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Global Circulation Models (GCMs) Simulate the Current Temperature Only If the Shortwave Radiation Anomaly of the 2000s Has Been Omitted

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The research article of Gillett et al. was published in Nature Climate Change (NCC) in March 2021. The objective of the NCC study was to simulate human-induced forcings to warming by applying 13 CMIP6 (Coupled Model Intercomparison Project Phase 6) climate models. NCC did not accept the author's remarks as a "Matters arising" article. The purpose of this article is to detail the original three remarks and one additional remark: 1) the discrepancy between the graphs and reported numerical values, 2) the forcings of aerosols and clouds, 3) the positive water feedback, and 4) the calculation basis of the Paris agreement. The most important finding is that General Circulation Models (GCMs) used in simulations omit the significant shortwave anomaly from 2001 to 2019, which causes a temperature error of 0.3°C according to climate change physics of Gillett et al. For the year 2019, this error is 0.8°C showing the magnitude of shortwave anomaly impact. The main reason for this error turns out to be the positive water feedback generally applied in climate models. The scientific basis of the Paris climate agreement is faulty for the same reason.
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*Corresponding author: E-mail: aveollila@yahoo.com;
Current Journal of Applied Science and Technology
40(17): 45-52, 2021; Article no.CJAST.70331
ISSN: 2457-1024
(Past name:
British Journal of Applied Science & Technology,
Past
ISSN: 2231-0843,
NLM ID: 101664541)
Global Circulation Models (GCMs) Simulate the
Current Temperature Only If the Shortwave
Radiation Anomaly of the 2000s Has Been Omitted
Antero Ollila
1*
1
Department of Civil and Environmental Engineering (Emer.), School of Engineering, Aalto University,
Espoo, Otakaari 1, Box 11000, 00076 AALTO, Finland.
Author’s contribution
The sole author designed, analysed, inteprted and prepared the manuscript.
Article Information
DOI: 10.9734/CJAST/2021/v40i1731433
Editor(s):
(1) Dr. Elena Lanchares Sancho, University of Zaragoza, Spain.
(2)
Dr. Meng Ma, Mount Sinai Genomics Inc., USA.
Reviewers:
(1)
Opeyemi Salau, University of Ado – Ekiti, Nigeria.
(2)
Samuel O. Sedara, Adekunle Ajasin University, Nigeria.
(3)
Blajina Ovidiu, University Politehnica of Bucharest, Romania.
4. Miral R. Thakker, S. N. Patel Institute of Technology and Research Centre, India.
Complete Peer review History:
https://www.sdiarticle4.com/review-history/70331
Received 17 May 2021
Accepted 22 July 2021
Published 24 July 2021
ABSTRACT
The research article of Gillett et al. was published in Nature Climate Change (NCC) in March 2021.
The objective of the NCC study was to simulate human-induced forcings to warming by applying 13
CMIP6 (Coupled Model Intercomparison Project Phase 6) climate models. NCC did not accept the
author’s remarks as a “Matters arising” article. The purpose of this article is to detail the original
three remarks and one additional remark: 1) the discrepancy between the graphs and reported
numerical values, 2) the forcings of aerosols and clouds, 3) the positive water feedback, and 4) the
calculation basis of the Paris agreement. The most important finding is that General Circulation
Models (GCMs) used in simulations omit the significant shortwave anomaly from 2001 to 2019,
which causes a temperature error of 0.3°C according to climate change physics of Gillett et al. For
the year 2019, this error is 0.8°C showing the magnitude of shortwave anomaly impact. The main
reason for this error turns out to be the positive water feedback generally applied in climate models.
The scientific basis of the Paris climate agreement is faulty for the same reason.
Original Research Article
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
46
Keywords: CMIP6; climate models; human-induced warming; positive water feedback; Paris climate
agreement.
