CO2 Has Almost No Effect on Global Temperature, Says Leading Climate Scientist

otto105 said:
CO2 doesn't have a political preference.

You however seem to think leadership is too hard if everyone doesn't move the same.
Click to expand...
Come on, Man! Have you written a letter to the CCP or otherwise let the know you AGW concerns? You can post on their social media, right?
 
Toddsterpatriot said:
No, I'm not worried about the human race adapting.

Did you ever link to the stupid website that got you all worried?
Click to expand...
Didn’t think you would. No more then a pet goldfish does.
No web site for you. Deniers are too lazy. It’s easier just to tune in Tucker every night
I’m sure your tuner is figuratively rusted in place to Fix News.
 
Open your copy of AR6's Physical Science Basis. Go to Chapter 7.5 on page 992. There the discussion will begin on Equilbrium Climate Sensitivity and Tranient Climate Response (ECS and TCR).

Just a taste to get you going and to show that the topic has been heavily investigated and is not the result of overworked, politically-driven conspiracy to overthrow the planet's governments.

7.5 Estimates of ECS and TCR
Equilibrium climate sensitivity (ECS) and transient climate response
(TCR) are metrics of the global surface air temperature (GSAT)
response to forcing, as defined in Box 7.1. ECS is the magnitude
of the long-term GSAT increase in response to a doubling of
atmospheric CO2 concentration after the planetary energy budget is
balanced, though leaving out feedbacks associated with ice sheets;
whereas the TCR is the magnitude of GSAT increase at year 70 when
CO2 concentration is doubled in a 1% yr –1 increase scenario. Both
are idealized quantities, but can be inferred from paleoclimate or
observational records or estimated directly using climate simulations,
and are strongly correlated with the climate response in realistic
future projections (Sections 4.3.4 and 7.5.7; Grose et al., 2018).

...

7.5.1.1 ECS Estimated Using Process-based
Assessments of Forcing and Feedbacks
The process-based assessment is based on the global energy budget
equation (Box 7.1, Equation 7.1), where the ERF (ΔF) is set equal to
the effective radiative forcing due to a doubling of CO2 concentration
(denoted as ΔF2×CO2) and the climate state reaches a new equilibrium,
that is, Earth’s energy imbalance averages to zero (ΔN = 0). ECS is
calculated as the ratio between the ERF and the net feedback
parameter: ECS = –ΔF2×CO2/α. Estimates of ΔF2×CO2 and α are obtained
separately based on understanding of the key processes that
determine each of these quantities. Specifically, ΔF2×CO2 is estimated
based on instantaneous radiative forcing that can be accurately
obtained using line-by-line calculations, to which uncertainty due
to adjustments are added (Section 7.3.2). The range of α is derived
by aggregating estimates of individual climate feedbacks based not
only on ESMs but also on theory, observations, and high-resolution
process modelling (Section 7.4.2).

The effective radiative forcing of CO2 doubling is assessed to be
ΔF2×CO2 = 3.93 ± 0.47 W m–2 (Section 7.3.2.1), while the net feedback
parameter is assessed to be α = –1.16 ± 0.40 W m–2 °C–1 (Table 7.10),
where the ranges indicate one standard deviation. These values are
slightly different from those directly calculated from ESMs because
more information is used to assess them, as explained above. Assuming
ΔF2×CO2 and α each follow an independent normal distribution, the
uncertainty range of ECS can be obtained by substituting the respective
probability density function into the expression of ECS (red curved bar
in Figure 7.16). Since α is in the denominator, the normal distribution
leads to a long tail in ECS towards high values, indicating the large
effect of uncertainty in α in estimating the likelihood of a high ECS
(Roe and Baker, 2007; Knutti and Hegerl, 2008).
The wide range of the process-based ECS estimate is not due
solely to uncertainty in the estimates of ΔF2×CO2 and α, but is partly
explained by the assumption that ΔF2×CO2 and α are independent in
this approach. In CMIP5 and CMIP6 ensembles, ΔF2×CO2 and α are
negatively correlated when they are calculated using linear regression
in abrupt4xCO2 simulations (r2 = 0.34; Andrews et al., 2012; Webb
et al., 2013; Zelinka et al., 2020). The negative correlation leads to
compensation between the inter-model spreads of these quantities,
thereby reducing the ECS range estimated directly from the models.
If the process-based ECS distribution is reconstructed from probability
distributions of ΔF2×CO2 and α assuming that they are correlated as in
CMIP model ensembles, the range of ECS will be narrower by 14%
(pink curved bar in Figure 7.16). If, however, the covariance between
ΔF2×CO2 and α is not adopted, there is no change in the mean, but the
wide range still applies.

A significant correlation between ΔF2×CO2 and α also occurs when
the two parameters are estimated separately from atmospheric ESM
fixed-SST experiments (Section 7.3.1) or fixed CO2 concentration
experiments (Section 7.4.1; Ringer et al., 2014; Chung and Soden,
2018). Hence the relationship is not expected to be an artefact of
calculating the parameters using linear regression in abrupt4xCO2
simulations. A possible physical cause of the correlation may be
a compensation between the cloud adjustment and the cloud
feedback over the tropical ocean (Ringer et al., 2014; Chung and
Soden, 2018). It has been shown that the change in the hydrological
cycle is a controlling factor for the low-cloud adjustment (Dinh and
Fueglistaler, 2019) and for the low-cloud feedback (Watanabe et al.,
2018), and therefore the responses of these clouds to the direct CO2
radiative forcing and to the surface warming may not be independent.
However, robust physical mechanisms are not yet established,
and furthermore, the process-based assessment of the tropical
low-cloud feedback is only indirectly based on ESMs given that
physical processes which control the low-clouds are not sufficiently
well-simulated in models (Section 7.4.2.4). For these reasons, the
co-dependency between ΔF2×CO2 and α is assessed to have low
confidence and, therefore, the more conservative assumption that
they are independent for the process-based assessment of ECS
is retained.

