msu schneider2007
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Stephen H. Schneider* Department of Biological Sciences
and Woods Institute for the Environment Stanford University, California, USA.
*[Website for more info: www.climatechange.net.]
“Key Vulnerabilities” and the Risks of Climate Change?
Michigan State University Ides of March 2007
The role of the scientific community #1: Provide climate change scenarios
The IPCC’s Special Report on Emissions Scenarios (SRES) 2000
What will be our future emissions?
Higher
Lower
Source: Intergovernmental Panel on Climate Change
WG 1Approved AR 4 SPM: In this Summary for Policymakers, the following terms have been used to indicate the assessed likelihood, using expert judgment, of an outcome or a result: Virtually certain > 99% probability of occurrence, Extremely likely > 95%, Very likely > 90%, Likely > 66%, More likely than not > 50%, Unlikely < 33%, Very unlikely < 10%, Extremely unlikely < 5%.
Approved uncertainties language for 1033% likelihood: “unlikely”
???
Pre Plenary proposed
“Low”
“High”
From the Sports Pages: Type 1 Error Aversion
Denver is allowing 7.3 points per game. Broncos defensive end Kenard Lang was asked to predict a point total for the Colts offense this Sunday:
"I‘m not predicting nothing. All I'm going to predict is a good game and I'm hoping the Broncos come out on top. If I make predictions and it goes the opposite way, then I'll look like a horse's fanny. And I ain't trying to look like a horse's fanny right now."
From the Sports Pages: Type 1 Error Aversion
Denver is allowing 7.3 points per game. Broncos defensive end Kenard Lang was asked to predict a point total for the Colts offense this Sunday:
"I'm not predicting nothing. All I'm going to predict is a good game and I'm hoping the Broncos come out on top. If I make predictions and it goes the opposite way, then I'll look like a horse's fanny. And I ain't trying to look like a horse's fanny right now."
From the Sports Pages: Type 1 Error Aversion
Denver is allowing 7.3 points per game. Broncos defensive end Kenard Lang was asked to predict a point total for the Colts offense this Sunday: "I'm not predicting nothing. All I'm going to predict is a good game and I'm hoping the Broncos come out on top. If I make predictions and it goes the opposite way, then I'll look like a horse's fanny. And I ain't trying to look like a horse's fanny right now."
“Type 1” versus “Type 2" errors and their consequences
Type 2 error
Correct Decision
Reject or ignore forecast (e.g., “too much” uncertainty)— no policy response
Correct decision
Type I error
[Squandered resources]
Accept forecast— policy response follows
Forecast proves true
Forecast proves false
Decision
“Type 1” versus “Type 2" errors and their consequences
Type 2 error [Unmitigated damages]
Correct Decision
Reject or ignore forecast (e.g., “too much” uncertainty)— no policy response
Correct decision
Type I error
[Squandered resources]
Accept forecast— policy response follows
Forecast proves true
Forecast proves false
Decision
“Type 1” versus “Type 2" errors and their consequences
************************************************* Role of Scientists: Assess Risk (= Consequence X Probability of Occurrence) as function of alternative policy choices ; confidence in the assessment of risks; distribution of risks and benefits; traceable account of aggregations. Role of Decisionmakers: Negotiate acceptability of risks and policies that alter risks; make policy choices; guide assessment process.
Type 2 error Correct Decision Reject or ignore forecast (e.g., “too much” uncertainty)—no policy response
Correct decision Type I error Accept forecast—policy response follows
Forecast proves true
Forecast proves false
Decision
“Type 1” versus “Type 2" errors and their consequences
************************************************* Role of Scientists: Assess Risk (= Consequence X Probability of Occurrence) as function of alternative policy choices ; confidence in the assessment of risks; distribution of risks and benefits; traceable account of aggregations. Role of Decisionmakers: Negotiate acceptability of risks and policies that alter risks; make policy choices; guide assessment process.
Type 2 error Correct Decision Reject or ignore forecast (e.g., “too much” uncertainty)—no policy response
Correct decision Type I error Accept forecast—policy response follows
Forecast proves true
Forecast proves false
Decision
Competing paradigms between science and policy communities.
