Ventura Photonics
Non Imaging Optics
Greenhouse Effect
Understanding Climate Change
Find Out More - Read the Book:
The Dynamic Greenhouse Effect and Climate Averaging Paradox  
For more information click
here.
Climate Model Fail: A Root Cause Analysis

Roy Clark PhD
At the time of the release of the 5 th Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (UN
IPCC) in September 2013, the Earth had already stopped warming for approximately 15 years.  The computer models used to simulate
climate change however, continued to predict climate warming in excess of any reasonable bounds of error.  The models must be
rejected as fraudulent.  However, the modelers have not yet learned their lesson.  They will continue to push out the time line of the
global warming apocalypse until they are shown errors of their ways.  In engineering terms we have to show the root cause of the
failure.  To do this we must start by going back and examining the history of the models.

The climate models had to fail, because they were incorrectly constructed from the outset.  The seeds of the failure were sown when
the first computerized climate models were developed back in the 1960s.  The Earth’s climate is complex, and the climate models have
to make various simplifying assumptions in order to simulate any kind of climate change.  The first models made some drastic
simplifying assumptions that appeared reasonable at the time.   The computer capabilities were very limited and relatively little climate
data was available.  An ‘average climate’ was created.  An exact flux balance was assumed between a 24 hour average incoming solar
flux and a similarly averaged outgoing long wave IR (LWIR) flux.  A black body surface with zero heat capacity was used to create an
‘equilibrium average surface temperature’.  The surface temperature can be related to the flux terms using a simple set of flux
equations.  The ‘equilibrium average climate’ can be altered by adding, for example, an increase in the CO
2 concentration to the
atmosphere.  A mathematical approach known as perturbation theory is then used to calculate the transition to a new ‘equilibrium
state’ and a new black body ‘surface equilibrium temperature’.  This approach is now known as ‘radiative forcing’

The mathematics of the flux equations follow logically from the radiative forcing assumptions.  The perturbation theory works just fine.  
From a mathematical perspective, the flux equations are even quite elegant.  We can build more elaborate computer models and
develop new algorithms to simulate the atmospheric energy transfer.  This was the original intent.  We remain honest if we admit the
assumptions and understand that the flux interacts with the surface.  We are calculating a change in average equilibrium surface
temperature for an assumed equilibrium atmosphere.  We are simply not dealing with Planet Earth.  As soon as we make the radiative
forcing assumptions we leave physical reality behind and enter a parallel universe of computational climate fiction.  In reality, there is
no climate equilibrium and no black body surface.  Furthermore, the LWIR emission to space is decoupled from the surface flux by
convection and radiative transfer linewidth effects.

In order to understand how the Earth’s climate really works, we must use the time dependent surface flux balance to calculate the
surface temperature.  The sun only heats the surface during the day and the solar flux varies continuously on a daily and seasonal
time scale.  There are four cooling terms.  There is a net LWIR flux emitted from the surface.  There is a dry air convection term or
sensible heat flux and a water evaporation term or latent heat flux.  There is also a subsurface thermal transport term.  Over land, the
heat is conducted locally below the surface and released later.  Over the oceans, the solar flux can penetrate to depths of up to 100 m
and the heat can be stored and transported over long distance by ocean currents.  In order for the solar heat to be dissipated back
into the atmosphere, there has to be a thermal gradient at the surface. This follows from the Second Law of Thermodynamics.  In
addition, the surface flux interacts with a real surface material layer that has well defined thermal properties.  In particular, the flux that
accumulates in the surface layer has to be divided by the heat capacity to calculate the temperature change.  When the real numbers
are used, the small increase in downward LWIR flux from any increase in ‘greenhouse gas concentration’ is too small to have any
measurable effect on the surface temperature.  

When the climate modelers made the original radiative forcing assumptions, they lost the Second Law of Thermodynamics.  Radiative
forcing cannot predict climate change.  The early modelers knew that their models were too inaccurate to attempt any kind of
prediction.  However, they continued to use the radiative forcing approach to improve the modeling algorithms.  

Now, before satellite observations, there were almost no surface temperature measurements.  The only long term temperature record
is the weather station record, which goes back with decreasing reliability to the late nineteenth century.  It must be emphasized that
this is not the surface temperature, but the meteorological surface air temperature (MSAT).  This is the temperature of the air
measured in an enclosure placed at eye level 1.5 to 2 m above the ground.  The minimum MSAT, usually recorded near sunrise, is an
approximate measure of the bulk air temperature at the base of the weather system as it is passing through.  The maximum MSAT is
generally recorded in the afternoon.  It is a measure of the turbulent mixing of the warm air rising from the surface with the cooler air
above at the level of the MSAT enclosure.  In many regions, the weather systems are formed over the oceans and the long term trend
in the minimum MSAT is a measure of the trend in ocean surface temperature in the region of the weather system formation.  For
example, in the continental US, the long term climate trend can be reconstructed reasonably well using a weighted average of the
Pacific Decadal Oscillation (PDO) and the Atlantic Multi-Decadal Oscillation (AMO).  

Starting in the mid 1980’s, an increase in temperature in the weather station climate record was detected.  This was immediately
correlated with the observed increase in atmospheric CO
2 concentration and the global warming scare was created.  In spite of their
many shortcomings, the climate models do a reasonably good job of calculating the increase in the LWIR flux in the atmosphere
produced by the increase in ‘greenhouse gas’ concentration.  This is what they were initially designed for.  To make the models give
the desired ‘surface temperature’, an empirical ‘climate sensitivity constant’ was created.  The observed increase of 100 ppm in
atmospheric CO
2 concentration produced an increase in downward LWIR flux at the surface of approximately 1.5 W m^-2.  This is a
reliable number that can be independently verified using radiative transfer calculations and the HITRAN spectroscopic database.  It
was decreed that the 1.5 W m^-2 increase in surface flux had produced a 1 C rise in surface temperature.  This is about three times
larger than it should be.  No problem, water vapor ‘feedback’ was added.  The increase in warming from CO
2 was now magically
amplified by water vapor.  This gave a climate sensitivity constant of 2/3 C per 1 W m^-2 increase in the downward LWIR flux at the
surface.  This approach worked for any ‘greenhouse gas.’  All you had to do was calculate the increase in downward LWIR flux and out
came the global warming temperature.  This is all empirical pseudoscience.  The models were really just ‘calibrated’ using ocean
surface temperature changes.  In fact, the calibration was too good.  The models overestimated the warming.  This was fixed for a
while with ‘aerosols’.  These reduced sunlight and cooled the surface.  Various flavors of aerosols were added to the mix.  Climate
‘prediction’ involves fiddling with the greenhouse gas concentrations and juggling the aerosols then ‘guiding’ the model to get the
desired result.  The models are inherently unstable and two identical model runs will give different answers because of computer
‘rounding’ etc.  This is climate theology, not climate science.  

The oceans cooperated for some time and the whole global warming gravy train really got rolling.  Everyone was paid to study a non-
existent problem.  Then finally, the oceans stopped warming and for AR5 the models failed.  Fifteen years is long enough to wait.  Now
we have to return to reality.  There is no climate equilibrium.  The solar flux is always changing.  The earth’s climate system has to be
described in terms of a series of coupled thermal reservoirs with rate limited heat transfer between them.  There is nothing new in this
concept.  Fourier understood the basics 200 years ago.  There is however, one catch.  We have to do our homework on the
atmospheric radiative transfer.  This shows that the troposphere splits into two thermal reservoirs.  Almost all of the downward LWIR
flux the reaches the surface comes from the lower tropospheric reservoir, which extends up to 2 km above the surface.  All of the LWIR
emission to space comes from the upper tropospheric reservoir, which extends upwards from 2 km to the tropopause.  

We now get a simple picture of how the earth’s climate really works.  It is an open cycle heat engine.  There are 2 hot reservoirs, the
land and the oceans which have to be treated separately.  The cold reservoir is the troposphere above 2 km.  The sun heats the hot
reservoirs during the day.  Some of the LWIR flux from the surface escapes directly to space through the atmospheric transmission
window (or is absorbed by clouds).  All of the heat that is coupled to the troposphere ends up directly or indirectly as convection.  
Moist air is the working fluid of the heat engine.  During the day, convection heats the troposphere.  As the air rises, it cools by
expansion and this sets the lapse rate or atmospheric temperature profile.  The upper tropospheric reservoir is heated slightly and the
temperature may rise by approximately 1 C during the late afternoon.  This reservoir is continuously cooled by LWIR emission to
space.  It cools until it is warmed again by convection the following day.  During the summer, more heat is stored in the reservoir and
the height of the tropopause rises.  In winter, this heat is lost and the height of the tropopause decreases.  The lower tropospheric
reservoir is heated by convection during the day.  However, at night it cools more slowly by LWIR emission.  The lower tropospheric
reservoir now acts as a ‘thermal blanket’ that slows the surface cooling.  

The dominant cooling process in the troposphere is LWIR emission from the water bands, usually at an altitude near 5 km.  At an
average lapse rate of -6.5 K km-1, the air cools by approximately 33 K as it rises to an altitude of 5 km.  This is the real source of the
so called ‘greenhouse effect’ temperature.  It has nothing to do with ‘infra red absorption’ keeping the surface warm.  It is just a
measure of the internal work performed by the expansion of the air as it rises and expands to 5 km in the atmospheric heat engine.  
The climate system has to be described in terms of dynamic thermal storage, not equilibrium flux.  

The fundamental root cause of the climate model failure is that the flux equilibrium assumption removes the Second Law of
Thermodynamics from the surface energy transfer.  

The basic radiative forcing approach therefore does not apply to the earth’s climate.  The use of the weather station record for
‘calibration’ is just empirical pseudoscience.  There can be no CO
2 ‘warming signature’ in the weather station record.   The observed
warming trend is a combination of ocean surface temperatures, weather station bias (urban heat island effects) and some downright
weather station data ‘fiddling’ disguised as ‘homogenization’.  The weather station data is processed or homogenized into a 5° x 5°
grid.  This process has been used to add warming to the raw data.  
SUMMARY
CLIMATE MODEL FAIL: A ROOT CAUSE ANALYSIS

DETAILED DISCUSSION
TABLE OF CONTENTS

Summary
1.0 An Overview of the Greenhouse Effect and the Earth’s Climate
1.1 The ‘Equilibrium Climate’ and the ‘Greenhouse Effect’
1.2 The Dynamic Description of the ‘Greenhouse Effect’
1.3: The Earth’s Climate: Overview
1.4 Climate Energy Transfer
1.5 Asking the Right Quantitative Questions
2.0 The Climate Record
2.1 Surface Temperature
2.2.1 The Temperature Record for the Continental US
2.2.2 Urban Heat Islands: Los Angeles
2.2.3 Air Temperatures in the Lower Troposphere
2.2.4 Land Surface Temperatures from Meteostat Satellite Data
2.3 Sea Level Rise
2.4 Polar Ice Extent
2.5 Glacier Retreat
2.6 US Rainfall
2.7 Hurricanes and Tornadoes
2.8 Extreme Weather Events
2.9 Longer Term Climate Variations: The Effect of Changes in the Solar Flux
3.0 Climate Energy Transfer and Surface Temperature
3.1 The Surface Flux Balance Equations
3.2 The Land-Air Interface
3.3 The Ocean-Air Interface
3.3.1 Energy Transfer in the Pacific Ocean Warm Pool
3.3.2 Global Changes in Ocean Evaporation and Surface Temperature
3.3.3 Climate Change, Ocean Circulation and Plate Tectonics
3.3.4 Solar Activity and Ocean Heating
3.4 The Lower and Upper Tropospheric Reservoirs
4.0 Climate Modeling and Climate Fraud
4.1 Climate Simulation
4.1.1 Model Validation
4.2 Climate Fraud
5.0 Conclusions
6.0 Points for Further Discussion
Acknowledgement
References
At the time of the release of the 5 th Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (UN
IPCC) in September 2013, the Earth had already stopped warming for approximately 15 years.  The computer models used to simulate
climate change however, continued to predict climate warming in excess of any reasonable bounds of error.  The models must be
rejected as fraudulent.  This is shown in Figure 1.  
Figure 1: The 15 year pause in ‘global warming’.  The black points are the observational data.  The colored
bands within the gray area are the model predictions.  (Fig 1.4 from the AR5 draft, Dec. 2012)
When the climate energy transfer processes involved are quantitatively analyzed, it becomes abundantly clear that carbon dioxide
induced global warming has no basis in physical reality.  The models are based on empirical pseudoscience.  The primary reason for
the model divergence is that the accepted description of climate change uses an overly simplistic ‘atmospheric equilibrium’ description
of climate energy transfer known as radiative forcing.  This assumes a non-existent ‘average equilibrium flux’ in which an average
incident solar flux is required to match an average long wave IR (LWIR) flux leaving the Earth’s atmosphere.  The equilibrium
assumption is based on a misunderstanding of the First Law of Thermodynamics and a blatant disregard of the Second.  In reality, the
Earth’s surface temperature is not controlled by the LWIR flux.  The Earth’s climate is determined mainly by the dynamic energy
balance between ocean solar heating and wind driven evaporative ocean surface cooling.  All of the surface thermal energy that is
LWIR transmission window, or is absorbed by clouds.  Convection involves mass transport through a gravitational potential.  The sun
illuminates the surface and drives the convection during the day.  At night, the lower troposphere acts as a ‘thermal blanket’ that slows
the surface cooling.  The troposphere acts as an open cycle heat engine and the temperature profile is set by the lapse rate, not the
radiative transfer or ‘greenhouse gas absorption’.  A significant fraction of the atmospheric LWIR flux emitted back to space originates
from the water bands at an altitude centered near 5 km.  The so called ‘greenhouse effect temperature’ of 33 K is just a measure of the
work required for the convection to overcome the gravitational potential and ascend to an altitude of approximately 5 km.  For an
average lapse rate of -6.5 km K^-1 this gives 5 x -6.5 = -32.5 K.  It has nothing to do with ‘greenhouse gas absorption’.  

The small increase in downward atmospheric LWIR surface flux from the increase in ‘greenhouse gas concentration’ has to be added
to the short term surface flux balance and used to calculate the surface temperature before any long term averaging is performed.  
When the surface temperature is calculated over short time intervals using the correct physics of the surface heat transfer, this small
increase in flux has no measurable effect on the surface temperature.  There can be no CO
2 induced global warming.  Furthermore,
the observed increase in CO
2 concentration has had no detectable influence on the Earth’s weather patterns.  There are no ‘extreme
weather events’ that have been caused by CO
2.

The observed climate changes attributed to CO
2 may be explained in terms of variations in ocean surface temperatures, weather
station bias effects, particularly urban heat island effects and some downright fraudulent manipulation of the climate record disguised
as ‘data adjustment and homogenization’.  There can be no CO
2 ‘signature’ in the weather station climate record.

An overview of the ‘greenhouse effect’ and the Earth’s climate are given in Section 1.  The climate record, including temperature, sea
level, polar ice, glaciers, hurricanes and tornadoes and ‘extreme’ weather events are reviewed in Section 2.  The physics of the surface
energy transfer is described in Section 3.  Climate modeling and some of the fraudulent activity related to climate science are
considered in Section 4.  Conclusions are presented in Section 5 and some points for further discussion are given in Section 6.  These
should provide the framework for an honest and open discussion of the global warming fraud.  

Further details on climate change may be found in the NIPCC Report Climate Change Reconsidered II: Physical Science (CCR-II)
[
NIPCC, 2013] and the Energy and Environment Special Issue Mechanisms of Climate Change and the AGW Concept: a critical review
[
Rörsch & Ziegler, 2013].  
1.0 AN OVERVIEW OF THE GREENHOUSE EFFECT AND THE EARTH’S CLIMATE

1.1 The ‘Equilibrium Climate’ and the ‘Greenhouse Effect’  

The conventional description of the so called ‘greenhouse effect’ is based on an overly simplistic description of climate energy transfer
derived from the rather old concept of an ‘infrared planetary atmosphere’.  It is assumed that some kind of ‘average climate equilibrium
state’ exists.  This requires an exact flux balance between the incoming ‘average’ solar flux and the outgoing ‘average’ long wave IR
(LWIR) flux.  The solar flux that reaches the surface is approximately 240 W m^-2 averaged over a 24 hour period.  This corresponds
to a blackbody emission temperature of 255 K (-18C).  The average temperature of the Earth’s surface is assumed to be 288 K (15
C).  In the original climate equilibrium models, this surface was assumed to be a ‘blackbody surface’ with ‘zero heat capacity’.  The
difference between these two ‘equilibrium’ temperatures is 33 K.  This is called the greenhouse effect temperature and it is assumed to
be caused by ‘atmospheric infrared absorption’.  If the atmospheric CO
2 concentration is increased, it is assumed that more LWIR
absorption increases the surface temperature.  This is analyzed using an approach known as radiative forcing.  Perturbation theory is
applied to a set of equilibrium flux equations to determine the increase in ‘equilibrium surface temperature’ when the atmospheric
‘greenhouse gas’ concentrations are changed [Alley et al., 2007; Taylor, 2006; Ramanathan and Coakley, 1978; Manabe and
Wetherald, 1967].  

Over the last 200 years the atmospheric concentration of CO
2 has increased by a little more than 100 ppm [Keeling et al, 2013,
2005].  This has produced an increase in the downward atmospheric LWIR flux at the surface of approximately 1.5 W m^-2 [Hansen et
al, 2005].  The flux increase can be calculated quite reliably using atmospheric radiative transfer theory with the HITRAN database
[Clark, 2010a; Rothman et al, 2004].  Using Stefan’s Law, 1.5 W m^-2 can only increase the equilibrium black body surface
temperature by 0.3 K to 288.3 K.  However, this did not stop the belief that climate change must be caused by CO
2.  The Earth had to
be saved from a nonexistent problem.  Using an average trend from the weather station climate record, it was empirically determined
that there was an increase of 1 K in the climate data that had to be caused by the increase of 100 ppm in the atmospheric
concentration of CO
2.  The extra 0.7 K was explained as ‘water vapor feedback’ and the flux equations were adjusted accordingly.  
Unrelated graphs of climate temperature and atmospheric CO
2 concentrations were overlapped and carefully scaled to produce the so
called hockey stick plot [Montford, 2010].  Correlation is not proof, but this was ignored.  In reality, the weather station climate record is
dominated by ocean surface temperatures as discussed below in Section 2.1.  There can be no CO
2 ‘signature’ in the weather station
record.  

