Research Page 11 - Ventura Photonics

Summary

Since it was first established, the US Global Change Research Program (USGCRP) has used the results of fraudulent ‘equilibrium’ climate models to perpetuate a massive Ponzi or pyramid scheme based on exaggerated claims of anthropogenic global warming. It takes the fraudulent climate model output generated by agencies such as NASA and DOE and without question cycles the fake climate warming through the 13 US Agencies to establish a US climate policy that mitigates a nonexistent problem. The pigs have been filling their own trough at taxpayer expense for over 30 years. There has been no significant oversight. None of the agencies using the climate model results have performed any independent validation (‘due diligence’) of the modeling data provided. The climate modelers are no longer scientists, they have become prophets of the Imperial Cult of the Global Warming Apocalypse. Irrational belief in ‘equilibrium’ climate model results has replaced scientific logic and reason. The same group of climate modelers also provides the same fraudulent climate warming data for use by the IPCC in their assessment reports.

There are two different types of fraud in the climate models. First, the climate energy transfer processes were oversimplified and this created global warming as a mathematical artifact of the assumptions used. Second, the general circulation climate models (GCMs) require the solution to a very large number of coupled non-linear equations. This means that the model solutions are unstable and the errors increase over time. The GCMs have no predictive capabilities over the time scales required for climate analysis. They are simply ‘tuned’ to give the desired result. Most of the discussion here is on the climate energy transfer processes, the simplification errors and the blatant disregard of these errors by the USGCRP.

The oversimplification of climate science started in the nineteenth century with the introduction of the equilibrium average climate assumption and speculation that changes in the atmospheric CO₂ concentration could cycle the earth through an Ice Age. The first person to try and calculate the changes in surface temperature produced by such changes in CO₂ concentration was Arrhenius in 1896. However, he used an oversimplified ‘equilibrium air column’. His results were just mathematical artifacts of his modeling assumptions. Unfortunately, the idea that an increase in atmospheric CO₂ concentration could warm the earth became accepted scientific dogma. Instead of an Ice Age, fossil fuel combustion was the cause of climate warming. The first generally accepted computer climate model was published by Manabe and Wetherald (M&W) in 1967. It was a modified version of the ‘equilibrium air column’, with radiative transfer and a prescribed relative humidity distribution. Not only did this model create a global warming artifact as the CO₂ concentration was increased, there was a ‘water vapor feedback’ as well that amplified the initial mathematical artifact. The model contained four fundamental scientific errors. These were ignored and M&W spent the next 8 years building a ‘primitive’ GCM. The 1967 artifacts were incorporated into every unit cell of the larger model.

As resources dwindled for space exploration and nuclear programs, other agencies jumped on the climate bandwagon and formed their own climate modeling groups. They started by copying the M&W ‘equilibrium’ approach. Melodramatic prophecies of the global warming apocalypse became such a good source of research funding that the scientific process of hypothesis and discovery collapsed. Continued employment was more important. The climate modelers became trapped in a web of lies of their own making. Various outside interests, including environmentalists and various political groups also began to exploit the climate apocalypse to further their own causes. In 1981, Hansen’s group at NASA Goddard added several ‘improvements’ to the basic M&W model. These added another three fundamental scientific errors to the ‘1-D radiative convective’ equilibrium climate model. Little has changed since then. The climate modelers have been playing computer games in an Equilibrium Climate Fantasy Land since 1967.

When the USGCRP was formed, the rest of the 13 government agencies involved simply followed the climate modelers down the rabbit hole into the Equilibrium Climate Fantasy Land. No independent validation or ‘due diligence’ was performed to check the climate model results. The climate Apocalypse was a good source of funding and employment. Very few people in these agencies understood anything about climate physics and most of the USGCRP soon became disciples of the Imperial Cult of the Global Warming Apocalypse.

As computer technology improved, climate models became more complex, but the underlying assumptions remained the same. An increase in the atmospheric concentration of ‘greenhouse gases’ produces a decrease in the LWIR flux at the top of the atmosphere (TOA). This perturbs the ‘radiation balance of the earth’. The climate system then ‘adjusts’ to increase the surface temperature and restore the ‘radiation balance’ at TOA. An elaborate pseudoscientific modeling ritual has been created using radiative forcings, feedbacks and a climate sensitivity to CO₂ to give the illusion that the observed increase in atmospheric CO₂ concentration is causing ‘climate change’. The surface temperature is warming and this must be caused by CO₂. The Sacred Spaghetti Plots from the computer models have to be correct. They have been ‘tuned’ to match the change in ‘global mean temperature’ using a contrived set of ‘radiative forcings’. The Apocalypse is coming. Pay for your sins. The US taxpayer is paying for the USGCRP. The world has to be saved from a non-existent problem. Eisenhower’s warning about the corruption of science by government funding has come true.

CO₂ is a good plant fertilizer, so there is a major agricultural benefit to an increase in CO₂ concentration - enhanced agricultural production. There is no climate emergency. There is no need for utility scale solar or wind energy. There is no need for the large scale deployment of electric vehicles. It is time to dismantle the entire climate fraud, including the USGCRP and rebuild the energy infrastructure of the US based on reliable, fossil fueled and nuclear electrical power.

The NCA5 Report

The USGCRP is in the process of preparing its Fifth National Climate Assessment Report. Instead of wasting taxpayer money on another lengthy and fraudulent report, this single page summary should suffice.

Since the start of the Industrial Revolution about 200 years ago, the atmospheric concentration of CO₂ has increased by approximately 140 parts per million (ppm), from 280 to 420 ppm. This has produced a decrease near 2 W m^-2 in the longwave IR (LWIR) flux emitted to space at the top of the atmosphere (TOA) within the spectral range of the CO₂ emission bands. There has also been a similar increase in the downward LWIR flux from the lower troposphere to the surface. At present, the annual average increase in CO₂ concentration is about 2.4 ppm. This produces an annual increase in the downward LWIR flux to the surface of approximately 0.034 W m^-2.

1) The additional absorption of 2 W m^-2 by the CO₂ bands has not changed the temperature of the troposphere. Nor does it change the energy balance of the earth.

2) The 2 W m^-2 increase in downward LWIR flux to the surface has not changed the land or ocean surface temperatures.

3) The annual increase of 0.034 W m^-2 in downward LWIR flux to the surface cannot increase the ‘frequency and intensity’ of ‘extreme weather events’?.

Any temperature increases produced by these changes in LWIR flux are ‘too small to measure’. In addition, CO₂ is a good plant fertilizer, so there is a major agricultural benefit to an increase in CO₂ concentration – enhanced agricultural production.

There is no climate emergency. There is no need for utility scale solar or wind energy. There is no need for the large scale deployment of electric vehicles. It is time to dismantle the entire climate fraud, including the USGCRP and rebuild the energy infrastructure of the US based on inexpensive, reliable fossil fueled and nuclear electrical power.

