Work on the the Fifth National Climate Assessment Report, NCA5 has started. A draft outline was published and public comments were requested. The comment period closed on Feb. 20th. The outline makes it clear that this is the Deep State refilling its Pork Barrel. This is discussed in more detail in the post below. An extensive set of comments was submitted by Roy Clark. A .pdf file of these comments is available at this link


RC_NCA5_Comments




'GREENWASHING' CONGRESS WITH NCA5, THE FIFTH NATIONAL CLIMATE ASSESSMENT: REFILLING THE PORK BARREL FOR THE DEEP STATE



Ventura Photonics Climate Post 007.1 Feb. 25, 2022


Roy Clark





The Global Change Research Act (GCRA) of 1990 requires a quadrennial ‘Climate Assessment Report’ from the 13 Federal Agencies involved in ‘Climate Research’. The fifth such report, NCA5 is in preparation and the comment period on the outline closed on February 20 th 2022.


The first question of course is


Do any of the NCA5 reviewers understand anything about the earth’s climate?


Based on the NCA5 outline, the short answer is no. The only ‘climate’ considered is the fictional one found in the CMIP5/6 climate model ‘ensembles’. There is no quantitative discussion of the relationship between the changes in the long wave IR (LWIR) flux in the atmosphere produced by an increase in the concentration of ‘greenhouse gases’ and the earth’s climate. The validity of the equilibrium climate model results is never questioned. Climate change is already a disaster that has to be ‘mitigated’. The climate crisis is real. Spend money. The authors of NCA5 want to keep their government jobs or government funds. Fill the trough.


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


Over the past 200 years, the atmospheric concentration of CO2 has increased by approximately 130 parts per million (ppm), from 280 to 410 ppm. The concentration continues to increase and is now approaching 420 ppm [Keeling, 2021]. This has produced a decrease near 2 W m-2 in the longwave IR (LWIR) flux emitted to space within 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. This produces an annual increase in the downward LWIR flux to the surface of approximately 0.034 W m-2.


Explain, using quantitative 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 downward LWIR flux to the surface changed the ocean surface temperatures?

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

4) How does an annual increase of 0.034 W m-2 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’. It is time to tell congress to dismantle a massive, multi-trillion dollar climate fraud. To start, shut down the equilibrium climate models and all of the secondary deep state ‘policy’ modeling that feeds from the same trough. There is no ‘climate crisis’. It is time to start the ‘clawback’ process used on other ‘Ponzi’ or pyramid schemes. Do you remember Bernie Madoff?


The underlying technical problem is the climate equilibrium assumption that has been used to oversimplify the climate transfer processes that determine the surface temperature. This creates a fake warming in the climate models. Has anyone seen a 24 hour average sun shining in the sky at night?




To start, the earth is not in thermal equilibrium. Unlike the moon, the earth’s surface does not heat up under solar illumination so that emitted LWIR flux matches the absorbed solar flux [Vasavada et al, 2012]. A change in flux produces a change in the rate of heating or cooling of the thermal reservoirs that form the earth’s climate system. A change in temperature produced by CO2 has to be determined from the change in heat content or enthalpy of the thermal reservoir of interest over a thermal cycle with and without the change in LWIR flux from CO2. The temperature change is the local change in enthalpy divided by the local heat capacity. A change in LWIR flux cannot be used to determine a change in temperature using the Stefan Boltzmann Law. The change in LWIR flux has to be added to all of the time dependent flux terms. These flux terms are interactive and cannot be separated and analyzed independently of each other [Clark, 2013].


There are also significant time delays or phase shifts between the peak daily or seasonal solar flux and the temperature response that are clear evidence of a non-equilibrium thermal response. For example, at mid latitudes, peak temperatures occur 4 to 8 weeks after summer solstice. Such phase shifts are not new science. They have been recorded in the weather station data for well over 100 years. Seasonal subsurface ground temperature phase shifts were described by Fourier in 1824 [Fourier, 1824]. The observation of these phase shifts is sufficient scientific evidence to invalidate the equilibrium climate assumption.


The outgoing longwave IR radiation (OLR) emitted to space at the top of the atmosphere (TOA) consists of the LWIR emission from many different levels in the atmosphere below. The LWIR emission from each level is modified by the absorption and emission of the layers above. Conservation of energy requires that the long term planetary average LWIR emission to space should be near 240 W m-2. Satellite radiometer measurements give a value of approximately 240±100 W m-2 [CERES, 2011]. The OLR is simply a cooling flux. The spectral distribution is not that of a blackbody [Wijngaarden and Happer, 2020]. This was obvious from the Nimbus satellite spectra published by Hanel et al [1971]. The planetary average OLR should not be inserted into the Stefan Boltzmann equation and used to calculate an ‘effective emission temperature’ near 255 K. This is just a mathematical construct for a hypothetical blackbody planet. Nor should this 255 K ‘emission temperature’ be combined with an ‘average surface temperature’ of 288 K to create a fictional ‘greenhouse effect temperature’ of 33 K.


The troposphere, land and oceans have different thermal properties and have to be analyzed separately.



In the troposphere, a ‘doubling’ of the CO2 concentration from 287 to 574 ppm at mid latitudes initially produces a maximum decrease in the rate of cooling of 0.08 K per day at an altitude near 2 km [Iacono et al, 2008]. This slight heating is dissipated through a combination of wideband LWIR emission, mainly from the water bands and changes in gravitational potential (net vertical convective motion). At the standard lapse rate of -6.5 K km-1, +0.08 K corresponds to a decrease in altitude of about 12 meters. This is equivalent to riding down 4 floors in an elevator. The overall effect is that the absorbed heat is re-radiated to space through the water bands. It cannot couple to the surface and produce a measureable change in temperature because of molecular line broadening effects. The LWIR component of a ‘radiative forcing’ from a ‘greenhouse gas’ does not change the energy balance of the earth. This means that the concept of radiative forcing is invalid and should not be used for climate assessment [IPCC, 2021, Ramaswamy et al, 2019].


