Download Probability in the attribution and prediction of climate change

Probability in the attribution and
prediction of climate change
Myles Allen
Departments of Physics, University of Oxford
[email protected]
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What was the most unrealistic aspect of the film
“The Day After Tomorrow”?
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Photo courtesy of Dave Mitchell
South Oxford on January 5th, 2003
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The problem in October 2000 and January 2003:
a consistently displaced Atlantic jet-stream
The Atlantic Jet Stream (500hPa wind speed)
Autumn climatology (colours) & Autumn 2000 (contours)
Blackburn & Hoskins, 2003
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But the jet-stream varies with the weather: how
can we pin down the role of climate change?
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“Climate is what you expect, weather is what you
get” (Lorenz, 1982)
and in the 21st century:
“Climate is what you affect, weather is what gets
you”
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Autumn 2000 events “were extreme, but cannot
in themselves be attributed to climate change.”
1947
2000
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It has happened before: Shillingford historic
flood levels
2003
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The 2001 conclusions of the Intergovernmental
Panel on Climate Change
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“Most of the warming over the past 50 years is is
likely (meaning a better than 2 in 3 chance) to have
been due to the increase in greenhouse gas
concentrations.”
But what does this tell us about flooding in Oxford?
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Model-simulated changes in extreme rainfall in
southern England
4-year
event
12-year
event
2090
2000
1860
30-year
event
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And now for the next century: carbon dioxide
trends
Note different scale! Source: IPCC Third Assessment Report
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Uncertainty in global warming under two
scenarios of future emissions
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Changing emission path buys time but does not
eliminate risk
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Ranges of uncertainty in regional predictions
require multi-model “ensembles”
Global temperature
change under 1% per
year increasing CO2
(CMIP-2 model inter-comparison)
Global precipitation
change under 1% per
year increasing CO2
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A shortage of models with high climate
sensitivities?
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Ranges of opinion in climate sensitivity
(Morgan and Keith, 1995)
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Dealing with uncertainty in modelling climate
change
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Climate is predictable, but cannot be directly
observed. Weather is observable, but unpredictable.
Any statement about climate change involves
probabilities: looking at the spread of results from
lots of climate simulations.
On long time-scales, simulations must allow for
uncertainty in modelling, not just chaotic variability
in the atmosphere-ocean system.
But full-scale climate models are expensive to run:
the largest conventional ensembles to date are only
20-50 members…
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The problem with dealing with uncertainty in
climate change prediction
Objective: find as many as possible alternative,
equally realistic, model versions that respond
differently to increasing carbon dioxide, to explore the
full range of possibilities.
Perturbed Physics
Ensemble
Initial Condition
Ensemble
Forcing Ensemble
Overall Grand
Ensemble
Standard
model set-up
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10000s
Model Versions
10s
10s
Simulations
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Climateprediction.net: the world’s largest
climate modelling facility
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..
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~100,000 volunteers, 130 countries, ~6M model-years
Upload servers
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Members of the public download and run a full
3-D climate model on their personal computers
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Visualization software for school and
undergraduate projects
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Active, and self-regulating, user forum
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Initial climateprediction.net experiment
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Using simplified model ocean to keep runs short
15-year calibration, 15-year control, 15-year 2xCO2
Up to 10-member initial-condition ensembles to
reduce noise and quantify sampling variability
Double CO2
15 yr, 2 x CO2
Calibration
15 yr spin-up
Diagnostics from final 8 yrs.
Derived fluxes
15 yr, base case CO2
Control
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Time-evolving frequency distribution
Remove models that
are unstable in the
control.
Few remaining
negatively drifting
2xCO2 model versions
are an unrealistic
consequence of using
a slab ocean.
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Not The Day After Tomorrow: why we got some
negative sensitivities…
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Estimating effective climate sensitivity from
short 2xCO2 runs
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Exploration of parameter space, focussing on
identifying non-linear interactions
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Perturbations to 21 atmospheric/surface parameters
Three values each, including combinations
Initial exploration of 6 parameters (clouds and
convection)
P2
High
Standard
Low
Low
Standard
High
P1
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Sensitivities from climateprediction.net
Stainforth et al, 2005
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Regional responses: temperature and
precipitation
Standard model
version
Low sensitivity
model
High sensitivity
model
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Can observations rule out high sensitivities?