1680262857882.png

Figure 7.16 | Probability distributions of ERF to CO2 doubling (ΔF2×CO2;
top) and the net climate feedback (α; right), derived from processbased
assessments in Sections 7.3.2 and 7.4.2. Central panel shows the joint
probability density function calculated on a two-dimensional plane of ΔF2×CO2 and
α (red), on which the 90% range shown by an ellipse is imposed to the background
theoretical values of ECS (colour shading). The white dot, and thick and thin curves
inside the ellipse represent the mean, likely and very likely ranges of ECS. An alternative
estimation of the ECS range (pink) is calculated by assuming that ΔF2×CO2 and α have
a covariance. The assumption about the co-dependence between ΔF2×CO2 and α
does not alter the mean estimate of ECS but affects its uncertainty. Further details on
data sources and processing are available in the chapter data table (Table 7.SM.14).

END EXCERPT

There are about 18 more pages of this discussion if you care to look.

IF you don't have a local copy, you can get one (for FREE) at AR6 Climate Change 2021: The Physical Science Basis — IPCC

I wouldn't mind Frank, Tommy, Todd, jc or even the OP, Bripat9643, addressing the particular points in this section of AR6 dealing with ECS and TCR.
 
Last edited:
Crick said:
Open your copy of AR6's Physical Science Basis. Go to Chapter 7.5 on page 992. There the discussion will begin on Equilbrium Climate Sensitivity and Tranient Climate Response (ECS and TCR).

Just a taste to get you going and to show that the topic has been heavily investigated and is not the result of overworked, politically-driven conspiracy to overthrow the planet's governments.

7.5 Estimates of ECS and TCR
Equilibrium climate sensitivity (ECS) and transient climate response
(TCR) are metrics of the global surface air temperature (GSAT)
response to forcing, as defined in Box 7.1. ECS is the magnitude
of the long-term GSAT increase in response to a doubling of
atmospheric CO2 concentration after the planetary energy budget is
balanced, though leaving out feedbacks associated with ice sheets;
whereas the TCR is the magnitude of GSAT increase at year 70 when
CO2 concentration is doubled in a 1% yr –1 increase scenario. Both
are idealized quantities, but can be inferred from paleoclimate or
observational records or estimated directly using climate simulations,
and are strongly correlated with the climate response in realistic
future projections (Sections 4.3.4 and 7.5.7; Grose et al., 2018).

...

7.5.1.1 ECS Estimated Using Process-based
Assessments of Forcing and Feedbacks
The process-based assessment is based on the global energy budget
equation (Box 7.1, Equation 7.1), where the ERF (ΔF) is set equal to
the effective radiative forcing due to a doubling of CO2 concentration
(denoted as ΔF2×CO2) and the climate state reaches a new equilibrium,
that is, Earth’s energy imbalance averages to zero (ΔN = 0). ECS is
calculated as the ratio between the ERF and the net feedback
parameter: ECS = –ΔF2×CO2/α. Estimates of ΔF2×CO2 and α are obtained
separately based on understanding of the key processes that
determine each of these quantities. Specifically, ΔF2×CO2 is estimated
based on instantaneous radiative forcing that can be accurately
obtained using line-by-line calculations, to which uncertainty due
to adjustments are added (Section 7.3.2). The range of α is derived
by aggregating estimates of individual climate feedbacks based not
only on ESMs but also on theory, observations, and high-resolution
process modelling (Section 7.4.2).

The effective radiative forcing of CO2 doubling is assessed to be
ΔF2×CO2 = 3.93 ± 0.47 W m–2 (Section 7.3.2.1), while the net feedback
parameter is assessed to be α = –1.16 ± 0.40 W m–2 °C–1 (Table 7.10),
where the ranges indicate one standard deviation. These values are
slightly different from those directly calculated from ESMs because
more information is used to assess them, as explained above. Assuming
ΔF2×CO2 and α each follow an independent normal distribution, the
uncertainty range of ECS can be obtained by substituting the respective
probability density function into the expression of ECS (red curved bar
in Figure 7.16). Since α is in the denominator, the normal distribution
leads to a long tail in ECS towards high values, indicating the large
effect of uncertainty in α in estimating the likelihood of a high ECS
(Roe and Baker, 2007; Knutti and Hegerl, 2008).
The wide range of the process-based ECS estimate is not due
solely to uncertainty in the estimates of ΔF2×CO2 and α, but is partly
explained by the assumption that ΔF2×CO2 and α are independent in
this approach. In CMIP5 and CMIP6 ensembles, ΔF2×CO2 and α are
negatively correlated when they are calculated using linear regression
in abrupt4xCO2 simulations (r2 = 0.34; Andrews et al., 2012; Webb
et al., 2013; Zelinka et al., 2020). The negative correlation leads to
compensation between the inter-model spreads of these quantities,
thereby reducing the ECS range estimated directly from the models.
If the process-based ECS distribution is reconstructed from probability
distributions of ΔF2×CO2 and α assuming that they are correlated as in
CMIP model ensembles, the range of ECS will be narrower by 14%
(pink curved bar in Figure 7.16). If, however, the covariance between
ΔF2×CO2 and α is not adopted, there is no change in the mean, but the
wide range still applies.