At the surface, the downward LWIR flux from the lower troposphere interacts with the upward LWIR flux from the surface to produce a time dependent exchange energy. Photons are exchanged with little heat transfer. When the surface and air temperatures are similar, the net LWIR cooling flux from the surface is limited to the emission into the LWIR transmission window, mainly in the 800 to 1300 cm-1 spectral region. The net LWIR cooling flux increases with decreasing humidity and decreases with increasing cloud cover. This is the real source of the so called ‘greenhouse effect’. In order to dissipate the absorbed solar heat, the surface warms up until the excess heat is removed by moist convection. This leads to a basic description of the surface temperature in terms of the coupling of four flux terms to the surface thermal reservoir. (Rainfall and freeze/thaw effects are not included here). A change in surface temperature is produced by a change in the heat content or enthalpy of the local thermal reservoir divided by the local heat capacity. The four flux terms, the absorbed solar flux, the net LWIR emission, the moist convection (evapotranspiration) and the subsurface transport are interactive and should not be separated and analyzed independently of each other. The energy transfer processes at the land-air and ocean-air interfaces are different and have to be considered separately [Clark, 2013].


Over the oceans, the penetration depth of the LWIR flux into the ocean surface is less than 100 micron (0.004 in) [Hale and Querry, 1973]. Here it is fully coupled to the wind driven evaporation or latent heat flux. Using long term zonal averages, within the ±30° latitude bands, the sensitivity of the latent heat flux to the wind speed is approximately 15 W m-2/m s-1 [Yu et al, 2008]. The entire increase of 2 W m-2 in downward LWIR flux from CO2 to the surface for the last 200 years is dissipated by an increase in wind speed of about 13 centimeters (5 inches) per second. For reference, a typical pet tortoise can run at about 10 cm s-1 (4 in s-1). An annual average increase in LWIR flux of 0.034 W m-2 from CO2 is dissipated by an increase in wind speed of 2 millimeters per second. This means that there can be no ‘climate sensitivity’ to CO2 or other greenhouse gases. Nor can there be any effect on ‘extreme weather events’ [Herring et al, 2020].



Over land, the solar flux is absorbed by a thin surface layer. The heating is localized and almost all of the stored heat is dissipated within the same diurnal cycle by a combination of net LWIR emission and moist convection as the surface warms and cools. In the evening, the convection essentially stops as the surface and air temperatures equalize. The surface then cools more slowly over night by net LWIR emission. The equalization or convection transition temperature is reset each day by the local weather system passing through. Effects such as air compression in downslope winds or the downward air flow within a ‘blocking’ high pressure system can produce an increase in temperature of 10 C within a few days or less [Math, 1934]. Thermal engineering analysis of the surface temperature using data from a S. California Ameriflux site shows that an increase in LWIR flux to the surface of 2 W m-2 produces an increase in surface or skin temperature of less than 0.1 C [Clark, 2013]. This is too small to measure in the normal diurnal and seasonal variation of the surface temperature. In signal processing terms, it is below the noise floor. In order to reach the lower 1.5 C temperature rise limit prescribed in the Paris Climate Accord, the CO2 concentration would have to increase to a level near 10000 ppm.


The recent warming found, for example in the HadCRUT global temperature record is a combination of natural warming from the Atlantic Multi-decadal Oscillation (AMO), urban heat island effects, warming bias from changes in the number and location of the weather stations used to create the climate average and downright fraudulent ‘adjustments’ to the raw data hidden under the guise of ‘homogenization’ [AMO, 2020, Andrews, 2017a, 2017b, 2017c, D’Aleo, 2010, Gray et al, 2004, HadCRUT4, 2020]. The climate models have simply been ‘tuned’ to match the temperature record. The creation of a climate sensitivity from HadCRUT4 using for example the ‘Gregory method’ is invalid [Gregory et al, 2020, Otto et al, 2013]. The process of ‘attribution’ used to relate the increases in CO2 concentration to ‘extreme weather events’ is also invalid [Herring et al, 2020].


So what is wrong with the climate models? The root technical cause is a fundamental misunderstanding of climate energy transfer starting with the use of the climate equilibrium assumption. The climate modelers have been playing computer games in an equilibrium climate fantasy land for over 50 years. This is compounded by the need for our so called government ‘scientists’ to keep their jobs and the exploitation of the ‘climate apocalypse’ by outside interests. Some groups are using ‘climate change’ to promote their own environmental or political agendas. Others are just stealing tax payer money in the multi-trillion dollar climate pyramid fraud or Ponzi scheme. Eisenhower’s warning about the corruption of science by government funding has come true. NCA5 is a good example of this.



Fourier’s work on the climate phase shift has been ignored for 200 years. Instead, the time dependence of the climate energy transfer was replaced by 24 hour averages. Physical reality was abandoned in favor of mathematical simplicity. Has anyone seen a 24 hour average sun shining in the sky at night? The equilibrium assumption was used by Arrhenius in 1896 to create a spurious warming effect from CO2 and he traced this assumption back to Pouillet in 1836. The equilibrium assumption became accepted scientific dogma and was used by Manabe and Wetherald (M&W) in their 1967 climate model. To this they added a partially reflective blackbody surface with zero heat capacity and a fixed relative humidity distribution in the atmosphere. They also ignored molecular line broadening and assumed that the upward and downward LWIR fluxes were equivalent. They created global warming in their model, by definition, as a mathematical artifact of the simplifying assumptions – before any computer code was even written. Then they spent the next 8 years building their mathematical artifacts into a ‘crude’ global circulation model [M&W, 1975]. This approach was accepted and copied by all of the rest of the equilibrium climate modeling groups without any attempt at independent model validation. A recent re-analysis of the M&W 1967 model produced similar mathematical artifacts to the original work. The equilibrium assumption was accepted without question [Kluft, 2020].


