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The “User Metric” Concept
http://cfab.eas.gatech.edu/usermetric.html
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Contents
1. Introduction 1. Introduction
2. Concept 2. Concept
3. Problem 3. Problem
4. Providers 4. Providers
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Concept
User metric concept
Combining probabilistic forecasts with knowledge from the user community to provide a metric for optimal choice.
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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.
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Providers
1. Forecaster provider 1. Forecaster provider
2. User community provider 2. User community provider
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Forecaster provides:
Probabilities of particular event occurring at a particular time at a particular intensity
ECMWF: Sept. 9-13, 2002ECMWF: Sept. 9-13, 2002
Discharge Probabilities as Computed in April, 1998
Discharge Probabilities as Computed in April, 1998
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Do you have anything to say here?
ECMWF: Sept. 9-13, 2002ECMWF: Sept. 9-13, 2002
Discharge Probabilities as Computed in April, 1998
Discharge Probabilities as Computed in April, 1998
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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.
100-0 75-2550-50 25-75
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Med. Flood
Light Flood
No Flood
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Do you have anything to say here?
100-0 75-2550-50 25-75
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Med. Flood
Light Flood
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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.
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User Metric Flowchart
ForecasterForecasterUser CommunityUser Community
User Metric User Metric
Flow of input
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User Metric Flowchart
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Scenarios
1. Simple example 1. Simple example
2. Typical situation 2. Typical situation
3. Scenario A: 3. Scenario A:
4. Scenario B: 4. Scenario B:
5. Scenario C: 5. Scenario C:
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Scenarios
1. Simple example . . . 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?
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?
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Scenarios
2. Typical situation may be . . . 2. Typical situation may be . . .
Over successive periods forecasts of rainfall indicate:
Initially decreases (A) Increases significantly (B) Decreases slightly (C)
Over successive periods forecasts of rainfall indicate:
Initially decreases (A) Increases significantly (B) Decreases slightly (C)
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Scenarios A, B and C
AB C
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Scenarios
Scenario A: Scenario A:
Rainfall probabilities suggest that there will be significant decreases in rainfall amounts
Rainfall probabilities suggest that there will be significant decreases in rainfall amounts
A
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Scenario A
65%
25%
8% 2%
No Rain
Light rain
Mod. Rain
Heavy Rain
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Scenario A
100-0 75-25 50-50 25-75 10-90 0-100
Heavy Rain
Light Rain0
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Heavy Rain
Mod. Rain
Light Rain
No Rain
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Scenario A
Yield Based on Aggregate Risk
74
76
78
80
82
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86
88
100-0 75-25 50-50 25-75 10-90 0-100
Action (now-later)
Perc
enta
ge C
rop Y
ield
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Scenarios
Scenario B: Scenario B:
Rainfall forecast probabilities suggest that rainfall will increase dramatically
Rainfall forecast probabilities suggest that rainfall will increase dramatically
B
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Scenario B
5%
15%
50%
30%
No Rain
Light rain
Mod. Rain
Heavy Rain
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Scenario B
Yield Based on Aggregate Risk
0102030405060708090
100-0 75-25 50-50 25-75 10-90 0-100
Action (now-later)
Perc
enta
ge C
rop Y
ield
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Scenarios
Scenario C: Scenario C:
Forecast probabilities indicate that rainfall will decrease moderately
Forecast probabilities indicate that rainfall will decrease moderately
C
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Scenario C
15%
55%
25%
5%
No Rain
Light rain
Mod. Rain
Heavy Rain
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Scenario C
100-0 75-25 50-50 25-75 10-90 0-100
Heavy Rain
Light Rain0
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Heavy Rain
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Scenario C
Yield Based on Aggregate Risk
0102030405060708090
100-0 75-25 50-50 25-75 10-90 0-100
Action (now-later)
Perc
enta
ge C
rop Y
ield
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Chart Documents
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Dissemination Process
Forecaster
Interpretation
Dissemination
End User
ModellerData
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