1. INTRODUCTION
The objective of this study is to analyze the
reasons for differences and errors between the
observations of Clouds and the Earth's Radiant
Energy System (CERES) radiation
measurements and global temperature
measurements in respect to the simulation
results of [1] (later Gillett). The GCMs of Gillett
simulations follow the basic climate change
science of the Intergovernmental Panel on
Climate Change (IPCC). The most important
result is the warming caused by carbon dioxide
(CO
2
). The same average results for warming
can be calculated applying the simple climate
model, which is called the IPCC model in this
study. An alternative simple climate model called
the Ollila model has been applied as a reference
in calculating temperature impacts.
The simulations of Gillett using 13 GCMs show
that anthropogenic forcings have caused
warming 0.9°C to 1.3°C of warming in the global
surface temperature in 2010-2019 relative to
1850-1900. This average warming is the same
as the observed warming of 1.1°C according to
Gillett. An analysis of the simulations by Gillett
reveal that they have totally omitted strong
positive shortwave (SW) radiation anomaly of the
2000s, which causes a temperature impact of
0.3°C to 2010-2019 and 0.8°C for the year 2019
according to climate science applied by Gillett.
2. MATERIALS AND METHODS
The material is based on the common databases
available through internet and they are referred
to the original source as they appear the first
time in the text.
The analysis method is to compare the
simulation results of Gillett to the calculation
methods and results of the IPCC as found in the
latest assessment report (AR5) [2] in the first
step. In the second step the results are
compared to the simple model of the author
(Ollila model). IPCC uses both ECS (Equilibrium
Climate Sensitivity) and TCS (Transient Climate
Sensitivity) concepts and summarizes the
differences in AR5 [2], p. 1110: “ECS determines
the eventual warming in response to stabilization
of atmospheric composition on multi-century time
scales, while TCR determines the warming
expected at a given time following any steady
increase in forcing over a 50- to 100-year time
scale.” IPCC has changed the TCS to
TCR (transient climate response). On page 1112
of AR5, IPCC states that “TCR is a more
informative indicator of future climate than ECS.”
The warming values of any Radiative Forcings
(RF) can be calculated according to the [2] as
dT = λ * RF (1)
where dT is the global surface temperature
change (K or °C) starting from the year 1750 and
λ is climate sensitivity parameter (K/Wm
-2
) or
(°C/Wm
-2
). The λ value of 0.5 K/(Wm
-2
) of the
IPCC (2013) means positive water feedback, and
it is applicable in calculating temperature
responses for scenarios up to 1370 ppm
CO
2
concentration during this century. For
example, according to equation (1), the TCS
value is 1.85C. It can be compared to the
IPCC’s official TCS value, which is between 1.0
and 2.5C, meaning an average value of 1.75C.
In Table 9.5 of AR5 [2] is the average value of
TCS/TCR of the 30 most complicated GCMs,
and the value is 1.8C.
Since it turns out that the temperature responses
of Gillett’s simulations are much greater than the
observed temperatures of the present day,
another option of equation (1) has been applied
in the Ollila model without the positive water
feedback with λ value of 0.27 K/(Wm
-2
) [3].
The RF values of anthropogenic climate drivers
in the IPCC model are based on the data of the
AR5 [2] for the period from 1750 to 2013 and
thereafter to the Annual Greenhouse Gas Index
(AGGI) data of National Oceanic and
Atmospheric Administration (NOAA) [4]. In the
Ollila model the same values are calculated for
the period from 2001 to 2019 using the equation
in the Ollila model.
RF = 3.12 * ln (C/280), (2)
where C is the CO
2
concentration in ppm [3].
Both in the IPCC model and in the OIlila model
the El Nino Southern Oscillation (ENSO)
temperature effects have been calculated from
the Oceanic Nino Index (ONI) [5]
dT = 0.1 *ONI (3)
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
47
Equation (3) has been applied with 6 months
delay [6,7].
