Transcript Roger Jones - Climate sensitivity, coping ranges and risk

Operationalising Coping Ranges
climate sensitivity, coping ranges and risk
AIACC Training Workshop on Adaptation and Vulnerability
TWAS, Trieste
June 3-14 2002
Roger N. Jones
Atmospheric Research
Choices
• Roundtable of project needs regards coping ranges,
thresholds, climate risk and uncertainty management
• Choosing climate variables/sensitivity relationships
(exercise)
• How to construct thresholds
• Structure of climate probabilities (variability and
change, short exercise)
• Case studies
– hot cows (heat stress and adaptation)
– water resources (Monte Carlo uncertainty and
Bayesian analysis
– risk as a function of global warming
Atmospheric Research
Sensitivity to what?
Sector
Sensitivity to what?
Water
Rainfall variability, flood, drought
Agriculture
ENSO, flood, drought, cool/hot
extremes, storms
Health
Hot/wet conditions, temperature
extremes, violent storms, floods, crop
and water shortages
Coasts
Storm surges, wind/wave climates,
pressure extremes, tidal extremes
Biodiversity Fire, flood, drought, storms
Atmospheric Research
Linking climate to impacts
Climate
system
Impacted
activity
Socioeconomic
system
Current
climate
Current
adaptations
Future
climate
Future
adaptations
Atmospheric Research
2
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Health
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Waste
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Industry, coal & power
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Air quality
Dryland/irrigation salinity
Harbour
Coastal water supply
Beach
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Marine (esp. fisheries)
Horses
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Urban infrastructure
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Forest & biodiversity
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River management
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Wine
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Cropping
2
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Inland water supply
1
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Grazing
Rainfall - average
Rainfall - extreme
Rainfall - variability
Drought
Temperature - average
Temperature - max
Temperature - min
CO2
Cloud
Pressure
Humidity
Wind
Evaporation
Soil moisture
Stream flow
Flood
Watertable
Water salinity
Irrigation
Sea level
Storm surge
Waves
Lightning
Hail
Fire
Dairy
Poultry
Cross impacts analysis
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Workshop
Report
(example)
Worked
example in
MS Excel®
Atmospheric Research
Cross impacts analysis
Climate and related variables
(forcing)
Activities
(sensitivity)
High
Rainfall - extreme
Flood
Drought
Temperature - max
Rainfall - variability
Rainfall - average
Temperature - average
Soil moisture
Urban infrastructure
Cropping
Wine
River management
Forest & biodiversity
Inland water supply
Dairy
Grazing
Dryland/irrigation salinity
Moderate
Stream flow
Water salinity
Temperature - min
Wind
Irrigation
Watertable
Sea level
Fire
CO2
Humidity
Evaporation
Industry, coal & power
Marine (esp. fisheries)
Coastal water supply
Health
Harbour
Waste
Beach
Horses
Low
Waves
Storm surge
Hail
Cloud
Lightning
Pressure
Air quality
Poultry
Atmospheric Research
Uncertainty explosion
Emission scenarios
Global climate sensitivity
Regional changes
Climate variability
Biophysical impacts
Socio-economic impacts
Atmospheric Research
Uncertainty explosion
Emission scenarios
Global climate sensitivity
Regional variability
Biophysical impacts
Socio-economic impacts
Atmospheric Research
Likelihood
Probability can be expressed in two
ways:
1. Return period / frequency-based
(Climate variability)
2. Single event
(Mean climate change, one-off events)
Atmospheric Research
Return period / frequency-based
probability
Recurrent or simple event
Where a continuous variable reaches a critical level, or
threshold.
Eg. Extreme temperature (max & min), Extreme rainfall,
heat stress, 1 in 100 year flood
Discrete or complex event
An event caused by a combination of variables (an
extreme weather event)
Eg. tropical cyclone/hurricane/typhoon, ENSO event
Atmospheric Research
Frequency-based probability
distributions
Atmospheric Research
Single-event probability
Singular or unique event
An event likely to occur once only. Probability refers to
the chance of an event occurring, or to a particular
state of that event when it occurs.
Eg. Climate change, collapse of the West Antarctic Ice
Sheet, hell freezing over
Atmospheric Research
What is the probability of climate
change?
1. Will climate change happen?
•
IPCC (2001) suggests that climate change is occurring with
a confidence of 66% to 90%
2. What form will it take?
Uncertainties are due to:
• future rates of greenhouse gas emissions
• sensitivity of global climate to greenhouse gases
• regional variations in climate
• decadal-scale variability
• changes to short-term variability
Atmospheric Research
Range of uncertainty
M1
UNQUANTIFIABLE
UNCERTAINTY
M2
M3
M4
QUANTIFIABLE RANGE OF UNCERTAINTY
UNQUANTIFIABLE
UNCERTAINTY
TOTAL RANGE OF UNCERTAINTY
Atmospheric Research
CO2 emissions and concentrations
Atmospheric Research
Simulated global warming: A2
Atmospheric Research
Global warming
Atmospheric Research
Group exercise - estimating joint
probabilities
• Take a gold coin (preferably 1 pound coin)
• Heads represents low end (1.4°C), tails
represents high end (5.8°C)
• Flip coin 7 times and record the number of
heads and tails
• Which outcome is most likely?
Atmospheric Research
Risk exercise - conclusion
• Give coin to greedy presenter
Atmospheric Research
Probabilistic structure of climate
uncertainties
Variable(s)
Critical threshold
Critical threshold
Planning horizon
Time
Atmospheric Research
Placing thresholds within scenario
uncertainty
A
B
global climate
sensitivity