An empirical ‘climate sensitivity’ or calibration constant was then created from the assumed CO
2 induced warming.  It was decreed that
an increase in downward atmospheric LWIR flux of 1 W m^-2 at the surface from any IR active ‘greenhouse gas’ produced a surface
warming of 1/1.5 = 2/3 C [Hansen et al, 2005].  The increase in surface temperature from increasing atmospheric concentrations of
other ‘greenhouse gases’ such as methane and ozone can then be ‘calculated’ using this ‘climate sensitivity constant’.  However, once
the empirical ‘climate sensitivity constant’ and the gas concentrations are set, so is the estimate of ‘greenhouse gas warming’ from all
‘greenhouse gases’.  This all comes from HITRAN or related spectroscopic calculations.  However, the climate record did not
cooperate and provided less warming than expected.  Aerosol cooling was now added to the mix.  Sulfate aerosols were added to
provide surface cooling and volcanic aerosols were used for variable fine tuning.  ‘Black carbon’ was also added to the mix for further
adjustment.  As computer capabilities increased, more complex models were developed.  However, these models were evaluated, not
by comparison to measured climate data, but against each other using the ‘climate sensitivity constant’ as the benchmark [Meehl et al,
2007].  The computer runs were even called ‘experiments’.  The comparisons were made by ‘predicting’ the effect of a doubling of the
atmospheric CO
2 concentration on the surface temperature.  

All of this is pure pseudoscience.  As soon as the atmospheric equilibrium assumption is invoked, the models and modelers leave
physical reality behind and enter the universe of computerized climate fiction.  We are no longer dealing with climate science but
climate theology.  ‘How does a doubling of the atmospheric CO
2 concentration change the number of photonics angels that may reside
on the head of a climate pin?’  The modern form of the radiative forcing models was introduced in 1967 by Manabe and Wetherald.  
They were quite honest and stated all of their assumptions quite clearly on the second page of their paper.  The problem came later,
in about 1985, when the climate record was substituted for the surface temperature [Jones et al., 1999].  The weather station
temperature is not the surface temperature, but the meteorological surface air temperature (MSAT) measure in an enclosure placed at
eye level, 1.5 to 2 m above the ground [Oke, 2006].  There is no simple or obvious relationship between the MSAT and the surface
temperature.  In fact, the calculated ‘equilibrium surface temperature’ is not even a measurable climate variable.  This is conveniently
ignored in the climate simulation models.  Radiative forcing is a failed simplification algorithm that should have been abandoned nearly
30 years ago.  Unfortunately, the creation of the global warming problem opened up a huge flood of money and the radiative forcing
hypothesis has become the dogma that it is today.  It has left scientific reason behind and degenerated into a quasi religious cult.  We
now have an environmental Ponzi scheme based on global warming that has consumed trillions of dollars.  Current policies involving
global warming and alternative energy are founded on nothing more than the mathematical manipulation of a physically meaningless
set of equilibrium flux equations.  

1.2 The Dynamic Description of the ‘Greenhouse Effect’

The so called ‘greenhouse effect’ may be explained quite simply using the basic Laws of Physics and the time dependence of the solar
flux.  The First Law of Thermodynamics still requires that energy be conserved.  Furthermore, the observed long term climate stability
requires that the Earth maintain a relatively close balance between the incoming solar flux and the outgoing LWIR flux.  However, it
does so with the help of the Second Law of Thermodynamics and the heat capacity of the atmosphere, the land and especially the
oceans.  The Earth’s climate is stable because of the heat stored, transported and released by these thermal reservoirs.  The heat
transfer must follow the thermal gradient and since the solar flux changes continuously on a daily and seasonal time frame, the surface
temperature gradient also varies in a similar fashion.  Climate stability comes from rate limited heat transfer between the thermal
reservoirs.  It is governed by the Second Law of Thermodynamics [Clark, 2013a, 2013b, 2011a].  

During the day, the sun heats the surface and establishes a thermal gradient or temperature difference between the surface and the
air above.  However, all of the heat that is coupled from the surface to the troposphere is transferred either directly or indirectly by
(moist) convection.  As the warm air rises, it cools and water condenses.  The rising air has to do work to overcome the gravitational
potential of the Earth.  The troposphere is an open cycle heat engine.  The temperature profile or lapse rate of the troposphere is set
by convection not by LWIR radiation.  LWIR radiative transfer still occurs, but the LWIR absorption-emission temperature is set by the
lapse rate.  The tail does not wag the dog.  During the day, the rate of heat transfer by convection is usually much larger than that
from radiative transfer.

Convection is a complex transport and mixing process [Gilbert, 2010].  An air parcel continues to rise and expand until it matches the
buoyancy of the air surrounding it [Tsonis, 2007].  It then continues to cool by net LWIR radiation to space.  This is a much slower
cooling process than the convective ascent.  The LWIR cooling rate is set by the local temperature, pressure and the species
concentration.  This determines the absorption profile or linewidth of the individual molecular absorption-emission lines.  As the altitude
increases, the linewidth narrows and there is a gradual transition from the radiative transfer process of LWIR absorption and emission
to a free photon flux.  A major change occurs in the middle troposphere.  Here, over a range of altitudes near 5 km and temperatures
near 255 K the water vapor re-absorption decreases significantly because of condensation.  The individual water lines become
narrower and some of LWIR flux in the narrow spectral regions between the lines is not reabsorbed and continues on unimpeded to
space [Clark, 2011a, 2010a].  5 km is therefore the approximate altitude of the cold reservoir of the tropospheric heat engine.  The
average atmospheric lapse rate is near -6.5 K km^-1.  The air has to rise and cool by 5 x -6.5 = 32.5 K to reach the troposheric cold
reservoir.  This is the origin of the so called ‘greenhouse gas temperature’ [Jelbring, 2003].  

The troposphere divides naturally into two essentially decoupled thermal reservoirs [Clark, 2013a, 2013b, 2011a].  The lower reservoir
extends from the surface to approximately 2 km and the upper reservoir extends from 2 km to the tropopause.  Almost all of the
downward atmospheric LWIR flux that reaches the surface originates from within the first 2 km layer.  This again follows from molecular
linewidth considerations.  At night, the surface air and the land surface cool to a similar temperature.  Convection stops and the lower
troposphere acts as a ‘thermal blanket’ that slows the surface cooling.  At night surface cooling is limited to LWIR emission through the
atmospheric LWIR window.  Above 2 km, the troposphere cools continuously to space by LWIR emission. It is heated during the day by
convection.  The heat capacity of a column of air in the lower troposphere with dimensions 1 m^2 x 2 km is approximately 2 MJ K^-1.  
Typical night time cooling rates at the surface are approximately 50 W m^-2.  This gives a fully mixed cooling rate of ~0.1 K per hour
for the lower tropospheric reservoir.  

The radiative transfer absorption-emission process for CO
2 continues to a higher altitude above the main H2O emission band.  This
means that a satellite sensor looking down from space will detect a colder emission temperature from the CO
2 band than from the H2O
bands.  If the CO
2 concentration is increased, the absorption emission process is extended to a higher altitude, and the CO2 emission
band observed from space will appear colder.  This all follows from the radiative transfer process.  However, the observed cooling with
increased concentration in the upper troposphere has no connection to the surface temperature.  The radiative forcing flux equations
do not take into account the linewidth effects.  The upward and downward LWIR fluxes are not equivalent because of line narrowing
[Clark, 2013a, 2013b, 2011a, 2010a].  The downward flux at line center is reabsorbed by the molecules below.  The upward flux in the
wings of the lines below can escape to space between the narrower lines above (See Figure 55 b below). This is one way that nature
enforces the Second Law of Thermodynamics.  This also invalidates the radiative forcing equilibrium argument.  
The time interval is typically 0.5 to 2 hours, based on short term meteorological station data averages.  Long term climate change is
determined by the overall trend in the short term data.  When the 1.5 W m^-2 from CO
2 is added to Eqn. 2, it is too small to have any
measurable effect on surface temperature [Clark, 2013a, 2013b, 2011a].  This flux balance approach is common engineering
practice.  It is used for example in the evaluation of solar heating effects in overhead electrical power lines [IEEE 1993].

It also leads to the description of climate change in terms of the time dependent heat transfer between coupled thermal reservoirs.  
The oceans, the land surface and the upper and lower troposphere act as thermal reservoirs that ‘integrate’ the time dependent
energy transfer flux.  The interaction lengths and time delays from thermal storage effects must all be accounted for.  For example,
the penetration depth of the LWIR flux from the CO
2 bands into the surface is less than 100 micron (10^-4 m).  This means that only
the sun can heat the oceans.  The LWIR flux is blocked at the surface and can only couple to the surface skin layer and the wind
driven surface evaporation [Clark, 2013a, 2013b, 2011a].   

These energy transfer processes are considered in more detail in Section 3.0.  

1.3: The Earth’s Climate: Overview

Climate science is essentially a passive observational science involving the study of long term changes in the Earth’s weather
patterns.  Since these weather patterns are complex, the primary function of climate modeling is to explain climate observations.  
Climate simulation has not yet reached a level of maturity where valid predictions can be made.  The Earth is heated by the short
wave radiation (SWR) from the sun and cools by the emission of long wave infrared (LWIR) radiation back to space.  However, the
surface heat is coupled back into the troposphere by convection.  The thermal transfer to convection occurs through a combination
of direct surface heating, water condensation and LWIR absorption.  Some of the LWIR flux from the surface escapes directly back to
space through the atmospheric LWIR transmission window, but the rest is absorbed by the atmosphere and any heat produced is
converted to convection.  There can be no ‘radiative equilibrium surface temperature’.  The tropospheric temperature profile or lapse
rate is set by convection, not by the LWIR flux.  The surface is also cooled by evaporation, especially over the oceans.  As the warm,
moist air rises through the atmosphere water condenses and releases latent heat of evaporation.  This further heats the atmosphere
and adds to the convection.  It also reduces the magnitude of the lapse rate.  The dominant cooling process for the oceans is wind
driven evaporation.  This cools the ocean surface and the water produced in the cooler surface or ‘skin’ layer sinks and cools the
ocean below.  

Convection, both of the warm air upwards through the troposphere and the cool water down into the oceans is a mass transport
process.  Mass is attracted by gravitational forces, so the interactions of the convection with Earth’s gravitational field and those of
the moon and sun are an integral part of climate studies.  The gravitational fields from the sun and the moon produce the tides that
are observed both in the oceans and the atmosphere [Wilson & Sidorenkov, 2013].  In addition, the Earth rotates on its axis and the
coupling of this rotation or angular momentum produces the Earth’s basic weather patterns.  Approximately half of the heat from the
sun is incident within the ±30° latitude bands.  This establishes the Hadley cell circulation and the trade winds.  Convection at higher
latitudes produces the Ferrell and Polar cell circulations.  Within the Ferrell cell, the Earth’s rotation produces a torque or Coriolis
force that establishes the characteristic cyclone/anticyclone weather patterns.  The trade winds drive the ocean currents that
produce the large scale ocean gyres.  These patterns are changed by complex and subtle interactions between the ocean, the
atmosphere, the gravitational field and the rotation.  The principal interactions are the ocean oscillations, the El Nino Southern
Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the Atlantic Multi-decadal Oscillation (AMO).  The ENSO has an
oscillation period between 3 and 7 years.  The AMO and PDO have periods near 60 years, although the timing may vary.  All have a
major impact on the Earth’s weather systems.  These oscillations are the primary source of the observed warming attributed to CO
2
[Akasofu, 2010, Cheetham, 2013a].

Figures 2 through 6 illustrate the principal features of the Earth’s climate.  Figure 2 shows the basic convection cell structure and the
trade winds.  Figure 3 shows the basic ocean gyre structure that is driven by the trade winds.  Some of the warm water flowing from
the N. Atlantic and N. Pacific gyres, the Gulf Stream and the Kuroshio Currents, is not re-circulated and continues to the Arctic.  The
interaction of these currents with the Arctic weather systems plays a major role in the annual Arctic polar ice freeze-thaw cycle.  The
ocean gyres in the S. Hemisphere all interact with the Southern Ocean, which isolates the Antarctic from direct contact with the warm
gyre currents.  The S. Atlantic gyre divides off the coast of Brazil and part feeds warm water towards the Caribbean.  The
approximate locations of the AMO, ENSO and PDO oscillation regions are also indicated.  Figure 4 shows the 50 year average of the
latitude zone dependence of the ocean surface and air temperature, wind speed, latent hear flux, sensible heat flux and absolute
humidity [Yu et al, 2008].  Figure 5 shows a map of the 50 year averages of the ocean surface temperatures and Figure 6 shows a
map of the 50 year average evaporation rates [Yu, 2012, Yu et al, 2008].  The gyre driven warm pools can be clearly seen as dark
red in Figure 5.  It is important to note that the evaporation rates in Figure 6 are determined by a combination of the surface
temperature and the wind speed.  The peak surface temperatures and the peak evaporation rates do not coincide.  It must also be
emphasized that these are long term averages and that there are significant fluctuations on daily, seasonal and longer term, 3 to 7
and 60 year, time scales.  
Figure 2: The Earth’s convective circulation cell structure and the trade winds (schematic).
Figure 3: The Earth’s ocean gyre structure (schematic).  The approximate location of the main ocean
oscillations are also given.
b) Air Temperature (C)
a) Surface Temperature (C)
c) Wind Speed (m s^-1)
d) Latent Heat Flux (W m^-2)
f) Absolute Humidity (g kg^-1)
e) Sensible Heat Flux (W m^-2)
Figure 4: Latitude zone dependence of long term (50 year) averages of ocean and air
temperatures, wind speed, latent and sensible heat flux and absolute humidity. [Yu et al, 2008]
Figure 5: Fifty year average annual ocean surface temperatures. [Yu et al, 2008]
Figure 6: Average long term (50 year) ocean evaporation rates. [Yu, 2012]

1.4 Climate Energy Transfer

The intensity of the solar flux at the top of the atmosphere is approximately 1365 W m^-2.  This is considered in more detail below in
Section 2.9.  The solar radiation reaching the Earth’s surface at normal incidence (sun overhead) is approximately 1000 W m^-2.  This
is equivalent to the LWIR flux of a blackbody at 364.4 K or 91.4 C.  We are fortunate that convective cooling and the Earth’s rotation
keep the maximum land surface temperatures lower than this.  Since the solar flux is always changing, it is useful to consider the total
daily flux budget instead of a 24 hour average.  Under full summer sun ‘clear sky’ conditions, the total solar flux is approximately 25 MJ  
m^-2 day^-1.  At higher latitudes, the seasonal variation in the daily solar flux is significant.  At 45° latitude, the winter solstice flux is
reduced to 5 MJ m^-2 day^-1.  This is shown in Figure 7.  The data are calculated using the ‘clean air’ algorithm provided in IEEE
Standard 738 [1993].  The concept of a global average solar flux and a global average surface temperature are mathematical
abstractions with little physical meaning.  
Figure 7: Cumulative ‘clear sky’ daily flux values (MJ m^-2 day^-1) during the year at selected latitudes.
The solar spectrum at the top of the atmosphere and at the surface for an atmospheric optical depth of 1.5 (48.2° solar zenith angle)
are shown in Figure 8.  Below 200 nm, the UV radiation is absorbed by molecular oxygen, O
2. Some of the O2 is dissociated by the UV
radiation and the resulting atomic oxygen reacts with more O
2 to form ozone, O3 in the upper atmosphere.  This blocks the UV in the
200 to 300 nm region.  Rayleigh scattering, the elastic scattering of light by air molecules reduces the solar intensity in the blue and
near UV regions.  Rayleigh scattering varies as the inverse fourth power of the wavelength. This produces the characteristic blue color
of the sky.  In addition, Rayleigh scattering, when viewed at 90° to the incident light is strongly linearly polarized. However, this
polarization is not easily observed by the unaided human eye and plays a very minor role in climate energy transfer.  The atmosphere
transmits most of the visible spectrum from the sun, which peaks in the green near 550 nm.  In the near IR (NIR) region, the sunlight is
attenuated by the vibrational overtones of the water vapor IR bands and other IR active molecules.  In the LWIR region, almost all of
the solar flux is absorbed, except for a small fraction in the LWIR transmission window.  However, since black bodies at temperatures
near 288 K (15 C) also emit in the LWIR region, the LWIR solar flux is replaced by LWIR emission from the IR active molecules in the
atmosphere, particularly H
2O and CO2.  There is a continuous exchange of LWIR photons through the absorption and emission
process.  Almost all of the downward LWIR flux reaching the surface comes from the lowest 2 km layer in the atmosphere.  Most of the
upward LWIR emission that is returned to space originates from altitudes above 2 km.
Figure 8: Atmospheric attenuation for top of the atmosphere, AM0 and for an atmospheric optical depth of
1.5, AM1.5 (48.2° solar zenith angle).
Figure 9 shows the LWIR emission to space from the Niger Valley, N. Africa recorded from the Nimbus 4 satellite, early afternoon May
5th 1970.  This figure, or similar ones have been used for many years to justify ‘global warming’ by claiming that an increase in ‘CO
2
absorption’ in the upper troposphere somehow increases the surface temperature.  This is simply impossible.  The LWIR flux that
reaches the surface originates from within the first 2 km layer.  The LWIR flux in the upper troposphere is decoupled from the surface.  
Starting from the left, in the 400 to 600 cm^-1 region, the emission is from the H
2O rotation band at an effective emission temperature
of 250 K (-23 C) and an altitude near 5 km.  In the 600 to 800 cm^-1 region, the emission is from the main CO
2 band at an effective
emission temperature near 220 K and an altitude near 10 km.  Between 800 and 1300 cm^-1, the emission is from the hot desert
surface at a temperature near 320 k (47 C).  In the middle of this is the O
3 stratospheric band which is absorbing some of the surface
flux.  Between 1300 and 1600 cm^-1, most the emission is from the H
2O v2 vibrational band, with some overlapping contribution from
CH
4.  