CMIP-2 coupled models
Original
model
Single perturbations
Stainforth et al, 2005
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Regional responses: temperature and
precipitation
Standard model
version
Low sensitivity
model
High sensitivity
model
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Still they come: 47334 simulations passing initial
quality control
Traditional range
Courtesy of Ben Sanderson
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Are these high sensitivities ruled out by the
observed response to Mount Pinatubo?
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No: EBM responses to Pinatubo forcing
blue = 0.5K sensitivity, deep red = 20K sensitivity
Frame et al, 2005, also fitting ENSO, background
climate and effective heat capacity
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Are these high sensitivities ruled out by
temperatures in the Last Glacial Maximum?
∆F=-6.6±1.5W/m2
∆T=-5.5±0.5K
Numbers courtesy of Stefan Rahmstorf and Gavin Schmidt, realclimate.org
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No: symmetric uncertainty in past forcing →
asymmetric, open-ended range for sensitivity
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Naïve sampling strategies can give the illusion
of a tight upper bound on sensitivity
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Would these high sensitivities necessarily be
ruled out if we uploaded more diagnostics?
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No: Murphy et al, 2004, distribution without prior
weighting towards low sensitivities
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Objective constraints on feedback parameter
inferred from the climateprediction.net ensemble
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Objective constraints on climate sensitivity
inferred from climateprediction.net
Piani et
al, 2005
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Not the first to report a risk of high sensitivity
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Forcing uncertainty: the main obstacle to
constraining climate sensitivity
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High risk of substantial warming even with
today’s greenhouse gas levels
Traditional range
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Lots of studies, same message: weak upper
bound on climate sensitivity
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If S is “likely” < 4K
(P>0.67)
then
S is “very likely < ~7K
(P>0.9)
and we can only say
S “virtually certain” <
10-15K
(P>0.99)
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And here’s why:
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Observable properties of
climate scale with
strength of atmospheric
feedbacks
Most constraints end up
fairly Gaussian (Central
Limit Theorem)
A Gaussian distribution of
inverse sensitivity gives…
no formal upper bound on
climate sensitivity
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High sensitivities and the challenge for the IPCC
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In 2001, all studies reported detectable greenhouse
warming at >90% confidence, yet IPCC stuck to
“unlikely to be entirely natural in origin” (>67%)
In 2005, no studies rule out S>5K at >90% confidence
except by prior assumption: but will IPCC want to
suggest sensitivity is only “likely” <5K?
Of course, there is the fact that…
No one is likely to drag an IPCC author through the
US courts for underestimating the chance of a high
sensitivity.
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Why they care
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Failure to place an upper bound on sensitivity
appears to undermine the policy relevance of IPCC.
Huge pressure to come up with the killer paper for
AR4 (the prize: world-wide fame, and a chocolate
from Susan Solomon).
New evidence will be indirect: direct observations of
GHG-induced warming or TOA fluxes don’t cut it.
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We have been here before
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Use of model-simulated variability, and the recovery
from the Little Ice Age, undermined the policy
relevance of “discernible human influence” in 1995.
In 1998, a new hemispheric millennial temperature
reconstruction appeared to obviate model-simulated
variability (and the Little Ice Age).
Of course, that reconstruction may yet turn out right:
maybe there was no global Little Ice Age.
And maybe the climate sensitivity really is <4K.
Premature declarations, even if vindicated,
permanently undermine the credibility of the IPCC.
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The irony is, it doesn’t really matter, because we
already agree on so much else
Michaels et al,
2000, 2004
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The irony is, it doesn’t really matter, because we
already agree on so much else
Michaels + 7 years
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Given we won’t actually stabilize concentrations
indefinitely, why care about sensitivity?
Equilibrium warming under 550ppm stabilisation
Maximum warming under 550ppm peak in 2100
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Why can’t the IPCC just say
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For well-understood physical reasons, we cannot
place an objective upper bound on climate
sensitivity.
So, we cannot estimate the risks associated with a
given stabilisation CO2 concentration.
