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  1. Paleo temperature reconstructions show that at some period between the 1500AD and 1900AD, Europe, and many other parts of the world, experienced a multi-centennial period of a cooling trend with growth of glaciers and ice sheets {Thompson, Lonnie G., et al. “The Little Ice Age as recorded in the stratigraphy of the tropical Quelccaya ice cap.” Science234.4774}. A bibliography of this event is provided in a related post on this site  [LINK]. This cold period, known as the Little Ice Age (LIA), was a period of great hardship for Europeans. Canals and rivers were frozen, growth of sea ice around Iceland closed down harbors and shipping, hailstorms and snowstorms were heavy and frequent, and road and water transport was made difficult or impossible. Agricultural failure and consequent starvation and death devastated Europe. The Scandinavian colonies in Greenland starved to death and disappeared.
  2. At some time between 1700AD and 1800AD the cooling trend of the LIA ended and soon thereafter, the the surface temperature reversed into a warming trend to the great delight of the suffering Europeans. By the 1930s, when the sustained warming trend was strong and it was noted that the end of the LIA and the beginning of the warming trend coincided roughly with the change from an agrarian economy with windmills, watermills, and beasts of burden as sources of energy, to an industrial economy with the combustion of coal and other fossil fuels dug up from under the ground providing the energy to drive rapid economic growth.
  3. In a 1938 paper {Callendar, G. (1938). The artificial production of carbon dioxide and its influence on temperature. Quarterly Journal of the Royal Meteorological Society , 64.275}, Guy Stewart Callendar wrote the world’s first AGW (anthropogenic global warming) paper. It is described in some detail in a related post on this site  [LINK] . The Callendar paper lays out the AGW scenario as it is preached by climate scientists today except that Callendar preferred the word “artificial” rather than “anthropogenic” to denote human cause and that the paper does not present the warming as an alarming trend but as a welcome relief from the LIA. The Callendar paper notes that atmospheric CO2 measurements taken at the surface in various parts of the UK and Europe showed a rising trend since 1900 during a time when the industrial economy was burning large quantities of fossil fuels and during a time when temperatures in England and in Europe were showing a warming trend. Callendar tied these three datasets together by (1) attributing rising atmospheric CO2 to the burning of fossil fuels in the rapidly growing industrial economy purely on the basis that both of these time series showed a rising trend and (2) attributing the warming trend to the heat trapping effect of atmospheric CO2 (and water) as described by Arrhenius in his now discredited theory of ice age cycles but applied by Callendar to a much shorter time scale. In his historic paper, Callendar concludes that from 1900 to 1936 fossil fuel emissions drove up atmospheric CO2 by an amount that explains the observed warming trend and that therefore the observed warming trend 1900-1936 is artificial (human caused) by way of fossil fuel combustion of the industrial economy. Interestingly, Callendar computed a climate sensitivity of λ=2 in his paper consistent with Manabe {Manabe, Syukuro, and Richard T. Wetherald. “Thermal equilibrium of the atmosphere with a given distribution of relative humidity.” Journal of the Atmospheric Sciences 24.3, 1967}, but not consistent with the Charney/IPCC range of 1.5<λ<4.5 or with its 2019 revision by the IPCC to λ=5.
  4. There was some interest in this paper and a few papers followed in support of the Callendar artificial warming hypothesis but interest in this line of research was dampened when the strong warming of the 1900-1940, that had rescued boreal communities from the LIA, reverted to a sustained 30-year cooling trend from the 1940s to the 1970s. The cooling caused a real fear among boreal communities of a return to LIA conditions. The cooling trend, described in a related post  [LINK], discouraged the attempt to explain warming. The salient research paper of this period is Stephen Schneider’s evaluation that fossil fuel emissions contain not only CO2 but also aerosols that can end up in the stratosphere where they can “backscatter” incident solar radiation to cause cooling {Rasool, S. Ichtiaque, and Stephen H. Schneider. “Atmospheric carbon dioxide and aerosols: Effects of large increases on global climate.” Science 173.3992 (1971)}. Schneider’s concern was that the the rate of temperature increase due to CO2 diminishes with increasing carbon dioxide in the atmosphere; but for aerosols the rate of temperature decrease due to backscatter increases with increasing aerosol concentration of the stratosphere. Because of the exponential dependence of the backscattering, the rate of temperature decrease is augmented with increasing aerosol content. An increase by only a factor of 4 in global aerosol background concentration may be sufficient to reduce the surface temperature by as much as 3.5 ° K. If sustained over a period of several years, such a temperature decrease over the whole globe is believed to be sufficient to trigger a return to LIA glaciation. Thus at a time of cooling, it could be rationalized that fossil fuel emissions of the industrialized economy can cause cooling which understandably, created fear of a return to LIA conditions.