Introduction

The US Global Change Research Program (USGCRP) was established by Presidential initiative in 1989 and mandated by Congress in 1990. Its mission is ‘to coordinate federal research and investments in understanding the forces shaping the global environment, both human and natural, and their impacts on society’. Thirteen government agencies are involved, the Department of Agriculture (USDA), the Department of Commerce (DOC), (NOAA and NIST), the Department of Defense (DOD), the Department of Energy (DOE), including the National Laboratories, Department of Health and Human Services (HHS), Department of the Interior (DOI) (USGS), Department of State (DOS), Department of Transportation (DOT), Environmental Protection Agency (EPA), National Aeronautics and Space Administration (NASA), National Science Foundation (NSF), The Smithsonian Institution (SI) and the US Agency for International Development (USAID).

Since it was first established, the USGCRP has used the results of fraudulent ‘equilibrium’ climate models to perpetuate a massive Ponzi or pyramid scheme based on exaggerated claims of anthropogenic global warming. It takes the climate model output generated by agencies such as NASA and DOE and without question cycles the fake climate warming through the 13 US Agencies to establish a US climate policy that mitigates a nonexistent problem. The pigs have been filling their own trough at taxpayer expense for over 30 years. There has been no significant oversight. None of the agencies using the climate model results have performed any independent validation (‘due diligence’) of the data provided. The climate modelers are no longer scientists, they have become prophets of the Imperial Cult of the Global Warming Apocalypse. Irrational belief in ‘equilibrium’ climate model results has replaced scientific logic and reason. The same group of climate modelers also provides the same fraudulent climate warming data for use by the UN Intergovernmental Panel on Climate Change (IPCC) in their assessment reports.

The first requirement for anyone going down the rabbit hole to live in the USGCRP Equilibrium Climate Fantasy Land is that they should have no understanding of climate energy transfer. Physical reality must be abandoned in favor of mathematical simplicity, starting with the Second Law of Thermodynamics. They should believe everything that they told about the climate models, forcings, feedbacks and climate sensitivity by the prophets of the Imperial Cult. Their job is to support the USGCRP Climate Ponzi scheme and save the world from a nonexistent problem, even if it means inflicting major economic damage on the US economy. They will soon be trapped in the climate web of lies.

The Beginnings of the Equilibrium Climate Fantasy Land

When the USGCRP was created in 1989/1990, the Equilibrium Climate Fantasy Land was already well established at the agencies involved in equilibrium climate modeling including NOAA, NASA, DOE and NSF. The Imperial Cult of the Global Warming Apocalypse had already been established. The first generally accepted equilibrium climate model was published by Manabe and Wetherald (M&W) in 1967. They chose to ignore physical reality and used an oversimplified ‘equilibrium air column’ climate model. When the CO₂ concentration was increased, global warming was created as a mathematical artifact of the simplifying assumptions used to build the model. These included a constant ‘24 hour average’ solar flux and a surface with zero heat capacity [M&W, 1967]. Their model contained four fundamental scientific errors that were ignored. They then spent the next 8 years incorporating the mathematical artifacts from their 1967 model into a ‘primitive’ global circulation model [M&W, 1975]. No independent thermal engineering analysis was performed to validate the model. They also ignored the climate model instabilities that had been demonstrated by Lorenz in 1963. Because of the large number of coupled nonlinear equations, there is no reason to expect the climate models to have any predictive capabilities over the time scales required for climate analysis [Lorenz, 1963, 1973].

As resources dwindled for space exploration and nuclear programs other agencies jumped on the climate bandwagon and formed their own climate modeling groups. They started by copying the M&W ‘equilibrium’ approach. Melodramatic prophecies of the global warming apocalypse became such a good source of research funding that the scientific process of hypothesis and discovery collapsed. Continued employment was more important. The climate modelers became trapped in a web of lies of their own making. Various outside interests, including environmentalists and various political groups also began to exploit the climate apocalypse to further their own causes. In 1981, Hansen’s group at NASA Goddard added several ‘improvements’ to the basic M&W model. These added another three fundamental scientific errors to the ‘1-D radiative convective’ equilibrium model [Hansen et al, 1981]. Little has changed since then. The climate modelers have been playing computer games in the Equilibrium Climate Fantasy Land since 1967 (see Climate Pseudoscience, VPCP 012 and Nine Papers That Reveal The Equilibrium Climate Modeling Fraud VPCP 014 for additional information).

The climate modelers started from the a-priori assumption that an increase in the atmospheric concentration of CO₂ had to cause global warming. They chose to ignore the natural climate variations produced by ocean oscillations and were searching for a ‘CO₂ signal’ in the climate record. The focus of the climate models was the increase in ‘global mean temperature’ produced by a doubling of the CO₂ concentration. The preface to a major DOE climate report from 1985 [MacCracken and Luther, 1985] started:

"Virtually all theoretical studies suggest that the increasing atmospheric CO₂ concentration will significantly increase the global average temperature. However, even though the CO₂ concentration has risen about 25% since the middle of the last century, such a warming is not yet clearly identifiable in the observational record."

The following year Jones et al [1986] claimed to have detected such a signal and started to ramp up the climate modeling fraud. In reality, this ‘signal’ was just the Atlantic Multi-decadal Oscillation (AMO) that had switched to its warming phase (see Figure 11). The USGCRP started to perpetuate this fraud when it was founded in 1989.

As computer technology improved, climate models became more complex, but the underlying assumptions remained the same. An increase in the atmospheric concentration of ‘greenhouse gases’ produces a decrease in the LWIR flux at the top of the atmosphere (TOA). This perturbs the ‘radiation balance of the earth’. The climate system then ‘adjusts’ to increase the surface temperature and restore the ‘radiation balance’ at TOA. An elaborate pseudoscientific modeling ritual has been created using radiative forcings, feedbacks and a climate sensitivity to CO₂ to give the illusion that the observed increase in atmospheric CO₂ concentration is causing ‘climate change’. This is based on nothing more than correlation. The surface temperature is warming and this must be caused by CO₂. The climate models must be right. They have been ‘tuned’ to match the change in ‘global mean temperature’ using a contrived set of ‘radiative forcings’. The Apocalypse is coming. Pay for your sins. Eisenhower’s warning about the corruption of science by government funding has come true.

In reality the small, wavelength specific decrease in LWIR flux at TOA produced by an increase in the atmospheric concentration of CO₂ or other ‘greenhouse gases’ is caused by small increases in absorption at many different levels in the atmosphere. There is no ‘climate equilibrium’. Any atmospheric heating effects have to be evaluated as changes in the local rate of cooling. The maximum change in the rate of cooling in the troposphere produced by a ‘CO₂ doubling’ is +0.08 K per day [Iacono et al, 2008]. This is too small to measure. It is equivalent to the temperature increase produced by riding an elevator down four floors. The small amount of additional heat produced by the CO₂ absorption is coupled to the local air parcel and dissipated by a combination of wideband LWIR emission and turbulent convective motion. There is no change to the ‘radiation balance of the earth’.

In addition to the greenhouse gas ‘radiative forcing’, or decrease in LWIR flux at TOA, there is also a similar increase in downward LWIR flux emitted by the lower troposphere to the surface. The surface temperature changes produced by this increase in flux are too small to measure in the normal variation of the daily and seasonal surface temperatures. Over the oceans, the penetration depth of the LWIR flux is less than 100 micron (0.004 inches). Here it is fully coupled to the much larger and more variable wind driven evaporation or latent heat flux. Over land, the surface temperature is reset each day by the change in diurnal convective transition temperature. These temperature variations sufficiently large that they overwhelm any warming effects from an increase in the CO₂ flux [Clark and Rörsch, 2023, Clark, 2013].