NASA needed money after the end of the Apollo (moon landing) program and NASA Goddard jumped on the global warming bandwagon. The 1981 Science paper by Hansen et al added three more invalid assumptions to M&W. They added a ‘slab’ ocean model with no surface evaporation and created the ‘CO2 doubling’ ritual that became radiative forcing. They also did a ‘bait and switch’ from the ‘equilibrium’ model temperatures to the weather station or meteorological surface air temperature (MSAT) measured at eye level above the ground. No changes were made to the model. The non-equilibrium energy transfer processes that determine the minimum and maximum MSAT are different and have to be determined separately. An average MSAT has little physical meaning. They also ignored the obvious 1940 peak in the weather station data related to the Atlantic Multi-decadal Oscillation (AMO) [Hansen et al, 1981]. The only other change to the climate model assumptions was the addition of radiative forcing ‘efficacies’ [Hansen et al, 2005]. The old Atomic Energy Commission became part of the newly formed Department of Energy in 1977. As funding for nuclear programs diminished, DOE and the National Labs jumped on the global warming bandwagon - ‘super computers for hire’, ‘experts’ available. Today there are about 49 climate modeling groups worldwide running large scale ‘equilibrium’ climate models as part of the CMIP6 ‘ensemble’ [Hausfather, 2019]. None of these groups has ever attempted to validate the underlying assumptions incorporated into these models.



The basic climate assumption is still the same:


“When the radiation balance of the Earth is perturbed, the global surface temperature will warm and adjust to a new equilibrium state. But by how much?”

Knutti and Hegerl 2008


The correct answer is ‘too small to measure’.


The change in flux at TOA is called a ‘radiative forcing’. It is also assumed that there is a linear relationship between the change in forcing and the change in surface temperature. This is governed by a ‘climate sensitivity’. The ‘equilibrium climate sensitivity’ or ECS is the supposed increase in surface temperature for a ‘doubling of the CO2 concentration after the climate system has reached a new ‘equilibrium state’. This requires the absurd belief that all of the increase in the ‘global average temperature anomaly’ is caused by a contrived ‘radiative forcing’. This is also the justification for the 1.5 or 2 C temperature ‘limit’ in the Paris Climate Accord.


In addition, the radiative forcing is amplified by a ‘water vapor feedback’. This is just a carryover from the M&W ‘fixed relative humidity’ assumption. The change in ‘equilibrium’ surface temperature produced by the initial ‘forcing’ creates an increase in ‘equilibrium’ water vapor pressure, which in turn increases the LWIR flux and ‘amplifies’ the temperature increase from CO2. There can be no ‘feedback’ from a temperature increase that is too small to measure. The effect of the moist convection is to reduce any temperature increase as the downward LWIR flux to the surface increases.


There is an extensive discussion of radiative forcings and climate sensitivity in Chapter 7 of Climate Change 2021: The Physical Science Basis, the Working Group 1 Report in the sixth IPCC climate assessment report [IPCC 2021]. All of this is pseudoscientific nonsense. Similar discussions can also be found in all of the prior five climate assessment reports. The IPCC reports are political documents that should not be used as scientific references. Nor should they be used for NCA5.



Another issue that was ignored by M&W and subsequent climate modelers is that the models contain very large numbers of coupled non-linear equations. The numerical solutions to these equations are unstable and the errors increase with time. This was first described by Lorenz in 1963 [Lorenz, 1963]. It is well known that weather forecasting models become unreliable by about 12 days ahead. There is no reason to expect that the climate models have any predictive capabilities over climate time scales. The CMIP ‘ensemble’ is just a collection of quasi-stable pseudo random number generators that are all ‘tuned’ to create the same temperature record using the same pseudoscientific assumptions about radiative forcings and climate sensitivities. The fact that all of these models have a similar climate sensitivity to CO2 is clear evidence of the climate fraud [Zelinka et al, 2020]. A realistic climate model should not show any ‘climate sensitivity’ to CO2.


By accepting the ‘equilibrium assumption’ the climate modelers have abandoned physical reality and entered the realm of computerized climate fiction. They are simply playing computer games in an equilibrium climate fantasy land. Instead of using game boxes, they are wasting billions of tax payer dollars on supercomputers. The equilibrium climate modeling process is still GIGO – garbage in - gospel out. The size and speed of the computer or the quality of the graphics makes no difference. Our so called ‘climate scientists’ are no longer scientists. They have become Prophets of the Imperial Cult of the Global Warming Apocalypse. The peer review process has been replaced by blatant cronyism. Irrational belief in computer models has replaced the Laws of Physics. They have claimed the Divine Right to save the world from a nonexistent problem. They are trapped in a web of lies of their own making.



A quantitative description of the energy transfer processes related to the changes in LWIR flux in the atmosphere can be found in Clark [2013], Fourier [1824], Hale and Querry, [1973], Hanel et al, [1971], Harde, [2017], Iacono et al [2008], Math [1934], Wijngaarden and Happer, [2020] and Yu et al [2008]. The weather station fraud is described by Andrews, [2017a, 2017b, 2017c] and D’Aleo [2010]. Ocean oscillations and adiabatic air compression are described in the Appendix, (Figs 13-15 and 21-24). The fraudulent creation of a ‘climate sensitivity’ from the temperature increase in the ‘global mean temperature change’ related to the AMO is also described in the Appendix, (Figs 21 and 22).


The climate modeling fraud can be understood by examining nine ‘scientific’ papers, starting with five on climate modeling: Arrhenius [1896], Manabe and Wetherald [1967], [1975], Hansen et al [1981] and Knutti and Hegerl [2008]. Radiative forcing is explained by Ramaswamy et al [2019]. Climate sensitivity is described by Gregory et al [2020] and Otto [2013]. The process of climate attribution is described by Herring et al [2020]. Further details may be found in the IPCC climate assessment reports [IPCC, 2021].


This short collection of papers should be sufficient to convince any competent scientist or engineer of the climate fraud. However, are there any competent scientists or engineers to be found among the authors of NCA5? Even so, would any of the NCA5 ‘scientist’ authors risk their job or even jail time by calling out the climate fraud? These are fundamental issues of conflict of interest and fraud that need to be resolved. Most of the authors of NCA5 are involved in equilibrium climate modeling or are part of the next tier of deep state climate ‘policy’ analysts that have chosen to believe the climate models results. They are members of the Imperial Cult of the Global Warming Apocalypse.


