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The potency of carbon dioxide (CO2) as a greenhouse gas

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According to this study the commonly applied radiative forcing (RF) value of 3.7 Wm-2 for CO2 concentration of 560 ppm includes water feedback. The same value without water feedback is 2.16 Wm-2 which is 41.6 % smaller. Spectral analyses show that the contribution of CO2 in the greenhouse (GH) phenomenon is about 11 % and water’s strength in the present climate in comparison to CO2 is 15.2. The author has analyzed the value of the climate sensitivity (CS) and the climate sensitivity parameter () using three different calculation bases. These methods include energy balance calculations, infrared radiation absorption in the atmosphere, and the changes in outgoing longwave radiation at the top of the atmosphere. According to the analyzed results, the equilibrium CS (ECS) is at maximum 0.6 °C and the best estimate of  is 0.268 K/(Wm-2 ) without any feedback mechanisms. The latest warming scenarios of Intergovernmental Panel on Climate Change (IPCC) for different CO2 concentrations until the year 2100 include the same feedbacks as the 2011 warming i.e. only water feedback. The ECS value of 3.0 °C would mean that other feedback mechanisms should be stronger than water feedback. So far there is no evidence about these mechanisms, even though 40 % of the change from 280 ppm to 560 ppm has already happened. The relative humidity trends since 1948 show descending development which gives no basis for using positive water feedback in any warming calculations. Cloudiness changes could explain the recent stagnation in global warming.
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http://www.seipub.org/des Development in Earth Science Volume 2, 2014
20
The Potency of Carbon Dioxide (CO2) as a
Greenhouse Gas
Antero Ollila
Department of Civil and Environmental Engineering (Emer.), School of Engineering, Aalto University, Espoo,
Finland, Otakaari 1, Box 11000, 00076 AALTO, Finland
E-mail: aveollila@yahoo.com
Abstract
According to this study the commonly applied radiative
forcing (RF) value of 3.7 Wm-2 for CO2 concentration of 560
ppm includes water feedback. The same value without water
feedback is 2.16 Wm-2 which is 41.6 % smaller. Spectral
analyses show that the contribution of CO2 in the
greenhouse (GH) phenomenon is about 11 % and water’s
strength in the present climate in comparison to CO2 is 15.2.
The author has analyzed the value of the climate sensitivity
(CS) and the climate sensitivity parameter () using three
different calculation bases. These methods include energy
balance calculations, infrared radiation absorption in the
atmosphere, and the changes in outgoing longwave
radiation at the top of the atmosphere. According to the
analyzed results, the equilibrium CS (ECS) is at maximum
0.6 °C and the best estimate of is 0.268 K/(Wm-2) without
any feedback mechanisms. The latest warming scenarios of
Intergovernmental Panel on Climate Change (IPCC) for
different CO2 concentrations until the year 2100 include the
same feedbacks as the 2011 warming i.e. only water
feedback. The ECS value of 3.0 °C would mean that other
feedback mechanisms should be stronger than water
feedback. So far there is no evidence about these
mechanisms, even though 40 % of the change from 280 ppm
to 560 ppm has already happened. The relative humidity
trends since 1948 show descending development which
gives no basis for using positive water feedback in any
warming calculations. Cloudiness changes could explain the
recent stagnation in global warming.
Keywords
Strength of CO2; Climate Change; Global Warming; Climate
Sensitivity; Climate Sensitivity Parameter
Introduction
The CS is calculated based on the doubling of the CO2
concentration from the pre-industrial concentration
from 280 ppm to 560 ppm. Before calculating these
future effects, climate science should find a good
understanding of the effect of CO2 on the present
greenhouse (GH) phenomenon and on the warming
starting 1750. It should be alarming that there is not
even a broad consensus on these figures. The values of
the CO2 effect on GH phenomenon vary in scientific
articles from 9% (Miskolczi and Mlynczak, 2004) to
about 33% (Pierrehumbert, 2011).
The primary effect of increased CO2 concentration
occurs in the lower part of the atmosphere, where GH
gases have absorbed 95% of the infrared radiation (IR)
emitted by the earth's surface up to 2 km high
(Ohmura, 1997; Ollila, 2012a). The secondary effect is
that the outgoing longwave radiation (OLR) at the top
of the atmosphere (TOA) is reduced, and IPCC names
this OLR change (IPCC, 2007a) the radiative forcing
(RF). Because the Earth must reach the radiative
energy balance, the third effect is the increase in the
surface temperature until the OLR is the same as the
incoming shortwave (SW) radiation. The changes are
so small that they can be analyzed only by
computational methods.
The global mean surface temperature change can be
calculated multiplying the RF change at TOA by
climate sensitivity parameter () according to IPCC
(2007a). The value and accuracy of is critical in
calculating the global warming value.
The objectives of this paper are to show that the
potency of CO2 as a GH gas is much lower than used
by IPCC, that the CS is much lower than used by IPCC
and finally that the global warming value is much
lower than calculated by IPCC. The calculation
methods are the same as used by IPCC, but the basic
differences are the water content of the atmosphere
and finally the relative humidity (RH) trends of the
atmosphere.