The atmospheric temperature profile is set by the lapse rate, not the LWIR emission.  As the warm air rises from the surface it expands
and cools.  At night, in this geographic region, the surface cools to approximately 300 K, (27 C) and the surface emission profile shifts
to the region indicated by the blue areas.  The net LWIR emission from the surface decreases by over 100 W m^-2.  However, the
atmospheric emission bands change little because LWIR emission is coupled to the bulk air mass of the atmosphere.  The diurnal
temperature fluctuation in the middle troposphere is approximately 2 K or less.  The atmosphere is always cooling by LWIR emission to
are reduced to a single ‘equilibrium average flux’ the energy transfer physics is lost and we enter into a fictional ‘greenhouse land’
where the Second Law of Thermodynamics no longer applies.  
Figure 9: LWIR emission to space from the Niger Valley, N. Africa recorded from the Nimbus 4 satellite,
early afternoon May 5th 1970
The sun only illuminates the surface during the day and the solar flux at the surface varies continuously with both a diurnal and a
seasonal cycle.  The solar heat is not immediately returned to space.  The atmosphere, the land and especially the oceans store some
of the solar heat and release it later.  Ocean thermal storage and transport plays a major role in stabilizing the Earth’s climate,
especially at higher latitudes.  An important characteristic of these storage reservoirs is the time delay or phase shift between the solar
flux and the temperature response.  Peak diurnal surface temperatures may not be reached until 2 hours after local noon.  Similarly,
peak seasonal temperatures may not be reached until 6 weeks after the summer solstice.  There is a similar delay between the
minimum solar seasonal flux and the minimum temperature.  The Earth’s climate is dynamic and long term climate changes have to be
analyzed as an accumulation of short term variations.  There is no such thing as an ‘average equilibrium climate state’ that can be
analyzed using perturbation theory.  Instead climate has to be analyzed in terms of the dynamic, or time dependent heat transfer
between a set of coupled thermal reservoirs.  At minimum these include the land, the ocean and the lower and upper tropospheric
reservoirs [Clark. 2011].  All of this is governed by the Second Law of Thermodynamics.

Over land, the solar flux is absorbed and converted into heat at the surface.  Thermal storage effects are localized and limited to a few
meters in depth.  Over the oceans, almost all of the solar flux is transmitted below the ocean surface.  The amount of heat that is
stored in these reservoirs is determined by the cumulative effect of the short term time dependent flux balance at the surface.  The
solar heating establishes a set of time dependent thermal gradients at the surface-air interface that cools the surface through a
combination of moist convection and net LWIR emission.  These processes couple the surface heat back into the atmosphere.  In
addition, over land, the increase in surface temperature creates a thermal gradient the conducts heat down into the subsurface
layers.  Under full summer sun conditions, the dry land surface temperature may reach or exceed 323 K (50 C). Over the oceans, the
temperature rise is much smaller, typically near 2 K.  The solar heating is distributed over a range of ocean depths that may extend to
100 m.  The dominant surface cooling process is the wind driven surface evaporation.  The water produced in the cooler surface ‘skin
layer’ sinks and cools the warmer water below [Gentemann et al, 2004; Donlon et al, 2002; Zeng et al, 1999].  In addition, the heat
stored in subsurface ocean layers can be transported over very long distances by wind driven ocean currents (Figure 2) [Cheetham,
2013a].  As discussed above, all of the surface cooling flux that heats the atmosphere does so by convection.  Advection also
contributes to the atmospheric thermal energy transport, particularly at higher altitudes.  The basic reservoir energy transfer
processes are illustrated in Figure 10.  
Figure 10: Climate energy transfer between the four basic thermal reservoirs (schematic)

1.5 Asking the Right Quantitative Questions

Over the last 200 years, the atmospheric concentration of CO2 has increased by approximately 100 ppm from 280 to 380 ppm.  Most
of this increase has occurred within the last 50 years and the current CO
2 concentration is now close to 400 ppm [Keeling, 2013].  This
is shown in Figure 11.  As discussed in more detail below, the observed increase in CO
2 concentration has produced an increase in
downward atmospheric LWIR flux at the surface of approximately 1.5 W m^-2.  This number is derived from atmospheric radiative
transfer calculations using the HITRAN spectroscopic database.  This database has been developed over many years in an effort
initiated by the US Air Force Geophysics Laboratory [Rothman, 2005].  The result can be accepted as valid and reliable.  
Figure 11: The measured increase in atmospheric CO2 concentration [Keeling, 2013]
The global warming question can then be posed in quantitative terms as follows:

1) How does the Second Law of Thermodynamics apply to the energy transfer processes that occur at the Earth’s surface and to the
  so called ‘greenhouse effect’?

2) Has the 1.5 W m^-2 increase in downward LWIR flux from a 100 ppm increase in atmospheric CO
2 concentration produced any
  measurable effect on the Earth’s climate?’  

3) How are the basic physics of the surface energy transfer and the greenhouse effect incorporated into the climate simulation models
  used by UN International Panel on Climate Change (IPCC)?

4) How have these models been validated and what software quality controls have been applied?

The answer too must be given in quantitative terms.  Correlation is not acceptable.  The rooster crows before the sun rises in the
morning.  The high correlation between the rooster crowing and the sunrise does not mean that the rooster causes the sun to rise.  

In order to answer these questions correctly it is necessary to break the discussion into three parts.  First the measured climate record
has to be examined to evaluate possible effects from CO
2.  A valid data set has to be established along with a clearly defined set of
performance requirements that the models have to meet.  Second, the energy transfer processes need to be evaluated to determine
quantitatively how the 1.5 W m^-2 increase in downward LWIR flux from CO
2 interacts dynamically with the climate thermal reservoirs.  
Third, the experimental data have to be compared with the climate model to predictions.  This requires a critical analysis of the various
modeling assumptions used in the climate simulations.  These areas will now be considered in turn.  
Various predictions have been made about the effect of an increase in atmospheric CO2 concentration on the Earth’s climate.  These
include a warming of the surface temperature, an increase in sea level from the melting of glaciers and the polar ice caps, an increase
in ‘weather extremes’ such as hurricanes, tornadoes, droughts, floods and every other disaster imaginable [Alley, 2007].  These will
now be considered in turn.  

2.1 Surface Temperature

The systematic recording of weather station data began in the middle of the nineteenth century with the spread of the railroad and the
telegraph [Benjamin, 2006].  With some exceptions, the instrument climate record really starts at about 1880.  Data recording and
averaging practices have varied, so some care is needed in interpreting the raw data, particularly from different countries.  It is also
important to understand that the climate record is not simply the average of the weather station data archive.  It has been
‘homogenized’ to produce points on a regular coordinate grid, typically 5 x 5° latitude longitude grids for easier comparison to model
output.  (The climate models do not have the fidelity to simulate the temperature record that they are supposed to be predicting).  
Some adjustments are necessary to account for station changes and instrumental bias effects.  However, the same groups of climate
modelers have also been ‘homogenizing’ the data and well documented extra warming has mysteriously appeared in the climate
record.  The climate fox is still guarding the climate henhouse even today [Hansen et al, 1999].  The climate temperature record has
been ‘adjusted’ to fit the modeling results [Cheetham, 2013b; D’Aleo, 2010].  

The temperatures recorded by a weather station are not true surface temperatures.  The weather station temperature is the
meteorological surface air temperature (MSAT).  This is the temperature measured in a ventilated enclosure paced for convenience at
eye level, 1.5 to 2 m above the ground.  Historically in the US, the maximum and minimum daily temperatures were recorded using Six’s
thermometer.  The minimum MSAT generally occurs near dawn.  At this time, the air and ground are at similar temperatures and the
minimum MSAT is approximately the bulk temperature of the air mass of the local weather system that is passing through.  The
maximum MSAT is generally recorded in the early afternoon.  It is the air temperature produced by the convective mixing of the warm
air rising from the surface as it interacts with the cooler air at the MSAT thermometer level.  Under full summer sun illumination, bare,
dry ground temperature may easily reach 50 C (~120 F).  The maximum MSAT will generally be some 20 C cooler near 30 C (~85 F)
[Clark, 2011a].  

The maximum and minimum MSATs measure temperatures from two very different processes.  In many parts of the world, the weather
systems are formed over the oceans and the ocean temperature of formation is ‘carried’ by the air mass over long distances.  This
information is found in the minimum MSAT data.  The sun heats the surface during the day and the surface temperature that drives the
convection depends on the solar flux and the surface evaporation.  The increase in temperature from the minimum to the maximum is a
combined measure of convective mixing, solar flux, cloud cover and surface moisture/precipitation.  This may be understood by
examining the temperature record for the continental US.  

2.2.1 The Temperature Record for the Continental US

The homogenized NASA GISTEMP temperature record for the continental US is shown in Figure 12 [NASA 2013].  The annual and 5
year averages are plotted from 1880.  The data are presented as a temperature anomaly.  This is just the data set with the long term
mean subtracted out to show the variations.  The first point to note is that there is a peak in the 1930s from the Dust Bowl Drought.  
Temperatures then dropped and started rising again about 1980.  There are also large ‘spikes’ in the annual temperature data.  The
spike in annual temperature in 2012 is not unusual.  Figure 11 above shows that there was no significant increase in CO2
concentration during the period of the dust bowl drought.   The upward trend from 1980 is just a repeat of the dust bowl cycle
superimposed on an upward sloping baseline.  The explanation of Figure 12 is that the cycles are the caused by variations in ocean
surface temperatures, the PDO and AMO mentioned above [D’Aleo, 2008].  The rising baseline is a combination of two effects.  First,
there is a long term, 200 year warming trend as the Earth recovers from the Little Ice Age or Maunder Minimum [Akasofu, 2010].  
Almost no sunspots were observed on the sun between approximately 1650 and 1700.  This caused a slight reduction in the solar flux
which was sufficient to reduce global temperatures.  During this period the River Thames regularly froze at London Bridge and ice fairs
were held on the river.  Second, most of the weather stations have stayed in the same location as the cities and suburbs were built up
around them.  The replacement of fields with houses and roads has increased the local temperature because of changes in vegetation
and thermal storage.  This is known as the urban heat island effect or UHI.  It is discussed in more detail below in Section 2.2.2.  

The effect of the AMO and the PDO on the US continental temperature record can be demonstrated by scaling and adding the PDO
and AMO anomalies together to obtain the best least squares fit to the 5 year average temperature data.  This is illustrated in Figure
13.  The best fit was obtained using 0.85 AMO + 0.21 PDO with a 0.78 correlation coefficient.  The data homogenization process has
also produced well documented warming effects in the data.  This is illustrated in Figure 14 and 15.  Figure 14 shows the annual
GISTEMP data set downloaded in 2008 compared to the 2012 data.  The arrows indicate some of the places where the data has
changed.  Figure 15 shows the difference between the two data sets (2012-2008).  A ‘new and improved’ homogenization algorithm
has conveniently added over 0.2 C to the observed ‘global warming’ since 1940.  
SUMMARY
2.0 THE CLIMATE RECORD
Figure 12: Continental US temperature record from 1880, 1 year and 5 year averages, homogenized
(adjusted) data from NASA GISTEMP.
Figure 13: Fit of the combined PDO and AMO ocean temperature anomalies to the US continental
temperature record (5 year average).  The best fit was obtained using 0.85 AMO+0.21PDO.
Figure 14: 2008 and 2012 GISTEMP annual temperatures for the continental US.  Some of the
‘homogenization’ changes are indicated by the arrows.
Figure 15: [2012-2008] temperature anomaly differences calculated from Figure 4.  ‘Homogenization’ has
added 0.2 C of warming to the 2012 data set from 1940 to 2007compared to the 2008 data set.
2.2.2 Urban Heat Islands: Los Angeles

Figure 13, above illustrates the effect of ocean surface temperatures on the continental US temperature record.  In California, the
principal ocean influence is the PDO.  This may be investigated by examining the long term temperature trends of individual weather
stations.  The minimum MSAT temperature is basically a measure of the air temperature of the prevailing weather systems as they move
through the state.  The maximum MSAT is a measure of the solar heating of the ground and the convective coupling of the warmer
surface air to the MSAT thermometer.  Figure 16 shows the five year average of the minimum MSAT anomaly (temperature series with
the mean subtracted) for the Los Angeles Civic Center from 1925 to 2005.  The five year trend of the PDO is also plotted over the same
time scale.  The straight line fits to the data are also shown.  It can be seen that the LA temperature data follows the PDO trend with a
change in slope.  This slope is an approximate measure of the urban heat island (UHI) effect for Los Angeles.  As the city was built up
around the weather station, open land was replaced by roads and buildings.  The change in heat storage effects leads to an increase in
the average minimum temperature.  This is a local weather station bias.  The difference in slope between the station data and the PDO
provides an initial measure of the UHI effect for Los Angeles.  In this case the UHI coefficient is 0.022 C per year.  This means that over
the 80 year period of record, the five year average minimum temperature of Los Angeles at the Civic Center has increase by almost 1.8
C relative to the PDO.  This has nothing to do with CO
2.  It is just the effect of warmer roads and buildings.  
Figure 16:  Five year averages of the trend for the minimum MSAT for the LA Civic
Center and for the PDO [Clark 2013b, 2011, 2010b].
Figure 17 shows the same type of plot for the Los Angeles Airport weather station.  The period of record is 60 years from 1950.  This
station is located on the coast, about 20 km west of the Civic Center.  The prevailing marine air flow reduces any urban heat island
effects and the linear slope of the five year minimum MSAT average tracks the PDO reference slope quite closely.  The difference in
this case is 0.005 C per year.  This means that five year average temperature at LA Airport has increased by 0.3 C over 60 years.  
The PDO slope is different from Figure 6 because the period of record is different.   
Figure 17: Five year averages of the trend for the minimum MSAT for LA Airport
and for the PDO. [Clark 2013b, 2011a, 2010b]
This technique is a general one for California.  By using the PDO as a reference, weather station bias can be investigated and UHI
effects can be identified.  The analysis described here only used a linear fit to the data to demonstrate the basic technique.  More
sophisticated analytical techniques may also be used to investigate the data trends and microclimate effects in more detail.  Figure 18
shows the UHI bias coefficients determined for 33 California weather stations from different parts of the state.  These are divided into
four groups: coastal; rural; urban and anomalous based on the magnitude of the UHI coefficient and obvious discontinuities in the data.  
It should be clear from Figure 16 through 18 that there has been no CO
2 induced global warming in the State of California.  The
observed increases in the weather station minimum MSAT data can be explained quite simply in terms of the warming trend of the PDO
from 1950 to 2000 and urban heat island effects.  Raw weather station data was used, so there is no ‘homogenization’.  
Figure 18: Warming trend data for the weather stations divided into four groups.  See text for further discussion
[Clark 2013b, 2011, 2010a].

2.2.3 Air Temperatures in the Lower Troposphere

Since 1979, air temperature data has been available from satellite sensors.  This record is compiled by two groups, the University of
Alabama, Huntsville (UAH) and Remote Sensing Systems (RSS).  There is little difference between these two data sets and they are
free of weather station ‘homogenization’.  One of the most important results from the satellite data is the demonstration of the role of
the ENSO El Nino events in changing the air temperatures in the lower troposphere.  Figure 19 shows the RSS lower troposphere
global average temperature.  There was no trend in the data from 1979 to 1997 [REMSS, 2011].  After the major El Nino event of
1997/8 there was a step increase in temperature followed by stable record with no trend.  This again illustrates the importance of
ocean surface temperatures in setting the Earth’s climate.  It also shows that there is no measurable effect from CO
2 in the satellite
record.
Figure 19: RSS lower troposphere global average satellite temperature data
2.2.4 Land Surface Temperatures from Meteostat Satellite Data

Surface temperatures for Africa, Western Europe and parts of the Middle East have been recorded by a series of Meteostat satellites.  
The satellites were placed in geosynchronous orbit with the observation axis pointed to 0° latitude, 0° longitude (the Equator at the
Greenwich Meridian).  Surface temperatures were derived from IR camera data.  Over an observation period of 20 years using data
from satellites 2 through 7, the overall temperature trend was a cooling of up to 2 K per decade.  In addition, there were two areas that
showed warming trends because of changes in local land use.  In SE. Iraq, at location L4, the draining of the marshes produced a
noticeable warming trend.  In Tanzania, at location L5, the observed warming trend was attributed to mining operations.  This is shown
in Figure 20 [Rosema et al, 2013].
Figure 20: Decadal surface temperature trends from Meteostat satellite data

2.3 Sea Level Rise

The accurate determination of sea level is not an easy undertaking.  The continents move with plate tectonics.  Sea level changes with
the tides, winds, atmospheric pressure and ocean temperature.  The historical record from tide gauges is quite sparse.  The
interpretation of satellite radar altimetry sea level data has been questioned.  However, from the analysis of the available records, sea
levels have been rising by approximately 170 mm (~7”) per century for the last 150 years as the Earth has warmed up from the Little
Ice Age.  Superimposed on this trend are fluctuations caused by the ocean oscillations [Akasofu, 2010; Houston & Dean, 2011;
Morner, 2010
; 2013].  This is illustrated in Figure 21.  

Predictions of a dramatic sea level rise are based on model projections that have never been validated.  Current IPCC projections are
in the range of 5 mm/yr.  Figure 22 shows the results of an analysis of the tide gauges along the US west coast [Clark, 2011b].  
Instead of increasing to match model projections, the slope is decreasing.  This is consistent with the negative or cooling phase of the
PDO.  The 5 mm/yr projection is also included for reference in the 1990 to 2010 period.  There is no evidence in the tide gauge data
of any effect from CO2.  Similarly, claims that rising sea levels will flood South Pacific Islands are fraudulent [Gray, V. 2011].

An independent indicator of sea level change is the small variation in the length of the day measured using atomic clock techniques.
The basic argument is that if sea level is rising, then the moment of inertia of the Earth should increase, the speed of rotation should
slow and the length of the day should increase.  Figure 23 shows that the length of the day has decreased by approximately 2.5 msec
since 1970.  While the detailed analysis may be complex, this again indicates that sea level rise is not an issue [Morner, 2011
; 2013].   
Figure 21: Sea level rise as a result of the recovery from the Little Ice Age [Akasofu, 2010]
Figure 22: Linear fit to the average tide gauge anomaly data using 20 year interval subsets.  The recent
downward trend can clearly be seen in the 1990 to 2010 data subset [Clark, 2011b]
Figure 23: Change in the length of the day (msec.) from 1960 onwards

2.4 Polar Ice Extent

The Earth’s climate has been warming since the end of the Little Ice Age in the early eighteenth century.  Unfortunately, detailed
satellite observations of ice extent are only available from the 1970’s.  One long term record that is available is the summer limit of the
ice edge in the Norwegian Sea.  This is shown in Figure 24, along with part of the more recent satellite record [Akasofu, 2010].  The
Norwegian Sea ice edge retreat shows an approximately linear decrease in ice extent from 1800.  Superimposed on this are periodic
fluctuations from ocean oscillations.  Minima occur near 1860, 1940 and 2010.  Maxima occur near 1920 and 1950.  Since
atmospheric CO
2 levels did not begin to increase significantly until the 1960’s, there is no reason to attribute any of the observed
changes to CO
2 induced global warming.  These observations have recently been confirmed by ice core isotope analysis from the
Akademii Nauk ice core [Opel et al, 2013].
extent data from 1970 to 1998 [Akasofu, 2010].
Figure 25 shows the ice area for the Artic, Antarctic and total polar ice area from 1979.  The Arctic ice area shows a slight decrease
and the Antarctic ice area shows a slight increase.  This can be seen more clearly in the ice area anomaly plots for the Arctic and
Antarctic shown in Figure 26 and 27 [Cryosphere Today, 2013].  There was a decrease in ice area in the Arctic in 2007 that was
caused by unusual weather conditions [Lindsay et al, 2009].  This occurred again in 2012.  These events are circled in Figure 26.  
The winds drove the ice out of the Artic into the open sea where it melted.  The ice area extent recovered between 2007 and 2012.  
The latest 2012-2013 Arctic ice freeze was one of the fastest and most extensive in the satellite record.  However the record is still
only half of the duration of the typical 60 year ocean cycle.  The slight decrease over the period of observation is consistent with a
continued recovery from the Little Ice Age.  There is no obvious trend in the data to indicate any effect from increased atmospheric
CO
2 levels, nor should any be expected.  
Figure 25: Arctic, Antarctic and total polar ice area from 1979
Figure 26: Northern hemisphere sea ice area anomaly (deviation from 1979-2008 mean).
Figure 27: Southern hemisphere sea ice area anomaly (deviation from 1979-2008 mean).

