Strong Horizontal Engineer Graph Paper: Fill & Download for Free

Question: Why are they saying Earth will become unlivable by 2048? Not that I don't slightly believe it, but where is that exact prediction coming from?Short answer: Mr. “I wrote a book on global warming” is dead wrong. Here is the truth about Global Warming based on real Physics and supporting Mathematics.Abstract: I’ve been reading and writing about Global Warming for 2-years. Initially I didn’t give this subject much attention, but over time I noticed a disturbing trend. As a young research associate at the Johns Hopkins University many decades ago, grant proposals and awards paid my salary. I was lucky; I got to play Scientist while professors raised research funding. Integrity was paramount however, and I never dreamed of the situation we find today.In a recent EurekAlert by the American Association for the Advancement of Science we find that integrity has been substituted with greed. Dr Miyakawa, Editor-in-Chief of the peer-reviewed journal Molecular Brain recently said… "it is sometimes difficult to believe the results of manuscripts that are 'too beautiful to be true'." In 41 such cases, when asked the manuscripts' authors to provide the raw data supporting their conclusions, in more than 97% of cases, the authors withdrew their manuscripts rather than provide raw data. In my opinion, the absence of raw data is strong indication of fraud. And apparently when it comes to swaying public opinion, fraud is now an acceptable tool.I am writing this answer specifically for the scientifically challenged. In layman’s terms I’m going to explain graphing techniques and the difference between linear and logarithmic scales and why this distinction is required to understand Global Warming. I’m going to present Global Warming theory at the same scale of the atmosphere, and demonstrate the relationship between water vapor and CO2. And by the end of this answer, I’m going to present a solution to end the Global Warming debacle.I’m hopeful the reader will allow me to veer off-topic to explain logarithmic graphing with an event that is both familiar and relevant – the current corona virus pandemic. I assure the reader this is relevant to the discussion, and you may learn beneficially about viruses.In this graph we find corona virus data display graphically on both linear and logarithmic vertical axis scales. When data varies more than a factor of 10, logarithmic scales are the choice of science. Notice in this graph that early virus data is obscured by the application of a Linear Scale, while the Logarithmic Scale of ending virus data is by far more realistic in term of comparison.Important note: These graphs (previous and next) are logarithmic only in the vertical axis. In science and engineering, a semi-log plot, or semi-log graph, has one axis on a logarithmic scale, the other on a linear scale. This is useful for data with exponential relationships, or where one variable covers a large range of values. The factor of ‘time’ (as in these graphs) is usually displayed on the linear horizontal scale.Here is another example of a logarithmic vertical axis in a graph. Logarithmic scales are beneficial to understand long-term stock market trends of Prices verses Time. For example, most of the early historical details are washed out with linear scaling on the right of this graph, while all of the early data integrity is maintained by the logarithmic scaling on the left. As an investor the linear scale data does not properly display stock market volatility; that’s why many investors prefer logarithmic trend data. Before proceeding, insure a basic understanding of logarithmic scale graphing techniques. Google searching may help if this topic remains confusing.This semi-logarithmic graph displays a typical Atmospheric distribution of Water Vapor from 10 ppm – 10,000 ppm covering 3-decades. Notice the vertical axis displays 10 ppm, 100 ppm, 1000 ppm and 10,000 ppm at the top. Global Warming historical data is often hidden in linear scale AGW graphs.Reviewing the above graph, I would call your attention to the little box at the red arrow. There is a virus in this data, and the virus is represented by the graph in the little box in the red circle. I placed the CO2 graph in the Water Vapor graph at the same scale for demonstration purposes. Notice the blue lines at 300 and 400 correspond to the same values on the vapor graph.Let’s expand the scale (magnify the tiny image from the previous graph) to explore the ‘virus’ in the water vapor graph. This virus is incredibly small, only 100 PPM – 1/10 of 1 decade. Compared to water vapor - 100 ppm / 10,000 ppm = .01 (1.0%). During the remainder of this paper we will be exploring this virus in ever increasing detail.Before proceeding I must explain my rational for labeling CO2 a virus. The AGW Community utilizes CO2 much like a computer virus designed to corrupt and alter a computer’s operating system for nefarious purposes. The CO2 virus works in the identical fashion; it is designed to corrupt the science of CO2 by altering data with the specific intention to influence public opinion for political purposes.Let’s return to the science and explore the contrast between CO2 and water vapor emissivity.Emissivity is defined as the ratio of the energy radiated from a material's surface to that radiated from a perfect emitter, known as a blackbody, at the same temperature and wavelength and under the same viewing conditions. The concept of a blackbody is theoretical with an emissivity = 1; however blackbody perfect emitters do not exist in nature.To fully appreciate the potential for Global Warming it imperative to comprehend the states of Matter in Physics. Everyone understands solid and liquids, but our atmosphere is made of Diffuse Gases. Consider for a moment the tires on your car. As more and more gas molecules are