The Strengths of Greenhouse Gases
IPCC (2013) claims that “The contribution of water
vapor to the natural greenhouse effect relative to that
of carbon dioxide (CO2) depends on the accounting
method, but can be considered to be approximately
Development in Earth Science Volume 2, 2014 http://www.seipub.org/des
21
two to three times greater.” There are no references to
any scientific papers supporting this claim. IPCC has
referred in its 2007 report (IPCC, 2007a) to the article
of Kiehl & Trenberth (1997). The author (Ollila, 2013a)
has shown that using the same US Standard
Atmosphere 76 with 12% less water he can get the
same results: H2O 60% and CO2 26% (60/26 = 2.3). This
atmosphere contains only 50 % of the real average
global atmosphere (AGA), see Table 1. The author has
concluded that the number “three times greater” could
refer to the article of Pierrehumbert (2011), which says
that CO2 absorption is not close to saturation and its
contribution in the tropical climate is about 33%.
Pierrehumbert shows no detailed calculations only
the claim above.
TABLE 1. WATER PROFILES OF U.S. STANDARD ATMOSPHERE 1976 (USST
76) AND AVERAGE GLOBAL ATMOSPHERE (AGA). THE ACRONYM VMR IS
VOLUME MIXING RATIO.
H2O
USST 76
AGA
USST 76
AGA
alt, km
vmr
vmr
g/m3
g/m3
0
7.750*10-3
1.656*10-2
5.857
12.037
1
6.070*10-3
1.246*10-2
4.171
8.264
2
4.630*10-3
9.539*10-3
2.885
5.756
3
3.180*10-3
5.705*10-3
1.792
3.122
4
2.160*10-3
3.234*10-3
1.096
1.607
5
1.400*10-3
2.226*10-3
0.640
0.999
6
9.250*10-4
1.412*10-3
0.379
0.571
7
5.720*10-4
8.685*10-4
0.210
0.316
8
3.670*10-4
5.078*10-4
0.120
0.166
9
1.580*10-4
2.814*10-5
0.046
0.082
10
7.000*10-5
1.433*10-4
0.018
0.037
11
3.610*10-5
5.475*10-5
0.008
0.013
Precipitated water in cm’s (prcm)
1.43
2.60
I have calculated the AGA profiles (Ollila, 2012a) by
combining the values of three climate zones published
by Ellingson et al. (1991) These profiles are available
also in the Spectral Calculator program (Gats, 2014)
which I have used in the spectral analyses of this
paper.
The AGA’s surface temperature is 15 °C, and the
concentrations of the anthropogenic GH gases as
measured in 2005: CO2 393 ppm, CH4 1.774 ppm, and
N2O 0.319 ppm) as reported by IPCC (2007b).
I have used one dimensional (1D) Polar Summer
atmosphere values, modifying the profiles where
needed. The temperature and pressure profiles of
AGA are the same as Polar Summer values, but GH
gas profiles have been adjusted to the 2005 values
using scale factors.
In Fig.1, the absorption graphs of major GH gases are
depicted up to 25 µm, because thereafter water can
totally absorb all the IR radiation (Ollila, 2012a). The
shaded green area gives a good image of the
magnitude of CO2 in the GH phenomenon. The total
contributions of GH gases are up to 120 km calculated
by the Spectral Calculator (Gats, 2014) and by the
Hitran database of Harvard-Smithsonian Center for
Astrophysics (2014): H2O 82.2%, CO2 11.0%, O3 5.2%,
and CH4 0.8 % and N2O 0.8%.
FIG 1. THE ABSORPTION BAND GRAPHS OF GH GASES IN THE
ATMOSPHERE IN THE AGA CONDITIONS 2005. THE GREEN-
SHADED AREAS INDICATE A TOTAL GH IMPACT OF CO2
CONCENTRATION OF 379 PPM.
The curve of each GH gas in Fig.1 is calculated when it
is the only gas in the AGA conditions. The real
combined absorption of GH gases is not a simple
summary of the band areas of single GH gases. The
real total absorption can be calculated only when all
the GH gases are present at the same time. The total
absorption is depicted by the purple line. Therefore for
example, the total absorption curve does not follow
the green line of CO2 absorption curve, because it is
essentially caused by the total absorption of H2O and
CO2 present at the same time in the atmosphere.
Some important conclusions can be drawn from the
absorption graphs. The GH gases have different effects
on the total absorption when compared to the
absorption caused by water. Ozone pushes the total
absorption curve effectively upward, but CH4 and N2O
only minimally increase the total absorption in
comparison to water absorption. The radiation flux
transmitted into space in the clear sky conditions is
83.2 Wm-2, and it is the only potential area for
increased absorption caused by higher GH gas
concentrations. In all-sky conditions, clouds absorb
about 66% of the transmitted flux, and thus about 28.3
Wm-2 - that is, only about 7 % of the emitted LW
radiation - escapes directly into space.
Because the effects of GH gases are very nonlinear, the
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above contributions are not the actual strengths of GH
gases for the changes around the present
concentrations. The author has calculated the relative
strengths of GH gases (Ollila, 2013a) based on the
increased IR absorptions from 1990 to 2005. The most
important GH gas is water and its strength in respect
to CO2 impact (value = 1) is 15.2. The same values of
other GH gases are: CH4 0.144, N2O 0.168, and O3
0.629. Fig. 1 shows that any impact of GH gases that
could actually increase warming must do it in the
wavelength zone from 7.5 µ m to 14 µ m in the so-
called atmospheric window.
FIG. 2. THE TOTAL ABSORTION BAND GRAPHS FOR
INCREASED CO2 CONCENTRATIONS IN THE AGA 2012
CONDITIONS IN THE TROPOSPHERE.