2.5 Glacier Retreat

As the Earth’s climate has warmed since the end of the Little Ice Age, glaciers have generally decreased in length [Oerlemans 2005].  
Glaciers are flowing rivers of ice and the length depends on the glacier mass balance which is related to the precipitation, solar
radiation and air temperature.  Figure 28 shows the observed changes in length for 5 glaciers from different parts of the world.  These
glaciers have clearly been retreating since the end of the Little Ice Age.  Figure 29 shows the temperature changes derived from
glacier length/mass balance analysis.  There is nothing to indicate any effects on glacier length that could be attributed to an increase
in atmospheric CO
2 concentration.  It should also be noted that recent claims of Himalayan Glacier melting by the IPCC have been
shown to be incorrect [McLean, 2010a].  In addition, loss of ice cover on Mount Kilimanjaro has been attributed to long term local
climate changes that have resulted in increased sublimation of the ice [Fairman et al, 2011].  Again, no CO
2 induced global warming is
involved.  
Figure 28: Glacier length data for 5 glaciers in different parts of the world [Oerlemans 2005].
Figure 29: Temperature changes derived from glacier length data [Oerlemans 2005].

2.6 US Rainfall

Extended periods of low rainfall in parts of the US for periods of 30 years or longer should be considered as normal climate variation
consistent with ocean cycle lengths.  Figures 30 and 31 show the average annual rainfall for the US since 1895 [NOAA, Rainfall,
2011].  The totals have remained within the 29±5 inch range for over 100 years.  There has been a slight increase in average rainfall
of 2 inches over this period as determined using a simple linear fit to the data.  However, a more careful examination reveals a climate
shift in the 1970’s related to the El Nino event in 1977-78.  When the rainfall data is separate into 2 data series with a split at 1970, the
climate shift becomes apparent.  
Figure 30: Average annual rainfall for the continental US from 1895 showing a simple linear trend.
Figure 31: Data from Figure 30 showing the step increase in rainfall from the 1977 climate shift.

2.7 Hurricanes and Tornadoes

The increase in atmospheric CO2 concentration has been blamed for increases in cyclone (hurricane) intensity and even increases in
the number of tornados.  There is no evidence to support such claims.  Figure 32 shows the estimated global and Northern
Hemisphere cyclone intensities from 1972 inwards.  The intensities are plotted as accumulated cyclone energy or ACE, which is a
combination of the square of the wind speed and the duration of the event.  Current cyclone activity is at rather low levels [COAPS,
2013].  In addition, there have been fewer hurricanes making landfalls in the US.  It is also important to separate hurricane damage
from hurricane intensity.  In the US, the increase in population in areas such as Florida means that the amount of damage that even a
modest hurricane can cause has increased significantly in recent years.  The formation of hurricanes and the false claims of CO
2
effects have been addressed in detail by William Gray [2011].  
Figure 32:  Global and Northern Hemisphere cyclone intensities from 1972
Tornadoes are produced by localized, intense storms that form at the interface between warm and cold weather systems.  They are
quite common in the central regions of the US because of the interactions between moist tropical air from the south and cold polar air
from the north.  There are two important points to consider in evaluating the tornado data.  First, the introduction of Doppler radar has
resulted in the detection of a larger number of smaller tornadoes.  Second, urban growth in tornado prone areas has produced more
financial damage from the same annual tornado count.  Figure 33 shows the US annual count of strong to violent tornaodoes (F3+)
from 1954 [NOAA, 2013].  There is clearly no trend that can be attributed to CO
2.  
Figure 33: US F3+ tornado count from 1954

2.8 Extreme Weather Events

One of the most egregious claims used in the global warming argument is that the observed increase in atmospheric CO2
concentration is causing an increase in ‘extreme weather events’.  This has resulted in numerous sensational claims about global
warming as the cause of local temperature records, floods, droughts, hurricanes and other natural disasters.  None of these claims
have any basis in reality [Khandekar, 2013].  Consider for example the heat wave and forest fires that occurred in Russia during the
summer of 2010.  These were caused by a persistent ‘blocking high’ over Western Europe.  This is part of the normal fluctuation in
weather patterns over Western Russia.  There has been no change in the long term trend of July monthly temperatures in this region
since 1880.  Similarly, the 2010/2011 cold winter along the Pacific Coast of S. America is part of a natural weather sequence that has
been documented since Aztec times [Ambler, 2010].  In spite of all the sensationalist claims related to ‘hurricane Sandy’, it was simply a
normal, predictable ‘100 year’ storm.  Such storms have been documented since the US was first settled by Europeans in the
seventeenth century.  Two such storms occurred in 1635 and 1638 [Donnelley et al, 2001].  The modern urban infrastructure was
simply not designed to withstand such a storm.  

There have also been numerous fraudulent claims of relationships between global warming and droughts.  Various regions of the
world, including parts of North America and the Sahel (sub Sahara) region in Africa have experienced extended droughts.  All of these
have been related to changes in ocean surface temperatures [Hagos & Cook, 2008; McCabe et al, 2008].  

2.9 Longer Term Climate Variations: The Effect of Changes in the Solar Flux

The number of sunspots visible on the sun fluctuates with an approximate 11 year cycle.  The sunspot cycle is in fact a nominal 22
year cycle with a magnetic field reversal after 11 years.  The length of the sunspot cycle and the number of sunspots at the solar
maximum is highly variable.  In addition, the solar flux at the top of the Earth’s atmosphere is not constant, but increases by
approximately 1 W m^-2 at the solar maximum for a sunspot number near 100.  This is shown in Figure 34 using VIRGO satellite
radiometry data [VIRGO, 2013].  The sunspot index at the solar maximum in 2000 was 120.  The latest solar cycle has been rather
slow to start and will have a maximum sunspot count near 67.  [NASA, Sunspot Cycle, 2013].  This can be clearly seen in Figure 34
and 35.  Sunspots were first observed by Galileo in 1610.  From 1645 to 1715 very few sunspots were observed.  This period is known
as the Maunder Minimum.  It is associated with a cool climate period known as the Little Ice Age.  Contemporary records indicate that
the River Thames in London regularly froze over in winter during this time and ice fairs were held on the frozen river.  In addition, there
was a period of lower sunspot activity from 1790 to 1820 that is known as the Dalton Minimum.  This was also associated with a cool
climate period.  Over the last 50 years, sunspot activity has passed through a modern maximum with the sunspot index running 70%
above the long term average.  This period of high sunspot activity has now ended.  Prior to 1610, the sunspot record has been
reconstructed using 14C or 10Be isotope data.  Figure 33 shows the sunspot record.  Figure 35a shows the14C reconstruction from
800 AD and Figure 33b shows the observational record from 1610.  The various minima and maxima are labeled.  Please note that the
time scales are reversed between these two figures.  Figure 33c shows the sunspot record from 2000 on an enlarged scale.  The
marked decrease in sunspot activity can clearly be seen.  The peak for the latest cycle is approximately half of the previous one.  
Inspection of Figure 35b shows that this behavior is similar to the start of the Dalton Minimum in about 1800.  Instead of global warming
a major concern should be cooling and the possible onset of another Maunder type minimum [Abdussamatov,
2013].  However, it is
still very difficult to predict the future behavior of the sun and we will have to wait and see what happens.  
Figure 34: Changes in total solar irradiance from the VIRGO radiometer.
Figure 35: The sunspot record from 1600 and a longer time reconstruction using 14C isotope data. (The
time scales are reversed between a and b) [http://en.wikipedia.org/wiki/Maunder_Minimum]
The meteorological surface air temperature record dates back to the middle of the nineteenth century, with some limited earlier data.  
Prior to this, climate temperature data has to be reconstructed using proxy data based on isotope ratios or other means.  Tree ring
data is usually considered unreliable for climate temperature data, although it can be used to provide drought information [Helliker &
Richter, 2008].  Figure 36 shows a climate reconstruction for the last 2000 years based on 18 different climate proxy records,
excluding tree ring data.  The relationship between the climate record and the sunspot record is quite apparent.  Furthermore, there is
nothing exceptional about the current climate warming.  It is still cooler than the Medieval Maximum.  The atmospheric CO
2
concentration did not even start to rise above 280 ppm until after 1800.  The climate has fluctuated for 1800 of the last 2000 years
without any change in CO
2 concentration, so there is no reason to expect any effect from the recent 100 ppm increase in CO2
concentration.  Changes in sunspot activity are quite sufficient to explain the climate variation over this time scale.  
Figure 36: 2000 year climate reconstruction using proxy data from 18 records excluding tree rings, after
Loehle and McCulloch [2008].

In addition to changes in the solar flux caused by sunspots, there is also a longer term variation in the solar flux caused by planetary
perturbations of the Earth’s orbit, mainly by Jupiter and Saturn.  These are known as Milankovitch cycles [Varadi, 2003; Milankovitch,
1920]. In the recent geological past, a nominal 100,000 year variation in the ellipticity of the Earth’s orbit has cycled the Earth through
a series of Ice Ages.  The change in solar flux is approximately 1 W.m-2.  During the last Ice Age, average sea level decreased by 120
m and the water was deposited at higher latitudes in ice sheets over 1 km thick.  Simple calorimetric calculation shows that an increase
in surface flux of 0.4 W m^-2 coupled to the ice was sufficient to bring the Earth out of the last Ice Age.  However, it requires 10,000
years for the ice to melt.  As the ice melted, the atmospheric CO
2 concentration increased from 200 to 280 ppm.  However, in this
case, the egg has to come before the chicken and the oceans have to warm first before the CO
2 concentration increases.  The
storage of CO
2 in the oceans also involves some complex buffer chemistry [Follows et al, 2006].  It has also been proposed that
variations in the solar /galactic comic ray intensity balance cause changes in cloud cover and that this contributes to climate change
[Svensmark, 2012].


2.10 Ocean 'Acidification'

Since the Earth’s climate has not been cooperating and global warming has stalled, another environmental scare is needed.  This is
ocean acidification.  The increase in the atmospheric concentration of CO
2 is partially absorbed by the oceans.  This may result in a
rather small decrease in ocean pH that should not cause concern.  However, environmental alchemy has been invoked and alarmist
claims of ocean acidification have been made.  This has been addressed for example by Idso and Ferguson [2009] and will not be
considered here.  

The solar flux is always changing both on a daily and a seasonal time scale.  The peak solar flux reaching the Earth’s surface is
approximately 1000 W m^-2.  At night it is zero.  Under full ‘clear sky’ summer sun conditions, the total daily solar flux is approximately
25 MJ m^-2 day^-1.  In order to dissipate this flux, there has to be a temperature gradient.  This is required by the Second Law of
Thermodynamics.  Furthermore, the temperature gradient is not fixed, but it changes continuously in response to the solar flux.  The
land and the oceans interact in very different ways with the solar flux, so it is necessary to consider the air-land and the air ocean
interfaces separately.  All of the surface heat is transported back through the atmosphere by one of two basic pathways.  Some of the
LWIR flux emitted by the surface is transmitted through the atmospheric LWIR window and is radiated directly to space.  The rest ends
up as convection.  The dry air convection or sensible heat flux is produced when the air at the surface is heated and rises through the
atmosphere.  When the surface is moist or over liquid water, evaporation occurs.  Latent heat of evaporation is removed from the
surface and is transported upwards with the air convection.  As the air rises, it cools.  The water condenses above the saturation level
to produce clouds.  The latent heat is released and drives further convection.  In addition any excess LWIR flux emitted by the surface
outside of the LWIR window is absorbed by the atmosphere and this drives more convection.  Although it is not part of the surface
energy transfer, some of the incident solar flux also heats the atmosphere directly by NIR absorption in the H
2O and CO2 vibrational
overtone bands.  

The basic flux balance equations that give the surface temperature will now be considered, followed by their application to the land-air
and ocean-air interface.  This is followed by a description of the energy transfer through the upper and lower tropospheric reservoirs.  
3.0 CLIMATE ENERGY TRANSFER AND SURFACE TEMPERATURE
The thermal conductivity may be calculated analytically using a finite element approach [Billo, 2007].  Over the ocean, almost all of the
solar flux is transmitted through the ocean surface.  Ocean heating has to be calculated using a combination of depth dependent solar
absorption from Eqn. 7 and downward layer mixing or diffusion [Clark, 2013a, 2013b, 2010a].  

Eqns. 3 through 11 provide a basic description of the time dependent surface energy transfer.  The full details of the fluid dynamics
are complex, so the equations include several simplifications to the energy transfer processes.  In particular, Eqn. 9 uses a bulk
parametric description of the sensible heat convection and Eqn. 10 assumes linear relationship between wind speed and ocean
surface evaporation.  However, these equations provide a suitable framework that may be used to examine ocean heating and the
ocean surface flux balance.  

Over land, both the solar and the LWIR flux are absorbed at the surface and the surface heating is localized and limited to a few
meters in depth.  In addition, the change in temperature lags the change in flux, which is a characteristic property of a thermal storage
reservoir.  The diurnal lag or phase shift is typically up to 2 hours and the seasonal lag is near 2 months. The phase shift also
changes with depth below the surface.  This thermal behavior was understood and explained by Fourier early in the nineteenth
century [Fourier, 1827].  It clearly shows that there is no thermal equilibrium at the surface.  

Eqn. 3 means that all of the flux balance terms are coupled to the heat capacity of the surface.  The 1.5 W m^-2 increase in downward
LWIR flux from a 100 ppm increase in atmospheric CO
2 concentration has to be added to the time dependent flux balance and the
result is then divided by the heat capacity of the surface layer to obtain the surface temperature change.  The change in flux from CO
2
cannot be treated as an independent ‘add on’ average.  Land surface heating was investigated by Clark [2013b] using measured
surface flux data from a monitoring site in S. California.  Eqn. 3 was used to develop a basic model of the measured surface
temperature over a 1 year period.  When the downward LWIR flux was increased by 1.5 W m^-2, the increase in surface temperature
was less than 0.07 C.  In practice, the daily fluctuations in surface flux from cloud cover and surface evaporation mean that this
temperature change is too small to measure.  

3.2 The Land-Air Interface

Figure 37 illustrates the diurnal flux balance for dry convection over land under full summer sun conditions.  This is based on
measured flux data from the University of Irvine ‘Grasslands’ monitoring site [Clark, 2011a, Goulden, 2012].  The solar heating flux, the
convection and net IR cooling fluxes and the subsurface thermal transfer are plotted for a 24 hour cycle in Figure 37a.  The
corresponding surface and air temperatures are shown in Figure 37b.  In this illustrative example, the total thermal flux dissipated by
the surface during the 24 hour period from both net LWIR emission and convection in Figure 37a is 25.4 MJ m-2 representing full
summer sun ‘clear sky’ conditions.  Of this, approximately 23 MJ m^-2, or 90% is dissipated during the day and early evening.  The
convective flux is 14.5 MJ m^-2 or 57% of the total flux and the associated LWIR flux is 8.5 MJ m-2 or 33% of the total flux.  Only 2 4 MJ
m^-2 is dissipated at night through the LWIR transmission window.  The time delay or phase shift between the maximum solar flux and
surface cooling flux in this case is almost 2 hours.  The convection continues after sunset until the ground and air temperatures
equalize.  After that the surface cooling is limited to the net IR flux through the LWIR window.  Under these conditions, the lower
tropospheric reservoir acts as a ‘thermal blanket’ that slows the night time cooling.  This is how the surface temperature is maintained
at night.  The night time surface cooling flux typically varies between 0 and 100 W m^-2, depending on humidity and cloud cover.  The
increase in the downward LWIR flux from a 100 ppm increase in atmospheric CO
2 concentration is approximately 1.5 W m^-2. This is
too small to have any measureable effect on surface temperatures when it is added to the net LWIR flux term and used to calculate the
total flux balance [Clark, 2011a].  In signal processing terms it is ‘buried in the noise’.

Figure 37 shows the energy transfer for the dry land-air interface under full summer sun conditions.  If the solar flux is reduced, the
diurnal flux behavior will be similar, but with a reduced magnitude.  If water is present, surface evaporation will add a latent heat flux.  
This will reduce the surface heating and therefore the LWIR emission and the sensible heat flux.  Energy is still conserved and the
latent heat will be released through condensation of the water vapor in the troposphere as the warm air rises from the surface and
cools.  The surface evaporation will also vary with the wind speed and the humidity gradient.  Vegetation will also increase the surface
area and reduce the temperature rise.  The details of vegetation related photosynthesis and evapotranspiration are complex, but the
net result can still be considered in terms of a time dependent net surface flux balance [Mengelkamp et al, 2006].  
Figure 37:  Diurnal surface and air temperatures and the dry convection
surface flux terms for full summer sun illumination conditions.

3.3 The Ocean-Air Interface

The ocean-air interface is very different from the land-air interface.  The surface temperature gradients are much smaller, most of the
solar flux penetrates below the surface and the dominant cooling process is wind driven evaporation.  The thermal storage is not
localized and heat is transported and recirculated over very long distances.  The penetration depth of LWIR radiation into water near
650 cm-1 is less than 100 micron.  This means that the LWIR flux from CO
2 is coupled to the surface evaporation and small changes in
this LWIR flux cannot heat the ocean below.  Figure 38 shows the absorption profile of the solar flux, normal incidence, 300 nm to 2
µm, into water [ASTM, 2012; Hale and Querry, 1973].  Over half of the solar flux is absorbed within the first meter layer of the ocean.  
The rest is attenuated within the first 100 m depth.  
Figure 38: Penetration of solar flux, normal incidence, 300 nm to 2 µm into water
Figure 39 shows the penetration depth of the LWIR flux into water (99% attenuation).  Figure 39a shows the absorption below 3000
cm-1.  Figure 39b shows the CO
2 LWIR region on an expanded scale.  The approximate location of the P and R branches of the main
absorption bands and the adjacent overtone bands are indicated.
to 1200 cm-1.  The approximate locations of the CO2 absorption features are also indicated.