added the pressure increases, however the volume occupied by the gas is also proportional to temperature at a fixed pressure. For the atmosphere a convenient unit of measure is ‘Pressure at Altitude’When considering the atmosphere as a blackbody a fictitious temperature is called the effective sky temperature Tsky. For cold clear sky Tsky = 230K; for warm cloudy sky Tsky = 285 K. (Avg: 257.5). Adding an average altitude for CO2 (15,000 Meters) we can apply these number to the calculator below to obtain an Air Pressure at Altitude of 0.09 atm-m.The take home message for Diffuse Mater (from the chart above) is that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.From my perspective as a scientist, there’s always been something missing in Global Warming theory. The usual retort that “all objects with a temperature above absolute zero emit as Black Bodies” is missing the Scalar. The language of science is mathematics, and Scalers describe magnitude; such as volume, density, speed, energy, mass, and time. Where are the Scalars and Mathematics for Global Warming? To answer this question we first apply the Average Atmospheric temperature (257.5°K) to determine the Air Pressure at 15Km Altitude (0.09 Atm-m) and apply the result to these tables.Note: Temperatures are measured in degrees Kelvin. The Kelvin scale is similar to the Centigrade scale except it begins at absolutely zero where all molecular motion stops; 257.5°K is slightly below freezing.These tables are the result of research by Hoyt Clarke Hottel, professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT). Hottel was an expert on energy, radiant heat transfer, fire, fuels and combustion and was in charge of solar energy research program at MIT. He was a member of the National Academy of Sciences, the National Academy of Engineering and a fellow of the American Academy of Arts and Sciences and the American Institute of Chemical Engineers.Through the application of these tables, we find that water vapor exhibits 2-times emissivity of CO2. When adjusted for CO2 and H2O concentration in the atmosphere, water vapor exhibits a minimum of 10-times emissivity at the lowest concentration (very dry) and over 100-times with increasing humidity.This graph is the same as the previous one, describing the typical Atmospheric distribution of Water Vapor in the atmospheric, except all of the data is converted to PPM for direct comparison. At 400 PPM atmospheric humidity, water vapor exhibits double (x2) CO2 Emissivity, at 1,000 PPM atmospheric humidity, water vapor exhibits 5-times Emissivity CO2, and at 4,000 PPM atmospheric humidity, water vapor exhibits 20-times Emissivity CO2.For the atmospheric concentration of 100 – 4000 PPM, Water Vapor Emissivity Averages Over 6 Times the Emissivity of CO2, and at higher vapor concentrations may exceed 20 times CO2. Water Vapor is the dominate greenhouse gas; not CO2. Any suggestion to the contrary is nonsense. Recall that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.I’m hopeful by now I have demonstrated that scales matter when reviewing climate data. Below is a prime example. The CO2 atmospheric scale to the left is not difficult to visualize, but the graphs to the right with mixed scales are easily misunderstood. This technique applied below is purposely deceptive.The upper graph on the right by James Hansen et. al., published in Science Briefs, August, 1999, displays the U.S. and Global Temperature anomalies. The scales on these graphs have been manipulated to reinforce one-another in a way that non-scientists are unlikely to comprehend. When the graphs are adjusted to the same scale, the Global data reveals considerably less variation. This is to be expected since the Oceans are a stabilizing factor of Global temperature.Now I recognize that some may argue these scales were adjusted for clarity and not necessarily for deception, however I have challenged the AGW crowd on many occasions to explain the following graphs where data has been altered over time. The next two graphs are prime examples why all raw data must be published and archived.Climate scientists didn’t like explaining the 1940 heat wave so they made it disappearIn what might be the largest scientific fraud ever uncovered, GISS has been caught red-handed altering historical temperature data to produce a “climate change narrative” that defies reality. We now know that historical temperature data for the continental United States were deliberately altered by GISS scientists in a politically-motivated attempt to rewrite history and claim global warming is causing U.S. temperatures to trend upward. Here they discuss altering data.A virus is an agent that commandeers an entity and reprograms its purpose. Above find a Goddard Institute of Space Science created virus that alters data.I created these comparative graphs to highlight this and expose the continued corruption at GISS.Notice how all of the early century warm data points (red circles, left graph) have been cooled (blue circles, right graph)Conversely, notice how all of the late century cool data points (blue circles, left graph) have been warmed (red circles, right graph).When data does not fit the hypothesis, cooling the past while warming the present makes Global Warming more plausible to explain. GISS has given their fraudulent activities a fancy name – it’s called “correction analysis,” but no amount of data manipulation justifies cooling the July 25, 1936 heat wave; the hottest period ever recorded in American history. This is our government, and offers a compelling example why all raw data must be published and archived.In the following graphs, GISS failed to consider the National Academy of Sciences had access to the same raw climate data, For differentiation, compare only the blue lines; (top & bottom) both are for the Northern Hemisphere Temperature Anomaly.I created these