It is common in policy analysis to refer to an incorrect forecast that was taken to be true as a “type 1 error” and a decision to ignore an uncertain forecast that turns out to be true as a “type 2 error”. The prime paradigm within the scientific community is to view the type 1 error as the more egregious mistake, whereas within the policy arena, the type 2 error is often more concerning. Decisionmakers often prefer to hedge against a potentially damaging event rather than wait for it to possibly happen.
Chapter 19 (draft, do not quote) identifies seven criteria for assessing and defining key vulnerabilities:
• magnitude • distribution • timing • persistence and reversibility • likelihood and confidence • potential for adaptation • “importance” of the vulnerable system
No single metric can adequately aggregate the diversity of key vulnerabilities, nor determine their ranking.
What will be our future emissions?
Higher
Lower
Source: Intergovernmental Panel on Climate Change
Nearly stabilized at 2100
Not nearly stabilized at 2100
Emissions Scenarios Emissions Scenarios
0
1
2
3
4
5
6
2000 2050 2100 2150 2200 2250 Year
Radiative Forcing 600 ppm CO 2 e
500 ppm CO 2 e
(O’Neill and Oppenheimer, 2004)
Gradual increase to stabilization
Overshoot to stabilization
Source: Schneider and Mastrandrea, PNAS, Oct 2005
DT
Source: Schneider and Mastrandrea, PNAS, Oct 2005
Exceedence of DAI threshold: dependence on scenarios
The great “greenhouse gamble”…(for 2100)
Source: MIT Joint Program on the Science and Policy of Climate Change
<1°C (4.1%; 1 in 24 odds)
1 to 1.5°C (11.4%; 1 in 9 odds)
1.5 to 2°C (20.6%; 1 in 5 odds)
2 to 2.5°C (22.5%; 1 in 4 odds)
2.5 to 3°C (16.8%; 1 in 6 odds)
3 to 4°C (16.2%; 1 in 6 odds)
4 to 5°C (4.6%; 1 in 22 odds)
>5°C (3.8%; 1 in 26 odds)
A NEW WHEEL with lower odds
of EXTREMES
What would we buy with STABILIZATION
of CO 2 at 550 ppm?
Compared with NO POLICY
HOW CAN WE EXPRESS THE VALUE OF A CLIMATE POLICY UNDER UNCERTAINTY?
A NEW WHEEL with lower odds
of EXTREMES
What would we buy with STABILIZATION
of CO 2 at 550 ppm?
Compared with NO POLICY
HOW CAN WE EXPRESS THE VALUE OF A CLIMATE POLICY UNDER UNCERTAINTY?
Risk = Probability x Consequence
[What metrics of harm?] $/ton C avoided lives lost/ton C avoided species lost/ton C avoided increased inequity/ton C avoided* quality of life degraded/ton
*Perception that prime generators of the risks are not accepting responsibility for their emissions or helping victims to adapt (e.g., OECD countries refusing to join in Kyoto Protocol) itself creates risks.
[Source: “The Five Numeraires”, Schneider, KuntzDuriseti and Azar 2000]
Risk of catastrophic fires Risk of catastrophic fires (and other disturbances) (and other disturbances)
Agriculture: The Wine Industry
• ‘Potentially devastating’ effect on industry
•Water availability
•Temperature
•Storms
A u s t r a l i a n w i n e r e g i o n s A u s t r a l i a n w i n e r e g i o n s M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d
( m a x i m u m v a l u e ( $ / h e c t a r e ) ) ( m a x i m u m v a l u e ( $ / h e c t a r e ) )
Climate change scenario A1B CSIRO Mk 3 model MJT23C2000
Leanne Webb CSIRO and Melbourne University
A u s t r a l i a n w i n e r e g i o n s A u s t r a l i a n w i n e r e g i o n s M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d
( m a x i m u m v a l u e ( $ / h e c t a r e ) ) ( m a x i m u m v a l u e ( $ / h e c t a r e ) )
Climate change scenario A1B CSIRO Mk 3 model
MJT23C2000
MJT23C2030
Leanne Webb CSIRO and Melbourne University
A u s t r a l i a n w i n e r e g i o n s A u s t r a l i a n w i n e r e g i o n s M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d M e a n J a n u a r y T e m p e r a t u r e o f 2 3 C h i g h l i g h t e d
( m a x i m u m v a l u e ( $ / h e c t a r e ) ) ( m a x i m u m v a l u e ( $ / h e c t a r e ) )
Climate change scenario A1B CSIRO Mk 3 model
MJT23C2000
MJT23C2030
MJT23C2050
Leanne Webb CSIRO and Melbourne University
The cost to stabilize the atmosphere
Global GDP
0
50
100
150
200
250
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Year
Trillion USD/yr
Bau
350 ppm
450 ppm
550 ppm
Source: Azar & Schneider, 2002.