Down the Rabbit Hole

A good way to start exploring this Fantasy Land is by examining 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 1 (The temperature scale is °F not °C). Simple inspection of the ‘observed temperatures’ reveals a distinct peak near 1940 and an earlier minimum near 1910. The slope from 1970 to 2000 is similar to the slope from 1910 to 1940. This is the ‘signal’ from the Atlantic Multi-decadal Oscillation (AMO) [AMO, 2022]. It has nothing to do with CO₂. There are also various biases and ‘adjustments’ that have been made to the raw weather station data as part of the global averaging process. There has been no investigation of this by the USGCRP. If it does not conform to the ‘climate change narrative’ and has been ignored. Similarly, there has been no investigation of the energy transfer processes that determine the surface temperature. How does the increase in atmospheric CO₂ concentration heat the surface? Where are the thermal engineering calculations?

The caption for this Figure is:

Figure 1. Graphs comparing modeled changes (orange line in panel A and blue line in panel B) and three independent estimates of observed changes (teal, red, and black lines in both panels) in the global annual-mean air temperature since 1880. All the time series are presented relative to the average temperature (in degrees Fahrenheit, °F) over the period from 1901 through 1960. The temperature changes in panel A are from models that include both anthropogenic climate drivers (for example, greenhouse gases [GHGs], ground level ozone, land use change) and natural climate drivers (for example, solar output, orbital variability, observed volcanic eruptions). In contrast, modeled temperatures in panel B include only the natural climate drivers. The thick orange and yellow curve (panel A) and thick blue curve (panel B) each represent the mean across dozens of climate model simulations obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5, Lawrence Livermore National Laboratory, 2008). The shading indicates the standard deviation of all simulations. The outer dashed lines depict the absolute range of temperature differences across all simulations. Panel B shows that after about 1970, the observed global temperatures (green, orange, and black lines) diverge from the temperature simulated by the climate models that consider only natural factors (blue line). The consistency between the trajectory shape and magnitude of the modeled temperature changes and those of the observed temperature changes in panel A show that the observed warming since 1970 is attributable primarily to anthropogenic factors. This modeled response of temperature to GHGs was produced by the earliest versions of climate models that were applied in the 1970s and continues to be produced as the models have undergone significant refinements over the years through addition of many more natural and anthropogenic drivers (Hausfather, Drake, and others, 2020). Figures modified from figure 3.1 of Wuebbles and others (2017), used with permission.

The figure shows CMIP5 climate model results with and without ‘anthropogenic climate drivers’. These include greenhouse gases etc. This figure is used to ‘attribute’ the recent increase in the ‘global mean temperature change’ to anthropogenic causes, mainly the observed increase in atmospheric CO₂ concentration. The references cited are:

Hausfather, Z., H. F. Drake, T. Abbott and G. A. Schmidt (2020), “Evaluating the Performance of Past Climate Model Projections” Geophys. Res. Letters 47(1) e2019GL085378 pp. 1-10. [https://doi.org/10.1029/2019GL085378] Hausfather

Knutson, T., J.P. Kossin, C. Mears, J. Perlwitz and M.F. Wehner (2017), “Detection and attribution of climate change” In: Climate Science Special Report: Fourth National Climate Assessment, Volume I, Wuebbles, D.J., D.W. Fahey, K.A. Hibbard, D.J. Dokken, B.C. Stewart, and T.K. Maycock (eds.). U.S. Global Change Research Program, Washington, DC, USA, pp. 114-132, doi: [https://doi.org/10.7930/J0J964J6] Knutson

Before considering the results presented in Figure 1 in more detail, it is instructive to trace the source of this Figure. It is the same as Figure 3.1 of NCA4, the Fourth Climate Assessment report as shown in Figure 2.

The caption for this figure is:

Figure 3.1: Comparison of observed global mean temperature anomalies from three observational datasets to CMIP5 climate model historical experiments using: (a) anthropogenic and natural forcings combined, or (b) natural forcings only. In (a) the thick orange curve is the CMIP5 grand ensemble mean across 36 models while the orange shading and outer dashed lines depict the ±2 standard deviation and absolute ranges of annual anomalies across all individual simulations of the 36 models. Model data are a masked blend of surface air temperature over land regions and sea surface temperature over ice-free ocean regions to be more consistent with observations than using surface air temperature alone. All time series (°F) are referenced to a 1901–1960 baseline value. The simulations in (a) have been extended from 2006 through 2016 using projections under the higher scenario (RCP8.5). (b) As in (a) but the blue curves and shading are based on 18 CMIP5 models using natural forcings only. See legends to identify observational datasets. Observations after about 1980 are shown to be inconsistent with the natural forcing-only models (indicating detectable warming) and also consistent with the models that include both anthropogenic and natural forcing, implying that the warming is attributable in part to anthropogenic forcing according to the models. (Figure source: adapted from Melillo et al. and Knutson et al.).

The references cited are:

Knutson, T. R., F. Zeng and A. T. Wittenberg (2013), “Multimodel Assessment of Regional Surface Temperature Trends: CMIP3 and CMIP5 Twentieth-Century Simulations” J. Climate 26(22) pp. 8709-8743. [https://doi.org/10.1175/JCLI-D-12-00567.1] Knutson

Melillo, J. M., T. C. Richmond, and G. W. Yohe, eds., (2014) Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 841 pp. [https://www.nrc.gov/docs/ML1412/ML14129A233.pdf on line https://nca2014.globalchange.gov/] Melillo

The Melillo source is NCA3, the Third National Climate Assessment. Figures 14, 15 and 16 from Appendix 4, pages 802 to 804 NCA4 are shown in Figure 3a through 3c. The first panel in Figure 3a is an earlier version of USGS2020 Figure 1. Figure 4 from Knutson et al is shown here as Figure 4. Both NCA3 and Knutson et al show climate model results from CMIP3 and CMIP5 and ‘global mean temperature changes’ from up to three similar sources, HadCRUT4, NASA GISS and NCDC.

Figure 14. Changes in surface air temperature at the continental and global scales can only be explained by the influence of human activities on climate. The black line depicts the annually averaged observed changes. The blue shading represents estimates from a broad range of climate simulations including solely natural (solar and volcanic) changes in forcing. The orange shading is from climate model simulations that include the effects of both natural and human contributions. These analyses demonstrate that the observed changes, both globally and on a continent-by-continent basis, are caused by the influence of human activities on climate. (Figure source: updated from Jones et al. 201311).

Figure 15. The green band shows how global average temperature would have changed due to natural forces only, as simulated by climate models. The blue band shows model simulations of the effects of human and natural factors combined. The black line shows observed global average temperatures. As indicated by the green band, without human influences, temperature over the past century would actually have cooled slightly over recent decades. The match up of the blue band and the black line illustrate that only the inclusion of human factors can explain the recent warming. (Figure source: adapted from Huber and Knutti, 201212).