composite graphs as incontrovertible evidence of fraudulent activity by GISS. Long accepted scientific criticism reveals… upon finding any fraudulent data, one must assume it’s all fraudulent.For those with remaining doubts, challenge Global Warming advocates to explain the dichotomy in these graphs. I’ve done so many times, only to receive silence.The upper portion of this composite graph is an outright forgery; there is no other explanation. Here we find GISS data compared to National Academy of Science data (NAS) with reference lines to insure alignment. The scales are sufficiently close to effect comparison. The 1975 report accompanying the NAS graph stated (p. 36) that, "The average surface air temperature in the northern hemisphere increased from the 1880's until about 1940 and has been decreasing thereafter."To the left of the red reference line GISS and NAS data track agreeably, but to the right consistency weakens approaching 1970. It would appear warmth has been added to the GISS data in contrast to the 1975 report… "The average surface air temperature… has been decreasing thereafter" (up until 1975). The variance is most notable between the pale blue Northern Hemisphere track (GISS) and its rapid divergence from the identically titled NAS data. Considering the prior history of altering data as previously demonstrated, it’s difficult to ascribe any credibility to GISS Global Warming assertions. Let’s look at one more example of forgery.After discovering the previous anomalies, an AGW alarmist sent me the graph to the right in the above composite; I was literally in disbelief. Since GISS won’t provide raw data, I’ve been archiving old GISS graphs for later comparison. In the original graph of Global Average Temperature (to the left) consider that while industrialization expanded exponentially over 140 years beginning in 1880, the preexisting data-trend has continued without significant alternation.Today’s so named ‘warming’ that initiated concurrent with the recording of U.S. temperature data in 1880, has continued mostly uninterrupted on the same trend-line for 140 years. This warming trend began centuries ago with minimal (if any) change in acceleration due to CO2 nonsense AGW. There’s reason to believe the AGW alarmists recognized this trend, but fully expected the trend-line to change over time. When it did not, they created new fraudulent archival data to accomplish the same effect.The graph to the right was created to suggest there was no warming from 1850 - 1925 (75 years) and then Global warming accelerated thereafter. I generally avoid such terms, but this is just bullshit. Scientists mark the start of modern global record-keeping as 1880, because earlier available climate data did not cover enough of the planet to make an accurate assessment, and certainly didn’t include continental North America. The graph on the right is truly disturbing because it demonstrates a broad collaborative effort to fabricate data for purposes of rewriting history.At the beginning of this paper I promised a solution to the current CO2 Global Warming crisis. Based on the above demonstrations of forgery and all of the other factors previously presented herein, the solution is not difficult to imagine. GISS is funded with the tax dollars of the United States. The mere fact that GISS does not publish raw data, and has been exposed for altering data, leaves no other alternative. GISS must be defunded.For those who would object, let’s consider one last piece of evidence. There is not a shred of evidence demonstrating an unequivocal measurement of atmospheric CO2 ‘Blackbody Radiation’ or ‘Terrestrial ‘CO2 Back Radiation.” Quantum Physics suggests the first one is non-existent, and the second is dominated by water vapor. If I’m wrong, reply to this answer with your credential – provide a direct measurement of Atmospheric Blackbody radiation. Astrophysicist measure blackbody radiation light-years away. If its present in the atmosphere, then show us the data.

Question: Has the equable climate problem been solved? YESShort answer: I’ve been working on this problem for over a year; I’ve got the solution.Abstract: I’ve been reading and writing about Global Warming for 2-years. Initially I didn’t give this subject much attention, but over time I noticed a disturbing trend. As a young research associate at the Johns Hopkins University many decades ago, grant proposals and awards paid my salary. I was lucky; I got to play Scientist while professors raised research funding. Integrity was paramount however, and I never dreamed of the situation we find today.In a recent EurekAlert by the American Association for the Advancement of Science we find that integrity has been substituted with greed. Dr Miyakawa, Editor-in-Chief of the peer-reviewed journal Molecular Brain recently said… "it is sometimes difficult to believe the results of manuscripts that are 'too beautiful to be true'." In 41 such cases, when asked the manuscripts' authors to provide the raw data supporting their conclusions, in more than 97% of cases, the authors withdrew their manuscripts rather than provide raw data. In my opinion, the absence of raw data is strong indication of fraud. And apparently when it comes to swaying public opinion, fraud is now an acceptable tool.I am writing this answer specifically for the scientifically challenged. In layman’s terms I’m going to explain graphing techniques and the difference between linear and logarithmic scales and why this distinction is required to understand Global Warming. I’m going to present Global Warming theory at the same scale of the atmosphere, and demonstrate the relationship between water vapor and CO2. And by the end of this answer, I’m going to present a solution to end the Global Warming debacle.I’m hopeful the reader will allow me to veer off-topic to explain logarithmic graphing with an