don’t always have the name number of days. The purpose of showing these three radiation plots from the sun is to show that large changes in the planets albedo cannot account for the large energy swings and so the large changes in the NASA data such as shown here just don’t happen. That means that even these large albedo changes cannot account for the large required movements in energy indicated by NASA’s numbers shown in their table LOTI, the actual smaller albedo changes we experience surely can’t.

The blue plot for the NASA temperatures is actually the “required” energy out flow to balance the suns energy inflow. Given the process that NASA uses to determine global temperatures it would be expect that there would be some variations, but surely not of the magnitude shown in this chart.

NOAA and NASA have spend a lot of time and resources developing complex systems with the intent to show how “current’ temperatures were being driven up by the level of greenhouse gasses in the atmosphere caused by the burning of fossil fuels. This was called anthropogenic climate change meaning climate change caused by man. These apparent upward global temperature changes in the 1980’s and 1990’s were assumed by politicians to be dangerous and the scientific community given the task of showing the dangers to the planet of increasing temperatures. Although there was some real scientific validity to the man made climate change movement a true cause and effect review of the concept was never made and money poured in to “prove’ the concept.

Had a true review of the apparent problem been done first it would have been obvious that there were other factors involved besides greenhouse gases the most obvious was the well documented thousand year cycle of warm and cold periods going back several thousand years. The most recent of these cycles ended around 1650 during the coldest part of what is called the Little Ice Age. Assuming the thousand year cycle is valid that means that the global temperature would be ascending for five hundred years peaking around 2150. Based on this principle of multiple reasons for the apparent climate change, a climate model was then developed that fit the historic patterns that includes the increases in greenhouse gases. This model is called a pattern model and designated the PCM and shown next.

The next Chart 1a was developed exactly the same way as the NASA Chart 1 was except we used the temperatures generated by the PCM model as shown in the previous PCM chart instead of those developed by NASA in their computer system. We can clearly see in this Chart 1a that this PCM model generates a plot that very closely matches the suns input but is negative which it must be to keep the planet in thermal balance.

The next Chart 2a is based on the same principle as that shown for the NASA data in Chart 2 looking at 2000 to the present for more detail and we can see that the sun’s is exactly balanced by the energy leaving the planet as it must be when we use the PCM model to generate the temperatures. The model was developed in 2007 and this review used the values calculated by the PCM model.

Further from a total energy, heat, perspective the current increase in global temperatures of just over plus 1 degree Celsius from 1880 is less than 4 tenths of a percent change in the planets heat content. Even 2 degrees Celsius as predicted by the PCM model would be less than 6 tens of a percent change in the planets heat content so making claims of utter disaster for such small amounts of a heat increase is really stretching the point especially since the planet has reached temperatures beyond where we are now many times in the distant past; we are still just barely out of the last ice age after all.

The point to this analysis is to show that whatever the method used to analyze global temperatures, the in’s and out’s must balance. Clearly the NASA-GISS table LOTI data is not valid for the monthly temperature swings exceed what would be possible in the real world. Maybe if NASA would concentrate on developing real systems and models instead of doing the bidding of politicians their work might actually be valid.

This paper contains original research on the energy balance of the climate (weather) of the planet. A more sophisticated analysis could possibly be done showing what the effect of the1 to 2 degree Celsius increase in global temperatures that has accrued since the end of the little ice age in ~1650 would look like; maybe a 3D chart would work giving another dimension to work with. The energy balance would still be there but the in’s and out’s would have a pattern similar to what is shown in the chart of the PCM model and trending upward indicated that there is an increase in temperature

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 3.0^O Celsius, lastly, a plot based on an alternative climate model designated ‘PCM’ and based on a sensitively value of 0.65^O Celsius.

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. 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 known that the climate is not a constant; I learned that in my undergrad geology and climatology courses in 1964.

The following observations give a starting point to any serious study. First, 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; probably because of the apsidal precession of about 21,000 years for a complete cycle. However about every 10,000 years the seasons are reversed making the winter colder and the summer warmer in the northern hemisphere. 10,000 years from now the seasons will be reversed. Secondly, there are also 60 to 70 year cycles in the Pacific and the Atlantic oceans that are well documented. Lastly we also know that there are greenhouse gases such as carbon dioxide. The National Academy of Sciences (NAS) estimated that carbon dioxide had a doubling rate of 3.0^O Celsius plus or minus 1.5^O Celsius in 1979.