In Fig. 2 are depicted absorption graphs for various
CO2 concentrations from 10 µm to 14 µm. In this
wavelength zone 85-90% of absorption caused by
increased CO2 concentrations occurs. Even by eye, it is
easy to estimate that the absorption area increase from
379 ppm to 560 ppm is almost the same as the area
from 280 ppm to 379 ppm. The warming effect is
directly proportional to the total area caused by the
GH gases between the x-axis and the total emission
curve of the GH gases.
The Climate Sensitivity According to the
Earth’s Energy Balance
The radiative forcing (RF change) at TOA has a linear
relationship to the global mean surface temperature
change Ts if two equilibrium climate states are
assumed:
Ts = RF (1)
IPCC states (2007a) that is a climate sensitivity
parameter, which is nearly invariant parameter having
a typical value about 0.5 K/(Wm-2). This value is based
on rather old calculations (Ramanathan et al., 1985)
before 1985, at which time narrow-band models were
applied and not the accurate line-by-line methods of
today. IPCC no longer keeps the climate sensitivity
parameter as a nearly invariant parameter like in AR4.
In AR5 its value varies in broad limits. The value of
the climate sensitivity parameter is 0.811 K/Wm-2 for
the CO2 forcing of 3.7 Wm.2 and the warming of 3.0 °C.
The author has used three different methods in
calculating the CS and values. The simplest analysis
of CS and is based on the total energy balance of the
Earth by equalizing the absorbed and emitted
radiation fluxes
SC(1-α) * (¶r2) = sT4 * (4¶ r2), (2)
Where SC is solar constant (1368 W/m2), α is the total
albedo of the Earth, s is Stefan-Bolzmann constant
(5.6704*10-8), and T is the temperature (K). The
temperature value of T can be solved:
T = (SC * (1 α) (4s))0.25 (3)
Where T is the temperature corresponding the emitted
longwave (LW) flux in the atmosphere. The average
albedo (Ollila, 2013b; Ollila, 2014) is (104.2 Wm-2)/(342
Wm-2) = 0.30468. Using this albedo value, the
temperature T would be -18.7 °C (=254.5 K). According
to the Planck’s equation, this temperature corresponds
to LW radiation flux 237.8 Wm-2, which is the actual
average emitted LW radiation flux of the Earth. The
most common reported global mean surface
temperature is 1C, which means that the greenhouse
effect would be 33.7 K. The surface temperature Ts can
be calculated by adding 33.7 K into T
Ts = T +33.7 (4)
The term SC(1-α)/4 is the same as the net radiative
forcing (RF) and therefore Eq. (2) can be written in the
form RF = sT4. When this equation is derived, it will
be d(RF)/dT = 4sT3 = 4(RF)/T. The ratio d(RF)/dT can
be inverted transforming it into :
dT/(d(RF)) = = T/(4RF)= T/(SC(1-α)) (5)
In the all-sky conditions the total albedo flux 104.2
Wm-2 is the sum of the cloud reflected flux of 67.8 Wm-
2, the surface reflected flux of 22.7 Wm-2 and the air
reflected flux of 13.7 Wm-2. These values as well as the
following three pairs of cloudiness and albedo values
for clear, all-sky and cloudy sky conditions are based
on energy balance analysis of global radiative fluxes
(Ollila, 2013b; Ollila, 2014; Zhang et al., 2004; Bodas-
Salcedo et al., 2008; Loeb et al., 2009): (0%,
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53/342=0.155), (66%, 104.2/342=0.305), and (100%,
120/342=0.351). The second-order polynomial can be
fitted through these points and the result is
α = 0.15497 + 0.0028623 * CL – 0.000009 * CL2 (6)
where α is albedo and CL is cloudiness-%.
The differences between sky conditions are due to the
degrees of cloudiness in different skies. This effect is
generally called cloud forcing (CF). Normally the CF
has been calculated at TOA as the difference between
clear sky and all-sky conditions. Using the values of
Ollila (2013b), the albedo flux change 53 - 104.2 = -51.2
Wm-2. The outgoing LW radiation decrease is the
difference between OLR fluxes, which is 259 - 237.8 =
21.2 Wm-2. According to the most common definition,
the CF is the sum of these two fluxes, which in this
case is -30.0 W/m2, a cooling effect. This value is close
to the values used in other studies (Ohring and Clapp,
1980; Harrison et al., 1990; Ardanuy et al., 1991; Zhang
et al., 2004; Raschke et al., 2005; Loeb et al., 2009;
Stephens et al., 2012), which vary between -17.0 and -
28 W/m2 average being -23.4 W/m2.
Spencer and Braswell (2011) have created a more
complicated calculation method for cloud forcing by
separating the effects and feedback of the clouds. Their
final conclusion is that clouds have a negative impact
on the surface temperature. Dressler (2010) has
analysed the TOA radiation budget in response to
short-term climate variations from the years 2000 to
2010, and his results showed positive feedback of the
clouds. So the issue of cloud forcing still remains
unclear without common acceptance and
understanding but the big majority of CF studies show
the cooling effect of cloudiness increase.
The specification of the CF can be criticized, because it
is based on the instant radiation flux changes after a
cloudiness change and it does not recognize the
dynamic delays of the climate system. Ollila (2014) has
concluded that the real CF is based on the SW
radiation changes only, because the Earth has yet to
reach the radiation flux balance according to the 1st
law of thermodynamics, which means that the OLR
flux must be the same as the net solar input flux. This
approach would increase the CF values by about 46 %
(Ollila, 2014b).
The equation (6) does not mean that only the total
cloudiness changes can cause albedo changes. The
changes of other reflected fluxes (by surface and air
and by different cloud types) have their effects on the
total albedo but the numerical effects are not known.