3. RESULTS
3.1 Discrepancy between the Graphs and
Numerical Values
The reported anthropogenic forcing from Gillett is
0.9 to 1.3°C in 2010–2019 relative to 1850–1900,
meaning the average value of 1.1°C. The
graphical presentation of the included data files
and Fig. 1b of Gillett shows that the average
value for the period of 2010–2019 is about 0.8°C,
which is the sum of greenhouse gases 1.3°C and
the aerosols -0,5°C. So, there is a relatively great
difference between the values of 1.1°C and
0.8°C which has not been explained in the paper
of Gillett. The value of 1.1°C in the graphical
presentations is for the end of 2019.
3.2 Forcing of Aerosols and Clouds
According to graphical presentations on the
temperature effect of aerosols by Gillett, the
aerosol effect has been slowly declining since
1920 and being about -0.5 °C from 1990 onward.
There are research results based on ground
stations and satellite observations showing that
the global dimming turned into brightening about
1985 to 1990
[8,9,10].
The decisive evidence has
come from the shortwave (SW) radiation
measurements by the (CERES) satellites since
March 2000 [11]. These satellites measure total
solar irradiation (TSI) and upwelling SW
radiation, and the difference is the downwelling
SW radiation
[7], Fig. 1.
The average temperature effect of the SW
anomaly in 2000–2019 is about 0.6 Wm
-2
corresponding to +0.3°C by using λ value of 0.5
K/(Wm
-2
). If this effect is added to the reported
total warming value, it would be from 1.2 to
1.6°C. It should be noted that SW radiation
upwelling depends on all factors affecting the SW
radiation travelling through the atmosphere and
reflecting from the atmosphere, the clouds, and
the Earth’s surface. In this sense, it is the
observation-based magnitude of three different
aerosol related climate drivers as defined by the
IPCC
in AR5 [2]
for 2011: aerosols and
precursors, -0.27 Wm
-2
; cloud adjustments due
to aerosols, -0.55 Wm
-2
; and albedo changes
due to land use, -0.15 Wm
-2
. Altogether, these
total -0.97
Wm
-2
, corresponding to the -0.5°C, which is the
same as the aerosol effect of Gillett from 1990
onward. The authors of the Gillett study have not
commented on this drastic change of SW forcing
caused by the atmospheric aerosol and/or cloud
conditions, even though it questions the most
important results of GCMs.
Fig. 1. SW fluxes since March 2000 and the temperature anomaly effect of the downwelling SW
radiation based on dynamic simulation
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
48
3.3 Positive Water Feedback
The term Radiative Forcing (RF) has not been
used in the article of Gillett, but it is an essential
concept of the IPCC in calculating warming
impacts as explained in section 2. The positive
water feedback is a common property in GCMs,
and it means duplicating the original forcing
values of other climate drivers. This property of
GCMs applied in the article can be tested using
the RF effect of carbon dioxide, which is the most
accurate RF value according to the IPCC [1]
(very high confidence). Since the CO
2
forcing of
GCMs in 2019 is about 1.0°C, it means that λ
value of 0.5 K/(Wm
-2
) has been applied together
with the RF value according to the equation of
[12]: dT = 0.5 * 5.35 * ln(411.16/280) = 1.03°C.
The strong impact of positive water feedback can
be seen in Fig. 3, where the temperature
simulations of two models have been depicted
for the period from March 2001 to the end of
2019.
The author has shown that the temperature
impacts of GCMs and the simple IPCC model are
practically the same for the simulation period of
Gillett since they are based on water feedback.
The temperature effects of three major climate
drivers of the simple IPCC model in 2019 are:
anthropogenic factors 0.29°C, ENSO effect
0.08°C, and SW radiation forcing 0.8°C, totaling
1.17°C. The Ollila model is without water
feedback, and the same temperature effects are:
anthropogenic factors 0.1°C, ENSO effect
0.08°C, and SW radiation forcing 0.37°C, totaling
0.55°C. The Ollila model follows very well the
temperature changes from 2000 to 2019, Fig. 3.