3.3.1 Energy Transfer in the Pacific Ocean Warm Pool

The tropical Atlantic and Pacific Oceans are heated by the sun as ocean water is transported from east to west by the equatorial
currents.  This leads to the formation of the tropical warm pools in the western equatorial regions as shown above in Figure 5.  
Maximum ocean surface temperatures in the equatorial warm pools are near 30 C and do not normally exceed 32 C.  In these regions,
the ocean cooling flux is in a dynamic balance with the tropical solar flux.  This balance is controlled by the wind speed.  The total daily
‘clear sky’ solar flux is approximately 25 MJ m^-2.day^-1.  The net LWIR emission from the surface is approximately 50 W m^-2 and the
sensible heat flux is near 10 W m^-2.  This gives a daily cooling flux of 5 MJ m^-2 day^-1 from these two processes.  The balance of the
cooling, 20 MJ m^-2.day has to come from wind driven evaporation.  All of the cooling has to occur within a thin surface or skin layer.  
The cooler water produced at the surface has a higher density so it sinks and diffuses down through the warmer water below.  Typical
daily wind driven evaporative cooling rates based on Pacific Ocean TRITON Buoy data for 156º E are 20±10 MJ m^-2.day for average
wind speeds of 5±4 m s^-1.  This is illustrated in Figure 40 [Clark, 2011a].  

The sun only illuminates the ocean surface during the day.  If 10 MJ m^-2 of heat is coupled into the first cubic meter of the ocean
without any cooling, the temperature rise is near 2.4 C.  Depending on the wind speed, the near surface afternoon temperature at
latitude 156 º E normally rises between 0 and 1 C from 30 up to 31 C.  It then cools back down at night with continued surface cooling
and downward diffusion.  If the wind speed stays low and the temperature starts to reach 32 C, the increased evaporation causes the
2010].  Now, the total daily increase in LWIR flux from the observed 100 ppm increase in atmospheric CO
2 concentration is only 0.13
MJ m^-2 day^-1 coupled into the surface skin layer as part of the LWIR flux balance.  This LWIR flux balance also varies by at least ±2
MJ m^-2 day^-1 as the surface and air temperatures and the humidity change.  It is simply impossible for an increase of 100 ppm in
atmospheric CO
2 concentration to have any measurable effect on the ocean temperature under these conditions.  

Similarly, at mid latitudes, the seasonal change in ocean temperatures stores and releases 1000 MJ of thermal energy, or 40 days
supply of full tropical solar flux from a column of water with an area of 1 m^2 and a depth of 100 m.  An increase of 1.5 W m^-2 in LWIR
flux from CO
2 coupled to the skin layer is like a flea on an elephant.  
Figure 40: The dynamic ocean surface energy balance in the tropical warm pools (schematic).  The solar
flux is balanced by the total surface cooling, which is dominated by wind driven surface evaporation.

3.3.2 Global Changes in Ocean Evaporation and Surface Temperature

Small, long term changes in wind speed have had a significant effect on ocean evaporation rates.  Yu [2007] found that between 1977
and 2003 the global ocean evaporation rate has increased 11 cm yr^-1 from 103 to 114 cm yr^-1, with an uncertainty of ±2.72 cm yr^-
1.  This was caused by a 0.1 m s^-1 increase in average wind speed.  When fully coupled to the ocean surface evaporation, the 1.5 W
m^-2 in LWIR flux from 100 ppm CO
2 produces an increase in the evaporation rate of 2.4 cm per year.  This is below the measurement
uncertainty of Yu’s estimates.  The evaporation rates are presented as a bar chart in Figure 41.  
Figure 41: Changes in average ocean evaporation rates from 1997 to 2003 and the evaporation from
1.5 W m^-2 of CO
2 LWIR flux fully coupled to the ocean surface skin layer.
Average ocean surface temperatures have not increased significantly in the last 15 years.  The details may vary depending on the
data set and the averaging periods used.  Figure 42 shows average ocean surface temperature anomalies from the ±60 latitude
bands.  Two data sets are shown.  The first is the Reynolds Optimal Interpolation (ROI) data set from 1983 on and the second is the
satellite microwave sounding data set from 2003 on developed by Dr. Roy Spencer (SMS) [Eschenbach, 2013].  For comparison, the
ROI data set has been split into two plots showing the data before and after the major El Nino event in 1998.  The increase in
atmospheric CO
2 concentration is also shown.  From 1983 to 1998, the ocean surface temperatures increased.  However, since then
the temperatures have been stable.  There is no relationship between the measured ocean temperatures and the increase in CO
2
concentration.  The oceans can only be heated by the sun.
Figure 42:  Changes in the world ocean surface temperature anomaly from 1983 for the ±60° latitude
bands.  For further explanation see text.

From this discussion, it should be clear that the increase of 1.5 W.m-2 in downward LWIR flux from a 100 ppm increase in atmospheric
CO2 concentration cannot produce any measurable ocean heating.  Instead, changes in wind speed, coupled through the ocean
gyres can cause significant changes in ocean surface temperature.  This is the source of the observed changes in the climate record

3.3.3 Climate Change, Ocean Circulation and Plate Tectonics

The Earth’s climate is set by the long term dynamic balance between the ocean solar heating and the wind driven ocean surface
evaporative cooling.  The effect of wind speed and solar flux on ocean surface temperature may be understood by using a scaling
argument based on Yu’s formulation of the ocean evaporation [Yu 2007; Yu et al., 2008].  This is shown in Figure 43.  The relative
evaporation rate of 1.0 at 30 C indicated by the black circle is ocean warm pool surface temperature for which the cooling flux
balances the current tropical solar flux at a wind speed of 5 m s^-1 and a surface-air temperature difference delta T of 1 C.  The
relative humidity is set to 70%.  The cooling flux is much more sensitive to the wind speed than the surface–air thermal gradient or the
ocean surface temperature.  A doubling of the wind speed from 5 to 10 m s^-1 doubles the evaporation rate.  Similarly, halving the
wind speed from 5 to 2.5 m s^-1 halves the evaporation rate.  An increase from 1 to 2 and then to 3 C in the surface-air temperature
difference only increases the evaporation rate by 10 and then 20%.  Similarly, a reduction in solar flux to 80% of the current value only
decreases the ocean surface temperature warm pool balance by 4 C to 26 C.  This is very different from the results obtained using
blackbody equilibrium surface temperature arguments.  There is no need to invoke ‘atmospheric IR absorption’ to increase the
‘equilibrium surface temperature’ by 33 K from 255 to 288 K [Taylor, 2006].  The tropical oceans simply accumulate the solar heat until
the equatorial warm pools reach a flux balance at surface temperatures near 303 K (30 C).  This also provides an alternative
explanation for the so called ‘faint young sun paradox’ [Goldblatt & Zahnle, 2011].  During earlier geological times, approximately 2.5
billion years ago, the solar flux was only 80% of its current value.  The ocean surface flux balance still gives a warm pool temperature
limit near 26 C.  This of course assumes similar ocean and wind circulation patterns to those of today.  
Figure 43: Relative ocean evaporative cooling rates as a function of wind speed, surface temperature and
surface-air temperature difference.
The basic process of setting the Earth’s climate involves formation and dissipation of the solar heated equatorial warm pools by the
ocean gyre circulation coupled with solar heating and surface cooling at higher latitudes.  The maximum ocean surface temperature
near 30 C in the warm pools is determined by the cooling flux needed to dissipate the full tropical solar flux.  However, the area extent
of the warm pools depends on the ocean circulation properties.  The heating process that leads to the formation of the warm pools,
particularly in the Pacific Ocean is not smooth and continuous.  The interaction of the wind speed with the ocean reservoirs leads to
quasi-periodic ocean oscillations.  The direct tropical oscillation in the Pacific Ocean is the El Nino Southern Oscillation (ENSO) [Kao &
Yu, 2009].  This has a period of 3 to 7 years.  Possible atmospheric lunar tide contributions to the ENSO have recently been discussed
by [Wilson & Sidorenkov, 2013].  The warm pools are dissipated by ocean gyre circulation that transports the ocean waters to higher
latitudes.  The oceans are also heated locally by the solar flux.  Complex interactions between the ocean heating and cooling terms
within the gyre circulation lead to the formation of longer scale, 50 to 60 year quasi-periodic ocean oscillations such as the AMO and
the PDO [Dijkstra et al, 2006; Lorenzo et al, 2008].  At higher latitudes, the surface area decreases and the depth of the ocean
currents increase.  This leads to the so called re-emergence mechanism in which ocean heat is stored at the lower current depths
[Alexander et al, 2001].  

The present ocean gyre structure is established by the continental boundaries to the ocean basins and the dynamic ocean solar
heating-surface cooling balance.  Over geological time, the continents were formed by plate tectonics.  The continents today were
produced by the breakup of the super continent Pangaea starting in the Jurassic period about 175 million years BP.  Any
interpretation of atmospheric CO
2 levels over geological time has to include the effects of changes in ocean circulation and
temperatures produced by the process of plate tectonics as well as more recent Ice Age fluctuations [Zachos et al, 2001].  The
atmospheric CO
2 concentration is determined by the ocean temperature through a complex set of chemical buffer reactions [Follows et
al, 2006].  The CO
2 concentration follows the ocean temperature change.  The changes in downward LWIR flux at the ocean surface
produced by the changes in atmospheric CO
2 concentration are too small to have any effect on ocean temperatures.  

3.3.4 Solar Activity and Ocean Heating  

The connection between the increase in ocean temperature, the change in solar flux and the ocean oscillations proposed by [Akasofu,
2010] may be analyzed in more detail by comparing the HADCRUT 4 climate record with the AMO, changes in ocean heat content and
the change in solar flux derived solar sunspot index.  

The HADCRUT4 global temperature anomaly from the Hadley Climate Data Center is available from 1850 onwards [HadCRUT4,
2013].  The data set, as downloaded, is shown in Figure 44. The linear fit to the data is also shown.  The slope corresponds to an
increase in temperature of 0.47 C per century, in good agreement with Akasofu.  Next, the data is ‘detrended’ by subtracting the linear
slope.  The 5 year rolling average of this data set is then compared to the 5 year rolling average of the AMO [NOAA, 2012].  This is
shown in Figure 45.  The detailed ‘signature’ of the AMO can clearly be seen in the 5 year average of the detrended HADCRUT4
data.  This includes both the overall trend with minima near 1920 and 1980 as well as the more detailed decadal structure.  The AMO
anomaly is higher by approximately 0.2 C in the regions near 1900 and 1950.  However, this plot confirms that the basic explanation of
Akasofu is correct and that the dominant ocean oscillation is the AMO.  
Figure 44: HADCRUT4 global temperature anomaly with linear trend line added.
Figure 45: Comparison of detrended HADCRUT4 data set with the AMO.  (Thick lines are 5 year rolling
averages).

Ocean temperatures are determined by the balance between solar heating and ocean surface cooling.  The dominant ocean cooling
process is wind driven evaporation.  This is often assumed to increase linearly with wind speed [Yu, 2007, Yu et al., 2008].  The
penetration depth of the LWIR flux into the ocean is less than 100 µm, so small changes in LWIR flux, such as the 1.5 W m^-2
produced by a 100 ppm increase in atmospheric CO
2 concentration are simply overwhelmed by the surface evaporation and
fluctuations in the wind speed.  Such small changes in LWIR flux cannot couple to the bulk ocean layers below and are dissipated as
part of the surface evaporation.  The ocean surface however, is almost transparent to the solar flux.  As shown above in Figure 38,
approximately half of the solar flux is absorbed within the first meter layer of the ocean and the balance is absorbed within the first 100
m.  While the changes in solar flux produced by the variation in the sunspot index are small, they can accumulate over time in the
subsurface ocean layers.  Such solar heating effects may be investigated by using the sunspot index and comparing the estimated
solar flux with the change in ocean heat content given by [Levitus et al. 2011].

Following Clark, [2010a] using VIRGO radiometer data, an increase of 100 in the sunspot index corresponds to an increase of
approximately 1 W m^-2 in the solar flux at the top of the atmosphere (TOA).  The sunspot index from 1650 is shown in Figure 46.  The
change in the TOA flux is simply the sunspot index divided by 100.  This may be used to calculate the total cumulative flux increase in
W m^-2 since 1650.  This is shown in Figure 47.  The linear slope is 0.45 W m^-2 per year.  By coincidence, this is also close to the
linear increase per century in temperature from the HADCRUT4 data set shown in Figure 44.  Inspection of the sunspot data and the
cumulative flux show that the flux accumulation is not quite linear.  In particular, the slope from approximately 1850 to 1940 is lower
than that from 1940 to 2010.  This is consistent with the lower average sunspot index from 1850 to 1950.  Linear fits to these shorter
time periods are shown in Figure 48.  From 1855 to 1933 the slope was 0.4 W m^-2 yr^-1.  From 1933 to 2009 the slope was 0.74 W
m^-2 yr^-1.  The start and end dates were selected to include complete solar cycles from minimum to minimum.  This suggests that the
single linear increase in temperature proposed by Akasofu should be modified to include two separate slopes with a split near the
middle of the 20th century.  
Figure 46:  Sunspot index from 1650.  An index increase of 100 corresponds approximately to an increase
of 1 W m^-2 in the solar flux.
Figure 47: Cumulative increase in solar flux from Figure 46.
Figure 48: Cumulative in solar flux from 1855 to 1933 and from 1933 to 2009 determined separately.
Based on this result the climate analysis process may be reversed. The two linear temperature slopes may be added to the 5 year
rolling average of the AMO to recreate the 5 year rolling average of the HADCRUT4 data set.  This is illustrated in Figure 49.  The
upper (magenta) line labeled Lin1 is the 5 year rolling average of the AMO with the linear coefficients from Figure 48 used directly as
adjusting the linear temperature coefficients to 0.003 and 0.0077 C/yr with the date split at 1950.  This is shown as Lin2
Figure 49: 5 year average Hadcrut4 average synthesized using the 5 year AMO average and two linear
warming trends.

The 24 hour average surface heat flux input and resulting average temperature change for the 0 to 700 m ocean depth from 1955 to
2010 based on linear fits to the data are summarized in Figure 50.  The data are shown for the individual ocean basins and for the
world and hemispheric ocean summaries.  This is from Table S2 of Levitus et al. [2011].  The world average ocean heating flux for 0 to
700 m depth was 0.27 W m^-2 and the average temperature rise was 0.18 C.  There is significant variation between the individual
ocean basins.  The lowest heating flux and temperature increase was obtained for the S. Pacific Ocean basin, 0.14 W m^-2 and 0.09
C.  The highest was obtained for the N. Atlantic Ocean basin, 0.53 W m^-2 and 0.37 C.  However, these are average data over 700 m
that need to be modified to include the thermal distribution within the 0 to 700 m layer.  This is shown in Figure 51 (from Levitus at al.
[2011], Figure 2).  The change in heat stored in each 100 m layer is shown for the World Ocean, and the Pacific, Atlantic and Indian
Ocean basins.  Approximately 40% of the increase in World Ocean heat content is retained in the first 100 m layer.  This means that
0.11 of the 0.27 W m^-2 estimated World Ocean heating flux was coupled into the first 100 m of the oceans.  This gives a temperature
rise of 0.45 C for the first 100 m ocean layer.  This may be compared to the average World Ocean temperature data to 100 m depth
over the same time period [NOAA, 2013].  The data are shown in Figure 52 along with a linear fit to the data.  The annual slope
increase is 0.007 C yr^-1.  Over 60 years this gives a temperature increase of 0.42 C.  These data also show the change caused by
the 1997-98 El Nino event.  There is a distinct step in the temperature during this time period.  This suggests that the data should be
split into two separate data sets.  This is shown in Figure 53.  The data from 1953 to 1976 show a decreasing temperature trend of
-0.004 C yr^-1.  The data from 1977 to 2012 show an increase of 0.071 C yr^-1.  However, these are parts of the long term ocean
temperature fluctuations and care is needed in the evaluation of the short term data.  This also shows that there is no influence on
ocean heat content or temperature from the observed increase in atmospheric CO
2 concentration [Keeling, 2013].
Figure 50: Surface flux input and average 0 to 700 m temperature increases for the ocean basins from
1955 to 2010 based on ocean heat content data, from Levitus et al. [2011]
Figure 51: Linear trend and total increase of ocean basin heat content
based on the linear trend of global and individual basins as a function of
depth (0–2000 m) for 100 m thick layers, from Levitus et al [2011].
Figure 52: World ocean heat content 0 to 100 m depth, 1953 to 2012 [NOAA, 2013]
Figure 53:  World ocean heat content 0 to 100 m depth, data split at 1977
These stored heat and ocean heating terms represent small differences in the ocean flux balance between the incident solar flux and
the wind driven evaporation.  The solar heat is accumulated initially within the first 100 m layer of the ocean.  The wind driven
evaporation and the LWIR flux interactions are limited to a very thin surface layer.  The mixing processes that transport the ocean heat
to lower ocean depths are complex. These involve diffusion associated with thermal and salinity gradients and/or transport by ocean
currents.  

The increase in 24 hour average ‘clear sky’ solar flux at the ocean surface for increases in TOA flux of 0.75 W m^-2 and 0.4 W m^-2
may be estimated by scaling the data from Figure 7.  This is shown in Figure 54.  An increase of 0.75 W m^-2 in the TOA solar flux
corresponds approximately to an increase of 0.16 W m^-2 in the 24 hour average tropical solar flux at the ocean surface.  
Approximately half of this flux is coupled initially into the first meter layer of the ocean and half into the first 100 m layer.  The coupling
of 0.08 W m^-2 into the first 100 m ocean layer would produce a temperature rise of 0.6 C per century, or 0.4 C over a 60 year period.  
The heat capacity of the first few meters of the oceans is equivalent to the heat capacity of the entire atmosphere, so it is the near
surface ocean solar heating that is important in setting climate temperatures.  

While further investigation of the ocean reservoir flux balance is required, it is clear from this analysis that the increase in solar flux
derived from the increase in sunspot activity is sufficient to have a measurable effect on ocean surface temperatures.  As discussed
above, the ocean surface temperature is coupled to the weather station record through the effect of the bulk weather system air mass
temperatures on the night time convection transition temperature.  This is the temperature at which the air and surface temperatures
equalize and convection significantly slows or stops.  An increase of 100 ppm in the atmospheric CO
2 concentration can have no effect
on ocean temperatures, because the penetration depth of the LWIR flux into the oceans is only 100 µm.  The small increase in LWIR
flux is simply overwhelmed by the surface evaporation.  
Figure 54: Latitude resolved increases in 24 hour average ‘clear sky’ solar flux at the ocean surface for
increases in TOA solar flux of 0.75 and 0.4 W m^-2.

