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The IPCC as parliament of things Dealing with uncertainty and value commitments in climate simulation

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The IPCC as parliament of things Dealing with uncertainty and value commitments in climate simulation 13 March 2012 | Arthur Petersen Different sources of uncertainty ... – PowerPoint PPT presentation

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Title: The IPCC as parliament of things Dealing with uncertainty and value commitments in climate simulation


1
The IPCC as parliament of thingsDealing with
uncertainty and value commitments in climate
simulation
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IBM SupercomputerEuropean Centre for
Medium-Range Weather Forecasts
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IPCC 2001 taking into account all uncertainties
(including model uncertainty) largest part of
warming is likely due to anthropogenic
greenhouse gases
Warning take into account uncertainty in
climate simulation
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IPCC 2007 taking into account all uncertainties
(including model uncertainty) largest part of
warming is very likely due to anthropogenic
greenhouse gases
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de Kwaadsteniet versus van Egmond
  • de KwaadstenietComputer simulations are
    seductive due to their perceived speed, clarity
    and consistency. However, simulation models are
    not rigorously compared with data.
  • van EgmondPolicy makers are confronted with
    incomplete knowledge task of scientific advisers
    to report on the current state of knowledge,
    including uncertainties. Simulation models are
    indispensable.

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Simulation in scientific practice
  • Definition of computer simulationmathematical
    model that is implemented on a computer and
    imitates real-world processes
  • Functions of simulation
  • technique (to investigate detailed dynamics)
  • heuristic tool (to develop hypotheses, theories)
  • substitute for an experiment
  • tool for experimentalists
  • pedagogical tool

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Central activities in simulation practice
  • Formulating the mathematical model(conceptual
    and mathematical model ideas)
  • Preparing the model inputs(model inputs
    marks)
  • Implementing and running the model(technical
    model implementation things)
  • Processing the data and interpreting
    them(processed output data marks)

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Four claims re. climate simulation
  1. Different models give conflicting descriptions of
    the climate system.
  2. There exists no unequivocal methodology for
    climate simulation.
  3. The assumptions in climate simulations are
    value-laden.
  4. Pluralism in climate modelling is an essential
    requirement both for good science and for
    appropriate science advising.

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Funtowicz and Ravetz, Science for the Post Normal
age, Futures, 1993
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The challenge of post-normal science
  • Expert advisers should be reflexive
  • Methods for dealing with uncertainty should
    merely be considered as tools, not as the
    solutions
  • Fear for paralysis in policy making should not be
    allowed to block communication about uncertainty
  • Communication with a wider audience about
    uncertainties is crucial

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Shifting notions of reliability
  • Statistical reliability (expressed in terms of
    probability)
  • How do you statistically assess climate
    predictions?
  • Methodological reliability (expressed
    qualitatively in terms of weak/strong points)
  • How do you determine the methodological quality
    of the different elements in simulation practice,
    given the purpose of the model?
  • Public reliability (expressed in terms of public
    trust)
  • What determines public trust in modellers?

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Lesson learnt in uncertainty communication (I)
  1. Conditional character of probabilistic
    projections requires being clear on assumptions
    and potential consequences (e.g. robustness,
    things left out)
  2. Room for further development in probabilistic
    uncertainty projections how to deal decently
    with model ensembles, accounting for model
    discrepancies
  3. There is a role to be played for knowledge
    quality assessment, as complementary to more
    quantitative uncertainty assessment

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Lessons learnt in uncertainty communication (II)
  • Recognizing ignorance often more important than
    characterizing statistical uncertainty
  • Communicate uncertainty in terms of
    societal/political risks

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A case of deep uncertainty adaptation to changes
in extreme weather in the Netherlands
  • Extreme weather events are predominantly
    associated with the risk of flooding, which is
    generally considered a government responsibility.
  • However, future projections for the Netherlands
    provide a picture which is somewhat more complex.
    The changes require awareness among society at
    large.
  • Yet, individuals and economic sectors have
    already dealt with the weather for ages and have
    developed knowledge and behavioural responses
    with respect to weather extremes.

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Notions from the policy sciences and social
psychology
  • Articulation(views with respect to extreme
    weather are not always coherent)
  • Information(access to information shapes
    articulation)
  • Differentiation(different perspectives lead to
    different assessments of risk and potentials)
  • Learning by interaction(stakeholders and
    scientists can learn from interacting, by which
    preferences for, possibly new, policy options
    evolve)

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Two cold winters don't deny global warming
  • Dutch winter 2009-2010 coldest since 1996
  • Questions one may ask
  • How 'extreme' was this?
  • Will this happen less (or more...) often in the
    future?
  • Does this fit in the 'Global Warming'-picture?
  • How to optimally adapt to changes in extremes?