The equation (6) is well established because it is based
on the measured fluxes in the global scale.
When the changes in radiative forcing are known, the
equations (2), (3), and (4) can be used in calculating T,
ECS and values for the variations of RF and α. The
climate sensitivity parameter calculated according
equation (5) is 0.268 K/(Wm-2).
FIG. 3. THE SURFACE TEMPERATURE AS A FUNCTION OF
CLOUDINESS ACCORDING TO THE ENERGY BALANCE
EQUATIONS (2)…(6).
The surface temperature is very sensitive for the
cloudiness and albedo changes of the Earth, as one can
see in Fig. 3.
Climate Sensitivity According to Absorption
and Longwave Radiation Changes
The author has also calculated the CS and values
applying two simulation tools available in the
network, namely Modtran (Berk et al., 2013) and the
Spectral Calculator (Gats, 2014). The results are
collected in Table 2. The all-sky conditions have been
calculated by combining the clear and cloudy sky
values (Bellouin et al., 2003; Ollila, 2013b):
(1-CL/100) * Fclear + (CL/100) * Fcloudy = Fall-sky (7)
Where F is a radiation flux of a sky in question and CL
is a cloudiness-%. Also temperatures of different skies
are combined according to this equation.
The average global atmosphere’s (AGA) surface
temperature is 15 °C, and the concentrations of the
anthropogenic GH gases measured in 2005 (AGA
2005) or in 2012 (AGA 2012) have been used. The GH
gas concentrations (2005/2012) are: CO2 (379/393 ppm),
CH4 (1.774/1.866 ppm), and N2O (0.319/0.324 ppm), as
reported by IPCC (2007c, 2013). The graphs in Fig. 1
and Fig. 2 are based on the AGA 2005 gas
concentrations and Fig. 4 graphs are based on the
AGA 2012 conditions. The parameters and choices
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24
applied in Modtran simulations, are depicted in Table
2.
TABLE 2. PARAMETERS AND CHOICES APPLIED IN MODTRAN
SIMULATIONS
Parameter
Value
Tropospheric ozone
28 ppb
Stratospheric ozone scale
1
Water vapor scale
1.2384
Ground temperature offset
1 °C (T= 288.2 K)
Holding fixed
Water vapor pressure
Locality
Subarctic summer
Clear sky
No clouds or rain
Cloudy sky
Cumulus cloud base
0.66 km, top 2.7 km
Altitude
70 km
The CS and calculations are carried out to an altitude
of 70 km. In these calculations, a few iterations are
needed in both calculation tools in order to find the
surface temperature, which compensates the increased
absorption caused by a CO2 increase to 560 ppm,
bringing the OLR flux exactly to the same the OLR
flux caused by a CO2 concentration of 280 ppm.
Because both the OLR change and the temperature
change are calculated at the same time, the value can
be easily calculated. The cloudy sky values are
calculated using the Modtran simulations, which show
about 30 % lower OLR change than the clear sky
simulations. This relationship has been used in
estimating the cloudy sky values of Spectral Calculator
simulations. IPCC’s report AR5 (2013) summarizes
that according to several studies, the overall reduction
of RF values in cloudy sky conditions is in average 25
% lower than the clear sky values. The results of the
simulations carried out by Modtran and Spectral
Calculator are summarized in Table 3.
TABLE 3. CLIMATE SENSITIVITY AND CLIMATE SENSITIVTY PARAMETER
CALCULATED IN AVERAGE GLOBAL ATMOSPHERE (AGA) AT TOA
Sky
ECS, °C
OLR, Wm-2
, K/(Wm-2)
MODTRAN
Clear
0.69
2.29
0.301
Cloudy
0.53
1.6
0.331
All-sky
0.584
1.834
0.319
Spectral Calculator
Clear
0.66
2.69
0.245
Cloudy
0.507
1.88
0.270
All-sky
0.559
2.16
0.259
The change of CO2 concentration from 280 ppm to 560
ppm would increase the total absorption of shortwave
(SW) radiation by 0.40 Wm-2 according to the 1D
model simulations. This change alone would mean an
essential warming impact, but the situation is not
straightforward, because this absorption directly
decreases the SW radiation reaching the surface.
Myhre et al. (1998) have concluded that the absorption
of solar radiation in the troposphere yields a positive
RF at the tropopause and a negative RF in the
stratosphere contributing to a net cooling effect of CO2
absorption of -0.06 Wm-2 for the concentration change
from 280 ppm to 381 ppm. On these bases the author
has not included the solar radiation absorption
changes of CO2 into his calculations. The net effect of
solar radiation absorption would slightly decrease the
RF values of CO2 according to the analyses of Myhre et
al. (1998).
The clear sky OLR change 2.69 Wm-2 calculated by
Spectral Calculator at the TOA is the sum of
transmittance flux change 1.12 Wm-2 and the radiance
flux change 1.57 Wm-2. The OLR changes and the
warming values of different CO2 concentrations are
summarized in Table 4. The global warming caused
by the CO2 concentration increase from 280 ppm to 393
ppm calculated through OLR change is 0.24 °C
without water feedback.
The logarithmic fitting gives the following equation
between RF values and CO2 concentrations in Table 4:
RF = 3.12 * ln(C/280), (8)
Where RF is the radiative forcing in Wm-2, C is the CO2
concentration in ppm.
