1. Uncertainty and controversy in environmental research
Liew Xuan Qi (A N)
Cheong Hui Ping (A W)
Hong Chuan Yin (A M)

2. Best Practice Approaches for Characterizing, Communicating, and Incorporating Scientific Uncertainty in Climate Decision Making
U.S. Climate Change Science Program Synthesis and Assessment Product 5.2
January 2009

3. Sources and Types of Uncertainty
The Importance of Quantifying Uncertainty
Cognitive Challenges in Estimating Uncertainty
Statistical Methods and Models
Methods for Estimating Uncertainty
Propagation and Analysis of Uncertainty
Making Decisions in the Face of Uncertainty
Communicating Uncertainty

4. 1. Sources and types of uncertainty
Random error in measurement
“Systematic” error in measurement

5. 1. Sources and types of uncertainty
Expert elicitation

6. 1. Sources and types of uncertainty
probability distributions
“model” uncertainty
ignorance

7. 2. The Importance of Quantifying Uncertainty
Odds
What are the odds of Liverpool winning this Sunday?
Highly Likely
Highly Unlikely

8. 3. Cognitive Challenges in Estimating Uncertainty
“cognitive heuristics”
brains make some judgments
estimating and making decisions about uncertainty
involves unconsciously using some simple rules
Over-confidence of uncertainty

9. 4. Statistical Methods and Models
Methods to assess how well alternative mathematical models fit existing evidence
Hypothesis testing
Model selection

10. 5. Methods for Estimating Uncertainty
climate sensitivity
amount of warming that would result if the concentration of carbon dioxide in the atmosphere is doubled and then held constant
expert judgments in the form of probability distributions
careful consideration and synthesis of all the data, model results, and theoretical arguments
overall level of uncertainty by individual > uncertainty from consensus panels suchas those of the IPCC.

11. 6. Propagation and Analysis of Uncertainty
Probabilistic descriptions
Known key quantities
value in their own right as an input to research planning and in a variety of assessment activities.
stochastic simulation
analysis over and over again on a fast computer
using different input values
single model to estimate “optimal”
highest “expected value” (i.e., offers the best bet).
However, models are uncertain so not wise to do so

12. 7. Making Decisions in the Face of Uncertainty
Irreducible uncertainty is not one of them
Decision analysis
framing and analyzing complex decisions
consistent and rational way.
Behavioral Decision Theory
how and why people make decisions in the way that they do

13. In the face of high uncertainty:
Resilient Strategies
Identify the range of future circumstances
seek to identify approaches that will work
across that range
Adaptive Strategies
choose strategies that can be modified for better performances
When learn more about the issues
And how future is unfolding
Precautionary Principle
incorporates ideas of resilient or adaptive policy

14. 8. Communicating Uncertainty
Psychologist Baruch Fischhoff and colleagues suggest that:
Either will work, if they’re used consistently
In isolation: present the result both in terms of odds and probabilities.
Probably more confusion about what is meant by the specific events being discussed than about the numbers attached to them.

15. In conclusion: Does what we are doing make sense?
Are there other important factors that are equally or more important than the factors we are considering?
Are there key correlation structures in the problems that are being ignored?

16. In conclusion:
Are there normative assumptions and judgments about which we are not being explicit?
Is information about the uncertainties related to research results and potential policies being communicated

18. Thank you:D Any Question?