emission
scenarios

regional
variability

range of
possible impacts
Atmospheric Research
Impact thresholds
4.0
3.5
Global Warming (°C)
Threshold
examples
&
workshop
synthesis
3.0
2.5
2.0
Threshold A
1.5
1.0
0.5
Threshold B
0.0
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Year
Atmospheric Research
Metrics for measuring costs
•
•
•
•
•
Monetary losses (gains)
Loss of life
Change in quality of life
Species and habitat loss
Distributional equity
Atmospheric Research
System responses
• Resistance (e.g. seawall)
• Resilience (e.g. regrowth, rebuilding after
storm or fire)
• Adaptation (adjustments made in response to
stress)
• Transformation (old system stops, new one
starts)
• Cessation (activity stops altogether)
Atmospheric Research
Hot cows and heat stress
THI between 72 and 78
THI between 79 and 88
mild stress
moderate stress
THI between 89 and 98
THI above 98
severe stress
DEAD COWS!
Atmospheric Research
Frequency of exceeding
heat index threshold
Threshold
examples
&
workshop
synthesis
90.0
THI Units
80.0
THI78
THI72
70.0
60.0
50.0
1/10/98
31/10/98
30/11/98
30/12/98
29/01/99
28/02/99
30/03/99
Date
Atmospheric Research
Production effects
Powerpoint
THI between 72 and 78
Report
mild stress
no stress
THI between 79 and 88
moderate stress
mild stress
Atmospheric Research
Coral bleaching
• Caused by SST above a threshold
• Expels xosanthellae algae
• Severity related to days above
bleaching threshold
• Corals may recover or die
Atmospheric Research
Macquarie River Catchment
Macquarie
Marshes
Major Areas of
Abstraction
Burrendong Dam
Macquarie R
Contributing
Area

Area ~ 75,000 km2

P = 1000 to <400 mm.