  5. The cooling ended in the late 1970s and returned to warming in 1979. By 1981, the warming had intensified and this point in time is marked by a significant paper by James Hansen of NASA GISS {Hansen, J. (1981). Climate impact of increasing atmospheric carbon dioxide. Science , 213.4511}. The Hansen paper brought the CO2 heat trapping argument of Callendar back to life along with the attribution of rising atmospheric CO2 to fossil fuel emissions of the industrial economy; and of the observed warming to the higher CO2 concentration of the atmosphere thus created. But quite unlike the Callendar paper of 1938 that had celebrated the warming in terms of relief from the Little Ice Age and the life giving property of CO2 in terms of photosynthesis, the Hansen paper of 1981 did an about turn in the evaluation of CO2 driven warming and declared Callendar’s “artificial warming” now rephrased as Anthropogenic Global Warming (AGW) and climate change, as a calamitous Biblical catastrophe that threatened the end the world as we know it with impacts such as sea level rise, floods, droughts, heat waves, superstorms, and wildfires. This assessment sowed the seeds of fear based activism.
  6. The evolution of AGW into a fear mongering device thus initiated accelerated in 1988 with Hansen’s congressional testimony [LINK]  of the horrors of AGW if the use of fossil fuels is not eliminated or drastically reduced and the estimation of a much greater catastrophe in his 1988 paper than in the 1981 paper {Hansen, James, et al. “Global climate changes as forecast by Goddard Institute for Space Studies three‐dimensional model.” Journal of geophysical research: Atmospheres 93.D8 (1988)}. The year 1988 was also the year that James Hansen presented his Congressional Testimony on the dangers of AGW that gripped his nation and the world with fear of AGW. The year 1988 thus marks the beginning of fear  based climate change activism against fossil fuels based on the proposition that the use of fossil fuels must be eliminated to save the planet [LINK] . This trend is apparent in this list of climate change news items 1980 to 2010 [LINK] .
  7. It was at this point in time that the United Nations, eager to extend its global jurisdiction by defining environmental problems on a global scale, stepped into the climate change arena and seized administrative control of the effort to “tackle” climate change by curtailing global emissions from fossil fuel combustion in a program that has come to be called “climate action”. The UN takeover was facilitated by the existence of the UNEP, the United Nations Environment Program founded in 1972 by global environmentalism visionary Maurice Strong.
  8. The apparent success of the UNEP was presented to the world in terms of its ability to tackle an apparently calamitous ozone depletion crisis of the 1980s with the “Montreal Protocol”. This international agreement to reduce or eliminate human emissions of ozone depleting substances masterminded by the UNEP is credited with saving the world from the harmful effects of anthropogenic ozone depletion. This was the world’s first globally defined environmental issue and the first apparently successful effort by the UNEP in its self described role as a global environmental protection authority.
  9. The ozone depletion chapter of global environmentalism by the UNEP is described in three related posts on this site [LINK][LINK] [LINK] . What is shown in these posts is that there was never any evidence of ozone depletion on a global scale and that the Montreal Protocol and its grand success is a case of first falsely declaring the existence of a non-existent problem and then after the HFC reduction was completed, simply declaring the false problem to have been solved by way of the Montreal Protocol with the UNEP taking the credit for having solved it.
  10. Having tasted great success in the ozone depletion scare with the Montreal Protocol of 1987, and having seen the power of debilitating fear, the UNEP was now poised to take charge of the AGW issue as it had been described by Hansen in his Congressional testimony of 1988 and related research papers.  Describing it broadly as a global environmental crisis that can be addressed only at the global level and therefore only by the United Nations, the role of the United Nations in the extension of its ozone success to the AGW issue is thus established [LINK].
  11. The Montreal Protocol success of the United Nations was driven by an extreme form of fear based activism that can be seen in its historical context described in a related post [LINK]. And yet, as shown in another related post [LINK] , the claimed scientific basis for the fear of human caused ozone depletion is shown to be flawed and without empirical support in the observational data. The success of the ozone depletion scare and the Montreal Protocol therefore established that a sufficient level of fear in fear based activism overcomes weaknesses and flaws in the science that is claimed to validate the basis for the fear.
  12. The UN thus proceeded on this basis to replicate their Montreal Protocol success in climate change with a hastily convened Kyoto Protocol in the model of the Montreal Protocol, to ban the production and use of fossil fuels just as the Montreal Protocol had banned the production and use of Chlorofluorocarbon (CFC) that was claimed by scientists to be causing ozone depletion according to the Rowland Molina ozone depletion mechanism described in a related post [LINK] .
  13. However, there is, of course, a big difference between making refrigeration and hairspray somewhat more expensive and overhauling the fossil fueled energy infrastructure that gave us the industrial revolution and the high standard of living we enjoy today compared with the horse and buggy days. The idea that fossil fuels could be replaced with solar and wind power turned out to be superficial and poorly thought out by the UN bureaucrats involved.
  14. Their further bureaucratic errors led to an immensely complicated structure with the countries of the world divided into four different categories each with different climate action obligations that left all developing countries, even large consumers of fossil fuels such as India and China, without any climate action obligation. President Bush of the USA balked at this bureaucratic boondoggle and refused to sign the Kyoto Protocol. In response, the UN quietly shelved the Kyoto Protocol and then resurrected it as the UNFCCC.
