Reject NCA5


Ventura Photonics Climate Post 33, VPCP 033.1


May 3, 2024


Roy Clark PhD


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Summary


The claim by the US Global Change Research Program (USGCRP) in the Fifth National Climate Assessment (NCA5) that the observed increase in atmospheric greenhouse gases has caused global warming and an increase in ‘extreme weather events’ is fraudulent. It is based on the pseudoscience of radiative forcings, feedbacks and climate sensitivity that create spurious warming in the climate models used by USGCRP.


Congress should reject NCA5, shut down the USGCRP and dismantle both the multi-trillion dollar climate fraud and the disastrous Net Zero energy policy that has been justified by using the fraudulent climate model results.



A Failed Mission


The USGCRP was established by Congress in 1990 'to coordinate federal research and investments in understanding the forces shaping the global environment, both human and natural, and their impacts on society’.


It has failed in its mission by ignoring the natural causes of climate change. Floods, droughts, wildfires and other ‘extreme weather events’ are caused by natural weather conditions including downslope winds, high pressure domes and ocean oscillations that are not influenced by an increase in the atmospheric concentration of greenhouse gases. The USGCRP has blindly accepted the pseudoscientific climate modeling approach used by the UN Intergovernmental Panel on Climate Change (IPCC) without any attempt at independent model validation. The mission of the IPCC is 'to assess the scientific, technical and socioeconomic information relevant for the understanding of the risk of human-induced climate change.' This is based on the a-priori assumption that human activities are causing CO2 induced global warming. The IPCC is a political organization, not a scientific one. In the IPCC climate assessments, the science is distorted to match the political narrative. There is also a fundamental conflict of interest within the USGCRP. The same climate modeling groups are involved with both the IPCC and the USGCRP. These climate groups have used the USGCRP to feed fraudulent climate model results to Congress and ensure a continued flow of funds to solve a nonexistent problem.


The starting point for any realistic climate assessment is quite straightforward:


Since 1800, the atmospheric concentration of CO2 has increased by approximately 140 parts per million (ppm), from 280 to 420 ppm [Keeling, 2023]. This has produced a decrease near 2 W m-2 in the longwave IR (LWIR) flux emitted to space within the spectral region of the CO2 emission bands. There has also been a similar increase in the downward LWIR flux from the lower troposphere to the surface [Harde, 2017]. At present, the annual average increase in CO2 concentration is about 2.4 ppm per year. This produces an annual increase in the downward LWIR flux to the surface of approximately 0.034 W m-2 per year or 34 mW m-2 per year (mW = milliWatt =1/1000 Watt).


The USGRP shall explain to Congress, using quantitative, time dependent energy transfer analysis how these changes in flux have changed the earth’s climate. Specifically:


1) How has the absorption of 2 W m-2 by the CO2 bands changed the temperature of the troposphere?

2) How has the 2 W m-2 increase in the downward LWIR flux to the surface changed ocean surface temperatures?

3) How has the 2 W m-2 increase in the downward LWIR flux to the surface changed land surface temperatures?

4) How does an increase of 34 mW m-2 per year in downward LWIR flux to the surface increase the frequency and intensity of ‘extreme weather events’?


The short answer is that any temperature increases produced by these changes in LWIR flux are ‘too small to measure’, nor can there be any changes in ‘extreme weather events’.


The small amount of additional heat released into the troposphere by the increase in greenhouse gases is reradiated back to space by wideband LWIR emission. At the surface, any small increase in temperature produced by the increase in greenhouse gases is too small to measure in the normal daily and seasonal variations in surface and surface air temperatures.


A hypothetical doubling of the atmospheric CO2 concentration from 300 to 600 ppm produces a small decrease in the daily rate of LWIR cooling of the troposphere that may reach +0.08 °C per day [Feldman et al, 2008, Iacono et al, 2008, Ackerman, 1979]. At an average lapse rate (change in temperature with altitude) of -6.5 °C per kilometer, an increase in temperature of +0.08 °C is produced by a decrease in altitude of 12 meters. This is equivalent to riding an elevator down four floors. At present we are only halfway towards a CO2 doubling, so we only need to ride the elevator down two floors to experience all of the climate change since 1800.



A Well Established Fraud


There are three parts to the climate fraud. First, starting in the nineteenth century climate energy transfer was oversimplified using the equilibrium climate assumption. The time dependent energy transfer processes that determine the surface temperature were replaced by average values. This created global warming as a mathematical artifact when the CO2 concentration was increased in the early steady state air column climate models. Later, the coupled GCM atmosphere-ocean models were simply ‘tuned’ to match a global mean temperature record. Second, there was mission creep. As funding was reduced for NASA space exploration and US Department of Energy (DOE) nuclear programs, climate modeling became an alternative source of revenue [Hansen et al, 2000]. The oversimplified climate models were accepted without question. A paycheck was more important. Third, there was a deliberate decision by various outside interests, including environmentalists and politicians to exploit the fictional climate apocalypse to further their own causes [Hecht, 2007]. The climate models used to perpetuate the climate fraud are no longer based on science. They are political models based on the pseudoscience of radiative forcings, feedbacks and climate sensitivity that are ‘tuned’ to meet political goals. The climate modelers, including those associated with the USGCRP are paid to provide the climate lies and propaganda needed to justify public policy that restricts the use of fossil fuels. Climate science has degenerated beyond dogma into the Imperial Cult of the Global Warming Apocalypse. The climate modelers that provide the results used by the USGCRP are not scientists, they are prophets of the Imperial Cult. They have chosen to believe that the results created by the climate models are real. NCA5 is not a scientific report, it is a political document designed to support misguided energy policies that are already causing significant economic hardship to the people of the United States.