The observed increases in the atmospheric concentration of CO2 and CH4 since the start of the industrial revolution have had no measurable effect on the earth’s climate as determined by the weather station or satellite temperature record, sea level changes, polar ice melt, heat waves, fires, floods, hurricanes or tornados. The mathematical artifacts created by the equilibrium climate models, starting with Manabe and Wetherald in 1967 are the imaginary source of the climate warming scare. The primary purpose of NCA5 is to ‘greenwash’ Congress to keep the money flowing. This is the deep state refilling its pork barrel.



APPENDIX

A SUMMARY OF THE SCIENTIFIC EVIDENCE



This Appendix provides a summary of the evidence for a non-equilibrium climate with a climate sensitivity that is ‘too small to measure’


A1: The 'Greenhouse Effect'


The idea behind the so called ‘greenhouse effect’ is that the earth’s surface is warmer is should be based on rather simple conservation of energy arguments. The average solar flux at the top of the atmosphere (TOA) is near 1368 W m-2. The albedo or reflectivity is near 0.3. The geometry is that of a sphere illuminated by a circular beam of nearly collimated solar radiation. The sphere to disk surface area ratio is four. This means that the average LWIR flux returned to space should be near 1368*(1-0.3)/4 ≈ 240 W m-2. IPCC AR6 gives 239 (237 to 242) W m-2. Figure 1 shows an IR image of the long wave IR (LWIR) flux returned to space [CERES, 2011]. While the longer term planetary average may be near 240 W m-2, the short term local variation is ±100 W m-2. The various heating and cooling rates within the climate system interact to keep the surface temperature within the relatively narrow range needed to sustain the development of life on earth. These rates are always changing on diurnal, seasonal and longer time scales. There is no equilibrium.





Figure 1: CERES IR image of the earth, March 8, 2011



Figure 2 shows the spectrally resolved outgoing LWIR radiation (OLR) at TOA for ‘clear sky’ conditions and a surface temperature of 288 K (15 C). The LWIR flux consists of a mix of atmospheric emission, mainly from the H2O and CO2 bands and surface emission through the LWIR transmission window. Some of the surface emission is absorbed by stratospheric ozone. The main spectral features are labelled. Blackbody emission curves at selected temperatures are also shown. The 255 K blackbody emission curve is shown as the black dotted line. It has no relationship to the TOA flux shown by the orange line. The LWIR flux at TOA is just a cooling flux that should not be used to define an ‘effective emission temperature’. There is no ‘shell’ of gas surrounding the earth with a temperature near 255 K. This means that there can be no greenhouse effect temperature near 33 K.





Figure 2: The LWIR flux emitted at TOA. The blackbody emission curves at selected temperatures are also shown. This TOA flux cannot be described as blackbody emission near 255 K. MODTRAN calculation, 288 K surface temperature, 80% RH, 400 ppm CO2, 100 to 1500 cm-1 spectral range, 2 cm-1 spectral resolution, mid latitude summer [MODTRAN, 2020].



Figure 3 shows the downward LWIR flux to the surface for the same conditions as the OLR shown in Figure 2. When the surface and air temperatures are similar, the net LWIR flux limited to the LWIR transmission window, mainly in the 750 to 1300 cm-1 spectral region. The net LWIR flux increases with decreasing humidity and decreases with increasing cloud cover. In order to dissipate the excess absorbed solar insolation, the surface warms up until the heat is removed by moist convection (evapotranspiration). This is the real source of the so called ‘greenhouse effect’.





Figure 3: a) The surface exchange energy (schematic) and b) MODTRAN calculation of the downward LWIR flux to the surface, using the same conditions as Figure 2.



A2: Energy Transfer at the Land-Air and Ocean-Air Interfaces


Over the oceans, the surface is almost transparent to the solar flux. Approximately half of the flux is absorbed within the first meter layer and 90% is absorbed within the first 10 m layer. The diurnal temperature rise at the surface is quite small, typically 2 C or less. The dominant cooling term is the wind driven evaporation or latent heat flux. The LWIR flux is absorbed within the first 100 micron layer. Here it is fully coupled to the wind driven evaporation or latent heat flux. The sensible heat flux term is usually small, less than 10 W m-2. The cooling terms are fully coupled at the surface and should not be separated and analyzed independently of each other. The cooler water produced at the surface then sinks and is replaced by warmer water from below. This is a Rayleigh-Benard type of convective flow with columns of warmer and cooler water moving in opposite directions. It is not a simple diffusion process. In addition, the ocean gyres form a flow system that has to be analyzed separately from the bulk ocean thermal reservoirs.


Over land, the various flux terms interact with a thin surface layer. Almost all of the absorbed solar flux is dissipated within the same diurnal cycle. As the surface warms and cools during the day, heat is removed by a combination of net LWIR emission and evapotranspiration. Some of the absorbed heat is also conducted below the surface and returned later in the day as the subsurface thermal gradient reverses. An important parameter is the evening convection transition temperature at which the evapotranspiration essentially stops. The surface then cools more slowly through the night, mainly by net LWIR emission. The transition temperature is reset each day by the local weather conditions.





Figure 4: The energy transfer processes at a) the ocean-air and b) the land-air interfaces are different and have to be considered separately. The two are coupled through the diurnal convection transition temperature related to weather systems that move over land from the oceans. There is no thermal equilibrium.



A3: The Climate Phase Shift


Figure 5 shows the seasonal phase shifts recorded by seven selected US weather stations near 45° north. The data are from the 1981 to 2010 climate summaries for each station [WRCC, 2020]. The phase shifts vary between 30 and 42 days. Figure 6 shows the monthly temperatures at various depths from 2.5 to 200 m for the Atlantic Ocean at 30 N, 20 W from Argo float data. There is a seasonal phase shift near 8 weeks. These phase shifts are clear evidence for a non-equilibrium climate. Subsurface seasonal phase shifts were described by Fourier in 1824.





Figure 5: Thirty year daily average climate 1981-2010 summary weather station data, a) Tmin and b) Tmax and c) seasonal phase shifts (days past solstice) for 7 selected US weather stations near 45° N, Kennewick, WA, Portland, OR, Casper, WY, Flandreau and Sioux Falls, SD, and Orono and Eastport ME.