event that is both familiar and relevant – the current corona virus pandemic. I assure the reader this is relevant to the discussion, and you may learn about viruses.In this graph we find corona virus data display graphically on both linear and logarithmic vertical axis scales. When data varies more than a factor of 10, logarithmic scales are the choice of science. Notice in this graph that early virus data is obscured by the application of a Linear Scale, while the Logarithmic Scale of ending virus data is by far more realistic in term of comparison.Important note: These graphs (previous and next) are logarithmic only in the vertical axis. In science and engineering, a semi-log plot, or semi-log graph, has one axis on a logarithmic scale, the other on a linear scale. This is useful for data with exponential relationships, or where one variable covers a large range of values. The factor of ‘time’ (as in these graphs) is usually displayed on the linear horizontal scale.Here is another example of a logarithmic vertical axis in a graph. Logarithmic scales are beneficial to understand long-term stock market trends of Prices verses Time. For example, most of the early historical details are washed out with linear scaling on the right of this graph, while all of the early data integrity is maintained by the logarithmic scaling on the left. As an investor the linear scale data does not properly display stock market volatility; that’s why many investors prefer logarithmic trend data. Before proceeding, insure a basic understanding of logarithmic scale graphing techniques. Google searching may help if this topic remains confusing.This semi-logarithmic graph displays a typical Atmospheric distribution of Water Vapor from 10 ppm – 10,000 ppm covering 3-decades. Notice the vertical axis displays 10 ppm, 100 ppm, 1000 ppm and 10,000 ppm at the top. Global Warming historical data is often hidden in linear scale AGW graphs.Reviewing the above graph, I would call your attention to the little box at the red arrow. There is a virus in this data, and the virus is represented by the graph in the little box in the red circle. I placed the CO2 graph in the Water Vapor graph at the same scale for demonstration purposes. Notice the blue lines at 300 and 400 correspond to the same values on the vapor graph.Let’s expand the scale (magnify the tiny image from the previous graph) to explore the ‘virus’ in the water vapor graph. This virus is incredibly small, only 100 PPM – 1/10 of 1 decade. Compared to water vapor - 100 ppm / 10,000 ppm = .01 (1.0%). During the remainder of this paper we will be exploring this virus in ever increasing detail.Before proceeding I must explain my rational for labeling CO2 a virus. The AGW Community utilizes CO2 much like a computer virus designed to corrupt and alter a computer’s operating system for nefarious purposes. The CO2 virus works in the identical fashion; it is designed to corrupt the science of CO2 by altering data with the specific intention to influence public opinion for political purposes.Let’s return to the science and explore the contrast between CO2 and water vapor emissivity.Emissivity is defined as the ratio of the energy radiated from a material's surface to that radiated from a perfect emitter, known as a blackbody, at the same temperature and wavelength and under the same viewing conditions. The concept of a blackbody is theoretical with an emissivity = 1; however blackbody perfect emitters do not exist in nature.To fully appreciate the potential for Global Warming it imperative to comprehend the states of Matter in Physics. Everyone understands solid and liquids, but our atmosphere is made of Diffuse Gases. Consider for a moment the tires on your car. As more and more gas molecules are added the pressure increases, however the volume occupied by the gas is also proportional to temperature at a fixed pressure. For the atmosphere a convenient unit of measure is ‘Pressure at Altitude’When considering the atmosphere as a blackbody a fictitious temperature is called the effective sky temperature Tsky. For cold clear sky Tsky = 230K; for warm cloudy sky Tsky = 285 K. (Avg: 257.5). Adding an average altitude for CO2 (15,000 Meters) we can apply these number to the calculator below to obtain an Air Pressure at Altitude of 0.09 atm-m.The take home message for Diffuse Mater (from the chart above) is that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.From my perspective as a scientist, there’s always been something missing in Global Warming theory. The usual retort that “all objects with a temperature above absolute zero emit as Black Bodies” is missing the Scalar. The language of science is mathematics, and Scalers describe magnitude; such as volume, density, speed, energy, mass, and time. Where are the Scalars and Mathematics for Global Warming? To answer this question we first apply the Average Atmospheric temperature (257.5°K) to determine the Air Pressure at 15Km Altitude (0.09 Atm-m) and apply the result to these tables.Note: Temperatures are measured in degrees Kelvin. The Kelvin scale is similar to the Centigrade scale except it begins at absolutely zero where all molecular motion stops; 257.5°K is slightly below freezing.These tables are the result of research by Hoyt Clarke Hottel, professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT). Hottel was an expert on energy, radiant heat transfer, fire, fuels and combustion and was in charge of solar energy research program at MIT. He was a member of the National Academy of Sciences, the National Academy of Engineering and a fellow of the American Academy of Arts and Sciences and the American Institute of Chemical Engineers.Through the application of these tables, we find that water vapor exhibits 2-times emissivity of CO2. When adjusted for CO2 and H2O concentration in the atmosphere, water vapor exhibits a minimum