The “User Metric” Concept cfab.eas.gatech/usermetric.html

1. The “User Metric” Concepthttp://cfab.eas.gatech.edu/usermetric.html

2. Contents 1. Introduction 2. Concept 3. Problem 4. Providers

3. Concept • User metric concept • Combining probabilistic forecasts with knowledge from the user community to provide a metric for optimal choice.

4. Problem • Issues to address: • A user community is faced with making an absolute decision (yes or no). • Forecasts are in the form of probabilities. • How can we use probabilistic forecasts to provide the best information to the user community? • Can only occur with incorporation of user information.

5. Providers 1. Forecaster provider 2. User community provider

6. Forecaster provides: • Probabilities of particular event occurring at a particular time at a particular intensity

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8. User community provides: • An assessment of the cost if a certain phenomena were to occur with a particular intensity. • This may be quantified to provide the cost of occurrence of a phenomena. • Community input provides an assessment of the cost of a strategy if an event were to occur.

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10. The user metric . . . • Takes the probabilistic forecast and the statistics provided by the user community to produce…. • A statistical assessment of the aggregate risk of taking a particular action so that…. • The user community can choose an optimal strategy given all of the available information.

11. User Metric Flowchart Forecaster User Community Flow of input User Metric

12. User Metric Flowchart

13. Scenarios 1. Simple example 2. Typical situation 3. Scenario A: 4. Scenario B: 5. Scenario C:

14. Scenarios 1. Simple example . . . • What is the best strategy for harvesting crops • for a particular forecast? • Are there some strategies better than others? • We assume that the farming community may • harvest all crops early with reduced yield, • harvest a certain % early and the rest later, • or all later - noting that the closer to maturation, • the greater the crop yield. • What is the risk in making a particular decision?

15. Scenarios 2. Typical situation may be . . . • Over successive periods forecasts of rainfall indicate: • Initially decreases (A) • Increases significantly (B) • Decreases slightly (C)

16. Scenarios A, B and C B C A

17. Scenarios Scenario A: • Rainfall probabilities suggest that there will be significant decreases in rainfall amounts A

18. Scenario A

19. Scenario A

20. Scenario A

21. Scenarios Scenario B: • Rainfall forecast probabilities suggest that rainfall will increase dramatically B

22. Scenario B

23. Scenario B

24. Scenarios Scenario C: • Forecast probabilities indicate that rainfall will decrease moderately C

25. Scenario C

26. Scenario C

27. Scenario C

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32. Chart Documents

33. Dissemination Process Interpretation Dissemination Forecaster End User Modeller Data

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