[Vision2020] Skeptics Confirmation Bias Filter?" Climate Sensitivity Probability: MIT Integrated Global System Model 2009: Median Surface Warming 2091–2100: 4.1-5.1 °C

[Ted Moffett]

And again, why trust the competence of climate scientists at MIT?  They also
are deluded fools, indulging in unjustified assertions of a high probability
that human impacts on climate are profound, who need to be set straight that
their analysis is too doubtful, by certain Vision2020 participants, or so it
seems someone implies...

Odd that neither the recent reports from the National Academy of Sciences on
human impacts on climate, or this MIT study, which I posted to
Vision2020,.resulted in a response from anyone... This might imply someone
has a confirmation bias filter that ignores credible competent science that
does not fit their preconceptions...
---------------------------
Quotes from MIT website regarding the MIT study that this post references:

http://globalchange.mit.edu/resources/gamble/no-policy.html

"The "roulette" wheel below depicts the MIT Joint Program's estimation of
the range of probability of potential global warming over the next hundred
years..."

"...the smallest predicted change, less than 3 °C (shown in blue), has a
probability of less than 1% (1 in 100 odds)."
-------------------------
Discussion of predictions regarding climate sensitivity (increase in global
average temperature from a doubling of atmospheric CO2 level) sometimes
focuses on the lower range of possible temperature increases, below 2
degrees Celsius, to argue that the impacts of anthropogenic climate warming
are not probable enough to take profound action to address the problem.  But
what are the probabilities of minimal impacts, compared to the more costly,
such as global coastal flooding from sea level rise?

The MIT study referenced below indicates the odds of minimal impacts from
anthropogenic climate warming are far less probable than very costly
impacts.  Those who argue policy should be based on the improbable low range
of temperature increases from human greenhouse gas emissions and other human
impacts are making a very risky bad bet on the future of humanity and life
on Earth.

A brief article summarizing the findings of this study regarding the range
of probabilities for different values of temperature increases is at the
first website below, followed by a reference to the paper published in the
"Journal of Climate":


[image: The MIT Joint Program on the Science and Policy of Global Change]

http://globalchange.mit.edu/resources/gamble/no-policy.html

-----------------
http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI2863.1

Journal of Climate 2009; 22: 5175-5204

Probabilistic Forecast for Twenty-First-Century Climate Based on
Uncertainties in Emissions (Without Policy) and Climate Parameters

*A. P. Sokolov, P. H. Stone, C. E.
Forest*<http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI2863.1#n101>,
R. Prinn, M. C.
Sarofim+<http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI2863.1#n102>,
M. Webster#<http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI2863.1#n103>,
S. Paltsev, and C. A. Schlosser*

Joint Program on the Science and Policy of Global Change, Massachusetts
Institute of Technology, Cambridge, Massachusetts
*D. Kicklighter*

The Ecosystems Center, Marine Biological Laboratory, Woods Hole,
Massachusetts
*S. Dutkiewicz, J. Reilly, and C. Wang*

Joint Program on the Science and Policy of Global Change, Massachusetts
Institute of Technology, Cambridge, Massachusetts
*B. Felzer@<http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI2863.1#n104>and
J. M. Melillo
*

The Ecosystems Center, Marine Biological Laboratory, Woods Hole,
Massachusetts
*H. D. Jacoby*

Joint Program on the Science and Policy of Global Change, Massachusetts
Institute of Technology, Cambridge, Massachusetts

  Abstract

The Massachusetts Institute of Technology (MIT) Integrated Global System
Model is used to make probabilistic projections of climate change from 1861
to 2100. Since the model’s first projections were published in 2003,
substantial improvements have been made to the model, and improved estimates
of the probability distributions of uncertain input parameters have become
available. The new projections are considerably warmer than the 2003
projections; for example, the median surface warming in 2091–2100 is 5.1°C
compared to 2.4°C in the earlier study. Many changes contribute to the
stronger warming; among the more important ones are taking into account the
cooling in the second half of the twentieth century due to volcanic
eruptions for input parameter estimation and a more sophisticated method for
projecting gross domestic product (GDP) growth, which eliminated many
low-emission scenarios.

However, if recently published data, suggesting stronger twentieth-century
ocean warming, are used to determine the input climate parameters, the
median projected warming at the end of the twenty-first century is only
4.1°C. Nevertheless, all ensembles of the simulations discussed here produce
a much smaller probability of warming less than 2.4°C than implied by the
lower bound of the Intergovernmental Panel on Climate Change (IPCC) Fourth
Assessment Report (AR4) projected likely range for the A1FI scenario, which
has forcing very similar to the median projection in this study. The
probability distribution for the surface warming produced by this analysis
is more symmetric than the distribution assumed by the IPCC because of a
different feedback between the climate and the carbon cycle, resulting from
the inclusion in this model of the carbon–nitrogen interaction in the
terrestrial ecosystem.

Keywords: Probability
forecasts/models<http://journals.ametsoc.org/action/doSearch?action=runSearch&type=advanced&result=true&prevSearch=keywordsfield%3A(%22Probability+forecasts/models%22)>,
Climate prediction<http://journals.ametsoc.org/action/doSearch?action=runSearch&type=advanced&result=true&prevSearch=keywordsfield%3A(%22Climate+prediction%22)>,
Anthropogenic effects<http://journals.ametsoc.org/action/doSearch?action=runSearch&type=advanced&result=true&prevSearch=keywordsfield%3A(%22Anthropogenic+effects%22)>,
Numerical analysis/modeling<http://journals.ametsoc.org/action/doSearch?action=runSearch&type=advanced&result=true&prevSearch=keywordsfield%3A(%22Numerical+analysis/modeling%22)>,
Feedback<http://journals.ametsoc.org/action/doSearch?action=runSearch&type=advanced&result=true&prevSearch=keywordsfield%3A(%22Feedback%22)>

Received: September 29, 2008; Accepted: March 19, 2009

* Current affiliation: Department of Meteorology, The Pennsylvania State
University, University Park, Pennsylvania.

+ AAAS Science and Technology Policy Fellow, Washington, D.C.

# Current affiliation: Engineering Systems Division, Massachusetts Institute
of Technology, Cambridge, Massachusetts.

@ Current affiliation: Department of Earth and Environmental Sciences,
Lehigh University, Bethlehem, Pennsylvania.

*Corresponding author address:* Andrei Sokolov, Joint Program on the Science
and Policy of Global Change, Massachusetts Institute of Technology, 77
Massachusetts Ave., E40-431, Cambridge, MA 02139. Email: sokolov at mit.edu
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Vision2020 Post: Ted Moffett
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