TABLE 4. THE RADIATIVE FORCING AND WARMING VALUES OF DIFFERENT
CO2 CONCENTRATIONS (REFERENCE LEVEL 280 PPM). THE CLEAR SKY
VALUES ARE CALCULATED BY SPECTRAL CALCULATOR AND CLOUDY
SKIES BY MODTRAN
Sky
OLR, Wm-2
T, °C
CO2, 393 ppm
Clear
1.29
0.28
Cloudy
0.90
0.22
All-sky
1.03
0.24
CO2, 560 ppm
Clear
2.69
0.66
Cloudy
1.88
0.51
All-sky
2.16
0.56
CO2, 1370 ppm
Clear
6.29
1.60
Cloudy
4.39
1.23
All-sky
5.04
1.36
Using Spectral Calculator simulation, a CO2
concentration of 393 ppm gives the value 0.230 and
1,370 ppm gives the value 0.269. According to
several studies (Zhang et al., 2004; Bodas-Salcedo et
al., 2008; Loeb et al., 2009), the OLR flux varies
between 233-240 Wm2 and using Eq. (3) shows that RF
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value 233 Wm-2 gives value 0.270, and RF value 240
Wm-2 gives value 0.265. The variation of is
relatively small but is not invariant. The values
vary in totality from 0.230 to 0.319 in simulations. If
Eq. (3) is applied for OLR changes calculated by the
RF 2.16 Wm-2 of Spectral Calculator, the ECS is 0.576
°C and is 0.267. The same values using the
RF=1.834 Wm-2 of Modtran, the ECS is 0.49 °C and
is 0.267. The Modtran calculations’ results are not as
accurate and reliable as the Spectral Calculator results,
because the atmospheric conditions of Modtran cannot
be specified with the same accuracy as in Spectral
Calculator.
The author has also calculated the ECS value utilizing
the IR absorption in the clear atmosphere; this value is
0.46 °C. Some other researchers (Miskolczi and
Mlynczak, 2004) have calculated almost the same
value, namely 0.48 °C. The most reliable results and
best estimates are the values calculated by energy
balance equations: ECS = 0.576 °C and = 0.268
K/(Wm-2) with the uncertainty ranges of 0.460.6 °C
and 0.230.32 K/(Wm-2).
Some researchers have paid attention to the fact that
the temperatures simulated by General Circulation
Models (GCM) have departed from the real
temperatures since 1998. There are several new
research studies, which show lower ECS values than
those of IPCC. According to these results, the best
estimates and minimum values for ECS are: (Aldrin,
2012) 2.0 °C / 1.1°C; (Bengtson & Schwartz, 2012) 2.0
°C / 1.15 °C; (Otto et al., 2013) 2.0 °C / 1.2 °C and
(Lewis, 2012) 1.6 °C / 1.2 °C. Common features of
these studies are mathematical methods like Bayes’s
theorem to analyze the impact of CO2 based on the
measured global data of radiative forcing factors,
temperatures and ocean heat content.
These studies’ minimum values of ECS are practically
same in the range 1.1-1.2 °C. Bengtson & Schwartz
(2012) draw a conclusion that this value is the same as
the no-feedback Planck sensitivity. An interesting
point is that the ECS value of this study without any
feedback mechanisms (including the Planck sensitivity
calculation which is the same as equation (3)) is in the
range 0.559…0.584 °C, and with water feedback the
ECS according to the Plank’s equation is 1.1 °C. Is this
a coincidence? There could be a very simple
explanation. All the referred studies use the radiative
forcing value of 3.7 Wm-2 for CO2 and they do not
mention, whether or not water feedback has been used
in their analyses.
The author’s conclusion is that the researchers of these
studies have applied the RF value of 3.7 Wm-2 as in the
study of Bengtson & Schwartz (2012). If this RF value
has been calculated in the atmosphere, where is
constant relative humidity, it would mean that it
includes the positive water feedback duplicating the
warming values. The author has carried further
analyses later on.
The Analysis of IPCC’s Warming
Calculations
According to IPCC (2013) the water vapor/lapse rate,
albedo and cloud feedbacks are the principal
determinants of equilibrium radiative forcing and
these feedbacks are assessed to be positive. The water
provides the largest positive feedback, which doubles
the other forcing elements like GH gas effects.
According to IPCC the forced component of the global
mean surface temperature (GMST) trend responds to
the effective radiative forcing (ERF) trend rapidly and
almost linearly (medium confidence). Hence, an ERF
trend can be approximately converted to a forced-
response GMST trend. The air temperature follows the
GMST without essential time delays. It should be
noticed that ERF and RF values are same up to 2011
(IPCC, 2013).
According to IPCC, the amount of water in the
atmosphere is controlled mostly by the air
temperature and therefore water does not cause direct
radiative forcing but it is classified as a feedback
element. The temperature data show a warming of
0.85 °C, over the period 1880 to 2012, and the total
radiative forcing is 2.34 Wm-2 (IPCC, 2013). Because
water amount in the atmosphere follows the air
temperature, water feedback acts with short delay in
respect to the GH gas impacts. Therefore the GMST
increase of 0.85 °C must include the water feedback.
Otherwise the concept of water feedback does not
follow the mechanism specified by IPCC: RF trend can
be converted to GMST trend and water feedback
follows the air temperature/surface temperature
almost without time delay. Shine et al. (2009) have
analyzed the annual cycles of the surface temperature,
and the result is a mean time lag of 56 ± 11 days for
oceans and 29 ± 6 days for land. The radiative energy
budget follows the surface temperatures of land and
ocean.