Figure 16. Three different global surface temperature records all show increasing trends over the last century. The lines show annual differences in temperature relative to the 1901-1960 average. Differences among data sets, due to choices in data selection, analysis, and averaging techniques, do not affect the conclusion that global surface temperatures are increasing. (Figure source: NOAA NCDC / CICS-NC).

Figure. 4. Time series of global-mean surface temperature anomalies (8C, combined SST and land surface air temperature) from observations (HadCRUT4, black curves). The red curves depict the 5th and 95th percentiles of annual-mean anomalies for the multimodel mean (thick) or of single model realizations (thin lines with gray stippling) for the (a),(b) CMIP3 and (c) CMIP5 20c3m historical all forcing runs. The mean curve is not shown but lies approximately midway between the 5th and 95th percentiles. The series in (a) are from eight CMIP3 models run with volcanic forcing. The historical runs in (b) include 19 CMIP3 models with and without volcanic forcing (as identified in Figs. 1a, b). All of the 23 CMIP5 model runs included in the computations in (c) incorporated volcanic forcing. (d) The blue curves are based on seven CMIP5 models that had natural-forcing-only runs extending through 2010. See text for description of how the confidence limits were computed. The time series have been recentered so that the ensemble-mean value, averaged for the years 1881– 1920, is 0. Model data were masked with the observed spatially and temporally evolving missing data mask. The total number of individual experiments included in each panel was 26, 51, 78, and 25 for (a)–(d), respectively.

The original source for Figure 3a is Jones et al, [2013] figure 7. This figure was also used in the IPCC AR5 WG1 report, Chapter 10, Figure 10.7. In addition, Figure 4 of Jones et al. shows the global plot in more detail. Figure 5a shows figure 7 from Jones et al and Figure 5b shows the IPCC version. Figure 6 shows figure 4 from Jones et al.

Jones, G. S., P. A. Stott and N. Christidis (2013), “Attribution of observed historical near surface temperature variations to anthropogenic and natural causes using CMIP5 simulations” J. Geophys. Res. Atmos. 118(10) pp. 4001-4024. [https://doi.org/10.1002/jgrd.50239] Jones

Figure 7. Global, land, ocean, and continental annual mean temperatures for CMIP3 and CMIP5 historical (red) and historicalNat (blue) MME and HadCRUT4 (black). Weighted model means shown as thick dark lines and 5–95% ranges shown as shaded areas. Continental regions as defined in insert. Temperatures shown with respect to 1880–1919 period apart for Antarctica which is shown with respect to 1951–1980 period mean.

Figure 10.7. Global, land, ocean and continental annual mean temperatures for CMIP3 and CMIP5 historical (red) and historicalNat (blue) simulations (multi-model means shown as thick lines, and 5 to 95% ranges shown as thin light lines) and for Hadley Centre/Climatic Research Unit gridded surface temperature data set 4 (HadCRUT4, black). Mean temperatures are shown for Antarctica and six continental regions formed by combining the sub-continental scale regions defined by Seneviratne et al. (2012). Temperatures are shown with respect to 1880–1919 for all regions apart from Antarctica where temperatures are shown with respect to 1950–2010. (Adapted from Jones et al., 2013.)

Figure 4. Global annual mean TAS for CMIP3 (thin blue lines) and CMIP5 (thin red lines) for (a) historical, (b) historicalNat, and (c) historicalGHG ensemble members, compared to the four observational data sets (black lines) — also shown individually in the insert of Figure 4a. The weighted ensemble average for CMIP3 (blue thick line) and CMIP5 (red thick line) are estimated by given equal weight to each model’s ensemble mean (supporting information). All model and observed data have same spatial coverage as HadCRUT4. TAS anomalies with respect to 1880–1919 period.

Figure 6c shows the temperatures derived from the ‘radiative forcing’ caused by ‘greenhouse gases’ used in the climate models (red line). The history of radiative forcing was reviewed by Ramaswamy et al [2019]. This provides a convenient source for the earlier history of climate modeling and radiative forcing.

Ramaswamy, V., W. Collins, J. Haywood, J. Lean, N. Mahowald, G. Myhre, V. Naik, K. P. Shine, B. Soden, G. Stenchikov and T. Storelvmo (2019), “Radiative Forcing of Climate: The Historical Evolution of the Radiative Forcing Concept, the Forcing Agents and their Quantification, and Applications” Meteorological Monographs Volume 59 Chapter 14. [https://doi.org/10.1175/AMSMONOGRAPHS-D-19-0001.1] Ramaswamy

The concept of radiative forcing has been used in the climate modeling results reported by the IPCC since it was established in 1988. The USGCRP has blindly followed the IPCC and many of the climate modeling groups have contributed to both the IPCC and the USGCRP reports.

Assessment of RF has been firmly embedded in IPCC assessments from its FAR [First Assessment Report] onward. FAR (Shine et al. 1990) took as its starting point the fact that the climate impact of a range of different climate forcing agents could be compared using RF, in watts per square meter, even though this was only starting to be done routinely in the wider literature at the time. Ramaswamy et al, 2019 p. 14.11

An earlier version of USGS2020 Figure 1 can be found as figure 19 in a review paper by Hansen et al [1993]. This is shown in Figure 7. In particular, the top panels are similar to figures 4c and 7 (‘global’ panel) from Jones et al [2013]. These show model calculations of the influence of a ‘greenhouse gas forcing’ on the global average temperature.

Hansen, J., A. Lacis, R. Ruedy M. Sato and H. Wilson (1993), “How sensitive is the world's climate?” National Geographic Research and Exploration 9(2) pp. 142-158. [https://pubs.giss.nasa.gov/docs/1993/1993_Hansen_ha02800o.pdf] Hansen.1993

Ramaswamy et al credit Hansen et al, 1981 (H81) as the first to demonstrate the evolution of the irradiance changes in their radiative convective model. The reference is:

Hansen, J., D. Johnson, A. Lacis, S. Lebedeff, P. Lee, D. Rind and G. Russell (1981), “Climate impact of increasing carbon dioxide” Science 213 pp. 957-956. [https://pubs.giss.nasa.gov/docs/1981/1981_Hansen_ha04600x.pdf] Hansen.1981

Figure 8a shows H81 figure 4 that illustrates the perturbation produced in a 1-D radiative convective model by a radiative forcing, in this case a doubling of the CO₂ concentration from 300 to 600 ppm and the subsequent return to an ‘equilibrium state’ with a higher surface temperature. Figure 8b shows H81 figure 2 that illustrates the estimated change in temperature produced by changes in various ‘forcing agents’. Figure 8c shows the global temperature from H81 figure 3. For comparison, the increase in atmospheric CO₂ concentration has been added to this plot [Keeling, 2022]. The large peak centered near 1940 is clearly not related to changes in the CO₂ concentration. This is the same peak as the one near 1940 in USGS2020.

The changes in equilibrium flux produced by a doubling of the CO₂ concentration shown in Figure 8a evolved into the more elaborate pseudoscientific CO₂ doubling ritual and the climate sensitivities still used today. The aerosol ‘control knobs’ were not working properly, so additional ‘efficacy’ fudge factors were added to radiative forcings by Hansen et al in 2005. Figure 9 shows the illustration of the CO₂ doubling ritual from Figure 8.1 of the IPCC AR5 WG 1 report [IPCC, 2013]. This was adapted from Hansen et al [2005]. When the normal daily and seasonal changes in flux and temperature are included, the surface and tropospheric temperature changes produced by the ‘CO₂ doubling’ are too small to measure.