When it was established by Congress in 1990, the USGCRP simply copied the approach taken by the IPCC and accepted the results created by the early climate models without question. Since it was founded in 1988, the IPCC has relied on the results from climate models based on radiative forcings, feedbacks and climate sensitivity [Ramaswamy et al, 2019]. The climate modeling fraud was established earlier, between 1967 and 1981 mainly by the work of Manabe’s group at the US Weather Bureau and Hansen’s group at NASA [Clark, 2024]. This established the equilibrium climate fantasy land where the climate modelers play their computer games. Instead of Xboxes, they use supercomputers. The final part of the part of the climate modeling fraud, the use of radiative forcings to ‘attribute’ an increase in ‘extreme weather events’ to the increase in atmospheric greenhouse gases was introduced in the Third IPCC Climate Assessment in 2001. The USGCRP has continued to ignore physical reality and still relies on the results from the fantasy equilibrium climate models published in the IPCC Climate Assessments.



NCA5: A Pack of Lies


In the recently released Fifth National Climate Assessment Report, NCA5 [Crimmins et al, 2023] the USGCRP has made a series of absurd claims about the effects of human activities on the earth’s climate. For example, Chapter 3, Earth System Processes contains five ‘Key Messages’ that are based on an irrational belief in the climate model results published by the IPCC.


Key Message 3.1

Human activities—primarily emissions of greenhouse gases from fossil fuel use—have unequivocally caused the global warming observed over the industrial era. Changes in natural climate drivers had globally small and regionally variable long-term effects over that period. Key Message 3.2

Recent improvements in the understanding of how climate feedbacks vary across timescales have narrowed the estimated likely range of warming expected from a doubling of atmospheric carbon dioxide by 50% to between 4.5°F and 7.2°F (high confidence).

Key Message 3.3

A number of scientific developments have enabled deeper understanding of climate processes and their responses to human influence. Observational records have lengthened, and new observing systems have come online. New scenarios of socioeconomic development, and their associated emissions and land-use changes, drive updated climate projections from Earth system models. Large ensemble simulations from multiple models have enabled scientists to better distinguish anthropogenic climate change from natural climate variability. More targeted model evaluation techniques are using observations to narrow the estimated range of future climatic changes. Finally, advances in methods for extreme event attribution enabled scientists to estimate the contributions of human influence to some types of individual extreme events in near-real-time.

Key Message 3.4

Human activities cause changes throughout the Earth system, including the land surface, cryosphere, ocean and atmosphere, and carbon and water cycles. The magnitude, and for some processes the direction, of these changes can vary across regions, including within the US. These changes also occur against a background of substantial natural climate variability.

Key Message 3.5

Human activities are affecting climate system processes in ways that alter the intensity, frequency, and/or duration of many weather and climate extremes, including extreme heat, extreme precipitation and flooding, agricultural and hydrological drought, and wildfire (medium to high confidence)”.


These ‘Key Messages’ provide the foundation for the NCA5 report and have been blindly accepted and used without independent validation by the authors of NCA5.


These messages are based on the results shown in NCA5 Figures 3.1, 3.2 and 3.3 adapted from the Working Group 1 Report, WG1, that is part of the Sixth IPCC Climate Assessment, AR6, [IPCC, 2021]. These are shown here as Figures 1, 2 and 3. Figure 3.1 claims that the observed increase in temperature (in °F) can be attributed to a decrease in LWIR flux emitted at the top of the atmosphere produced by the increase in ‘greenhouse gases’. This has been partially compensated by changes in aerosol concentration that reflect more sunlight back to space. These changes in flux at TOA are called radiative forcings. Specifically, it is claimed that the decrease in LWIR flux at TOA changes the energy balance of the earth and that the surface temperature increases to restore the flux balance at TOA. The introduction to Chapter 7 of AR6, WG1 ‘The Earth’s energy budget, climate feedbacks, and climate sensitivity’ [IPCC, 2021] starts:


This chapter assesses the present state of knowledge of Earth’s energy budget, that is, the main flows of energy into and out of the Earth system, and how these energy flows govern the climate response to a radiative forcing. Changes in atmospheric composition and land use, like those caused by anthropogenic greenhouse gas emissions and emissions of aerosols and their precursors, affect climate through perturbations to Earth’s top-of-atmosphere energy budget. The effective radiative forcings (ERFs) quantify these perturbations, including any consequent adjustment to the climate system (but excluding surface temperature response). How the climate system responds to a given forcing is determined by climate feedbacks associated with physical, biogeophysical and biogeochemical processes. These feedback processes are assessed, as are useful measures of global climate response, namely equilibrium climate sensitivity (ECS) and the transient climate response (TCR).


A more concise summary was provided by Knutti and Hegerl [2008]:


When the radiation balance of the Earth is perturbed, the global surface temperature will warm and adjust to a new equilibrium state.


This is pseudoscientific nonsense. There earth is never in thermal equilibrium [Clark, 2023, Essex et al, 2007]. The small amount of additional heat released into the troposphere by the increase in greenhouse gases is radiated back to space as wideband LWIR emission. It does not change the energy balance of the earth, nor does it increase the surface temperature. A closer inspection of NCA5 Figure 3.1 reveals a distinct peak in the temperature record near 1940 and an earlier minimum near 1910. This shows the influence of the Atlantic Multidecadal Oscillation (AMO) on the temperature record [AMO, 2022]. There is no requirement for an exact energy balance between the solar heating of the oceans and the surface cooling. This produces natural quasi-periodic variations in ocean surface temperature that are known as ocean oscillations. These include the AMO, the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and the Pacific Decadal Oscillation (PDO). They are related to changes in surface evaporation and ocean gyre circulation produced by natural variations in wind speed. They have no connection to any increase in atmospheric greenhouse gases. Radiative forcings do not ‘drive the climate’.