  15. The UNFCCC contained the same structure as the Kyoto Protocol but in a different political stance such that it gave the UN greater control over its content. The fundamental problem faced by the Kyoto Protocol/UNFCCC proposals, however, was the immensity of the task of removing the source of energy that produced and sustained the “industrial economy” and the high standard of living now enjoyed by humans. This turned out to be a bigger issue than the CFC ban by orders of magnitude – a difference apparently overlooked by the UNEP in its assumption that the Montreal Protocol success could be replicated with its  climate change version in the Kyoto Protocol / UNFCCC. The UN was thus forced to respond to this problem either by down-scaling their demands or by scaling up the fear of climate change to force the fossil fuel issue. They chose the latter.
  16. This is the path that would eventually lead to the transformation of climate science into fear based activism and its gradual escalation until it became necessary to recruit school children as protesters and of the incarnation of Greta Thunberg as their messiah. It is thus that what began with Callendar as relief from the horrors of the Little Ice Age and described as an effect of fossil fuel combustion of the industrial economy as a scientific curiosity without activism and without a call for reduction in emissions to prevent warming, became escalated into fear based activism after the dramatic claims of extreme weather and sea level rise of the Hansen testimony [LINK], derived mostly not from realities of the current interglacial but from what had happened naturally 120,000 years ago in the prior interglacial [LINK] , and yet claimed to be too extreme to be natural and that therefore they were the creation of human activity in terms of fossil fuel emissions of the industrial economy.
  17. When the UN entered the scene to take over Hansen’s call for a ban on fossil fuel emissions, climate change was fully transformed from Callendar’s scientific curiosity to the UN’s ozone-style fear based activism. Faced with failure after failure in the “Conference of Parties” (COP), the UN was forced to raise the fear level and escalate activism until it got to the point when all pretense to science was abandoned and the climate movement was thus thrust into full activism mode.
  18. The Greta phenomenon in climate science is not a validation of its claimed scientific credentials but a validation of the absence of a scientific basis for activism against fossil fuel emissions.











  1. Congressional Testimony of Dr. James Hansen, June 23, 1988
    On June 23, 1988, James Hansen of the NASA Goddard Space Institute gave testimony to the U.S. Senate Committee on Energy and Natural Resources.
  2. Opening Statement to the Committee, by Dr. James Hansen, Director, NASA Goddard Institute for Space Studies: Mr. Chairman and committee members, thank you for the opportunity to present the results of my research on the greenhouse effect which has been carried out with my colleagues at the NASA Goddard Institute for Space Studies. I would like to draw three main conclusions. Number one, the earth is warmer in 1988 than at any time in the history of instrumental measurements. Number two, the global warming is now large enough that we can ascribe with a high degree of confidence a cause and effect relationship to the greenhouse effect. And number three, our computer climate simulations indicate that the greenhouse effect is already large enough to begin to effect the probability of extreme events such as summer heat waves.
  3. My first chart shows the global temperature over the period of instrumental records which is about 100 years. The present temperature is the highest in the period of record. The rate of warming in the past 25 years, as you can see on the right, is the highest on record. The four warmest years, as the Senator mentioned, have all been in the 1980s. And 1988 is so much warmer than 1987, that barring a remarkable and improbable cooling, 1988 will be the warmest year on the record.
  4. Now let me turn to my second point which is causal association of the greenhouse effect and the global warming. Causal association requires first that the warming be larger than natural climate variability and, second that the magnitude and nature of the warming be consistent with the greenhouse mechanism. These points are both addressed in my second chart. The observed warming during the past 30 years, which is the period when we have accurate measurements of atmospheric composition, is shown by the heavy black line in this graph. The warming is almost 0.4 degrees Centigrade by 1987 relative to climatology, which is defined as the 30-year mean, 1950 to 1980 and, in fact, the warming is more than 0.4 degrees Centigrade in 1988. The probability of a chance warming of that magnitude is about 1 percent. So with 99 percent confidence we can state that the warming during this time period is a real warming trend.
  5. The other curves in this figure are the results of global climate model calculations for three scenarios of atmospheric trace gas growth. We have considered several scenarios because there are uncertainties in the exact trace gas growth in the past and especially in the future. We have considered cases ranging from business as usual, which is scenario A, to draconian emission cuts, scenario C, which would totally eliminate net trace gas growth by the year 2000.
  6. The main point to be made here is that the expected global warming is of the same magnitude as the observed warming. Since there is only a 1 percent chance of an accidental warming of this magnitude, the agreement with the expected greenhouse effect is of considerable significance. Moreover, if you look at the next level of detail in the global temperature change, there are clear signs of the greenhouse gas effect. Observational data suggests a cooling in the stratosphere while the ground is warming. The data suggest somewhat more warming over land and sea ice regions than over open ocean, more warming at high latitudes than at low latitudes, and more warming in the winter than in the summer. In all of these cases, the signal is at best just beginning to emerge, and we need more data. Some of these details, such as the northern hemisphere high latitude temperature trends, do not look exactly like the greenhouse effect, but that is expected. There are certainly other climate factors involved in addition to the greenhouse effect.
