Uncertainty and controversy in environmental research Liew Xuan Qi (A0157765N) Cheong Hui Ping (A0127945W) Hong Chuan Yin (A0155305M)

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

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

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

1. Sources and types of uncertainty Expert elicitation

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

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

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

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

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.

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

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

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

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.

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?

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

Thank you:D Any Question?