The Atlantic Multi-decadal Oscillation

To start, the ‘signal’ of the Atlantic Multi-decadal Oscillation (AMO) has to be extracted from the ‘global mean temperature change’. Inspection of Figure 8c, the temperature record used in H81, shows a large peak centered near 1940. This is from the warming phase of the AMO. It has nothing to do with changes in the atmospheric CO₂ concentration. Figure 10a shows the AMO and the HadCRUT4 ‘global temperature record’ plotted on the same graph. The plots are temperature anomalies with the mean subtracted from the averages. The AMO offset was adjusted to overlap with HadCRUT4 from 1850 to 1970. 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 on the figure. Before 1970, the AMO and HadCRUT4 track quite closely. This includes both the long period oscillation and 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 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 Indian Ocean Dipole (IOD) and the Pacific Decadal oscillation (PDO) are dipoles that tend to cancel and the El Nino Southern Oscillation (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 10b shows a tree ring construction of the AMO from 1567 [Gray, 2004, Gray.NOAA, 2021]. 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. (See the post ‘Climate Pseudoscience’ VPCP.012 for further details).

Using Figure 10a as a guide, the AMO signal can be identified in the global temperature record shown in Figure 1 from USGS2020. This is illustrated in Figure 11. The red shaded box from 1910 to 1940 is drawn to include most of the warming AMO signal from the temperature record. This box has simply been copied and superimposed on the temperature record starting from 1970 to indicate the most recent warming phase of the AMO, assuming it to be similar to the 1910 to 1940 temperature changes. 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 by Andrews [2017a, 2017b and 2017c] and by D’Aleo and Watts [2010]. Adjustments to the Australian temperature record have been discussed by Berger and Sherrington [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 in 1938. He used weather station temperatures up to 1935 that included most of the 1910 to 1940 warming phase of the AMO [Callendar, 1938]. The warming that he observed was from the AMO not 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, Douglas, 1975, 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 [Hansen, 1981] (see Figure 8c). Similarly Jones et al conveniently overlooked the 1940 AMO peak when they started to ramp up the modern global warming scare in 1986 [Jones et al, 1986]. This is illustrated in Figure 12. The AMO and the periods of record used are shown in Figure 12a. The temperature records used by Callendar, Douglas, Jones et al and Hansen et al are shown in Figures 12b through 12e. The Keeling curve showing the increase in atmospheric CO₂ concentration is also shown in Figures 12d and 12e [Keeling, 2022].

Radiative Forcing

When the atmospheric concentration of CO₂ is increased in the M&W ‘equilibrium air column’ model, there is an initial decrease in the LWIR flux emitted at the top of the model atmosphere (TOMA) within the spectral region of the CO₂ emission bands. The model is configured so that the surface and air layer temperatures then adjust until the LWIR flux at TOMA is restored to its equilibrium value, equal to the absorbed solar flux. In addition, the relative humidity (RH) distribution of the air layers is fixed. As the temperature increases, the water vapor pressure increases and so does the water vapor concentration at fixed RH. This establishes a ‘water vapor feedback’ in the model that ‘amplifies’ the temperature increase.

In the real world, on planet earth, there is no equilibrium. The solar flux changes on both a daily and a seasonal time scale. There are significant time delays or phase shifts between the peak solar flux and the surface temperature response. This is clear evidence of a non-equilibrium thermal system [Clark and Rörsch, 2023]. A change in flux produces a change in the rate of heating or cooling of a set of coupled thermal reservoirs. The surface is cooled by a combination of net LWIR emission and moist convection (evapotranspiration). Heat is also transported below the surface. Over land, this subsurface heating is localized and almost all of the absorbed solar flux is dissipated within the same diurnal cycle. Over the oceans, the absorbed subsurface heat can be transported over long distance by ocean currents. Convection is a mass transport process that is coupled to both the gravitational potential and the rotation or angular momentum of the earth. This leads to the formation of the Hadley, Ferrel and polar cell convective structure, the trade winds, the mid latitude cyclones/anticyclones and the ocean gyre circulation. The LWIR flux cannot be separated from the mass transport processes and analyzed independently of the other flux terms.

The effect of an increase in atmospheric CO₂ concentration on the LWIR flux is illustrated in Figure 13. The observed increase in atmospheric CO₂ concentration since 1800 is shown in Figure 13a [Keeling, 2022]. The decrease in LWIR flux at TOA (radiative forcing) and the corresponding increase in downward LWIR flux to the surface as the CO₂ concentration is increased from 0 to 760 ppm is shown in Figure 13b [Harde, 2017]. The total (10 to 3250 cm^-1) and spectral band average LWIR cooling rates for a tropical atmosphere are shown in Figure 13c [Feldman et al, 2017]. The cooling rate for most of the troposphere is in the range 2 to 2.5 K per day. The change in the rate of LWIR cooling in the troposphere produced by a doubling of the CO₂ concentration is shown in Figure 13d [Iacono et al, 2008]. The maximum change is +0.08 K per day. This daily change in temperature is equivalent to riding an elevator down four floors. Figure 13e illustrates the energy transfer processes for an air parcel in the troposphere (within the plane parallel atmosphere approximation). The air parcel is emitting LWIR radiation upwards and downwards at the local temperature. It is also absorbing part of the upward LWIR flux from below and the downward LWIR flux from above. The air parcel is also in a turbulent convective flow field. Vertical motion changes the temperature of the air parcel at the local lapse rate. Figure 13f illustrates the dissipation of the radiative forcing in the troposphere. There is an initial decrease in the LWIR flux at TOA within the spectral region of the CO₂ emission bands. However, this is produced by local absorption at many different levels in the atmosphere as shown in Figure 13d. The heat is coupled to the local air parcels and dissipated as wideband LWIR emission, mainly by the water bands. Any change in temperature is too small to measure. Figure 13g shows the vertical velocity profile up to 2 km altitude in the turbulent surface boundary layer. This is from Doppler heterodyne LIDAR measurements recorded over 10 hours at the École Polytechnique, south of Paris, July 10th 2005 [Gibert et al, 2007]. The change in vertical velocity is ±2 m s^-1. This is sufficient to overwhelm any changes in cooling from a ‘CO₂ doubling’ as shown in Figure 12d. The radiative forcings produced by the increase in atmospheric concentration of ‘greenhouse gases' cannot change the energy balance of the earth.

Figure 13: a) the measured increase in atmospheric CO₂ concentration from 1800 (Keeling curve). b) Calculated changes in atmospheric LWIR flux produced by an increase in atmospheric CO₂ concentration from 0 to 760 ppm. c) Total (10 to 3250 cm^-1) and band-averaged IR cooling rate profiles for the Tropical Model Atmosphere on a log-pressure scale. d) Tropospheric heating rates produced by a CO₂ ‘doubling’ from 287 to 574 ppm at mid latitude. e) The energy transfer processes for a local tropospheric air parcel (in a plane-parallel atmosphere). f) The dissipation of the absorbed heat from a ‘CO₂ doubling’ by the normal tropospheric energy transfer processes (schematic). The wavelength specific increase in absorption in the CO₂ P and R bands is dissipated as small changes in broadband LWIR emission and gravitational potential energy. g) Vertical velocity profile in the turbulent boundary layer recorded over 10 hours at the École Polytechnique, south of Paris, July 10th 2005 using Doppler heterodyne LIDAR.