  7. Altogether the evidence that the earth is warming by an amount which is too large to be a chance fluctuation and the similarity of the warming to that expected from the greenhouse effect represents a very strong case. In my opinion, that the greenhouse effect has been detected, and it is changing our climate now.
  8. Then my third point. Finally, I would like to address the question of whether the greenhouse effect is already large enough to affect the probability of extreme events, such as summer heat waves. As shown in my next chart, we have used the temperature changes computed in our global climate model to estimate the impact of the greenhouse effect on the frequency of hot summers in Washington, D.C. and Omaha, Nebraska. A hot summer is defined as the hottest one-third of the summers in the 1950 to 1980 period, which is the period the Weather Bureau uses for defining climatology. So, in that period the probability of having a hot summer was 33 percent, but by the 1990s, you can see that the greenhouse effect has increased the probability of a hot summer to somewhere between 55 percent and 70 percent in Washington according to our climate model simulations. In the late 1980s, the probability of a hot summer would be somewhat less than that. You can interpolate to a value of something like 40 to 60 percent.
  9. I believe that this change in the frequency of hot summers is large enough to be noticeable to the average person. So, we have already reached a point that the greenhouse effect is important. It may also have important implications other than for creature comforts.
  10. My last chart shows global maps of temperature anomalies for a particular month, July, for several different years between 1986 and 2029, as computed with our global climate model for the intermediate trace gas scenario B. As shown by the graphs on the left where yellow and red colors represent areas that are warmer than climatology and blue areas represent areas that are colder than climatology, at the present time in the 1980s the greenhouse warming is smaller than the natural variability of the local temperature. So, in any given month, there is almost as much area that is cooler than normal as there is warmer than normal. A few decades in the future, as shown on the right, it is warm almost everywhere.
  11. However, the point that I would like to make is that in the late 1980s and in the 1990s we notice a clear tendency in our model for greater than average warming in the southeast United States and the Midwest. In our model this result seems to arise because the Atlantic Ocean of the coast of the United States warms more slowly than the land. This leads to high pressure along the east coast and circulation of warm air north into the Midwest or southeast. There is only a tendency for this phenomenon. It is certainly not going to happen every, and climate models are certainly an imperfect tool at this time. However, we conclude that there is evidence that the greenhouse effect increases the likelihood of heat wave drought situations in the southeast and Midwest United States even though we cannot blame a specific drought on the greenhouse effect.
  12. Therefore, I believe that it is not a good idea to use the period 1950 to 1980 for which climatology is normally defined as an indication of how frequently droughts will occur in the future. If our model is approximately correct, such situations may be more common in the next 10 to 15 years than they were in the period 1950 to 1980.
  13. Finally, I would like to stress that there is a need for improving these global climate models, and there is a need for global observations if we’re going to obtain a full understanding of these phenomena. That concludes my statement, and I’d be glad to answer questions if you’d like.
  14. The prepared statement of Dr. Hansen follows
  15. The Greenhouse Effect: Impacts on Current Global Temperature and Regional Heat Waves; Presented to United States Senate Committee on Energy and Natural Resources, June 23, 1988. This statement is based largely on recent studies carried out with my colleagues S. Lebedeff, D. Rind, I. Fung, A. Lacis, R. Ruedy, G. Russell, and P. Stone at the NASA Goddard Institute for Space Studies.
  16. My principal conclusion are: (1) the earth is warmer in 1988 than at any time in the history of instrumental measurements, (2) the global warming is now sufficiently large that we can ascribe with a high degree of confidence a cause and effect relationship to the greenhouse effect, and (3) in our computer climate simulations the greenhouse effect now is already large enough to begin to effect the probability of occurrence of extreme events such as summer heat waves; the model results imply that heat wave/drought occurrences in the Southeast and Midwest United States may be more frequent in the next decade than in climatological (1950 – 1980) statistics.
  17. Current global temperatures: Present global temperatures are the highest in the period of instrumental records. The rate of global warming in the past two decades is higher than at any earlier time in the record. The four warmest years in the past century all have occurred in the 1980s. The global temperature in 1988 up to June 1 is substantially warmer than the like period in any previous year in the record. … The most recent two seasons (Dec.-Jan.-Feb. and Mar.-Apr.-May 1988) are the warmest in the entire record. The first five months are so warm globally that we conclude that 1988 will be the warmest year on record unless there is a remarkable, improbable cooling in the remainder of the year.
  18. Relationship of global warming and greenhouse effect
    Causal association of current global warming with the greenhouse effect requires determination that (1) the warming is larger than natural climate variability, and (2) the magnitude and nature of the warming is consistent with the greenhouse warming mechanism. Both of these issues are addressed quantitatively in Fig. 3, which compares recent observed global temperature change with climate model simulations of temperature changes expected to result from the greenhouse effect.