The SW radiation anomaly of 1.6 Wm
-2
in 2019 is
about the same as 1.68 Wm
-2
by CO
2
from 1750
to 2011 [2], meaning the temperature effect of
+0.8°C. The SW anomaly is probably due to the
changes in low-level clouds
[13], and it may be
mainly caused by natural changes, which are not
known by climate researchers, but the
mechanism has been proposed [14]. Since this
positive SW anomaly temperature effect is based
on the most accurate available radiation
measurements with the same accuracy as the
TSI, it should be added to the final temperature.
In this case, the average simulated temperature
of 2019 by Gillett would increase to 1.7–2.1°C,
causing an error of 55–91% in respect to
HadCRUT4 [15].
Fig. 2. The temperature trend and TPW (Total Precipitable Water) [16] trends from 1980 to 2020
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
49
Fig. 3. The temperature effects of three major climate drivers applying water feedback (IPCC
model) or without water feedback (Ollila model)
This great error is probably due mainly to the
positive water feedback applied in GCMs and by
the IPCC. The theory of positive water feedback
is based on the equation of Clausius-Clapeyron
(C-C), which shows the relationship between the
saturated water pressure and the temperature.
The atmosphere’s relative humidity varies
typically from 35% to 90% and only occasionally
and locally the value is 100%. The conditions are
not applicable for C-C theory in climate science.
A common C-C relationship applied in climate
models is that the tropospheric water amount
increases at the rate of 7% per degree Celsius,
meaning positive water feedback. Direct
observations do not show the positive water
feedback (Fig. 2).
The surface temperature increased according to
all temperature data sets from 1980 to 2000, but
the TPW value declined during this period [16].
Only during ENSO (El Nino Southern Oscillation)
events, which are short-term climate
disturbances, does the positive water feedback
mechanism work, but the overall long-term
absolute humidity trend does not behave in this
way. The inaccuracies of humidity
measurements cannot be blamed, since both
short-term and long-term effects are based on
the same measurement data sets.
The λ is related to the Earth’s radiation balance
[3]:
SC(1-α) * ¶r
2
= sT
4
* 4¶r
2
(3)
where SC is the solar constant, T is the
temperature corresponding to the emitted
longwave radiation by the surface, α is the
average albedo, and s is the Stefan-Boltzmann
constant. Since the term SC(1-α)/4 is the same
as the net RF, equation (3) can be written in the
form RF = sT
4
. Using derivation, the λ value can
be calculated to be:
dT/(dRF)) = λ = T/(4RF) = T/(SC(1-α)) (4)
Using the present numerical flux values, λ is
about 0.27 K(/Wm
2
). It means no positive water
feedback.
3.4 The Calculation Basis of the Paris
Agreement
The anthropogenic warming calculations of the
Paris agreement (also called the
21st Conference of the Parties – COP21) are
based on IPCC science. The UNFCCC (United
Nations Framework Convention on Climate
Change) has used the calculation methods of the
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
50
IPCC and the RCP8.5 (Representative
Concentration Pathway) scenario for defining the
baseline scenario to calculate future temperature
impacts of human-induced climate change [17].
The original goal of COP21 was to limit the
temperature increase to 2.0°C. The IPCC’s
Special Report on Global Warming [18] has
recommended keeping it at 1.5°C.
The results of Gillett’s simulations show the
warming is caused mainly by two anthropogenic
warming drivers, which are greenhouse gases
and aerosols, causing a temperature change of
between 0.9 to 1.3°C, meaning an average value
of 1.1°C. In the year 2019 the SW forcing was
1.61 Wm
-2
, causing the temperature effect of
0.8°C, according to the calculation basis of the
IPCC and Gillett simulations. Thus, the
temperature increase would have been 1.1 + 0.8
= 1.9°C, overshooting the COP21 limit of 1.5°C.
4. DISCUSSION
One can only speculate what the reasons could
be for omitting the SW radiation anomaly of the
2000s.