Figure 1: NCA5 Fig. 3.1, observed warming 2010 to 2019 relative to 1850-1900 and its attribution to climate drivers (radiative forcings). Adapted from Figures SPM.2, 2.11c and 7.8 in IPCC AR6 WG1 [2021]



The changes in radiative forcings alone are insufficient to cause the observed temperature changes. They need help from feedbacks that may either amplify or reduce the effect of the forcings. This is shown in Figure 2. The two main feedbacks are the Planck feedback and the water vapor feedback. First, as the surface temperature warms for any reason, more LWIR radiation is emitted to space. The value for the Planck feedback from AR6 is 3.2 W m-2 per °C. Second, as the greenhouse gas concentration increases, it is assumed that the water vapor concentration also increases and this amplifies the initial temperature increase. This assumption can be traced back to the second of two mathematical artifacts created by the 1967 climate model developed by Manabe and Wetherald (M&W) [1967]. When the CO2 concentration was increased in their oversimplified one dimensional radiative convective (1-D RC) steady state model, it was assumed that the surface and air layer temperatures increased until a new steady state was reached. This created warming as a mathematical artifact in their calculations. In order to match the average measured atmospheric temperature profile, they imposed a fixed relative humidity (RH) distribution on the air layers in their model. As the temperature increased, the absolute water vapor concentration had to increase to maintain the fixed RH. This created water vapor feedback as a second mathematical artifact in their 1-D RC model. Using this approach, they calculated a 2.9 °C increase in equilibrium surface temperature for a CO2 doubling from 300 to 600 ppm for clear sky conditions. In the real atmosphere, the daily and seasonal variations in both temperature and humidity near the surface are sufficiently large that the small change in downward LWIR flux to the surface produced by a CO2 doubling cannot have any measurable effect on temperature or humidity [Clark, 2024, Clark and Rörsch, 2023]. The small changes in temperature calculated at each step in their time integration algorithm cannot accumulate in the real atmosphere. They are too small to detect in the normal daily and seasonal temperature cycles. A steady state climate has no basis in physical reality.





Figure 2: NCA5 Fig. 3.2, the magnitude of the feedbacks used to modify the response of the climate models to the radiative forcings. Adapted from Figure TS.17 in IPCC AR6 WG1 [2021].



M&W went on to incorporate their 1967 mathematical artifacts into every unit cell of their ‘highly simplified’ 1975 global circulation model (GCM) [M&W, 1975]. In this model, a CO2 doubling produced an average increase in temperature of 2.9 °C. However, this should be compared to the 2.4 °C increase for average cloudiness reported for the 1967 M&W model. The results from this GCM model were used by the Charney Report [1979] to claim that a CO2 doubling would produce an increase in surface temperature between 2 and 3.5 °C (3.6 to 6.3 °F). This provided a fraudulent warming benchmark for future climate fantasy models.


Later, Manabe and Stouffer extended the MW75 model to include a mixed ocean layer. They ignored the surface energy transfer processes that determine the ocean surface temperature. In particular, the increase in downward LWIR flux at the surface is fully coupled to the wind driven evaporation. For a quadrupling of the CO2 concentration, they obtained an increase in ocean temperature of 4.1 °C. The correct result should be 'too small to measure' [Manabe and Stouffer, 1979, 1980]


M&W and later climate modelers also ignored the instabilities introduced into a global circulation model by the large number of coupled non-linear equations that had to be solved. Lorenz [1963, 1973] found that such solutions were unstable, even for a simple convection model with 3 equations. A practical limit for weather forecasting was 12 days ahead. This work should have made it clear that such GCMs had no predictive capabilities over the time scales associated with climate change.


The increase in temperature produced by a doubling of the CO2 concentration from 280 to 560 ppm (or 300 to 600 ppm) is now known as the equilibrium climate sensitivity (ECS). It is used as a benchmark to compare climate models. The first climate sensitivity of 5.5 °C (9.9 °F) was published by Arrhenius [1896] based on calculations using his oversimplified steady state model. In 1967, Manabe and Wetherald obtained an ECS for clear sky of 2.9 °C (5.2 °F). As discussed above, this was a combination of two mathematical artifacts. The initial steady state ECS, obtained using a modified version of the Arrhenius model was amplified by a water vapor feedback created by the fixed RH assumption. In 1981, Hansen et al tuned the mathematical artifacts in their 1-D RC model to give a climate sensitivity of 2.8 °C (5 °F) Hansen et al, 1981]. The range of estimates of the ECS (°F) for the Charney Report and the six IPCC Climate Assessment Reports is shown in Figure 3, from NCA5, Figure 3.3. The correct value is ‘too small to measure’. In addition, the 1940 AMO peak and the 1910 AMO minimum are indicated on the temperature plot.





Figure 3: NCA5 Fig. 3.3, equilibrium climate sensitivity (ECS) estimates (°F) from the Charney Report and the six IPCC Climate Assessments. The correct value should be ‘too small to measure’.



When the Royal Swedish Academy of Sciences awarded part of the 2021 Nobel Prize for Physics to Syukuro Manabe they failed to recognize that the climate models used to justify the award were fraudulent. They did not understand that the climate sensitivity of 2.9 °C for clear sky conditions claimed in Table 5 of the 1967 M&W paper was produced by two mathematical artifacts that were created in the oversimplified M&W 1-D RC model. The 2021 Nobel Prize was awarded to Manabe for climate modeling errors [Clark, 2024].



Facts vs. Fiction


The basic requirement of a science or engineering model is that it should reproduce the measured values it was designed to simulate. The opposite has happened in climate science. The a-priori assumption was made that an increase in atmospheric CO2 concentration must cause global warming. The mathematical warming artifacts created by the early 1-D RC steady state models were accepted as real. The time integration approach used in the 1-D RC models was incorporated into the individual unit cells of the larger GCMs. Later, coupled ocean-atmosphere GCMs were ‘tuned’ to match the contrived global mean temperature record. The equilibrium climate assumption became accepted scientific dogma starting in the nineteenth century. Climate science has now degenerated past dogma into the Imperial Cult of the Global Warming Apocalypse. Data that contradict the global warming narrative have been ignored or even altered to support the climate prophesies generated by the climate models. When the real data are examined, it is found that fossil fuel combustion has made a minor contribution to the observed increase in CO2 concentration. Thermal engineering calculations of the surface temperature using the time dependent flux terms show that the small increase in downward LWIR flux from the lower troposphere to the surface produced by the observed increase in greenhouse gases does not cause a measurable increase in surface temperature. Nor can it have any influence on the earth’s weather patterns. There can be no ‘CO2 signature’ in the surface temperature record. These areas will now be considered in turn.