Major dams: Burrendong and
Windamere

Water demands: irrigation
agriculture; Macquarie
Marshes; town supply

Most flow from upper
catchment runoff

Most demand in the lower
catchment
Windamere Dam
Atmospheric Research
Ranges of seasonal rainfall change
for the MDB
Summer
Winter
-40
-20
0
20
Rainfall Change (%)
40
2030
2070
Autumn
Spring
-40
-20
0
20
Rainfall Change (%)
40
Atmospheric Research
P and Ep changes for Macquarie
catchment
Change for 1ºC global warming (%)
16.0
8.0
0.0
-8.0
-16.0
J
F
M
A
M
J
Evaporation (Ep)
J
A
S
O
N
D
Rainfall (P)
In change per degree global warming
Atmospheric Research
Changes to MAF for 9 models in 2030 (%)
Based on IPCC 2001
Low
Mid
0
0
-8
-8
High
0
-10
-16
-16
-20
-24
-30
B1 at 1.7°C
0.55°C
A1 at 2.5°C
0.91°C
A1T at 4.2°C
1.27°C
Atmospheric Research
Climate change – flow relationship
flow = a  ( atan (Ep / P ) – b
Standard error < 2%
Atmospheric Research
Sampling strategy
• The range of global warming in 2030 was 0.55–
1.27°C with a uniform distribution. The range of
change in 2070 was 1.16–3.02°C.
• Changes in P were taken from the full range of
change for each quarter from the sample of nine
climate models.
• Changes in P for each quarter were assumed to be
independent of each other
• The difference between samples in any consecutive
quarter could not exceed the largest difference
observed in the sample of nine climate models.
• Ep was partially dependent on P (dEp = 5.75 –
0.53dP, standard error = 2.00, randomly sampled
using a Gaussian distribution)
Atmospheric Research
Potential evaporation change (%)
Changes to Burrendong Dam storage
2030
Cumulative
Probability (%)
15
-40
-30
-10
-20
<100
0
10
<95
5
10
<90
<80
<70
0
20
<60
-5
<50
-10
-5
0
5
10
Rainfall change (%)
Atmospheric Research
Potential evaporation change (%)
Changes to bulk allocations for
irrigation 2030
15
-30
-20
-10
Cumulative
Probability (%)
<100
10
<95
0
<90
5
<80
10
<70
0
<60
-5
<50
-10
-5
0
5
10
Rainfall change (%)
Atmospheric Research
Potential evaporation change (%)
Changes to Macquarie Marsh
inflows 2030
15
-40
-30
-20
-10
Cumulative
Probability (%)
<100
10
<95
0
<90
5
10
<80
<70
0
20
-5
<60
<50
-10
-5
0
5
10
Rainfall change (%)
Atmospheric Research
Probabilities of flow changes impacts view
Range of possible outcomes
Atmospheric Research
Critical thresholds
Macquarie River Catchment
Irrigation
5 consecutive years below 50% allocation of
water right
Wetlands
10 consecutive years below bird breeding
events
Atmospheric Research
Irrigation allocations and wetland inflows
- historical climate and 1996 rules
100
Flow (Gl x 10)
80
1,000,000
60
40
100,000
20
10,000
1890
Irrigation allocation (%)
10,000,000
0
1910
1930
1950
1970
1990
Year
Allocations
Marshes
Atmospheric Research
Threshold exceedance as a function
of change in flow (irrigation)
Sequences below
threshold (years)
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Percent of total years
below threshold
+5%
Change in mean average allocation
0
-10%
-15%
-30%
-40%
1
1
-45%
1
1
1
1
0
1
1
2
6
12
1
2
2
4
5
7
38
50
2
1
5
10
1
4
13
2
1
6
11
22
23
34
1
4
1
6
4
1
5
1
2
4
58
64
Atmospheric Research
Threshold exceedance as a function
of change in flow (bird breeding)
Sequences below
threshold (years)
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Percent of total years
below threshold
+5%
0
Change in MAF
-10%
-15%
-30%
1
1
1
1
1
1
-40%
1
1
1
1
1
1
2
2
-50%
1
2
2
3
3
1
1
1
1
1
3
2
4
4
1
2
1
7
3
1
2
3
4
7
1
3
4
2
5
2
4
3
2
3
40
45
52
56
63
2
1
2
3
1
1
3
1
1
3
71
79
Atmospheric Research
Risk analysis results
Macquarie 2030
Report
DDR
N or m a l
FD R
-10
-20
-30
C um u la tiv e P rob ability
100
90
80
70
60
50
40
30
20
10
0
20
10
0
-40
C ha nge in sup ply (% )
B u r ren d on g
M a rsh es
Irr ig ation
Atmospheric Research
Risk analysis results
Macquarie 2070
DDR Normal FDR
100
90
Cumulative Probability