A significant correlation between ΔF2×CO2 and α also occurs when
the two parameters are estimated separately from atmospheric ESM
fixed-SST experiments (Section 7.3.1) or fixed CO2 concentration
experiments (Section 7.4.1; Ringer et al., 2014; Chung and Soden,
2018). Hence the relationship is not expected to be an artefact of
calculating the parameters using linear regression in abrupt4xCO2
simulations. A possible physical cause of the correlation may be
a compensation between the cloud adjustment and the cloud
feedback over the tropical ocean (Ringer et al., 2014; Chung and
Soden, 2018). It has been shown that the change in the hydrological
cycle is a controlling factor for the low-cloud adjustment (Dinh and
Fueglistaler, 2019) and for the low-cloud feedback (Watanabe et al.,
2018), and therefore the responses of these clouds to the direct CO2
radiative forcing and to the surface warming may not be independent.
However, robust physical mechanisms are not yet established,
and furthermore, the process-based assessment of the tropical
low-cloud feedback is only indirectly based on ESMs given that
physical processes which control the low-clouds are not sufficiently
well-simulated in models (Section 7.4.2.4). For these reasons, the
co-dependency between ΔF2×CO2 and α is assessed to have low
confidence and, therefore, the more conservative assumption that
they are independent for the process-based assessment of ECS
is retained.

View attachment 771371
Figure 7.16 | Probability distributions of ERF to CO2 doubling (ΔF2×CO2;
top) and the net climate feedback (α; right), derived from processbased
assessments in Sections 7.3.2 and 7.4.2. Central panel shows the joint
probability density function calculated on a two-dimensional plane of ΔF2×CO2 and
α (red), on which the 90% range shown by an ellipse is imposed to the background
theoretical values of ECS (colour shading). The white dot, and thick and thin curves
inside the ellipse represent the mean, likely and very likely ranges of ECS. An alternative
estimation of the ECS range (pink) is calculated by assuming that ΔF2×CO2 and α have
a covariance. The assumption about the co-dependence between ΔF2×CO2 and α
does not alter the mean estimate of ECS but affects its uncertainty. Further details on
data sources and processing are available in the chapter data table (Table 7.SM.14).

END EXCERPT

There are about 18 more pages of this discussion if you care to look.

IF you don't have a local copy, you can get one (for FREE) at AR6 Climate Change 2021: The Physical Science Basis — IPCC

I wouldn't mind Frank, Tommy, Todd, jc or even the OP, Bripat9643, addressing the particular points in this section of AR6 dealing with ECS and TCR.
Click to expand...

Is that the part where the Nobel Prize winner hides the decline?
 
Crick said:
Open your copy of AR6's Physical Science Basis. Go to Chapter 7.5 on page 992. There the discussion will begin on Equilbrium Climate Sensitivity and Tranient Climate Response (ECS and TCR).

Just a taste to get you going and to show that the topic has been heavily investigated and is not the result of overworked, politically-driven conspiracy to overthrow the planet's governments.

7.5 Estimates of ECS and TCR
Equilibrium climate sensitivity (ECS) and transient climate response
(TCR) are metrics of the global surface air temperature (GSAT)
response to forcing, as defined in Box 7.1. ECS is the magnitude
of the long-term GSAT increase in response to a doubling of
atmospheric CO2 concentration after the planetary energy budget is
balanced, though leaving out feedbacks associated with ice sheets;
whereas the TCR is the magnitude of GSAT increase at year 70 when
CO2 concentration is doubled in a 1% yr –1 increase scenario. Both
are idealized quantities, but can be inferred from paleoclimate or
observational records or estimated directly using climate simulations,
and are strongly correlated with the climate response in realistic
future projections (Sections 4.3.4 and 7.5.7; Grose et al., 2018).

...

7.5.1.1 ECS Estimated Using Process-based
Assessments of Forcing and Feedbacks
The process-based assessment is based on the global energy budget
equation (Box 7.1, Equation 7.1), where the ERF (ΔF) is set equal to
the effective radiative forcing due to a doubling of CO2 concentration
(denoted as ΔF2×CO2) and the climate state reaches a new equilibrium,
that is, Earth’s energy imbalance averages to zero (ΔN = 0). ECS is
calculated as the ratio between the ERF and the net feedback
parameter: ECS = –ΔF2×CO2/α. Estimates of ΔF2×CO2 and α are obtained
separately based on understanding of the key processes that
determine each of these quantities. Specifically, ΔF2×CO2 is estimated
based on instantaneous radiative forcing that can be accurately
obtained using line-by-line calculations, to which uncertainty due
to adjustments are added (Section 7.3.2). The range of α is derived
by aggregating estimates of individual climate feedbacks based not
only on ESMs but also on theory, observations, and high-resolution
process modelling (Section 7.4.2).