The core problem with the current climate change theory is that the IPCC still uses the NAS 3.0^O 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. This places the value between 0.65^O and 1.5^O 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 (non manipulated) 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 are 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, to my knowledge. 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, to smooth out highly erratic 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 0.30^O Celsius (currently negative .0070^O 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 1.36^O Celsius (currently plus .0029^O Celsius per year) also observed in the NASA data. Lastly, there is CO₂ adding about .005^O 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 .002^O 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 +/- 0.1 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 +0.5^O above expected.

Note: Since I first started posting this monthly analysis a year and a half ago NOAA and NASA were directed make the global temperatures fit the political narrative that the planet was over heating and something drastic need to be done right now. The problem was as shown in this analysis the “real” world temperatures were not at the level that the IPCC GCM’s said they should be. Major adjustments to the data have been made that give the illusion that temperatures are going up even though they are not. However, as this analysis shows even with the manipulation that has destroyed all credibility from NOAA and NASA they cannot get the global temperatures even close to what their false theory claims they should be.

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 2300. The plot matches reasonably well with history and fits the current NASA-GISS table LOTI date very closely, despite homogenization. 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 any of the IPCC’s GCM’s. 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. 150 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 even 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.

The Obama administration’s “need” for a binding UN climate treaty with mandated CO₂ reductions in Europe and America means there will be such a resolution presented at the COP12 conference in Paris in December. To support this NASA will be forced to show ever increasing global temperatures for the rest of 2015 that will make less and less sense based on observations and satellite data which will all be dismissed or ignored.

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 for 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.

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.
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 known that the climate is not a constant; I learned that in my undergrad geology and climatology courses in 1964.

The following observations give a starting point to any serious study. One 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; probably because of the apsidal precession of about 21,000 years for a complete cycle. However about every 10,000 years the seasons are reversed making the winter colder and the summer warmer (northern hemisphere) 10,000 years from now the seasons will be reversed. Two there are also 60 to 70 year cycles in the Pacific and the Atlantic oceans that are well documented. Lastly 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 core problem with the current climate change theory is that 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 (non manipulated) 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, to my knowledge. 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, to smooth out highly erratic 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 .30^O Celsius (currently negative .0070^O 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 1.36^O Celsius (currently plus .0029^O Celsius per year) also observed in the NASA data. Lastly there is CO2 adding about .005^O 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 .002^O 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 +.5^O above expected.

Note: Since I first started posting this monthly analysis a year and a half ago NOAA and NASA were directed make the global temperatures fit the political narrative that the planet was over heating and something drastic need to be done right now. The problem was as shown in this analysis the “real” world temperatures were not at the level that the IPCC GCM’s said they should be. Major adjustments to the data have been made that give the illusion that temperatures are going up even though they are not. However as this analysis shows even with the manipulation that has destroyed all credibility from NOAA and NASA they cannot get the global temperatures even close to what their false theory claims they should be.

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 2300. The plot matches reasonably well with history and fits the current NASA-GISS table LOTI date very closely, despite homogenization. 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 any of the IPCC’s GCM’s. 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. One hundred fifty 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 even 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.

The Obama administration’s “Need” for a binding UN climate treaty with mandated CO₂ reductions in Europe and America means there will be such a resolution presented at the COP12 conference in Paris in December. To support this NASA will be forced to show ever increasing global temperatures for the rest of 2015 that will make less and less sense based on observations and satellite data which will all be dismissed or ignored.

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

Something has been bothering me about the method that NASA-GISS (NASA) determines global temperatures and I don’t mean the more and more obvious data manipulation which we all know is there. NASA publishes values representing the global surface temperature of the planet supposedly based on actual measurements processed in a complex algorithm. The process is explained on their web site for those that are interested. The problem I saw in their data was the magnitude of swings in their numbers on a month to month basis; at a local level yes, of course, but on a global level the changes would have to be very gradual because of the extremely large numbers involved in the energy content of the Earth’s atmosphere and further there are natural atmospheric and oceanic energy flows that stabilize the planets temperature.