Over the oceans, the surface is almost transparent to the solar flux. Approximately 90% of the solar flux is absorbed within the first 10 m layer of the ocean. 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. This is illustrated in Figures 14a and 14b [Hale and Querry, 1973]. 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 14c 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 13b, 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. At present, the average increase in CO₂ concentration is near 2.4 ppm per year. This produces an increase in downward LWIR to the surface near 0.034 W m^-2. This is dissipated by an increase in wind speed of approximately 2 mm per year.

Over land, all of the flux terms are absorbed by a thin surface layer. The surface temperature initially increases after sunrise as the solar flux is absorbed. This establishes a thermal gradient with both the cooler air above and the subsurface ground layers below. The surface-air gradient drives the evapotranspiration and the subsurface gradient conducts heat below the surface during the first part of the day after sunrise. Later in the day, as the surface cools, the subsurface gradient reverses and the stored heat is returned to the surface. As the land and air temperatures equalize in the evening, the convection stops and the surface cools more slowly by net LWIR emission. This convection transition temperature is reset each day by the local weather system passing through. Almost all of the absorbed solar heat is dissipated within the same diurnal cycle. The temperature changes produce by an increase in LWIR flux near 2 W m-2 are too small to detect in the normal diurnal and seasonal variations of the surface temperature [Clark and Rörsch, 2023 Clark, 2013].

Climate Sensitivity

The denizens of the Equilibrium Climate Fantasy Land have chosen to believe that the ‘global mean temperature change’ is caused by radiative forcing combined with feedback effects. The equilibrium climate models are ‘tuned’ so that there is a set of ‘radiative forcings’ in each model that create the global temperature change record. The models are compared by simulating the increase in ‘global temperature’ produced by a doubling of the CO₂ concentration in the model. This pseudoscientific benchmark is called the climate sensitivity. There are two different ways that the climate sensitivity is determined. First, the CO₂ concentration is simply doubled and the model is run to ‘equilibrium’. This is called the equilibrium climate sensitivity (ECS). Second, the CO₂ concentration is increase gradually, usually by 1% per year. The temperature change at the CO₂ doubling point is call the transient climate response (TCR).

In order to ‘validate’ the climate models, a similar exercise is applied in reverse to the measured ‘global mean temperature record’. This may be illustrated by considering the work of Otto et al [2013]. They defined the climate sensitivities as

The change in temperature is taken from the HadCRUT4 global temperature anomaly and the radiative forcings are taken from the CMIP5 /RCP4.5 model ensemble. The change in heat content is dominated by ocean heat uptake. The decadal temperature and forcing estimates from data given by Otto et al are shown in Figures 15a and 15b. The 1910 AMO cycle minimum and the 1940 maximum are indicated. The increase in the downward LWIR flux related to the ‘radiative forcing’ shown in Figure 15b cannot couple below the ocean surface and cause any measurable change in ocean temperature. Using the data from Figures 15a and 15b combined with estimates of Delta Q from various sources, Otto et al assume that their net radiative forcing estimates are responsible for the observed heating effects and that the temperature response to the change in LWIR flux is linear. Plots of Delta T vs (Delta F-Delta Q) and Delta T vs Delta F are therefore presumed to be linear with a slope that changes with the value of ECS or TCR. The results generated by Otto et al are shown in Figures 15c and 15d. Using the data for 2000 to 2010, they create an ECS of 2.0 °C with a 5-95% confidence interval of 1.2 to 3.9 °C and a TCS of 1.3 °C with a confidence level of 0.9 to 2.0 °C. The radiative forcings and their time evolution published in the IPCC AR5 climate assessment report [IPCC AR5 Wgp 1 Chap 8, 2013, Figures 8.17 and 8.18] are shown in Figure 15e and 15f. The forcings for the ‘greenhouse gases’ are derived from radiative transfer calculations using the HITRAN database or similar data. The various aerosol terms are simply ‘tuning knobs’ that can be adjusted to give a better fit to the measured temperature data. As shown in Figure 14 above, the LWIR flux cannot heat the oceans because the penetration depth of the LWIR flux is less than 100 micron. Within the ±30° latitude bands the increase in downward LWIR flux of 2 W m-2 from the 140 ppm increase in atmospheric CO₂ concentration is dissipated as latent heat by an increase in wind speed of 13 cm s^-1. The red dotted lines added to Figure 15f indicate the total LWIR forcings and the increase in latent heat flux produced by an increase in wind speed of 13 cm s^-1. The ECSs for the CMIP5 and CMIP6 model ‘ensembles’ are shown in Figures 15g and 15h. The CMIP 5 range is from 2.1 to 4.7 °C and the CMIP6 range is from 1.8 to 5.6 °C [IPCC 2013, Chap. 9 Zelinka et al, 2020 Hausfather, 2019]. The correct number is ‘too small to measure’. The fundamental error, that the increase in LWIR flux can heat the oceans, can be traced back to Hansen et al, 1981.

Figure 15: a) Decadal mean temperature estimates derived from the HadCRUT4 global mean temperature series. b) Decadal mean forcing with standard errors from the CMIP5 /RCP4.5 ensemble. c) Estimates of ECS and d) TCR from Otto et al [2013]. e) Radiative forcings from Figure 8.17 of IPCC AR5 WG1. f) The time dependences of the radiative forcings from f) adapted from figure 8.18 of IPCC AR5. g) The climate sensitivities of various CMIP5 models from IPCC AR5 WG1 Table 9.5 and h) CMIP6 climate sensitivities from Hausfather [2019].

The ‘Attribution’ of Extreme Weather Events

The use of radiative forcings to create a spurious ‘climate sensitivity’ to CO₂ have led to absurd claims that increases in the atmospheric CO₂ concentration can cause increases in every imaginable form of ‘extreme weather event’. One of the more egregious examples of this is 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 clearly 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 climate sensitivities created in CMIP5 and CMIP6 model ensembles and other in 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.

An important source of heat in the lower troposphere is air compression. This has been largely ignored by the USGCRP. As dry air descends to lower altitudes, the lapse rate is 9.8 K km^-1. There are two main effects. The first is heating by downslope winds and the second is the heating produced by the down flow of air within a high pressure ‘dome’. These processes can produce temperature changes of 10 °C or more over a few days or less. Downslope winds are well known in many regions or the world and there are many different names for the same effect. In S. California they are Santa Ana Winds. In N. California they are diablo winds. In the Rocky Mountains they are chinook (‘snow eating’) winds. In the Alps they are föhn winds. There is no connection between these downslope wind events and any increase in atmospheric CO₂ concentration. Once the necessary weather pattern is established, the hot, dry winds will finish drying out the vegetation very quickly and any ignition source will start a wildfire. The Santa Ana winds in S. California are a good example of this.