The effective radiative forcing of CO2 doubling is assessed to be
ΔF2×CO2 = 3.93 ± 0.47 W m–2 (Section 7.3.2.1), while the net feedback
parameter is assessed to be α = –1.16 ± 0.40 W m–2 °C–1 (Table 7.10),
where the ranges indicate one standard deviation. These values are
slightly different from those directly calculated from ESMs because
more information is used to assess them, as explained above. Assuming
ΔF2×CO2 and α each follow an independent normal distribution, the
uncertainty range of ECS can be obtained by substituting the respective
probability density function into the expression of ECS (red curved bar
in Figure 7.16). Since α is in the denominator, the normal distribution
leads to a long tail in ECS towards high values, indicating the large
effect of uncertainty in α in estimating the likelihood of a high ECS
(Roe and Baker, 2007; Knutti and Hegerl, 2008).
The wide range of the process-based ECS estimate is not due
solely to uncertainty in the estimates of ΔF2×CO2 and α, but is partly
explained by the assumption that ΔF2×CO2 and α are independent in
this approach. In CMIP5 and CMIP6 ensembles, ΔF2×CO2 and α are
negatively correlated when they are calculated using linear regression
in abrupt4xCO2 simulations (r2 = 0.34; Andrews et al., 2012; Webb
et al., 2013; Zelinka et al., 2020). The negative correlation leads to
compensation between the inter-model spreads of these quantities,
thereby reducing the ECS range estimated directly from the models.
If the process-based ECS distribution is reconstructed from probability
distributions of ΔF2×CO2 and α assuming that they are correlated as in
CMIP model ensembles, the range of ECS will be narrower by 14%
(pink curved bar in Figure 7.16). If, however, the covariance between
ΔF2×CO2 and α is not adopted, there is no change in the mean, but the
wide range still applies.

A significant correlation between ΔF2×CO2 and α also occurs when
the two parameters are estimated separately from atmospheric ESM
fixed-SST experiments (Section 7.3.1) or fixed CO2 concentration
experiments (Section 7.4.1; Ringer et al., 2014; Chung and Soden,
2018). Hence the relationship is not expected to be an artefact of
calculating the parameters using linear regression in abrupt4xCO2
simulations. A possible physical cause of the correlation may be
a compensation between the cloud adjustment and the cloud
feedback over the tropical ocean (Ringer et al., 2014; Chung and
Soden, 2018). It has been shown that the change in the hydrological
cycle is a controlling factor for the low-cloud adjustment (Dinh and
Fueglistaler, 2019) and for the low-cloud feedback (Watanabe et al.,
2018), and therefore the responses of these clouds to the direct CO2
radiative forcing and to the surface warming may not be independent.
However, robust physical mechanisms are not yet established,
and furthermore, the process-based assessment of the tropical
low-cloud feedback is only indirectly based on ESMs given that
physical processes which control the low-clouds are not sufficiently
well-simulated in models (Section 7.4.2.4). For these reasons, the
co-dependency between ΔF2×CO2 and α is assessed to have low
confidence and, therefore, the more conservative assumption that
they are independent for the process-based assessment of ECS
is retained.

View attachment 771371
Figure 7.16 | Probability distributions of ERF to CO2 doubling (ΔF2×CO2;
top) and the net climate feedback (α; right), derived from processbased
assessments in Sections 7.3.2 and 7.4.2. Central panel shows the joint
probability density function calculated on a two-dimensional plane of ΔF2×CO2 and
α (red), on which the 90% range shown by an ellipse is imposed to the background
theoretical values of ECS (colour shading). The white dot, and thick and thin curves
inside the ellipse represent the mean, likely and very likely ranges of ECS. An alternative
estimation of the ECS range (pink) is calculated by assuming that ΔF2×CO2 and α have
a covariance. The assumption about the co-dependence between ΔF2×CO2 and α
does not alter the mean estimate of ECS but affects its uncertainty. Further details on
data sources and processing are available in the chapter data table (Table 7.SM.14).

END EXCERPT

There are about 18 more pages of this discussion if you care to look.

IF you don't have a local copy, you can get one (for FREE) at AR6 Climate Change 2021: The Physical Science Basis — IPCC

I wouldn't mind Frank, Tommy, Todd, jc or even the OP, Bripat9643, addressing the particular points in this section of AR6 dealing with ECS and TCR.
Click to expand...
IPCC....ROFLMFAO!

....baffle them with bullshit.
 
Crick said:
Aside from your assumption, Todd, what evidence do you have that "decline" referred to temperature?
Click to expand...

Climatic Research Unit email controversy - Wikipedia

en.wikipedia.org en.wikipedia.org

All underlined text is hyperlinked back to Wikipedia.

The Climatic Research Unit email controversy (also known as "Climategate")[2][3] began in November 2009 with the hacking of a server at the Climatic Research Unit (CRU) at the University of East Anglia (UEA) by an external attacker,[4][5] copying thousands of emails and computer files (the Climatic Research Unit documents) to various internet locations several weeks before the Copenhagen Summit on climate change.