1) The model-calculated temperatures are
approaching the observed temperatures, which
are the same for the period of 2000-2019
according to Gillet. This is a piece of good news
for the climate society since the different has
been significant in 2011: the model calculated
temperature 1.37°C versus the observed
temperature of 0.85°C [2].
2) The SW anomaly impacts show that there are
natural climate drivers that have rapid and
significant temperature impacts exceeding the
anthropogenic drivers for the period of 2000-
2019. The IPCC and the climate community have
claimed that the natural climate impacts have
been close to zero as also shown by the GCM
simulations by Gillet. The GCMs show still the
same perception. For climate scientists, it is well-
known that the present average yearly
CO
2
increase of 2.5 ppm causes only a 0.02°C
temperature increase. Also, the rapid
temperature decline from 0.4°C in October 2020
to -0.05°C in April 2021 per UAH
temperature [19]. shows that it cannot be due to
anthropogenic reasons. The temperature
increase since the 2015–16 El Nino year cannot
be due to anthropogenic reasons, but it has been
omitted, even though the SW anomaly should be
well-known. This is worrisome since this fact will
emerge to general awareness sooner or later.
3) The author has received feedback from some
climate scientists that the existence and the
magnitude of the SW anomaly from 2001 to 2021
might be a wrong misconception of the author
since there are no other published researched
results of this matter. This remark is justified
since there is no data bank source representing
SW radiation graphical trends. The recent
research paper of Loeb et al. [20] published in
May 2021 contains Fig. 2a showing the same
SW radiation trend as in Fig. 3 of this paper. Dr.
Norman Loeb is responsible director of the
CERES satellite program. There is no slightest
suspicion that the SW anomaly is a real and
strong phenomenon.
4) Natural and anthropogenic forcings should
have caused a temperature increase of about
1.9°C for the year 2019, according to the IPCC
and COP21 science, but the observed
temperature rise is only 1.1°C per Gillett’s
simulations applying 13 climate models. This fact
would crumble the scientific basis of the Paris
agreement and the agreement would lose its
credibility.
5. CONCLUSIONS
The main result of this article is that the GCMs
do not consider the significant SW radiation
anomaly happening from 2001 onward and
having a maximum value of 1.61 Wm
-2
in 2019.
This effect is almost the same as the CO
2
RF of
the value of 1.68 from 1750 to 2011 [2], which
corresponds to the temperature effect of 0.8°C
according to the IPCC science. It is a general
observation that the climate community has been
silent about this SW anomaly and has omitted its
impacts on temperature, since only three articles
have been published on this matter [5,13,20].
The basic scientific reason behind these errors
between the observations and models is the
positive water feedback applied in both simple
and complicated climate models, as also used in
the GCMs of Gillett’s simulations. These findings
mean that climate models applying positive water
feedback result in about 50% too high warming
values.
COMPETING INTERESTS
Author has declared that no competing interests
exist.
Ollila; CJAST, 40(17): 45-52, 2021; Article no.CJAST.70331
51
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© 2021 Ollila; This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Peer-review history:
The peer review history for this paper can be accessed here:
https://www.sdiarticle4.com/review-history/70331
... The purpose and the scope of this study are to carry out analyses on the impact of ASR forcings on the temperature since 2000 except in a couple of studies giving perspective. The present GCMs do not apply to the analyses, since they do not utilise direct CERES radiation observations (Ollila, 2021) and are poor at simulating ASR variations (Trenberth and Fasullo, 2005;Stephens et al., 2022). The later analyses below reveal that GCMs do not consider indirect aerosols and cloud observations or estimates either according to the AR5 and the AR6 (IPCC, 2013; IPCC 2021). ...
... The warming impact of the ENSO effect emerged after April 2023 (ONI, 2023), when La Niña started to fade, and the present El Niño emerged in May. The positive impact of ENSO on surface temperatures started in August-September 2023 since there is a 6-month delay in the temperature impact of the ONI index (Trenberth and Fasullo, 2015;Ollila, 2021). The conclusion is that the increase in recent temperatures in 2023 has mainly been due to non-anthropogenic causes. ...