An example about the short time lag of the sea is the
situation of the Finnish gulf. In the beginning of May,
the surface sea water temperature is about 0 °C and in
http://www.seipub.org/des Development in Earth Science Volume 2, 2014
26
the end of July it is about 20 °C. This is in line with the
time lag defined by Stine and confirms IPCC’s
statement (IPCC, 2013) that ERF and GMST trends
have no time delays thinking the time scales of the
climate change.
IPCC has not introduced any other feedback
mechanisms other than water feedback in its report
AR4 and AR5 causing the observed warming up till
the year 2011. Using the warming and radiative
forcing values of AR4, the following analysis can be
carried out. The warming of 0.76 °C according to IPCC
(2007c) happens through the mechanism that a CO2
increase of 99 ppm (an addition of 35.4% since 1750)
warms the climate first by 0.38 °C. The temperature
increases another 0.38 °C because of assumed constant
relative humidity. The total water amount increases by
2.3%, from 2.6 prcm (precipitated water in
centimeters) to 2.66 prcm. This means that the strength
of water is 15.4 in comparison to CO2, which is very
close to the value of 15.2 as calculated in the AGA 2005
conditions.
It is useful to compare the results of this study to those
reported by IPCC. IPCC (2013) has utilized the
logarithmic relationship the 3rd report introduced by
Myhre et al. (1998):
RF = 5.35 * ln(C/280), (9)
Where RF is the radiative forcing in Wm-2, C is the CO2
concentration in ppm. The RF values of CO2 in AR5
are still based on equation (9). Myhre et al. (1998)
informs that “only the direct forcing to a change in
WMGG (well mixed greenhouse gases) concentration
is considered here” in calculating RF values. There are
two other studies referred in AR4 (2007a). The RF
values of 560 ppm CO2 concentrations in these three
studies are: Myhre et. al. (1998) 3.71 Wm-2, Hansen et
al. (1998) 3.63 Wm-2, and Shi (1992) 3.98 Wm-2. IPCC
has regarded these three simplified expressions to be
reliable and one can see the RF values are very close to
each other. Only Shi specifies that he has used “fixed
relative humidity”, which means positive water
feedback. The other studies do not specify humidity
conditions. The author’s conclusion is that also Myhre
et al. and Hansen et al. have used the constant relative
humidity conditions in the atmosphere. Otherwise
Shi’s RF value for CO2 should be about twice as much
as in the other studies. The exact water content has not
been specified in any of these studies.
The RF value according to equation (8) for the CO2
concentration 560 ppm is 2.16 Wm-2 and it is 58.4 % of
the RF value of 3.7 Wm-2 according to equation (9). The
same RF value according to MODTRAN simulations is
exactly 50 % smaller. This is another evidence that
equation (9) has been calculated in the constant RH
conditions, because this RF value of CO2 is practically
100 % bigger than the value calculated without water
increase.
The author has carried out two analyses based on his
own calculations and the warming results as
published by IPCC. In the first analysis the warming
results have been depicted in Fig. 4 according to the
different calculation bases. The x-axis is CO2
concentration or the CO2 equivalent including all
anthropogenic radiative forcing elements in the case of
Representative Concentration Pathways (RCP) (IPCC,
2007d). The red graph is the warming calculated
according to equation (9) by transforming RF values
into temperatures by multiplying by =0.5. The actual
values in AR4 and AR5 would be 0.442 and 0.363
respectively for the years 2005 and 2011. The
temperature increases of this study based on the
absorption and OLR changes are very close to each
other.
The most interesting curve is the one labelled
'modified Myhre et. al' (purple dashed line), which is
the original Eq. (9), in which RF has been divided by 2
to eliminate positive water feedback and thereafter
multiplied by the newly calculated value of 0.268
K/Wm-2 to get the temperature. This curve overlaps
the two other curves calculated by the author.
FIG. 4. GLOBAL WARMING INCREASE ACCORDING TO
DIFFERENT SIMULATION AND ESTIMATION METHODS.
The latest future projections of IPCC called RCPs are
also depicted with symbols of midpoints and
whiskers. The numeric value of each RCP indicates
radiative forcing in the year 2100, and the equivalent
CO2 concentrations include the effects of GH gases.
Development in Earth Science Volume 2, 2014 http://www.seipub.org/des
27
The RCP warming values are lower than the warming
values caused by CO2 according to equation (9). The
author’s conclusion is that equation (9) includes very
probably water feedback i.e. the calculations for
finding the relationship have been carried out in the
constant relative humidity conditions.
The old ECS value of 3 °C (IPCC, 2007b), which is also
the mean value of CS in AR5 (IPCC, 2013), has been
depicted in Fig. 3. The curve fitting through three
points (280/0, 379/0.76, 560/3.0 values as ppm/°C)
produces an exponential curve T = - 0.6 + 0.635 *
(C/280)2.52. It is not possible to achieve such a high
value by CO2 warming and water feedback alone. The
studies of Myhre et al. (1998) and equation (8) of this
study show that the relationship between RF and CO2
concentration is very close to a logarithmic form.
According to the general laws of IR absorption, the
exponential relationship is not possible, and this fact is
illustrated in Fig. 3. This kind of exponential
relationship would be possible only, if the other
feedback effects of the climate change would be
positive and highly nonlinear. The ECS value of 3 °C is
a combination of several GCM models (IPCC, 2007a).
A recent study (von Storch et al., 2013) reveals that 23
common GCMs cannot simulate temperature even at a
2% confidence level since temperature stagnation
began in 1998.