The story was first broken by climate change denialists,[6][7] who argued that the emails showed that global warming was a scientific conspiracy and that scientists manipulated climate data and attempted to suppress critics.[8][9] The CRU rejected this, saying that the emails had been taken out of context.[10][11] FactCheck.org confirmed that climate change deniers misrepresented the contents of the emails.[12] Columnist James Delingpole popularised the term "Climategate" to describe the controversy.[13]

The mainstream media picked up the story, as negotiations over climate change mitigation began in Copenhagen on 7 December 2009.[14] Because of the timing, scientists, policy makers and public relations experts said that the release of emails was a smear campaign intended to undermine the climate conference.[15] In response to the controversy, the American Association for the Advancement of Science (AAAS), the American Meteorological Society (AMS) and the Union of Concerned Scientists (UCS) released statements supporting the scientific consensus that the Earth's mean surface temperature had been rising for decades, with the AAAS concluding: "based on multiple lines of scientific evidence that global climate change caused by human activities is now underway... it is a growing threat to society".[16]
...
Eight committees investigated the allegations and published reports, finding no evidence of fraud or scientific misconduct.[17] [Committees listed at endnote 17] The scientific consensus that global warming is occurring as a result of human activity remained unchanged by the end of the investigations.[18] However, the reports urged the scientists to avoid any such allegations in the future, and to regain public confidence following this media storm, with "more efforts than ever to make available all their supporting data – right down to the computer codes they use – to allow their findings to be properly verified". Climate scientists and organisations pledged to improve scientific research and collaboration with other researchers by improving data management and opening up access to data, and to honour any freedom of information requests that relate to climate science.[89]