The earth has been cooling for the last 6000 years as it starts the long, slow transition into the next Ice Age. However, this is not a simple linear decrease in temperature. It has been a roller coaster ride with a series of warming periods superimposed on an overall downward trend. These include Minoan, Roman, Medieval and Modern warming periods. During the Medieval warming period Greenland was settled and farmed for about 500 years. The cool period between the Medieval and Modern warming period is known as the Maunder minimum or Little Ice Age. These climate changes have been caused by small variations in solar activity as measured by the sunspot index and other solar parameters. They are not related to any increase in greenhouse gases caused by human activity [Clark and Rörsch, 2023].


The primary cause of the observed increase in CO2 concentration has been the increase in temperature. The increase in CO2 concentration lags the temperature change by 9 to 12 months. This is illustrated in Figure 4 [Humlum 2024, Humlum et al, 2013]. A detailed analysis of the changes in CO2 concentration, including 14CO2 isotope variations following the 1963 nuclear test ban, shows that the contribution of human activity to the observed increase in CO2 concentration to be low, about 4% [Salby and Harde, 2022a, 2022b, 2021a, 2021b]. This is shown in Figure 5. Since the primary driver of the CO2 concentration is temperature, the CO2 concentration should have increased during earlier warming periods. The IPCC has relied on Antarctic ice core data to promote the idea that the CO2 concentration did not change significantly during the recent geological past. There are serious issues with ice core data related to chemical and physical changes that occur during the slow conversion of compressed snow (firn) to ice. The effects of the drilling process on ice core integrity have also been minimized [Jaworowski, 2007]. CO2 concentrations determined from various ice core data and leaf stomata proxies are shown in Figure 6 [Hannon, 2021]. There are larger variations and higher concentrations in the CO2 concentration in these data than in the Antarctic Dome C CO2 data. A large data set of CO2 concentration measurements made using conventional chemical method has also been ignored by the IPCC. Some of these date back to the early nineteenth century. Figure 7 shows the 1870 to 1960 CO2 background concentration level derived from this data set [Beck, 2022]. The levels are consistently above the Law Dome CO2 ice core data and there is a prominent peak near 1940.





Figure 4: Rate of change of temperature from the HadCRUT 5 and HadCRUT4 data series (red and blue) and the rate of change of CO2 (green). The change in CO2 concentration lags the temperature change by 9 to 12 months.





Figure 5: Observed increase in CO2 concentration (green) since 1959 compared to the calculated increase (purple). The natural CO2 concentration (blue) and the human or anthropogenic contribution (magenta) are also shown. The calculated increase is almost hidden by the measured values.





Figure 6: CO2 concentrations derived from Arctic ice cores and leaf stomata proxies compared to Antarctic ice core data.





Figure 7: Atmospheric CO2 background level 1870 to 1960 (red), CO2 law dome ice core data (blue crosses) and leaf stomata data (green stars).



Tree ring data have also been manipulated using invalid statistical techniques in an attempt to eliminate the medieval warming period [Montford, 2010, Wegman et al, 2010]. The well-known ‘hockey stick’ plot was published in the Third IPCC Climate Assessment Report (TAR) in 2001. The temperature records published in the First IPCC Climate Assessment Report compared to the fraudulent ‘hockey stick’ published in the TAR are shown in Figure 8. The IPCC has manipulated both the CO2 concentration and temperature data to promote the fraudulent CO2 induced global warming narrative based on the fantasy climate models. The USGCRP has accepted this fraud without question.





Figure 8: The Holocene (10,000 year) and 1000 year temperature records published in the IPCC FAR, 1990, compared to the fraudulent ‘hockey stick’ record published in the IPCC TAR, 2001 (Fig. 7.1, WG1, FAR, 1990 and Fig. SPM 1, WG1, TAR, 2001)



The decrease in the LWIR flux at TOA and the increase in downward LWIR flux to the surface produced as the CO2 concentration is increased from zero to 760 ppm are shown in Figure 9 [Harde, 2017]. These results are based on detailed line by line radiative transfer calculations. The radiative transfer calculations in the fantasy climate models are usually simplified using a correlated k distribution method to minimize the computation time [Lacis and Oinas, 1991]. However, the determination of both the changes in flux and the rates of cooling are quite reasonable and have been validated using detailed line by line calculations. There are three main issues with the fantasy climate model approach. First, the effects of molecular line broadening have been neglected. Second, the daily and seasonal variations in the temperature and humidity near the surface have been ignored. Third, it has been assumed that the LWIR flux can be separated and analyzed independently of the other flux terms. When these issues are addressed, it becomes clear that is impossible for the changes in LWIR flux produced by a so called greenhouse gas forcing to cause any kind of climate change. Any surface or tropospheric temperature increases are too small to measure. There can be no climate sensitivity to CO2. Nor can there be any effect on extreme weather events. There are five parts to this analysis:





Figure 9: Calculated changes in the upward and downward atmospheric LWIR flux produced by an increase in atmospheric CO2 concentration from 0 to 760 ppm.



1) It is impossible for the small decrease in LWIR flux (radiative forcing) at the top of the atmosphere to couple to the surface because of molecular line broadening effects in the troposphere. A greenhouse gas radiative forcing does not produce a measurable change the energy balance of the earth. The small amount of additional heat released into the troposphere is radiated back to space by wide band LWIR emission.


2) There is no thermal equilibrium or steady state, so a change in flux has to be interpreted as a change in the rate of cooling (or heating) of a set of coupled thermal reservoirs. In the troposphere, at low to mid latitudes, a doubling of the CO2 concentration from 300 to 600 ppm produces a maximum decrease in the LWIR cooling rate, or a slight warming of +0.08 °C per day. This is too small to measure in the normal temperature variations found in the turbulent boundary layer near the surface. The temperature of an air parcel in the troposphere depends on both the LWIR cooling rate and the vertical motion (turbulent convection). These should not be separated and analyzed independently of each other.