Figure 6: The 2.5 m to 200 m depth ocean temperature profiles for 2018 for the N. Atlantic Ocean at 30° N, 20° W derived from Argo float data [Argo 2020]. The data are for a 5° x 1° (latitude x longitude) strip. The seasonal phase shifts are indicated.



A4: The Heating of the Troposphere


Figure 7a shows the increase in the atmospheric concentration of CO2 in parts per million (ppm) since 1800. Figure 7b shows the decrease in LWIR flux at emitted to space at TOA and the increase in downward LWIR flux emitted to the surface from the lower troposphere. The increase in CO2 concentration to date is near 130 ppm and this has produced a decrease in LWIR flux at TOA near 2 W m-2. At present, the average annual increase in CO2 concentration is near 2.4 W m-2 and the annual change in LWIR flux is approximately 0.034 W m-2.





Figure 7: a) The increase in atmospheric CO2 concentration from 1800 [Keeling, 2021] and b) calculated changes in atmospheric LWIR flux produced by an increase in atmospheric CO2 concentration from 35 to 760 ppm [Harde, 2017].



Figure 8a illustrates the effect of molecular line broadening for a single H2O line near 231 cm-1. This is the result of molecular collisions. Near the surface, within the main absorption bands the individual lines merge to form a quasi-continuous blackbody. The upward and downward LWIR fluxes through the atmosphere are not equivalent. Some of the upward flux from the wings of the broader lines below can pass through the gaps between the lines above. Conversely the downward flux from the narrower lines above is absorbed by the wider lines below. Almost all of the downward flux reaching the surface from the main absorption bands is emitted from within the first 2 km layer above the surface. Approximately half of this flux is emitted by the first 100 m layer above the surface. It is this downward flux that provides the photons for the surface exchange energy. The cumulative downward flux from H2O and CO2 vs. altitude is shown in Figure 8b. Four cases are plotted for surface temperatures of 272 and 300 K each with relative humidities of 20 and 70%. The downward flux to the surface increases with temperature and humidity. Even for the lowest flux case, 272 K and 20% RH, 95% of the surface flux originates from within the first 2 km layer. The downward flux to the surface is decoupled from the LWIR emission to space. There is no ‘radiative forcing’.





Figure 8: a) Transition from absorption-emission to free photon flux as the linewidth decreases with altitude. Single H2O line near 231 cm-1, b) Cumulative fraction of the downward flux at the surface vs. altitude for surface temperatures of 272 and 300 K, each with 20 and 70% RH. Almost all of the downward flux reaching the surface originates from within the first 2 km layer. This is the location of the lower tropospheric reservoir [Clark, 2013].



The troposphere divides naturally into two thermal reservoirs. The lower reservoir extends from the surface to 2 km and the upper reservoir extends from 2 km to the tropopause. The troposphere also functions as an open cycle heat engine that transports heat from the surface to higher altitudes in the troposphere by moist convection. From here it is radiated back to space, mainly by the water bands. The local temperature profile of the troposphere is set by the local lapse rate, which depends on the surface temperature, the relative humidity and the convection. The downward flux from the LWIR emission in the stratosphere and upper troposphere is absorbed in the lower troposphere and does not reach the surface.


The local temperature of an air parcel in the troposphere depends on the local flux balance. Within the plane parallel atmosphere approximation there are four contributing flux terms. The air parcel absorbs part of the LWIR flux from above and below. It is also emitting LWIR radiation upwards and downwards. This emission depends on the local temperature and IR species concentrations. As the air parcel changes altitude, particularly during convective ascent, the temperature change from expansion/compression is generally much larger than the LWIR cooling rate. As an air parcel rises and cools, internal molecular energy is converted to gravitational potential energy. For an ascent rate of 1 km per hour at a lapse rate of -6.5 K km-1, the cooling rate is 6.5 K per hour. The tropospheric cooling rate from LWIR emission is near 2 K per day or 0.08 K per hour. The rate of cooling during convective ascent may easily be 100 times larger than that produced by LWIR emission. The energy transfer processes related to the tropospheric heat engine and for an air parcel in the troposphere are illustrated schematically in Figure 9.





Figure 9: a) The tropospheric heat engine and b) energy transfer processes for a local tropospheric air parcel (in a plane-parallel atmosphere)



The decrease in LWIR flux at TOA produced by an increase in the atmospheric CO2 concentration is the result of absorption within the CO2 bands at lower levels in the atmosphere. This is dissipated by the normal convective and radiative energy transfer processes in the troposphere and produces a small increase in both the broadband LWIR emission and the gravitational potential energy as illustrated in Figure 10a. The maximum increase in the rate of heating of the troposphere from a ‘doubling’ of the CO2 concentration is near 0.08 K per day as shown in Figure 10b. Any increase in downward LWIR emission is decoupled from the surface by molecular line broadening effects. For reference, at a lapse rate of -6.5 C km-1, a change in temperature of +0.08 C corresponds to a decrease in altitude of 12 meters. This is equivalent to riding an elevator down about four floors. This is the real heating effect from a doubling of the CO2 concentration.





Figure 10: a) The dissipation of the ‘radiative forcing’ 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. b) Tropospheric heating rate produced by a CO2 ‘doubling’ from 287 to 574 ppm at mid latitude [data from Iacono et al. 2008].



A5: Ocean Evaporation


The penetration depth of the downward LWIR radiation from CO2 into the oceans is 100 micron (0.004 in) or less. This is shown in Figure 11. Here it is fully coupled to the wind driven surface evaporation or latent heat flux. The sensitivity of the ocean latent heat flux to the wind speed may be estimated from long term zonal data. This is shown in Figure 12. Over the ±30° latitude bands, the sensitivity is at least 15 W m-2/m s-1. From Figure 7b, the increase in downward LWIR flux to the surface produced by the observed 130 ppm increase in atmospheric CO2 concentration over 200 years 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. The average increase in CO2 concentration at present is near 2.4 ppm. This corresponds to an annual increase of 0.034 W m-2 in the downward LWIR flux to the surface. This is dissipated by an increase in wind speed near 2 millimeters per second.