The air circulation within a high pressure system produces a downward air flow because of the Coriolis Effect. This provides a natural heat source for these systems. A stationary or blocking high pressure system can result in significant warming over a period of several days [Clark and Rörsch, 2023]. For example, a high pressure dome formed over the Pacific NW region in late June, 2021 and stayed there for a week as maximum daily temperatures increased from 83 to 116 F. When this system moved east, the overnight temperature in Portland OR, June 28 to 29, dropped 52 °F from 116 to 64 °F (29 °C from 47 to 18 °C) [Mass, 2021]. None of this has any relationship to CO₂. At present the annual average increase in atmospheric CO₂ concentration is near 2.4 ppm and the corresponding annual increase in downward LWIR flux to the surface is 0.034 W m^-2.

Similarly, there has been no increase in hurricanes or tornados. However with satellite and radar observations, more hurricanes and tornados can be detected. In addition, with more construction in hurricane and tornado prone areas, the amount of damage that can be produced is larger. This has to be included in any analysis. Figure 16 shows the global frequency of hurricanes (12 month running sums) from 1980 for all hurricanes (≥ 64 knots) and all major hurricanes (≥ 96 knots) [Maue, 2022]. There is no obvious upward trend in the data. Figure 17 shows the monthly US tornado count from 1990 during the period when Doppler radar was in use. The count is highly variable and there is no obvious trend in the data [NOAA, tornadoes, 2022]. For reference, the average is 102±98 tornadoes per month (1 sigma standard deviation) and the slope for the linear fit is flat (+0.15 tornadoes per decade).

The melodramatic claims of increases in ‘global temperature’ based on nothing more than fraudulent climate model results are then used to make equally melodramatic claims of adverse effects on the regional climates of the United States. Droughts and floods from the climate apocalypse have replaced the fire and brimstone of older religious beliefs. The role of natural weather events is understated or ignored. Historical data has been ignored. For example, there were two periods of low rainfall in the western US that lasted over 100 years each between 900 and 1300 AD as shown in Figure 18 [Cook et al, 2007]. These occurred when the CO₂ concentration was still at ‘preindustrial’ levels.

These droughts occurred during a time known as the medieval warming period. Greenland was inhabited by Norsemen for approximately 500 years from about 985 AD. At its peak, the population has been estimated to be between six and ten thousand people. Archaeological excavations have revealed 620 Norse farms that are now under permafrost [Shepherd, 2016]. Figure 19 shows the ruins of Hvalsey Church, Greenland. Church records ended there in 1408. Clearly, the coastal areas of Greenland that were farmed by the Norsemen were warmer during the Medieval Warming Period than they are today.

In spite of the melodramatic claims made about global warming apocalypse by the USGCRP, the climate record is clear. There is nothing unusual about the earth’s climate today. There is good reason to expect the long term cooling trend that started about 6000 years ago to continue as the earth slowly transitions into the next Ice Age.

All claims of an increase in ‘extreme weather events’ such as droughts, floods, heat waves, hurricanes and tornadoes because of an increase in atmospheric CO₂ concentration are completely fraudulent.

The Radiation Balance of the Earth

The radiative forcing argument assumes that an exact annual average planetary flux balance between the absorbed solar flux and the LWIR flux at TOA should exist for a hypothetical ‘equilibrium climate state’. The First Law of Thermodynamics, conservation of energy, simply requires that any energy imbalance at TOA be accounted for as a change in the energy stored somewhere in the climate system. The earth’s climate has been sufficiently stable over several billion years to allow for the evolution of life into its present forms. This means that there is an approximate planetary energy balance between the absorbed solar insolation and the outgoing longwave radiation (OLR) at TOA). The only requirement is that this energy balance has to maintain the surface temperature within the bounds needed to sustain life. There is no requirement for an exact flux balance at the ocean surface between the absorbed solar flux and the surface cooling. There are natural, quasi-periodic, wind driven oscillations that provide the ‘noise floor’ for the surface temperature. Therefore, there is no reason to expect an exact flux balance at TOA.

The earth is a rotating water planet with a surface that is 71% ocean. The ocean surface is almost transparent to the solar flux. Approximately 90% of the solar flux is initially absorbed within the first 10 m layer of the ocean and this heat is distributed by convection and wave action within a thermal layer that may reach 100 m depth or more. The large heat capacity of this ocean layer stabilizes the earth’s climate. The diurnal surface temperature change is typically 1 °C or less. The seasonal change is generally near 6 °C or less. The ocean temperature changes with latitude from approximately 30 °C in the equatorial warm pools to -1.8 °C at higher latitudes when seawater starts to freeze. The earth has been warming naturally since the end of the Maunder minimum or Little Ice Age (LIA) [Akasofu, 2010]. From 1955 to 2021 the heat content in world’s oceans to 700 m depth has increased by approximately 22x10²² J. The corresponding average temperature rise is near 0.2 °C [NOAA, 2022].

The energy transfer processes that determine the surface temperature of the earth and the radiation balance at TOA are complex. The net radiation budget of the earth is illustrated in Figures 21 and 22. Near equinox in March and September, there is a wide band centered on the equator where the net radiation is positive. This region extends over a nominal ±35° latitude range. More solar heat is absorbed than is radiated back to space by the OLR. This band shifts north and south with the seasons and at solstice it extends from the equator to 70° N or 70° S [Kandel and Viollier, 2010, CERES, 2004]. In addition, the maps are projections of a spherical surface. The surface area of a sphere decreases as the latitude increases. This has to be included in the quantitative analysis of the earth’s radiation budget.

Starting with Nimbus 6 in 1975, satellite observations have been used to establish a radiation budget for the earth (ERB). The complexities of the climate energy transfer, as illustrated in Figure 16, have been reduced to three numbers, an average incident solar flux at TOA or total solar insolation (TSI), an average absorbed solar flux, usually determined by the difference between the reflected solar flux and the TSI, and the average OLR. The reflected solar flux is often converted to an albedo or reflectivity. Early work on ERB is described by Kyle et al [1993]. Further details are provided by Kandel and Viollier [2010]. Dewitte and Clerbaux [2017] give the TSI at solar minimum as 1362 W m^-2 with an albedo of 29.8% and a mean OLR of 238 W m^-2. These mathematical averages have no useful physical meaning and the dominant term in any residual imbalance is usually a change to the amount of heat stored in the oceans. There is no relationship between changes in ocean heat content and the ‘radiative forcing’ by ‘greenhouse gases’.

Where was the Oversight?

Speculation that changes in the atmospheric concentration of CO₂ could cycle the earth through an Ice Age started in nineteenth century [Tyndall, 1861, 1863]. An ‘equilibrium air column’ model was used by Arrhenius in his invalid 1896 calculations of the temperature changes caused by variations in the atmospheric CO₂ concentration [Arrhenius, 1896]. By the early 1960s the idea that increases in the atmospheric concentration of CO₂ from fossil fueled combustion could warm the earth had become scientific dogma. The first generally accepted climate model was published by Manabe and Wetherald (M&W) in 1967. They used a modified version of the ‘equilibrium air column’. The assumptions that they used were clearly stated in their paper [M&W, 1967]:

At the top of the atmosphere, the net incoming solar radiation should be equal to the net outgoing long wave radiation.
No temperature discontinuity should exist
Free and forced convection and mixing by the large scale eddies prevent the lapse rate from exceeding a critical lapse rate equal to 6.5 C km^-1.
Whenever the lapse rate is subcritical, the condition of local radiative equilibrium is satisfied.
The heat capacity of the earth’s surface is zero.
The atmosphere maintains the given vertical distribution of relative humidity (new requirement).

