the ipcc and its dealing with uncertainty and errors · 25.04.2013 · the ipcc and its dealing...
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The IPCC and Its Dealing with Uncertainty and Errors A Dutch view
25 April 2013 | Arthur Petersen
Mission PBL Netherlands Environmental Assessment Agency contributes to improving the quality of political and administrative decision-making by conducting outlook studies, analyses and evaluations in which an integrated approach is considered paramount. Policy relevance is the prime concern in all our studies. We conduct solicited and unsolicited research that is always independent and scientifically sound.
25 April 2013 | Arthur Petersen
Formal basis: Government regulation for policy-analysis agencies
Organisational embedding: Ministry of Infrastructure and the Environment Clients: Ministry of Infrastructure and the Environment Several other ministries; e.g. Ministry of Economic Affairs and
Ministry of General Affairs European Union, UNEP, OECD
Governance structure
25 April 2013 | Arthur Petersen
PBL expertise
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
Structural products
Assessment of the Human Environment (biannual)
Nature Outlook (quadrennial) Assessment of Spatial Developments
(quadrennial) Trend reports (biannual) Compendium of the Environment
(in association with CBS en WUR) www.clo.nl
25 April 2013 | Arthur Petersen
Strategic multiannual programmes
Climate and energy transition agenda
Biodiversity, food security and development issues
Spatial developments beyond the systemic crisis
The importance of clusters and networks for the competitiveness
Infrastructure and sustainable urban regions
25 April 2013 | Arthur Petersen
Recent publications
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
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; it is the task of scientific advisers to report on the current state of knowledge, including uncertainties. Simulation models are indispensable.”
25 April 2013 | Arthur Petersen
Four claims regarding 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.
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
Funtowicz and Ravetz, Science for the Post Normal age, Futures, 1993
25 April 2013 | 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
25 April 2013 | 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?
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
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
25 April 2013 | Arthur Petersen
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
25 April 2013 | Arthur Petersen
“Two cold winters don't deny global warming” (2010)
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?
25 April 2013 | 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?
25 April 2013 | 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
25 April 2013 | Arthur Petersen
Estimates of present-day chance vary, depending on how cold the winters are
Global climate models and regional embedded models
Regional model
Global model
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | Arthur Petersen
25 April 2013 | 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.
25 April 2013 | 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 likelihood of an outcome or a result”
Draft SPM Final SPM
“assessed likelihood, using expert judgement, of an outcome or a result”
25 April 2013 | Arthur Petersen
Importance of identifying high-confidence findings
25 April 2013 | 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
25 April 2013 | Arthur Petersen
Quite some risk for losing uncertainty information
25 April 2013 | 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)
25 April 2013 | 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 1 E1a(2),E2,C5(2),
C6 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
25 April 2013 | 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
25 April 2013 | 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...
25 April 2013 | Arthur Petersen
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