REFERENCES

  1. Secretary of State for Energy and Climate Change (28 September 2010). Government Response to the House of Commons Science and Technology 8th Report of Session 2009–10: The disclosure of climate data from the Climatic Research Unit at the University of East Anglia (PDF). The Stationery Office. ISBN 978-0-10-179342-1. Archived (PDF) from the original on 5 July 2013. Retrieved 14 October 2010.
  2. ^ Chameides, Bill. "Climategate Redux". Scientific American, 30 August 2010. Retrieved 17 August 2011.
  3. ^ "Closing the Climategate Archived 20 January 2017 at the Wayback Machine". Nature. 18 November 2010. Retrieved 17 August 2011.
  4. ^ Pooley 2010, p. 425: "Climategate broke in November, when a cache of e-mails was hacked from a server at the Climatic Research Unit (CRU) of the University of East Anglia in Norwich, England." See: Pooley, Eric (2010). The Climate War: True Believers, Power Brokers, and the Fight to Save the Earth. Hyperion Books. ISBN 1-4013-2326-X; Karatzogianni 2010: "Most media representations of the Climategate hack linked the events to other incidents in the past, suggesting a consistent narrative frame which blames the attacks on Russian hackers... Although the Climategate material was uploaded on various servers in Turkey and Saudi Arabia before ending up in Tomsk in Siberia..." Extensive discussion about the media coverage of hacking and climategate in Karatzogianni, Athina. (2010). "Blame it on the Russians: Tracking the Portrayal of Russians During Cyber conflict Incidents Archived 1 October 2015 at the Wayback Machine". Digital Icons: Studies in Russian, Eurasian and Central European New Media. 4: 128–150. ISSN 2043-7633.
  5. ^ Jump up to:a b c d Norfolk Constabulary (18 July 2012). "Police closes UEA investigation". Archived from the original on 19 July 2012. Retrieved 18 July 2012.
  6. ^ Jump up to:a b c Leiserowitz et al., 2010, "Climategate, Public Opinion, and the Loss of Trust Archived 20 July 2011 at the Wayback Machine". Working Paper, Subject to Revision. Yale University.
  7. ^ McKie, Robin (9 November 2019). "Climategate 10 years on: what lessons have we learned?". The Guardian. Archived from the original on 4 July 2021. Retrieved 21 May 2020.
  8. ^ Jump up to:a b c d e Hickman, Leo; Randerson, James (20 November 2009). "Climate sceptics claim leaked emails are evidence of collusion among scientists". The Guardian. UK. Archived from the original on 10 September 2013. Retrieved 27 July 2010.
  9. ^ Somaiya, Ravi (7 July 2010). "Third Inquiry Clears 'Climategate' Scientists of Serious Wrongdoing Archived 21 January 2011 at the Wayback Machine". Newsweek. Retrieved 15 May 2011. "For sceptics, the 1,000 or so e-mails and documents hacked last year from the Climactic [sic] Research Unit of the University of East Anglia (UEA), in England, establish that global warming is a scientific conspiracy ... Climategate, now a firmly established "gate," will probably continue to be cited as evidence of a global-warming conspiracy";
    Efstathiou Jr., Jim; Alex Morales (2 December 2009). "UK climate scientist steps down after email flap Archived 29 November 2011 at the Wayback Machine". Bloomberg. LiveMint. Retrieved 15 May 2011. "The emails, dating back as far as 1996, have been cited by sceptics of man’s contribution to global warming as evidence of a conspiracy to manipulate data to support research... They’re conspiring to keep papers out of published journals," Marc Morano, a climate sceptic who is editor of a website on the issue, said referring to the emails in a 24 November interview. "You see them as nothing more than a bunch of activists manufacturing science for a political goal."
  10. ^ Eilperin, Juliet (21 November 2009). "Hackers steal electronic data from top climate research center". The Washington Post. Archived from the original on 15 May 2017. Retrieved 22 August 2017.
  11. ^ Webster, Ben (21 November 2009). "Sceptics publish climate e-mails 'stolen from East Anglia University'". The Times. London. Archived from the original on 3 August 2020. Retrieved 21 November 2019.
  12. ^ Henig, Jess (10 December 2009). "Climategate". FactCheck.org. Archived from the original on 27 July 2021. Retrieved 21 June 2020.
  13. ^ Jump up to:a b Allchen 2010, p. 591: "James Delingpole, in a blog for England's Telegraph, promptly dubbed it "Climategate." See: Allchin, Douglas (2010). "Using a Free Online Citizen-Science Project to Teach Observation". The American Biology Teacher. 72: 590–592. doi:10.1525/abt.2010.72.9.15. S2CID 198130418.; Booker 2009: "A week after my colleague James Delingpole, on his Telegraph blog, coined the term 'Climategate' to describe the scandal revealed by the leaked emails from the University of East Anglia's Climatic Research Unit, Google was showing that the word now appears across the internet more than nine million times." See: Booker, Christopher (2009) "Climate change: this is the worst scientific scandal of our generation Archived 7 April 2018 at the Wayback Machine". The Telegraph. 28 November; For the original article see: Delingpole, James (2009). "Climategate: the final nail in the coffin of 'Anthropogenic Global Warming'?" The Telegraph. 20 November; Nine days after his original article, Delingpole clarified how he came up with the name. Although he has been given credit for coining and popularizing the term (Booker 2009; Allchin 2010, etc.) he got the original idea from an anonymous blogger named "Bulldust" on the Watts Up With That blog. See: Delingpole, James (2009). "Climategate: how the 'greatest scientific scandal of our generation' got its name". The Telegraph. 29 November; Delingpole told Dennis Miller, "Climategate was the story that I helped to break..." See The Dennis Miller Show. (28 June 2011). "James Delingpole Interview". Event begins at 2:45.
  14. ^ Jump up to:a b Mooney & Kirshenbaum p. xi: "In the ensuing scandal after the e-mails became public, top climate scientists were accused of withholding information, suppressing dissent, manipulating data, and worse, particularly by right wing media and blogs. The controversy garnered dramatic press attention, especially on outlets like Fox News; and because Climategate occurred just before the critical United Nations climate conference in Copenhagen, Denmark, it knocked the whole event off rhythm in the media sphere." See: Mooney, Chris; Kirshenbaum, Sheril (2010) Unscientific America: How Scientific Illiteracy Threatens Our Future. Basic Books. ISBN 0-465-01917-X; Boslough 2010: "As evidence for human-caused climate change has mounted, global warming denialists have responded by blaming the messengers. Climate researchers have endured abuse by bloggers, editorial writers, Fox News pundits, and radio talk show hosts who have called them liars and vilified them as frauds. The attacks had become increasingly vile as the past decade, the hottest in human history, came to an end. Angry activists have called for firings and criminal investigations, and some prominent scientists have received physical threats." Boslough, Mark (2010). "Mann bites dog: why 'climategate' was newsworthy". Skeptical Inquirer. March–April. 