What we are going to do here is reverse engineering we’ll start with the NASA temperature and then calculate the energy flows required to make those changes. If the “Required” energy flows are not reasonable then the NASA temperatures are not reasonable. They must be in synchronization with each other as energy can neither be created nor destroyed.

So to start I decided to try and calculate the heat value of the NASA temperatures and their changes and so from Wikipedia we find that the dry atmosphere is 5.1352E+18 kg and the water is 1.27E+16 kg for a total of 5.1479E+18 kg. From these values we can calculate that water is on average .247% of the atmosphere. We also find that 1006 Joules per degree Kelvin (J/kg/K) is the specific heat value of the Earth’s atmosphere without water and so we need to add 4.6 J/kg/K for water and 9.8 J/kg/K for latent heat to the 1006 J/kg/K making a total of 1020.4 J/kg/K for the earth’s atmosphere with .0247% water at standard air.

The next step was to take the most current (at the time this was written) NASA global temperatures values from their Land Ocean Temperature Index (LOTI) which runs from January 1880 to June 2015 and place all 1925 values in a spreadsheet. To calculate the heat value of the atmosphere we need to turn the NASA anomalies (a deviation from a base of 14.0 degrees Celsius) into temperatures by dividing by 100 and then adding that value to the base 14.0 degrees Celsius and lastly add that result to 273.15 to convert to degrees Kelvin.

With that completed we need one last step since the NASA values are “surface” temperatures, we need an adjustment for altitude cooling if we are looking for the total energy in the atmosphere. To accomplish this we’ll subtract 28.5 degrees Celsius making the answer the theoretical temperature at 5 km above sea level which is about where 50% of the atmosphere is above 5 km and 50% below; so this makes for a reasonable estimate for calculating total energy. Actually it’s probably a low estimate because of the constant atmospheric temperature above 11km and most of the water is in the lower half.

With all the monthly NASA temperatures in a column it was only a few hours work to set up the equations and plot a few charts. We calculated the heat value of each month’s anomaly for example for January 1880 the value was 1.3572E+24 Joules and for June 2015 the value was 1.36266E+24 Joules. Those values are a result of energy coming in from the sun minus what leaves the planet as infrared energy assuming no large change in the temperature of the land or oceans. To my knowledge these kinds of temperature changes (energy flows) have not been observed on the surface of the planet.

Chart 1 shows two plots the monthly change in the NASA anomalies in red and the sun’s input in blue. The sun’s input is adjusted for the orbital distance to the sun and the number of days in the month. There are 1625 values in the LOTI table so because of the large number of values the Chart line width was set to zero to make it readable and the scale set to mega joules.

It’s clear when looking at Chart 1 that there have to be extremely large monthly energy flows involved here if the NASA numbers are actually valid. To put this in perspective three lines were added to Chart 1 but also running only from 2000 to the present so that more detail could be seen making Chart 2. These lines are for the incoming solar using 1414.44 Wm² for solar radiation at aphelion (January) and 1322.97 Wm² for solar radiation at perihelion (July) in the earth’s orbit using the following albedo percentages 20.0% orange plot, 30.0% (Actual) blue plot and 40.0% dark blue plot. The blue plot is also shown on Chart 1.

These values were based on the cross sectional area of the planet adjusted by dividing by 4 which compensates for the spherical earth so the energy is spread over a larger large than the cross sectional area. Obviously the Wm² had to be converted to Joules and we used 84600 seconds per day for the conversion since we were looking monthly changes. The large number of values on Chart 1 makes the variance hard to see; but on Chart 2 you can see the annual swings. The choppy lines in the Sun radiation plots are a result of using monthly values and the months don’t always have the name number of days. The purpose of the sun’s radiation plots is to show that small changes it the planets albedo cannot account for the large energy swings.

The next Chart 3 is made using the same data as that used in Charts 1 and 2 but this time we calculate a percentage change in heat month to month instead of Joules. It appears that there is a consistent monthly variance of +/- .05% which may seem small but that represents about +/- 6.25E+13 Mega Joules of energy moving around on a monthly basis, so where does that energy come from or go to?