of 10-times emissivity at the lowest concentration (very dry) and over 100-times with increasing humidity.This graph is the same as the previous one, describing the typical Atmospheric distribution of Water Vapor in the atmospheric, except all of the data is converted to PPM for direct comparison.At 400 PPM atmospheric humidity, water vapor exhibits double (x2) CO2 EmissivityAt 1,000 PPM atmospheric humidity, water vapor exhibits 5-times Emissivity CO2At 4,000 PPM atmospheric humidity, water vapor exhibits 20-times Emissivity CO2.For the atmospheric concentration of 100 – 4000 PPM, Water Vapor Emissivity Averages Over 6 Times the Emissivity of CO2, and at higher vapor concentrations may exceed 20 times CO2. Water Vapor is the dominate greenhouse gas; not CO2. Any suggestion to the contrary is nonsense. Recall that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.I’m hopeful by now I have demonstrated that scales matter when reviewing climate data. Below is a prime example. The CO2 atmospheric scale to the left is not difficult to visualize, but the graphs to the right with mixed scales are easily misunderstood. This technique applied below is purposely deceptive.The upper graph on the right by James Hansen et. al., published in Science Briefs, August, 1999, displays the U.S. and Global Temperature anomalies. The scales on these graphs have been manipulated to reinforce one-another in a way that non-scientists are unlikely to comprehend. When the graphs are adjusted to the same scale, the Global data reveals considerably less variation. This is to be expected since the Oceans are a stabilizing factor of Global temperature.Now I recognize that some may argue these scales were adjusted for clarity and not necessarily for deception, however I have challenged the AGW crowd on many occasions to explain the following graphs where data has been altered over time. The next two graphs are prime examples why all raw data must be published and archived.Climate scientists didn’t like explaining the 1940 heat wave so they made it disappearIn what might be the largest scientific fraud ever uncovered, GISS has been caught red-handed altering historical temperature data to produce a “climate change narrative” that defies reality. We now know that historical temperature data for the continental United States were deliberately altered by GISS scientists in a politically-motivated attempt to rewrite history and claim global warming is causing U.S. temperatures to trend upward. Here they discuss altering data.A virus is an agent that commandeers an entity and reprograms its purpose. Above find a Goddard Institute of Space Science created virus that alters data.I created these comparative graphs to highlight this and expose the continued corruption at GISS.Notice how all of the early century warm data points (red circles, left graph) have been cooled (blue circles, right graph)Conversely, notice how all of the late century cool data points (blue circles, left graph) have been warmed (red circles, right graph).When data does not fit the hypothesis, cooling the past while warming the present makes Global Warming more plausible to explain. GISS has given their fraudulent activities a fancy name – it’s called “correction analysis,” but no amount of data manipulation justifies cooling the July 25, 1936 heat wave; the hottest period ever recorded in American history. This is our government, and offers a compelling example why all raw data must be published and archived.In the following graphs, GISS failed to consider the National Academy of Sciences had access to the same raw climate data, For differentiation, compare only the blue lines; (top & bottom) both are for the Northern Hemisphere Temperature Anomaly.I created these composite graphs as incontrovertible evidence of fraudulent activity by GISS. Long accepted scientific criticism reveals… upon finding any fraudulent data, one must assume it’s all fraudulent.For those with remaining doubts, challenge Global Warming advocates to explain the dichotomy in these graphs. I’ve done so many times, only to receive silence.This upper portion of this composite graph is an outright forgery; there is no other explanation. Here we find GISS data compared to National Academy of Science data (NAS) with reference lines to insure alignment. The scales are sufficiently close to effect comparison. The 1975 report accompanying the NAS graph stated (p. 36) that, "The average surface air temperature in the northern hemisphere increased from the 1880's until about 1940 and has been decreasing thereafter."To the left of the red reference line GISS and NAS data track agreeably, but to the right consistency weakens approaching 1970. It would appear warmth has been added to the GISS data in contrast to the 1975 report… "The average surface air temperature… has been decreasing thereafter" (up until 1975). The variance is most notable between the pale blue Northern Hemisphere track (GISS) and its rapid divergence from the identically titled NAS data. Considering the prior history of altering data as previously demonstrated, it’s difficult to ascribe any credibility to GISS Global Warming assertions. Let’s look at one more example of forgery,After discovering the previous anomalies, an AGW alarmist sent me the graph to the right in the above composite; I was literally in disbelief. Since GISS won’t provide raw data, I’ve been archiving old GISS graphs for later comparison. In the original graph of Global Average Temperature (to the left) consider that while industrialization expanded exponentially over 140 years beginning in 1880, the preexisting data-trend has continued without significant alternation.Today’s so named ‘warming’ that initiated concurrent with the recording of U.S. temperature data in 1880, has continued mostly uninterrupted on the same trend-line for 140 years. This warming trend