34 (2): 14; Goldenberg 2010: "Journalists at Fox News were under orders to cast doubt on any on-air mention of climate change, a leaked email obtained by a media monitoring group revealed today. According to the email, obtained by Media Matters, Fox News's Washington bureau chief, Bill Sammon, imposed an order to make time for climate sceptics within 15 minutes of the airing of a story about a scientific report showing that 2000–2009 was on track to be the hottest decade on record. Media Matters said the bureau chief's response to the report exhibited a pattern of bias by Fox News in its coverage of climate change. It also noted the timing of the directive. The email went out on 8 December last year, when the leaders of nearly 200 countries met in Copenhagen to try to reach a deal on climate change...In addition to the email, it said Fox had tried to delegitimise the work of climate scientists in its coverage of the hacked emails from the University of East Anglia. The network had displayed a pattern of trying to skew coverage in favour of the fringe minority which doubts the existence of climate change, Media Matters said." See Goldenberg, Suzanne. (15 December 2010). "Fox News chief enforced climate change scepticism – leaked email Archived 6 January 2017 at the Wayback Machine". guardian.co.uk. Guardian News and Media Limited; In addition to the 24/7 news coverage, Fox News created a 17 minute documentary starring climate sceptic Patrick J. Michaels. See: Baier, Bret. (2010) Fox News Reporting: Global Warming...or a lot of Hot Air? Fox News.
  15. ^ Winter, Brian (25 November 2009) ""Scientist: Leaked climate e-mails a distraction" Archived 5 January 2012 at the Wayback Machine. USA Today. Retrieved 12 May 2011. "A controversy over leaked e-mails exchanged among global warming scientists is part of a 'smear campaign' to derail next month's United Nations climate summit in Copenhagen, one of the scientists, meteorologist Michael Mann, said Tuesday...Climate change sceptics 'don't have the science on their side any more, so they've resorted to a smear campaign to distract the public from the reality of the problem and the need to confront it head-on in Copenhagen' said Mann";
    Feldman, Stacy (25 November 2009). "Hacked climate emails called a "smear campaign" Archived 29 July 2021 at the Wayback Machine. Reuters. Retrieved 15 May 2011. "Three leading scientists who on Tuesday released a report documenting the accelerating pace of climate change said the scandal that erupted last week over hacked emails from climate scientists is nothing more than a "smear campaign" aimed at sabotaging December climate talks in Copenhagen"; Carrington, Damian;
    Suzanne Goldenberg (4 December 2009). "Gordon Brown attacks 'flat-earth' climate change sceptics Archived 1 December 2016 at the Wayback Machine". guardian.co.uk. Retrieved 15 May 2011. "On the eve of the Copenhagen summit, Saudi Arabia and Republican members of the US Congress have used the emails to claim the need for urgent action to cut carbon emissions has been undermined...The concern for some of those attempting to drive through a global deal is that the sceptics will delay critical decisions by casting doubt over the science at a time when momentum has been gathering towards a historic agreement...'The sceptics have clearly seized upon this as an incident that they can use to their own ends in trying to disrupt the Copenhagen agreements,' said Bob Watson, Defra chief scientist and former head of the Intergovernmental Panel on Climate Change";
    Fimrite, Peter (5 December 2009). "Hacked climate e-mail rebutted by scientists Archived 16 July 2011 at the Wayback Machine". San Francisco Chronicle. Retrieved 12 May 2011. "A group of the nation's top scientists defended research on global climate change Friday against what they called a politically motivated smear campaign designed to foster public doubt about irrefutable scientific facts...'They have engaged in this 11th-hour smear campaign where they have stolen personal e-mails from scientists, mined them for single words or phrases that can be taken out of context to twist their words and I think this is rather telling,' Mann said";
    Carrington, Damian (28 October 2010). "IPCC vice-chair: Attacks on climate science echo tobacco industry tactics Archived 23 September 2016 at the Wayback Machine". The Guardian. Retrieved 13 May 2011. "The attacks on climate science that were made ahead of the Copenhagen climate change summit were 'organised' to undermine efforts to tackle global warming and mirror the earlier tactics of the tobacco industry, according to the vice-chair of the Intergovernmental Panel on Climate Change (IPCC)... 'It is a very similar process to what the tobacco industry was doing 30 or 40 years ago, when they wanted to delay legislation, and that is the result of research – not my subjective evaluation – by Prof Naomi Oreskes and Erik Conway.' Oreskes, a science historian at the University of California San Diego, told The Guardian she agreed with Van Ypersele's that the attacks on climate science were organised: 'Many of us were expecting something to happen in the run-up [to Copenhagen]. When it happened, the only thing that surprised me was that, compared with the events we documented in our book, the attacks had crossed the line into illegality.'"
  16. ^ Henig, Jess (2009). "FactCheck: Climategate Doesn't Refute Global Warming Archived 17 June 2016 at the Wayback Machine". Newsweek. 11 December.
  17. ^ Jump up to:a b The eight major investigations covered by secondary sources include: House of Commons Science and Technology Committee Archived 4 November 2021 at the Wayback Machine (UK); Independent Climate Change Review Archived 4 November 2021 at the Wayback Machine (UK); International Science Assessment Panel Archived 9 May 2013 at the Wayback Machine (UK); Pennsylvania State University first panel Archived 25 September 2010 at the Wayback Machine and second panel Archived 30 January 2012 at the Wayback Machine (US); United States Environmental Protection Agency Archived 31 October 2021 at the Wayback Machine (US); Department of Commerce Archived 27 July 2013 at the Wayback Machine (US); National Science Foundation (US).
  18. ^ Jump up to:a b Biello, David (Feb 2010). "Negating 'Climategate' Archived 1 November 2013 at the Wayback Machine". Scientific American. (302):2. 16. ISSN 0036-8733. "In fact, nothing in the stolen material undermines the scientific consensus that climate change is happening and that humans are to blame";
    See also: Lubchenco, Jane (2 December 2009) House Select Committee on Energy Independence and Global Warming (House Select Committee). "The Administration's View on the State of Climate Science Archived 7 November 2018 at the Wayback Machine". House Hearing, 111 Congress. U.S. Government Printing Office. "...the e-mails really do nothing to undermine the very strong scientific consensus and the independent scientific analyses of thousands of scientists around the world that tell us that the Earth is warming and that the warming is largely a result of human activities." As quoted in the report published by Office of Inspector General.
  19. [[89]] Venkatraman, Archana (September–October 2010). "Data Without the Doubts". Information World Review. Bizmedia Ltd.: 18–19. Archived from the original on 1 February 2014. Retrieved 20 July 2012.
 