Figure 11: Penetration depth of LWIR radiation into the oceans, a) 3300 to 50 cm-1 and b) 1200 to 200 cm-1. The locations of the main CO2 band and the overtones are indicated [Hale and Querry, 1973].





Figure 12: The sensitivity of the ocean latent heat flux to the wind speed [Yu et al, 2008].



This means that LWIR component of a ‘radiative forcing’ cannot heat the oceans. The small increase in LWIR flux is overwhelmed by the much larger magnitude and variation in wind driven evaporation or latent heat flux.


A6: The Role of the AMO in Setting the Surface Temperature


The downward LWIR flux from the lower troposphere creates the so called ‘greenhouse effect’ by ‘blocking’ most of the upward LWIR flux from the surface. This produces the LWIR exchange energy that limits the net LWIR cooling flux. The excess surface heat is removed by moist convection or evapotranspiration, which is a mass transport process. The coupling of the convection to the rotation of the earth leads to the formation of the trade winds that drive the ocean gyre circulation. There is no requirement for an exact local flux balance at the ocean surface between the solar heating and the surface cooling. This leads to natural oscillations in ocean surface temperature. There is no simple mathematical solution to the fluid dynamics of the air-ocean interface and the oscillations are quasi-periodic. The oceans and their fluid dynamics representations can shift from one state to another. The ocean gyre circulation and the four main ocean oscillations are shown in Figure 13. The linear underlying linear trend is attributed to the temperature recovery from the Little Ice Age (LIA) or Maunder Minimum [Akasofu, 2010].





Figure 13: The ocean gyre circulation and the four main ocean oscillations.



Because of the averaging procedures used, the dominant term in the global climate records such as HadCRUT4 is the AMO. The correlation coefficient between the two data sets is 0.8. This is illustrated in Figure 14a. 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. 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 14b shows a tree ring construction of the AMO from 1567. 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 14: 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 [Gray, 2004].



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. 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. 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 in 1986. This is illustrated in Figure 15. The AMO and the periods of record used are shown in Figure 15a. The temperature records used by Callendar, Douglas, Jones et al and Hansen et al are shown in Figures 15b through 15e. The Keeling curve showing the increase in atmospheric CO2 concentration is also shown in Figures 15d and 15e. At present the AMO should have passed through the peak of its warming phase and started the next 30 year cooling phase. However, the AMO is quasi-periodic and the timing of the next cooling phase change may vary.





Figure 15: 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 Hansen et al, [1981] and e) global temperature anomaly from Jones et al, [1986]. The changes in CO2 concentration (Keeling curve) are also shown in c and d. The periods of record for the weather station data are also indicated.



A7: Climate Sensitivity


The HadCRUT4 global average temperature anomaly record and other similar data sets have been used to create two pseudoscientific ‘climate sensitivities’. The first is an ‘equilibrium climate sensitivity’ (ECS) and the second is a ‘transient climate response’ (TCR). The ECS is the equilibrium climate temperature response to a ‘CO2 doubling’ after the model oceans have adjusted to a new ‘equilibrium state’ and the TCR is the response to a gradual increase in the radiative forcing, usually from a 1% per year increase in CO2 concentration before equilibrium is reached.


Otto et al [2013] define these 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 [2013] are shown in Figures 16a and 16b. The 1910 AMO cycle minimum and the 1940 maximum are indicated. The increase in the downward LWIR flux from the lower troposphere to the surface related to the ‘radiative forcing’ shown in Figure 16b cannot couple below the ocean surface and cause any measurable change in ocean temperature.





Figure 16: a) Decadal mean temperature estimates derived from the HadCRUT4 global mean temperature series and b) decadal mean forcing with standard errors from the CMIP5 /RCP4.5 ensemble. Data from Otto et al [2013].



Using the data from Figure 16 and estimates of DQ 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 DT vs (DF-DQ) and DT vs FF 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 Figure 17. Using the data for 2000 to 2010, they give 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.





Figure 17: Estimates of ECS and TCR from Otto et al [2013]



The ECS for the CMIP5 model ‘ensemble’ is in the range from 2.1 to 4.7 C. For the AR6 IPCC report, the ECS range of the CMIP6 climate model ‘ensemble’ is given as 1.8 to 5.6 K. These climate sensitivities are shown in Figure 18. The correct value should be ‘too small to measure’. This is the pseudoscientific basis of the 1.5 or 2 C temperature limit incorporated into the Paris Climate Accord.





Figure 18: Pseudoscientific equilibrium climate sensitivity (ECS) for a doubling of the CO2 concentration from 280 to 560 ppm for selected CMIP5 and CMIP6 climate models [IPCC, 2013, Hausfather, 2019] .



The pseudoscientific radiative forcings published in the sixth IPCC climate assessment report are shown in Figure 19 and the changes in temperature over time ‘derived’ from these forcings are shown in Figure 20.





Figure 19: ‘Effective’ radiative forcings from IPCC AR6 WGp 1 Chapter 7.





Figure 20: Temperature changes from 1750 attributed to the ‘forcings’ shown in Figure 19 [IPCC, 2021].



The assumption that all of the observed temperature increase found in the global average climate record is caused by ‘radiative forcing’ provides the fraudulent foundation of the process of ‘attribution’ used to create the connection between CO2 and ‘extreme weather’. Since the real cause of the increase in global average temperature is the AMO, this may be called the ‘flat ocean assumption’. The variations in wind driven evaporation that drive the ocean oscillations have been ‘turned off’. This is illustrated in Figure 21 [Terando et al, 2020]. The contributions of the warming phases of the AMO, the recovery from the Little Ice Age (LIA) and the ‘adjustments’ to the raw weather station date to the ‘global mean temperature change’ are illustrated schematically in Figure 22.





Figure 21: The ‘flat ocean assumption’: the ‘climate sensitivity’ found in the climate models is based on the fraudulent assumption that the ‘global mean temperature change’ has been caused by radiative forcing. The dominant role of the AMO has been ignored. When the LWIR ‘forcings’ are turned off in the climate models, the real effect is that the ocean oscillations are suppressed [Terando et al, 2020].

(Note: Temperatures are in Fahrenheit not Celsius).