  19. The present observed global warming is close to 0.4 degrees C, relative to ‘climatology,’ which is defined as the thirty-year (1951 – 1980) mean. A warming of 0.4 degrees C is three times larger than the standard deviation of annual mean temperatures in the 30-year climatology. The standard deviation of 0.13 degrees C is a typical amount by which the global temperature fluctuates annually about its 30-year mean; the probability of a chance warming of three standard deviations is about 1 percent. Thus, we can state with about 99 percent confidence that current temperatures represent a real warming trend rather than a chance fluctuation over the 30-year period.
  20. We have made computer simulations of the greenhouse effect for the period since 1958, when atmospheric CO2 began to be measured accurately. A range of trace gas scenarios is considered so as to account for moderate uncertainties in trace gas histories and larger uncertainties in future trace gas growth rates. The nature of the numerical climate model used for these simulations is described in attachment A. There are major uncertainties in the model, which arise especially from assumptions about (1) global climate sensitivity and (2) heat uptake and transport by the ocean, as discussed in attachment A. However, the magnitude of temperature changes computed with our climate model in various test cases is generally consistent with a body of empirical evidence and with sensitivities of other climate models.
  21. The global temperature change simulated by the model yields a warming over the past 30 years similar in magnitude to the observed warming. In both the observations and model, the warming is close to 0.4 degrees C by 1987, which is the 99 percent confidence level. It is important to compare the spatial distribution of observed temperature changes with computer model simulations of the greenhouse effect, and also to search for other global changes related to the greenhouse effect, for example, changes in ocean heat content and sea ice coverage. As yet, it is difficult to obtain definitive conclusions from such comparisons, in part because the natural variability of regional temperatures is much larger than that of global mean temperature. However, the climate model simulations indicate that certain gross characteristics of the greenhouse warming should begin to appear soon, for example, somewhat greater warming at high latitudes than at low latitudes, greater warming over continents than over oceans, and cooling in the stratosphere while the troposphere warms. Indeed, observations contain evidence for all these characteristics, but much more study and improved records are needed to establish the significance of trends and to use the spatial information to understand better the greenhouse effect. Analyses must account for the fact that there are climate change mechanisms at work, besides the greenhouse effect; other anthropogenic effects, such as changes in surface albedo and tropospheric aerosols, are likely to be especially important in the Northern Hemisphere.
  22. We can also examine the greenhouse warming over the full period for which global temperature change has been measured, which is approximately the past 100 years. On such a longer period the natural variability of global temperature is larger; the standard deviation of global temperature for the past century is 0.2 degrees C. The observed warming over the past century is 0.6 – 0.7 degrees C. Simulated greenhouse warming for the past century is in the range of 0.5 to 1.0 degrees C, depending upon various modeling assumptions. Thus, although there are greater uncertainties about climate forcings in the past century than in the past 30 years, the observed and simulated greenhouse warming are consistent on both these time scales.
  23. Conclusion
    Global warming has reached a level such that we can ascribe with a high degree of confidence a cause and effect relationship between the greenhouse effect and the observed warming. Certainly further study of this issue must be made. The detection of a global greenhouse signal represents only a first step in analysis of the phenomenon. With regard to greenhouse impacts on summer heat waves, global climate models are not yet sufficiently realistic to provide reliable predictions of the impact of greenhouse warming on detailed regional climate patterns. However, it is useful to make initial studies with state-of-the-art climate models; the results can be examined to see whether there are regional climate change predictions which can be related to plausible physical mechanisms. At the very least, such studies help focus the work needed to develop improved climate models and to analyze observed climate change.
  24. One prediction of regional climate change which has emerged in such climate model studies of the greenhouse effect is a tendency for mid-latitude continental drying in the summer (references 3, 4, 5). Dr. Manabe will address this important issue in his testimony today. Most of these studies have been for the case of doubled atmospheric CO2, a condition which may occur by the middle of the next century.
  25. Our studies during the past several years at the Goddard Institute for Space Studies have focused on the expected transient climate change during the next few decades, as described in the attachment to my testimony. Typical results from our simulation for trace gas scenario B … shows computed July temperature anomalies in several years between 1986 and 2029. In the 1980s, the global warming is small compared to the natural variability of local monthly mean temperatures; thus, the area with cool temperatures in a given July is almost as great as the area with warm temperatures. However, within about a decade the area with above normal temperatures becomes much larger than the area with cooler temperatures.
  26. The specific temperature patterns for any given month and year should not be viewed as predictions for that specific time, because they depend upon unpredictable weather fluctuations. However, characteristics which tend to repeat warrant further study, especially if they occur for different trace gas scenarios. We find a tendency in our simulations of the late 1980s and the 1990s for greater than average warming in the Southeast and Midwest United States. These areas of high temperatures are usually accompanied by below normal precipitation.