3) Over the oceans, the penetration depth of the LWIR radiation is less than 100 micron (0.004 inches). Here it is fully coupled to the wind driven evaporation or latent heat flux. At present the annual increase in average CO2 concentration is near 2.4 ppm per year. This produces an increase in the downward LWIR flux to the surface of near 34 mW m-2 per year. There can be no water vapor feedback in the evaporation process at the ocean surface. Any increase in ocean surface temperature produced by an increase in downward CO2 LWIR flux is too small to measure.


4) Over land, almost all of the absorbed solar flux is dissipated within the same diurnal cycle in which it is received. Most of the absorbed solar heat is dissipated by convection during the day. There is a convection transition temperature each evening when the convection stops and the surface continues to cool more slowly by net LWIR emission. This transition temperature is reset each day by the local weather system passing through. Any surface warming produced by an increase in downward LWIR flux from CO2 is too small to measure in the day to day variations in the surface and surface air temperatures.


5) There can be no CO2 signal in the global temperature record. The main term is temperature change from ocean oscillations, mostly the Atlantic Multidecadal Oscillation (AMO). There is an obvious peak near 1940 from the warming phase of the AMO. In addition, there is heating from urban heat island effects, and warming related to changes to the weather station rural/urban mix and ‘adjustments’ related to ‘homogenization’.


A detailed analysis is provided by Clark [2023, 2024, 2013a, 2013b] and by Clark and Rörsch [2023]. Only the ocean surface energy transfer and the global temperature record will be considered here.


The downward LWIR flux from the lower troposphere to the surface establishes a partial LWIR exchange energy with the upward LWIR flux emitted by the surface. When the surface and surface air layer are at similar temperatures, within the main tropospheric absorption emission bands, IR photons are exchanged without any significant transfer of thermal energy. The net LWIR cooling flux (upward minus downward LWIR flux) at the surface is limited to the emission into the LWIR atmospheric transmission window. This net LWIR flux is insufficient to dissipate the absorbed solar insolation. The surface warms so that the excess solar heat is removed by moist convection (evapotranspiration). The energy transfer processes at the ocean-air and land-air interfaces are different and have to analyzed separately.


Over the oceans, the surface is almost transparent to the solar flux. The diurnal temperature rise is small and the bulk ocean temperature increases until the water vapor pressure at the surface is sufficient for the excess absorbed solar heat to be removed by wind driven evaporation. The sensible heat flux is usually small, less than 10 W m-2. The penetration depth of the LWIR flux into the ocean surface is less than 100 micron, Hale and Querry [1973]. This is illustrated in Figure 10. The LWIR flux and the wind driven evaporation are coupled together at the surface and should not be analyzed separately. The cooler water produced at the surface sinks and is replaced by warmer water from the bulk ocean below. This allows the evaporation to continue at night. Figure 11 shows the long term zonal average sensitivity of the latent heat flux to the wind speed. This is calculated from the long term zonal average ocean latent heat flux and wind speed data given by Yu et al [2008]. Over the ±30° latitude bands, the sensitivity is at least 15 W m-2/m s-1. As shown above in Figure 9, the increase in downward LWIR flux to the surface produced by the observed 140 ppm increase in atmospheric CO2 concentration is approximately 2 W m-2. Within the ±30° latitude bands, this is dissipated by an increase in wind speed near 13 cm s-1. For comparison, the long term 1σ variation in wind speed along the equator, recorded by the TRITON buoy network is near 2 m s-1, [Clark and Rörsch, 2023]. The average annual increase in atmospheric CO2 concentration at present is near 2.4 ppm. This corresponds to an annual increase of 34 mW m-2 in the downward LWIR flux to the surface which is dissipated by an increase in wind speed near 2 millimeters per second. Any change in ocean temperature produced by the current annual increase in the atmospheric CO2 concentration is therefore too small to measure. Furthermore, there can be no water vapor feedback that amplifies such a small signal. This illustrates another failure of the equilibrium climate models. They assume, incorrectly, that a radiative forcing by a greenhouse gas, including the CO2 doubling benchmark, can heat the oceans. This can be traced back to Figure 1 of the 1981 paper by Hansen et al and to Manabe and Stouffer, [1979, 1980].





Figure 10: The penetration depth (99% absorption) of the LWIR flux into water a) below 3300 cm-1 and b) 1200 to 200 cm-1. The locations of the main CO2 absorption bands and the overtones are indicated.





Figure 11: The sensitivity of the ocean latent heat flux to the wind speed. Data from Yu et al (2008).



When the global mean temperature record, such as the HadCRUT4 data set is evaluated, the dominant term is found to be the AMO [HadCRUT4, 2022, Morice et al, 2012]. This is illustrated in Figure 12a. The AMO is a long term quasi-periodic oscillation in the surface temperature of the N. Atlantic Ocean from 0° to 60° N [AMO, 2022]. Superimposed on the oscillation is a linear increase in temperature related to the recovery from the Little Ice Age (LIA) or Maunder minimum [Akasofu, 2010]. The linear equation for the slope and the least squares fit to the oscillation are shown in Figure 12a. Before 1970, the AMO and HadCRUT4 track quite closely. This includes both the long period oscillation and the short term fluctuations. There is an offset that starts near 1970 with HadCRUT4 approximately 0.3 °C higher than the AMO. The short term fluctuations are still similar. The correlation coefficient between the two data sets is 0.8. The influence of the AMO extends over large areas of N. America, Western Europe and parts of Africa. The weather systems that form over the oceans and move overland couple the ocean surface temperature to the weather station data through the diurnal convection transition temperature, [Clark and Rörsch 2023]. The contributions of the other ocean oscillations to the global temperature anomaly are smaller. The IOD and the PDO are dipoles that tend to cancel and the ENSO is limited to a relatively small area of the tropical Pacific Ocean. However, small surface temperature variations in the tropical oceans have a major impact on ocean evaporation and rainfall. Figure 12b shows a tree ring construction of the AMO from 1567 [Gray et al, 2004a, 2004b]. The modern instrument record is also indicated in green. None of the temperature changes related to the AMO can be attributed to an increase in atmospheric CO2 concentration.