3.4 The Lower and Upper Tropospheric Reservoirs.  

The troposphere splits naturally into two independent thermal reservoirs based on their energy transfer properties [Clark, 2013a,
2013b, 2011a].  The lower thermal reservoir extends up to an altitude of approximately 2 km.  Almost all of the LWIR flux reaching the
surface from the atmosphere originates from within this reservoir.  It is heated during the day by convection and cools slowly at night
by LWIR emission.  At night, the surface acts as ‘heat pump’ that removes heat from the air at the base of this reservoir by emission
through the LWIR transmission window.  This reservoir also cools through LWIR emission at the interface between the upper and lower
tropospheric reservoirs.  However, unlike the land and ocean surfaces, this interface is not a distinct boundary.  It is the approximate
altitude where the downward LWIR emission no longer has any significant influence on the surface flux balance.  

The upper tropospheric reservoir extends from 2 km up to the tropopause.  It cools continuously by LWIR emission to space and is
heated during the day by moist convection from below.  The height of the tropopause varies with latitude and season.  Over the
tropics, when convection is driven by strong tropical thunderstorm activity, it may extend up to 18 km [Eschenbach 2010].  At high
latitudes, the tropopause height is typically near 8 km.  The US standard atmosphere sets the tropopause near 11 km with an average
lapse rate of -6.5 K km^-1 [NASA, 1976].  The corresponding tropopause temperature is 216.5 K (–56.5 C) and the pressure is near
0.2 atm.  The maximum LWIR cooling emission in the upper tropospheric reservoir occurs from water vapor in a limited altitude band
with temperatures in the 240 to 260 K range.  This emission band shifts in altitude as the surface temperature and the height of the
tropopause change.  It is typically near 5 km.  This is illustrated in Figure 58 below.  

The detailed description of the high resolution atmospheric radiative transfer calculations is complex and only a brief overview and
summary of the pertinent results will be presented here.  The results are derived from high resolution radiative transfer calculations
using a spectral resolution of 0.01 cm-1 and an altitude resolution of 100 m.  Further details are given in Clark, [2010a].

Within the atmospheric absorption bands, LWIR radiation is absorbed and emitted.  The net heating or cooling depends on the
balance between the absorption and emission terms as illustrated in Figure 55a.  The molecular collision frequency in troposphere is
larger than 109.  This means that as soon as an IR photon is absorbed, the excited molecular vibration-rotation state is quenched by
collisions and the thermal energy transferred to the local air mass.  Conversely, the emission of IR photons removes heat from the
local air mass.  The absorbed and emitted LWIR flux is coupled to the bulk thermal mass of the air in the atmosphere.  

The IR absorption bands in the atmosphere consist of thousands of overlapping lines.  Historically, detailed line by line radiative
transfer calculations were difficult and time consuming.  Instead, simplified band models were used to approximate the LWIR flux.  
These gave reasonable results for the total flux at the top and bottom of the atmosphere, but the lineshape dependence was lost
[Lacis and Oindas, 1991].  Today, the high resolution line by line computation of the LWIR flux is relatively straightforward.   The
required spectral parameters are available from the HITRAN database [Rothman et al, 2004].  This database has been compiled over
many years by various research groups operating independently of climate science.  Once the atmospheric temperature and species
profile is defined, the atmospheric LWIR flux may be reliably determined using the HITRAN data.  
The total atmospheric absorption is the sum of all of the molecular line contributions to each spectral interval.  Further details of the
HITRAN calculations are given by Rothman [2004].  The important point is that the attenuation and the molecular linewidths decrease
as the pressure, temperature and the species concentration decrease with altitude.  In particular, the water vapor concentration
decreases rapidly as the temperature decreases and the water condenses.  The radiative transfer process of absorption and emission
is gradually replaced by a transition to a free photon flux.  This is illustrated in Figure 55b.  

Figure 56 shows the cumulative downward LWIR flux reaching the surface for five different conditions of humidity, surface and air
temperature.  Over 90% of the downward LWIR flux originates from within the first 2 km layer.  Similarly, over 90% of the upward LWIR
flux from the surface is absorbed within this 2 km layer.  The spectrally resolved absorption vs. altitude for a surface/air temperature of
325/295 K at 50% relative humidity is shown in Figure 57.  For this case, 75% of the surface flux is absorbed within the first 100 m.  
Further details are given in Clark [2011a, 2010a].  The upper limit to the local LWIR flux is the blackbody emission at the local air
temperature.  In this case, all of the incident LWIR flux is absorbed within a short interaction path length and replaced by LWIR
emission from the local air volume.  
Figure 55: a) The atmospheric absorption and emission process and b) line narrowing effects.
Figure 56:  Cumulative normalized downward LWIR atmospheric flux vs. altitude, 200 to 2000 cm-1.  Most
of the flux originates from within the first 2 km air layer.
Figure 57:  Spectrally resolved absorbed flux vs. altitude.  Only the H2O and CO2 bands are shown.  
The surface temperature is 325 K, the surface air temperature is 295 K, and the RH is 50%.  75% of
the LWIR radiation from the surface is absorbed in the first 100 m.  (H
2O and CO2 only - truncated
data set, see Clark [2011a, 2010a] for further details.
The cooling of the upper thermal reservoir by LWIR emission is dominated by emission from the water bands [Feldman, 2008].  Figure
58 shows a plot of the calculated net emission vs. altitude up to 9 km for surface/air temperatures of 297/295 K, 287/285 K and
277/275 K with 50% RH and 380 ppm CO
2.  The 2 K surface-air temperature difference is representative of the ocean-air reservoir
interface.  The plot shows total net absorption in the 200 to 2000 cm-1 spectral range and the negative sign means that there is net
emission to space and therefore cooling.  The altitude resolution is 100 m.  The plot shows the net upward emission (cooling) for each
100 m layer.  The approximate contributions of H
2O and CO2 to the total emission are plotted separately.  There is a minor
discontinuity (‘spike’) in the radiative transfer model output at the transition of the lapse rate from -6.5K km^-1 to the saturated lapse
rate.  The H
2O absorption lines show a peak cooling rate of ~-1.5 W m^-2.  This is the net upward free photon LWIR emission from a
100 m layer.  It produces a cooling rate of approximately 0.1 K per hour in the middle troposphere.  The emission peak shifts to lower
altitude as the surface/air temperatures decreases, but the emission profile is similar for all cases.  This is because the peak emission
comes from an emission band in the H
2O concentration range from 10^16 to 10^17 molecules cm^-3.  The corresponding temperatures
are 240 to 260 K.  Since there is only a 2 K difference between the surface and air temperatures, the net cooling starts close to the
surface, above 100 m.  From 1 to 9 km, the total cumulative H
2O cooling rate was over 2.5 times larger than that of CO2 at all surface
temperatures.  Figure 59 shows the absorbed flux vs. altitude for a surface/air temperature of 325/295 K and RH of 90, 50 and 10 %.  
The large thermal gradient is representative of the air-land interface under full summer sun illumination.  The emission peak increases
from an altitude of approximately 6 km to 7 km as the RH increases.  The saturation altitude for the 10% RH case is at 5 km.  There is
a net absorption at altitudes below 1 km because of the higher surface temperature compared to Figure 58.  
Figure 58:  Absorbed flux vs. altitude for the surface/air temperatures of 297/295; 287/285 and 277/275 K,
50% RH, 380 ppm CO
2 and 100 m altitude resolution.  The negative flux means that there is a net emission
to space.  The approximate contributions of H
2O and CO2 to the total emission are shown separately
(truncated data set, see Clark [2011a, 2010a] for further details).
Figure 59: Absorbed flux vs. altitude for the surface/air temperature of 325/295 at 10, 50 and 90% RH, 380
ppm CO
2 and 100 m altitude resolution.  The negative flux means that there is a net emission to space.  
The approximate contributions of H
2O and CO2 to the total emission are shown separately (truncated data
set, See Clark, 2011a, 2010a for further details).

Figure 56 to 59 clearly show that the upper and lower tropospheric thermal reservoirs are decoupled.  The LWIR emission to space
occurs mainly from the upper thermal reservoir and the downward LWIR flux reaching the surface comes from the lower surface
reservoir.  Both are heated by the convective flux from the surface.  The peak convective flux occurs in the afternoon, after the peak in
the solar flux [Seidel et al, 2005].  The sensible heat and the net LWIR flux absorbed by the atmosphere are coupled to the lower
thermal reservoir before it reaches the upper reservoir.  The release of latent heat depends on the local lapse rate, the humidity and
the saturation level.  There is no steady state or equilibrium flux.  The LWIR emission to space continuously cools the upper
tropospheric reservoir.  It continues to cool through the night until it is warmed again by convection the following day.  Both the
convection and the LWIR flux are coupled to the same thermal reservoir and these energy transfer processes must be analyzed
together for the coupled system.  

The upward and downward LWIR fluxes are not equivalent because of the molecular line narrowing.  The downward flux is emitted
closer to line center and is absorbed by the broader lines below.  Upward LWIR emission from the wings of the broader lines at lower
altitudes that is not reabsorbed becomes part of the free photon flux to space.  This is illustrated above in Figure 55b.  

The whole concept of an equilibrium atmosphere in which the surface temperature is controlled by LWIR emission has no basis in
physical reality.  The energy transfer processes are dynamic, rate limited, and controlled by the Second Law of Thermodynamics.  
4.0 CLIMATE MODELING AND CLIMATE FRAUD
It must be emphasized that the International Panel for Climate Change (IPCC) is a political body, not a scientific one [McLean, 2010b;
Cheetham 2009].  It was formed in 1988 with the purpose of assessing “the scientific, technical and socioeconomic information
relevant for the understanding of the risk of human-induced climate change.”  Its main goal is based on the a priori assumption of
“human-induced climate change” – there was never an attempt to evaluate the scientific evidence of the cause of climate change.  The
IPCC has published four major reports, the first, second, third assessment reports, FAR (1990), SAR (1995), TAR (2001) and AR4
(2007), the fourth in the series.  It is in the process of releasing AR5, the fifth report.  While the reports may contain a useful
compendium of scientific references, material that does not conform to global warming dogma has usually been omitted.  Authors and
editors have been selected based on their willingness to find global warming whether it exists or not.  The primary focus of these
reports has been on the use of modeling ‘scenarios’ to predict future global warming using invalid computer models.  There are no
accepted software performance requirements or independent validation data sets that have been applied to the climate change
simulations.  The dominant role of ocean oscillations in climate change is generally ignored.  As discussed in detail above, radiative
forcing is a simplification algorithm that has been enshrined as dogma to ‘prove’ global warming.  The radiative forcing constants that
figure so prominently in the IPCC reports are nothing more than empirical pseudoscience.  The IPCC reports should not be cited as
scientific references.  Every ‘scientific’ publication based on radiative forcing should be clearly labeled ‘Does Not Apply to Planet
Earth’.  

The content of AR5 should be compared to NIPCC Report Climate Change Reconsidered II: Physical Science (CCR-II) [NIPCC, 2013]
and the Energy and Environment Special Issue Mechanisms of Climate Change and the AGW Concept: a critical review [Rörsch &
Ziegler, 2013].  This comparison will make it clear that AR5 should be rejected as fraudulent.  

4.1 Climate Simulation

Two basic types of computer model have been used in climate simulation.  The first is the radiative forcing model that was introduced
in its present form by Manabe and Wetherald in 1967.  The second is the general circulation model (GCM) which is an attempt to
simulate the Earth’s climate from first principles using fluid dynamics and energy transfer.  However, some kind of climate equilibrium
and radiative forcing assumptions are still incorporated in the GCMs.  As first implemented, radiative forcing was an honest attempt
to simulate atmospheric radiative transfer with limited data and very limited computer capabilities.  The basic assumptions were clearly
stated by Manabe and Wetherald [1967].  These assumptions however, were ‘lost’ to later workers, who modified and used the
computer codes with little understanding of the underlying energy transfer physics.  When the climate record is substituted for the
surface temperature the boundary is crossed from invalid simplification to scientific fraud.  This approach is climate astrology, not
climate science.  

There are at least three basic issues with the GCMs.  The first is that the complexities of the climate energy transfer physics have to
be simplified to enable any kind of simulation.  Second, the resolution of the models in terms of the number of layers, grid size and grid
interactions are limited by the available computer resources.  Third, the solution of the nonlinear equations used in these models is
strongly dependent on the starting conditions.  The models have to be ‘constrained’ and ‘guided’ to a stable solution.  The errors and
uncertainties are hidden behind fancy graphics and a wall of jargon.  Figure 60 shows the typical radiative forcing approach [Huber &
Knutti, 2011].  The model is first configured with a set of empirical ‘radiative forcing constants’ to match the measured data.  The
projected increase in the atmospheric concentration of the various ‘radiative forcing agents’ is then used to estimate the future change
in ‘radiative forcing’.  This is shown in Figure 60a.  The model is then run to make estimates of future changes in such parameters as
‘surface temperature’ and ocean heat content.  The physical reality of the surface energy transfer is ignored.  The model averaging
removes the thermal gradients that are needed to dissipate the heat, so the Second Law of Thermodynamics is set aside.  As
discussed above, the penetration depth of the LWIR flux into the oceans is less than 100 µm and the role of the wind speed is
overlooked.  Somehow this LWIR flux mysteriously finds its way into the oceans, to 700 m depth.  The models are incapable of
reproducing the ocean oscillations.  This can be clearly seen in Figure 60b and 60c.  The dust bowl drought in the 1930’s, the climate
change that resulted from the major El Nino event in 1978, and the recent 15 year  ‘pause’ in climate warming are indicated by the red
circles.  Something is clearly wrong with the surface energy transfer physics in this model.  The model is configured to produce global
warming to match the ‘predictions’ of the failed radiative forcing models.  Agreement between models is still the criteria for success in
these modeling ‘experiments’.  Physical reality is not allowed to intrude.  The ‘climate sensitivity constant’ is still the yardstick of a
successful model.  Such models have no predictive capability.

Figure 61 shows the comparison between IPCC model output and measured surface temperatures.  (This is a repeat of Figure 1).  
The colored bands in indicate the comparison of various IPCC model projections with the observed climate temperatures [Cheetham,
2013c].  Figure 62 shows a similar comparison between the model predictions and tropospheric temperature data from balloons and
satellites.   In both cases the models overestimate the real temperatures and by any reasonable criteria, the model predictions have
failed.  These models have never been validated or independently audited and performance requirements have never been
established.  The IPCC climate simulation process is little more than a closed group of climate theologians ‘tuning’ their divine models
for their best estimate of the global warming apocalypse.  The computer description of GIGO – garbage in, gospel out most definitely
applies.  

4.1.1 Model Validation

In the first quarter of the 20 th century, there was a major debate over the interpretation of quantum mechanics.  This was
conveniently summarized by Werner Heisenberg [1925]:

In any physical theory one must distinguish the concepts and quantities that are physically observable from those which are not.  The
former must of necessity play a role in theory.  The later can be modified or abandoned without impairment.

The ‘equlibrium average surface temperatures’ calculated by many of the climate models are not measurable climate variables.  
Similarly, the main drivers of the Earth’s climate, the ocean oscillations and small changes in the solar flux are not even included in the
climate simulations.  The models were created for one purpose: to create carbon dioxide induced global warming whether or not it was
observed in the climate system.  

The paradox now facing the climate modeling community is that when the models are properly validated, global warming will
disappear.  The temperature record is quite clear: the Earth stopped warming 15 years ago and there is little expectation of any
further warming for several decades.  In fact, the sun may decide to provide the Earth with another Little Ice Age.  The coincidence
between the warm phases of the ocean cycles, an active sun and the increase in atmospheric carbon dioxide concentration has
ended.  This is shown in Figure 63 [Akasofu, 2010].  
It is also interesting to note that the concern in the 1970’s was global cooing, not
warming, based on the cooling phase of the ocean oscillation.  The creation of warming and cooling from the same climate record is
illustrated in Figure 64.  This is an adaptation of Figure 63.
Figure 60: Representative climate ‘scenario’ modeling.  The arrows indicate real climate trends that are
not predicted by the models.
Figure 61:  Comparison of IPCC simulations from various assessment reports (colored bands) with the
climate record (black data points).  The models consistently overestimate the climate trends.
Figure 62: Comparison between tropical mid troposphere temperatures from satellites and balloons with
75 CIMP-5 rdp8.5 model simulations, from Spencer [2013].
Figure 63: Temperature recovery from the Little Ice Age (LIA), upward IPCC projections from ocean warm
phase and possible return to a new LIA with a ‘quiet’ sun.