  27. Examination of the changes in sea level pressure and atmospheric winds in the model suggests that the tendency for larger than normal warming in the Midwest and Southeast is related to the ocean’s response time; the relatively slow warming of surface waters in the mid-Atlantic off the Eastern United States and in the Pacific off California tends to increase sea level pressure in those ocean regions and this in turn tends to cause more southerly winds in the eastern United States and more northerly winds in the western United States. However, the tendency is too small to be apparent every year; in some years in the 1990s, the eastern United States is cooler than climatology (the control run mean).
  28. It is not possible to blame a specific heatwave/drought on the greenhouse effect. However, there is evidence that the greenhouse effect increases the likelihood of such events; our climate model simulations for the late 1980s and the 1990s indicate a tendency for an increase of heatwave/drought situations in the Southeast and Midwest United States. We note that the correlations between climate models and observed temperatures are often very poor at subcontinental scales, particularly during Northern Hemisphere summer (reference 7). Thus, improved understanding of these phenomena depends upon the development of increasingly realistic global climate models and upon the availability of global observations needed to verify and improve the models.
  29. With thanks to David Burton for maintaining the text of the Hansen testimony on his site at [LINK] .







  1. The phrase “greenhouse effect” to describe long wave absorption/radiation by atmospheric CO2 implies that this effect has something to do with greenhouses. It is true that large a quantity of carbon dioxide is inserted into greenhouses to maintain CO2 levels of 1000 ppm to 2000 ppm but elevated levels of CO2 is used in greenhouses to supply photosynthesis demands of the plants and not for temperature control. Temperature control is achieved with heaters and during daylight, also by the glass walls and roof that prevent convection. Related post   [LINK].
  2. A point stressed more than once by Hansen is the very high temperature in the year 1988 described as much hotter than 1987 and as the highest in the instrumental record going back 100 years. The high temperature in 1988 is also described as a harbinger of much hotter times to come. The GIF image in Figure 1 above shows UAH tropospheric temperatures for each calendar month. The GIF animation cycles through the twelve calendar months. Here we can see that in the summer and early autumn months of July, August, and September, the Hansen emphasis on 1988 is defensible at least in terms of being higher than at any time in the previous decade but even there it does not appear to be a harbinger of higher temperatures to come in the short term as lower temperatures immediately follow. In any case, the year 1988 does not stand out as a high temperature event in any of the other nine calendar months.
  3. It should also be pointed out that Hansen’s excessive reliance on alarming temperature events is inconsistent with the theory of AGW by way of long wave absorption by atmospheric CO2 which relates only to long term trends and not to temperature events which are known to contain large natural short term extremes. For example, the extreme El Nino events in the years 1998 and 2016 are clearly visible as high temperature events in Figure 1 but they have no AGW implication although NASA (and climate scientists in general) have repeatedly used the high temperature in 2016 as evidence of AGW and the dangers of “human caused climate change”.
  4. The statement that “our computer climate simulations indicate that the greenhouse effect is already large enough to begin to affect the probability of extreme events such as summer heat waves” is inconsistent with patterns seen in the daily station data. These data, for both hemispheres (USA and Australia) show a clear, consistent, and persistent pattern that indicates that the warming trend derives mostly from rising nighttime daily low temperatures (TMIN) and not from daytime daily high temperatures (TMAX). These data also show that the warming is found mostly in the winter months and not in the summer months. Details of the data analysis for these patterns may be found in related posts on this site [LINK] [LINK]  .
  5. However, the AGW issue is not whether it is warming but whether the warming if any is caused by fossil fuel emissions and whether the prescribed climate action of reducing fossil fuel emissions will change the rate of warming. Hansen’s approach to this critical issue is stated as “Causal association requires first that the warming be larger than natural climate variability and, second that the magnitude and nature of the warming be consistent with the greenhouse mechanism“. However, that the warming is larger than natural variability and that the “nature” of warming is consistent with the greenhouse mechanism do not constitute empirical evidence particularly so since these subjective patterns were derived from climate models which contain the theory. It is not possible to test theory with a device that assumes the theory. It must be shown in the observational data, without the use of climate models, that the observed rise in atmospheric CO2 is causally related to fossil fuel emissions and that the observed rate of warming is causally related to rising atmospheric CO2 concentration. Hansen does not present any such evidence.
  6. The relationship between emissions and atmospheric CO2 concentration is studied in four related posts [LINK] [LINK] [LINK] [LINK] . No evidence is found to relate changes in atmospheric CO2 concentration to fossil fuel emissions and it is shown that the flow accounting of the carbon cycle that relates rising atmospheric CO2 to emissions does so with the use of circular reasoning.
  7. In terms of AGW theory, the relationship between atmospheric CO2 concentration and the rate of warming is established with the so called climate sensitivity parameter (ECS) derived from the required linear relationship between temperature and log(atmospheric CO2) but the value of this relationship, even in climate models, suffers from uncertainty with values ranging from ECS<2 to ECS>4. When observational data are used in the estimation the uncertainty becomes much larger as described in related posts [LINK] [LINK] [LINK] [LINK] .  In a parody it is shown that the methodology used to relate warming to CO2 also relates homicides to CO2 but with stronger statistical confidence [LINK] .