The results of the second analysis have been depicted
in Fig. 5. The RF values of different RCP scenarios are
the same as reported by IPCC (IPCC, 2007d). The
graph named as “Linear warming 1750-2011” has been
calculated using the linear coefficient of 0.85 °C / 2.34
Wm-2, which is the value of 0.363. The RCP values
follow closely the same linear relationship as
calculated by the warming values of 2011 only the
RCP8.5 warming value is 0.7 °C higher.
FIG. 5. THE GLOBAL WARMING VALUES ACCORDING TO THE
ANTHROPOGENIC RADIATIVE FORCING BY IPCC.
One conclusion is that the RCP warming values
include the same feedback mechanisms as the
warming value of 2011 and so only water feedback can
be considered. The linear straight gives the warming
value of 1.4 °C for CS including the anthropogenic
warming 0.7 °C and the water feedback 0.7 °C. If the
ECS would be 3.0 °C, the other feedback mechanisms
would cause 1.6 °C increase. Of course the situation is
more complicated considering cross effects but this is a
rough estimate about the magnitudes of different
warming mechanisms.
The transient climate sensitivity is 1.75 °C (1.0 to 2.5
°C) according to IPCC (IPCC, 2013) and it is depicted
in Fig. 4 and Fig. 5. This value can be calculated using
equation (9) of Myhre et al. (1998) and the climate
sensitivity parameter 0.5 k(Wm-2) of the IPCC’s report
AR4 (IPCC, 2007a).
Conclusions
Pierrehumbert (2011) has come to a conclusion that
CO2 is not near to saturation. The total saturation has
not yet been reached, but the warming effects are
much smaller than generally believed. The reason is
that the equation of Myhre et al. includes water
feedback effect making the radiative forcing of CO2
about 100 % higher than it should be. This applies to
other GH gases as well. The evidence is based on the
almost similar results of Shi (1992) and Myhre et al.
(1998) and two analyses of this study, which are based
on the spectral analyses.
The final conclusion is that climate sensitivity and
future warming projections depend totally on the
behaviors of water in the atmosphere. If the water
content is kept constant, ECS is in the range 0.46 to
0.58 °C. If positive water feedback is applied, ECS is
about 1.1 °C, and negative water feedback can force
warming to 0 °C. The actual relative humidity (RH)
measurements since 1948 show negative trends
(NOAA, 2012) indicating strongly a negative feedback
mechanism in the climate system, Fig.6. Also studies
of tropospheric humidity have revealed descending
trends (Hoinka, 1999; Paltridge et al., 2009).
These real RH measurements show that there is no
basis for using positive water feedback in calculating
global warming.
The CS value calculations of this study can be
criticized in that they do not cover all feedback
mechanisms. On the other hand IPCC calculations can
be criticized in that there is no information about the
contributions of feedback mechanisms to the CS value
http://www.seipub.org/des Development in Earth Science Volume 2, 2014
28
of 3.0 °C. The role of the clouds in the climate change
according to IPCC (IPCC, 2013) is likely positive but
confidence is still low. Today the CO2 concentration
change from 280 ppm to 560 ppm has passed the point
of 40%. Regardless of this big change, feedback
mechanisms other than water feedback cannot be
quantified. Water feedback mechanism is likely
negative as proposed by Miskolczi (2010) and not
positive as assumed by IPCC.
FIG. 6. RELATIVE HUMIDITY TRENDS ACCORDING TO NOAA
AT DIFFERENT ALTITUDES IN THE TROPOSPHERE.
The recent CS calculations as referred to in this study
(Aldrin, 2012; Bengtson & Schwartz, 2012; Otto et al.,
2013; Lewis, 2012) use the mathematical analyses and
the real data but they do not test the possibility of
theories like “The Sun theory”. The author has carried
out a study (Ollila, 2012b) showing that the global
temperature in the period 1871-2002 has a r2 = 0.936
correlation to the sun activity changes and a r2=0.860
correlation to the CO2 concentration changes. The
mathematical analyses alone do not provide enough
evidence to conclude, if there are several potential
mechanisms available.
One conclusion is that the original Eq. (9) of Myhre et
al. (1998) is in line with the calculations of this paper if
the RF value is reduced by 41.6 % i.e. positive water
feedback is eliminated. Confusion and different results
of climate sensitivity are based on positive water
feedback used in Eq. (9) and unrealistic high impacts
of other feedback mechanisms.
The competing theory of the anthropogenic warming
theory is the so called “Sun theory”. The majority of
clouds forcing studies show that the clouds have
played an important role in fortifying the insolation
changes of the Sun. The change in cloudiness in the
range from 60% to 70% causes a temperature change
of 1.5 °C according to energy balance analysis as
depicted in Fig. 3. The dynamic analysis (Ollila 2014)
gives the value of -0.1 °C/cloudiness-% for cloudiness
sensitivity. Applying this value, the temperature
increase of 0.76 °C could be attributed to a decrease in
the total cloudiness of 7.6%. Even though clouds
remain a subject of confusion in climatology, it is clear
that climate is very sensitive to albedo changes, and
the cloudiness changes are the biggest contributors to
albedo changes.
According to IPCC (2013) the total anthropogenic
forcing increase during the last 15 years has been
about 0.3 Wm-2. Because there has been no
temperature increase, it means that the counterforce of
the same size has been affecting in the global climate.
The global cloudiness increase of 0.54% could cause
this kind of effect (Ollila, 2014) together with
decreasing sun activity. There is a sound physical
mechanism available to explain the cooling in period
1945-1980 as well as the stagnation of the temperature
since 1998.