Chart 4, is the same as Chart 3 except again we look at 2000 to the present just as we did with Chart 2. We can see that there are energy swings month to month of well over 1.5E+14 Joules which just don’t seem reasonable. Some of these swings go over .1% month to month which on a global scale is a very large number, more on this later in the paper.

In the next Chat 5 we look at the two items that make up the different of the monthly changes. Like Chart 2 and 4 we are looking at 2000 to the present so we can see the movements in greater detail. The red line represents the energy in from the sun and the blue line represents the energy out or in to make the NASA number for the current month work as listed. Trend lines were added to both along with their equations and R² values. The trend line shows the mean value which shows the swings in temperature movements are more or less the opposite of the energy coming in from the sun. In my opinion this blue plot should look more like the red plot.

Also, for all practical purposes the energy in and out flows would have to be in and out of the planets oceans; would that not be noticeable?

Chart 6, the next Chat is based on the blue plot shown in Chart 5. We can see in Chart 5 that there is a lot of energy moving in and out of someplace? But since this value is so high we need to get a handle on it and so we can equate it to the energy released by an atomic bomb. The most common size today is about one mega ton, which is about 50 time the size of the larger atomic bomb, Fat Man, dropped on Nagasaki from a Boeing B-29 super fortress named Bockscar .

Dividing the values in Chart 5 by 4.18E+12 Joules per a one mega ton atomic bomb we can create a chart representing One Mega Ton Atomic bombs, so the energy movements are equivalent to between 10 and 800 one mega ton bombs going off every day of the year.

We can see that the monthly NASA-GISS energy flows far and away exceed any possible variation in the planets albedo or, in my opinion from the oceans, and so the values in the NASA-GISS table LOTI cannot be correct.

I would appreciate feedback on this analysis as there are serious implications to the integrity of the NOAA and NASA published data!

Something has been bothering me about the NASA-GISS LOTI data table for a long time now, and I don’t mean the data manipulation which we all know is there. NASA publishes a table of values representing the global temperature of the planet supposedly based on actual measurements. The problem I saw in their data was the large swings in their numbers on a month to month basis; at a local level yes, of course, but on a global level the changes would have to be very gradual because of the very large numbers involved in the energy content of the atmosphere.

Last week I decided to try and calculate the heat value of the NASA LOTI changes and so from Wikipedia we find that the dry atmosphere is 5.1352E+18 kg and the water is 1.27E+16 kg for a total of 5.1479E+18 kg. with that all that was needed was a heat value and so a Google search brought up a guest post on WUWT from April 6, 2011 by Jeff Id from his the Air Vent blog where a thermal analysis was completed for a different purpose but in the post was the number I was seeking of 1005 Joules per degree Kelvin for the heat value of the Earth’s atmosphere.

The next step was to take the most current (at the time this was written) NASA LOTI values from January 1880 to June 2015 and place them in a spreadsheet it was then simple to calculate the heat value of each months anomaly for example for January 1880 the value was 1.48193E+21 Joules and for June 2015 the value was 1.48728E+21 Joules. There were 1625 values in the LOTI table; because of the large number of values the line width was set to zero to make it readable and the scale is in mega joules. A second chat was added from January 2000 to the present so that more detail can be seen

It’s clear when looking at this chart that there are extremely large monthly energy flows involved here if the NASA numbers are actually valid. To put this in perspective four lines were added to this chart for the incoming solar radiation using the following albedo percentages 0.0%, 20.0%, 30.6% and 40.0% and using 1368 Wm² for solar radiation at the earth’s orbit adjusted to 342 Wm² to compensate for the spherical earth. Obviously the Wm² had to be converted to Joules we used 2,592,000 seconds for the conversion since we were looking a monthly changes.

With that done we can see that the monthly NASA-GISS energy flows far and away exceed any possible variation in the planets albedo and so the values in the NASA-GISS table LOTI cannot be correct.

I would appreciate feedback on this analysis as there are serious implications to the integrity of the NOAA and NASA published data!