  8. Climate science has responded to its uncertainty problem in relating warming to atmospheric CO2 concentration by proposing a relationship between cumulative emissions and surface temperature. It has been shown that there is an almost perfect “proportionality” (correlation) between cumulative emissions and temperature. The regression coefficient of this relationship for surface temperature as a function of cumulative emissions is called the Transient Climate Response to Cumulative Emissions (TCRE). It has been proposed by Knutti and others that the climate science should move past the problematic ECS and adopt the TCRE as the appropriate way to relate warming to emissions. And in fact, climate action policies in terms of mitigation pathways derived from a carbon budget for any level of warming are derived from the TCRE. Thus, climate science now claims to have the empirical evidence from observational data that relates warming to emissions.
  9. However, as shown in a related post, the TCRE “proportionality” suffers from a fatal statistical flaw because the correlation has neither time scale nor degrees of freedom [LINK] . When finite time scales are introduced and degrees of freedom are created for the statistical test, the correlation disappears [LINK] . A parody shows that, not just emissions, but any  time series that contains mostly positive values will produce the high “proportionality” seen in the TCRE [LINK] .
  10. In response to Hansen’s vague responses to empirical evidence in terms of  “Causal association requires first that the warming be larger than natural climate variability and, second that the magnitude and nature of the warming be consistent with the greenhouse mechanism“, we propose that this argument is insufficient because the results of rigorous statistical tests of the observational data do not show the relationship between emissions and warming implied by these vague and subjective generalities.
  11. With regard to the statement about stratospheric cooling stated as “Moreover, if you look at the next level of detail in the global temperature change, there are clear signs of the greenhouse gas effect. Observational data suggests a cooling in the stratosphere while the ground is warming”. Climate models do indeed show that lower stratospheric temperature is indeed inversely responsive to tropospheric temperature in the GHG effect of CO2 because of the longwave energy removed by CO2 from earth’s radiation. However, the direction of long term trends by itself cannot be used to infer causation as demonstrated in a large collection of spurious correlations by Tyler Vigen [LINK] . To infer causation, the correlation must be shown at the time scale of interest. A related post shows that there is no evidence in the observational data to indicate that either tropospheric warming or lower stratospheric cooling is responsive to changes in LN(CO2) or that stratospheric cooling is responsive to tropospheric warming, at an annual time scale. These result do not support the theory of causation that links stratospheric cooling to tropospheric warming as claimed by Hansen. Two related posts on the effect of atmospheric CO2 on temperature are relevant to these findings [LINK] [LINK] .
  12. CONCLUSION: Claims by Hansen in the testimony of the extreme temperature in 1988 as a harbinger of hotter years to come, of summer heat waves caused by AGW, of proof of the GHG effect of CO2 in terms of observed variability greater than what is assumed to be natural and of the warming behavior, and the additional proof of the GHG effect in terms of stratospheric cooling, are not consistent with the observational data. 














bandicam 2019-05-01 16-57-19-983









  1. Figure 1 is a graphical representation of a large number of climate sensitivity values from the literature 1970-2018, both purely empirical (unconstrained) and constrained by climate models. The Charney 1979 estimate of ECS=3 with 90% confidence interval of ECS=[1.5, 4.5] is sanctioned by the IPCC and widely accepted in climate science. It is used here to compare all values in Figure 1 against this interval.
  2. Figure 2 is a comparison of all the reported ECS values in Figure 1 against the Charney/IPCC interval ECS=[1.5, 4.5]. In the GT section of Figure 2 we find that in the full sample 1963-2018, only 20% of the ECS values shown in Figure 1 were greater than the the Charney interval ECS=[1.5, 4.5]. This rate is somewhat lower in the early period 1963-2001 at just 13% but much higher in the later period 2001-2018 at 30%. It appears that there has been a gradual inflation of ECS estimates in the literature over the period 1963-2018.
  3. In the LT section of Figure 2 we find that in the full sample 1963-2018, 18% of the ECS values shown in Figure 1 were less than the the Charney interval ECS=[1.5, 4.5]. This rate is somewhat lower in the early period 1963-2001 at just 13% but somewhat higher in the later period 2001-2018 at 23%.
  4. The EITHER section of the chart in Figure 2 is test of whether the reported ECS value lies within the Charney interval. The first column displays the sum of the GT and LT values and the second column, computed as 100% minus the sum, is the percent of reported ECS values that were within the Charney interval. Here we find good agreement of reported values with the Charney interval with 62% of the reported values within the interval in the full sample period 1963-2018. However, the agreement appears to be driven primarily by early values 1963-2001 with 75% within the interval. The agreement is less impressive in the later period 2001-2018 with less than half or 48% of the reported values within the Charney/IPCC interval of ECS=[1.5,4.5].
  5. A possible reason for the gradual departure from the Charney interval over time is that both the Charney and Manabe estimates of old were derived from computer models with little if any constraints of observational data. This approach to climate sensitivity has gradually changed over time with both paleo and observational data used directly for ECS estimates. Many of these estimates are of course “constrained” by climate models but lately the trend has been mostly to empirical estimates. This evolution of ECS estimation methodology is consistent with the observed divergence of ECS estimates from Charney’s climate model derived interval.
