1 estimating risk probabilities roger jones february 26 2009 centre for strategic economic studies...
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1WWW.VU.EDU.AU
ESTIMATING RISK PROBABILITIES
Roger JonesFebruary 26 2009
CENTRE FOR STRATEGIC ECONOMIC STUDIESBUSINESS AND LAW
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Structure of talk
• The problem with prediction• Estimating risk probabilities• Hedging adaptation and mitigation• How much climate change do we need to adapt to by
when?
3
Scales of approach
Global
Local
Economic resources
Infrastructure
Institutions
Technology
Information & skills
Equity
Indicators based on:
Adaptive capacity
Vulnerability (social)
Bottom-up approach
Economic resources
Infrastructure
Institutions
Technology
Information & skills
Equity
Indicators based on:
Adaptive capacity
Vulnerability (social)
Bottom-up approach
Impacts
Regionalisation
Global climate models
Global greenhouse gases
Vulnerability (physical)
World development
Top-down approach
Impacts
Regionalisation
Global climate models
Global greenhouse gases
Vulnerability (physical)
World development
Top-down approach
Past Present Future
Climate adaptation
policy
Climate adaptation
policy
Dessai and Hulme 2005
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Characterising uncertainty in AR4
0
1
2
3
4
5
-1 0 1 2 3 4 5 6 7 8 9 10
Global Mean Temperature Change (°C)
Pro
babi
lity
(%)
Likely
Very Likely
Virtually Certain
5
The likelihood of prediction
0
1
2
3
4
5
0 1 2 3 4 5 6 7 8 9 10
Global Mean Temperature Change (°C)
Pro
babi
lity
(%)
Virtually Certain
Highly Likely
Likely
As Likely As Not
Unlikely
Highly Unlikely
Exceptionally unlikely
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The likelihood of risk
0
1
2
3
4
5
6
1990 2010 2030 2050 2070 2090Year
Glo
bal m
ean
war
min
g (°
C)
.
Remote chance
Highly unlikely
Unlikely
As likely as not
Likely
Highly likely
Virtually certain
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Framing climate change risk
Almost certain
Highly likely
Least likely
Low probability, extreme outcomes
Damage to the most sensitive, many benefits
Increased damage to
many systems, fewer benefits
Considerable damage to most
systems
Moderately likely
Probability Consequence
Core benefits of adaptation and mitigation
Probability – the likelihood of reaching or exceeding a given level of global warmingConsequence – the effect of reaching or exceeding a given level of global warming
Risk = Probability × Consequence
Vulnerable to current climate
Happening now
Almost certain
Highly likely
Least likely
Low probability, extreme outcomes
Damage to the most sensitive, many benefits
Increased damage to
many systems, fewer benefits
Considerable damage to most
systems
Moderately likely
Probability Consequence
Core benefits of adaptation and mitigation
Probability – the likelihood of reaching or exceeding a given level of global warmingConsequence – the effect of reaching or exceeding a given level of global warming
Risk = Probability × Consequence
Vulnerable to current climate
Happening now
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0
20
40
60
80
100
0 100
Probability (%)
Sea
Lev
el R
ise
(cm
)
25 cm
50 cm
75 cm
0
20
40
60
80
100
0 100
Probability (%)
Sea
Lev
el R
ise
(cm
)
25 cm
50 cm
75 cm
0
20
40
60
80
100
0 100
Probability (%)
Se
a L
eve
l Ris
e (
cm)
25 cm
50 cm
75 cm
0
20
40
60
80
100
0 5 10
Probability (%)
Se
a L
eve
l Ris
e (
cm)
25 cm
50 cm
75 cm
0
20
40
60
80
100
0 5 10
Probability (%)
Se
a L
eve
l Ris
e (
cm)
25 cm
50 cm
75 cm
0
20
40
60
80
100
0 100
Probability (%)
Se
a L
eve
l Ris
e (
cm)
25 cm
50 cm
75 cm
25 cm
50 cm
75 cm
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The new global growth path
• Global growth has accelerated in the past decade, driven by the developing countries, especially China and India
• This growth is energy and coal intensive, and likely to continue• Realistic projections of energy use and CO2 emissions to 2030 are
above the SRES marker scenarios, including A1FI
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Implications for GHG emissions and atmospheric concentrations
• The implications this new growth path are explored by: • developing a reference case projections of CO2 emissions from fuel combustion to
2030• assuming that other emissions grow in a similar manner• developing policy emissions paths (minimum emissions paths)• explore CO2-e concentrations and temperatures in a simple climate model
• Minimum emissions paths (MEPs) from 2010 to 2030 were explored in Sheehan et al. GEC 2007
• The 2030 MEP resembles the SRES A1B “on steroids”• Current growth to 2100 under reference conditions resembles SRES
A1FI “on steroids”
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Minimum emissions paths 2010–2030
0
5
10
15
20
25
1990 2010 2030 2050 2070 2090
CO
2em
issi
ons
(Gt/y
r C)
Year
MEP2030 MEP 2025 MEP 2020
MEP 2015 MEP 2010
a)
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Likelihood of exceedance – range of reference and policy scenarios
0
1
2
3
4
5
6
7
1990 2010 2030 2050 2070 2090Year
Glo
bal m
ean
war
min
g (°
C)
.
RemotechanceHighlyunlikelyUnlikely
As likely asnotLikely
Highly likely
VirtuallycertainIPCC Low
IPCC High
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Framing adaptation
• Goal setting• Where do we want to go? (aspirational goals)• How do we want to get there?