began centuries ago with minimal (if any) change in acceleration due to CO2 nonsense AGW. There’s reason to believe the AGW alarmists recognized this trend, but fully expected the trend-line to change over time. When it did not, they created new fraudulent archival data to accomplish the same effect.The graph to the right was created to suggest there was no warming from 1850 - 1925 (75 years) and then Global warming accelerated thereafter. I generally avoid such terms, but this is just bullshit. Scientists mark the start of modern global record-keeping as 1880, because earlier available climate data did not cover enough of the planet to make an accurate assessment, and certainly didn’t include continental North America. The graph on the right is truly disturbing because it demonstrates a broad collaborative effort to fabricate data for purposes of rewriting history.At the beginning of this paper I promised a solution to the current CO2 Global Warming crisis. Based on the above demonstrations of forgery and all of the other factors previously presented herein, the solution is not difficult to imagine. GISS is funded with the tax dollars of the United States. The mere fact that GISS does not publish raw data, and has been exposed for altering data, leaves no other alternative. GISS must be defunded.For those who would object, let’s consider one last piece of evidence. There is not a shred of evidence demonstrating an unequivocal measurement of atmospheric CO2 ‘Blackbody Radiation’ or ‘Terrestrial ‘CO2 Back Radiation.” Quantum Physics suggests the first one is non-existent, and the second is dominated by water vapor. If I’m wrong, reply to this answer with your credential – provide a direct measurement of Atmospheric Blackbody radiation. Astrophysicist measure blackbody radiation light-years away. If its present in the atmosphere, then show us the data.This work is distributed under the Creative Commons Attribution 4.0 License.

Question: What are some substantial scientifically based reads to understand global warming challenges (causes, potential consequences, solutions)?Abstract: I’ve been reading and writing about Global Warming for 2-years. Initially I didn’t give this subject much attention, but over time I noticed a disturbing trend. As a young research associate at the Johns Hopkins University many decades ago, grant proposals and awards paid my salary. I was lucky; I got to play Scientist while professors raised research funding. Integrity was paramount however, and I never dreamed of the situation we find today.In a recent EurekAlert by the American Association for the Advancement of Science we find that integrity has been substituted with greed. Dr Miyakawa, Editor-in-Chief of the peer-reviewed journal Molecular Brain recently said… "it is sometimes difficult to believe the results of manuscripts that are 'too beautiful to be true'." In 41 such cases, when asked the manuscripts' authors to provide the raw data supporting their conclusions, in more than 97% of cases, the authors withdrew their manuscripts rather than provide raw data. In my opinion, the absence of raw data is strong indication of fraud. And apparently when it comes to swaying public opinion, fraud is now an acceptable tool.I am writing this answer specifically for the scientifically challenged. In layman’s terms I’m going to explain graphing techniques and the difference between linear and logarithmic scales and why this distinction is required to understand Global Warming. I’m going to present Global Warming theory at the same scale of the atmosphere, and demonstrate the relationship between water vapor and CO2. And by the end of this answer, I’m going to present a solution to end the Global Warming debacle.I’m hopeful the reader will allow me to veer off-topic to explain logarithmic graphing with an event that is both familiar and relevant – the current corona virus pandemic. I assure the reader this is relevant to the discussion, and you may learn beneficially about viruses.In this graph we find corona virus data display graphically on both linear and logarithmic vertical axis scales. When data varies more than a factor of 10, logarithmic scales are the choice of science. Notice in this graph that early virus data is obscured by the application of a Linear Scale, while the Logarithmic Scale of ending virus data is by far more realistic in term of comparison.Important note: These graphs (previous and next) are logarithmic only in the vertical axis. In science and engineering, a semi-log plot, or semi-log graph, has one axis on a logarithmic scale, the other on a linear scale. This is useful for data with exponential relationships, or where one variable covers a large range of values. The factor of ‘time’ (as in these graphs) is usually displayed on the linear horizontal scale.Here is another example of a logarithmic vertical axis in a graph. Logarithmic scales are beneficial to understand long-term stock market trends of Prices verses Time. For example, most of the early historical details are washed out with linear scaling on the right of this graph, while all of the early data integrity is maintained by the logarithmic scaling on the left. As an investor the linear scale data does not properly display stock market volatility; that’s why many investors prefer logarithmic trend data. Before proceeding, insure a basic understanding of logarithmic scale graphing techniques. Google searching may help if this topic remains confusing.This semi-logarithmic graph displays a typical Atmospheric distribution of Water Vapor from 10 ppm – 10,000 ppm covering 3-decades. Notice the vertical axis displays 10 ppm, 100 ppm, 1000 ppm and 10,000 ppm at the top. Global Warming historical data is often hidden in linear scale AGW graphs. The horizontal time scale appears compressed because the instrumentation was mounted on a Lear-jet.Reviewing