  6. It should also be considered that the high rate of agreement with the Charney interval (particularly in older estimates) derives in large part from the great width of this interval from ECS=1.5 to ECS=4.5. The carbon budget and climate action implications of the two ends are so different that the interval loses all value as a tool for formulating climate action plans. The Charney interval is not very useful in that context because of its large span which in turn also serves to show good agreement with a large and varied set of climate sensitivity estimates.
  7. In fact the large span of the Charney climate sensitivity interval of ECS=[1.5, 4.5] traverses significant differences in carbon budget and climate action options and possibilities. This interval is not useful information but rather an admission of the absence of information. It is not possible for climate science to propose climate action options without sensitivity information and the IPCC climate sensitivity range is a useless range in that regard and perhaps an inadvertent admission by the IPCC that though we urge and promote climate action, we do not have the information we need to formulate climate action plans.
  8. A related issue in constructing climate action plans is a statistical weakness in the TCRE parameter that forms the basis of computing carbon budgets in terms of cumulative emissions. This issue is presented in a related post [LINK] .








  1. Box, G. (1994). Time series analysis: forecasting and control. . Englewood Cliffs, NJ: : Prentice Hall.
  2. Caldeira, K. (2003). Climate sensitivity uncertainty and the need for energy without CO2 emission. Science, 299.5615 (2003): 2052-2054.
  3. Callendar, G. (1938). The artificial production of carbon dioxide and its influence on temperature.” . Quarterly Journal of the Royal Meteorological Society, 64.275 (1938): 223-240.
  4. Callendar, G. (1958). On the amount of carbon dioxide in the atmosphere. Tellus, 10.2 (1958): 243-248.
  5. Cess, R. (1974). Radiative transfer due to atmospheric water vapor: Global considerations of the earth’s energy balance.” . Journal of Quantitative Spectroscopy and Radiative Transfer , 14.9 (1974): 861-871.
  6. Charney, J. (1979). Carbon dioxide and climate: a scientific assessment. Washington DC: National Academy of Sciences.
  7. Christy/Spencer. (2018). UAH-CDC MSU dataset v6. . Retrieved from UAH:
  8. CSIRO. (2017). CSIRO. Retrieved from CSIRO:
    Curry, J. (2011). Reasoning about climate uncertainty. Climatic Change, 108.4 (2011): 723.
  9. Curry/Webster. (2011). Climate science and the uncertainty monster. Bulletin of the American Meteorological Society, 92.12 (2011): 1667-1682.
  10. Danabasoglu, G. (2009). Equilibrium climate sensitivity: Is it accurate to use a slab ocean model? Journal of Climate , 22.9 (2009): 2494-2499.
  11. Draper&Smith. (1998). Applied Regression Analysis. . Wiley.
  12. Hansen, B. (1992). Testing for parameter instability in linear models. Journal of policy Modeling , 14.4 (1992): 517-533.
  13. Hansen-Lacis. (1984). Climate sensitivity: Analysis of feedback mechanisms. Climate processes and climate sensitivity, 130-163.
  14. IPCC. (2007). IPCC AR4 The Physical Science Basis. Retrieved 2017, from IPCC:
  15. IPCC. (2013). AR5 The Physical Science Basis. Retrieved 2017, from IPCC:
  16. Keeling, C. (1978). The Influence of the Mauna Loa Observatory on the Development of Atmospheric CO2 Research. San Diego: Scripps Institution of Oceanography, University of California San Diego.
  17. Keeling, C. (1982). Measurements of the concentration of carbon dioxide at Mauna Loa Observatory, Hawaii. Carbon dioxide review.
  18. Keeling, C. (1986). Reassessment of late 19th century tmospheric carbon dioxide variations. Tellus, 38B: 87-105.
  19. Kuder, G. (1937). The theory of the estimation of test reliability. Psychometrika, 2.3(1937): 151-160.
  20. Lacis, A. (2010). Atmospheric CO2: Principal control knob governing Earth’s temperature. Science , 330.6002 (2010): 356-359.
  21. Munshi, J. (2017-5). Correlation of Regional Warming with Global Emissions. SSRN,
  22. Munshi, J. (2018). From Equilibrium Climate Sensitivity to Carbon Climate Response. SSRN,
  23. Munshi, J. (2018). Uncertainty in Empirical Climate Sensitivity Estimates 1850-2017. SSRN,
  24. Scripps. (2017). Scripps. Retrieved from CO2:
  25. Shumway, R. (2011). Time series analysis. . NY: Springer .
  26. Stainforth, D. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature , 433.7024 (2005): 403.
  27. Wigley, T. (1983). The pre-industrial carbon dioxide level. Climate Change, 5: 315-320.
  28. WMO. (1983). CO2 Concentrations from pre-industrial times. Geneva: WMO.