4.2 Climate Fraud

In November of 2009, and again in November 2011, a large archive of e mails and other files from the Climate Research Unit of the
University of East Anglia Climate was released on the Internet.  A third round was released, 3/13/2013.  This archive has revealed to
many people outside of the close knit climate community that there had been an ongoing fraud for many years to promote the global
warming agenda and prevent the publication of material that did not support the prevailing global warming dogma.  The peer review
process in climate science had collapsed and been replaced by climate cronyism.  Climate science had become detached from its
foundation in physical science and degenerated into a quasi religious cult.  Belief in global warming was a prerequisite for funding in
climate science.  The release of this climate archive became known as ‘Climategate’.  The information provided has been analyzed in
detail by several authors [Monckton, 2009; Montford 2010; Mosher & Fuller, 2010].  The following two samples are e-mails from the
archive (bold emphasis added):

From: Kevin Trenberth trenbert@xxxxxxxxx.xxx
To: Michael Mann mann@xxxxxxxxx.xxx
Subject: Re: BBC U-turn on climate
Date: Mon, 12 Oct 2009 08:57:37 -0600
Cc: Stephen H Schneider <shs@xxxxxxxxx.xxx>, Myles Allen <allen@xxxxxxxxx.xxx>, peter stott <peter.stott@xxxxxxxxx.xxx>, "Philip D.
Jones" <p.jones@xxxxxxxxx.xxx>, Benjamin Santer <santer1@xxxxxxxxx.xxx>, Tom Wigley <wigley@xxxxxxxxx.xxx>, Thomas R Karl
<Thomas.R.Karl@xxxxxxxxx.xxx>, Gavin Schmidt <gschmidt@xxxxxxxxx.xxx>, James Hansen <jhansen@xxxxxxxxx.xxx>, Michael
Oppenheimer omichael@xxxxxxxxx.xxx

Hi all

Well I have my own article on where the heck is global warming? We are asking that here in Boulder where we have broken records
the past two days for the coldest days on record. We had 4 inches of snow. The high the last 2 days was below 30F and the normal is
69F, and it smashed the previous records for these days by 10F. The low was about 18F and also a record low, well below the previous
record low. This is January weather (see the Rockies baseball playoff game was canceled on saturday and then played last night in
below freezing weather). Trenberth, K. E., 2009: An imperative for climate change planning: tracking Earth's global energy. Current
Opinion in Environmental Sustainability, 1, 19-27, oi:10.1016/j.cosust.2009.06.001. [1][PDF] (A PDF of the published version can be
obtained from the author.)
The fact is that we can't account for the lack of warming at the moment and it is a travesty that we
can't.
The CERES data published in the August BAMS 09 supplement on 2008 how there should be even more warming: but the data
are surely wrong. Our observing system is inadequate. That said there is a LOT of nonsense about the PDO. People like CPC are
tracking PDO on a monthly basis but it is highly correlated with ENSO. Most of what they are seeing is the change in ENSO not real
PDO. It surely isn't decadal. The PDO is already reversing with the switch to El Nino. The PDO index became positive in September for
first time since Sept 2007. see
[2]http://www.cpc.ncep.noaa.gov/products/GODAS/ocean_briefing_gif/global_ocean_monitoring_current.ppt
Kevin

Michael Mann wrote:
extremely disappointing to see something like this appear on BBC. its particularly odd, since climate is usually Richard Black's beat at
BBC (and he does a great job). From what I can tell, this guy was formerly a weather person at the Met Office. We may do something
about this on Real Climate, but meanwhile it might be appropriate for the Met Office to have a say about this, I might ask Richard Black
what's up here?
mike

The release of the Climategate archive provided the incentive to look much more closely at the workings of the IPCC and the climate
data on which the IPCC reports were based.  This has revealed a pattern of systematic fraud and distortion.  Some of these include
‘Glaciergate’, and ‘Amazongate’ [McLean 2010a; ICSC 2010; Eschenbach, 2010b]. The first involved unfounded claims of melting of the
Himalayan glaciers and related disasters that were based on magazine articles that had never been peer reviewed.  This is contrary to
IPCC claims that they used only reference peer reviewed articles.  The second involved unsubstantiated claims of droughts in the
Amazon basin.  More recently, it has been revealed that many of the IPCC reports were written by unqualified reviewers with strong
links to the Word Wildlife Fund [LaFramboise, 2011]

The IPCC modelers have also published numerous fraudulent claims linking hurricanes to global warming.  This has been addressed
by William Gray [2010]:

Society, not understanding the physics of climate change, has unfortunately fallen for and accepted the climate doom scenarios of the
climate modelers erroneous simulations, ambitious politicians, and environmentalists who have axes they want to grind under the cover
of an exaggerated warming threat.
The IPCC reports should be discontinued. These reports are not free of political control. They cannot be objective – and they have
grossly exaggerated the CO2 threat to society.
An independent investigation needs to be conducted of the US research agencies, such as NSF, NASA, DOE and NOAA as to why
they have been totally one-sided in supporting pro-AGW studies at the total exclusion of support for research which questions the
AGW hypothesis. This is not science but advocacy. Eisenhower’s warning on the perils of government sponsored science being taken
over by a class of special interest elitists is coming true – to the detriment of our society and to the very great detriment of American
science.

Various scientific societies, including the Royal Society, the American Physical Society and the American Chemical Society have
published strong statements supporting global warming.  These are based on little more than the IPCC reports and reflect the vested
interests of the influential members of these societies that wrote and supported these reports.  The late Professor Hal Lewis, a very
senior and respected scientist at the University of Santa Barbara resigned from APS because of its position on global warming.  His
letter of resignation reads in part [Lewis, 2011]:

It is of course, the global warming scam, with the (literally) trillions of dollars driving it, that has corrupted so many scientists, and has
carried APS before it like a rogue wave. It is the greatest and most successful pseudoscientific fraud I have seen in my long life as a
physicist. Anyone who has the faintest doubt that this is so should force himself to read the ClimateGate documents, which lay it bare.
(Montford's book organizes the facts very well.) I don't believe that any real physicist, nay scientist, can read that stuff without revulsion.
I would almost make that revulsion a definition of the word scientist.

So what has the APS, as an organization, done in the face of this challenge? It has accepted the corruption as the norm, and gone
along with it.

In the interim the ClimateGate scandal broke into the news, and the machinations of the principal alarmists were revealed to the world.
It was a fraud on a scale I have never seen, and I lack the words to describe its enormity. Effect on the APS position: none. None at all.
This is not science; other forces are at work.

The same comments may be applied to ACS, the National Academy of Sciences, the Royal Society and many other Scientific Societies.  
5.0 CONCLUSIONS
In Section 1.5, four basic questions were posed related to climate change.  Based on the discussion presented above they may be
answered as follows:

1) How does the Second Law of Thermodynamics apply to the energy transfer processes that occur at the Earth’s surface and to the
so called ‘greenhouse effect’?

Answer: The Second Law of Thermodynamics requires that there must be a thermal gradient to dissipate the heat from the surface.  
The Earth’s climate and climate change cannot be explained unless the time dependences of these thermal gradients are explicitly
addressed.  There is no such thing as an ‘average climate equilibrium state’.  The greenhouse effect has to be explained in terms of
rate limited heat transfer between a set of coupled thermal reservoirs.

2) Has the 1.5 W m^-2 increase in downward LWIR flux from a 100 ppm increase in atmospheric CO
2 concentration produced any
measurable effect on the Earth’s climate?’  

Answer: No.  When the LWIR flux increase is properly incorporated into the time dependent surface flux balance it can have no
measurable effect on the Earth’s climate.  There is no ‘CO
2 signature’ in the climate record.

3) How are the basic physics of the surface energy transfer and the greenhouse effect incorporated into the climate simulation models
used by UN International Panel on Climate Change (IPCC)?

Answer: They are completely ignored.  The IPCC climate models are based on nothing more than empirical pseudoscience.  In
particular, the Second Law of Thermodynamics has been ‘lost’.  The increase in downward LWIR flux from so called ‘greenhouse
gases’ is empirically converted to a surface temperature using a completely fraudulent set of ‘radiative forcing constants’.

4) How have these models been validated and what software quality controls have been applied?

Answer:  The models have never been validated and no software quality controls have been applied.  
6.0 POINTS FOR FURTHER DISCUSSION

1)        There is no such thing as an ‘Equilibrium Earth’ or ‘Average Equilibrium Climate’

2)        The First Law of Thermodynamics requires an overall planetary energy balance for climate stability.  It does not require an
       exact flux balance.  

3)        The flux equilibrium arguments used in radiative forcing are invalid.

4)        A planet’s climate system has a large thermal mass.  Heat is stored and released in response to changes in the solar flux.
      Temperature changes require the dynamic, or time dependent transfer of heat between coupled thermal reservoirs.  

5)        Climate change is determined by the Second Law of Thermodynamics, not the First.

6)        The Earth’s atmosphere acts as an open cycle heat engine.  There are two basic hot reservoirs, the land and the oceans that
       have very different thermal properties.  The cold reservoir is the troposphere above 2 km.  The transfer fluid is moist air.  

7)        The hot reservoirs are heated by the time dependent solar flux.  The cold reservoir cools to space continuously by long wave
       infrared (LWIR) emission to space.  The heat from the hot reservoirs is transported to the cold reservoir directly or indirectly by
       moist convection through the lower troposphere.  Some LWIR flux also escapes to space directly through the LWIR
       transmission window.  

8)        Convection is a mass transport process.  Ascent through the atmosphere requires that the air mass perform work to overcome
       the Earth’s gravitational potential.  As the air rises, it cools and water condenses.  Moist convection sets the lapse rate, or
       temperature profile of the troposphere.  

9)        The infrared active molecules in the atmosphere also absorb and re-emit LWIR flux.  However, the rate of heat transfer by
       convection is generally much faster than LWIR radiative transfer.

10)        The downward LWIR flux from the atmosphere balances most of the upward LWIR flux from the surface.  However, this does
         not control the surface temperature.  

11)        Almost all of the downward LWIR flux reaching the surface originates from within the first 2 km layer of the atmosphere.    

12)        During the day, the troposphere is heated by convection.  The surface heat transfer rate is determined by the thermal
        gradient(s) between the surface and the air above.  At night, when the surface and air reach the same temperature,
        convection stops and the surface cools mainly by LWIR emission through the atmospheric transmission window.  The lower
        troposphere then acts as a ‘thermal blanket’ that slows the nighttime cooling.  

13)        In order to ascend the 5 km from the surface to the cold reservoir, the air expands cools by approximately 33 K.  This is the
        basis of the so called ‘greenhouse effect temperature’.  

14)        The convection is also coupled to the rotation or angular momentum of the Earth.  This establishes the three convection cells,
        Hadley, Ferrell and Polar, in each hemisphere and the Earth’s basic weather patterns.  Half of the solar flux reaching the
        surface is incident within the ±30° latitude bands.  Tropical convection within the Hadley Cell structure produces the trade
        winds. The trade winds in turn drive the large scale ocean gyres that transport and re-circulate warm ocean water over very
        long distances.

15)        The principal cooling process for the oceans is wind driven evaporation.  Subtle interactions between the ocean currents and
         the wind speed produce the ocean surface temperature oscillations within the ocean gyre structure.  These include the El
         Nino Southern Oscillation, (ENSO), Pacific Decadal Oscillation (PDO) and the Atlantic Multi-decadal Oscillation (AMO).  These
         are the real sources of the observed climate change.  

16)        The penetration depth of the atmospheric LWIR flux into the ocean surface is approximately 100 micron.  Here it is coupled to
         the surface evaporation.  The solar flux may penetrate to depths of 100 m.  This means that small changes in LWIR flux such
        as those from a 100 ppm increase in atmospheric CO2 concentration cannot heat the oceans.  The climate change attributed
        to CO
2 came from changes in ocean surface temperatures related to the ocean oscillations.  

17)        Small changes in the solar flux accumulate in the ocean gyre circulation system and cause long term climate change.  This is
        the cause of the longer term climate cycles such as the Ice Ages and the Maunder Minimum.  

18)        Given the decrease in sunspot activity observed in the current solar cycle, that there will be global cooling instead of warming.
        The extent of the cooling will depend on the number of sunspots over the upcoming solar cycles.  

19)        The radiative forcing argument that is used to justify global warming is based on the invalid concept of flux equilibrium in an
         infra-red atmosphere.  An exact flux balance is imposed between the average incoming solar flux and the outgoing LWIR flux.
        The surface is assumed to be a blackbody surface with no heat capacity.  These assumptions lead to a very elegant set of flux
        equations that have no connection whatsoever to the real Planet Earth.  

20)        Using Stefan’s Law the increase in LWIR flux from 100 ppm of CO
2 can only produce an increase in ‘equilibrium surface
        temperature’ of 0.3 K to 288.3 K.  Using the long term climate record, it was determined empirically that the real increase had
        to be 1 C.  The ‘proof’ was based on correlation, not energy transfer.  

21)        A ‘climate sensitivity constant’ was created using the climate record.  It was decreed that the 1.5 W m^-2 increase in downward
        LWIR flux had produced a 1 C rise in ‘surface temperature’.  A 1 W m^-2 increase in downward LWIR flux from any other
       ‘greenhouse gas’ would therefore produce an increase in ‘equilibrium surface temperature’ of 1/1.5 = 2/3 C.  The flux equations
        were suitably adjusted using ‘water vapor feedback’ to amplify the heating effect and produce the desired 1 C temperature
        increase.  

22)        Using the ‘climate sensitivity constant’ derived from CO
2, a set of ‘radiative forcing constants’ has been created for other so
        called greenhouse gases and aerosols.  This allows the increase in surface temperature from any increase in greenhouse
        gases to be determined.  All of this is pure pseudoscience that has no basis in the physics of the surface energy transfer.  

23)        All of the obsolete scientific papers that used radiative forcing to create global warming need to be labeled ‘Does Not Apply to
        Planet Earth’.  

24)        The climate or weather temperature is not the surface temperature, but the meteorological surface air temperature (MSAT)
         measured in a ventilated enclosure placed at eye level 1.5 to 2 m above ground.  It is simply impossible for a 1.5 W m^-2
         increase in LWIR flux at the surface to have any measurable effect on the temperatures measured inside the MSAT
         enclosure.  There can be no CO
2 induced ‘global warming’ signature in the climate record.  

25)        The minimum MSAT is usually representative of the bulk air temperature of the local weather systems as they pass through.  
        Many of these weather systems form over the oceans where they are strongly influenced by ocean surface temperatures.  It is
        the change in these ocean surface temperatures that is the real source of climate change.  

26)        The climate record used as a reference for comparison to computer climate models is not the average of the weather station
        MSAT data.  The record has been ‘adjusted’ or ‘homogenized’ to account for weather station bias and site changes.  A uniform
        temperature grid has been created for convenient comparison to lower resolution models.  The homogenization process has
        been used to introduce a fraudulent artificial warming bias in the temperature data.   

27)        The observed increase in atmospheric CO
2 concentration has had no effect on climate trends including temperatures, sea
        level, polar ice, hurricanes and tornadoes or rainfall.

28)        There is no evidence of any acceleration in sea level rise above 2 mm per year in tide gauge data. In fact sea levels may be
        decreasing instead of increasing.  The IPCC modeling predictions of 5 mm per year rates are based on invalid models.  

29)        There is no evidence in the recent climate record of any ‘extreme weather events’ that may be attributed to an increase in the
        atmospheric CO
2 concentration.   

30)        Global warming is based on nothing more than the a-priori belief in carbon dioxide induced climate change.  It began as
        speculation in the middle of the nineteenth century and became a rather dubious scientific hypothesis.  Instead of being
        superseded by a new, dynamic climate hypothesis, it has become enshrined as dogma.  Global warming has been separated
        from physical science and made into a quasi religious cult.  We are told to ‘believe in global warming’.  

31)        The computer models used to simulate global warming have never been formally validated and are ‘hard wired’ to produce
        global warming whether it exists or not.  There has been no serious attempt to compare the computer predictions against the
        measured climate record.  The results of one invalid model are compared to those from another.  The primary performance
        yardstick has been conformance to the expected ‘climate sensitivity’ to CO2.  This is a classic example of ‘garbage in, gospel
        out’.

32)        The International Panel for Climate Change (IPCC) is a political body, not a scientific one.  It was formed in 1988 with the
         purpose of assessing “the scientific, technical and socioeconomic information relevant for the understanding of the risk of
         human-induced climate change.”  Its main goal is based on the assumption of “human-induced climate change” – there
         was never an attempt to evaluate the scientific evidence of the cause of climate change.  

33)        The IPCC has published four major reports, the first, second third assessment reports, FAR (1990), SAR (1995), TAR (2001)
        and AR4 (2007), the fourth in the series.  A fifth report, AR5 is now in the release cycle.  While the reports may contain a
        useful compendium of scientific references, material that does not conform to global warming dogma has usually been
        omitted.  Authors and editors have been selected based on their willingness to find global warming whether it exists or not.
       The primary focus of these reports has been on the use of modeling ‘scenarios’ to predict future global warming using invalid
       computer models.  

34)        The IPCC reports should not be cited as scientific references.

35)        The global warming scare has been a lucrative source of funding for many research groups and has spawned a huge
        secondary industry of global warming ‘analysis’ etc.  The UN IPCC reports are used without question to analyze the social and
        economic impacts of a completely fictional problem.  

36)        In November of 2009, and again in November 2011, a large archive of e mails and other files from the Climate Research Unit
        of the University of East Anglia Climate was released on the Internet.  This revealed to many people outside of the close knit
        climate community that there had been an ongoing fraud for many years to promote the global warming agenda and prevent
        the publication of material that did not support the prevailing global warming dogma.  The release of this climate archive
        became known as ‘Climategate’.  It shows a pattern of egregious scientific misconduct.  (A third round of ‘Climategate’ e mails
        was released 3/13/2013)

37)        A pattern of systematic fraud and distortion by the IPCC has emerged.  This includes ‘Glaciergate’, and ‘Amazongate’.  The
        first involved unfounded claims of melting of the Himalayan glaciers. The second involved unsubstantiated claims of droughts
        in the Amazon basin.  More recently, it has been revealed that many of the IPCC ‘science’ reports were written by unqualified
        reviewers with strong links to the Word Wildlife Fund.

38)        The need for tax subsidized utility scale alternative energy was created using the global warming scare.  The sun does not
         shine at night and the wind is not reliable.  Electricity cannot be stored on a utility scale.  The conventional power grid must
         still have the capacity to meet peak consumer demand.  Even worse, wind power must have ‘spinning reserve’ to turn on when
          the wind stops blowing, or when the wind blows too hard.  

39)        The use of advanced recovery techniques has produced a large increase in the availability of fossil fuel, particularly natural
         gas.  There is no shortage of fossil fuel.

40)        The increase in observed atmospheric CO
2 concentration is beneficial because it enhances plant growth.  This will be
        advantageous if the climate cools in response to the observed reduction in solar cycle sunspot activity.  

41)        The increase in observed atmospheric CO
2 concentration may cause a slight decrease in ocean pH.  ‘Ocean Acidification’ is
         not going to be a problem.  It is just another environmental 'scare'.