Figure 12: a) Plots of the HadCRUT4 and AMO temperature anomalies overlapped to show the similarities. Both the long term 60 year oscillation and the shorter term ‘fingerprint’ details can be seen in both plots. The role of ‘adjustments’ in the 0.3 °C offset since 1970 requires further investigation. b) Tree ring reconstruction of the AMO from 1567.



There is still an additional part of the recent HadCRUT4 warming that is not included in the AMO signal. This may be explained as a combination of three factors. First there are urban heat islands related to population growth that were not part of the earlier record. Second, the mix of urban and rural weather stations used to create the global record has changed. Third, there are so called ‘homogenization’ adjustments that have been made to the raw temperature data. These include the ‘infilling’ of missing data and adjustments to correct for ‘bias’ related to changes in weather station location and instrumentation. It has been estimated that half of the warming in the global record has been created by such adjustments. This has been considered in more detail for example by Andrews [2001a, 2017b, and 2017c], D’Aleo and Watts [2010], Berger and Sherrington [2022] and O’Neill et al [2022].


The role of the AMO in setting the surface air temperature has been misunderstood or ignored for a long time. The first person to claim a measurable warming from an increase in CO2 concentration was Callendar [1938]. The warming that he observed was from the 1910 to 1940 warming phase of the AMO and not from CO2. During the 1970s there was a global cooling scare that was based on the cooling phase of the AMO from 1940 to 1970 [McFarlane, 2018, Peterson et al, 2008, Bryson and Dittberner, 1976]. In their 1981 paper, Hansen et al chose to ignore the 1940 AMO peak in their analysis of the effects of CO2 on the weather station record. Similarly, Jones et al conveniently overlooked the 1940 AMO peak when they started to ramp up the modern global warming scare [Hansen et al, 1981, Jones et al, 1986, 1988]. The IPCC also ignored the AMO peak in its First Assessment Report [FAR WG1 fig. 11 SPM p. 29, IPCC 1990] and it has continued to ignore it as shown in the recent Sixth Assessment Report [AR6 WG1 TS CS Box 1 fig. 1c p. 61, IPCC 2021]. This is illustrated in Figure 13. The AMO and the periods of record used are shown in Figure 13a. The temperature records used by Callendar, Douglas, Jones et al, Hansen et al and IPCC 1990 and 2021 are shown in Figures 13b through 13g. The increase in atmospheric CO2 concentration is also shown in Figures 13d through 13g [Keeling, 2023].





Figure 13: a) AMO anomaly and HadCRUT4 global temperature anomaly, aligned from 1860 to 1970, b) temperature anomaly for N. temperate stations from Callendar (1938), c) global cooling from Douglas (1975), d) global temperature anomaly from Jones et al, (1986) e) global temperature anomaly from Hansen et al, (1981), f) and g) global temperature anomalies from IPCC (1990) and IPCC (2021). The changes in CO2 concentration (Keeling curve) are also shown in d) through g). The periods of record for the weather station data are also indicated in a).



Extreme Weather Attribution and The Double Fantasy of Net Zero


Starting with the Third IPCC Climate Assessment Report (TAR) [2001], a new level of political fraud was added to the fantasy climate models. The contrived time series of radiative forcings used to create the illusion of a fit to the global mean temperature record was split into ‘natural’ and ‘anthropogenic’ forcings. The climate models were then rerun to create a separate ‘natural baseline’ and an ‘anthropogenic contribution’. A vague statistical argument using changes to the normal distribution (‘bell’ or Gaussian curve) of temperature was then used to claim that the increase in temperature caused by ‘anthropogenic’ forcings would cause an increase in the frequency and intensity of ‘extreme weather events’.


As computer technology has improved, the fantasy climate models have become more complex, but the underlying assumptions have not changed significantly. The pseudoscience of radiative forcings, feedbacks and climate sensitivity still provides the foundation for the global warming fantasy [Ramaswamy et al, 2019]. ‘Effective’ radiative forcings were introduced by Hansen et al in 2005. These were used to provide additional ‘tuning’ in the climate models [Hansen et al, 2005]. The time series of the radiative forcings used in the CMIP6 models and the related temperature changes are shown in Figures 14a and 14b. This is the basis for Figure 3.1c in NCA5 (see Figure 1). The comparison to the global temperature record is shown in Figure 14c. The fraudulent attribution to human produced by dividing the radiative forcings into ‘natural’ and ‘human caused’ is shown in Figure 14d. The real causes of the observed temperature changes are shown in Figure 14e. As discussed above, they are a combination of ocean temperature changes, urban heat island effects, changes to the rural/urban mix in the weather station averages and various ‘adjustments’ used to ‘homogenize’ the temperature data. The fantasy climate models are simply ‘tuned’ to match the global temperature record. The ‘tuned’ models are then used to simulate the increase in global average temperature produced by a doubling of the CO2 concentration. This gives the climate sensitivities shown in Figure 14f. This is basis for Figure 3.3 in NCA5 (see Figure 3).