But we can estimate the range of transient changes
expected over the coming decades, and …
We can also estimate the effort required to hit a
given temperature target.
Sometimes, admission of ignorance is the most
policy-relevant option of all.
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Implications…
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Many studies have found there is some risk of a
substantial climate change even with today’s
greenhouse gas levels.
Climateprediction.net, with the help of the public,
confirmed this result for the first time with a fullcomplexity climate model.
But warming takes time (many decades) to emerge:
what about the here and now?
We mentioned the possibility of increased flood risk,
but that was one model study. Are there other events
more closely related to rising temperatures?
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Summer 2003 temperatures relative to 2000-2004
From NASA’s
MODIS - Moderate
Resolution Imaging
Spectrometer,
courtesy of Reto
Stöckli, ETHZ
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Heat-wave blamed for US$12.3 billion uninsured
crop losses + US$1.6 billion forest fire damage
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Excess mortality rates in early August 2003
indicate 22,000 - 35,000 heat-related deaths
Daily mortality in Baden-Württemberg
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But a single heat-wave is a weather event: how
can we pin down the role of climate change?
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The immediate cause of the heat-wave was a
persistent anti-cyclone over Northwest Europe.
There is still no evidence that human influence on
climate makes such circulation patterns more likely.
Instead, we ask how human influence on climate has
affected the risk of such a weather event (however
induced) causing such an intense heat-wave?
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June-August temperatures in 2003, relative to
1961-90 mean, Mediterranean region
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Modelling Southern European area-averaged
June-July-August summer temperatures
Future projection
Instrumental
observations
Natural drivers only
All drivers included
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External contributions to European summer
temperatures, relative to pre-industrial
Anthropogenic
0.5K
Natural
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Human contribution to the risk of the 2003
heat-wave: loading the weather dice
Increase in risk
Range of uncertainty
Fraction of current risk attributable to human influence
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Tuyuksu Glacier, Kazakhstan: a vital water source
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Tuyuksu mass balance
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The Spectre of Liability
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Modest (0.5oC) background warming substantially
increases the risk of extreme high temperatures.
It is likely (90% confidence) that past human
influence on climate was responsible for at least half
the risk of the 2003 European summer heat-wave.
“Plaintiffs ... must show that, more probably than
not, their individual injuries were caused by the risk
factor in question, as opposed to any other cause.
This has sometimes been translated to a
requirement of a relative risk of at least two.”
(Grossman, 2003)
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By the 2030s, >50% of anthopogenic GHG
loading will be due to post-1990 emissions
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What was the most unrealistic aspect of the film
“The Day After Tomorrow”?
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There weren’t any lawyers
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The contribution of past greenhouse gas emissions
to some current climate risks may already exceed
50%, the threshold for civil tort actions.
Over the coming decade, both the cost and the
inevitability of climate change will become clearer,
fuelling demands for compensation for:
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Flooding
Heat wave damages and deaths
Threats to water supplies, especially from glacial sources
Coastal erosion etc.
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Giving climate change back to the people
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Politicians tend to talk about climate change as an
environmental or ethical issue: care for polar bears
or future generations.
This diverts attention from the injustices that are
happening now: we all benefit from burning fossil
fuels, but some are losing out much more than
others from the impacts of climate change.
The risk, even quite remote, of a successful classaction damages suit would have far more impact
than any conceivable follow-up to the Kyoto
Protocol.
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But what could be done?
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How can an oil company or coal miner avoid selling
a product whose use involves increasing
atmospheric CO2?
Simple: they bury (“sequester”) the equivalent
amount of carbon.
Of course, this would make oil or coal more
expensive, which would hurt – but how much?
“All OECD countries besides the US impose big
taxes on fuel, but curiously it hasn’t reduced
consumption.” Lord Browne, BP (Financial Times)
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But what could be done?
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Fossil fuels are still remarkably cheap, since we pay
for the cost of extraction (and cartel-like profits), not
the cost of their impact.
If politicians were to apply the “Polluter Pays
Principle” to producers of fossil fuels, this would
change rapidly: it might well make more sense to sell
carbon-neutral fuel than risk liability.
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