... The λ value was calculated according to the actual CERES observation variations (SWup / TSI). In both models, the temperature impact dTs of the ENSO effect has been calculated from the ONI index by applying an equation dTs = 0.1 * ONI with a 6-month delay in temperature impact (Trenberth and Fasullo, 2013;Ollila 2021). The dynamical time constants for the ocean were 2.74 months and for land 1.04 months (Stine et al., 2009). ...
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According to the paradigm of the IPCC global warming is solely due to anthropogenic causes. Record-high temperatures have been measured for the summer months of 2023 and the anthropogenic climate drivers – mainly greenhouse gases - have been named as culprits. Simple analyses reveal that the temperature increase of the year 2023 cannot be explained exclusively by anthropogenic climate drivers. The hypothesis of this study is to show that the main climate driver for the high temperature of 2023 has been the Absorbed Shortwave Radiation (ASR). The approach has been to apply the CERES (Clouds and the Earth’s Radiant Energy System) satellite radiation measurements, which started in March 2001. Simple climate models have been applied since General Climate Models (GCM) cannot simulate cloudiness and shortwave radiation (SW) changes properly. The ASR changes are related mainly to cloudiness and aerosol particle changes. Since 2014 the global surface temperature growth rate has accelerated but this does not apply to anthropogenic climate drivers, and therefore the ASR changes are probably related to external forcings. The total Radiative Forcing (RF) according to the AR6 was 2.70 Wm-2 for the period 1750-2019. This can be compared to the change in the ASR, which was 2.01 Wm-2 from the year 2000 to the year 2023. This finding means that natural climate drivers have altogether an important role in recent global warming.
... The significant SW anomaly of the 2000s (depicted as shortwave radiation downwelling in Fig. 11) is a reality but its warming impact has not been generally acknowledged in climate science since it challenges the basis of GCMs. Figure 11. SW and LW radiation changes at the TOA from 2001 to 2020 (Ollila, 2021). The SWnet change is the same as the Shortwave radiation downwelling. ...
... The most important issues in climate change are the RF value of CO2 and the positive water feedback. The SW radiation anomaly of the 2000s created a unique opportunity to test the accuracies of the GCMs applied by the IPCC and a challenging model of Ollila (2021). According to the glossary of AR5 (IPCC, 2013), the portion of any top-of-atmosphere radiative effect that is due to anthropogenic or other external influences, such as changes in the Sun, is termed instantaneous radiative forcing (IRF). ...
... According to the glossary of AR5 (IPCC, 2013), the portion of any top-of-atmosphere radiative effect that is due to anthropogenic or other external influences, such as changes in the Sun, is termed instantaneous radiative forcing (IRF). Ollila (2021) simulated the temperature effects during SW radiation anomaly from 2001 to 2019 using both the IPCC's simple climate model and his simple climate model by starting temperature changes from zero in 2001, Fig. 12. In the IPCC model, a λ value of 0.47 Wm -2 was applied, and the CO2 impact was calculated using Eq. ...
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... The findings of this study support the conclusion that the 60 & 88years cycles have their grand maximum impacts in around 1939 and 2000-2020 but thereafter the impact of these cycles weakens during the rest of the century. Since solar activity has been slightly declining from 2000 onward according to CERES observations (Ollila, 2021), it means that warming of the Earth originating from solar and other natural periodicities should not increase during the 2020 decade and decrease gradually thereafter. ...
... Cloudiness changes have a significant impact on shortwave (SW) radiation changes and surface temperature. According to CERES satellite measurements, the SW radiation increased by 1.61 Wm -2 from 2001 to 2019 (Ollila 2021, Loeb et al., 2021, which can be compared to the CO2 radiative forcing of 2.16 Wm -2 from 1750 to 2019 (IPCC, 2021). According to , the correlation between SST and low cloud cover is robust. ...
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