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Uncertainty, climate scenarios and adaptation
Suraje DessaiTyndall Centre for Climate Change Research, UK and
School of Environmental Sciences
University of East Anglia, Norwich, UK
CLIMATE CHANGE KIOSK EVENT CALENDAR
GLOBAL CLIMATE SCIENCE
Uncertainty in climate changeSEA -LEVELIMPACTSCL IM ATERAD IAT IVE
FORC INGCONC EN -TRAT IO N S
EM ISSION SSO C IETY /ECONOM Y
[Source: Carter, 2000]
Why might we need probabilities of climate change?
• To assess the seriousness of impacts we need to know how likely they are to occur (Schneider, 2001, 2002).
• Probabilities represent uncertainty explicitly and thus better fit a risk assessment framework: “the reason for quantifying risk it to make coherent risk management decisions under uncertainties and within resource constrains” (Pate-Cornell 1996); this allows decision-makers to hedge the risk of climate change
• Several communities (water resource managers and engineers) demand it!
• The central role played by prediction in guiding decision-making.
What are the problems in estimating probabilities?
• Probabilities only one method to represent uncertainties
• Confusion about probabilities, risk and uncertainty (various definitions and typologies)
Firm basis for probabilities
Shaky basis for probabilities
No basis for probabilities
Continuum of outcomes
Set of discrete outcomes
Outcomes poorly defined
Frequentistprobabilities
Subjective probabilities Scenario
analysis
Fuzzylogic
Ignorance
Knowledge aboutlikelihoods
Knowledge aboutoutcomes
Uncertainty
Risk
Firm basis for probabilities
Shaky basis for probabilities
No basis for probabilities
Continuum of outcomes
Set of discrete outcomes
Outcomes poorly defined
Frequentistprobabilities
Subjective probabilities Scenario
analysis
Fuzzylogic
Ignorance
Knowledge aboutlikelihoods
Knowledge aboutoutcomes
Uncertainty
Risk
Stirling (1998)
Incomplete vs unknowable knowledgeEpistemic vs stochastic uncertaintySubjective vs aleatory uncertaintyType B vs type A uncertaintyReducible vs irreducible uncertainty…
Different types of uncertainty in the context of climate change
Type of knowledge Type of uncertainty
Possible to represent with probabilities
Incomplete Epistemic Yes, but limited by knowledge
Incomplete-Unknowable
Natural stochastic Yes, but with limits
Unknowable Human reflexive No, scenarios required
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10
Climate sensitivity (K)
Cu
mu
lati
ve d
istr
ibu
tio
n f
un
ctio
n
Uniform Forest et al. (2002) Expert Forest et al. (2002)Gregory et al. (2002) Andronova & Schlesinger (2001)Expert Wigley & Raper (2001) IPCC TAR GCMs (2001)Knutti et al. (2002) Tol & de Vos (1998)IPCC range (1990-2001)
Emission scenarios
Global climate sensitivity
Regional climate change
Local climate change
0
0.01
0.02
0.03
0.04
0.05
0.06
0 1 2 3 4 5 6 7 8
Global mean temperature change (ºC)
p
SRES A1
SRES A2
SRES B1
SRES B2
IPCC TAR (2001)
0
0.05
0.1
0.15
0.2
0.25
0 1 2 3 4 5 6 7 8
Global mean temperature change (ºC)
p
SRES A1
SRES A2
SRES B1
SRES B2
2030
2070
2100
Mean precipitation change for Southeast Asia in 2100 under SRESA2-ASF
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
-50 -40 -30 -20 -10 0 10 20 30 40 50
PREC_djf
PREC_jja
Sensitivity of adaptation decision-making
Probability
Climate variable
A B C D E F G
Decisions
Adaptation decisions
A – Alternative supply required
B – Build new storage
C – Operations management changes
D – No changes required
E – Operations management changes
F – Develop small infrastructure
G – Develop big infrastructure
Sensitivity of adaptation decision-making
Probability
Climate variable
A B C D E F G
Decisions
Adaptation decisions
A – Alternative supply required
B – Build new storage
C – Operations management changes
D – No changes required
E – Operations management changes
F – Develop small infrastructure
G – Develop big infrastructure
Further reading
Dessai and Hulme (2003) Does climate policy need probabilities? Tyndall Working Paper 34
http://www.tyndall.ac.uk/publications/working_papers/wp34.pdf