Figure 22: The contributions of the AMO warming cycles, recovery from the Little Ice Age (LIA) and raw weather station data ‘adjustments’ to the ‘mean average global temperature’ (schematic).



A8: Extreme Weather


One of the more egregious applications of the equilibrium climate models has been the ‘attribution’ of ‘extreme’ natural weather events to the effects of the increased CO2 levels in the atmosphere. At present, the annual average increase in the atmospheric concentration of CO2 is near 2.4 ppm per year. The corresponding annual increase in downward LWIR flux from the lower troposphere to the surface is 0.034 W m-2. This can have no effect on such ‘extreme’ weather events. One of the main errors has been the neglect of the heating affects produced by air compression. As dry air descents 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 produces 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. A good example of the effect of downslope winds on temperature was recorded at Havre, Montana, December 16 to 18, 1933. At this time the CO2 concentration was near 310 ppm. The thermograph trace is shown in Figure 23a. The temperature first rose by 27 F in five minutes and increased by a total of 53 F in less than 2 days. The temperature then cooled by 41 F in two hours.


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 dry out the vegetation very quickly and any ignition source will start the fire. In S. California, a high pressure system over the Great Basin produces an offshore flow that descends from the desert plateau. The winds may be increased by an adjacent low pressure region. This is illustrated in Figure 23b. Figure 23c shows a Terra Satellite image taken 12/5/17 showing the fires in S. California. The smoke is blown out to sea by the offshore winds. The Marshall fire in Boulder Colorado, December 30, 2021 that destroyed about 1000 houses was caused by strong downslope winds and an ignition source related to human activity. The fuel was dry grass and any residual moisture would have been removed very quickly by the dry 100 mph winds [Mass, 2022].





Figure 23: a) Thermograph trace of a downslope wind (Chinook) event, Havre Montana, December 1933 [Math, 1934], b) The formation of Santa Ana winds in S. California and c) Terra satellite image of the fires in S. California, taken 12/5/17.



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. None of this has any relationship to CO2. A high pressure dome formed over the Pacific Northwest in late June 2021. This produced record high temperatures as shown in Figure 24. As the high pressure system moved east, the temperature in Portland OR dropped from 116 to 64 F over the night of June 28 to 29. Once a ‘blocking’ high pressure system pattern is established, it can persist for weeks or even months. Since these systems also block rainfall and remove soil moisture, additional heating is produced by the reduced latent heat flux at the surface. For example, there was nothing unusual about the 2003 European heat wave [Black et al, 2004]. Brush fires produced by ‘blocking’ high pressure systems are a normal part of the Australian climate. Similarly, a high pressure system regularly forms over the area near Verkhoyansk, Siberia. This produces very high summer temperatures and very low winter temperatures [Autio, 2020 Watts, 2020].





Figure 24: Blocking high pressure system over the Pacific NW, late June 2021. As the high pressure system moved east, the temperature in Portland OR dropped by 29 C from 4 to 18 C overnight, June 18 to 29.



Figure 25a shows the total daily solar insolation (MJ m-2 day-1) and precipitation for Woomera, S. Australia for the 2 year period 2018 to 2019. Figure 25b shows the corresponding minimum and maximum weather station temperatures [BOM, 2020]. Figures 25c and 25d show the December temperatures for 2018 and 2019 on an enlarged scale. The minimum temperatures are determined by the weather systems passing through and the daily temperature change from minimum to maximum is determined by a combination of solar heating and air compression effects. The decreases in solar insolation are caused by clouds. Temperatures may change by 10 C or more over a period of 5 to 10 days because of the effects of blocking high pressure systems. Almost all of the absorbed solar heat is generally dissipated within the same diurnal cycle. The night time surface temperature is similar to the minimum MSAT temperature. The dotted lines in Figures 25c and 25d show the temperature rise produced by a ‘blocking’ high pressure system. The minimum and maximum temperatures increase each day as the air is warmed and recirculated by the high pressure system. The 2019 high pressure system was also associated with a record high Indian Ocean Dipole index. The ocean temperatures were lower near Australia and higher in the western Indian Ocean near the coast of Africa. This condition leads to drier conditions and higher temperatures over large parts of Australia. Figure 26 shows the 11 day temperature sets indicated in Figures 25c and 25d overlapped and plotted on an enlarged scale. The 2019 blocking high pressure system also remained over the area for 2 additional days compared to 2018 and this combination produced record high temperatures.





Figure 25: a) Solar insolation and precipitation and b) minimum and maximum temperatures for Woomera. S. Australia, 2018 and 2019, c) and d) December 2018 and 2019 temperatures on an enlarged scale.





Figure 26: Eleven day temperature data sets for the blocking high events shown in Figures 24c and 24d.



A9: Lorenz Instabilities


In 1963, Lorenz was evaluating a simple model of three coupled non-linear equations that described two dimensional convective flow. He discovered that the solutions to these equations were unstable and sensitive to small changes in the starting variables. This is illustrated in Figure 27. He later established that weather forecasting predictions were limited to approximately 12 days ahead before the model instabilities became dominant.





Figure 25: Instabilities in the solution of three coupled non-linear equations from Lorenz [1963]



The large scale climate models used today require the solution of an enormous number of coupled non-linear equations. There is no reason to expect such models to have any predictive capabilities. They are inherently unstable and have to be ‘tuned’ to give the desired results. In fact, they can be ‘tuned’ to give any desired result. All of the climate models shown in Figure 18 have been tuned based on the pseudoscience of radiative forcing to have an ‘equilibrium climate sensitivity’ or ECS that creates the global surface temperature anomaly. The fact that all of these models have a similar climate sensitivity to CO2 is clear evidence of the climate fraud. A realistic climate model should not show any ‘climate sensitivity’ to CO2.