Figure 14: The extreme weather attribution fraud from the CMIP6 model ensemble used in AR6. a) time dependence of the radiative forcings and b) time dependence of the temperature changes derived from a), c) ‘tuned’ temperature record using a contrived set of radiative forcings that appear to simulate the global mean temperature record, d) the separation of the contrived forcings to create fraudulent ‘human’ and ‘natural’ temperature records, e) the contributions of the AMO, UHI etc. to the global mean climate record, f) the pseudoscientific equilibrium climate sensitivity (ECS) estimated from the CMIP6 models (IPCC AR6, WG1, figures 2.10, 7.8, 3.4b and FAQ 3.1 Fig. 1, ECS data from Table 7.SM.5)



The fraudulent link between ‘anthropogenic’ radiative forcings and extreme weather began with work at the UK Hadley Center [Stott et al, 2006, 2000, Tett et al, 2007, 2000]. Later, this led to one of the more egregious examples of ‘extreme weather attribution’- the annual supplement to the Bulletin of the American Meteorological Society ‘Explaining Extreme Events of [Year] from a Climate Perspective’ [Herring et al, 2022]. The series has been published annually since 2012. The BAMS publication guidelines state:


‘Each paper will start with a 30 word capsule summary that includes, if possible, how anthropogenic climate change contributed to the magnitude and/or likelihood of the event’.


The fraudulent climate sensitivities created in CMIP5 and CMIP6 model ensembles and in other climate models are used without question to ‘explain’ the observed ‘extreme weather events’ for the year of interest. Natural climate changes related, for example to ocean oscillations and blocking high pressure systems have to be ‘enhanced’ by the pseudoscience of radiative forcings.


The question that all of the authors of the papers in these supplements should answer is:


How does an increase of 34 mW m-2 per year in the downward LWIR flux to the surface produced by the measured 140 ppm increase in atmospheric CO2 concentration increase the ‘frequency and intensity’ of extreme weather events?


The fantasy climate models have been used to create the illusion in the Paris Climate Accords that a 1.5 or 2 °C increase in global temperature is dangerous and that that we should eliminate fossil fuel combustion. This so called Net Zero energy policy is a double fantasy. The first fantasy is the illusion of a dangerous global warming created by the fraudulent climate models. The second fantasy is the delusion that we can eliminate fossil fuel combustion. The technology simply does not exist, nor can it be created by spending massive amounts of money to try and solve a nonexistent problem. Wind and solar power are intermittent and unreliable sources of electricity that have to be backed up by fossil fuel electrical power generation. The technology needed for large scale electrical power storage does not exist. Similarly, the supply of raw materials needed for electric vehicles far exceeds the known reserves. Hydrogen is an explosion waiting to happen.



Down the Rabbit Hole


We are all crazy here” – The Cheshire Cat


M&W were applied mathematicians. Their interest was the solution of the fluid dynamics equations used for weather forecasting and their modification for climate prediction. They abandoned physical reality in favor of mathematical simplicity and constructed a model that they could solve with the limited computer capabilities that were available in 1967. Once they had created their equilibrium climate fantasy land, they never left it. They never recognized the mathematical artifacts that they created with their 1-D RC model. They allowed very small increases in temperature to accumulate in their time integration procedure. It required a year of model time to reach the +2.9 °C steady state condition for a CO2 doubling. They failed to investigate the limitations of their model assumptions and never considered the daily and seasonal variations in temperature and humidity found in the real atmosphere, particularly near the surface. They spent the next 8 years incorporating their 1967 model artifacts into a ‘highly simplified’ GCM. This provided the foundation for the fantasy climate modeling fraud.


When the Apollo (moon landing) program ended in 1972 and funding for NASA was significantly reduced, the planetary atmospheres group was told to switch to earth studies [Hansen et al, 2000]. They joined M&W in the equilibrium climate fantasy land. In 1976 they extended the M&W 1967 1-D RC model to include another 10 minor species, N2O, CH4, NH3, HNO3, C2H4, SO2, CF2Cl2, CFCl3, CH3Cl and CCl4 [Wang et al, 1976]. They failed to understand that their calculated temperature changes were nothing more than mathematical artifacts of the 1-D RC fantasy climate model that they were using. This is the fraudulent source of the warming claimed for chlorofluorocarbons, CH4 and N2O.


The basic climate fraud was completed by Hansen et al in 1981. They began by tuning their model so that a CO2 doubling produced an increase in temperature of 2.8 °C. Then they introduced a slab ocean model with a mixed ocean layer 100 m thick and a thermocline layer below this. The surface energy transfer, particularly the wind driven evaporation was ignored (see Figure 11) and only the time delays related to the increase in heat capacity were considered. The slab ocean was a flat ocean without wind or waves. Next, they added the CO2 doubling ritual. The CO2 concentration was doubled and the 1981 1-D RC model with the slab ocean was allowed to adjust to a new steady state. This became the method used to determine the pseudoscientific equilibrium climate sensitivity (ECS) in the fantasy climate models. Available weather station and related data were then combined and averaged into a global mean temperature record. The obvious large peak near 1940 produced by the warming phase of the AMO was ignored (see Figure 13e). The 1981 model was then ‘tuned’ to create the illusion that it could be used to simulate the global temperature record. As shown in Figure 15, a combination of increased CO2, solar variation and volcanic aerosols was used to fit the climate model artifacts to the temperature record. The H81 paper is one of the earliest examples of the use of a contrived set of radiative perturbations, later called radiative forcings to fraudulently tune an equilibrium climate model to match the global average temperature record.





Figure 15: The first use of radiative forcing to create the illusion that a 1-D RC fantasy climate model can simulate the global climate record. The forcing agents used here were CO2, volcanic aerosols and variations in the solar flux. The red asterisk indicates the 1940 AMO peak. Figure 5 from Hansen et al, 1981.



The equilibrium climate fantasy land was now illuminated by a 24 hour average sun and surrounded by a flat ocean without wind or waves. The relative humidity of the air was also fixed. In the First IPCC Climate Assessment Report in 1990, in Table 3.2a, 21 values for the ECS are listed from nine modeling groups. They range from 2.0 to 5.2 °C (3.6 to 9.4 °F). The population of the climate fantasy land had increased from two to at least 9 modeling groups and the fantasy climate models had spread to six other countries.