80
70
60
50
40
30
20
10
0
40
20
-20
0
-40
-60
-80
Change in supply (%)
Burrendong
Marshes
Irrigation
Atmospheric Research
Bayesian analysis results
Macquarie 2030
100
90
Cumulative Probability
80
70
60
50
40
30
20
10
0
20
10
0
-10
-20
-30
-40
Change in supply (%)
Standard
W&R warming
All
Atmospheric Research
Bayesian analysis results
Macquarie 2070
100
90
Cumulative Probability
80
70
60
50
40
30
20
10
0
40
20
0
-20
-40
-60
-80
Change in supply (%)
Standard
W&R warming
All
Atmospheric Research
Characterising risk as a function of
global warming
The standard “7 step method” of impact
assessment progresses from climate to
impacts to adaptation. This infers that we
must predict the likeliest climate before we
can predict the likeliest impacts.
Can we get around this limitation?
Atmospheric Research
Characterising risk
There is another way.
Impacts = function(Global warming)
Impacts = function(global, local CC & CV )
p(impacts) = no. of scenarios > threshold = risk
Atmospheric Research
Risk exercise - estimating threshold
exceedance: sea level rise
• Recover coin from greedy presenter
• Heads represents low end (9 cm), tails
represents high end (88cm)
• The group chooses two critical thresholds
• Flip coin 7 times and record the number of
heads and tails
• Which outcome is most likely?
Atmospheric Research
6
5
5
4
3
2
4
3
2
1
1
0
0
0
1
2
3
4
Frequency (%)
5
Probability of threshold
exceedance
6
Global warming (°C)
Global warming (°C)
Characterising the risk of global
warming
0
50
100
Frequency (%)
Increasing likelihood of
global warming
Atmospheric Research
100
100
80
50 cm
25 cm
Sea Level Rise (cm)
Sea Level Rise (cm)
75 cm
80
75 cm
60
50 cm
40
25 cm
20
75 cm
60
50 cm
40
0
0
0
100
0
Probability (%)
75 cm
60
50 cm
40
25 cm
20
0
80
75 cm
60
50 cm
40
25 cm
20
0
0
5
10
Probability (%)
100
80
75 cm
60
50 cm
40
25 cm
20
0
0
100
Probability (%)
Sea Level Rise (cm)
80
100
Probability (%)
100
Sea Level Rise (cm)
100
Sea Level Rise (cm)
Sea Level Rise (cm)
100
25 cm
20
80
75 cm
60
50 cm
40
25 cm
20
0
0
5
10
Probability (%)
0
100
Probability (%)
Characterising the risk of global
warming
5
Global warming (°C)
Probability of threshold
exceedance
6
Risks to Large Negative
Net
Higher
Many Increase for most Negative
regions
in all
metrics
4
3
Markets
+ and -
2
1
Negative
for some
Risks to
Some Increase regions
0
0
50
Frequency (%)
Most
people
worse
off
Very
low
IV
V
100
I
I
II
III
IV
V
II
III
Risks to unique and threatened systems
Risks from extreme climate events
Distribution of impacts
Aggregate impacts
Risks from large-scale discontinuities
Atmospheric Research
Long-term planning
Short-term policy response
1. Enhance adaptive capacity so that the
current coping range expands,
reducing present vulnerability.
2. Develop this capacity in such a way
that the longer-term risks to climate
change are also reduced.
Atmospheric Research
Basic principles
• Pay greater attention to recent climate experience. Link
climate, impacts and outcomes to describe the coping range.
• Address adaptation to climate variability and extremes as part
of reducing vulnerability to longer-term climate change.
• Assess risk according to how far climate change, in
conjunction with other drivers of change, may drive activities
beyond their coping range.
• Focus on present and future vulnerability to ground future
adaptation policy development in present-day experience.
• Consider current development policies and proposed future
activities and investments, especially those that may increase
vulnerability.
Atmospheric Research
Foresighting your project
• Visualise how you will present the results
(graph, text, table, animation)
• Rehearse how you will communicate the
uncertainties
• Anticipate questions upon presentation or
review
• How will you engage different stakeholders?
Atmospheric Research