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The author has reanalysed the warming effects of greenhouse (GH) gases utilising the latest HITRAN 2012 database and improved water continuum calculations in the spectral analysis tool. The contributions of GH gases in the GH effect in the all-sky conditions are found to be: H2O 81%, CO2 13%, O3 4%, CH4 & N2O 1%, and clouds 1%. Because the total absorption is already 93% from the maximum in the altitude of 1.6 km, which is the average global cloud base, the GH gas impacts are almost the same in the clear and all-sky conditions. The impacts of clouds are based on the normal cloudiness changes between the clear and cloudy skies. The positive impact of clouds is analysed and it is based on the warming impact of clouds during the night-time. The warming impact of CO2 is very nonlinear and it means that in the present climate the strength of H2O is 11.8 times stronger than CO2, when in the total GH effect this relationship is 6.2:1. The atmospheric Total Precipitable Water (TPW) changes during ENSO events are the essential parts of the ENSO process and they are not actually separate feedback processes. The TPW changes during the ENSO events almost double the original ENSO effects. On the other hand, during Mt. Pinatubo eruption and during the three latest solar cycles, the long-term water feedback effect cannot be found despite of rapid warming from 1980 to 2000. This empirical result confirms that the assumption of no water feedback in calculating the climate sensitivity of 0.6°C is justified. Because there is no long-term positive feedback, it explains why the IPCC model calculated temperature 1.2°C in 2015 is 44 % greater than the average 0.85ºC of the pause period since 2000.
... Ollila has analysed [19] the future warming values based on the RF values of greenhouse gases. This analysis showed that the warming values of RCP2.5, RCP4.5, and RCP6 could be calculated using the λ value of ~0.37 K/(Wm -2 ). ...
... It means a lower λ value of about 0.27 -0.3 K/(Wm -2 ). Some researchers have calculated even lower values like ~0.6°C for climate sensitivity [19,26] or 0.7°C [27]. Ollila [19] has calculated the λ value using three different methods and his results vary between 0.245 and 0.331 the most reliable value being 0.268 K/(Wm -2 ). ...
... Some researchers have calculated even lower values like ~0.6°C for climate sensitivity [19,26] or 0.7°C [27]. Ollila [19] has calculated the λ value using three different methods and his results vary between 0.245 and 0.331 the most reliable value being 0.268 K/(Wm -2 ). In this study these two most common values have been applied: 0.27 K/(Wm -2 ) and 0.5 K/(Wm -2 ). ...
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The author has developed a dynamic model (DM) to simulate the surface temperature change (∆T) caused by the eruption of Mount Pinatubo. The main objectives have been 1) to test the climate sensitivity parameter (λ) values of 0.27 K/(Wm-2) and 0.5 K/(Wm-2), 2) to test the time constants of a simple first-order dynamic model, and 3) to estimate and to test the downward longwave radiation anomaly (∆LWDN). The simulations show that the calculated ∆T of DM follows very accurately the real temperature change rate. This confirms that theoretically calculated time constants of earlier studies for the ocean (2.74 months) and for the land (1.04 months) are accurate and applicable in the dynamic analyses. The DM-predicted ∆T values are close to the measured value, if the λ-value of 0.27 K/(Wm-2) has been applied but the λ-value of 0.5 K/(Wm-2) gives ∆T values, which are about 100% too large. The main uncertainty in the Mount Pinatubo analyses is the ∆LWDN flux, because there are no direct measurements available during the eruption. The author has used the measured ERBS fluxes and has also estimated ∆LWDN flux using the apparent transmission measurements. This estimate gives the best and most consistent results in the simulation. A simple analysis shows that two earlier simulations utilising General Circulation Models (GCM) by two research groups are depending on the flux value choices as well as the measured ∆T choices. If the commonly used minimum value of-6 Wm-2 would have been used for the shortwave anomaly in the GCM Original Research Article Ollila; PSIJ, 9(4): 1-14, 2016; Article no.PSIJ.23242 2 simulations, instead of-4 Wm-2 , the ∆T values would differ from the measured ∆T values almost 100%. The main reason for this error seems be the λ-value of 0.5 K/(Wm-2).
... Usually researchers have used some other methods than the specification of CS, which requires using spectral analysis methods. Harde [9] and Ollila [7]have used the spectral analysis method, the average global atmosphere, and the specification of CS. In both studies the CS is 0.6 °C. ...
... In both studies the CS is 0.6 °C. Ollila [7] shows that this same CS value can be calculated from the energy balance of the Earth. Ollila [7]shows also what the reasons for this big gap are: 1.85 °C versus 0.6 °C. ...
... Ollila [7] shows that this same CS value can be calculated from the energy balance of the Earth. Ollila [7]shows also what the reasons for this big gap are: 1.85 °C versus 0.6 °C. The reasons are in water feedback. ...
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... Harde [21] has used spectral analysis methods and the two-layer climate model in calculating the ECS values and his result is 0.6°C. Ollila [22] has also reported the ECS value of 0.6°C by utilizing spectral analysis and no water feedback in CSP and in RF formula: ...
... It is also obvious that the climate model of IPCC [1], which is based on the sums of the radiative forcings (RF), gives about 50% too high of a value in 2015. In this study, the author has used the formula of Ollila [22] in calculating the warming impact of CO 2 . This formula does not assume the constant relative humidity but the constant absolute humidity both in the radiative forcing and in the climate sensitivity parameter calculations. ...
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