In 1990, the total USGCRP budget was 191.5 million dollars with M$21.5 to NASA, M$27.2 to DOE and M20.0 to NOAA [USGCRP, 1990]. In order to maintain and increase its funding, the USGCRP joined the climate modelers in the equilibrium climate fantasy land and began to perpetuate the climate modeling fraud. Few, if any, of the personnel associated with the USGCRP had any understanding of climate energy transfer and many had no scientific background at all. The IPCC relied on the concepts of radiative forcing, feedbacks and climate sensitivity to promote the climate warming fantasy and the USGCRP blindly followed along. Nothing has changed in over 30 years. Figures 3.1, 3.2 and 3.3 in NCA5 were adapted from the IPCC AR6 WG1 Report.


The personnel associated with the USGCRP have a vested interest in maintaining the climate modeling fraud. For example, Gavin Schmidt, the review editor for Chapter 3 of NCA5 is the Director of Goddard Institute for Space Studies (GISS) and Principal Investigator for the GISS ModelE Earth System Model. The ECS listed for the GISS -E2-1-H model in IPCC AR6 was 3.11 °C. The correct value should be ‘too small to measure’. When he became Director of GISS in 2014 he inherited the NASA versions of the fantasy climate models that were built on the pseudoscientific foundation of radiative forcings, feedbacks and climate sensitivity. This fraud started at NASA in the early 1970s when the planetary atmospheres group copied the 1967 1-D RC model developed by Manabe and Wetherald. The foundation of this fraud was completed by the work of Hansen et al in 1981.


Similarly, L. Ruby Leung, the Lead Author for Chapter 3 of NCA5 is the Chief Scientist for the Energy Exascale Earth System Model (E3SM) at the Pacific Northwest National Laboratory (PNNL). The climate sensitivity of this model has recently been reduced from 5.2 to 4.0 °C by adjusting the cloud feedbacks. The foundation of this model is again the pseudoscience of radiative forcings, feedbacks and climate sensitivity that can be traced back to the work of Hansen et al and Manabe and Wetherald between 19967 and 1981. PNNL evolved out of the old Hanford nuclear site. Instead of winding down the operation, additional funding was obtained by jumping on the fraudulent climate bandwagon.


Adam Terando, the Federal Coordination Lead Author for Chapter 3 NCA5, illustrates another aspect of the NCA5 fraud. He has blindly accepted the results of the fantasy climate models without any attempt at independent model validation. This is demonstrated in the US Geological Survey Report, ‘Using information from global climate models to inform policymaking-The role of the U.S. Geological Survey’ (USGS2020) [Terando et al, 2020]. Figure 1 from USGS2020 is shown here as Figure 16. (The temperature scale is °F not °C). This figure was copied from Figure 3.1 of the Fourth National Climate Assessment Report, NCA4. The NCA4 figure can be traced back to Figures 14, 15 and 16 in Appendix 4 of the Third National Climate Assessment Report (NCA4). The original source was Jones, Stott and Christidis [2013], Figures 4 and 7. This figure was also used as Figure 10.7 in the Fifth IPCC Climate Assessment [2013]. The original fantasy climate modeling work was performed at the UK Met. Office and Peter Stott also helped to create the extreme weather scam for the Third IPCC Climate Assessment in 2001.





Figure 16: Figure 1 from USGS Report 2020-1058, showing the fraudulent attribution of the global mean temperature change record to natural and human causes.



Figure 16 is an earlier version of Figure 14d from AR6, WG1, FAQ 3.1 Figure 1. The real sources of the temperature changes are illustrated in Figure 14e. Instead of King Canute trying to stop the rising tide, the natural baseline created by the pseudoscientific radiative forcing argument may compared to using the fantasy climate models to try and stop the ocean waves and create a flat ocean without the gyre circulation.


The USGCRP has failed to provide any training in basic climate energy transfer or meteorology to the people it expects to provide a climate assessment for delivery to Congress. Similarly, the Agencies not directly involved in the fantasy climate modeling have failed to conduct any ‘due diligence’ or independent validation of the modeling results provided for their use. The small increase in downward LWIR flux from the lower troposphere to the surface produced by an increase in greenhouse gases cannot cause any change to ‘extreme weather events’ including floods, droughts, wildfires, hurricanes and tornadoes. Nor can there be any changes in sea level attributable to greenhouse gases.



Where was the Oversight?


The peer review process in climate science has collapsed and been replaced by blatant cronyism. In fact, there never was any independent review of climate modeling. As the group of NASA trained ‘equilibrium’ climate modelers grew and moved on to other research positions, they formed a group of cronies that reviewed each other’s work. Melodramatic predictions of the global warming apocalypse became such a lucrative source of funds that no one wanted to kill the pseudoscientific goose that laid the golden eggs. The climate modelers were soon trapped in a web of lies of their own making. They retreated into their equilibrium climate fantasy land and have never left.


In addition to the traditional scientific peer review process, there are multiple levels of oversight, all of which have failed. As government agencies funded by US taxpayers, NASA, DOE, NOAA, (Department of Commerce), NSF etc. are subject to Congressional oversight. Each agency has an Inspector General to investigate fraud. In addition, the National Labs are operated by private companies. The operating contracts between these labs and DOE are governed by Federal Acquisition Regulations (FAR). For many years, Lawrence Livermore and Los Alamos National Laboratories were operated by the University of California. Lawrence Livermore is now operated by a consortium that includes Amentum, Battelle, Bechtel, BWXT, Texas A&M University and the University of California. Similarly, the NASA Jet Propulsion Laboratory is operated by the California Institute of Technology. The NOAA Geophysical Fluid Dynamics Laboratory is located on the Princeton University Campus and is government operated but has close associations with the University of Princeton.


NASA also has a well-established process of Technical Readiness Levels used for technology development. These were not applied to the climate models. In addition, the mission reviews for satellites that monitor greenhouse gases such as OCO were inadequate. They never included a thermal engineering analysis of the possible warming effects that an increase in greenhouse gases could produce.


There has been a complete failure to identify and answer the basic climate energy transfer question:


How does an increase of 34 mW m-2 per year in downward CO2 LWIR flux to the surface increase the surface temperature and the frequency and intensity of extreme weather events?



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