Last edited:
Crick said:
Open your copy of AR6's Physical Science Basis. Go to Chapter 7.5 on page 992. There the discussion will begin on Equilbrium Climate Sensitivity and Tranient Climate Response (ECS and TCR).

Just a taste to get you going and to show that the topic has been heavily investigated and is not the result of overworked, politically-driven conspiracy to overthrow the planet's governments.

7.5 Estimates of ECS and TCR
Equilibrium climate sensitivity (ECS) and transient climate response
(TCR) are metrics of the global surface air temperature (GSAT)
response to forcing, as defined in Box 7.1. ECS is the magnitude
of the long-term GSAT increase in response to a doubling of
atmospheric CO2 concentration after the planetary energy budget is
balanced, though leaving out feedbacks associated with ice sheets;
whereas the TCR is the magnitude of GSAT increase at year 70 when
CO2 concentration is doubled in a 1% yr –1 increase scenario. Both
are idealized quantities, but can be inferred from paleoclimate or
observational records or estimated directly using climate simulations,
and are strongly correlated with the climate response in realistic
future projections (Sections 4.3.4 and 7.5.7; Grose et al., 2018).

...

7.5.1.1 ECS Estimated Using Process-based
Assessments of Forcing and Feedbacks
The process-based assessment is based on the global energy budget
equation (Box 7.1, Equation 7.1), where the ERF (ΔF) is set equal to
the effective radiative forcing due to a doubling of CO2 concentration
(denoted as ΔF2×CO2) and the climate state reaches a new equilibrium,
that is, Earth’s energy imbalance averages to zero (ΔN = 0). ECS is
calculated as the ratio between the ERF and the net feedback
parameter: ECS = –ΔF2×CO2/α. Estimates of ΔF2×CO2 and α are obtained
separately based on understanding of the key processes that
determine each of these quantities. Specifically, ΔF2×CO2 is estimated
based on instantaneous radiative forcing that can be accurately
obtained using line-by-line calculations, to which uncertainty due
to adjustments are added (Section 7.3.2). The range of α is derived
by aggregating estimates of individual climate feedbacks based not
only on ESMs but also on theory, observations, and high-resolution
process modelling (Section 7.4.2).

The effective radiative forcing of CO2 doubling is assessed to be
ΔF2×CO2 = 3.93 ± 0.47 W m–2 (Section 7.3.2.1), while the net feedback
parameter is assessed to be α = –1.16 ± 0.40 W m–2 °C–1 (Table 7.10),
where the ranges indicate one standard deviation. These values are
slightly different from those directly calculated from ESMs because
more information is used to assess them, as explained above. Assuming
ΔF2×CO2 and α each follow an independent normal distribution, the
uncertainty range of ECS can be obtained by substituting the respective
probability density function into the expression of ECS (red curved bar
in Figure 7.16). Since α is in the denominator, the normal distribution
leads to a long tail in ECS towards high values, indicating the large
effect of uncertainty in α in estimating the likelihood of a high ECS
(Roe and Baker, 2007; Knutti and Hegerl, 2008).
The wide range of the process-based ECS estimate is not due
solely to uncertainty in the estimates of ΔF2×CO2 and α, but is partly
explained by the assumption that ΔF2×CO2 and α are independent in
this approach. In CMIP5 and CMIP6 ensembles, ΔF2×CO2 and α are
negatively correlated when they are calculated using linear regression
in abrupt4xCO2 simulations (r2 = 0.34; Andrews et al., 2012; Webb
et al., 2013; Zelinka et al., 2020). The negative correlation leads to
compensation between the inter-model spreads of these quantities,
thereby reducing the ECS range estimated directly from the models.
If the process-based ECS distribution is reconstructed from probability
distributions of ΔF2×CO2 and α assuming that they are correlated as in
CMIP model ensembles, the range of ECS will be narrower by 14%
(pink curved bar in Figure 7.16). If, however, the covariance between
ΔF2×CO2 and α is not adopted, there is no change in the mean, but the
wide range still applies.

A significant correlation between ΔF2×CO2 and α also occurs when
the two parameters are estimated separately from atmospheric ESM
fixed-SST experiments (Section 7.3.1) or fixed CO2 concentration
experiments (Section 7.4.1; Ringer et al., 2014; Chung and Soden,
2018). Hence the relationship is not expected to be an artefact of
calculating the parameters using linear regression in abrupt4xCO2
simulations. A possible physical cause of the correlation may be
a compensation between the cloud adjustment and the cloud
feedback over the tropical ocean (Ringer et al., 2014; Chung and
Soden, 2018). It has been shown that the change in the hydrological
cycle is a controlling factor for the low-cloud adjustment (Dinh and
Fueglistaler, 2019) and for the low-cloud feedback (Watanabe et al.,
2018), and therefore the responses of these clouds to the direct CO2
radiative forcing and to the surface warming may not be independent.
However, robust physical mechanisms are not yet established,
and furthermore, the process-based assessment of the tropical
low-cloud feedback is only indirectly based on ESMs given that
physical processes which control the low-clouds are not sufficiently
well-simulated in models (Section 7.4.2.4). For these reasons, the
co-dependency between ΔF2×CO2 and α is assessed to have low
confidence and, therefore, the more conservative assumption that
they are independent for the process-based assessment of ECS
is retained.

View attachment 771371
Figure 7.16 | Probability distributions of ERF to CO2 doubling (ΔF2×CO2;
top) and the net climate feedback (α; right), derived from processbased
assessments in Sections 7.3.2 and 7.4.2. Central panel shows the joint
probability density function calculated on a two-dimensional plane of ΔF2×CO2 and
α (red), on which the 90% range shown by an ellipse is imposed to the background
theoretical values of ECS (colour shading). The white dot, and thick and thin curves
inside the ellipse represent the mean, likely and very likely ranges of ECS. An alternative
estimation of the ECS range (pink) is calculated by assuming that ΔF2×CO2 and α have
a covariance. The assumption about the co-dependence between ΔF2×CO2 and α
does not alter the mean estimate of ECS but affects its uncertainty. Further details on
data sources and processing are available in the chapter data table (Table 7.SM.14).

END EXCERPT

There are about 18 more pages of this discussion if you care to look.

IF you don't have a local copy, you can get one (for FREE) at AR6 Climate Change 2021: The Physical Science Basis — IPCC

I wouldn't mind Frank, Tommy, Todd, jc or even the OP, Bripat9643, addressing the particular points in this section of AR6 dealing with ECS and TCR.
Click to expand...
As I suspected and knew, no experiments, just models

Go ahead and double CO2 in a lab and show us how the cylinder with 560PPM of CO2 is 1.5C warmer than the one at 280. Can you do that?
 
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