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Eleven city marathon
  • Marathon has been organized 15 times in the
    period 1901-2008, in the province of
    Friesland
  • How has the chance for holding a marathon changed
    over the past century?
  • How will it change in the future?

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Eleven city marathon
Projections for 2050 for four scenarios once
every 18, 29, 55 or 183 years
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What is the impact of weather extremes, how can
we adapt?
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Bridging the gap between science and policy
  • Uncertainties with respect to climate change and
    extreme weather events knowledge about future is
    based on models
  • Need for adaptive governanceand for methodology
    to assesspolicy options with different,even
    conflicting, outcomes
  • Need for indicators ofoutcomes for
    evaluatingpolicy options relevant
    forstakeholders and reliablefor scientists

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Bridging the gap selected approach
  • Two postdoctoral studies
  • Social scientist engaging with the stakeholders
    analysing the process co-developing adaptation
    options
  • Statistician/climate scientist studying the
    uncertainty range of climate projections and
    decadal predictions of weather extremes
    co-developing indicators
  • Team of political scientists,statisticians,
    climate modellers,social scientists

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Global climate models and regional embedded models
Global model

Regional model
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Different sources of uncertainty - Global
  • Source E. Hawkins R. Sutton, Bull. of Amer.
    Meteor. Soc., aug. 2009, 1097-1107

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Different sources of uncertainty - Regional
  • Source E. Hawkins R. Sutton, Bull. of Amer.
    Meteor. Soc., aug. 2009, 1097-1107

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Example from the Intergovernmental Panel on
Climate Change WG I (2007)
  • Most of the observed increase in globally
    averaged temperatures since the mid-20th century
    is very likely due to the observed increase in
    anthropogenic greenhouse gas concentrations12.
    (SPM)

12 Consideration of remaining uncertainty is
based on current methodologies.
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Example from the IPCC WG I 2007 (continued)
  • Very likely means a chance gt90. But what kind
    of probability are we dealing with here?

assessed likelihoodof an outcome or a result
assessed likelihood, using expert judgement, of
an outcome or a result
Draft SPM
Final SPM
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Importance of identifying high-confidence findings
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Process Openness, peer review, supervision
  • Openness PBL registration website for possible
    errors
  • 40 reactions in total 3 of which relevant for
    our investigation
  • Draw on IPCC authors to give feedback
  • Internal and external peer review
  • Independent supervision by KNAW Royal Netherlands
    Academy of Arts and Sciences

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Quite some risk for losing uncertainty information
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What can go wrong?
  • E1 Inaccurate statement
  • E1a Errors that can be corrected by an erratum
    (5)
  • E1b Errors that require a redoing of the
    assessment of the issue at hand (2)
  • E2 Inaccurate referencing (3)
  • C1 Insufficiently substantiated attribution (1)
  • C2 Insufficiently founded generalization (2)
  • C3 Insufficiently transparent expert judgment
    (10)
  • C4 Inconsistency of messages (2)
  • C5 Untraceable reference (3)
  • C6 Unnecessary reliance on grey referencing (2)
  • C7 Statement unavailable for review (1)

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Errors and shortcomings in AR4 WG II (8 chapt.)
Table SPM.2 Table SPM.2 Table SPM.2 Table SPM.2 Table SPM.2 Additional Additional Additional Additional Additional
Major Major Minor Minor S Major Major Minor Minor S
Africa Africa C3,C5,C7 C3,C5,C7 E1b,C3 E1b,C3 3 E1a,C4 E1a,C4 E1b E1b 3
Asia Asia C2,C3 C2,C3 1 C3,C6 C3,C6 E2 E2 2
Aust NZ Aust NZ E2,C3 E2,C3 1 C1 C1 C4,E1a C4,E1a 3
Europe Europe C3 C3 1 E1a,C3(3),C4 E1a,C3(3),C4 5
L America L America C2 C2 1 E1a(2),E2,C5(2),C6 E1a(2),E2,C5(2),C6 6
N America N America C3 C3 1
Poles Poles
Islands Islands E2,C3 E2,C3 2
Total E E1b, E2 2 2 E1a 1 E1a(4),E1b,E2(3) 8 8
Total C C2(2),C3(2) C5, C7 6 C3(4) 4 6 C3,C4,C6,C1 4 C3(3),C4,C5(2),C6 8 13
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The IPCC science or politics?
  • Assessments are social constructs that contain
    both scientific and political elements
  • Successful? Depends on ability to connect to
    climate science and policy
  • Generally voiced criticism IPCC not open enough
    to skeptics

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The IPCC science or politics? (II)
  • Practice procedures ensure inclusivity skeptics
    do have influence reflexivity on dissensus is
    moderate (neither low nor high)
  • Not scientific consensus. But
    policy-relevant assessment acknowledging
    uncertainty
  • Still, the communication of uncertainty can be
    further improved
  • The IPCC acts as a Latourian Parliament of
    Things if only the actors would admit...
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