coping with uncertaintyuser.iiasa.ac.at/~gruebler/presentations/... · • first performed by yssp...
TRANSCRIPT
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Coping with Uncertainty
Arnulf Grublerwith Yuri Ermoliev and Arkady Kryazhimskiy
special thanks to:
Tanja Ermolieva, Volker Krey, Keywan Riahi, Alexey Smirnov
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Uncertainty and Systems Science
• Overview of uncertainty types• Description of uncertainties
(climate change & technology)• Improved decision making
(technology and insurance portfolios)
• Some IIASA highlights
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A Taxonomy of Uncertainties
• What’s the problem?Context and problem framing(linguistic) uncertainty
• How big is it?Data and modeling (epistemic) uncertainty
• What should be done about it?Policy response and effectiveness (contingency/agency) uncertainty
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Example Climate Change:Projected Global Mean Temperature Change
and Sources of Uncertainty
INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)
IPCC WG1 TAR: “By 2100, the range in the surface temperature response acrossthe group of climate models run with a given scenario is comparableto the range obtained from a single model run with the different SRES scenarios”
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Example Climate Change:Projected Global Mean Temperature Change
and Sources of Uncertainty
INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)
Baseline Uncertainty:50 % climate (sensitivity) modeling25% emissions (POP+GDP influence)25% emissions (TECH influence)
Uncertainty on extent and success of climate policies
IPCC WG1 TAR: “By 2100, the range in the surface temperature response acrossthe group of climate models run with a given scenario is comparable
to the range obtained from a single model run with the different SRES scenarios”
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Ask the Experts?• “Heavier-than-air flying machines are
impossible.” Lord Kelvin, 1895.
• “I think there is a world market for maybe five computers.” Tom Watson, IBM chair, 1943.
• “But what ... is it good for?” IBM engineer commenting on the microchip in 1968.
• “There is no need for any individual to have a computer in their home.” Ken Olson, President, Digital Equipment, 1977.
More fun: http://my.athenet.net/~jlindsay/SkepticQuotes.html
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Describing Technological Uncertainty
• Andrii Gritsevskyi and Nebojsa Nakicenovic
• Full technology uncertainty and impacts onemissions (climate change)
• All major TC mechanisms:innovation uncertainty, increasing returns, spillovers
• Builds on of increasing returns workof Brian Arthur
• Use of massive parallel computing
• Uncertainty distribution bi-modal,illustrating lock-in into alternate states
• Environmental characteristics and costs notcorrelated (clean can be as cheap as dirty)
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Emissions by 2100, GtC
Rel
ativ
e fr
eque
ncy
(per
cent
)
5 10 15 20 25 30
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Set of 520 technology dynamics
Emissions from 130,000 Scenarios of Technological Uncertainty
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Emissions from 130,000 Scenarios of Technological Uncertainty
Emissions by 2100, GtC
Rel
ativ
e fr
eque
ncy
(per
cent
)
5 10 15 20 25 30
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Set of 520 technology dynamics
Optimal set of 53technology dynamics(equal cost minima)
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Linguistic/Context Uncertainty:
What does this plant do?
Vienna waste incinerator bowing to “green” public
perception
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Linguistic/Context Uncertainty:
What does this plant do?
Vienna waste incinerator bowing to “green” public
perception
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Attainability Domain Analysis ofClimate Change Policy
• Analytical analysis of all possiblestates of Nordhaus’ DICE model
• Two policy variables:investment & emissions (abatement)
• First performed by YSSP Alexey Smirnov • Successive overlays of
-- objective function, revealing “indifference”…space (linguistic ambiguity of “optimality”)-- risk surfaces of catastrophic event …(thermohaline shut-down with different …climate sensitivities based on Keller et al.)
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Attainability Domain of DICE with original Optimality Point2100
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DICE Attainability Domain and Isolinesof Objective Function Surface
Percent of max. of objective function.Note the large “indifference” area
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Attainability Domain, Objective Function, and Thermohaline Collapse Risk Surfaces
Risk Surface of Thermohaline collapse(years of exposure 1990-2100)
climate sensitivity = 3 ºC
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Risk Surface of Thermohaline collapse(years of exposure 1990-2100)
climate sensitivity = 3.5 ºC
Attainability Domain, Objective Function, and Thermohaline Collapse Risk Surfaces
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Risk Surface of Thermohaline collapse(years of exposure 1990-2100)
climate sensitivity = 4 ºC
Attainability Domain, Objective Function, and Thermohaline Collapse Risk Surfaces
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Improved Decisions under Uncertainty
• Exploration of full uncertainty space• Explicit treatment of risk• Risk hedging via portfolio approach• Today (pars pro toto):
stochastic programming as applied to:- technology portfolios (Riahi/Krey)- insurance portfolio diversificationfor catastrophic risks (Ermolieva et al.)
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Technological Uncertainty : Patented but non-functional smoke-spark arrestors
Source: J. White, American Locomotives, 1968.
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Energy Technology Portfolio Investmentsand Resulting Cumulative Carbon Emissions
without uncertainty
Stochastic MESSAGE model (Keywan Riahi & Volker Krey)
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Energy Technology Portfolio Investmentsand Resulting Cumulative Carbon Emissions
under Uncertain Costs and Uncertain Carbon Taxes
Stochastic MESSAGE model (Keywan Riahi & Volker Krey)
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Risk Management: The Precautionary Principle?
Protective clothing for railway passengers (1847)
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Improved Decisions under Uncertainty
• Catastrophic risk management(e.g. floods, disease, earthquakes)
• Multi-agent and spatially explicit analysis
• Probabilistic “catastrophe generators”coupled with risk management (stochastic optimization)
• Example: Earthquake insurance risk management in Italy
• IIASA colleagues: T. Ermolieva, Y. Ermoliev, F. Fischer, G. MacDonald, et al.
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Study Region and Earthquake Scenario Generator
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Insurer 2Insurer 1
Initial Spread of Insurers’ Coverage
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Initial Spread with Insufficient Diversification
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Insurer 2Insurer 1
Optimized Spread
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Optimized Spread: No Risk of Bankruptcies
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Summary and Conclusion
• Important IIASA achievements• Recurrent threads:
-- multi-models, multi-disciplines -- treatment of risk as decision variable-- risk hedging -- address public goods problem
(environment, knowledge, spillovers)• Importance of patient, long-term basic
research strategy, recognizing long diffusion time