Upload
august-nelson
View
214
Download
1
Tags:
Embed Size (px)
Citation preview
The IPCC as parliament of things
Dealing with uncertainty and value commitments in climate simulation
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
IBM SupercomputerEuropean Centre for Medium-Range Weather Forecasts
Warning:take into account uncertainty
in climate simulation
IPCC 2001: taking into account all uncertainties (including model uncertainty):
largest part of warming is ‘likely’ due to anthropogenic greenhouse gases
IPCC 2007: taking into account all uncertainties (including model uncertainty): largest part of warming is ‘very likely’ due
to anthropogenic greenhouse gases
de Kwaadsteniet versus van Egmond
de Kwaadsteniet:“Computer simulations are seductive due to their perceived speed, clarity and consistency. However, simulation models are not rigorously compared with data.”
van Egmond:“Policy makers are confronted with incomplete knowledge; task of scientific advisers to report on the current state of knowledge, including uncertainties. Simulation models are indispensable.”
13 March 2012 | Arthur Petersen
Simulation in scientific practice
Definition of computer simulation:“mathematical 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
13 March 2012 | Arthur Petersen
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’)
13 March 2012 | Arthur Petersen
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.
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
Funtowicz and Ravetz, Science for the Post Normal age, Futures, 1993
13 March 2012 | Arthur Petersen
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
13 March 2012 | Arthur Petersen
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?
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
2222
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
13 March 2012 | Arthur Petersen
2323
Lessons learnt in uncertainty communication (II)
4. Recognizing ignorance often more important than characterizing statistical uncertainty
5. Communicate uncertainty in terms of societal/political risks
13 March 2012 | Arthur Petersen
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.
13 March 2012 | Arthur Petersen
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)
13 March 2012 | Arthur Petersen
“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?
13 March 2012 | Arthur Petersen
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?
13 March 2012 | Arthur Petersen
Eleven city marathon
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
0.0
0.1
0.2
0.3
0.4
0.5
Cha
nce
for
a m
arat
hon
Et
4.0
6.7
3.3
Ave
rage
ret
urn
peri
od (
year
s)
Annual chance for an 'Elfstedentocht'95% confidence limits (approx.)
20
10
5.0
2.5
Projections for 2050 for four scenarios: once every 18, 29, 55 or 183 years
13 March 2012 | Arthur Petersen
What is the impact of weather extremes, how can we adapt?
13 March 2012 | Arthur Petersen
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
13 March 2012 | Arthur Petersen
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
13 March 2012 | Arthur Petersen
Global climate models and regional embedded models
Regional model
Global model
13 March 2012 | Arthur Petersen
Different sources of uncertainty - Global
Source: E. Hawkins & R. Sutton, Bull. of Amer. Meteor. Soc., aug. 2009, 1097-1107
13 March 2012 | Arthur Petersen
Different sources of uncertainty - Regional
Source: E. Hawkins & R. Sutton, Bull. of Amer. Meteor. Soc., aug. 2009, 1097-1107
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
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.
13 March 2012 | Arthur Petersen
Example from the IPCC WG I 2007 (continued)
“Very likely” means a chance >90%. But what kind of probability are we dealing with here?
“assessed likelihoodof an outcome or a result”
Draft SPMFinal SPM
“assessed likelihood, using expert judgement, of an outcome or a result”
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
13 March 2012 | Arthur Petersen
Importance of identifying high-confidence findings
13 March 2012 | Arthur Petersen
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
13 March 2012 | Arthur Petersen
Quite some risk for losing uncertainty information
13 March 2012 | Arthur Petersen
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)
13 March 2012 | Arthur Petersen
Errors and shortcomings in AR4 WG II (8 chapt.)Table SPM.2 Additional
Major Minor#S Major Minor #S
Africa C3,C5,C7 E1b,C3 3 E1a,C4 E1b 3
Asia C2,C3 1 C3,C6 E2 2
Aust & NZ E2,C3 1 C1 C4,E1a 3
Europe C3 1 E1a,C3(3),C4 5
L America C2 1E1a(2),E2,C5(2),C
6 6
N America C3 1
Poles
Islands 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
13 March 2012 | Arthur Petersen
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
13 March 2012 | Arthur Petersen
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...
13 March 2012 | Arthur Petersen