42)        The use of global warming to justify policies in areas such as ‘sustainability’ and ‘green chemistry’ is not justified.  
ACKNOWLEDGEMENT
This work was performed as independent research by the author.  It was not supported by any grant awards and none of the work was
conducted as a part of employment duties for any employer.  The views expressed are those of the author.  
REFERENCES
Abdussamatov, H., 2013, ‘Grand minimum of the total solar irradiance leads to the little ice age’, http://scienceandpublicpolicy.
org/images/stories/papers/originals/grand_minimum.pdf

Akasofu, S-I, Natural Science 2(11) 1211-1224 (2010), ‘On the recovery from the Little Ice Age’
Alexander, M. A.; M. S. Timlin, and J. D. Scott,
Progress in Oceanography 49 41-61 (2001), ‘Winter to winter recurrence of sea surface
temperature, salinity and mixed layer depth anomalies’
Alley R. B., et al, (51 authors), IPCC, Summary for Policymakers, Climate Change 2007: The Physical Science Basis. Contribution of
Working Group I to the Fourth Assessment, eds: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B. Tignor, M.
and Miller, H. L.,
Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA., 2007
Ambler, D., Extreme weather, extreme claims, SPPI, 2010
http://scienceandpublicpolicy.org/originals/extreme_weather_extreme_claims.html
ASTM, 2012, G173-3, Solar reference spectra AM1.5, http://rredc.nrel.gov/solar/spectra/am1.5/
Benjamin, M., Meteorology, NOAA History Series, NOAA Library 2006
Billo, E. J.;
Excel for Scientists and Engineers, J. Wiley & Sons, Hoboken, NJ, USA, 2007
Cheetham, A., 2013a, Ocean Oscillations,  
http://www.appinsys.com/GlobalWarming/PDO_AMO.htm
Cheetham, A., 2013b, Hansen’s revisions,
http://www.appinsys.com/GlobalWarming/Hansen_GlobalTemp.htm
Cheetham, A., 2013c, Global Temperature Change Projections – Fail
http://www.appinsys.com/GlobalWarming/IPCC_AR5_Fail.htm
Cheetham, A., 2009 A history of the global warming scare, SPPI,
http://scienceandpublicpolicy.org/reprint/history_of_global_warming_scare.html?Itemid=0
Clark, R. Energy and Environment 24(3, 4) 319-340 (2013) ‘A dynamic coupled thermal reservoir approach to atmospheric energy
transfer Part I: Concepts’
Clark, R.
Energy and Environment 24(3, 4) 341-359 (2013) ‘A dynamic coupled thermal reservoir approach to atmospheric energy
transfer Part II: Applications’
Clark, R., 2011a,
The dynamic greenhouse effect and the climate averaging paradox, Ventura Photonics Monograph, VPM 001,
Thousand Oaks, CA, Amazon, 2011.
http://www.amazon.com/Dynamic-Greenhouse-Climate-Averaging-Paradox/dp/1466359188/ref=sr_1_1?
s=books&ie=UTF8&qid=1318571038&sr=1-1
Clark, R., 2011b, ‘There is no carbon dioxide induced global warming and there can be no sea level rise above the present long term
trend’ (pdf attachment to comment)
http://www.regulations.gov/#!documentDetail;D=FWS-R8-ES-2010-0070-0127
Clark, R., 2010a, Energy and Environment 21(4) 171-200 (2010), ‘A null hypothesis for CO2’
Clark, R., 2010b, ‘CA Climate Change is Caused by the Pacific Decadal Oscillation, Not by Carbon Dioxide’, SPPI Sept 16 th 2010,
http:
//scienceandpublicpolicy.org/originals/pacific_decadal.html
COAPS, 2013, Florida State University, Global tropical cyclone activity http://www.coaps.fsu.edu/~maue/tropical/
Cryosphere Today 2013, Polar Research, University of Illinois at Urbana-Champaign http://arctic.atmos.uiuc.edu/cryosphere/  
D’Aleo, J. ‘Progressive Enhancement of Global Temperature Trends’, Science and Public Policy Institute, July 2010.
http:
//scienceandpublicpolicy.org/originals/progressive_enhancement.html
D’Aleo, J., Effects of AMO and PDO on temperatures, Intellicast, May 2008.  http://www.intellicast.com/Community/Content.aspx?a=127]
Dijkstra, H. A.; L. te Raa, M. Schmeits and J. Gerrits, Ocean Dynamics DOI 10.1007/s102360005-0043-0, (2006) ‘On the physics of
the Atlantic multidecadal oscillation’
Donlon, C. J.; Minnet, P.J., Gentemann, C. Nightingale, T.J., Barton, I.J.Ward, B. and Murray, M.J.2002,
J. Climate, 15 353-369 (2002)
‘Towards improved validation of satellite sea surface skin temperature measurements for climate research’
Donnelly J. P.; S. S. Bryant, J. Butler, J. Dowling, L. Fan, N. Hausmann, P. Newby, B. Shuman, J. Stern, K. Westover and T. Webb III,
GSA Bulletin 113(6) 714 –727 (2001), ‘700 yr Sedimentary Record of Intense Hurricane Landfalls in Southern New England’
Eschenbach, W., 2013,
http://wattsupwiththat.com/2013/03/06/dr-roy-spencers-sea-surface-temperatures/
Eschenbach, W., Energy and Environment 21(4) 201-200 (2010), ‘The thunderstorm thermostat hypothesis’
Eschenbach, W., 2010b, Out in the Ama-Zone, SPPI 4/7/2010
http://scienceandpublicpolicy.org/reprint/out_in_the_ama_zone.html
Fairman, J. G., Jr., U. S. Nair, S. A. Christopher, and T. Mölg, J. Geophys. Res., 116, D03110, (2011) ‘Land use change impacts on
regional climate over Kilimanjaro’
Feldman D.R., Liou K.N., Shia R.L. and Yung Y.L.,
J. Geophys Res. 113 D1118 pp1-14 (2008), ‘On the information content of the
thermal IR cooling rate profile from satellite instrument measurements’
Follows, M. J.; T. Ito and S. Dutkiewicz,
Ocean Modeling 12 290-301 (2006) ‘On the solution of the carbonate chemistry system in
ocean biogeochemistry models’
Fourier, B. J. B.;
Mem. R. Sci. Inst., 7 527-604 (1827), ‘Memoire sur les temperatures du globe terrestre et des espaces planetaires’
Gentemann C. L.; F. J. Wentz, C. A. Mears and D. K. Smith,
J. Geophys Res. 109 C04029 pp1-9 (2004), ‘In situ validation of Tropical
Rainfall Measuring Mission microwave sea surface temperatures’
Gilbert, W.C.,
Energy and Environment 21(4) 263-276 (2010) ‘The thermodynamic relationship between surface temperature and
water vapor concentration in the troposphere’
Goldblatt, C. and K. J. Zahnle,
Climate of the Past 7 203-220 (2011) ‘Clouds and the faint young sun paradox’
Goulden, M. L., 2012, Ameriflux Data, Grasslands Site Data
http://ameriflux.ornl.gov/fullsiteinfo.php?sid=193
Gray, W. M., 2011 ‘Gross errors in the IPCC-AR4 report regarding past and future changes in global tropical cyclone activity - (A
Nobel disgrace)’
http://scienceandpublicpolicy.org/originals/gross_errors_ipcc_ar4.html
Gray, V. R., ‘South Pacific sea level: a reassessment’, SSPI, Aug 16, 2010
http://scienceandpublicpolicy.org/south_pacific.html
HadCRUT4, 2013, UK Met. Office, Hadley Center, Observations datasets, http://www.metoffice.gov.
uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.4.2.0.0.monthly_ns_avg.txt
Hagos, S. M. and K. H. Cook, Journal of Climate 21(15) 3797-3814 (2008), ‘Ocean warming and late-twentieth-century Sahel drought
and recovery’
Hale, G. M. and Querry, M. R.,
Applied Optics, 12(3) 555-563 (1973), ‘Optical constants of water in the 200 nm to 200 µm region’
Hansen, J. et al, (45 authors),
J. Geophys. Research 110 D18104 1-45 (2005) ‘Efficacy of climate forcings’ http://pubs.giss.nasa.
gov/abs/ha01110v.html  
Hansen J.; R. Ruedy, J. Glascoe, and M. Sato, ‘GISS analysis of surface temperature change’
http://pubs.giss.nasa.
gov/docs/1999/1999_Hansen_etal.pdf
Helliker, B. R. and S. L. Richter, Nature 454 511-514 (2008), ‘Subtropical to boreal convergence of tree leaf temperatures’
Houston J. R. and R.G. Dean,
Journal of Coastal Research 27(3) 409-417(2011), ‘Sea-level acceleration based on U.S. tide gauges
and extensions of previous global-gauge analyses’
http://www.jcronline.org/doi/abs/10.2112/JCOASTRES-D-10-00157.1
Huber, M. and R. Knutti, Nature Geoscience Letters DOI: 10.1038/NGEO1327 pp. 1-6, (2011), ‘Anthropogenic and natural warming
inferred from changes in the Earth’s energy balance’
Idso, C. and R. Ferguson, 2009, ‘Effects of Ocean Acidification on Marine Ecosystems’
http://scienceandpublicpolicy.
org/images/stories/papers/originals/acidification.pdf
IEEE, IEEE Std 738-1993, IEEE Standard for calculating the current temperature relationship of bare overhead conductors
Jelbring, H.,
Energy and Environment 14(2)351-356 (2003), ‘The greenhouse effect as a function of atmospheric mass’
Jones, P. D., New, M., Parker, D. E., Martin, S. and Rigor, I. G.,
Rev. Geophysics 37(2) 173-199 (1999), ‘Surface air temperature and
its changes over the past 150 years’
Kao, H-Y. and J-Y Yu,
Journal of Climate 22(3) 615-632 (2009), ‘Contrasting Eastern-Pacific and Central-Pacific Types of ENSO’
Keeling, 2013, Scripps CO2 Program,
http://scrippsco2.ucsd.edu
Keeling, C. D.; S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann and H. A. Meijer, ‘Atmospheric CO2 and 13CO2
exchange with the terrestrial biosphere and oceans from 1978 to 2000: observations and carbon cycle implications’, pages 83-113, in
"
A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems", editors, Ehleringer, J.R., T. E. Cerling, M. D.
Dearing, Springer Verlag, New York, 2005.
Khandekar, M. L.
Energy and Environment 24(3, 4) 537-550 (2013) ‘Are extreme weather events on the rise?’
Lacis, A. A. & V. Oindas,
J. Geographical Res. 96(D5) 9027-9063 (1991), ‘A description of the correlated k distributing method for
modeling non gray gaseous absorption, thermal emission and multiple scattering in vertically inhomogenous atmospheres’
Laframboise, D. 2011, The delinquent teenager who was mistaken for the world’s top climate expert, Amazon,
http:
//nofrakkingconsensus.com/
S. Levitus et al, (11 Authors), Geophysical Research Letters, 39 L10603 1-5 (plus auxiliary material) (2011) ‘World ocean heat content
and thermosteric sea level change (0-2000 m), 1955-2010’
Lewis, H. (2011),
http://www.thegwpf.org/hal-lewis-my-resignation-from-the-american-physical-society/
Lindsay, R. W.; J. Zhang, A. Schweiger, M. Steele and H. Stern, Journal of Climate 22(1) 165-176 (2009), ‘Arctic sea ice retreat in
2007 follows thinning trend’
Loehle, C. and J. H. McCulloch,
Energy and Environment 19(1) 93-100 (2008), ‘Correction to: A 2000 year global temperature
reconstruction based on non-tree ring proxies’
Lorenzo E. D. et al (12 Authors),
Geophys Res. Letts 35, L08607 1-6, (2008) ‘North Pacific gyre oscillation links ocean and ecosystem
change’
McCabe, G. J.; J. L. Betancourt, S. T. Gray, M. A. Palecki & H. G. Hidalgo,
Quaternary International 188 31-40 (2008) , ‘Associations of
multi-decadal sea-surface temperature variability with US drought’
Manabe, S. and Wetherald, R. T.,
J. Atmos. Sci., 24 241-249 (1967), ‘Thermal equilibrium of the atmosphere with a given distribution
of relative humidity’
Maunder Minimum 2013,
http://en.wikipedia.org/wiki/Maunder_Minimum
McLean, J., 2010a, GlacierGate highlights IPCC's flaws, SPPI 2010,
http://scienceandpublicpolicy.org/originals/glacier_gate.html
McLean, J., 2010b, ‘We have been conned – an independent review of the IPCC’, SPPI 2010 http://scienceandpublicpolicy.
org/originals/we_have_been_conned.html
Meehl, G. A.; C. Covey, T. Delworth, M. Latif, B. McAvaney, J. F. B. Mitchell, R. J. Stouffer, Bulletin of the American Meteorological
Society
, 88(9) 1383-1394 (2007), ‘The WCRP CMIP3 multimodel dataset’
Mengelkamp, H-T.; F. Beyrich, G. Heinemann, F. Ament, J. Bange, F. Berger, J. Bosenberg, T. Foken, B. Hennemuth, C. Heret, S.
Huneke, Kp-P. Johnsen, M. Kerschgens, W. Kohsiek, J-P Leps, C. Liebethal, H. Lohse, M. Mauder, W. Meijninger, S. Raasch, C.
Simmer, T, Spiess, A. Tettebrand, J. Uhlenbrock and P. Zittel,
Bull. Amer. Met. Soc. 87(6) 775-786 (2006), ‘Evaporation over a
heterogeneous land surface’
Milankovitch, M.,
Théorie Mathématique des Phénomenes Thermiques Produits par la Radiation Solaire, Gauthier-Villars, Paris
(1920);
Canon of Insolation and the Ice-Age Problem, Royal Serbian Acad. Sp. Pub. 132 (1941), Israel Program Sci. Trans.,
Jerusalem (1969)
Monckton, C., SPPI, 2009: ‘Climategate: caught green-handed’,
http://scienceandpublicpolicy.org/monckton/climategate.html
Montford, A. W., The Hockey Stick Illusion, Stacey International, 2010
Morner, N-A, 2013, Energy and Environment 24(3, 4) 509-534 (2013), ‘Sea level changes, past records and future expectations’
Morner, N-A, 2011 http://www.sasnet.lu.se/sites/default/files/u4/mornermumbai.pdf
Morner, N-A., 21st Century Science and Technology, pp.7-17 (Fall 2010), ‘There is no alarming sea level rise’
Mosher, S. and T. W. Fuller, Climategate: The Crutape Letters, Create Space, 2010.
NASA Gistemp 2013
http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.D.txt
NASA Sunspot Cycle, 2013 http://solarscience.msfc.nasa.gov/SunspotCycle.shtml
NASA, U. S. Standard Atmosphere, NASA-TM-X-74335, 1976
NIPCC 2013, Idso, C. D.; R. M. Carter and S. F. Singer,
Climate Change Reconsidered II: Physical Science (CCR-II), http://www.
nipccreport.org/reports/ccr2a/ccr2physicalscience.html
NOAA, 2012, Earth System Research Laboratory, Atlantic Multidecadal Oscillation, Long Series, http://www.esrl.noaa.
gov/psd/data/correlation/amon.us.long.data
NOAA, 2011, Rainfall Data, http://climvis.ncdc.noaa.gov/cgi-bin/cag3/hr-display3.pl
NOAA, 2013 National Oceanographic Data Center, basin time series, http://www.nodc.noaa.
gov/OC5/3M_HEAT_CONTENT/basin_avt_data.html
NOAA, 2013 Tornado Count
http://www1.ncdc.noaa.gov/pub/data/cmb/images/tornado/clim/EF3-EF5.png
Oerlemans, J., Science 308 675-677 (2005), ‘Extracting a climate signal from 169 glacier records’
Oke T. R., WMO/TD-No. 1250, World Meteorological Association, 2006, ‘
Initial guidance to obtain representative meteorological
observations at urban sites

Opel, T.; D. Fritzshe and H. Meyer,
Clim. Past 9 2379-2389 (2013), ‘Eurasian Arctiv climate over the past millennium as recorded in
the Akademii Nauk ice core (Severnaya Zemlya)
Ramanathan, V. and J. A. Coakley,
Rev. Geophysics and Space Physics 16(4) 465-489 (1978), ‘Climate modeling through radiative
convective models’
REMSS, 2011,
http://www.remss.com/msu/msu_data_description.html
Rörsch, A. and P. A. Ziegler Energy and Environment, 24 #3 to 4 June 2013, ‘Mechanisms of Climate Change and the AGW Concept:
a critical review’
http://multi-science.metapress.com/content/p216726u0442/?p=3790bfc929874b10abc46594801ea62f&pi=1
Rosema, A.; S. Foppes and J. van der Woerd, Energy and Environment 24(3, 4) 381-396 (2013), ‘Metostat planetary temperature
trend 1982-2006.’
Rothman, L. S. et al, (30 authors),
J. Quant. Spectrosc. Rad. Trans. 96 139-204 (2005), ‘The HITRAN 2004 molecular spectroscopic
database’
Sahlee, E.; A-S Smedman, A. Rutgersson, and H. Ulf,
Journal of Climate 21(22) 5925-5941 (2008), ‘Influence of a New Turbulence
Regime on the Global Air–Sea Heat Fluxes’
Seidel, D. J.; M. Free and J. Wang,
J. Geophys Res. 110 D090102 1-13 (2005), ‘Diurnal cycle of upper air temperature estimated from
radiosondes’
Spencer, R. W., 2013, STILL Epic Fail: 73 Climate Models vs. Measurements, Running 5-Year Means June, 2013.  
http://www.
drroyspencer.com/2013/06/still-epic-fail-73-climate-models-vs-measurements-running-5-year-means/
Svensmark, H., Evidence of nearby supernovae affecting life on Earth, MNRAS, 2012, ftp://ftp2.space.dtu.
dk/pub/Svensmark/MNRAS_Svensmark2012.pdf
Taylor, F. W.,
Elementary Climate Physics, Oxford University Press, Oxford, 2006, chapter 7
Tsonis, A. A.,
An Introduction to Atmospheric Thermodynamics, 2nd edn., Cambridge University Press, Cambridge, UK, 2007
Varadi, F., B. Runnegar, B. and Ghil, M.,
Astrophys. J., 562 620-630 (2003), ‘Successive refinements in long term integrations of
planetary orbits’
VIRGO, SOHO Satellite VIRO Radiometer Data
http://www.pmodwrc.ch/pmod.php?topic=tsi/virgo/proj_space_virgo#VIRGO_Radiometry
Wilson, I. R. G. and N. S. Sidorenkov, The Open Atmospheric Science Journal, 7 51-76 (2013), ‘Long term lunar atmospheric tides in
the S. Hemisphere’
Yu, L. (2012),
http://oaflux.whoi.edu/images2_flux/EV_50a.jpg
Yu, L., J. Climate, 20(21) 5376-5390 (2007), ‘Global variations in oceanic evaporation (1958-2005): The role of the changing wind
speed’
Yu, L., Jin, X. and Weller R. A., OAFlux Project Technical Report (OA-2008-01) Jan 2008, ‘
Multidecade Global Flux Datasets from the
Objectively Analyzed Air-sea Fluxes (OAFlux) Project: Latent and Sensible Heat Fluxes, Ocean Evaporation, and Related Surface
Meteorological Variables
’ (Available at: http://oaflux.whoi.edu/publications.html
Zachos, J.; M. Pagani, L. Sloan, E. Thomas and K. Billups, Science 292 686-689 (2001), ‘Trends, rhythms and aberrations in the
global climate, 65 Ma to present’
Zeng, X., Zhao, M., Dickinson, R.E. and He, Y.,
J. Geophys Res. 104 1525-1536 (1999), ‘A multiyear hourly sea surface skin
temperature data set derived from the TOGA TAO bulk temperature and wind speed over the tropical Pacific’
Figure 64:  The creation of the 1970’s global cooling and the 1980s global warming scares from the same
climate record.  It is all based on a misinterpretation of the ocean cycles.