probability in the attribution and prediction of climate change...are there other events more...
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Probability in the attribution and prediction of climate change
Myles AllenDepartments of Physics, University of Oxford
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What was the most unrealistic aspect of the film “The Day After Tomorrow”?
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South Oxford on January 5th, 2003
Phot
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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?
“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
“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
30-yearevent
12-yearevent
4-yearevent
18602000
2090
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Note different scale! Source: IPCC Third Assessment Report
And now for the next century: carbon dioxide trends
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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
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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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.
Stan
dard
m
odel
set
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Perturbed Physics Ensemble
Initial Condition Ensemble
Forcing Ensemble
Overall G
rand Ensem
ble
10000s 10s10s
Model Versions Simulations
The problem with dealing with uncertainty in climate change prediction
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Climateprediction.net: the world’s largest climate modelling facility
~100,000 volunteers, 130 countries, ~6M model-years
....
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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
Using simplified model ocean to keep runs short15-year calibration, 15-year control, 15-year 2xCO2
Up to 10-member initial-condition ensembles to reduce noise and quantify sampling variability
15 yr spin-up 15 yr, base case CO2
15 yr, 2 x CO2
Derived fluxes
Diagnostics from final 8 yrs.
Calibration
Control
Double CO2
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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
Perturbations to 21 atmospheric/surface parametersThree values each, including combinationsInitial exploration of 6 parameters (clouds and convection)
P1Low HighStandard
Standard
Low
High
P2
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Sensitivities from climateprediction.net
Stainforth et al, 2005
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Standard model version
Low sensitivity model
High sensitivity model
Regional responses: temperature and precipitation
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Can observations rule out high sensitivities?
Stainforth et al, 2005
CMIP-2 coupled models
Single perturbationsSingle perturbationsOriginal model
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Standard model version
Low sensitivity model
High sensitivity model
Regional responses: temperature and precipitation
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Still they come: 47334 simulations passing initial quality control
Courtesy of Ben Sanderson
Traditional range
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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 forcingblue = 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?
Numbers courtesy of Stefan Rahmstorf and Gavin Schmidt, realclimate.org
∆F=-6.6±1.5W/m2
∆T=-5.5±0.5K
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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
If S is “likely” < 4K (P>0.67) thenS is “very likely < ~7K (P>0.9) and we can only sayS “virtually certain” < 10-15K(P>0.99)
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And here’s why:
Observable properties of climate scale with strength of atmospheric feedbacksMost 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
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
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
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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Michaels + 7 years
The irony is, it doesn’t really matter, because we already agree on so much else
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Given we won’t actually stabilize concentrations indefinitely, why care about sensitivity?
Equilibrium warming under 550ppm stabilisationMaximum warming under 550ppm peak in 2100
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Why can’t the IPCC just say
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…
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 full-complexity 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?
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
Natural drivers onlyAll drivers included
Future projection
Instrumental observations
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External contributions to European summer temperatures, relative to pre-industrial
Anthropogenic
Natural
0.5K
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Human contribution to the risk of the 2003 heat-wave: loading the weather dice
Increase in risk
Fraction of current risk attributable to human influence
Range of uncertainty
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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
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
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:– 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
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 class-action 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?
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?
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.