The cost to stabilise the atmosphere
Global GDP
0
50
100
150
200
250
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Year
Trillion USD/yr
Bau
350 ppm
450 ppm
550 ppm
Source: Azar & Schneider, 2002.
Delay time to 500% richer per capita with tough climate policy ~ 12 years
Questions?
Comments??
Risk = Probability x Consequence
[What metrics of harm?] $/ton C avoided lives lost/ton C avoided species lost/ton C avoided increased inequity/ton C avoided* quality of life degraded/ton
*Perception that prime generators of the risks are not accepting responsibility for their emissions or helping victims to adapt (e.g., two OECD countries refusing to join in Kyoto Protocol) itself creates risks.
[Source: “The Five Numeraires”, Schneider, KuntzDuriseti and Azar 2000]
Munich Re: “We need to stop this dangerous
experiment humankind is conducting on the Earth’s
atmosphere.”
What does “dangerous” climate change really mean?
Article 2 of the UN Framework Convention on Climate Change (UNFCCC) states that: “The ultimate objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system”. The Framework Convention on Climate Change further suggests that “Such a level should be achieved within a time frame sufficient
• to allow ecosystems to adapt naturally to climate change, • to ensure that food production is not threatened and • to enable economic development to proceed in a sustainable manner.”
Climate Uncertainty Climate Uncertainty
• • Inherent uncertainty in projections of future Inherent uncertainty in projections of future climate climate
• • Best guess Best guess à à Range Range à à PDFs PDFs
Climate Uncertainty Climate Uncertainty
Climate Uncertainty Climate Uncertainty
0
0.01
0.02
0.03
0.04
0 1 2 3 4 5
Temperature Change above 2000 ( o C)
Den
sity
Climate Uncertainty Climate Uncertainty
0
0.01
0.02
0.03
0.04
0 1 2 3 4 5
Temperature Change above 2000 ( o C)
Den
sity
Temperature probability density function for 2100 based on PDF for climate sensitivity
The great “greenhouse gamble”…
Source: MIT Joint Program on the Science and Policy of Climate Change
<1°C (4.1%; 1 in 24 odds)
1 to 1.5°C (11.4%; 1 in 9 odds)
1.5 to 2°C (20.6%; 1 in 5 odds)
2 to 2.5°C (22.5%; 1 in 4 odds)
2.5 to 3°C (16.8%; 1 in 6 odds)
3 to 4°C (16.2%; 1 in 6 odds)
4 to 5°C (4.6%; 1 in 22 odds)
>5°C (3.8%; 1 in 26 odds)
Governor of California: 80% reduction in emissions by 2050
Strategic Plan for SA
‘Changes in the location of Goyder’s line’ 2070
Port Augusta
Quorn
Adelaide
2
Goyder’s Line Study Site
3
4
5
6
7
8
1
9
10
Mark Howden CSIRO sustainable ecosystems
Howden and Hayman – Greenhouse 2005
Premier of South Australia: 60% reduction in emissions by 2050
Governor of California: 80% reduction in emissions by 2050
Risk = Probability x Consequence
[What metrics of harm?] $/ton C avoided lives lost/ton C avoided species lost/ton C avoided increased inequity/ton C avoided* quality of life degraded/ton
*Perception that prime generators of the risks are not accepting responsibility for their emissions or helping victims to adapt (e.g., OECD countries refusing to join in Kyoto Protocol) itself creates risks.
[Source: “The Five Numeraires”, Schneider, KuntzDuriseti and Azar 2000]