the above graph, I would call your attention to the little box at the red arrow. There is a virus in this data, and the virus is represented by the graph in the little box in the red circle. I placed the CO2 graph in the Water Vapor graph at the same scale for demonstration purposes. Notice the blue lines at 300 and 400 correspond to the same values on the vapor graph.Let’s expand the scale (magnify the tiny image from the previous graph) to explore the ‘virus’ in the water vapor graph. This virus is incredibly small, only 100 PPM – 1/10 of 1 decade. Compared to water vapor - 100 ppm / 10,000 ppm = .01 (1.0%). During the remainder of this paper we will be exploring this virus in ever increasing detail.Before proceeding I must explain my rational for labeling CO2 a virus. The AGW Community utilizes CO2 much like a computer virus designed to corrupt and alter a computer’s operating system for nefarious purposes. The CO2 virus works in the identical fashion; it is designed to corrupt the science of CO2 by altering data with the specific intention to influence public opinion for political purposes.Let’s return to the science and explore the contrast between CO2 and water vapor emissivity.Emissivity is defined as the ratio of the energy radiated from a material's surface to that radiated from a perfect emitter, known as a blackbody, at the same temperature and wavelength and under the same viewing conditions. The concept of a blackbody is theoretical with an emissivity = 1; however blackbody perfect emitters do not exist in nature.To fully appreciate the potential for Global Warming it imperative to comprehend the states of Matter in Physics. Everyone understands solid and liquids, but our atmosphere is made of Diffuse Gases. Consider for a moment the tires on your car. As more and more gas molecules are added the pressure increases, however the volume occupied by the gas is also proportional to temperature at a fixed pressure. For the atmosphere a convenient unit of measure is ‘Pressure at Altitude’When considering the atmosphere as a blackbody a fictitious temperature is called the effective sky temperature Tsky. For cold clear sky Tsky = 230K; for warm cloudy sky Tsky = 285 K. (Avg: 257.5). Adding an average altitude for CO2 (15,000 Meters) we can apply these number to the calculator below to obtain an Air Pressure at Altitude of 0.09 atm-m.The take home message for Diffuse Mater (from the chart above) is that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.From my perspective as a scientist, there’s always been something missing in Global Warming theory. The usual retort that “all objects with a temperature above absolute zero emit as Black Bodies” is missing the Scalar. The language of science is mathematics, and Scalers describe magnitude; such as volume, density, speed, energy, mass, and time. Where are the Scalars and Mathematics for Global Warming? To answer this question we first apply the Average Atmospheric temperature (257.5°K) to determine the Air Pressure at 15Km Altitude (0.09 Atm-m) and apply the result to these tables.Note: Temperatures are measured in degrees Kelvin. The Kelvin scale is similar to the Centigrade scale except it begins at absolutely zero where all molecular motion stops; 257.5°K is slightly below freezing.These tables are the result of research by Hoyt Clarke Hottel, professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT). Hottel was an expert on energy, radiant heat transfer, fire, fuels and combustion and was in charge of solar energy research program at MIT. He was a member of the National Academy of Sciences, the National Academy of Engineering and a fellow of the American Academy of Arts and Sciences and the American Institute of Chemical Engineers.Through the application of these tables, we find that water vapor exhibits 2-times emissivity of CO2. When adjusted for CO2 and H2O concentration in the atmosphere, water vapor exhibits a minimum of 10-times emissivity at the lowest concentration (very dry) and over 100-times with increasing humidity.This graph is the same as the previous one, describing the typical Atmospheric distribution of Water Vapor in the atmospheric, except all of the data is converted to PPM for direct comparison. At 400 PPM atmospheric humidity, water vapor exhibits double (x2) CO2 Emissivity, at 1,000 PPM atmospheric humidity, water vapor exhibits 5-times Emissivity CO2, and at 4,000 PPM atmospheric humidity, water vapor exhibits 20-times Emissivity CO2.For the atmospheric concentration of 100 – 4000 PPM, Water Vapor Emissivity Averages Over 6 Times the Emissivity of CO2, and at higher vapor concentrations may exceed 20 times CO2. Water Vapor is the dominant greenhouse gas; not CO2. Any suggestion to the contrary is nonsense. Recall that Dense Gases contain many molecules tightly packed, while Thin Gases contain fewer molecules widely spaced.I’m hopeful by now I have demonstrated that scales matter when reviewing climate data. Below is a prime example. The CO2 atmospheric scale to the left is not difficult to visualize, but the graphs to the right with mixed scales are easily misunderstood. This technique applied below is purposely deceptive.The upper graph on the right by James Hansen et. al., published in Science Briefs, August, 1999, displays the U.S. and Global Temperature anomalies. The scales on these graphs have been manipulated to reinforce one-another in a way that non-scientists are unlikely to comprehend. When the graphs are adjusted to the same scale, the Global data reveals considerably less variation. This is to be expected since the Oceans are a stabilizing factor of Global temperature.Now I recognize that some may argue these scales were adjusted for clarity and not necessarily for deception, however I have challenged the AGW crowd on many occasions to explain the following graphs where data has been altered