The basic requirement of any climate model is that it should predict the measured variables of the climate system. This means the measured minimum weather station temperature and the delta T or change from minimum to maximum MSAT. Any weather station bias terms should be incorporated into the model. The measured data should not be changed. Since the dominant term in the climate record is the AMO, the climate models should be capable of predicting the ocean oscillations and global ocean temperatures derived from these oscillations. Figure 28 shows global ocean temperatures from 1979 to 2021 and 68 model ‘predictions’ from 26 different CMIP6 models. The models have clearly failed. The ‘predicted’ ocean surface temperatures are too large. This is to be expected, based on consideration of Lorenz instabilities and model ‘tuning’. Such models may perhaps best be described as quasi-stable pseudo-random number generators, all tuned to the same temperature series. The pseudo-random number generators used in Monte Carlo calculations give exactly the same random number sequence for each model run until the seeds used in the generator are changed. Here, the models are unstable because of the underlying Lorenz instabilities related to rounding errors and other modeling effects. Two model runs for exactly the same model conditions run on the same computer will give different results. The spread between the maximum and minimum model results increases from approximately 0.6 C to 1.6 C over time span of the model runs. This is characteristic of Lorenz instabilities.





Figure 28: Global sea surface temperatures (60° N to 60°S), 1979 to 2021, CMIP6 models compared to ERSSTv5 observations (thick black line) [Spencer, 2021]



A10: The Climate Model Fantasy Land


The 1967 paper by Manabe and Wetherald (M&W) described the first generally accepted radiative-convective equilibrium climate model and provided the foundation for later [fraudulent] equilibrium climate model development. As soon as the equilibrium assumption is made, physical reality is abandoned and the climate models no longer describe planet earth. The M&W model was just a mathematical platform for the development and evaluation of radiative transfer and related algorithms. This is illustrated in Figure 29. The model consisted of a static column of air divided into 9 or 18 layers. This was illuminated by a ‘24 hour average’ sun with a fixed intensity. The surface at the bottom of the model was a partially reflective blackbody surface with zero heat capacity. The absorbed solar flux was re-radiated as heat. The various air layers contained water, carbon dioxide and ozone modeled using the spectroscopic constants that were available at the time. The relative humidity of each layer was fixed so that the water vapor concentration changed with the layer temperature. The model was run iteratively until the layer temperatures stabilized and the LWIR flux emitted by the top layer matched the absorbed solar flux. In terms of model time (number of steps times the step time) the model took over a year to reach equilibrium. The computational time was much less. When the CO2 concentration was increased, the LWIR flux emitted by the top layer was reduced and the surface and layer temperatures were increased until the LWIR flux emitted by the top layer again matched the absorbed solar flux. This created global warming by definition as a result of model input assumptions. Furthermore, since the relative humidity was fixed, there was an additional amplification or ‘feedback’ caused by the increase in water vapor concentration as the temperature increased. Again, this is a mathematical artifact of the model assumptions.





Figure 29: The 9 or 18 layer M&W model. Three separate model runs to steady state were required to generate the three temperature distributions with different CO2 concentrations [M&W, 1967].



M&W spent the next 8 years building their 1967 algorithms into a simplified global circulation model (GCM) with several thousand ‘unit cells’ [M&W, 1975]. The model had many simplifications including a ‘swamp’ ocean, no surface thermal storage, no ocean transport and fixed cloudiness. Each cell created the same type of global warming mathematical artifact as the original 1967 ‘platform’. The GCM was first run to an ‘equilibrium state’ over a period of 800 days from an ‘isothermal’ start. The model was then rerun with a ‘doubled’ CO2 concentration from 300 to 600 ppm. The computer runs were repeated using a different start temperature and the results for the last 100 days were compared. The results are shown in Figure 30. The temperatures plotted are the zonal mean temperatures from the lowest air layer in the model. The model showed a similar average response to the 1967 model. The temperature increases were 2.36 K and 2.93 K for the 1967 and 1975 models. A doubling of the CO2 concentration had to produce a warming, by definition, because of the way the model was constructed. This model of course has no relationship to planet earth.





Figure 30: Results from the M&W 1975 GCM showing the mathematical artifacts from a doubling of the CO2 concentration.



The prescribed mathematical ritual of ‘radiative forcing’ was introduced by Hansen et al in 1981. This was based on the perturbation of an equilibrium climate state by a ‘doubling’ of the CO2 concentration followed by the transition to a new equilibrium state with a higher surface temperature. Small changes in equilibrium LWIR flux were assumed to be capable of changing the surface temperature including the oceans. The changes in ‘equilibrium flux’ are shown in Figure 31. No thermal engineering calculations of the change in surface temperature were performed to validate the model. No one bothered to ask how such small changes in LWIR flux would be dissipated in a real climate system.





Figure 31: Discussion of the effects of a hypothetical ‘CO2 doubling’ from 300 to 600 ppm on an equilibrium average climate from Hansen et al, 1981.



By now, a range of ‘forcing agents’ had been added to the CO2 and O3 used by M&W. Additional ‘greenhouse gases’ included N2O, CH4 and halogenated hydrocarbons. Various aerosols were added that could be used as ‘tuning knobs’ to adjust the model output. All of this was part of a growing equilibrium average climate fantasy land. The changes in temperature produced by changes in such ‘forcing agents’ are shown in Figure 32. The only change to the concept of radiative forcing was the addition of ‘efficacies’ in 2005.





Figure 32: Effects of various ‘forcing agents’ on surface temperature calculated using an equilibrium average climate model artificially constrained by an exact flux balance at TOA [Hansen. 1981].



The CO2 doubling discussed by Hansen et al in 1981 has grown into a prescribed modeling ritual in which an ‘equilibrium climate state’ is perturbed by a step ‘doubling’ of the CO2 concentration. The various parts of the model are adjusted sequentially until a new equilibrium state is reached with a higher surface temperature. This is illustrated in Figure 33. In the real climate, there is no equilibrium and no CO2 doubling. This is accounted for using a ‘transient climate response’ in which the all of the increase in temperature in the global ‘temperature anomaly’ is produced by a combination of magical forcings such as that shown in Figure 16b. The coupling to the convection in the troposphere and the wind driven evaporation at the ocean surface are ignored.





Figure 33: The radiative forcing ritual used to determine the change in surface temperature from a ‘radiative forcing’ at TOA or the tropopause

[IPCC, 2013, Chapter 8].



The climate modelers are trapped in a web of lies of their own making.







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