These assumptions contain three fundamental scientific errors.

There is no flux balance at TOA. (Has anyone seen a 24 hour average sun shining in the sky at night?)
The heat capacity and the effects of moist convection have to be included in the surface heating
The relative humidity distribution is not fixed.

In addition, molecular line broadening in the lower troposphere means that the upward and downward LWIR fluxes are not equivalent.

When the CO₂ concentration was increased in the M&W model, the surface temperature had to increase as a mathematical artifact of the simplifying assumptions used in the model. M&W did not discuss the limitations of the assumptions used to construct the model. There were no independent thermal engineering calculations of the change in surface temperature using the time dependent flux terms. Detailed surface temperature and flux data were available from Letteau and Davidson [1957]. The model required a year to reach equilibrium (time step multiplied by the number of iterations). No one asked how these small changes could be measured in the real climate when the normal daily and seasonal temperature changes were included.

M&W were the first to play computer games in the Equilibrium Climate Fantasy Land.

They spent the next 8 years building a totally useless ‘primitive’ GCM in which the 1967 mathematical artifacts were built into each unit cell of the larger model. Why were they allowed to do this? Why were the Lorenz instabilities ignored?

The 1981 Hansen paper contained three more scientific errors in addition to the four already made by M&W.

When the ‘slab’ ocean was added to their model, there was no consideration of the ocean surface energy transfer, particularly the surface evaporation and the penetration depth of the LWIR flux into the oceans. The small increase in LWIR flux from CO₂ does not change the temperature of the oceans (see Figure 13).
The discussion of ‘CO₂ doubling’ was based on the M&W equilibrium approach. It had nothing to do with the real non-equilibrium climate.
There was a ‘bait and switch’ from ‘equilibrium model’ surface and air temperatures to weather station temperatures. There was no quantitative discussion of the surface energy transfer and how the change in LWIR flux from a CO₂ doubling could heat the surface when the time dependence was included. The obvious 1940 AMO peak in the temperature record was also ignored (see Figure 11e).

NASA has a well-established review process based on Technology Readiness Levels (TRLs). Why was this process not applied to Hansen’s models? Similarly, where is the thermal engineering analysis of the effect on CO₂ on the surface temperature for such missions as the OCO satellite and the EMIT instrument on the Space Station?

The M&W approach was officially ‘sanctified’ by the Charney report [1979]. This was a review of CO₂ induced warming effects derived from equilibrium climate models, including feedback effects. The reviewers concluded that a warming of 3±1.5 °C from a ‘doubling’ of the atmospheric CO₂ concentration was likely. The mathematics used in the climate models appeared reasonable based on the acceptance of the invalid equilibrium assumption, so no further investigation was needed. Lorenz’s work and the limitations of the weather forecasting models were ignored.

The reviewers involved in the Charney report also chose to ignore the history of CO₂ induced climate change and its origin as the explanation of the cause of an Ice Age cycle. The real cause of an Ice Age was planetary perturbations of the earth’s orbit known as Milankovitch cycles. This had been established in 1976 from an analysis of deep drilled ocean sediment cores [Hays et al, 1976]. A more detailed description was given in the book ‘Ice Ages’ by Imbrie and Imbrie [1979]. Since changes in CO₂ concentration did not cause an Ice Age, there was no reason to expect that such changes from fossil fuel combustion would cause climate change. Tyndall’s speculations from the 1860’s had been disproved.

From 1940 to 1970, the AMO was in its cooling phase. This led to speculation about ‘global cooling’ and the onset of an Ice Age. The AMO then changed to its warming phase. By 1986, the AMO warming could be detected in the weather station record (see Figure 12 and the related discussion). Why was this change from global cooling to global warming accepted without question? Did this not demonstrate that something was wrong with the equilibrium climate models?

By the time that the USGCRP was established in 1989/90, the equilibrium climate modeling fraud was fully established. The climate modelers were not scientists capable of independent inquiry. They were disciples of the Imperial Cult of the Global Warming Apocalypse. They chose to believe in the radiative forcings and the mathematical equations coded into their computers. The forcings changed the energy balance of the earth and perturbation to the climate equilibrium state was restored as the global surface temperature increased. The Sacred Spaghetti Plots from the computer models had to be correct. They had to save the world from a non-existent problem. When they went down the rabbit hole into the Equilibrium Climate Fantasy Land they became trapped in the Climate Web of Lies. Continued funding required that they maintain the illusion of the Climate Apocalypse. Eisenhower’s warning about the corruption of science by government funding had already come true.

Instead of conducting an independent review of the equilibrium climate models and their ‘predictions’, the USGCRP has blindly copied climate model results and the IPCC reports. The organization has relied on melodramatic temperature increases from fraudulent climate models to promote the coming of the Climate Apocalypse. Figure 23a shows the plot of climate model results from page 17 of the 2000 ‘National Assessment Synthesis Report Overview’. Figure 23b shows some later CMIP5 model results compared to the HadCRUT4 and UAH lower troposphere temperatures [Spencer, 2013]. The divergence of the model results with time is caused by Lorenz instabilities. The climate models have clearly failed and yet they are still used by USGCRP and the IPCC.

There are several reasons for the lack of oversight at USGCRP. First of all, most of the people associated with the program do not have a strong background in climate physics. Even climate modeling requires expertise in mathematics in areas such as fluid dynamics and the computer skills to run very large programs on super computers. Second there is a basic issue with conflict of interest. Who is going to risk unemployment and even jail time by revealing the climate fraud? The people playing computer games in the Equilibrium Climate Fantasy Land have a vested interest in perpetuating the illusion of the climate apocalypse. The signal from the AMO in the ‘global temperature record’ has been ignored for over 40 years. Why did Terando et al overlook this? Third, the various measurement programs associated with the USGCRP are required to produce the data that supports the fantasy of radiative forcing in an equilibrium average climate, otherwise their funding is at risk. These programs include the earth’s radiation budget, the Argo float program, ARM and AmeriFlux research programs and a many other related activities. Similarly, the climate apocalypse has been used to justify extensive radiative transfer and related calculations. The results from Iacono et al (Figure 12d) were published in 2008. Why have they been ignored for 14 years? This is just the first tier of a massive multi-trillion dollar pyramid scheme that feeds the on the fraudulent climate model data. There are a large number of powerful vested interests that want to perpetuate the climate fraud including some at very high national and international levels. This is the work of the Imperial Cult of the Global Warming Apocalypse. It is time to shut down the USGCRP and dismantle the Equilibrium Climate Fantasy Land.

References

Akasofu, S.-I. (2010), “On the recovery from the Little Ice Age” Natural Science 2(11) pp. 1211-1224. Akasofu

AMO (2022), AMO

Andrews, R. (2017a), “Adjusting Measurements to Match the Models – Part 3: Lower Troposphere Satellite Temperatures” Energy Matters Sept 14. Andrews a

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