• What are the risks? • What are the barriers? (e.g., lack of adaptive capacity)
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Planning horizons
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Operational pathways and aspirational goals
Operational pathways
Up-front responseStrong initial responseSome ongoing adjustment
Weak initial responseStrong late adjustment
Operational pathways
Up-front responseStrong initial responseSome ongoing adjustment
Weak initial responseStrong late adjustment
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How much climate change needs to be adapted to by when
Types of climate information required:• Climate variability (daily to decadal)• Ongoing rate of change• Past and near term commitments to climate change• Climate sensitivity• Regional climate change projections• Greenhouse gas emission policies (Mitigation)
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Reference and policy scenarios for hedging adaptation and mitigation
0
1
2
3
4
5
1990 2010 2030 2050 2070 2090
Year
Mea
n G
loba
l War
min
g (°
C)
Reference Policy Observations
Warming rate
Past and near-term
commitments
Climate sensitivity
Emission scenarios
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Hedging adaptation and mitigation – reference and policy scenarios
0
1
2
3
4
5
1990 2010 2030 2050 2070 2090
Year
Mea
n G
loba
l War
min
g (°
C)
Reference Policy Observations
Adaptation benefits
AD-MIT
Mitigation benefits
MIT-AD
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Hedging strategies between reference and policy scenarios with high policy uncertainty
0
1
2
3
4
5
6
7
1990 2010 2030 2050 2070 2090
Mea
n G
loba
l War
min
g (°
C)
Year
Adaptation Ad-Mit Mit-Ad Mitigation A1FI aug–MEP2030 MEP2010–2030
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Whole of climate approach
• Links current climate and adaptive responses with future possibilities • Ongoing variability and extremes are the main drivers of current adaptation to
climate, links between variability and longer-term change give these experiences a future dimension.
• Long-term fluctuations in natural climate variability may be affecting some regions• Not all change is anthropogenic
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Whole of climate approach
An understanding of the dynamics of climate variability is needed to:• Diagnose fluctuations, shifts or trends as temporary, persistent or
permanent. • If the dynamics of the change are not understood, statistical or other
methods can be used to explore “what if” questions based on understandings of climate model and historical behaviour.
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Regional example of climate changes – Melbourne, Australia
The Melbourne Region has experienced many step changes rather than trends
For a 1 by 1 degree area over greater Melbourne:Annual rainfall :statistically significant downward shift in 1996 in rainfall
from just over 900 mm to 750 mm, -17%. Max temp: Statistically significant upward step change 1998 of 0.6°C.
About half of this can be explained by the decrease in rainfall (due to a decrease in cloud cover). About half (0.3°C) is added warming
Analysis of annual frequency of days >35°C and >40°C not significant All days under 30°C have become significantly warmerDuring summer (DJF) almost 1°C warmer
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Regional example of impacts – south-eastern Australia
Streamflow: 60% up to 80% across western Victoria, 25–60% in eastern Victoria.Extreme fire weather index (temperature, lower humidity and higher winds):
100 on Black Friday in 1939, 115 on Ash Wednesday in 1983 150–200 on Black Saturday, February 2000
Viticulture: harvest 4–6 weeks earlier, crop losses, smoke damageHorticulture, dairy: under stress in irrigation regionsSnow: reduced snow coverHuman health (heat stress): hundreds(?) dead from heat stress, 220+ from fires,
event trauma, drought stress in rural regionsEnvironment: woodland birds decline, tree die-back accelerated, tree planting
failures, icon wetlands critical, frequent hot fires
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Exploring decision analysis
Post 1997 rain short term CV + climate
change
Post 1997 rain long term CV + climate
change
Post 1997 rain –climate change
Recovery expected soon, long-term
gradual reduction?
Partial recovery expected in decades
Serious long-term deficits
p1 p2 p3
Benefit if correctPenalty if incorrect
Benefit if correctPenalty if incorrect
Benefit if correctPenalty if incorrect
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Choosing climate information
• Understand risk and risk management options – how is climate information used in decision-making for specific risks?
• What is my planning horizon and operational pathway? E.g., up front, incremental, wait and see
• What’s my climate baseline?• Choose global scenarios based on sensitivity, risk tolerance and
hedging strategies – choose scenarios that are 50% likely to be exceeded to
• Determine local scaling and down-scaling needs for key climate variables
• Undertake assessment e.g., modelling, expert analysis
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Thresholds and key vulnerabilities
• Determine critical limits. E.g., sea level rise, storm severity or surge protection, flooding, public health limits, water quality and supply
• Diagnose specific climate conditions leading to critical limits• Establish plausible combinations of change in mean and variability,
natural and anthropogenic, leading to critical thresholds• Determine likelihood that such conditions may be exceeded within
planning horizons. For cities, many of these horizons will be long-term
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Caveats and working principles
• All probabilities are subjective – test different plausible assumptions to test whether outcomes (decisions on risk management) are sensitive to assumptions
• What information is required to make a specific decision? The less important climate is compared to other risk factors, the less precision will be required
• A 1°C warming in 2030 (from 1990) is as likely as not. From 2040+, considerable hedging between adaptation and mitigation is required. Without solid emissions policy, hedging for >3°C warming by 2100 needs to be contemplated.
• Sea level rise estimates need to consider outcomes not quantified in the AR4, including Greenland and perhaps West Antarctica
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ROGER N JONESBUSINESS AND LAWCENTRE FOR STRATEGIC ECONOMIC STUDIES
PHONE +61 3 9919 1992FAX +61 3 9919 1350EMAIL [email protected]
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