over time. The next two graphs are prime examples why all raw data must be published and archived.Climate scientists didn’t like explaining the 1940 heat wave so they made it disappearIn what might be the largest scientific fraud ever uncovered, GISS has been caught red-handed altering historical temperature data to produce a “climate change narrative” that defies reality. We now know that historical temperature data for the continental United States were deliberately altered by GISS scientists in a politically-motivated attempt to rewrite history and claim global warming is causing U.S. temperatures to trend upward. Here they discuss altering data.A virus is an agent that commandeers an entity and reprograms its purpose. Above find a Goddard Institute of Space Science created virus that alters data.I created these comparative graphs to highlight this and expose the continued corruption at GISS.Notice how all of the early century warm data points (red circles, left graph) have been cooled (blue circles, right graph)Conversely, notice how all of the late century cool data points (blue circles, left graph) have been warmed (red circles, right graph).When data does not fit the hypothesis, cooling the past while warming the present makes Global Warming more plausible to explain. GISS has given their fraudulent activities a fancy name – it’s called “correction analysis,” but no amount of data manipulation justifies cooling the July 25, 1936 heat wave; the hottest period ever recorded in American history. This is our government, and offers a compelling example why all raw data must be published and archived.In the following graphs, GISS failed to consider the National Academy of Sciences had access to the same raw climate data, For differentiation, compare only the blue lines; (top & bottom) both are for the Northern Hemisphere Temperature Anomaly.I created these composite graphs as incontrovertible evidence of fraudulent activity by GISS. Long accepted scientific criticism reveals… upon finding any fraudulent data, one must assume it’s all fraudulent.For those with remaining doubts, challenge Global Warming advocates to explain the dichotomy in these graphs. I’ve done so many times, only to receive silence.The upper portion of this composite graph is an outright forgery; there is no other explanation. Here we find GISS data compared to National Academy of Science data (NAS) with reference lines to insure alignment. The scales are sufficiently close to effect comparison. The 1975 report accompanying the NAS graph stated (p. 36) that, "The average surface air temperature in the northern hemisphere increased from the 1880's until about 1940 and has been decreasing thereafter."To the left of the red reference line GISS and NAS data track agreeably, but to the right consistency weakens approaching 1970. It would appear warmth has been added to the GISS data in contrast to the 1975 report… "The average surface air temperature… has been decreasing thereafter" (up until 1975). The variance is most notable between the pale blue Northern Hemisphere track (GISS) and its rapid divergence from the identically titled NAS data. Considering the prior history of altering data as previously demonstrated, it’s difficult to ascribe any credibility to GISS Global Warming assertions. Let’s look at one more example of forgery.After discovering the previous anomalies, an AGW alarmist sent me the graph to the right in the above composite; I was literally in disbelief. Since GISS won’t provide raw data, I’ve been archiving old GISS graphs for later comparison. In the original graph of Global Average Temperature (to the left) consider that while industrialization expanded exponentially over 140 years beginning in 1880, the preexisting data-trend has continued without significant alternation.Today’s so named ‘warming’ that initiated concurrent with the recording of U.S. temperature data in 1880, has continued mostly uninterrupted on the same trend-line for 140 years. This warming trend began centuries ago with minimal (if any) change in acceleration due to CO2 nonsense AGW. There’s reason to believe the AGW alarmists recognized this trend, but fully expected the trend-line to change over time. When it did not, they created new fraudulent archival data to accomplish the same effect.The graph to the right was created to suggest there was no warming from 1850 - 1925 (75 years) and then Global warming accelerated thereafter. I generally avoid such terms, but this is just bullshit. Scientists mark the start of modern global record-keeping as 1880, because earlier available climate data did not cover enough of the planet to make an accurate assessment, and certainly didn’t include continental North America. The graph on the right is truly disturbing because it demonstrates a broad collaborative effort to fabricate data for purposes of rewriting history.At the beginning of this paper I promised a solution to the current CO2 Global Warming crisis. Based on the above demonstrations of forgery and all of the other factors previously presented herein, the solution is not difficult to imagine. GISS is funded with the tax dollars of the United States. The mere fact that GISS does not publish raw data, and has been exposed for altering data, leaves no other alternative. GISS must be de-funded.For those who would object, let’s consider one last piece of evidence. There is not a shred of evidence demonstrating an unequivocal measurement of atmospheric CO2 ‘Blackbody Radiation’ or ‘Terrestrial ‘CO2 Back Radiation.” Quantum Physics suggests the first one is non-existent, and the second is dominated by water vapor. If I’m wrong, reply to this answer with your credential – provide a direct measurement of Atmospheric Blackbody radiation. Astrophysicist measure blackbody radiation light-years away. If its present in the atmosphere, then show us the data.